\\n self._deallocate_statement(statement)\\n self.protocol.send_msg_without_ps(msg_type, msg, statement)\\n statement.changed = False\\n statement.reset_exec_counter()\\n elif not statement.changed and not statement.repeated:\\n # Prepare::Prepare + Prepare::Execute\\n if not statement.prepared:\\n self._prepare_statement(msg_type, msg, statement)\\n if not self._prepared_stmt_supported:\\n self.protocol.send_msg_without_ps(msg_type, msg, statement)\\n return\\n self.protocol.send_prepare_execute(msg_type, msg, statement)\\n elif statement.changed and statement.repeated:\\n # Prepare::Deallocate + Crud::<Operation>\\n self._deallocate_statement(statement)\\n self.protocol.send_msg_without_ps(msg_type, msg, statement)\\n statement.changed = False\\n statement.reset_exec_counter()\\n\\n statement.increment_exec_counter()\",\n \"def commit(self):\\n try:\\n db.session.commit()\\n except:\\n db.session.rollback()\\n raise\",\n \"def synchronous_prepare(self, shared_context):\\n shared_context.register_name(self.name)\\n self._prepared = True\",\n \"def handler_commit(event):\\n if not LOG_DB:\\n return\\n\\n # get the active transaction\\n txn = transaction.get()\\n\\n # get needed values now as the request contents will\\n # change after commit.\\n request = event.request\\n request_data = get_request_data(request)\\n\\n # transactions that will do a commit have a ZODB.Connection\\n # object in ``_resources``. Since the transaction has an\\n # open connection we know it will be committed.\\n for conn in (c for c in txn._resources if isinstance(c, Connection)):\\n # ZODB.Connection objects support callbacks on close.\\n # In this case we wrap the callback in another function\\n # so we can also pass in the event.\\n conn.onCloseCallback(__after_conn_close(request_data))\",\n \"def begin_commit(self, _stacklevel=1):\\n if self.commit_phase:\\n warnings.warn('the transaction already is on commit phase; '\\n 'begin_commit() method seems called twice or more' +\\n self.format_commit_stack(),\\n category=TransactionWarning,\\n stacklevel=1 + _stacklevel)\\n return\\n self.commit_phase = True\\n if self.session.verbose_transaction_error:\\n self.commit_stack = traceback.format_stack()\\n self.session.client.multi()\",\n \"def commit(self):\\n datastore_pre_commit.send(session=self.db.session)\\n super().commit()\\n datastore_post_commit.send(session=self.db.session)\",\n \"def prepare(self) -> None:\\n trans = self._transaction\\n if trans is None:\\n trans = self._autobegin_t()\\n\\n trans.prepare()\",\n \"def commit(self):\",\n \"def commit(self):\\n self._pipeline.execute()\\n self.current_chunk = 0\",\n \"def _commit_now(self):\\n self._database.commit()\",\n \"def commit(self) -> None:\\n trans = self._transaction\\n if trans is None:\\n trans = self._autobegin_t()\\n\\n trans.commit(_to_root=True)\",\n \"def Commit(self):\\n sql_cnxn = self.GetMasterConnection()\\n try:\\n sql_cnxn.commit()\\n except MySQLdb.DatabaseError:\\n logging.exception('Commit failed for cnxn, rolling back')\\n sql_cnxn.rollback()\",\n \"def _executeprepared(self, operation, parameters):\\n # Create a statement handle\\n p_statement = self._statement_cache.get_prepared_statement(operation)\\n\\n if p_statement.parameter_count != len(parameters):\\n raise ProgrammingError(\\\"Incorrect number of parameters specified, expected %d, got %d\\\" %\\n (p_statement.parameter_count, len(parameters)))\\n\\n # Use handle to query\\n return self.session.execute_prepared_statement(p_statement, parameters)\",\n \"def commit_to_database(self, table, output):\\n try:\\n # TODO: Is this the correct method for this?\\n with SESSION.begin_nested():\\n i = insert(getattr(db, table))\\n vals = i.values(output)\\n SESSION.execute(vals) # TODO: What is this?\\n SESSION.flush()\\n except Exception as error:\\n log.debug(error, exc_info=True)\\n SESSION.rollback()\\n\\n SESSION.commit() # TODO: Should this be here?\",\n \"def commit_transaction(self):\\n cursor = self._cursor()\\n cursor.close()\\n self._db.commit()\\n self._end_transaction()\",\n \"def commit(self):\\n self.success = True\\n self.close()\",\n \"def commit(self):\\n return self.connection.commit()\",\n \"def close(self):\\n assert not self.closed\\n if self.success:\\n run(self.connection, \\\"COMMIT\\\")\\n else:\\n run(self.connection, \\\"ROLLBACK\\\")\\n self.closed = True\\n self.on_close()\",\n \"def commit(self):\\n raise NotImplementedError\",\n \"def commit(self):\\n\\n if not self.is_active:\\n return\\n\\n if self.is_context_active:\\n raise states.Committed(self)\\n else:\\n self.__do_commit()\\n self._cleanup()\",\n \"def commit(self):\\n self.db.commit()\",\n \"def commit(self):\\n\\n if self.committed:\\n raise WriteAfterCommitException\\n\\n if len(self.cached_rows) > 0:\\n self.__write_bulk()\\n\\n self.committed = True\\n\\n self.client[self.credentials[\\\"database\\\"]][self.collection].drop()\\n self.write_coll.rename(self.collection)\\n\\n self.client.close()\\n self.client = None\\n self.write_coll = None\",\n \"def transactionEnd(self):\\n self.connection.commit()\",\n \"def close(commit=True):\\n\\tif commit:\\n\\t\\tconnection.commit()\\n\\tconnection.close()\",\n \"def dbcommit(self):\\n self.con.commit()\",\n \"def commit(self):\\n return\",\n \"def commit(self):\\n #main.signals['exit'].disconnect(self.commit)\\n self._dirty = False\\n with self._lock:\\n self._db.commit()\",\n \"def commit(self):\\n return self.conn.commit()\",\n \"def commit_updates(session, update_key, update_statements, table, commit_frequency = 1000):\\n primary_key = table.primary_key.columns.values()[0]\\n update_key = table.columns[update_key]\\n u = table.update().where(primary_key==bindparam('pk')).values({update_key: bindparam('update')})\\n numgroups = len(update_statements) / commit_frequency\\n for ng in range(numgroups):\\n if numgroups == 0:\\n break\\n chunk = update_statements[ng*commit_frequency:(ng+1)*commit_frequency]\\n session.connection().execute(u, *chunk)\\n print \\\"committing chunk\\\",ng+1,\\\"of\\\",numgroups,\\\"with length\\\",len(chunk),\\\"at\\\",datetime.now()\\n session.commit()\\n last_chunk = update_statements[numgroups*commit_frequency:]\\n if last_chunk:\\n print \\\"committing last\\\",len(last_chunk),\\\"records at\\\",datetime.now()\\n session.connection().execute(u, *last_chunk)\\n session.commit()\",\n \"def close(conn):\\n #conn.commit()\\n conn.close()\",\n \"def commitQuery(self):\\r\\n\\t\\tself.session.commit()\",\n \"def Save(self) -> None:\\n self.__conn.commit()\",\n \"def finish(self):\\n self.conn.commit()\\n self.conn.close()\",\n \"def commit(self, cursor):\\n\\t\\twith warnings.catch_warnings():\\n\\t\\t\\twarnings.simplefilter(\\\"ignore\\\")\\n\\t\\t\\tconnection = cursor.connection\\n\\t\\tconnection.commit()\\n\\t\\tself._close_cursor(cursor)\",\n \"def commit(self):\\n self.DB.commit()\",\n \"def prepare(self):\\n self._prepared = True\\n return True\",\n \"def commit_changes(self):\\n self.connection.commit()\",\n \"def commit(self):\\n self._session.commit()\\n self._session.close()\\n\\n return True\",\n \"def commit(self):\\n self.getSession().commit()\",\n \"def commit(self) -> None:\\n with self.lock:\\n self.wait(self._commit_gen())\",\n \"def prepare_table(self, connection, prepare_params=None):\\n cursor = connection.cursor()\\n cursor.execute(self.sqls[\\\"prepare_check\\\"], prepare_params or tuple())\\n if not cursor.fetchone():\\n cursor.execute(self.sqls[\\\"prepare_create\\\"])\\n connection.commit()\\n return True\\n else:\\n return False\",\n \"def prepare_table(self, connection, prepare_params=None):\\n cursor = connection.cursor()\\n cursor.execute(self.sqls[\\\"prepare_check\\\"], prepare_params or tuple())\\n if not cursor.fetchone():\\n cursor.execute(self.sqls[\\\"prepare_create\\\"])\\n connection.commit()\\n return True\\n else:\\n return False\",\n \"def commit(self):\\n self._size += self._size_uncommitted\\n self._size_uncommitted = 0\\n self.session.commit()\",\n \"def commit():\\n try:\\n yield\\n db.session.commit()\\n except:\\n print('Rolling back changes...')\\n db.session.rollback()\\n raise\",\n \"def prepare(self, stmt):\\n exstmt = self.replacevals(stmt)\\n self._stmt = convert_PROCEDURES(exstmt)\",\n \"def prepare(self, statement, params=None, name=None, call_type=None):\\n if not name:\\n self.prepared_statement_id += 1\\n name = '_pstmt_%03.3d' % self.prepared_statement_id\\n if params:\\n params = '(' + ','.join(params) + ')'\\n else:\\n params = ''\\n with self.cursor() as c:\\n c.execute('PREPARE %s %s AS %s' % (name, params, statement))\\n if call_type is None:\\n if statement.lower().startswith('select'):\\n call_type = 'query'\\n else:\\n call_type = 'execute'\\n return PreparedStatement(self, name, call_type)\",\n \"def _end_transaction(self):\\n self._db.autocommit=True\",\n \"def insert_many_execute(self) -> None:\\n self.connection.isolation_level = None\\n self.cursor.execute('BEGIN TRANSACTION')\\n for i in self.__sql_buffer.split(';'):\\n self.cursor.execute(i)\\n self.__sql_buffer = \\\"\\\"\\n self.cursor.execute('COMMIT')\",\n \"def commit(self):\\n if self.keys:\\n # If there used to be some keys, there must exist an old dictionary blob somewhere in the database. It should be deallocated after a successful commit to disk.\\n self.file.seek(0)\\n headerdump = self.file.read(16)\\n if sum(headerdump):\\n dictat,dictlen = struct.unpack(\\\"<QQ\\\", headerdump)\\n self.awaitingpunch.append((dictat,dictlen))\\n\\n # All buffered (modified but uncommited) values get serialized and sent to disk.\\n for key,value in self.buffered.items():\\n valuedump = pickle.dumps(value)\\n valueat = self.file.safeappend(valuedump, 16)\\n self.keys[key] = (valueat,len(valuedump))\\n self.buffered.clear()\\n\\n # A new dictionary blob gets serialized and sent to disk.\\n dictdump = pickle.dumps(self.keys)\\n dictat = self.file.safeappend(dictdump, 16)\\n\\n # Finally, the header gets overwritten atomically and orderly.\\n headerdump = struct.pack(\\\"<QQ\\\", dictat, len(dictdump))\\n self.file.fsync()\\n self.file.writep(0, headerdump)\\n self.file.fsync()\\n\\n # Whatever value blobs and dictionary blobs are no longer being pointed to, they can be safely deallocated.\\n for (punchat,punchlen) in self.awaitingpunch:\\n self.file.fallocate(2|1, punchat, punchlen)\\n self.awaitingpunch.clear()\\n\\n self.buffered.clear()\\n\\n else:\\n self.awaitingpunch.clear()\\n self.file.fsync()\\n self.file.truncate(0)\\n self.file.fsync()\",\n \"async def commit(self):\\n await self._pipeline.execute()\\n self.current_chunk = 0\",\n \"def save_and_exit():\\n con.commit()\\n con.close()\\n quit()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.69002336","0.68232703","0.677715","0.567485","0.5660226","0.5630717","0.5601845","0.55818135","0.55588466","0.5414727","0.537227","0.5353509","0.53374785","0.53097814","0.52796453","0.5208319","0.5195262","0.5135492","0.5135492","0.50988245","0.5068812","0.50601774","0.50596935","0.5052633","0.5039656","0.50149196","0.49667028","0.49408036","0.4909785","0.49095735","0.4893525","0.48843178","0.48825347","0.48816803","0.4857133","0.4856046","0.48539895","0.48343384","0.48107713","0.4809027","0.48041674","0.48035008","0.48035008","0.48035008","0.48035008","0.48035008","0.4796366","0.47952276","0.4792568","0.47732332","0.47659233","0.47614393","0.4759177","0.47483355","0.47310966","0.47308975","0.47287333","0.47065464","0.47045758","0.469137","0.46890557","0.46881086","0.46880978","0.46661317","0.4662497","0.46536025","0.4645912","0.46239954","0.46159115","0.46158114","0.4614831","0.46083245","0.4606021","0.45919266","0.45918155","0.45808694","0.45785168","0.45741102","0.45738333","0.45550448","0.4554904","0.45376095","0.45369375","0.453162","0.4515152","0.45097572","0.45091563","0.4507228","0.44930825","0.44930825","0.44778845","0.44742638","0.44662336","0.44653386","0.4445729","0.4421044","0.441969","0.44186005","0.4385507"],"string":"[\n \"0.69002336\",\n \"0.68232703\",\n \"0.677715\",\n \"0.567485\",\n \"0.5660226\",\n \"0.5630717\",\n \"0.5601845\",\n \"0.55818135\",\n \"0.55588466\",\n \"0.5414727\",\n \"0.537227\",\n \"0.5353509\",\n \"0.53374785\",\n \"0.53097814\",\n \"0.52796453\",\n \"0.5208319\",\n \"0.5195262\",\n \"0.5135492\",\n \"0.5135492\",\n \"0.50988245\",\n \"0.5068812\",\n \"0.50601774\",\n \"0.50596935\",\n \"0.5052633\",\n \"0.5039656\",\n \"0.50149196\",\n \"0.49667028\",\n \"0.49408036\",\n \"0.4909785\",\n \"0.49095735\",\n \"0.4893525\",\n \"0.48843178\",\n \"0.48825347\",\n \"0.48816803\",\n \"0.4857133\",\n \"0.4856046\",\n \"0.48539895\",\n \"0.48343384\",\n \"0.48107713\",\n \"0.4809027\",\n \"0.48041674\",\n \"0.48035008\",\n \"0.48035008\",\n \"0.48035008\",\n \"0.48035008\",\n \"0.48035008\",\n \"0.4796366\",\n \"0.47952276\",\n \"0.4792568\",\n \"0.47732332\",\n \"0.47659233\",\n \"0.47614393\",\n \"0.4759177\",\n \"0.47483355\",\n \"0.47310966\",\n \"0.47308975\",\n \"0.47287333\",\n \"0.47065464\",\n \"0.47045758\",\n \"0.469137\",\n \"0.46890557\",\n \"0.46881086\",\n \"0.46880978\",\n \"0.46661317\",\n \"0.4662497\",\n \"0.46536025\",\n \"0.4645912\",\n \"0.46239954\",\n \"0.46159115\",\n \"0.46158114\",\n \"0.4614831\",\n \"0.46083245\",\n \"0.4606021\",\n \"0.45919266\",\n \"0.45918155\",\n \"0.45808694\",\n \"0.45785168\",\n \"0.45741102\",\n \"0.45738333\",\n \"0.45550448\",\n \"0.4554904\",\n \"0.45376095\",\n \"0.45369375\",\n \"0.453162\",\n \"0.4515152\",\n \"0.45097572\",\n \"0.45091563\",\n \"0.4507228\",\n \"0.44930825\",\n \"0.44930825\",\n \"0.44778845\",\n \"0.44742638\",\n \"0.44662336\",\n \"0.44653386\",\n \"0.4445729\",\n \"0.4421044\",\n \"0.441969\",\n \"0.44186005\",\n \"0.4385507\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.62075883"},"document_rank":{"kind":"string","value":"3"}}},{"rowIdx":15588,"cells":{"query":{"kind":"string","value":"RollbackPrepared rolls back a prepared transaction."},"document":{"kind":"string","value":"def RollbackPrepared(self, request, context):\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\n context.set_details('Method not implemented!')\n raise NotImplementedError('Method not implemented!')"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def RollbackPrepared(self, request, context):\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)","def RollbackPrepared(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\n raise NotImplementedError()","def rollback(self):\n self._connection.execute_nonquery(\"sql\", \"ROLLBACK\", True)","def rollback(self):\n self.conn.rollback()","def RollBack(self):\r\n self.conn.rollback()","def rollback(self):\n if self.dbmi.__name__ == \"psycopg2\":\n if self.connected:\n self.connection.rollback()","def rollback(self):\n\n if not self.is_active:\n return\n\n if self.is_context_active:\n raise states.RolledBack(self)\n else:\n self.__do_rollback()\n self._cleanup()","def rollback(self):\n raise TransactionRollback('rollback called outside of transaction')","def _do_rollback(self):\n self.backend.rollback()","def rollback(self):\n conn = self.threadingLocal.connection\n if isinstance(conn, Transaction) and not conn._obsolete:\n self.threadingLocal.connection.rollback()","def rollback_transaction(self):\n cursor = self._cursor()\n cursor.close()\n self._db.rollback()\n self._end_transaction()","def rollback_transaction(self, event=None):\n assert self._current_transaction\n\n # Store stacks\n undo_stack = list(self._undo_stack)\n\n erroneous_tx = self._current_transaction\n self._current_transaction = None\n try:\n with Transaction(self.event_manager):\n try:\n erroneous_tx.execute()\n except Exception as e:\n logger.error(\"Could not roolback transaction\")\n logger.error(e)\n finally:\n # Discard all data collected in the rollback \"transaction\"\n self._undo_stack = undo_stack\n\n self._action_executed()","def rollback(self):\n try:\n if self._cur_batch:\n self._cur_batch.rollback()\n except ValueError:\n # ignore \"Batch must be in progress to rollback\" error\n pass\n self._cur_batch = None\n self._num_mutations = 0","def rollback(self):\n if self._transaction is None:\n raise TransactionNotStartedError(\"Cannot call rollback without a transaction\")\n else:\n def _resetTxn(result):\n self._transaction = None\n d = self._config.rollback(self._transaction)\n d.addCallback(_resetTxn)\n return d","def rollback(self):\r\n self.db.rollback()","def rollback(self):\n self.db.rollback()","def test_rollback(self, local_connection):\n\n users = self.tables.users\n connection = local_connection\n transaction = connection.begin()\n connection.execute(users.insert(), dict(user_id=1, user_name=\"user1\"))\n connection.execute(users.insert(), dict(user_id=2, user_name=\"user2\"))\n connection.execute(users.insert(), dict(user_id=3, user_name=\"user3\"))\n transaction.rollback()\n result = connection.exec_driver_sql(\"select * from users\")\n assert len(result.fetchall()) == 0","def rollback(self):\n self._rollback = True","def savepoint_rollback(self, id):\n self.execute(\"ROLLBACK TO SAVEPOINT {}\".format(id))","def rollback(self):\n pass","def rollback(self, stage, enodes, exception):","def rollback(self):\n return self.connection.rollback()","def rollback(self) -> None:\n if self._transaction is None:\n pass\n else:\n self._transaction.rollback(_to_root=True)","def rollback(self):\n return self.connection.rollback","def post_prepared_commit(self, key, prepared):\n docs = self.__splitprepared(prepared)\n docs[0][\"key\"] = key\n return self.client.post_commit(docs[0], docs[1])","def rollback_action(args, kwargs, was_interrupted, result=None):\n raise NotImplementedError()","def rollback(self):\n raise NotImplementedError","def rollback(self, dry_run=False, force=False):\n eh = SimpleErrorHandler()\n\n out = self._client.execute('rollback', n=dry_run, f=force, eh=eh)\n\n return bool(eh)","def rollback(self):\n self.success = False\n self.close()","def tpc_abort(self, transaction):\n raise NotImplementedError","def abort_transaction(self) -> None:\n pass","def rollback(self):\n self._session.rollback()\n\n return True","def rollback(self, snapshot):\n\n if not self.__settings:\n return\n\n _logger.debug('Performing rollback of data into '\n 'subsequent harvest period. Metric data and transaction events'\n 'will be preserved and rolled into next harvest')\n\n self.merge_metric_stats(snapshot)\n self._merge_transaction_events(snapshot, rollback=True)\n self._merge_synthetics_events(snapshot, rollback=True)\n self._merge_error_events(snapshot)\n self._merge_custom_events(snapshot, rollback=True)\n self._merge_span_events(snapshot, rollback=True)","def CommitPrepared(self, request, context):\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)","def rollback(self) -> None:\n with self.lock:\n self.wait(self._rollback_gen())","def rollback(self, cursor):\n\t\twith warnings.catch_warnings():\n\t\t\twarnings.simplefilter(\"ignore\")\n\t\t\tconnection = cursor.connection\n\t\tconnection.rollback()\n\t\tself._close_cursor(cursor)","def Rollback(self, request, global_params=None):\n config = self.GetMethodConfig('Rollback')\n return self._RunMethod(\n config, request, global_params=global_params)","def Rollback(self, request, global_params=None):\n config = self.GetMethodConfig('Rollback')\n return self._RunMethod(\n config, request, global_params=global_params)","def cancel(self):\n self.session.rollback()","async def rollback(self):\n if not self._active:\n raise ProfileSessionInactiveError()\n await self._teardown(commit=False)\n self._active = False","def rollback(self): \r\n if self._closed:\r\n raise Error('The connection to the database has been closed.')\r\n for table in self.tables.keys():\r\n if self.tables[table].open:\r\n self.tables[table].rollback()\r\n for table in self.createdTables:\r\n if self.tables.has_key(table):\r\n if self.tables[table].open:\r\n self.tables[table]._close()\r\n del self.tables[table]\r\n for end in self.tableExtensions:\r\n if os.path.exists(self.database+os.sep+table+end):\r\n os.remove(self.database+os.sep+table+end)\r\n self.createdTables = []","def test_rollback():","def test_no_rollback_in_committed_state(self):\n\n sess = fixture_session()\n\n def fail(*arg, **kw):\n raise BaseException(\"some base exception\")\n\n with mock.patch.object(\n testing.db.dialect, \"do_rollback\", side_effect=fail\n ) as fail_mock, mock.patch.object(\n testing.db.dialect,\n \"do_commit\",\n side_effect=testing.db.dialect.do_commit,\n ) as succeed_mock:\n # sess.begin() -> commit(). why would do_rollback() be called?\n # because of connection pool finalize_fairy *after* the commit.\n # this will cause the conn.close() in session.commit() to fail,\n # but after the DB commit succeeded.\n with expect_raises_message(BaseException, \"some base exception\"):\n with sess.begin():\n conn = sess.connection()\n fairy_conn = conn.connection\n\n eq_(succeed_mock.mock_calls, [mock.call(fairy_conn)])\n eq_(fail_mock.mock_calls, [mock.call(fairy_conn)])","def _rollback_context(self, persister):\n try:\n # Rollback the job transactional context.\n persister.rollback()\n\n except _errors.DatabaseError as error:\n _LOGGER.error(\n \"Error in %s rolling back job's context.\",\n self.__action.__name__, exc_info=error\n )\n\n # Update the job status.\n self.__result = False\n message = \"Tried to execute action ({0}).\".format(\n self.__action.__name__)\n self._add_status(Job.ERROR, Job.COMPLETE, message, True)\n\n # Finish context which means mark the job as finished\n # and update procedure's information.\n self._finish_context(False)","def CommitPrepared(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\n raise NotImplementedError()","def close(self):\n assert not self.closed\n if self.success:\n run(self.connection, \"COMMIT\")\n else:\n run(self.connection, \"ROLLBACK\")\n self.closed = True\n self.on_close()","def rollback(self, context: 'IconScoreContext', _block_height: int, _block_hash: bytes):\n Logger.info(tag=ROLLBACK_LOG_TAG, msg=\"rollback() start\")\n\n self.prep_address_converter: 'PRepAddressConverter' = context.storage.meta.get_prep_address_converter(context)\n\n self.preps = self._load_preps(context)\n self.term = self._load_term(context)\n\n Logger.info(tag=ROLLBACK_LOG_TAG, msg=f\"rollback() end: {self.term}\")","def rollback(commit_id):\n _confirm_branch()\n \n require('settings', provided_by=[production, staging])\n require('branch', provided_by=[stable, master, branch])\n \n maintenance_up()\n checkout_latest()\n git_reset(commit_id)\n gzip_assets()\n deploy_to_s3()\n maintenance_down()","def on_error_rollback(func):\n @functools.wraps(func)\n def db_safe_exec(*args, **kwargs):\n try:\n return func(*args, **kwargs)\n except Exception as e:\n logger.error('Error ({!s}) - rolling back'.format(e))\n session.rollback()\n raise\n return db_safe_exec","def abort(self, transaction):\n raise NotImplementedError","def rollback(self, block: 'Block') -> None:\n # Check for block validation before rollback\n self._precommit_data_manager.validate_precommit_block(block)\n self._precommit_data_manager.rollback(block)","def SetRollback(self, request, context):\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)","def prepare(self) -> None:\n trans = self._transaction\n if trans is None:\n trans = self._autobegin_t()\n\n trans.prepare()","def rollback(self, target_revision_id):\n url = DeckhandClient.get_path(\n DeckhandPaths.ROLLBACK\n ).format(target_revision_id)\n\n response = self._post_request(url)\n self._handle_bad_response(response)","def rollback(migrator, database, fake=False, **kwargs):\n pass","def rollback(tag):\n done = run_command(['git', 'tag', '-d', tag])\n if done.returncode:\n echo.bold(colors.red(str(done)))\n sys.exit(done.returncode)\n echo.cyan('Done:', done.stdout.strip())","def rollback_to(self, name):\n if not isinstance(name, str) or len(name.strip()) == 0:\n raise ProgrammingError(\"Invalid SAVEPOINT name\")\n self._connection.execute_nonquery(\n \"sql\",\n f\"ROLLBACK TO SAVEPOINT {quote_identifier(name)}\",\n True,\n )","def rollback_django(ref=None, debug=False, dirty=False):\n if has_version_info():\n #\n # To roll back we need to fetch the existing version, execute the\n # database rollback, and then do a deploy of a specific version\n #\n create_virtualenv()\n\n # Copy the new code... the one we want to back out, as we need the\n # migrations from this\n operations.fetch_render_copy(ref, debug, dirty)\n\n # Rollback the database\n migratedb(True)\n\n # Get the old code\n del env['tempdir']\n operations.fetch_render_copy(env.scm_tag[\"rollback\"], debug, dirty, True)\n\n pip_requirements()\n refresh_wsgi()\n\n else:\n abort(\"No version info present to allow rollback\")","def SetRollback(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\n raise NotImplementedError()","def rollback(self, project_id, transaction):\n request_pb = _datastore_pb2.RollbackRequest(\n project_id=project_id, transaction=transaction\n )\n # Response is empty (i.e. no fields) but we return it anyway.\n return _rpc(\n self.client._http,\n project_id,\n \"rollback\",\n self.client._base_url,\n self.client._client_info,\n request_pb,\n _datastore_pb2.RollbackResponse,\n )","def rollback(self):\n if len(self.__stack) == 0:\n raise EmptyStackException()\n self.__current_pos = self.__stack[-1][0]\n self.line = self.__stack[-1][1]\n self.linePos = self.__stack[-1][2]\n self.__stack = self.__stack[:-1]","def _Dynamic_Rollback(self, transaction, transaction_response,\n request_id=None):\n transaction.set_app(self.project_id)\n\n try:\n del self.__tx_actions[transaction.handle()]\n except KeyError:\n pass\n\n self._RemoteSend(transaction, transaction_response, \"Rollback\", request_id)\n \n return transaction_response","def commit(cls, sql, **kwargs):\n conn = kwargs['conn']\n\n cursor = conn.cursor(dictionary=True, buffered=False)\n if CHECKS_OFF:\n sql = TURN_CHECKS_OFF + sql\n\n for _ in cursor.execute(sql, kwargs.get('args'), multi=True):\n pass\n\n cls.close(conn, cursor)","def abort(self) -> None:\n self._connector.abort_transaction()","def test_auto_rollback(self):\n self.mocked_cursor.execute.side_effect = psycopg2.Error('testing')\n\n db = database.Database()\n try:\n db.execute(sql=\"SELECT * from FOO WHERE bar LIKE 'baz'\")\n except database.DatabaseError:\n pass\n\n self.assertEqual(self.mocked_connection.rollback.call_count, 1)","def perform_rollbacks(self, args: Tuple, kwargs: dict) -> None:\n for value in iter_nested_value((args, kwargs)):\n if isinstance(value, Handle):\n self.backend.rollback_handle(value)","def rollback(self, steps=1) -> None:\n raise NotImplementedError(\n \"Open transactions are currently not supported. To reset commit head, check WOQLClient.reset\"\n )","def rollback(self, rollback_to):\n raise NotImplementedError","def end(self):\n conn = self.threadingLocal.connection\n if not isinstance(conn, Transaction):\n return\n if not conn._obsolete:\n conn.rollback()\n self.threadingLocal.connection = self.threadingLocal.old_conn\n del self.threadingLocal.old_conn\n self.threadingLocal.connection.cache.clear()","def aborted(self, exc_info):\n self.exc_info = exc_info\n self.did_end = True\n self.write(format_exception(*self.exc_info))","def __exit__(self, exception_type, exception_val, trace):\n if not exception_type:\n self.commit()\n else:\n self.rollback()\n self.close()","def Rollback(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\n raise NotImplementedError()","def CommitPrepared(self, request, context):\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\n context.set_details('Method not implemented!')\n raise NotImplementedError('Method not implemented!')","def CommitPrepared(self, request, context):\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\n context.set_details('Method not implemented!')\n raise NotImplementedError('Method not implemented!')","def rollback_session_after_test(self, sandboxed_session):\n yield\n sandboxed_session.rollback()","def tearDown(self): \n db.session.rollback()","def tearDown(self): \n db.session.rollback()","def _end_transaction(self):\n self._db.autocommit=True","def process_exception(self, request, exception):\r\n if transaction.is_dirty():\r\n transaction.rollback()\r\n transaction.leave_transaction_management()","def commit(self):\n self.execute_sql(sql.commit)\n self.under_transaction = False","def db_session_rollback_and_globalize(self):\n self.db_session.rollback()\n self.session.worm_localized.remove(self.db_session)\n del self.db_session","def SetRollback(self, request, context):\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\n context.set_details('Method not implemented!')\n raise NotImplementedError('Method not implemented!')","def SetRollback(self, request, context):\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\n context.set_details('Method not implemented!')\n raise NotImplementedError('Method not implemented!')","def tearDown(self):\r\n\r\n db.session.rollback()","def __commit(self):\n from sqlalchemy.exc import IntegrityError\n\n try:\n db.session.commit()\n except IntegrityError:\n db.session.rollback()","def rollback(self):\n # PEP 249\n raise impala.error.NotSupportedError()","def tearDown(self):\r\n db.session.rollback()","def tearDown(self):\n model.DBSession.rollback()","def prepare_for_commit(self):","def rollback(self):\n for db in self.values():\n db.rollback()","def rollback(folder_name, with_subfolders):\n process_backups(folder_name, with_subfolders, lambda x: copy2(x, x[:-4]))","def rollbackVirtualMachine(self,node,vmid,snapname):\n post_data = None\n data = self.connect('post',\"nodes/%s/qemu/%s/snapshot/%s/rollback\" % (node,vmid,snapname), post_data)\n return data","def abort_transaction(self,xid):\n modlogger.debug( \"abort:%s\"%xid)\n opid = self.new_opid()\n xaction = AbortTxOperation(opid,xid)\n self._add_operation(xid,xaction)\n try:\n self.tx.rollback()\n finally:\n self.tx = None","def manual_transaction():\r\n try:\r\n yield\r\n except Exception:\r\n transaction.rollback()\r\n log.exception('Due to an error, this transaction has been rolled back')\r\n raise\r\n else:\r\n transaction.commit()","def svn_fs_abort_txn(*args):\r\n return _fs.svn_fs_abort_txn(*args)","def tearDown(self):\n\n db.session.rollback()","def tearDown(self):\n\n db.session.rollback()","def tearDown(self):\n\n db.session.rollback()","def tearDown(self):\n\n db.session.rollback()"],"string":"[\n \"def RollbackPrepared(self, request, context):\\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)\",\n \"def RollbackPrepared(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\\n raise NotImplementedError()\",\n \"def rollback(self):\\n self._connection.execute_nonquery(\\\"sql\\\", \\\"ROLLBACK\\\", True)\",\n \"def rollback(self):\\n self.conn.rollback()\",\n \"def RollBack(self):\\r\\n self.conn.rollback()\",\n \"def rollback(self):\\n if self.dbmi.__name__ == \\\"psycopg2\\\":\\n if self.connected:\\n self.connection.rollback()\",\n \"def rollback(self):\\n\\n if not self.is_active:\\n return\\n\\n if self.is_context_active:\\n raise states.RolledBack(self)\\n else:\\n self.__do_rollback()\\n self._cleanup()\",\n \"def rollback(self):\\n raise TransactionRollback('rollback called outside of transaction')\",\n \"def _do_rollback(self):\\n self.backend.rollback()\",\n \"def rollback(self):\\n conn = self.threadingLocal.connection\\n if isinstance(conn, Transaction) and not conn._obsolete:\\n self.threadingLocal.connection.rollback()\",\n \"def rollback_transaction(self):\\n cursor = self._cursor()\\n cursor.close()\\n self._db.rollback()\\n self._end_transaction()\",\n \"def rollback_transaction(self, event=None):\\n assert self._current_transaction\\n\\n # Store stacks\\n undo_stack = list(self._undo_stack)\\n\\n erroneous_tx = self._current_transaction\\n self._current_transaction = None\\n try:\\n with Transaction(self.event_manager):\\n try:\\n erroneous_tx.execute()\\n except Exception as e:\\n logger.error(\\\"Could not roolback transaction\\\")\\n logger.error(e)\\n finally:\\n # Discard all data collected in the rollback \\\"transaction\\\"\\n self._undo_stack = undo_stack\\n\\n self._action_executed()\",\n \"def rollback(self):\\n try:\\n if self._cur_batch:\\n self._cur_batch.rollback()\\n except ValueError:\\n # ignore \\\"Batch must be in progress to rollback\\\" error\\n pass\\n self._cur_batch = None\\n self._num_mutations = 0\",\n \"def rollback(self):\\n if self._transaction is None:\\n raise TransactionNotStartedError(\\\"Cannot call rollback without a transaction\\\")\\n else:\\n def _resetTxn(result):\\n self._transaction = None\\n d = self._config.rollback(self._transaction)\\n d.addCallback(_resetTxn)\\n return d\",\n \"def rollback(self):\\r\\n self.db.rollback()\",\n \"def rollback(self):\\n self.db.rollback()\",\n \"def test_rollback(self, local_connection):\\n\\n users = self.tables.users\\n connection = local_connection\\n transaction = connection.begin()\\n connection.execute(users.insert(), dict(user_id=1, user_name=\\\"user1\\\"))\\n connection.execute(users.insert(), dict(user_id=2, user_name=\\\"user2\\\"))\\n connection.execute(users.insert(), dict(user_id=3, user_name=\\\"user3\\\"))\\n transaction.rollback()\\n result = connection.exec_driver_sql(\\\"select * from users\\\")\\n assert len(result.fetchall()) == 0\",\n \"def rollback(self):\\n self._rollback = True\",\n \"def savepoint_rollback(self, id):\\n self.execute(\\\"ROLLBACK TO SAVEPOINT {}\\\".format(id))\",\n \"def rollback(self):\\n pass\",\n \"def rollback(self, stage, enodes, exception):\",\n \"def rollback(self):\\n return self.connection.rollback()\",\n \"def rollback(self) -> None:\\n if self._transaction is None:\\n pass\\n else:\\n self._transaction.rollback(_to_root=True)\",\n \"def rollback(self):\\n return self.connection.rollback\",\n \"def post_prepared_commit(self, key, prepared):\\n docs = self.__splitprepared(prepared)\\n docs[0][\\\"key\\\"] = key\\n return self.client.post_commit(docs[0], docs[1])\",\n \"def rollback_action(args, kwargs, was_interrupted, result=None):\\n raise NotImplementedError()\",\n \"def rollback(self):\\n raise NotImplementedError\",\n \"def rollback(self, dry_run=False, force=False):\\n eh = SimpleErrorHandler()\\n\\n out = self._client.execute('rollback', n=dry_run, f=force, eh=eh)\\n\\n return bool(eh)\",\n \"def rollback(self):\\n self.success = False\\n self.close()\",\n \"def tpc_abort(self, transaction):\\n raise NotImplementedError\",\n \"def abort_transaction(self) -> None:\\n pass\",\n \"def rollback(self):\\n self._session.rollback()\\n\\n return True\",\n \"def rollback(self, snapshot):\\n\\n if not self.__settings:\\n return\\n\\n _logger.debug('Performing rollback of data into '\\n 'subsequent harvest period. Metric data and transaction events'\\n 'will be preserved and rolled into next harvest')\\n\\n self.merge_metric_stats(snapshot)\\n self._merge_transaction_events(snapshot, rollback=True)\\n self._merge_synthetics_events(snapshot, rollback=True)\\n self._merge_error_events(snapshot)\\n self._merge_custom_events(snapshot, rollback=True)\\n self._merge_span_events(snapshot, rollback=True)\",\n \"def CommitPrepared(self, request, context):\\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)\",\n \"def rollback(self) -> None:\\n with self.lock:\\n self.wait(self._rollback_gen())\",\n \"def rollback(self, cursor):\\n\\t\\twith warnings.catch_warnings():\\n\\t\\t\\twarnings.simplefilter(\\\"ignore\\\")\\n\\t\\t\\tconnection = cursor.connection\\n\\t\\tconnection.rollback()\\n\\t\\tself._close_cursor(cursor)\",\n \"def Rollback(self, request, global_params=None):\\n config = self.GetMethodConfig('Rollback')\\n return self._RunMethod(\\n config, request, global_params=global_params)\",\n \"def Rollback(self, request, global_params=None):\\n config = self.GetMethodConfig('Rollback')\\n return self._RunMethod(\\n config, request, global_params=global_params)\",\n \"def cancel(self):\\n self.session.rollback()\",\n \"async def rollback(self):\\n if not self._active:\\n raise ProfileSessionInactiveError()\\n await self._teardown(commit=False)\\n self._active = False\",\n \"def rollback(self): \\r\\n if self._closed:\\r\\n raise Error('The connection to the database has been closed.')\\r\\n for table in self.tables.keys():\\r\\n if self.tables[table].open:\\r\\n self.tables[table].rollback()\\r\\n for table in self.createdTables:\\r\\n if self.tables.has_key(table):\\r\\n if self.tables[table].open:\\r\\n self.tables[table]._close()\\r\\n del self.tables[table]\\r\\n for end in self.tableExtensions:\\r\\n if os.path.exists(self.database+os.sep+table+end):\\r\\n os.remove(self.database+os.sep+table+end)\\r\\n self.createdTables = []\",\n \"def test_rollback():\",\n \"def test_no_rollback_in_committed_state(self):\\n\\n sess = fixture_session()\\n\\n def fail(*arg, **kw):\\n raise BaseException(\\\"some base exception\\\")\\n\\n with mock.patch.object(\\n testing.db.dialect, \\\"do_rollback\\\", side_effect=fail\\n ) as fail_mock, mock.patch.object(\\n testing.db.dialect,\\n \\\"do_commit\\\",\\n side_effect=testing.db.dialect.do_commit,\\n ) as succeed_mock:\\n # sess.begin() -> commit(). why would do_rollback() be called?\\n # because of connection pool finalize_fairy *after* the commit.\\n # this will cause the conn.close() in session.commit() to fail,\\n # but after the DB commit succeeded.\\n with expect_raises_message(BaseException, \\\"some base exception\\\"):\\n with sess.begin():\\n conn = sess.connection()\\n fairy_conn = conn.connection\\n\\n eq_(succeed_mock.mock_calls, [mock.call(fairy_conn)])\\n eq_(fail_mock.mock_calls, [mock.call(fairy_conn)])\",\n \"def _rollback_context(self, persister):\\n try:\\n # Rollback the job transactional context.\\n persister.rollback()\\n\\n except _errors.DatabaseError as error:\\n _LOGGER.error(\\n \\\"Error in %s rolling back job's context.\\\",\\n self.__action.__name__, exc_info=error\\n )\\n\\n # Update the job status.\\n self.__result = False\\n message = \\\"Tried to execute action ({0}).\\\".format(\\n self.__action.__name__)\\n self._add_status(Job.ERROR, Job.COMPLETE, message, True)\\n\\n # Finish context which means mark the job as finished\\n # and update procedure's information.\\n self._finish_context(False)\",\n \"def CommitPrepared(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\\n raise NotImplementedError()\",\n \"def close(self):\\n assert not self.closed\\n if self.success:\\n run(self.connection, \\\"COMMIT\\\")\\n else:\\n run(self.connection, \\\"ROLLBACK\\\")\\n self.closed = True\\n self.on_close()\",\n \"def rollback(self, context: 'IconScoreContext', _block_height: int, _block_hash: bytes):\\n Logger.info(tag=ROLLBACK_LOG_TAG, msg=\\\"rollback() start\\\")\\n\\n self.prep_address_converter: 'PRepAddressConverter' = context.storage.meta.get_prep_address_converter(context)\\n\\n self.preps = self._load_preps(context)\\n self.term = self._load_term(context)\\n\\n Logger.info(tag=ROLLBACK_LOG_TAG, msg=f\\\"rollback() end: {self.term}\\\")\",\n \"def rollback(commit_id):\\n _confirm_branch()\\n \\n require('settings', provided_by=[production, staging])\\n require('branch', provided_by=[stable, master, branch])\\n \\n maintenance_up()\\n checkout_latest()\\n git_reset(commit_id)\\n gzip_assets()\\n deploy_to_s3()\\n maintenance_down()\",\n \"def on_error_rollback(func):\\n @functools.wraps(func)\\n def db_safe_exec(*args, **kwargs):\\n try:\\n return func(*args, **kwargs)\\n except Exception as e:\\n logger.error('Error ({!s}) - rolling back'.format(e))\\n session.rollback()\\n raise\\n return db_safe_exec\",\n \"def abort(self, transaction):\\n raise NotImplementedError\",\n \"def rollback(self, block: 'Block') -> None:\\n # Check for block validation before rollback\\n self._precommit_data_manager.validate_precommit_block(block)\\n self._precommit_data_manager.rollback(block)\",\n \"def SetRollback(self, request, context):\\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)\",\n \"def prepare(self) -> None:\\n trans = self._transaction\\n if trans is None:\\n trans = self._autobegin_t()\\n\\n trans.prepare()\",\n \"def rollback(self, target_revision_id):\\n url = DeckhandClient.get_path(\\n DeckhandPaths.ROLLBACK\\n ).format(target_revision_id)\\n\\n response = self._post_request(url)\\n self._handle_bad_response(response)\",\n \"def rollback(migrator, database, fake=False, **kwargs):\\n pass\",\n \"def rollback(tag):\\n done = run_command(['git', 'tag', '-d', tag])\\n if done.returncode:\\n echo.bold(colors.red(str(done)))\\n sys.exit(done.returncode)\\n echo.cyan('Done:', done.stdout.strip())\",\n \"def rollback_to(self, name):\\n if not isinstance(name, str) or len(name.strip()) == 0:\\n raise ProgrammingError(\\\"Invalid SAVEPOINT name\\\")\\n self._connection.execute_nonquery(\\n \\\"sql\\\",\\n f\\\"ROLLBACK TO SAVEPOINT {quote_identifier(name)}\\\",\\n True,\\n )\",\n \"def rollback_django(ref=None, debug=False, dirty=False):\\n if has_version_info():\\n #\\n # To roll back we need to fetch the existing version, execute the\\n # database rollback, and then do a deploy of a specific version\\n #\\n create_virtualenv()\\n\\n # Copy the new code... the one we want to back out, as we need the\\n # migrations from this\\n operations.fetch_render_copy(ref, debug, dirty)\\n\\n # Rollback the database\\n migratedb(True)\\n\\n # Get the old code\\n del env['tempdir']\\n operations.fetch_render_copy(env.scm_tag[\\\"rollback\\\"], debug, dirty, True)\\n\\n pip_requirements()\\n refresh_wsgi()\\n\\n else:\\n abort(\\\"No version info present to allow rollback\\\")\",\n \"def SetRollback(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\\n raise NotImplementedError()\",\n \"def rollback(self, project_id, transaction):\\n request_pb = _datastore_pb2.RollbackRequest(\\n project_id=project_id, transaction=transaction\\n )\\n # Response is empty (i.e. no fields) but we return it anyway.\\n return _rpc(\\n self.client._http,\\n project_id,\\n \\\"rollback\\\",\\n self.client._base_url,\\n self.client._client_info,\\n request_pb,\\n _datastore_pb2.RollbackResponse,\\n )\",\n \"def rollback(self):\\n if len(self.__stack) == 0:\\n raise EmptyStackException()\\n self.__current_pos = self.__stack[-1][0]\\n self.line = self.__stack[-1][1]\\n self.linePos = self.__stack[-1][2]\\n self.__stack = self.__stack[:-1]\",\n \"def _Dynamic_Rollback(self, transaction, transaction_response,\\n request_id=None):\\n transaction.set_app(self.project_id)\\n\\n try:\\n del self.__tx_actions[transaction.handle()]\\n except KeyError:\\n pass\\n\\n self._RemoteSend(transaction, transaction_response, \\\"Rollback\\\", request_id)\\n \\n return transaction_response\",\n \"def commit(cls, sql, **kwargs):\\n conn = kwargs['conn']\\n\\n cursor = conn.cursor(dictionary=True, buffered=False)\\n if CHECKS_OFF:\\n sql = TURN_CHECKS_OFF + sql\\n\\n for _ in cursor.execute(sql, kwargs.get('args'), multi=True):\\n pass\\n\\n cls.close(conn, cursor)\",\n \"def abort(self) -> None:\\n self._connector.abort_transaction()\",\n \"def test_auto_rollback(self):\\n self.mocked_cursor.execute.side_effect = psycopg2.Error('testing')\\n\\n db = database.Database()\\n try:\\n db.execute(sql=\\\"SELECT * from FOO WHERE bar LIKE 'baz'\\\")\\n except database.DatabaseError:\\n pass\\n\\n self.assertEqual(self.mocked_connection.rollback.call_count, 1)\",\n \"def perform_rollbacks(self, args: Tuple, kwargs: dict) -> None:\\n for value in iter_nested_value((args, kwargs)):\\n if isinstance(value, Handle):\\n self.backend.rollback_handle(value)\",\n \"def rollback(self, steps=1) -> None:\\n raise NotImplementedError(\\n \\\"Open transactions are currently not supported. To reset commit head, check WOQLClient.reset\\\"\\n )\",\n \"def rollback(self, rollback_to):\\n raise NotImplementedError\",\n \"def end(self):\\n conn = self.threadingLocal.connection\\n if not isinstance(conn, Transaction):\\n return\\n if not conn._obsolete:\\n conn.rollback()\\n self.threadingLocal.connection = self.threadingLocal.old_conn\\n del self.threadingLocal.old_conn\\n self.threadingLocal.connection.cache.clear()\",\n \"def aborted(self, exc_info):\\n self.exc_info = exc_info\\n self.did_end = True\\n self.write(format_exception(*self.exc_info))\",\n \"def __exit__(self, exception_type, exception_val, trace):\\n if not exception_type:\\n self.commit()\\n else:\\n self.rollback()\\n self.close()\",\n \"def Rollback(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\\n raise NotImplementedError()\",\n \"def CommitPrepared(self, request, context):\\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\\n context.set_details('Method not implemented!')\\n raise NotImplementedError('Method not implemented!')\",\n \"def CommitPrepared(self, request, context):\\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\\n context.set_details('Method not implemented!')\\n raise NotImplementedError('Method not implemented!')\",\n \"def rollback_session_after_test(self, sandboxed_session):\\n yield\\n sandboxed_session.rollback()\",\n \"def tearDown(self): \\n db.session.rollback()\",\n \"def tearDown(self): \\n db.session.rollback()\",\n \"def _end_transaction(self):\\n self._db.autocommit=True\",\n \"def process_exception(self, request, exception):\\r\\n if transaction.is_dirty():\\r\\n transaction.rollback()\\r\\n transaction.leave_transaction_management()\",\n \"def commit(self):\\n self.execute_sql(sql.commit)\\n self.under_transaction = False\",\n \"def db_session_rollback_and_globalize(self):\\n self.db_session.rollback()\\n self.session.worm_localized.remove(self.db_session)\\n del self.db_session\",\n \"def SetRollback(self, request, context):\\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\\n context.set_details('Method not implemented!')\\n raise NotImplementedError('Method not implemented!')\",\n \"def SetRollback(self, request, context):\\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\\n context.set_details('Method not implemented!')\\n raise NotImplementedError('Method not implemented!')\",\n \"def tearDown(self):\\r\\n\\r\\n db.session.rollback()\",\n \"def __commit(self):\\n from sqlalchemy.exc import IntegrityError\\n\\n try:\\n db.session.commit()\\n except IntegrityError:\\n db.session.rollback()\",\n \"def rollback(self):\\n # PEP 249\\n raise impala.error.NotSupportedError()\",\n \"def tearDown(self):\\r\\n db.session.rollback()\",\n \"def tearDown(self):\\n model.DBSession.rollback()\",\n \"def prepare_for_commit(self):\",\n \"def rollback(self):\\n for db in self.values():\\n db.rollback()\",\n \"def rollback(folder_name, with_subfolders):\\n process_backups(folder_name, with_subfolders, lambda x: copy2(x, x[:-4]))\",\n \"def rollbackVirtualMachine(self,node,vmid,snapname):\\n post_data = None\\n data = self.connect('post',\\\"nodes/%s/qemu/%s/snapshot/%s/rollback\\\" % (node,vmid,snapname), post_data)\\n return data\",\n \"def abort_transaction(self,xid):\\n modlogger.debug( \\\"abort:%s\\\"%xid)\\n opid = self.new_opid()\\n xaction = AbortTxOperation(opid,xid)\\n self._add_operation(xid,xaction)\\n try:\\n self.tx.rollback()\\n finally:\\n self.tx = None\",\n \"def manual_transaction():\\r\\n try:\\r\\n yield\\r\\n except Exception:\\r\\n transaction.rollback()\\r\\n log.exception('Due to an error, this transaction has been rolled back')\\r\\n raise\\r\\n else:\\r\\n transaction.commit()\",\n \"def svn_fs_abort_txn(*args):\\r\\n return _fs.svn_fs_abort_txn(*args)\",\n \"def tearDown(self):\\n\\n db.session.rollback()\",\n \"def tearDown(self):\\n\\n db.session.rollback()\",\n \"def tearDown(self):\\n\\n db.session.rollback()\",\n \"def tearDown(self):\\n\\n db.session.rollback()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.65784436","0.6450222","0.6257658","0.5932248","0.5872741","0.5795709","0.5696239","0.5617441","0.55968213","0.5574776","0.5546432","0.54966366","0.5483333","0.54233134","0.5419659","0.5336303","0.5319498","0.5277183","0.52744156","0.52693737","0.52524066","0.5238949","0.5217942","0.5202639","0.51862377","0.5183209","0.51482093","0.5100971","0.50629705","0.5029153","0.50090724","0.49976885","0.4975234","0.4973341","0.4972644","0.49722967","0.49614966","0.49614966","0.49439016","0.49393198","0.49091414","0.48701665","0.47938088","0.4764793","0.47598147","0.4745087","0.47079083","0.4699249","0.46476915","0.46451828","0.4642751","0.46281844","0.46169618","0.4612241","0.46039093","0.45945477","0.4570147","0.45653647","0.45569673","0.4549615","0.45307684","0.4521128","0.4510648","0.45013508","0.4499716","0.44754854","0.44550958","0.44519636","0.44306222","0.4416421","0.44113058","0.44048128","0.43900958","0.43900958","0.4388267","0.43521208","0.43521208","0.4326656","0.4320019","0.4317849","0.43069908","0.42878252","0.42878252","0.42822364","0.4281912","0.4281614","0.42640182","0.4255935","0.42529374","0.4249257","0.42400685","0.42365533","0.42296502","0.42210895","0.42090672","0.4203308","0.4203308","0.4203308","0.4203308"],"string":"[\n \"0.65784436\",\n \"0.6450222\",\n \"0.6257658\",\n \"0.5932248\",\n \"0.5872741\",\n \"0.5795709\",\n \"0.5696239\",\n \"0.5617441\",\n \"0.55968213\",\n \"0.5574776\",\n \"0.5546432\",\n \"0.54966366\",\n \"0.5483333\",\n \"0.54233134\",\n \"0.5419659\",\n \"0.5336303\",\n \"0.5319498\",\n \"0.5277183\",\n \"0.52744156\",\n \"0.52693737\",\n \"0.52524066\",\n \"0.5238949\",\n \"0.5217942\",\n \"0.5202639\",\n \"0.51862377\",\n \"0.5183209\",\n \"0.51482093\",\n \"0.5100971\",\n \"0.50629705\",\n \"0.5029153\",\n \"0.50090724\",\n \"0.49976885\",\n \"0.4975234\",\n \"0.4973341\",\n \"0.4972644\",\n \"0.49722967\",\n \"0.49614966\",\n \"0.49614966\",\n \"0.49439016\",\n \"0.49393198\",\n \"0.49091414\",\n \"0.48701665\",\n \"0.47938088\",\n \"0.4764793\",\n \"0.47598147\",\n \"0.4745087\",\n \"0.47079083\",\n \"0.4699249\",\n \"0.46476915\",\n \"0.46451828\",\n \"0.4642751\",\n \"0.46281844\",\n \"0.46169618\",\n \"0.4612241\",\n \"0.46039093\",\n \"0.45945477\",\n \"0.4570147\",\n \"0.45653647\",\n \"0.45569673\",\n \"0.4549615\",\n \"0.45307684\",\n \"0.4521128\",\n \"0.4510648\",\n \"0.45013508\",\n \"0.4499716\",\n \"0.44754854\",\n \"0.44550958\",\n \"0.44519636\",\n \"0.44306222\",\n \"0.4416421\",\n \"0.44113058\",\n \"0.44048128\",\n \"0.43900958\",\n \"0.43900958\",\n \"0.4388267\",\n \"0.43521208\",\n \"0.43521208\",\n \"0.4326656\",\n \"0.4320019\",\n \"0.4317849\",\n \"0.43069908\",\n \"0.42878252\",\n \"0.42878252\",\n \"0.42822364\",\n \"0.4281912\",\n \"0.4281614\",\n \"0.42640182\",\n \"0.4255935\",\n \"0.42529374\",\n \"0.4249257\",\n \"0.42400685\",\n \"0.42365533\",\n \"0.42296502\",\n \"0.42210895\",\n \"0.42090672\",\n \"0.4203308\",\n \"0.4203308\",\n \"0.4203308\",\n \"0.4203308\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.58695024"},"document_rank":{"kind":"string","value":"6"}}},{"rowIdx":15589,"cells":{"query":{"kind":"string","value":"CreateTransaction creates the metadata for a 2pc transaction."},"document":{"kind":"string","value":"def CreateTransaction(self, request, context):\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\n context.set_details('Method not implemented!')\n raise NotImplementedError('Method not implemented!')"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def CreateTransaction(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\n raise NotImplementedError()","def CreateTransaction(self, request, context):\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)","def create_transaction(self, receiver, amount, comment=\"\"):\n new_tx = Transaction.new(sender=self.pubkey, receiver=receiver,\n amount=amount, privkey=self.privkey,\n comment=comment)\n tx_json = new_tx.to_json()\n msg = \"t\" + json.dumps({\"tx_json\": tx_json})\n self.add_transaction(tx_json)\n self.broadcast_message(msg)\n return new_tx","def __create_transactions_table(self):\n cmd = \"\"\" CREATE TABLE IF NOT EXISTS %s (\n %s text,\n %s text,\n %s text,\n %s real,\n %s text,\n %s text);\"\"\" %(TABLE_TRANSACTIONS,\n COL_TRANSACTION_BLOCK,\n COL_TRANSACTION_SENDER,\n COL_TRANSACTION_RECEIVER,\n COL_TRANSACTION_AMOUNT,\n COL_TRANSACTION_SUB_TIME,\n COL_TRANSACTION_VER_TIME)\n self.__dbcursor.execute(cmd)","def create_transaction():\n data = request.get_json()\n response = None\n status_code = None\n\n # Proposed transaction document validity checks\n if balance() < (data['amount']):\n response = dict(message='Your balance is not enough to complete transaction')\n status_code = 400\n elif not (\n any(node_['public_key'] == data['sender_address'] for node_ in node.network) and\n any(node_['public_key'] == data['recipient_address'] for node_ in node.network) and\n isinstance((data['amount']), (int, float))\n ):\n response = dict(message='Please make sure the proposed transaction is valid.')\n status_code = 400\n\n if response and status_code:\n return jsonify(response), status_code\n\n transaction_id = str(uuid4())\n\n # Use as many utxos as necessary to create the new transaction inputs\n sender_address = data['sender_address']\n sum_ = 0\n tx_inputs = []\n for utxo in node.blkchain.utxos[sender_address]:\n if sum_ >= (data['amount']):\n break\n elif not node.blkchain.transaction_unconfirmed(utxo):\n sum_ += utxo.amount\n tx_inputs.append(TransactionInput.from_output(utxo))\n\n # Create 2 transaction outputs, one for the transfer and one for the sender's change\n tx_outputs = [\n TransactionOutput(\n transaction_id=transaction_id,\n recipient_address=data['recipient_address'],\n amount=(data['amount'])\n ),\n TransactionOutput(\n transaction_id=transaction_id,\n recipient_address=data['sender_address'],\n amount=sum_ - (data['amount'])\n )\n ]\n\n # Actual transaction object:\n tx = Transaction(\n sender_address=data['sender_address'],\n recipient_address=data['recipient_address'],\n amount=(data['amount']),\n transaction_inputs=tx_inputs,\n transaction_outputs=tx_outputs,\n transaction_id=transaction_id\n )\n\n response = tx.to_dict()\n return jsonify(response), 200","def create_transaction(conn, transaction):\n sql = ''' INSERT INTO transactions(date, value, currency, desc, categ)\n VALUES(?, ?, ?, ?, ?) '''\n cur = conn.cursor()\n cur.execute(sql, transaction)","def CreateTx(self, request, context):\n channel_name = request.channel or conf.LOOPCHAIN_DEFAULT_CHANNEL\n utils.logger.info(f\"peer_outer_service::CreateTx request({request.data}), channel({channel_name})\")\n\n channel_stub = StubCollection().channel_stubs[channel_name]\n result_hash = asyncio.run_coroutine_threadsafe(\n channel_stub.async_task().create_tx(request.data),\n self.peer_service.inner_service.loop\n ).result()\n\n return loopchain_pb2.CreateTxReply(\n response_code=message_code.Response.success,\n tx_hash=result_hash,\n more_info='')","def createrawtransaction(self, inputs, outputs):\n return self.proxy.createrawtransaction(inputs, outputs)","def new_transaction():\n\n data = request.get_json()\n\n if not data:\n return \"No transation data passed\", 400\n\n required = ['sender', 'recipient', 'amount']\n\n if not (list(data.keys()) == required):\n return 'Missing Value', 400\n \n block_index = blockchain.add_transaction(data['sender'], data['recipient'], data['amount'])\n response = {'message':f'Adding the transaction to block at index: {block_index}'}\n\n return jsonify(response), 201","def tx_create(self,\n keypair,\n amount=1,\n deposit=CONTRACT_DEFAULT_DEPOSIT,\n init_state=\"()\",\n gas=CONTRACT_DEFAULT_GAS,\n gas_price=CONTRACT_DEFAULT_GAS_PRICE,\n fee=DEFAULT_FEE,\n vm_version=CONTRACT_DEFAULT_VM_VERSION,\n tx_ttl=DEFAULT_TX_TTL):\n try:\n call_data = self.encode_calldata(\"init\", init_state)\n\n # get the transaction builder\n txb = TxBuilder(self.client, keypair)\n # create spend_tx\n tx, sg, tx_hash, contract_id = txb.tx_contract_create(self.bytecode, call_data, amount, deposit, gas, gas_price, vm_version, fee, tx_ttl)\n # post the transaction to the chain\n txb.post_transaction(tx, tx_hash)\n if self.client.blocking_mode:\n txb.wait_tx(tx_hash)\n # store the contract address in the instance variabl\n self.address = contract_id\n return tx\n except OpenAPIClientException as e:\n raise ContractError(e)","def create_tx(self, coin, account, to, amount):\n if coin is ETH:\n gasEstimate = self.w3.eth.estimateGas(\n {\"from\": account.address, \"to\": to, \"value\": amount}\n )\n return {\n \"from\": account.address,\n \"to\": to,\n \"value\": self.w3.toWei(amount, 'ether'),\n \"gasPrice\": self.w3.eth.gasPrice,\n \"gas\": gasEstimate,\n \"nonce\": self.w3.eth.getTransactionCount(account.address),\n }\n elif coin is BTCTEST:\n return PrivateKeyTestnet.prepare_transaction(account.address, [(to, amount, BTC)])\n elif coin is BTC:\n return PrivateKey.prepare_transaction(account.address, [(to, amount, BTC)])\n else:\n return None","def cypher_transaction():\n session = cypher.Session(HOST)\n return session.create_transaction()","def createAccount_blockchain():\n\n logsOfError=''\n try:\n account = tron.create_account\n except Exception as e:\n logsOfError = logsOfError+str(e)\n return {'publicKey':str(account.public_key), 'base58':str(account.address.base58), 'hex':str( account.address.hex), 'privateKey':str(account.private_key), 'logs':logsOfError, 'status':'success'}","def __create_transaction(self):\n log.debug(\"Displaying __create_transaction\")\n # Make the admin select an user\n user = self.__user_select()\n # Allow the cancellation of the operation\n if isinstance(user, CancelSignal):\n return\n # Create an inline keyboard with a single cancel button\n cancel = telegram.InlineKeyboardMarkup([[telegram.InlineKeyboardButton(self.loc.get(\"menu_all_cancel\"),\n callback_data=\"cmd_cancel\")]])\n # Request from the user the amount of money to be credited manually\n self.bot.send_message(self.chat.id, self.loc.get(\"ask_credit\"), reply_markup=cancel)\n # Wait for an answer\n reply = self.__wait_for_regex(r\"(-? ?[0-9]{1,3}(?:[.,][0-9]{1,2})?)\", cancellable=True)\n # Allow the cancellation of the operation\n if isinstance(reply, CancelSignal):\n return\n # Convert the reply to a price object\n price = self.Price(reply)\n # Ask the user for notes\n self.bot.send_message(self.chat.id, self.loc.get(\"ask_transaction_notes\"), reply_markup=cancel)\n # Wait for an answer\n reply = self.__wait_for_regex(r\"(.*)\", cancellable=True)\n # Allow the cancellation of the operation\n if isinstance(reply, CancelSignal):\n return\n # Create a new transaction\n transaction = db.Transaction(user=user,\n value=int(price),\n provider=\"Manual\",\n notes=reply)\n self.session.add(transaction)\n # Change the user credit\n user.recalculate_credit()\n # Commit the changes\n self.session.commit()\n # Notify the user of the credit/debit\n self.bot.send_message(user.user_id,\n self.loc.get(\"notification_transaction_created\",\n transaction=transaction.text(w=self)))\n # Notify the admin of the success\n self.bot.send_message(self.chat.id, self.loc.get(\"success_transaction_created\",\n transaction=transaction.text(w=self)))","def create_outgoing_transaction(transaction: OutgoingTransactionCreate, db: Session = Depends(get_db), auth_user: User=Depends(manager)):\n try:\n transaction = transaction_service.create(db, auth_user, transaction)\n return transaction\n except ItensNotFound as err:\n\t raise HTTPException(status_code=404, detail=f\"Os seguintes produtos não foram encontrados no sistema: {str(err)}\")\n except ProductsNotFound as err:\n raise HTTPException(status_code=400, detail=\"A movimentação a ser registrada deve conter no minimo um produto.\")\n except InvalidStockQuantity as err:\n products_missing = transaction_service.make_response(db, str(err))\n raise HTTPException(status_code=400, detail={\n \"message\": \"A quantidade informada para os seguintes produtos deve ser maior do que zero.\",\n \"products_missing\": products_missing\n })\n except NotEnoughStockQuantity as err:\n products_missing = transaction_service.make_response(db, str(err))\n raise HTTPException(status_code=422, detail={\n \"message\": \"Os produtos informados não possuem quantidade em estoque suficiente para a saída.\",\n \"products_missing\": products_missing\n })","def create_incoming_transaction(transaction: IncomingTransactionCreate, db: Session = Depends(get_db), auth_user: User=Depends(manager)):\n try:\n transaction = transaction_service.create(db, auth_user, transaction)\n return transaction\n except ItensNotFound as err:\n\t raise HTTPException(status_code=404, detail=f\"Os seguintes produtos não foram encontrados no sistema: {str(err)}\")\n except ProductsNotFound as err:\n raise HTTPException(status_code=400, detail=\"A movimentação a ser registrada deve conter no minimo um produto.\")\n except ProviderNotFound as err:\n\t raise HTTPException(status_code=404, detail=f\"O fornecedor informado não foi encontrado: {str(err)}\")\n except InvalidStockQuantity as err:\n products_missing = transaction_service.make_response(db, str(err))\n raise HTTPException(status_code=400, detail={\n \"message\": \"A quantidade informada para os seguintes produtos deve ser maior do que zero.\",\n \"products_missing\": products_missing\n })","def _generate_transaction(\n payment: Payment,\n kind: str,\n amount: Decimal,\n *,\n id='',\n is_success=True,\n **data) -> Transaction:\n transaction = create_transaction(\n payment=payment,\n kind=kind,\n amount=amount,\n currency=data.pop('currency', payment.currency),\n gateway_response=data,\n token=id,\n is_success=is_success)\n return transaction","def create_tx(\n self,\n query: str,\n query_params: Optional[Mapping[str, Any]] = None,\n ):\n tx = self.get_session().begin_transaction()\n try:\n # logger.info(query)\n tx.run(query, parameters=query_params)\n tx.commit()\n except Exception as e:\n logger.error(e)\n finally:\n tx.close()","def create_transaction(self, xml):\n logging.info(xml)\n seqnum = self.__post(\"import/return_seq=true\", xml).text\n logging.warn(\"Transaction created with id \" + seqnum)\n return seqnum","def create_tx(coin, account, recipient, amount):\n if coin ==ETH:\n gasEstimate = w3.eth.estimateGas(\n {\"from\": account.address, \"to\": recipient, \"value\": amount})\n return{\n \"to\": recipient,\n \"from\": account.address,\n \"value\": amount,\n \"gasPrice\": w3.eth.gasPrice,\n \"gas\": gasEstimate,\n \"nonce\": w3.eth.getTransactionCount(account.address)\n }\n if coin == BTCTEST:\n return PrivateKeyTestnet.prepare_transaction(account.address, [(recipient, amount, BTC)])","async def test_tx_metadata(self):\n data_hex = pkg_resources.resource_string(__name__, os.path.join('data', 'tx_metadata_01.txt'))\n data_bin = binascii.unhexlify(data_hex)\n reader = x.MemoryReaderWriter(bytearray(data_bin))\n ar = xmrb.Archive(reader, False, xmr.hf_versions(9))\n\n msg = xmr.PendingTransaction()\n await ar.root()\n await ar.message(msg)\n\n self.assertEqual(msg.tx_key,\n binascii.unhexlify(b'a0a50810dbc38101a79525823428b500ac936dfea613c73b4864f7260ff26a0b'))\n self.assertEqual(msg.change_dts.amount, 99972803971000)\n self.assertEqual(msg.fee, 9119110000)\n self.assertEqual(msg.construction_data.use_rct, 1)\n self.assertEqual(len(msg.construction_data.extra), 44)\n self.assertEqual(len(msg.construction_data.sources), 1)\n self.assertEqual(msg.construction_data.sources[0].amount, 100000000000000)\n self.assertEqual(msg.construction_data.sources[0].mask,\n binascii.unhexlify(b'2dea8778cf4e89a7f32b5659d674d44795a370a00f79ee9b2ea37c1fcb005c0d'))\n self.assertEqual(len(msg.construction_data.sources[0].outputs), 7)\n self.assertEqual(msg.construction_data.sources[0].outputs[6][0], 1727)\n self.assertEqual(msg.construction_data.sources[0].outputs[6][1].mask,\n binascii.unhexlify(b'2eeec82a970bfa54c35b0b740f6fb0585de14818e3c6dceed75c76fe69e3e449'))\n\n self.assertEqual(len(msg.construction_data.dests), 1)\n self.assertEqual(len(msg.construction_data.splitted_dsts), 2)\n self.assertEqual(msg.construction_data.splitted_dsts[0].amount, 18076919000)\n self.assertEqual(msg.construction_data.splitted_dsts[1].amount, 99972803971000)\n self.assertEqual(len(msg.construction_data.subaddr_indices), 1)\n\n writer = x.MemoryReaderWriter()\n ar2 = xmrb.Archive(writer, True, xmr.hf_versions(9))\n await ar2.root()\n await ar2.message(msg)\n self.assertEqual(data_bin, bytearray(writer.get_buffer()))\n\n msg.construction_data.use_bulletproofs = False\n writer = x.MemoryReaderWriter()\n ar2 = xmrb.Archive(writer, True, xmr.hf_versions(9))\n await ar2.root()\n await ar2.message(msg)","def tpc_begin(self, transaction):\n raise NotImplementedError","def create_transaction(self, currency_name, to_address, amount):\n callback = lambda transaction_status, signal_name='transaction_completed', currency_name=currency_name: \\\n self.get_signal_by_name(signal_name).emit(currency_name, transaction_status)\n\n def sender(currency_name):\n def wrapper(to_address, amount):\n try:\n self.get_currency_by_name(currency_name).send(to_address, float(amount))\n return 'Success'\n except:\n return 'Error'\n return wrapper\n\n async = async_func_with_callback(sender(currency_name), callback)\n async(to_address, amount)","def create(self, *args, **kwargs):\n\n if not args and not kwargs:\n raise Exception('attributes for AbsenceTransaction are missing')\n\n initial_attributes = args[0] if args else kwargs\n attributes = dict((k, v) for k, v in initial_attributes.items())\n attributes.update({'service': self.SERVICE})\n _, _, absence_transaction = self.http_client.post(\"/absencetransactions\", body=attributes)\n return absence_transaction","def _create_payment_transaction(self, amount, description):\n PaymentTransaction = Pool().get('payment_gateway.transaction')\n Date = Pool().get('ir.date')\n\n return PaymentTransaction(\n description=description or 'Auto charge from sale',\n date=Date.today(),\n party=self.sale.party,\n credit_account=self.credit_account,\n payment_profile=self.payment_profile,\n address=(\n self.payment_profile and\n self.payment_profile.address or self.sale.invoice_address\n ),\n amount=self.sale.currency.round(amount),\n currency=self.sale.currency,\n gateway=self.gateway,\n sale_payment=self.id,\n provider_reference=self.reference,\n )","def create_transaction(inputs: list, outputs: dict) -> ((str, int), str):\n\ttry:\n\t\tc = Bitcoin(testnet=bitcoin_is_testnet)\n\t\touts = []\n\t\tfor outk, outv in outputs.items():\n\t\t\touts += [{'value': outv, 'address': outk}]\n\t\ttx = c.mktx(inputs, outs)\n\t\ttx_serialize = serialize(tx)\n\n\t\t# Signing each input to predict the transaction size\n\t\tpriv = sha256('a big long brainwallet password')\n\t\ttx_signed = tx.copy()\n\t\tfor i in range(len(inputs)):\n\t\t\ttx_signed = c.sign(tx_signed, i, priv)\n\n\t\t# The serialization uses one char per nibble so in order the get the number of bytes it's necessary to\n\t\t# divide the size of the string serialization by 2\n\t\treturn (str(tx_serialize), len(str(serialize(tx_signed))) // 2), None\n\texcept Exception as e:\n\t\t# It should be logging using the default log\n\t\tprint(f\"There was a problem trying to create the transaction: {e}\")\n\t\treturn (None, None), \"There was a problem trying to create the transaction\"","def create_bank_transactions(*, block, message):\n bank_transactions = []\n\n sender = block.get('sender')\n\n encrypted_symmetric_key = None\n keys_to_add = []\n keys_to_delete = []\n for tx in message['txs']:\n json_data_for_db = None\n if 'json_data' in tx:\n json_data = tx.get('json_data')\n type = json_data.get('type')\n encryption_key = json_data.get('account', sender)\n\n if type not in [\"register_data\", \"append_data\", \"ask_for_access\", \"grant_access\", \"revoke_access\"]:\n continue\n\n node_private_key = get_signing_key()\n node_public_key = node_private_key.verify_key\n if type == \"register_data\" or type == \"grant_access\":\n keys_to_add.append({'accessor': encryption_key, 'patient_id': sender})\n # add the node as an accessor so it can manipulate the symmetric key\n keys_to_add.append({'accessor': node_public_key, 'patient_id': sender})\n elif type == \"revoke_access\":\n keys_to_delete.append({'accessor': encryption_key, 'patient_id': sender})\n # get all transactions that contain JSON data for the patient\n transactions = get_json_transactions(sender)\n new_transaction_data = {}\n for transaction in transactions:\n if transaction[\"json_data\"][\"type\"] in [\"register_data\", \"append_data\"]:\n decrypted_data = asymmetric_decrypt(transaction[\"json_data\"][\"data\"], node_private_key)\n new_transaction_data.update(decrypted_data)\n new_data_symmetric_result = symmetric_encrypt(json.dumps(new_transaction_data))\n\n new_transaction_json_data_for_db = {\n \"patient_id\": encryption_key,\n \"type\": type\n \"data\": new_data_symmetric_result,\n \"access\": encrypted_symmetric_key\n }\n\n new_data_transaction = BankTransaction(\n amount=0,\n block=block,\n fee=tx.get('fee', ''),\n memo=tx.get('memo', ''),\n json_data=new_transaction_json_data_for_db,\n recipient=tx['recipient']\n )\n bank_transactions.append(new_data_transaction)\n\n symmetric_result = symmetric_encrypt(json.dumps(json_data[\"data\"]))\n encrypted_symmetric_key = asymmetric_encrypt(symmetric_result['key'], encryption_key)\n\n json_data_for_db = {\n \"patient_id\": encryption_key,\n \"type\": type\n \"data\": symmetric_result['message'],\n \"access\": encrypted_symmetric_key\n }","def startTransaction(self) -> int:\n ...","def create_transactions_table(conn):\n sql_create_transactions_table = \"\"\" CREATE TABLE IF NOT EXISTS transactions (\n id integer PRIMARY KEY,\n date text,\n value float,\n currency text,\n desc text,\n categ text\n ); \"\"\"\n try:\n c = conn.cursor()\n c.execute(sql_create_transactions_table)\n except sqlite3.Error as e:\n print(e, file=sys.stderr)","def create():","def create():","def create_block_message(self, block):\n msg = poet_transaction_block.PoetTransactionBlockMessage()\n msg.TransactionBlock = block\n return msg","def create_block(self):\n return poet_transaction_block.PoetTransactionBlock()","def __create_blockchain_table(self):\n cmd = \"\"\" CREATE TABLE IF NOT EXISTS %s (\n %s integer PRIMARY KEY AUTOINCREMENT,\n %s text,\n %s integer,\n %s real,\n %s text,\n %s text);\"\"\" %(TABLE_BLOCKCHAIN,\n COL_BLOCKCHAIN_BLOCKID,\n COL_BLOCKCHAIN_BLOCK,\n COL_BLOCKCHAIN_TRANS_COUNT,\n COL_BLOCKCHAIN_AMOUNT,\n COL_BLOCKCHAIN_TIME,\n COL_BLOCKCHAIN_BLOCK_HASH)\n self.__dbcursor.execute(cmd)","def start_transaction(self,):\n\n if self.tx is not None:\n raise OverlappedTransaction(str(self.tx.xid))\n\n modlogger.debug(\"start tx\")\n opid = self.new_opid()\n xaction = StartTxOperation(opid,opid)\n self.tx = Transaction(opid,self.home, track_state = self.track_state)\n self._add_operation(opid,xaction)\n return opid","def create_transactions(self, revocation_address):\n self.tree.make_tree()\n\n spendables = self.connector.get_unspent_outputs(self.issuing_address)\n if not spendables:\n error_message = 'No money to spend at address {}'.format(self.issuing_address)\n logging.error(error_message)\n raise InsufficientFundsError(error_message)\n\n last_input = spendables[-1]\n\n op_return_value = unhexlify(self.tree.get_merkle_root())\n\n tx_outs = self.build_recipient_tx_outs()\n tx_outs.append(tx_utils.create_transaction_output(revocation_address,\n self.tx_cost_constants.get_minimum_output_coin()))\n\n transaction = tx_utils.create_trx(\n op_return_value,\n self.total,\n self.issuing_address,\n tx_outs,\n last_input)\n\n transaction_data = TransactionData(uid=self.batch_id,\n tx=transaction,\n tx_input=last_input,\n op_return_value=hexlify(op_return_value),\n batch_metadata=self.batch_metadata)\n\n return [transaction_data]","def create_transaction(\n self,\n transaction_id: str = None,\n account_id: str = None,\n charge_amount: ChargeAmount = None,\n is_credit: bool = None,\n reference: str = None,\n status: TransactionStatus = None,\n value_timestamp: datetime = None,\n booking_timestamp: datetime = None,\n payee_id: str = None,\n payment_order_id: str = None,\n posting_instruction_batch_ids: List[str] = None,\n rejection_code: TransactionRejectionCode = None,\n ) -> Transaction:\n\n transaction = {}\n\n if transaction_id is not None:\n transaction['id'] = transaction_id\n if account_id is not None:\n transaction['account_id'] = account_id\n if charge_amount is not None:\n transaction['charge_amount'] = charge_amount.get_dict()\n if is_credit is not None:\n transaction['is_credit'] = is_credit\n if reference is not None:\n transaction['reference'] = reference\n if status is not None:\n transaction['status'] = status.value\n if value_timestamp is not None:\n transaction['value_timestamp'] = datetime_to_str(value_timestamp)\n if booking_timestamp is not None:\n transaction['booking_timestamp'] = datetime_to_str(\n booking_timestamp\n )\n if payee_id is not None:\n transaction['payee_id'] = payee_id\n if payment_order_id is not None:\n transaction['payment_order_id'] = payment_order_id\n if posting_instruction_batch_ids is not None:\n transaction['posting_instruction_batch_ids'] = (\n posting_instruction_batch_ids\n )\n if rejection_code is not None:\n transaction['rejection_code'] = rejection_code.value\n\n post_response = self._rest_api_client.post(\"/v1/transactions\", {\n \"transaction\": transaction\n })\n return Transaction.from_json(post_response)","def start_transaction(self) -> None:\n pass","def createrawtransaction(\n self,\n outpoints: List[Dict[str, Any]],\n send_to: Dict[str, float],\n locktime: Optional[int] = None,\n ) -> str:\n assert type(outpoints) == list\n assert type(send_to) == dict\n assert locktime is None or type(locktime) == int\n return self.rpc_call(\"createrawtransaction\", outpoints, send_to, locktime)","async def new_tx(request: Request) -> dict:\n peer = request.client.host\n tx = await request.json()\n tx = Transaction(**tx)\n chain.mempool.put_nowait(tx)\n return {\"sender\": peer, \"receipt\": tx.receipt()}","def transaction(self, app_name=None,\n op=None,\n attrs=None,\n status_descr=None,\n status=None,\n req_bytes=None,\n resp_bytes=None,\n uS=None,\n initiator=None,\n target=None):\n\n log.debug(\"SFlowManager.transaction: %s.%s\", app_name, op)\n\n tsample = { 'flow_sample':{\n 'app_name': app_name,\n 'sampling_rate': self._trans_sample_rate,\n 'app_operation': {\n 'operation': op,\n 'attributes': \"&\".join([\"%s=%s\" % (k, v) for k, v in attrs.iteritems()]),\n 'status_descr': status_descr,\n 'status': status,\n 'req_bytes': req_bytes,\n 'resp_bytes': resp_bytes,\n 'uS': uS\n },\n 'app_initiator': {\n 'actor': initiator,\n },\n 'app_target': {\n 'actor': target,\n }\n }\n }\n\n self._publish(tsample)","def add_transaction(self, block, transaction):\n cmd = \"\"\"INSERT INTO %s(%s, %s, %s, %s, %s, %s)\n VALUES(?,?,?,?,?,?);\"\"\" %(TABLE_TRANSACTIONS,\n COL_TRANSACTION_BLOCK,\n COL_TRANSACTION_SENDER,\n COL_TRANSACTION_RECEIVER,\n COL_TRANSACTION_AMOUNT,\n COL_TRANSACTION_SUB_TIME,\n COL_TRANSACTION_VER_TIME)\n self.__dbcursor.execute(cmd, (block, transaction.sender,\n transaction.receiver,\n transaction.amount,\n transaction.submitted_time,\n transaction.verified_time))","def cypher_create():\n graph.cypher.execute(\"CREATE (a:Person {name:{N}})\", {\"N\": \"yangyy\"})","def createrawtransaction(inputs, outputs, outScriptGenerator=p2pkh):\n if not type(inputs) is list:\n inputs = [inputs]\n\n tx = CTransaction()\n for i in inputs:\n tx.vin.append(CTxIn(COutPoint(i[\"txid\"], i[\"vout\"]), b\"\", 0xffffffff))\n for addr, amount in outputs.items():\n if addr == \"data\":\n tx.vout.append(CTxOut(0, CScript([OP_RETURN, unhexlify(amount)])))\n else:\n tx.vout.append(CTxOut(amount * BTC, outScriptGenerator(addr)))\n tx.rehash()\n return hexlify(tx.serialize()).decode(\"utf-8\")","def create_raw_transaction(amount, network_fee, from_address, to_address):\n tx_total = amount + network_fee\n tx_inputs = []\n input_total = 0\n unspent = list_unspent(from_address)\n\n # Are there enough funds in one block to cover the amount\n for block in unspent:\n if float(block[\"amount\"]) >= tx_total:\n tx_input = {\"txid\": block[\"txid\"], \"vout\": int(block[\"vout\"])}\n input_total = float(block[\"amount\"])\n tx_inputs.append(tx_input)\n break\n # If tx_inputs is empty that means we have to\n # build the transaction from multiple blocks\n if not tx_inputs:\n for block in unspent:\n if input_total >= tx_total:\n break\n else:\n tx_input = {\"txid\": block[\"txid\"], \"vout\": int(block[\"vout\"])}\n input_total += float(block[\"amount\"])\n tx_inputs.append(tx_input)\n\n # Amount left over after amount to send and network fees are subtracted\n # from input_total. Change is sent back to sender\n change = round((input_total - amount) - network_fee, 8)\n \n if change < dust:\n tx_output = {to_address: amount}\n else:\n tx_output = {to_address: amount, from_address: change}\n \n try:\n tx_hex_string = subprocess.check_output([\"litecoin-cli\", \"createrawtransaction\", json.dumps(tx_inputs), json.dumps(tx_output)])\n except:\n sys.exit(1)\n\n return tx_hex_string.strip()","def create_acct_packet(self, **args):\n return host.Host.create_acct_packet(self, secret=self.secret, **args)","def create_metadata(self) -> _metadata_fb.CustomMetadataT:\n custom_metadata_field = _metadata_fb.CustomMetadataT()\n custom_metadata_field.name = self.name\n custom_metadata_field.data = b'\\x01\\x02'\n return custom_metadata_field","def create_transactions(self, new_transactions):\n if new_transactions is None or len(new_transactions) == 0:\n # TODO: Create proper exception for this\n raise pynab.exceptions.PynabError\n\n path = f\"{pynab.Pynab._base_url}/budgets/{self.budget_id}/transactions\"\n data = {\n \"transactions\": [\n new_transaction.__dict__ for new_transaction in new_transactions\n ]\n }\n print(data)\n response = self.session.post(path, json=data)\n return pynab.factory.PynabFactory.parse(response.json(), self.budget_id)","def create(self, **kwargs):\n return Create(self, metadata=kwargs)","def indirectedTransactionFactory(*a, **b):\n return self.store.newTransaction(*a, **b)","def add_transaction():\n index = blockchain.add_transaction(request.form['sender'], request.form['receiver'], request.form['amount'])\n response = {'message': \"Transaction will be added to Block #{0}\".format(index)}\n return jsonify(response), 200","def create_transaction(session, user_uri, amount, transaction_type, commit=True):\n # Check parameters\n if transaction_type not in TransactionType.all_values():\n raise ValueError(transaction_type + \" is not a proper TransactionType.\")\n\n if amount == 0:\n raise ValueError(\"If no money is moved, this is not a money transaction!\")\n\n # First we get the user id\n user_id = user_uri.split(\"/\")[-1]\n\n # Perform a security check\n if amount < 0:\n check_user_has_enough_money(session, user_id, amount)\n\n # Create the resource\n transaction = Transaction(user_phone=user_id, amount=amount, type=transaction_type)\n session.add(transaction)\n session.flush()\n transaction_id = transaction.id\n\n # Update user's funds\n update_user_funds(session, user_id, amount)\n\n # And go go go!\n if commit:\n session.commit()\n return TRANSACTION_GET_URI.format(transaction_id=transaction_id)","def post_transaction():\n tx_dict = encode_transaction(\"gautham=awesome\") \n print(tx_dict)\n\n tendermint_host = 'localhost'\n tendermint_port = 26657\n endpoint = 'http://{}:{}/'.format(tendermint_host, tendermint_port)\n\n payload = {\n 'method': 'broadcast_tx_commit',\n 'jsonrpc': '2.0',\n #'params': [encode_transaction(tx_dict)],\n 'params': [tx_dict],\n 'id': str(uuid4())\n }\n # TODO: handle connection errors!\n print(payload)\n return requests.post(endpoint, json=payload)","def BeginTransaction(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\n raise NotImplementedError()","def __create_initiate_transaction_request(payment_details):\n head = CommonUtil.get_secure_request_header(MerchantProperty.get_client_id(), payment_details.get_channel_id())\n body = payment_details._PaymentDetail__create_initiate_transaction_request_body()\n return InitiateTransactionRequest().set_head(head).set_body(body)","def start_transaction(self) -> \"Transaction\":\n response = super().start_transaction()\n self._set_transaction_id(response.id)\n return response","def create_account():\n account = w3.eth.account.create()\n return account","def create_god_transaction(to_pk):\n\n god_pk, god_sk = signature.generate_keys()\n tx = Transaction(god_pk, to_pk, SEED_COIN_SUPPLY)\n tx.sign(god_sk)\n return tx","def t1_create(**kwargs):\n sessiontoken = kwargs['sessiontoken']\n proxy = kwargs['proxy']\n t1_id = kwargs[\"tier1_id\"]\n t1_type = kwargs['tier1_type']\n json_data = {\n \"type\": t1_type\n }\n status = create_t1_json(proxy, sessiontoken, t1_id, json_data)\n if status == 200:\n print(f'Tier1 gateway {t1_id} has been configured as {t1_type}')\n else:\n print(\"T1 was not created. Please check your syntax and try again.\")\n sys.exit(1)","def create(ctx):\n pass","def database_transaction_to_rlp_transaction(transaction):\n\n nonce = transaction['nonce']\n value = parse_int(transaction['value'])\n gas = parse_int(transaction['gas'])\n gas_price = parse_int(transaction['gas_price'])\n\n tx = create_transaction(nonce=nonce, gasprice=gas_price, startgas=gas,\n to=transaction['to_address'], value=value,\n data=data_decoder(transaction['data']),\n v=parse_int(transaction['v']),\n r=parse_int(transaction['r']),\n s=parse_int(transaction['s']))\n\n return tx","def create_from_transaction(tx, prev_hash):\n\n tx_hash = HashAssist.hash_value(tx.to_string_for_hashing())\n\n print(\"Mining nonce....\")\n nonce = proof.mint(prev_hash + tx_hash, WORK_FACTOR)\n header_hash = HashAssist.hash_value(prev_hash + tx_hash + nonce)\n\n return Block(header_hash, prev_hash, nonce, tx_hash, tx)","def createTable(self):\n results = self.db.table_create(self.entity).run(self.r)\n time.sleep(5)\n return results","def create():\n\tcreate_db()","def create(self,):\n\n self.getConnection()\n\n #\n # Create tables\n #\n self.c.execute('''CREATE TABLE reads (id,header,sequence1,sequence2,quality1,quality2,barcodeSequence,clusterId,annotation,fromFastq,PRIMARY KEY (clusterId))''')\n self.c.execute('''CREATE TABLE runs (startTime,command,commandLine,finishedSuccessfully,masterPid)''')\n self.c.execute('''CREATE TABLE fastqs (filePairId,fastq1,fastq2,readCount,addedToReadsTable,minReadLength,PRIMARY KEY (filePairId))''')\n \n self.commitAndClose()","def add_transaction(self, bitfinex_id, bitfinex_currency, bitfinex_timestamp, bitfinex_price, bitfinex_amount):\n\n new_transaction = Transaction(bitfinex_id=bitfinex_id,\n bitfinex_currency=bitfinex_currency,\n bitfinex_timestamp=bitfinex_timestamp,\n bitfinex_price=bitfinex_price,\n bitfinex_amount=bitfinex_amount,\n languages=languages,\n skills=skills)\n\n self.session.add(new_transaction)\n self.session.commit()\n\n return new_transaction.id","def _setup_transactions(\n biz_org,\n biz_admin,\n transaction_currents_amount,\n transaction_price_reported,\n price_actual=None,\n pop_type='rec',\n offer_item_name=\"Test Item\",\n currents_share=40,\n action_type='req'\n):\n offer_item = Item(name=offer_item_name)\n offer_item.save()\n\n offer = Offer(\n org=biz_org,\n item=offer_item,\n currents_share=currents_share\n )\n offer.save()\n\n if price_actual is None:\n price_actual = transaction_price_reported\n\n transaction = Transaction(\n user=biz_admin,\n offer=offer,\n price_reported=transaction_price_reported,\n currents_amount=transaction_currents_amount,\n price_actual=price_actual\n )\n transaction.save()\n\n action = TransactionAction(\n transaction=transaction,\n action_type=action_type\n )\n action.save()","def createTransaction(self, sender, recipient, amount):\n transaction = Transaction(sender, recipient, amount)\n\n if transaction.validate():\n self.__currentTransactionsList.append(transaction)\n return transaction, True\n return None, False","def create_transaction(self, sender, recipient, amount):\n\n self.current_transactions.append({\n 'sender': sender,\n 'recipient': recipient,\n 'amount': amount,\n })\n return self.last_block['index'] + 1","def create(self, identity, data=None, record=None, **kwargs):\n record.metadata = data.get('metadata', {})","def transaction(self, context: InjectionContext = None) -> \"ProfileSession\":","def test_create(self):\n with self.assertRaises(QiitaDBNotImplementedError):\n MetadataTemplate.create()","def create_random_transaction() -> dict:\n cust_dtls = _get_cust_dtls()\n source_cust = _random_customer(cust_dtls)\n print(f\"Source Customer: {source_cust}\")\n print(f\"Source Customer Type: {type(source_cust)}\")\n rand_amt = _random_amount(int(source_cust[1]))\n print(f\"Random Amt: {type(rand_amt)}\")\n target_cust = _random_customer(cust_dtls)\n print(f\"Target Customer: {target_cust}\")\n rand_event = _random_event()\n print(f\"Event: {str(rand_event)}\")\n\n return {\n # 'activityTimestampUTC': datetime.utcnow().timestamp(),\n 'eventName': rand_event,\n 'sourceAcct': source_cust[0],\n 'targetAcct': target_cust[0],\n 'amount': rand_amt,\n 'customerSpendType': int(source_cust[1]),\n 'currency': 'USD'\n }","def Create(ctx,\n name,\n attributes = None):\n if ctx.element is None:\n ctx.logger.error(\"You must establish at least one connection and specify which you intend to use.\")\n exit()\n\n\n if(attributes is not None):\n kwargsDict = simplejson.loads(attributes)\n attributes = dict(**kwargsDict)\n\n ctx.logger.info(\"\"\"name = \"\"\"+str(name)+\"\"\";\"\"\"+\"\"\"attributes = \"\"\"+str(attributes)+\"\"\";\"\"\"+\"\")\n try:\n CreateBackupTargetResult = ctx.element.create_backup_target(name=name, attributes=attributes)\n except common.ApiServerError as e:\n ctx.logger.error(e.message)\n exit()\n except BaseException as e:\n ctx.logger.error(e.__str__())\n exit()\n\n cli_utils.print_result(CreateBackupTargetResult, ctx.logger, as_json=ctx.json, depth=ctx.depth, filter_tree=ctx.filter_tree)","def create_network(self, context, network):\n LOG.debug(_(\"NeutronRestProxyV2: create_network() called\"))\n\n self._warn_on_state_status(network['network'])\n\n with context.session.begin(subtransactions=True):\n # Validate args\n tenant_id = self._get_tenant_id_for_create(context,\n network[\"network\"])\n\n # create network in DB\n new_net = super(NeutronRestProxyV2, self).create_network(context,\n network)\n self._process_l3_create(context, new_net, network['network'])\n mapped_network = self._get_mapped_network_with_subnets(new_net,\n context)\n\n # create network on the network controller\n self.servers.rest_create_network(tenant_id, mapped_network)\n\n # return created network\n return new_net","def begin_transaction(self, request):\n return self._call_method('beginTransaction', request,\n datastore_v1_pb2.BeginTransactionResponse)","def transaction():\n data = jsonpickle.decode(request.get_data())\n address = data[\"address\"]\n amount = int(data[\"amount\"])\n keyname = data[\"keyname\"]\n\n pkplus, pkminus = wallet.keys(keyname)\n\n my_balance = p2p.query(\"/balance\", address=pkplus)[\"balance\"]\n if my_balance < amount:\n abort(404, description=\"Not enough funds.\")\n\n my_utxo = p2p.query(\"/find-utxos\", address=pkplus, amount=amount)[\"utxos\"]\n rem = sum(utxo.amount for utxo in my_utxo) - amount\n address_amount = [(address, amount)]\n\n assert rem >= 0\n\n if rem > 0:\n address_amount.append((pkplus, rem))\n\n tx = build_transaction(my_utxo, address_amount, pkminus)\n try:\n p2p.broadcast(\"/transaction-pool\", transaction=tx)\n return SUCCESSFUL_PATCH\n except UnsuccessfulPatch:\n payload = jsonpickle.encode(\n {\"message\": \"Transaction wasn't accepted by the network.\"})\n return payload, 420, {\"ContentType\": \"application/json\"}","def begin_create(self):\n self.mdb.get().begin_create()","def create():\n pass","def create_dataBase(conn, create_cmd):\n if conn:\n cursor = conn.cursor()\n cursor.execute(create_cmd)\n conn.commit()\n #print '[sql management] Table Created...'","def create_network_precommit(self, mech_context):\n\n LOG.debug(\"create_network_precommit: called\")\n network = mech_context.current\n context = mech_context._plugin_context\n tenant_id = network['tenant_id']\n network_id = network['id']\n\n segments = mech_context.network_segments\n # currently supports only one segment per network\n segment = segments[0]\n\n network_type = segment['network_type']\n vlan_id = segment['segmentation_id']\n segment_id = segment['id']\n\n if network_type != 'vlan':\n raise Exception(\n _(\"SeaMicro Mechanism: failed to create network, \"\n \"only network type vlan is supported\"))\n\n try:\n seamicro_db.create_network(context, network_id, vlan_id,\n segment_id, network_type, tenant_id)\n except Exception:\n LOG.exception(\n _LE(\"SeaMicro Mechanism: failed to create network in db\"))\n raise Exception(\n _(\"SeaMicro Mechanism: create_network_precommit failed\"))\n\n LOG.info(_LI(\"create network (precommit): %(network_id)s \"\n \"of network type = %(network_type)s \"\n \"with vlan = %(vlan_id)s \"\n \"for tenant %(tenant_id)s\"),\n {'network_id': network_id,\n 'network_type': network_type,\n 'vlan_id': vlan_id,\n 'tenant_id': tenant_id})","def indirectedTransactionFactory(*a):\n return self.store.newTransaction(*a)","def begin_transaction(self, project_id, transaction_options=None):\n request_pb = _datastore_pb2.BeginTransactionRequest()\n return _rpc(\n self.client._http,\n project_id,\n \"beginTransaction\",\n self.client._base_url,\n self.client._client_info,\n request_pb,\n _datastore_pb2.BeginTransactionResponse,\n )","def gen_init_txn(txn_id: int, obj_list: List[DBObject]) -> Transaction:\n ops: List[Operation] = [\n Operation(Operation.Type.SET_ISOLATION, isolation_level=\"serializable\"),\n Operation(Operation.Type.BEGIN),\n ]\n for obj in obj_list:\n ops.append(Operation(Operation.Type.WRITE, obj=obj, value=obj_ver[obj.id]))\n\n ops.append(Operation(Operation.Type.COMMIT))\n return Transaction(txn_id, ops)","def populate_transaction(\n self,\n label: dict,\n txid: int,\n read: str,\n write: str,\n transaction: list,\n action: str,\n ):\n method_that_access_table = transaction[\"stacktrace\"][-1]\n class_name_next = re.sub(\n \"/\", \".\", method_that_access_table[\"method\"].split(\", \")[1][1:]\n )\n method_name_next = (\n method_that_access_table[\"method\"].split(\", \")[2].split(\"(\")[0]\n )\n method_signature = \".\".join([class_name_next, method_name_next])\n\n the_sql_query = transaction[\"sql\"]\n\n for tx_read in read:\n if tx_read.casefold() in the_sql_query.casefold():\n self.populate_transaction_read(\n method_signature,\n txid,\n tx_read.casefold(),\n action,\n the_sql_query.casefold(),\n )\n for tx_write in write:\n if tx_write.casefold() in the_sql_query.casefold():\n self.populate_transaction_write(\n method_signature,\n txid,\n tx_write.casefold(),\n action,\n the_sql_query.casefold(),\n )","def mk_simple_transaction(self, from_addr, to_addr, send_value):\n transaction = dict(\n nonce=self.web3.eth.get_transaction_count(from_addr),\n gasPrice=self.web3.eth.gasPrice,\n # there must be an automated way to automatically set the gas price\n # based off of the gas strategy\n gas=100000,\n to=to_addr,\n value=self.web3.toWei(send_value, 'wei')\n )\n return transaction","def make_fake_transaction_data(date=None,\n transaction_type=None,\n transaction_type_raw=None,\n spent_currency=None,\n spent_amount=None,\n source_peer=None,\n acquired_currency=None,\n acquired_amount=None,\n target_peer=None,\n fee_currency=None,\n fee_amount=None,\n tags=None):\n # pylint: disable=E1101\n\n fake = Faker()\n transaction_data = schema.TransactionData()\n transaction_data.date = date or fake.date_time_between(\n start_date=\"-30y\", end_date=\"now\",\n tzinfo=None).strftime(\"%d.%m.%Y %H:%m:%S\")\n transaction_data.transaction_type = transaction_type or \"exchange\"\n transaction_data.transaction_type_raw = transaction_type_raw or \"Buy\"\n transaction_data.spent_currency = \\\n spent_currency or fake.cryptocurrency_code()\n transaction_data.spent_amount = spent_amount or random.uniform(1, 20)\n transaction_data.source_peer = source_peer or 1\n transaction_data.acquired_currency = \\\n acquired_currency or fake.cryptocurrency_code()\n transaction_data.acquired_amount = \\\n acquired_amount or random.uniform(0.001, 10)\n transaction_data.target_peer = target_peer or 1\n transaction_data.fee_currency = fee_currency or transaction_data.spent_currency\n transaction_data.fee_amount = fee_amount or random.uniform(0.000001, 0.001)\n transaction_data.tags = tags or [\"tag1\", \"tag2\"]\n return transaction_data","async def create_appservice_txn(\n self,\n service: ApplicationService,\n events: Sequence[EventBase],\n ephemeral: List[JsonDict],\n to_device_messages: List[JsonDict],\n one_time_keys_count: TransactionOneTimeKeysCount,\n unused_fallback_keys: TransactionUnusedFallbackKeys,\n device_list_summary: DeviceListUpdates,\n ) -> AppServiceTransaction:\n\n def _create_appservice_txn(txn: LoggingTransaction) -> AppServiceTransaction:\n new_txn_id = self._as_txn_seq_gen.get_next_id_txn(txn)\n\n # Insert new txn into txn table\n event_ids = json_encoder.encode([e.event_id for e in events])\n txn.execute(\n \"INSERT INTO application_services_txns(as_id, txn_id, event_ids) \"\n \"VALUES(?,?,?)\",\n (service.id, new_txn_id, event_ids),\n )\n return AppServiceTransaction(\n service=service,\n id=new_txn_id,\n events=events,\n ephemeral=ephemeral,\n to_device_messages=to_device_messages,\n one_time_keys_count=one_time_keys_count,\n unused_fallback_keys=unused_fallback_keys,\n device_list_summary=device_list_summary,\n )\n\n return await self.db_pool.runInteraction(\n \"create_appservice_txn\", _create_appservice_txn\n )","def create_table(cls, *args, **kwargs):\n init = cls._meta.database.create_table_title(cls._meta.table_name)\n i = 1\n fields = zip(cls._meta.sorted_fields_names, cls._meta.sorted_fields)\n for field in fields:\n field_string = field[1].create_field(field[0])\n if i == len(fields):\n if cls._meta.unique:\n init = cls._meta.database.create_unique(init, cls._meta.unique)\n\n init = cls._meta.database.create_table_field_end(init, field_string)\n\n if cls._meta.hypertable:\n init = cls._meta.database.create_hypertable(init,\n cls._meta)\n else:\n init = cls._meta.database.create_table_field(init, field_string)\n i+=1\n\n yield cls._meta.database.runOperation(init)","def save_transaction(**kwargs):\n if not 'user_id' in kwargs:\n raise AttributeError(\"Cannot create a transaction without user_id\")\n\n\n return History.create(\n user_id=kwargs['user_id'],\n from_curr=kwargs['currencyFrom'],\n to_curr=kwargs['currencyTo'],\n amount=kwargs['amountTo'],\n address_in=kwargs['payinAddress'],\n address_out=kwargs['payoutAddress'],\n extraid=kwargs['payinExtraId'],\n transaction_id=kwargs['id'],\n exchange_status=kwargs['status'],\n )","def test_create_mbta(self):\n \"\"\"cbc-mbta.xml\"\"\"\n time.sleep(SLEEP_TIME)\n eventFile = os.path.join(testdatadir, \"cbc-mbta.xml\")\n mbta_event = gracedb.createEvent(\n \"Test\", \"MBTAOnline\", eventFile).json()\n self.assertEqual(mbta_event['group'], \"Test\")\n self.assertEqual(mbta_event['pipeline'], \"MBTAOnline\")\n self.assertEqual(float(mbta_event['gpstime']), 1078903329.421037)\n self.assertEqual(mbta_event['far'], 4.006953918826065e-7)","def create_tables(args):\n\n from bob.db.base.utils import create_engine_try_nolock\n\n engine = create_engine_try_nolock(args.type, args.files[0], echo=(args.verbose >= 2));\n Client.metadata.create_all(engine)\n File.metadata.create_all(engine) \n Annotation.metadata.create_all(engine)\n #Protocol_File_Association.metadata.create_all(engine)","def transactionally(transactionCreator):\n def thunk(operation):\n return inTransaction(transactionCreator, operation)\n return thunk","def transactionally(transactionCreator):\n def thunk(operation):\n return inTransaction(transactionCreator, operation)\n return thunk","def create_t2c(fasta_path, t2c_path):\n fasta = FASTA(fasta_path)\n with open_as_text(t2c_path, 'w') as f:\n for info, _ in fasta.entries():\n sequence_id = info['sequence_id']\n f.write('{}\\n'.format(sequence_id))\n return {'t2c': t2c_path}","def create_package(self, **kwargs):\n results = self.api.action.package_create(**kwargs)\n self.get_ckan_metadata(True)\n return results","def _create_td(self):\n raise NotImplementedError","def transaction(self, *args, **kwargs):\n # Build database transaction class\n class DBTransaction(BaseTransaction, self.__class__):\n pass\n return DBTransaction(self, *args, **kwargs)","def transaction(self, uuid):\r\n return tx.Transaction(self, uuid)"],"string":"[\n \"def CreateTransaction(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\\n raise NotImplementedError()\",\n \"def CreateTransaction(self, request, context):\\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)\",\n \"def create_transaction(self, receiver, amount, comment=\\\"\\\"):\\n new_tx = Transaction.new(sender=self.pubkey, receiver=receiver,\\n amount=amount, privkey=self.privkey,\\n comment=comment)\\n tx_json = new_tx.to_json()\\n msg = \\\"t\\\" + json.dumps({\\\"tx_json\\\": tx_json})\\n self.add_transaction(tx_json)\\n self.broadcast_message(msg)\\n return new_tx\",\n \"def __create_transactions_table(self):\\n cmd = \\\"\\\"\\\" CREATE TABLE IF NOT EXISTS %s (\\n %s text,\\n %s text,\\n %s text,\\n %s real,\\n %s text,\\n %s text);\\\"\\\"\\\" %(TABLE_TRANSACTIONS,\\n COL_TRANSACTION_BLOCK,\\n COL_TRANSACTION_SENDER,\\n COL_TRANSACTION_RECEIVER,\\n COL_TRANSACTION_AMOUNT,\\n COL_TRANSACTION_SUB_TIME,\\n COL_TRANSACTION_VER_TIME)\\n self.__dbcursor.execute(cmd)\",\n \"def create_transaction():\\n data = request.get_json()\\n response = None\\n status_code = None\\n\\n # Proposed transaction document validity checks\\n if balance() < (data['amount']):\\n response = dict(message='Your balance is not enough to complete transaction')\\n status_code = 400\\n elif not (\\n any(node_['public_key'] == data['sender_address'] for node_ in node.network) and\\n any(node_['public_key'] == data['recipient_address'] for node_ in node.network) and\\n isinstance((data['amount']), (int, float))\\n ):\\n response = dict(message='Please make sure the proposed transaction is valid.')\\n status_code = 400\\n\\n if response and status_code:\\n return jsonify(response), status_code\\n\\n transaction_id = str(uuid4())\\n\\n # Use as many utxos as necessary to create the new transaction inputs\\n sender_address = data['sender_address']\\n sum_ = 0\\n tx_inputs = []\\n for utxo in node.blkchain.utxos[sender_address]:\\n if sum_ >= (data['amount']):\\n break\\n elif not node.blkchain.transaction_unconfirmed(utxo):\\n sum_ += utxo.amount\\n tx_inputs.append(TransactionInput.from_output(utxo))\\n\\n # Create 2 transaction outputs, one for the transfer and one for the sender's change\\n tx_outputs = [\\n TransactionOutput(\\n transaction_id=transaction_id,\\n recipient_address=data['recipient_address'],\\n amount=(data['amount'])\\n ),\\n TransactionOutput(\\n transaction_id=transaction_id,\\n recipient_address=data['sender_address'],\\n amount=sum_ - (data['amount'])\\n )\\n ]\\n\\n # Actual transaction object:\\n tx = Transaction(\\n sender_address=data['sender_address'],\\n recipient_address=data['recipient_address'],\\n amount=(data['amount']),\\n transaction_inputs=tx_inputs,\\n transaction_outputs=tx_outputs,\\n transaction_id=transaction_id\\n )\\n\\n response = tx.to_dict()\\n return jsonify(response), 200\",\n \"def create_transaction(conn, transaction):\\n sql = ''' INSERT INTO transactions(date, value, currency, desc, categ)\\n VALUES(?, ?, ?, ?, ?) '''\\n cur = conn.cursor()\\n cur.execute(sql, transaction)\",\n \"def CreateTx(self, request, context):\\n channel_name = request.channel or conf.LOOPCHAIN_DEFAULT_CHANNEL\\n utils.logger.info(f\\\"peer_outer_service::CreateTx request({request.data}), channel({channel_name})\\\")\\n\\n channel_stub = StubCollection().channel_stubs[channel_name]\\n result_hash = asyncio.run_coroutine_threadsafe(\\n channel_stub.async_task().create_tx(request.data),\\n self.peer_service.inner_service.loop\\n ).result()\\n\\n return loopchain_pb2.CreateTxReply(\\n response_code=message_code.Response.success,\\n tx_hash=result_hash,\\n more_info='')\",\n \"def createrawtransaction(self, inputs, outputs):\\n return self.proxy.createrawtransaction(inputs, outputs)\",\n \"def new_transaction():\\n\\n data = request.get_json()\\n\\n if not data:\\n return \\\"No transation data passed\\\", 400\\n\\n required = ['sender', 'recipient', 'amount']\\n\\n if not (list(data.keys()) == required):\\n return 'Missing Value', 400\\n \\n block_index = blockchain.add_transaction(data['sender'], data['recipient'], data['amount'])\\n response = {'message':f'Adding the transaction to block at index: {block_index}'}\\n\\n return jsonify(response), 201\",\n \"def tx_create(self,\\n keypair,\\n amount=1,\\n deposit=CONTRACT_DEFAULT_DEPOSIT,\\n init_state=\\\"()\\\",\\n gas=CONTRACT_DEFAULT_GAS,\\n gas_price=CONTRACT_DEFAULT_GAS_PRICE,\\n fee=DEFAULT_FEE,\\n vm_version=CONTRACT_DEFAULT_VM_VERSION,\\n tx_ttl=DEFAULT_TX_TTL):\\n try:\\n call_data = self.encode_calldata(\\\"init\\\", init_state)\\n\\n # get the transaction builder\\n txb = TxBuilder(self.client, keypair)\\n # create spend_tx\\n tx, sg, tx_hash, contract_id = txb.tx_contract_create(self.bytecode, call_data, amount, deposit, gas, gas_price, vm_version, fee, tx_ttl)\\n # post the transaction to the chain\\n txb.post_transaction(tx, tx_hash)\\n if self.client.blocking_mode:\\n txb.wait_tx(tx_hash)\\n # store the contract address in the instance variabl\\n self.address = contract_id\\n return tx\\n except OpenAPIClientException as e:\\n raise ContractError(e)\",\n \"def create_tx(self, coin, account, to, amount):\\n if coin is ETH:\\n gasEstimate = self.w3.eth.estimateGas(\\n {\\\"from\\\": account.address, \\\"to\\\": to, \\\"value\\\": amount}\\n )\\n return {\\n \\\"from\\\": account.address,\\n \\\"to\\\": to,\\n \\\"value\\\": self.w3.toWei(amount, 'ether'),\\n \\\"gasPrice\\\": self.w3.eth.gasPrice,\\n \\\"gas\\\": gasEstimate,\\n \\\"nonce\\\": self.w3.eth.getTransactionCount(account.address),\\n }\\n elif coin is BTCTEST:\\n return PrivateKeyTestnet.prepare_transaction(account.address, [(to, amount, BTC)])\\n elif coin is BTC:\\n return PrivateKey.prepare_transaction(account.address, [(to, amount, BTC)])\\n else:\\n return None\",\n \"def cypher_transaction():\\n session = cypher.Session(HOST)\\n return session.create_transaction()\",\n \"def createAccount_blockchain():\\n\\n logsOfError=''\\n try:\\n account = tron.create_account\\n except Exception as e:\\n logsOfError = logsOfError+str(e)\\n return {'publicKey':str(account.public_key), 'base58':str(account.address.base58), 'hex':str( account.address.hex), 'privateKey':str(account.private_key), 'logs':logsOfError, 'status':'success'}\",\n \"def __create_transaction(self):\\n log.debug(\\\"Displaying __create_transaction\\\")\\n # Make the admin select an user\\n user = self.__user_select()\\n # Allow the cancellation of the operation\\n if isinstance(user, CancelSignal):\\n return\\n # Create an inline keyboard with a single cancel button\\n cancel = telegram.InlineKeyboardMarkup([[telegram.InlineKeyboardButton(self.loc.get(\\\"menu_all_cancel\\\"),\\n callback_data=\\\"cmd_cancel\\\")]])\\n # Request from the user the amount of money to be credited manually\\n self.bot.send_message(self.chat.id, self.loc.get(\\\"ask_credit\\\"), reply_markup=cancel)\\n # Wait for an answer\\n reply = self.__wait_for_regex(r\\\"(-? ?[0-9]{1,3}(?:[.,][0-9]{1,2})?)\\\", cancellable=True)\\n # Allow the cancellation of the operation\\n if isinstance(reply, CancelSignal):\\n return\\n # Convert the reply to a price object\\n price = self.Price(reply)\\n # Ask the user for notes\\n self.bot.send_message(self.chat.id, self.loc.get(\\\"ask_transaction_notes\\\"), reply_markup=cancel)\\n # Wait for an answer\\n reply = self.__wait_for_regex(r\\\"(.*)\\\", cancellable=True)\\n # Allow the cancellation of the operation\\n if isinstance(reply, CancelSignal):\\n return\\n # Create a new transaction\\n transaction = db.Transaction(user=user,\\n value=int(price),\\n provider=\\\"Manual\\\",\\n notes=reply)\\n self.session.add(transaction)\\n # Change the user credit\\n user.recalculate_credit()\\n # Commit the changes\\n self.session.commit()\\n # Notify the user of the credit/debit\\n self.bot.send_message(user.user_id,\\n self.loc.get(\\\"notification_transaction_created\\\",\\n transaction=transaction.text(w=self)))\\n # Notify the admin of the success\\n self.bot.send_message(self.chat.id, self.loc.get(\\\"success_transaction_created\\\",\\n transaction=transaction.text(w=self)))\",\n \"def create_outgoing_transaction(transaction: OutgoingTransactionCreate, db: Session = Depends(get_db), auth_user: User=Depends(manager)):\\n try:\\n transaction = transaction_service.create(db, auth_user, transaction)\\n return transaction\\n except ItensNotFound as err:\\n\\t raise HTTPException(status_code=404, detail=f\\\"Os seguintes produtos não foram encontrados no sistema: {str(err)}\\\")\\n except ProductsNotFound as err:\\n raise HTTPException(status_code=400, detail=\\\"A movimentação a ser registrada deve conter no minimo um produto.\\\")\\n except InvalidStockQuantity as err:\\n products_missing = transaction_service.make_response(db, str(err))\\n raise HTTPException(status_code=400, detail={\\n \\\"message\\\": \\\"A quantidade informada para os seguintes produtos deve ser maior do que zero.\\\",\\n \\\"products_missing\\\": products_missing\\n })\\n except NotEnoughStockQuantity as err:\\n products_missing = transaction_service.make_response(db, str(err))\\n raise HTTPException(status_code=422, detail={\\n \\\"message\\\": \\\"Os produtos informados não possuem quantidade em estoque suficiente para a saída.\\\",\\n \\\"products_missing\\\": products_missing\\n })\",\n \"def create_incoming_transaction(transaction: IncomingTransactionCreate, db: Session = Depends(get_db), auth_user: User=Depends(manager)):\\n try:\\n transaction = transaction_service.create(db, auth_user, transaction)\\n return transaction\\n except ItensNotFound as err:\\n\\t raise HTTPException(status_code=404, detail=f\\\"Os seguintes produtos não foram encontrados no sistema: {str(err)}\\\")\\n except ProductsNotFound as err:\\n raise HTTPException(status_code=400, detail=\\\"A movimentação a ser registrada deve conter no minimo um produto.\\\")\\n except ProviderNotFound as err:\\n\\t raise HTTPException(status_code=404, detail=f\\\"O fornecedor informado não foi encontrado: {str(err)}\\\")\\n except InvalidStockQuantity as err:\\n products_missing = transaction_service.make_response(db, str(err))\\n raise HTTPException(status_code=400, detail={\\n \\\"message\\\": \\\"A quantidade informada para os seguintes produtos deve ser maior do que zero.\\\",\\n \\\"products_missing\\\": products_missing\\n })\",\n \"def _generate_transaction(\\n payment: Payment,\\n kind: str,\\n amount: Decimal,\\n *,\\n id='',\\n is_success=True,\\n **data) -> Transaction:\\n transaction = create_transaction(\\n payment=payment,\\n kind=kind,\\n amount=amount,\\n currency=data.pop('currency', payment.currency),\\n gateway_response=data,\\n token=id,\\n is_success=is_success)\\n return transaction\",\n \"def create_tx(\\n self,\\n query: str,\\n query_params: Optional[Mapping[str, Any]] = None,\\n ):\\n tx = self.get_session().begin_transaction()\\n try:\\n # logger.info(query)\\n tx.run(query, parameters=query_params)\\n tx.commit()\\n except Exception as e:\\n logger.error(e)\\n finally:\\n tx.close()\",\n \"def create_transaction(self, xml):\\n logging.info(xml)\\n seqnum = self.__post(\\\"import/return_seq=true\\\", xml).text\\n logging.warn(\\\"Transaction created with id \\\" + seqnum)\\n return seqnum\",\n \"def create_tx(coin, account, recipient, amount):\\n if coin ==ETH:\\n gasEstimate = w3.eth.estimateGas(\\n {\\\"from\\\": account.address, \\\"to\\\": recipient, \\\"value\\\": amount})\\n return{\\n \\\"to\\\": recipient,\\n \\\"from\\\": account.address,\\n \\\"value\\\": amount,\\n \\\"gasPrice\\\": w3.eth.gasPrice,\\n \\\"gas\\\": gasEstimate,\\n \\\"nonce\\\": w3.eth.getTransactionCount(account.address)\\n }\\n if coin == BTCTEST:\\n return PrivateKeyTestnet.prepare_transaction(account.address, [(recipient, amount, BTC)])\",\n \"async def test_tx_metadata(self):\\n data_hex = pkg_resources.resource_string(__name__, os.path.join('data', 'tx_metadata_01.txt'))\\n data_bin = binascii.unhexlify(data_hex)\\n reader = x.MemoryReaderWriter(bytearray(data_bin))\\n ar = xmrb.Archive(reader, False, xmr.hf_versions(9))\\n\\n msg = xmr.PendingTransaction()\\n await ar.root()\\n await ar.message(msg)\\n\\n self.assertEqual(msg.tx_key,\\n binascii.unhexlify(b'a0a50810dbc38101a79525823428b500ac936dfea613c73b4864f7260ff26a0b'))\\n self.assertEqual(msg.change_dts.amount, 99972803971000)\\n self.assertEqual(msg.fee, 9119110000)\\n self.assertEqual(msg.construction_data.use_rct, 1)\\n self.assertEqual(len(msg.construction_data.extra), 44)\\n self.assertEqual(len(msg.construction_data.sources), 1)\\n self.assertEqual(msg.construction_data.sources[0].amount, 100000000000000)\\n self.assertEqual(msg.construction_data.sources[0].mask,\\n binascii.unhexlify(b'2dea8778cf4e89a7f32b5659d674d44795a370a00f79ee9b2ea37c1fcb005c0d'))\\n self.assertEqual(len(msg.construction_data.sources[0].outputs), 7)\\n self.assertEqual(msg.construction_data.sources[0].outputs[6][0], 1727)\\n self.assertEqual(msg.construction_data.sources[0].outputs[6][1].mask,\\n binascii.unhexlify(b'2eeec82a970bfa54c35b0b740f6fb0585de14818e3c6dceed75c76fe69e3e449'))\\n\\n self.assertEqual(len(msg.construction_data.dests), 1)\\n self.assertEqual(len(msg.construction_data.splitted_dsts), 2)\\n self.assertEqual(msg.construction_data.splitted_dsts[0].amount, 18076919000)\\n self.assertEqual(msg.construction_data.splitted_dsts[1].amount, 99972803971000)\\n self.assertEqual(len(msg.construction_data.subaddr_indices), 1)\\n\\n writer = x.MemoryReaderWriter()\\n ar2 = xmrb.Archive(writer, True, xmr.hf_versions(9))\\n await ar2.root()\\n await ar2.message(msg)\\n self.assertEqual(data_bin, bytearray(writer.get_buffer()))\\n\\n msg.construction_data.use_bulletproofs = False\\n writer = x.MemoryReaderWriter()\\n ar2 = xmrb.Archive(writer, True, xmr.hf_versions(9))\\n await ar2.root()\\n await ar2.message(msg)\",\n \"def tpc_begin(self, transaction):\\n raise NotImplementedError\",\n \"def create_transaction(self, currency_name, to_address, amount):\\n callback = lambda transaction_status, signal_name='transaction_completed', currency_name=currency_name: \\\\\\n self.get_signal_by_name(signal_name).emit(currency_name, transaction_status)\\n\\n def sender(currency_name):\\n def wrapper(to_address, amount):\\n try:\\n self.get_currency_by_name(currency_name).send(to_address, float(amount))\\n return 'Success'\\n except:\\n return 'Error'\\n return wrapper\\n\\n async = async_func_with_callback(sender(currency_name), callback)\\n async(to_address, amount)\",\n \"def create(self, *args, **kwargs):\\n\\n if not args and not kwargs:\\n raise Exception('attributes for AbsenceTransaction are missing')\\n\\n initial_attributes = args[0] if args else kwargs\\n attributes = dict((k, v) for k, v in initial_attributes.items())\\n attributes.update({'service': self.SERVICE})\\n _, _, absence_transaction = self.http_client.post(\\\"/absencetransactions\\\", body=attributes)\\n return absence_transaction\",\n \"def _create_payment_transaction(self, amount, description):\\n PaymentTransaction = Pool().get('payment_gateway.transaction')\\n Date = Pool().get('ir.date')\\n\\n return PaymentTransaction(\\n description=description or 'Auto charge from sale',\\n date=Date.today(),\\n party=self.sale.party,\\n credit_account=self.credit_account,\\n payment_profile=self.payment_profile,\\n address=(\\n self.payment_profile and\\n self.payment_profile.address or self.sale.invoice_address\\n ),\\n amount=self.sale.currency.round(amount),\\n currency=self.sale.currency,\\n gateway=self.gateway,\\n sale_payment=self.id,\\n provider_reference=self.reference,\\n )\",\n \"def create_transaction(inputs: list, outputs: dict) -> ((str, int), str):\\n\\ttry:\\n\\t\\tc = Bitcoin(testnet=bitcoin_is_testnet)\\n\\t\\touts = []\\n\\t\\tfor outk, outv in outputs.items():\\n\\t\\t\\touts += [{'value': outv, 'address': outk}]\\n\\t\\ttx = c.mktx(inputs, outs)\\n\\t\\ttx_serialize = serialize(tx)\\n\\n\\t\\t# Signing each input to predict the transaction size\\n\\t\\tpriv = sha256('a big long brainwallet password')\\n\\t\\ttx_signed = tx.copy()\\n\\t\\tfor i in range(len(inputs)):\\n\\t\\t\\ttx_signed = c.sign(tx_signed, i, priv)\\n\\n\\t\\t# The serialization uses one char per nibble so in order the get the number of bytes it's necessary to\\n\\t\\t# divide the size of the string serialization by 2\\n\\t\\treturn (str(tx_serialize), len(str(serialize(tx_signed))) // 2), None\\n\\texcept Exception as e:\\n\\t\\t# It should be logging using the default log\\n\\t\\tprint(f\\\"There was a problem trying to create the transaction: {e}\\\")\\n\\t\\treturn (None, None), \\\"There was a problem trying to create the transaction\\\"\",\n \"def create_bank_transactions(*, block, message):\\n bank_transactions = []\\n\\n sender = block.get('sender')\\n\\n encrypted_symmetric_key = None\\n keys_to_add = []\\n keys_to_delete = []\\n for tx in message['txs']:\\n json_data_for_db = None\\n if 'json_data' in tx:\\n json_data = tx.get('json_data')\\n type = json_data.get('type')\\n encryption_key = json_data.get('account', sender)\\n\\n if type not in [\\\"register_data\\\", \\\"append_data\\\", \\\"ask_for_access\\\", \\\"grant_access\\\", \\\"revoke_access\\\"]:\\n continue\\n\\n node_private_key = get_signing_key()\\n node_public_key = node_private_key.verify_key\\n if type == \\\"register_data\\\" or type == \\\"grant_access\\\":\\n keys_to_add.append({'accessor': encryption_key, 'patient_id': sender})\\n # add the node as an accessor so it can manipulate the symmetric key\\n keys_to_add.append({'accessor': node_public_key, 'patient_id': sender})\\n elif type == \\\"revoke_access\\\":\\n keys_to_delete.append({'accessor': encryption_key, 'patient_id': sender})\\n # get all transactions that contain JSON data for the patient\\n transactions = get_json_transactions(sender)\\n new_transaction_data = {}\\n for transaction in transactions:\\n if transaction[\\\"json_data\\\"][\\\"type\\\"] in [\\\"register_data\\\", \\\"append_data\\\"]:\\n decrypted_data = asymmetric_decrypt(transaction[\\\"json_data\\\"][\\\"data\\\"], node_private_key)\\n new_transaction_data.update(decrypted_data)\\n new_data_symmetric_result = symmetric_encrypt(json.dumps(new_transaction_data))\\n\\n new_transaction_json_data_for_db = {\\n \\\"patient_id\\\": encryption_key,\\n \\\"type\\\": type\\n \\\"data\\\": new_data_symmetric_result,\\n \\\"access\\\": encrypted_symmetric_key\\n }\\n\\n new_data_transaction = BankTransaction(\\n amount=0,\\n block=block,\\n fee=tx.get('fee', ''),\\n memo=tx.get('memo', ''),\\n json_data=new_transaction_json_data_for_db,\\n recipient=tx['recipient']\\n )\\n bank_transactions.append(new_data_transaction)\\n\\n symmetric_result = symmetric_encrypt(json.dumps(json_data[\\\"data\\\"]))\\n encrypted_symmetric_key = asymmetric_encrypt(symmetric_result['key'], encryption_key)\\n\\n json_data_for_db = {\\n \\\"patient_id\\\": encryption_key,\\n \\\"type\\\": type\\n \\\"data\\\": symmetric_result['message'],\\n \\\"access\\\": encrypted_symmetric_key\\n }\",\n \"def startTransaction(self) -> int:\\n ...\",\n \"def create_transactions_table(conn):\\n sql_create_transactions_table = \\\"\\\"\\\" CREATE TABLE IF NOT EXISTS transactions (\\n id integer PRIMARY KEY,\\n date text,\\n value float,\\n currency text,\\n desc text,\\n categ text\\n ); \\\"\\\"\\\"\\n try:\\n c = conn.cursor()\\n c.execute(sql_create_transactions_table)\\n except sqlite3.Error as e:\\n print(e, file=sys.stderr)\",\n \"def create():\",\n \"def create():\",\n \"def create_block_message(self, block):\\n msg = poet_transaction_block.PoetTransactionBlockMessage()\\n msg.TransactionBlock = block\\n return msg\",\n \"def create_block(self):\\n return poet_transaction_block.PoetTransactionBlock()\",\n \"def __create_blockchain_table(self):\\n cmd = \\\"\\\"\\\" CREATE TABLE IF NOT EXISTS %s (\\n %s integer PRIMARY KEY AUTOINCREMENT,\\n %s text,\\n %s integer,\\n %s real,\\n %s text,\\n %s text);\\\"\\\"\\\" %(TABLE_BLOCKCHAIN,\\n COL_BLOCKCHAIN_BLOCKID,\\n COL_BLOCKCHAIN_BLOCK,\\n COL_BLOCKCHAIN_TRANS_COUNT,\\n COL_BLOCKCHAIN_AMOUNT,\\n COL_BLOCKCHAIN_TIME,\\n COL_BLOCKCHAIN_BLOCK_HASH)\\n self.__dbcursor.execute(cmd)\",\n \"def start_transaction(self,):\\n\\n if self.tx is not None:\\n raise OverlappedTransaction(str(self.tx.xid))\\n\\n modlogger.debug(\\\"start tx\\\")\\n opid = self.new_opid()\\n xaction = StartTxOperation(opid,opid)\\n self.tx = Transaction(opid,self.home, track_state = self.track_state)\\n self._add_operation(opid,xaction)\\n return opid\",\n \"def create_transactions(self, revocation_address):\\n self.tree.make_tree()\\n\\n spendables = self.connector.get_unspent_outputs(self.issuing_address)\\n if not spendables:\\n error_message = 'No money to spend at address {}'.format(self.issuing_address)\\n logging.error(error_message)\\n raise InsufficientFundsError(error_message)\\n\\n last_input = spendables[-1]\\n\\n op_return_value = unhexlify(self.tree.get_merkle_root())\\n\\n tx_outs = self.build_recipient_tx_outs()\\n tx_outs.append(tx_utils.create_transaction_output(revocation_address,\\n self.tx_cost_constants.get_minimum_output_coin()))\\n\\n transaction = tx_utils.create_trx(\\n op_return_value,\\n self.total,\\n self.issuing_address,\\n tx_outs,\\n last_input)\\n\\n transaction_data = TransactionData(uid=self.batch_id,\\n tx=transaction,\\n tx_input=last_input,\\n op_return_value=hexlify(op_return_value),\\n batch_metadata=self.batch_metadata)\\n\\n return [transaction_data]\",\n \"def create_transaction(\\n self,\\n transaction_id: str = None,\\n account_id: str = None,\\n charge_amount: ChargeAmount = None,\\n is_credit: bool = None,\\n reference: str = None,\\n status: TransactionStatus = None,\\n value_timestamp: datetime = None,\\n booking_timestamp: datetime = None,\\n payee_id: str = None,\\n payment_order_id: str = None,\\n posting_instruction_batch_ids: List[str] = None,\\n rejection_code: TransactionRejectionCode = None,\\n ) -> Transaction:\\n\\n transaction = {}\\n\\n if transaction_id is not None:\\n transaction['id'] = transaction_id\\n if account_id is not None:\\n transaction['account_id'] = account_id\\n if charge_amount is not None:\\n transaction['charge_amount'] = charge_amount.get_dict()\\n if is_credit is not None:\\n transaction['is_credit'] = is_credit\\n if reference is not None:\\n transaction['reference'] = reference\\n if status is not None:\\n transaction['status'] = status.value\\n if value_timestamp is not None:\\n transaction['value_timestamp'] = datetime_to_str(value_timestamp)\\n if booking_timestamp is not None:\\n transaction['booking_timestamp'] = datetime_to_str(\\n booking_timestamp\\n )\\n if payee_id is not None:\\n transaction['payee_id'] = payee_id\\n if payment_order_id is not None:\\n transaction['payment_order_id'] = payment_order_id\\n if posting_instruction_batch_ids is not None:\\n transaction['posting_instruction_batch_ids'] = (\\n posting_instruction_batch_ids\\n )\\n if rejection_code is not None:\\n transaction['rejection_code'] = rejection_code.value\\n\\n post_response = self._rest_api_client.post(\\\"/v1/transactions\\\", {\\n \\\"transaction\\\": transaction\\n })\\n return Transaction.from_json(post_response)\",\n \"def start_transaction(self) -> None:\\n pass\",\n \"def createrawtransaction(\\n self,\\n outpoints: List[Dict[str, Any]],\\n send_to: Dict[str, float],\\n locktime: Optional[int] = None,\\n ) -> str:\\n assert type(outpoints) == list\\n assert type(send_to) == dict\\n assert locktime is None or type(locktime) == int\\n return self.rpc_call(\\\"createrawtransaction\\\", outpoints, send_to, locktime)\",\n \"async def new_tx(request: Request) -> dict:\\n peer = request.client.host\\n tx = await request.json()\\n tx = Transaction(**tx)\\n chain.mempool.put_nowait(tx)\\n return {\\\"sender\\\": peer, \\\"receipt\\\": tx.receipt()}\",\n \"def transaction(self, app_name=None,\\n op=None,\\n attrs=None,\\n status_descr=None,\\n status=None,\\n req_bytes=None,\\n resp_bytes=None,\\n uS=None,\\n initiator=None,\\n target=None):\\n\\n log.debug(\\\"SFlowManager.transaction: %s.%s\\\", app_name, op)\\n\\n tsample = { 'flow_sample':{\\n 'app_name': app_name,\\n 'sampling_rate': self._trans_sample_rate,\\n 'app_operation': {\\n 'operation': op,\\n 'attributes': \\\"&\\\".join([\\\"%s=%s\\\" % (k, v) for k, v in attrs.iteritems()]),\\n 'status_descr': status_descr,\\n 'status': status,\\n 'req_bytes': req_bytes,\\n 'resp_bytes': resp_bytes,\\n 'uS': uS\\n },\\n 'app_initiator': {\\n 'actor': initiator,\\n },\\n 'app_target': {\\n 'actor': target,\\n }\\n }\\n }\\n\\n self._publish(tsample)\",\n \"def add_transaction(self, block, transaction):\\n cmd = \\\"\\\"\\\"INSERT INTO %s(%s, %s, %s, %s, %s, %s)\\n VALUES(?,?,?,?,?,?);\\\"\\\"\\\" %(TABLE_TRANSACTIONS,\\n COL_TRANSACTION_BLOCK,\\n COL_TRANSACTION_SENDER,\\n COL_TRANSACTION_RECEIVER,\\n COL_TRANSACTION_AMOUNT,\\n COL_TRANSACTION_SUB_TIME,\\n COL_TRANSACTION_VER_TIME)\\n self.__dbcursor.execute(cmd, (block, transaction.sender,\\n transaction.receiver,\\n transaction.amount,\\n transaction.submitted_time,\\n transaction.verified_time))\",\n \"def cypher_create():\\n graph.cypher.execute(\\\"CREATE (a:Person {name:{N}})\\\", {\\\"N\\\": \\\"yangyy\\\"})\",\n \"def createrawtransaction(inputs, outputs, outScriptGenerator=p2pkh):\\n if not type(inputs) is list:\\n inputs = [inputs]\\n\\n tx = CTransaction()\\n for i in inputs:\\n tx.vin.append(CTxIn(COutPoint(i[\\\"txid\\\"], i[\\\"vout\\\"]), b\\\"\\\", 0xffffffff))\\n for addr, amount in outputs.items():\\n if addr == \\\"data\\\":\\n tx.vout.append(CTxOut(0, CScript([OP_RETURN, unhexlify(amount)])))\\n else:\\n tx.vout.append(CTxOut(amount * BTC, outScriptGenerator(addr)))\\n tx.rehash()\\n return hexlify(tx.serialize()).decode(\\\"utf-8\\\")\",\n \"def create_raw_transaction(amount, network_fee, from_address, to_address):\\n tx_total = amount + network_fee\\n tx_inputs = []\\n input_total = 0\\n unspent = list_unspent(from_address)\\n\\n # Are there enough funds in one block to cover the amount\\n for block in unspent:\\n if float(block[\\\"amount\\\"]) >= tx_total:\\n tx_input = {\\\"txid\\\": block[\\\"txid\\\"], \\\"vout\\\": int(block[\\\"vout\\\"])}\\n input_total = float(block[\\\"amount\\\"])\\n tx_inputs.append(tx_input)\\n break\\n # If tx_inputs is empty that means we have to\\n # build the transaction from multiple blocks\\n if not tx_inputs:\\n for block in unspent:\\n if input_total >= tx_total:\\n break\\n else:\\n tx_input = {\\\"txid\\\": block[\\\"txid\\\"], \\\"vout\\\": int(block[\\\"vout\\\"])}\\n input_total += float(block[\\\"amount\\\"])\\n tx_inputs.append(tx_input)\\n\\n # Amount left over after amount to send and network fees are subtracted\\n # from input_total. Change is sent back to sender\\n change = round((input_total - amount) - network_fee, 8)\\n \\n if change < dust:\\n tx_output = {to_address: amount}\\n else:\\n tx_output = {to_address: amount, from_address: change}\\n \\n try:\\n tx_hex_string = subprocess.check_output([\\\"litecoin-cli\\\", \\\"createrawtransaction\\\", json.dumps(tx_inputs), json.dumps(tx_output)])\\n except:\\n sys.exit(1)\\n\\n return tx_hex_string.strip()\",\n \"def create_acct_packet(self, **args):\\n return host.Host.create_acct_packet(self, secret=self.secret, **args)\",\n \"def create_metadata(self) -> _metadata_fb.CustomMetadataT:\\n custom_metadata_field = _metadata_fb.CustomMetadataT()\\n custom_metadata_field.name = self.name\\n custom_metadata_field.data = b'\\\\x01\\\\x02'\\n return custom_metadata_field\",\n \"def create_transactions(self, new_transactions):\\n if new_transactions is None or len(new_transactions) == 0:\\n # TODO: Create proper exception for this\\n raise pynab.exceptions.PynabError\\n\\n path = f\\\"{pynab.Pynab._base_url}/budgets/{self.budget_id}/transactions\\\"\\n data = {\\n \\\"transactions\\\": [\\n new_transaction.__dict__ for new_transaction in new_transactions\\n ]\\n }\\n print(data)\\n response = self.session.post(path, json=data)\\n return pynab.factory.PynabFactory.parse(response.json(), self.budget_id)\",\n \"def create(self, **kwargs):\\n return Create(self, metadata=kwargs)\",\n \"def indirectedTransactionFactory(*a, **b):\\n return self.store.newTransaction(*a, **b)\",\n \"def add_transaction():\\n index = blockchain.add_transaction(request.form['sender'], request.form['receiver'], request.form['amount'])\\n response = {'message': \\\"Transaction will be added to Block #{0}\\\".format(index)}\\n return jsonify(response), 200\",\n \"def create_transaction(session, user_uri, amount, transaction_type, commit=True):\\n # Check parameters\\n if transaction_type not in TransactionType.all_values():\\n raise ValueError(transaction_type + \\\" is not a proper TransactionType.\\\")\\n\\n if amount == 0:\\n raise ValueError(\\\"If no money is moved, this is not a money transaction!\\\")\\n\\n # First we get the user id\\n user_id = user_uri.split(\\\"/\\\")[-1]\\n\\n # Perform a security check\\n if amount < 0:\\n check_user_has_enough_money(session, user_id, amount)\\n\\n # Create the resource\\n transaction = Transaction(user_phone=user_id, amount=amount, type=transaction_type)\\n session.add(transaction)\\n session.flush()\\n transaction_id = transaction.id\\n\\n # Update user's funds\\n update_user_funds(session, user_id, amount)\\n\\n # And go go go!\\n if commit:\\n session.commit()\\n return TRANSACTION_GET_URI.format(transaction_id=transaction_id)\",\n \"def post_transaction():\\n tx_dict = encode_transaction(\\\"gautham=awesome\\\") \\n print(tx_dict)\\n\\n tendermint_host = 'localhost'\\n tendermint_port = 26657\\n endpoint = 'http://{}:{}/'.format(tendermint_host, tendermint_port)\\n\\n payload = {\\n 'method': 'broadcast_tx_commit',\\n 'jsonrpc': '2.0',\\n #'params': [encode_transaction(tx_dict)],\\n 'params': [tx_dict],\\n 'id': str(uuid4())\\n }\\n # TODO: handle connection errors!\\n print(payload)\\n return requests.post(endpoint, json=payload)\",\n \"def BeginTransaction(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\\n raise NotImplementedError()\",\n \"def __create_initiate_transaction_request(payment_details):\\n head = CommonUtil.get_secure_request_header(MerchantProperty.get_client_id(), payment_details.get_channel_id())\\n body = payment_details._PaymentDetail__create_initiate_transaction_request_body()\\n return InitiateTransactionRequest().set_head(head).set_body(body)\",\n \"def start_transaction(self) -> \\\"Transaction\\\":\\n response = super().start_transaction()\\n self._set_transaction_id(response.id)\\n return response\",\n \"def create_account():\\n account = w3.eth.account.create()\\n return account\",\n \"def create_god_transaction(to_pk):\\n\\n god_pk, god_sk = signature.generate_keys()\\n tx = Transaction(god_pk, to_pk, SEED_COIN_SUPPLY)\\n tx.sign(god_sk)\\n return tx\",\n \"def t1_create(**kwargs):\\n sessiontoken = kwargs['sessiontoken']\\n proxy = kwargs['proxy']\\n t1_id = kwargs[\\\"tier1_id\\\"]\\n t1_type = kwargs['tier1_type']\\n json_data = {\\n \\\"type\\\": t1_type\\n }\\n status = create_t1_json(proxy, sessiontoken, t1_id, json_data)\\n if status == 200:\\n print(f'Tier1 gateway {t1_id} has been configured as {t1_type}')\\n else:\\n print(\\\"T1 was not created. Please check your syntax and try again.\\\")\\n sys.exit(1)\",\n \"def create(ctx):\\n pass\",\n \"def database_transaction_to_rlp_transaction(transaction):\\n\\n nonce = transaction['nonce']\\n value = parse_int(transaction['value'])\\n gas = parse_int(transaction['gas'])\\n gas_price = parse_int(transaction['gas_price'])\\n\\n tx = create_transaction(nonce=nonce, gasprice=gas_price, startgas=gas,\\n to=transaction['to_address'], value=value,\\n data=data_decoder(transaction['data']),\\n v=parse_int(transaction['v']),\\n r=parse_int(transaction['r']),\\n s=parse_int(transaction['s']))\\n\\n return tx\",\n \"def create_from_transaction(tx, prev_hash):\\n\\n tx_hash = HashAssist.hash_value(tx.to_string_for_hashing())\\n\\n print(\\\"Mining nonce....\\\")\\n nonce = proof.mint(prev_hash + tx_hash, WORK_FACTOR)\\n header_hash = HashAssist.hash_value(prev_hash + tx_hash + nonce)\\n\\n return Block(header_hash, prev_hash, nonce, tx_hash, tx)\",\n \"def createTable(self):\\n results = self.db.table_create(self.entity).run(self.r)\\n time.sleep(5)\\n return results\",\n \"def create():\\n\\tcreate_db()\",\n \"def create(self,):\\n\\n self.getConnection()\\n\\n #\\n # Create tables\\n #\\n self.c.execute('''CREATE TABLE reads (id,header,sequence1,sequence2,quality1,quality2,barcodeSequence,clusterId,annotation,fromFastq,PRIMARY KEY (clusterId))''')\\n self.c.execute('''CREATE TABLE runs (startTime,command,commandLine,finishedSuccessfully,masterPid)''')\\n self.c.execute('''CREATE TABLE fastqs (filePairId,fastq1,fastq2,readCount,addedToReadsTable,minReadLength,PRIMARY KEY (filePairId))''')\\n \\n self.commitAndClose()\",\n \"def add_transaction(self, bitfinex_id, bitfinex_currency, bitfinex_timestamp, bitfinex_price, bitfinex_amount):\\n\\n new_transaction = Transaction(bitfinex_id=bitfinex_id,\\n bitfinex_currency=bitfinex_currency,\\n bitfinex_timestamp=bitfinex_timestamp,\\n bitfinex_price=bitfinex_price,\\n bitfinex_amount=bitfinex_amount,\\n languages=languages,\\n skills=skills)\\n\\n self.session.add(new_transaction)\\n self.session.commit()\\n\\n return new_transaction.id\",\n \"def _setup_transactions(\\n biz_org,\\n biz_admin,\\n transaction_currents_amount,\\n transaction_price_reported,\\n price_actual=None,\\n pop_type='rec',\\n offer_item_name=\\\"Test Item\\\",\\n currents_share=40,\\n action_type='req'\\n):\\n offer_item = Item(name=offer_item_name)\\n offer_item.save()\\n\\n offer = Offer(\\n org=biz_org,\\n item=offer_item,\\n currents_share=currents_share\\n )\\n offer.save()\\n\\n if price_actual is None:\\n price_actual = transaction_price_reported\\n\\n transaction = Transaction(\\n user=biz_admin,\\n offer=offer,\\n price_reported=transaction_price_reported,\\n currents_amount=transaction_currents_amount,\\n price_actual=price_actual\\n )\\n transaction.save()\\n\\n action = TransactionAction(\\n transaction=transaction,\\n action_type=action_type\\n )\\n action.save()\",\n \"def createTransaction(self, sender, recipient, amount):\\n transaction = Transaction(sender, recipient, amount)\\n\\n if transaction.validate():\\n self.__currentTransactionsList.append(transaction)\\n return transaction, True\\n return None, False\",\n \"def create_transaction(self, sender, recipient, amount):\\n\\n self.current_transactions.append({\\n 'sender': sender,\\n 'recipient': recipient,\\n 'amount': amount,\\n })\\n return self.last_block['index'] + 1\",\n \"def create(self, identity, data=None, record=None, **kwargs):\\n record.metadata = data.get('metadata', {})\",\n \"def transaction(self, context: InjectionContext = None) -> \\\"ProfileSession\\\":\",\n \"def test_create(self):\\n with self.assertRaises(QiitaDBNotImplementedError):\\n MetadataTemplate.create()\",\n \"def create_random_transaction() -> dict:\\n cust_dtls = _get_cust_dtls()\\n source_cust = _random_customer(cust_dtls)\\n print(f\\\"Source Customer: {source_cust}\\\")\\n print(f\\\"Source Customer Type: {type(source_cust)}\\\")\\n rand_amt = _random_amount(int(source_cust[1]))\\n print(f\\\"Random Amt: {type(rand_amt)}\\\")\\n target_cust = _random_customer(cust_dtls)\\n print(f\\\"Target Customer: {target_cust}\\\")\\n rand_event = _random_event()\\n print(f\\\"Event: {str(rand_event)}\\\")\\n\\n return {\\n # 'activityTimestampUTC': datetime.utcnow().timestamp(),\\n 'eventName': rand_event,\\n 'sourceAcct': source_cust[0],\\n 'targetAcct': target_cust[0],\\n 'amount': rand_amt,\\n 'customerSpendType': int(source_cust[1]),\\n 'currency': 'USD'\\n }\",\n \"def Create(ctx,\\n name,\\n attributes = None):\\n if ctx.element is None:\\n ctx.logger.error(\\\"You must establish at least one connection and specify which you intend to use.\\\")\\n exit()\\n\\n\\n if(attributes is not None):\\n kwargsDict = simplejson.loads(attributes)\\n attributes = dict(**kwargsDict)\\n\\n ctx.logger.info(\\\"\\\"\\\"name = \\\"\\\"\\\"+str(name)+\\\"\\\"\\\";\\\"\\\"\\\"+\\\"\\\"\\\"attributes = \\\"\\\"\\\"+str(attributes)+\\\"\\\"\\\";\\\"\\\"\\\"+\\\"\\\")\\n try:\\n CreateBackupTargetResult = ctx.element.create_backup_target(name=name, attributes=attributes)\\n except common.ApiServerError as e:\\n ctx.logger.error(e.message)\\n exit()\\n except BaseException as e:\\n ctx.logger.error(e.__str__())\\n exit()\\n\\n cli_utils.print_result(CreateBackupTargetResult, ctx.logger, as_json=ctx.json, depth=ctx.depth, filter_tree=ctx.filter_tree)\",\n \"def create_network(self, context, network):\\n LOG.debug(_(\\\"NeutronRestProxyV2: create_network() called\\\"))\\n\\n self._warn_on_state_status(network['network'])\\n\\n with context.session.begin(subtransactions=True):\\n # Validate args\\n tenant_id = self._get_tenant_id_for_create(context,\\n network[\\\"network\\\"])\\n\\n # create network in DB\\n new_net = super(NeutronRestProxyV2, self).create_network(context,\\n network)\\n self._process_l3_create(context, new_net, network['network'])\\n mapped_network = self._get_mapped_network_with_subnets(new_net,\\n context)\\n\\n # create network on the network controller\\n self.servers.rest_create_network(tenant_id, mapped_network)\\n\\n # return created network\\n return new_net\",\n \"def begin_transaction(self, request):\\n return self._call_method('beginTransaction', request,\\n datastore_v1_pb2.BeginTransactionResponse)\",\n \"def transaction():\\n data = jsonpickle.decode(request.get_data())\\n address = data[\\\"address\\\"]\\n amount = int(data[\\\"amount\\\"])\\n keyname = data[\\\"keyname\\\"]\\n\\n pkplus, pkminus = wallet.keys(keyname)\\n\\n my_balance = p2p.query(\\\"/balance\\\", address=pkplus)[\\\"balance\\\"]\\n if my_balance < amount:\\n abort(404, description=\\\"Not enough funds.\\\")\\n\\n my_utxo = p2p.query(\\\"/find-utxos\\\", address=pkplus, amount=amount)[\\\"utxos\\\"]\\n rem = sum(utxo.amount for utxo in my_utxo) - amount\\n address_amount = [(address, amount)]\\n\\n assert rem >= 0\\n\\n if rem > 0:\\n address_amount.append((pkplus, rem))\\n\\n tx = build_transaction(my_utxo, address_amount, pkminus)\\n try:\\n p2p.broadcast(\\\"/transaction-pool\\\", transaction=tx)\\n return SUCCESSFUL_PATCH\\n except UnsuccessfulPatch:\\n payload = jsonpickle.encode(\\n {\\\"message\\\": \\\"Transaction wasn't accepted by the network.\\\"})\\n return payload, 420, {\\\"ContentType\\\": \\\"application/json\\\"}\",\n \"def begin_create(self):\\n self.mdb.get().begin_create()\",\n \"def create():\\n pass\",\n \"def create_dataBase(conn, create_cmd):\\n if conn:\\n cursor = conn.cursor()\\n cursor.execute(create_cmd)\\n conn.commit()\\n #print '[sql management] Table Created...'\",\n \"def create_network_precommit(self, mech_context):\\n\\n LOG.debug(\\\"create_network_precommit: called\\\")\\n network = mech_context.current\\n context = mech_context._plugin_context\\n tenant_id = network['tenant_id']\\n network_id = network['id']\\n\\n segments = mech_context.network_segments\\n # currently supports only one segment per network\\n segment = segments[0]\\n\\n network_type = segment['network_type']\\n vlan_id = segment['segmentation_id']\\n segment_id = segment['id']\\n\\n if network_type != 'vlan':\\n raise Exception(\\n _(\\\"SeaMicro Mechanism: failed to create network, \\\"\\n \\\"only network type vlan is supported\\\"))\\n\\n try:\\n seamicro_db.create_network(context, network_id, vlan_id,\\n segment_id, network_type, tenant_id)\\n except Exception:\\n LOG.exception(\\n _LE(\\\"SeaMicro Mechanism: failed to create network in db\\\"))\\n raise Exception(\\n _(\\\"SeaMicro Mechanism: create_network_precommit failed\\\"))\\n\\n LOG.info(_LI(\\\"create network (precommit): %(network_id)s \\\"\\n \\\"of network type = %(network_type)s \\\"\\n \\\"with vlan = %(vlan_id)s \\\"\\n \\\"for tenant %(tenant_id)s\\\"),\\n {'network_id': network_id,\\n 'network_type': network_type,\\n 'vlan_id': vlan_id,\\n 'tenant_id': tenant_id})\",\n \"def indirectedTransactionFactory(*a):\\n return self.store.newTransaction(*a)\",\n \"def begin_transaction(self, project_id, transaction_options=None):\\n request_pb = _datastore_pb2.BeginTransactionRequest()\\n return _rpc(\\n self.client._http,\\n project_id,\\n \\\"beginTransaction\\\",\\n self.client._base_url,\\n self.client._client_info,\\n request_pb,\\n _datastore_pb2.BeginTransactionResponse,\\n )\",\n \"def gen_init_txn(txn_id: int, obj_list: List[DBObject]) -> Transaction:\\n ops: List[Operation] = [\\n Operation(Operation.Type.SET_ISOLATION, isolation_level=\\\"serializable\\\"),\\n Operation(Operation.Type.BEGIN),\\n ]\\n for obj in obj_list:\\n ops.append(Operation(Operation.Type.WRITE, obj=obj, value=obj_ver[obj.id]))\\n\\n ops.append(Operation(Operation.Type.COMMIT))\\n return Transaction(txn_id, ops)\",\n \"def populate_transaction(\\n self,\\n label: dict,\\n txid: int,\\n read: str,\\n write: str,\\n transaction: list,\\n action: str,\\n ):\\n method_that_access_table = transaction[\\\"stacktrace\\\"][-1]\\n class_name_next = re.sub(\\n \\\"/\\\", \\\".\\\", method_that_access_table[\\\"method\\\"].split(\\\", \\\")[1][1:]\\n )\\n method_name_next = (\\n method_that_access_table[\\\"method\\\"].split(\\\", \\\")[2].split(\\\"(\\\")[0]\\n )\\n method_signature = \\\".\\\".join([class_name_next, method_name_next])\\n\\n the_sql_query = transaction[\\\"sql\\\"]\\n\\n for tx_read in read:\\n if tx_read.casefold() in the_sql_query.casefold():\\n self.populate_transaction_read(\\n method_signature,\\n txid,\\n tx_read.casefold(),\\n action,\\n the_sql_query.casefold(),\\n )\\n for tx_write in write:\\n if tx_write.casefold() in the_sql_query.casefold():\\n self.populate_transaction_write(\\n method_signature,\\n txid,\\n tx_write.casefold(),\\n action,\\n the_sql_query.casefold(),\\n )\",\n \"def mk_simple_transaction(self, from_addr, to_addr, send_value):\\n transaction = dict(\\n nonce=self.web3.eth.get_transaction_count(from_addr),\\n gasPrice=self.web3.eth.gasPrice,\\n # there must be an automated way to automatically set the gas price\\n # based off of the gas strategy\\n gas=100000,\\n to=to_addr,\\n value=self.web3.toWei(send_value, 'wei')\\n )\\n return transaction\",\n \"def make_fake_transaction_data(date=None,\\n transaction_type=None,\\n transaction_type_raw=None,\\n spent_currency=None,\\n spent_amount=None,\\n source_peer=None,\\n acquired_currency=None,\\n acquired_amount=None,\\n target_peer=None,\\n fee_currency=None,\\n fee_amount=None,\\n tags=None):\\n # pylint: disable=E1101\\n\\n fake = Faker()\\n transaction_data = schema.TransactionData()\\n transaction_data.date = date or fake.date_time_between(\\n start_date=\\\"-30y\\\", end_date=\\\"now\\\",\\n tzinfo=None).strftime(\\\"%d.%m.%Y %H:%m:%S\\\")\\n transaction_data.transaction_type = transaction_type or \\\"exchange\\\"\\n transaction_data.transaction_type_raw = transaction_type_raw or \\\"Buy\\\"\\n transaction_data.spent_currency = \\\\\\n spent_currency or fake.cryptocurrency_code()\\n transaction_data.spent_amount = spent_amount or random.uniform(1, 20)\\n transaction_data.source_peer = source_peer or 1\\n transaction_data.acquired_currency = \\\\\\n acquired_currency or fake.cryptocurrency_code()\\n transaction_data.acquired_amount = \\\\\\n acquired_amount or random.uniform(0.001, 10)\\n transaction_data.target_peer = target_peer or 1\\n transaction_data.fee_currency = fee_currency or transaction_data.spent_currency\\n transaction_data.fee_amount = fee_amount or random.uniform(0.000001, 0.001)\\n transaction_data.tags = tags or [\\\"tag1\\\", \\\"tag2\\\"]\\n return transaction_data\",\n \"async def create_appservice_txn(\\n self,\\n service: ApplicationService,\\n events: Sequence[EventBase],\\n ephemeral: List[JsonDict],\\n to_device_messages: List[JsonDict],\\n one_time_keys_count: TransactionOneTimeKeysCount,\\n unused_fallback_keys: TransactionUnusedFallbackKeys,\\n device_list_summary: DeviceListUpdates,\\n ) -> AppServiceTransaction:\\n\\n def _create_appservice_txn(txn: LoggingTransaction) -> AppServiceTransaction:\\n new_txn_id = self._as_txn_seq_gen.get_next_id_txn(txn)\\n\\n # Insert new txn into txn table\\n event_ids = json_encoder.encode([e.event_id for e in events])\\n txn.execute(\\n \\\"INSERT INTO application_services_txns(as_id, txn_id, event_ids) \\\"\\n \\\"VALUES(?,?,?)\\\",\\n (service.id, new_txn_id, event_ids),\\n )\\n return AppServiceTransaction(\\n service=service,\\n id=new_txn_id,\\n events=events,\\n ephemeral=ephemeral,\\n to_device_messages=to_device_messages,\\n one_time_keys_count=one_time_keys_count,\\n unused_fallback_keys=unused_fallback_keys,\\n device_list_summary=device_list_summary,\\n )\\n\\n return await self.db_pool.runInteraction(\\n \\\"create_appservice_txn\\\", _create_appservice_txn\\n )\",\n \"def create_table(cls, *args, **kwargs):\\n init = cls._meta.database.create_table_title(cls._meta.table_name)\\n i = 1\\n fields = zip(cls._meta.sorted_fields_names, cls._meta.sorted_fields)\\n for field in fields:\\n field_string = field[1].create_field(field[0])\\n if i == len(fields):\\n if cls._meta.unique:\\n init = cls._meta.database.create_unique(init, cls._meta.unique)\\n\\n init = cls._meta.database.create_table_field_end(init, field_string)\\n\\n if cls._meta.hypertable:\\n init = cls._meta.database.create_hypertable(init,\\n cls._meta)\\n else:\\n init = cls._meta.database.create_table_field(init, field_string)\\n i+=1\\n\\n yield cls._meta.database.runOperation(init)\",\n \"def save_transaction(**kwargs):\\n if not 'user_id' in kwargs:\\n raise AttributeError(\\\"Cannot create a transaction without user_id\\\")\\n\\n\\n return History.create(\\n user_id=kwargs['user_id'],\\n from_curr=kwargs['currencyFrom'],\\n to_curr=kwargs['currencyTo'],\\n amount=kwargs['amountTo'],\\n address_in=kwargs['payinAddress'],\\n address_out=kwargs['payoutAddress'],\\n extraid=kwargs['payinExtraId'],\\n transaction_id=kwargs['id'],\\n exchange_status=kwargs['status'],\\n )\",\n \"def test_create_mbta(self):\\n \\\"\\\"\\\"cbc-mbta.xml\\\"\\\"\\\"\\n time.sleep(SLEEP_TIME)\\n eventFile = os.path.join(testdatadir, \\\"cbc-mbta.xml\\\")\\n mbta_event = gracedb.createEvent(\\n \\\"Test\\\", \\\"MBTAOnline\\\", eventFile).json()\\n self.assertEqual(mbta_event['group'], \\\"Test\\\")\\n self.assertEqual(mbta_event['pipeline'], \\\"MBTAOnline\\\")\\n self.assertEqual(float(mbta_event['gpstime']), 1078903329.421037)\\n self.assertEqual(mbta_event['far'], 4.006953918826065e-7)\",\n \"def create_tables(args):\\n\\n from bob.db.base.utils import create_engine_try_nolock\\n\\n engine = create_engine_try_nolock(args.type, args.files[0], echo=(args.verbose >= 2));\\n Client.metadata.create_all(engine)\\n File.metadata.create_all(engine) \\n Annotation.metadata.create_all(engine)\\n #Protocol_File_Association.metadata.create_all(engine)\",\n \"def transactionally(transactionCreator):\\n def thunk(operation):\\n return inTransaction(transactionCreator, operation)\\n return thunk\",\n \"def transactionally(transactionCreator):\\n def thunk(operation):\\n return inTransaction(transactionCreator, operation)\\n return thunk\",\n \"def create_t2c(fasta_path, t2c_path):\\n fasta = FASTA(fasta_path)\\n with open_as_text(t2c_path, 'w') as f:\\n for info, _ in fasta.entries():\\n sequence_id = info['sequence_id']\\n f.write('{}\\\\n'.format(sequence_id))\\n return {'t2c': t2c_path}\",\n \"def create_package(self, **kwargs):\\n results = self.api.action.package_create(**kwargs)\\n self.get_ckan_metadata(True)\\n return results\",\n \"def _create_td(self):\\n raise NotImplementedError\",\n \"def transaction(self, *args, **kwargs):\\n # Build database transaction class\\n class DBTransaction(BaseTransaction, self.__class__):\\n pass\\n return DBTransaction(self, *args, **kwargs)\",\n \"def transaction(self, uuid):\\r\\n return tx.Transaction(self, uuid)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7027417","0.65196544","0.64316773","0.62087923","0.60003686","0.59858954","0.58080804","0.57972205","0.5790327","0.57589394","0.5734144","0.5703672","0.5678347","0.5670476","0.5629838","0.56017053","0.55468065","0.55460596","0.5519897","0.5475936","0.5460465","0.543578","0.5399664","0.5393046","0.5379727","0.53723013","0.53435016","0.5292575","0.5287446","0.5287004","0.5287004","0.5283054","0.52645344","0.5240488","0.5223728","0.5217978","0.5207246","0.5201801","0.5188748","0.5161138","0.51462626","0.5144334","0.5142912","0.5058444","0.50483054","0.5039905","0.5034204","0.50217485","0.50121427","0.50065345","0.4984671","0.4982799","0.49755904","0.49705225","0.49677926","0.49663782","0.49661222","0.4965567","0.49619785","0.49612802","0.49492198","0.49402246","0.49383268","0.4937835","0.49354166","0.4933818","0.49311677","0.4923407","0.4922592","0.49206132","0.49198323","0.491939","0.49183685","0.49104682","0.48849005","0.4883122","0.48821098","0.48725513","0.48712158","0.4862252","0.48601094","0.48596814","0.48535714","0.4840235","0.483565","0.4830579","0.4830368","0.48239464","0.4805299","0.47975528","0.47961676","0.47928816","0.4788007","0.4788007","0.47856107","0.4785367","0.47820595","0.47739378","0.4773659"],"string":"[\n \"0.7027417\",\n \"0.65196544\",\n \"0.64316773\",\n \"0.62087923\",\n \"0.60003686\",\n \"0.59858954\",\n \"0.58080804\",\n \"0.57972205\",\n \"0.5790327\",\n \"0.57589394\",\n \"0.5734144\",\n \"0.5703672\",\n \"0.5678347\",\n \"0.5670476\",\n \"0.5629838\",\n \"0.56017053\",\n \"0.55468065\",\n \"0.55460596\",\n \"0.5519897\",\n \"0.5475936\",\n \"0.5460465\",\n \"0.543578\",\n \"0.5399664\",\n \"0.5393046\",\n \"0.5379727\",\n \"0.53723013\",\n \"0.53435016\",\n \"0.5292575\",\n \"0.5287446\",\n \"0.5287004\",\n \"0.5287004\",\n \"0.5283054\",\n \"0.52645344\",\n \"0.5240488\",\n \"0.5223728\",\n \"0.5217978\",\n \"0.5207246\",\n \"0.5201801\",\n \"0.5188748\",\n \"0.5161138\",\n \"0.51462626\",\n \"0.5144334\",\n \"0.5142912\",\n \"0.5058444\",\n \"0.50483054\",\n \"0.5039905\",\n \"0.5034204\",\n \"0.50217485\",\n \"0.50121427\",\n \"0.50065345\",\n \"0.4984671\",\n \"0.4982799\",\n \"0.49755904\",\n \"0.49705225\",\n \"0.49677926\",\n \"0.49663782\",\n \"0.49661222\",\n \"0.4965567\",\n \"0.49619785\",\n \"0.49612802\",\n \"0.49492198\",\n \"0.49402246\",\n \"0.49383268\",\n \"0.4937835\",\n \"0.49354166\",\n \"0.4933818\",\n \"0.49311677\",\n \"0.4923407\",\n \"0.4922592\",\n \"0.49206132\",\n \"0.49198323\",\n \"0.491939\",\n \"0.49183685\",\n \"0.49104682\",\n \"0.48849005\",\n \"0.4883122\",\n \"0.48821098\",\n \"0.48725513\",\n \"0.48712158\",\n \"0.4862252\",\n \"0.48601094\",\n \"0.48596814\",\n \"0.48535714\",\n \"0.4840235\",\n \"0.483565\",\n \"0.4830579\",\n \"0.4830368\",\n \"0.48239464\",\n \"0.4805299\",\n \"0.47975528\",\n \"0.47961676\",\n \"0.47928816\",\n \"0.4788007\",\n \"0.4788007\",\n \"0.47856107\",\n \"0.4785367\",\n \"0.47820595\",\n \"0.47739378\",\n \"0.4773659\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.62451214"},"document_rank":{"kind":"string","value":"3"}}},{"rowIdx":15590,"cells":{"query":{"kind":"string","value":"StartCommit initiates a commit for a 2pc transaction."},"document":{"kind":"string","value":"def StartCommit(self, request, context):\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\n context.set_details('Method not implemented!')\n raise NotImplementedError('Method not implemented!')"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def StartCommit(self, request, context):\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)","def StartCommit(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\n raise NotImplementedError()","def begin_commit(self, _stacklevel=1):\n if self.commit_phase:\n warnings.warn('the transaction already is on commit phase; '\n 'begin_commit() method seems called twice or more' +\n self.format_commit_stack(),\n category=TransactionWarning,\n stacklevel=1 + _stacklevel)\n return\n self.commit_phase = True\n if self.session.verbose_transaction_error:\n self.commit_stack = traceback.format_stack()\n self.session.client.multi()","def startTxn(self,msg=\"\"):\n\tif self.verbose and msg:\n\t message =\"Start transaction: \"+msg\n\t message+=\", commit flag=%s\"%self.commitFlag\n\t if self.dbType=='sqlite':\n\t message+=\", %s\"%self.db.isolation_level\n\t print message\n\t sys.__stdout__.flush()\n\tif self.dbType==\"mysql\":\n\t if self.commitFlag:\n\t self.updateDBAndLog(\"BEGIN\")\n\telif self.dbType==\"sqlite\":\n\t if not self.commitFlag:\n\t return\n\t if self.db.isolation_level:\n\t return\n\t counter=0\n\t query = \"BEGIN IMMEDIATE\"\n\t cu = self.db.cursor()\n\t while 1:\n\t if counter>10: break\n\t try:\n\t\t cu.execute(query)\n# self.cursor.execute(query)\n\t self.updateLog(query)\n\t break\n\t except:\n\t print \"Wait for BEGIN\"\n\t\t gen_util.printExcept()\n\t\t pass\n\t counter+=1\n\t cu.close()\n\t return","def svn_fs_begin_txn2(*args):\r\n return _fs.svn_fs_begin_txn2(*args)","def startTransaction(self) -> int:\n ...","def start_transaction(self) -> None:\n pass","def svn_fs_begin_txn(*args):\r\n return _fs.svn_fs_begin_txn(*args)","def tpc_begin(self, transaction):\n raise NotImplementedError","def start_transaction(self,):\n\n if self.tx is not None:\n raise OverlappedTransaction(str(self.tx.xid))\n\n modlogger.debug(\"start tx\")\n opid = self.new_opid()\n xaction = StartTxOperation(opid,opid)\n self.tx = Transaction(opid,self.home, track_state = self.track_state)\n self._add_operation(opid,xaction)\n return opid","def begin(self):\n if self.tx_id is None:\n self.tx_id = yield self.conn.query('*begin-tx*')\n yield self.conn.query('START TRANSACTION WITH CONSISTENT SNAPSHOT', tx_id=self.tx_id)","def begin(self):\n self._in_transaction = True\n self.execute(\"BEGIN\")","def begin(cls):\n db = cls.db\n db.b_commit = False","def commit(self) -> None:\n trans = self._transaction\n if trans is None:\n trans = self._autobegin_t()\n\n trans.commit(_to_root=True)","def begin(self):\n self._in_transaction = True","def cvmfsStart(reponame = None):\n if reponame == None:\n reponame = _getRepoName()\n\n rc = subprocess.call([\"cvmfs_server\", \"transaction\", reponame])\n if rc != 0:\n raise RuntimeError(\"Could not start CVMFS transaction\")","def __gitBisectStart(self):\n self.vcs.gitBisect(self.project.getProjectPath(), \"start\")","def begin(transactionId, *args):\n global _operationCount\n # noinspection PyUnresolvedReferences\n _log.info(\n # \"%s BEGIN %s\" % (transactionId.hex, \" \".join(util.encode2(a) for a in args))\n f\"{transactionId.hex} BEGIN {' '.join(impl.util.encode2(a) for a in args)}\"\n )\n _countLock.acquire()\n try:\n _operationCount += 1\n finally:\n _countLock.release()","def commit():\n query = {\"type\": \"commit\", \"cmd\": \"<commit></commit>\"}\n\n return _get_job_results(query)","def run_auto_commit(self):\n self.commit()\n if self.auto_commit_interval not in [None, 0]:\n Timer(self.auto_commit_interval, self.run_auto_commit).start()","def start_transaction(self):\n self._connection.execute_nonquery(\"sql\", \"START TRANSACTION\", True)","def start_transaction_sql(self):\n return \"BEGIN TRANSACTION\"","def run_autocommit(self, autocommit):\n # Create (or recreate) test table.\n table = 'test_autocommit'\n\n self.table_drop(table)\n\n self.table_create(table, 'col1 integer')\n\n # This code is meant to test autocommit mode, so can't assume one\n # way or the other and postgres requires that DDL activity be commited\n # before other connections can set it, so commit the current transaction\n # just in case.\n\n self.commit()\n\n # Get a second connection to make a change independent of the main test\n # connection to determine whether changes made via the second\n # connection can be seen from the main test connection.\n\n dbh2 = despydb.DesDbi(section=self.which_services_section())\n\n # Set the second connection's autocommit mode as instructed.\n\n if autocommit is not None:\n dbh2.autocommit(autocommit)\n\n try:\n # Insert a row without an explicit commit and try to access it\n # from the main connection. Record the result to return to\n # caller.\n\n cursor2 = dbh2.cursor()\n\n stmt = ('INSERT INTO %s (col1) VALUES (%s)' %\n (table, self.get_positional_bind_string()))\n cursor2.execute(stmt, (4, ))\n\n try:\n cursor1 = self.cursor()\n cursor1.execute('SELECT col1 FROM %s' % table)\n res = cursor1.fetchone()\n except Exception:\n self.rollback()\n raise\n finally:\n cursor1.close()\n except Exception:\n dbh2.rollback()\n raise\n finally:\n cursor2.close()\n dbh2.close()\n self.table_drop(table)\n self.commit()\n\n return res","def prepare_for_commit(self):","def test_commit(self):\n # TODO: Test errors while committing and recovery\n pass","def commit_transaction(self,xid):\n modlogger.debug( \"end tx:%s\"%xid)\n if xid != self.tx.xid:\n raise InvalidTransaction(xid)\n\n opid = self.new_opid()\n xaction = EndTxOperation(opid,xid)\n self._add_operation(xid,xaction)\n try:\n self.tx.commit()\n except Exception:\n self.tx = None\n #There is an arguement to call abort here...\n # but we don't because our (MysteryMachine) use\n # of this is a bottom layer store, which means the\n # schema should have already ensured the transactions\n # are meaningful and a exceptio here is probably a\n # due to local conditions (like diskspace).\n #\n # If we abort we would have to remove the commit record\n # from the log, and then undo the partial tranasction.\n # by not aborting, and re-raisig we make this the \n # problem of a higher layer. Once the problem is resolved\n # the journal can be replayied making ourselve consistent\n # again.\n #\n # There is one way though of provoking non-recoverable behavour\n # ad that is creating a file in a non-existant dir.\n \n #self.abort_transaction(xid)\n raise\n\n self.tx = None","def start_commit(self, revnum):\n\n assert revnum > self._youngest\n self._youngest = revnum\n\n # A map {node_id : _WritableMirrorDirectoryMixin}.\n self._new_nodes = {}","def commit_transaction(self) -> None:\n pass","def start_transaction(self):\n self._db.autocommit = False","def commit(self) -> None:\n self._connector.commit_transaction()","def start_transaction_sql(self):\n return 'START TRANSACTION;'","def BeginTransaction(self, request, context):\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)","def svn_fs_commit_txn(*args):\r\n return _fs.svn_fs_commit_txn(*args)","def commit(self, _context: 'IconScoreContext', precommit_data: 'PrecommitData'):\n # Updated every block\n self.preps = precommit_data.preps\n\n # Exchange a term instance for some reasons:\n # - penalty for elected P-Reps(main, sub)\n # - A new term is started\n if precommit_data.term is not None:\n self.term: 'Term' = precommit_data.term\n\n self.prep_address_converter: 'PRepAddressConverter' = precommit_data.prep_address_converter","def commit(self):\n self.cnx.commit()","def update_port_precommit(self, mech_context):\n LOG.debug(\"update_port_precommit(self: called\")","def test_autocommit_on(self):\n res = self.dbh.run_autocommit(True)\n self.assertIsNotNone(res)\n self.assertEqual(res[0], 4)","def begin_transaction(self, request):\n return self._call_method('beginTransaction', request,\n datastore_v1_pb2.BeginTransactionResponse)","def set_autocommit(self, conn: jaydebeapi.Connection, autocommit: bool) -> None:\n conn.jconn.setAutoCommit(autocommit)","def start_transaction(self):\n raise Unsupported()","def _Dynamic_BeginTransaction(self, request, transaction, request_id=None):\n request.set_app(self.project_id)\n self._RemoteSend(request, transaction, \"BeginTransaction\", request_id)\n self.__tx_actions[transaction.handle()] = []\n return transaction","def setCommitFlag(self,flag=1):\n self.commitFlag=flag","def commit(self) -> None:\n pass","def commit(self, snapshot):\n _, checkpoint_id = snapshot\n self.chaindb.commit(checkpoint_id)","def BeginTransaction(self, request, global_params=None):\n config = self.GetMethodConfig('BeginTransaction')\n return self._RunMethod(\n config, request, global_params=global_params)","def commitChanges(self):\n \n ## User is prompted that changes are being committed\n print(\"Committing changes to the CRM and Mailings database...\")\n db_connection.executeQuery(\"COMMIT;\")","def commit(self):\n if self.transaction:\n self.conn.commit()\n self.transaction = False","def end(self, commit: bool) -> None:\n ...","def commit(self) -> None:\n with self.lock:\n self.wait(self._commit_gen())","def _do_commit(self):\n self.backend.commit()","def svn_client_commit2(svn_client_commit_info_t_commit_info_p, apr_array_header_t_targets, svn_boolean_t_recurse, svn_boolean_t_keep_locks, svn_client_ctx_t_ctx, apr_pool_t_pool): # real signature unknown; restored from __doc__\n pass","def commit(self, block: 'Block') -> None:\n # Check for block validation before commit\n self._precommit_data_manager.validate_precommit_block(block)\n\n context = self._context_factory.create(IconScoreContextType.DIRECT)\n\n precommit_data: 'PrecommitData' = \\\n self._precommit_data_manager.get(block.hash)\n block_batch = precommit_data.block_batch\n new_icon_score_mapper = precommit_data.score_mapper\n if new_icon_score_mapper:\n self._icon_score_mapper.update(new_icon_score_mapper)\n\n self._icx_context_db.write_batch(\n context=context, states=block_batch)\n\n self._icx_storage.put_block_info(context, block_batch.block)\n self._precommit_data_manager.commit(block_batch.block)\n self._context_factory.destroy(context)","def commit(self):\n pass","def commit(self):\n pass","def commit(self):\n pass","def commit(self):\n pass","def commit(self):\n pass","def on_start(self):\n self.deposit(1000000)","def set_auto_commit(self, auto_commit):\n self.__aceQLHttpApi.set_auto_commit(auto_commit)","def commit(self):\n self.execute_sql(sql.commit)\n self.under_transaction = False","def commit( self ) :\n self.oracle_connection.commit()","def test_execute_begin_transaction_read_write(self):\n\n instruction = Instruction(\"Begin(T1)\")\n self.transaction_manager.execute(instruction)\n trans1 = self.transaction_manager.transactions[\"T1\"]\n self.assertEquals(len(self.transaction_manager.transactions), 1)\n self.assertEquals(trans1.identifier, \"T1\")\n self.assertEquals(trans1.transaction_type, TransactionType.READ_WRITE)\n self.assertEquals(trans1.start_time, 1)\n self.assertIsNone(trans1.end_time)\n self.assertEquals(trans1.state, TransactionState.RUNNING)","def begin_transaction(self):\r\n self.db.commit(False)","def test_commit(self):\n u = stellr.UpdateCommand(TEST_HTTP, commit=True)\n self.assertEqual(u.host, 'http://localhost:8983')\n self.assertEqual(u._handler, '/solr/update/json?wt=json&commit=true')\n\n u.add_commit()\n self.assertEqual(len(u._commands), 1)\n self.assertEqual(('commit', {}), u._commands[0])\n self.assertEqual(u.body, '{\"commit\": {}}')","def commit(self):\n self._connection.execute_nonquery(\"sql\", \"COMMIT\", True)","def test_autocommit_default(self):\n res = self.dbh.run_autocommit(None)\n self.assertIsNone(res)","def _do_commit(self):","def commit(self):\n\t\treturn Job(SDK.PrlVm_Commit(self.handle)[0])","def commitPrivateBefore(self):\n\n self._log(\"commit-private-before\").debug4(\"%s: interface commitPrivateBefore was called\", self.name)\n\n if self.allowDynamicConfig:\n if self.isTrxStart is True:\n\n adminStateChange = (self.candidateEnabled != self.runningEnabled)\n\n # rename device and change state up/down\n # Note: must be before addRule() is called\n #timeoutGuard = TimeoutGuard(self._log, '%s-commit-name-and-state' % (self.name), Interface.MAX_TIMEOUT_MILI_SEC) \n self.commitNameAndState()\n #timeoutGuard.checkAndLog(self.commitNameAndState)\n \n # ip address, route and rule\n self.commitDynamicCfg(adminStateChange)\n\n self.updateCfgCache()\n\n if self.isFirstTrx is True:\n\n shouldClearCounters= self._isCountersClearPostUp() is False and self._isCountersClearPostDown() is False\n if shouldClearCounters is True:\n # interface counters start as non-zeros\n # first transaction commit\n rc = self._doClearCounters()\n self.countersOnStart.copyDataFrom(self.countersOnClear) # copy counters snapshot\n \n if rc != ReturnCodes.kOk:\n self._log(\"interface-counters-on-start-fail\").error(\"%s: failed retrieve rx and tx counters on start\", \n self.name)\n self.isFirstTrx = False\n\n self.isTrxStart = False\n return ReturnCodes.kOk","def commit(self):\n return","def endTxn(self,msg=\"\"):\n\tif self.dbType==\"mysql\":\n\t if self.commitFlag:\n\t self.updateDBAndLog(\"COMMIT\")\n\telif self.dbType==\"sqlite\":\n\t if self.commitFlag:\n\t if self.db.isolation_level:\n\t\t return\n\t query=\"COMMIT\"\n\t counter=0\n\t cu = self.db.cursor()\n\t while 1:\n\t if counter>10: break\n\t\t try:\n self.db.commit() ## sdobbs, 4/19/14\n#\t\t cu.execute(query)\n# self.cursor.execute(query)\n self.updateLog(query)\n break\n\t except:\n\t\t print \"Wait for COMMIT\"\n\t\t gen_util.printExcept()\n\t\t pass\n\t counter+=1\n\t cu.close()\n\n# self.db.commit()\n# cu = self.db.cursor()\n# cu.execute(query)\n# cu.close()\n# self.db.commit()\n# self.updateLog(query)\n\t\n\tif self.verbose and msg:\n\t message = \" End transaction: \"+msg\n\t message+=\", commit flag=%s\"%self.commitFlag\n\t if self.dbType=='sqlite':\n\t message+=\", %s\"%self.db.isolation_level\n\t print message\n\t print\n\t sys.__stdout__.flush()","def setUp(self):\n self.instance = Commit('9b423f8c38516ed33acfa907ae56ad3868741803')","def begin_transaction(self, project_id, transaction_options=None):\n request_pb = _datastore_pb2.BeginTransactionRequest()\n return _rpc(\n self.client._http,\n project_id,\n \"beginTransaction\",\n self.client._base_url,\n self.client._client_info,\n request_pb,\n _datastore_pb2.BeginTransactionResponse,\n )","def commit(self):\n if self._transaction is None:\n raise TransactionNotStartedError(\"Cannot call commit without a transaction\")\n else:\n def _resetTxn(result):\n self._transaction = None\n d = self._config.commit(self._transaction)\n d.addCallback(_resetTxn)\n return d","def BeginTransaction(self, request, context):\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\n context.set_details('Method not implemented!')\n raise NotImplementedError('Method not implemented!')","def begin_transaction(self, event=None):\n assert not self._current_transaction\n self._current_transaction = ActionStack()","def create_subnet_precommit(self, mech_context):\n LOG.debug(\"create_subnetwork_precommit: called\")","def do_begin(begin):\n if begin:\n do_action(begin)","def commit_block(self, block):\n raise NotImplementedError('commit_block: Implementation of this method is required.')","def _auto_commit(self):\n\n # Check if we are supposed to do an auto-commit\n if not self.auto_commit or self.auto_commit_every_n is None:\n return\n\n if self.count_since_commit >= self.auto_commit_every_n:\n self.commit()","def commit(self):\n raise NotImplementedError","def end_commit(self):\n #scn = bpy.context.scene\n #for pt in self.b_pts:\n # point_obj = bpy.data.objects.new(pt.label, None)\n # point_obj.location = pt.location\n # scn.objects.link(point_obj)\n #self.end_commit_post()\n pass","def commit(self):\n self._pipeline.execute()\n self.current_chunk = 0","def handler_commit(event):\n if not LOG_DB:\n return\n\n # get the active transaction\n txn = transaction.get()\n\n # get needed values now as the request contents will\n # change after commit.\n request = event.request\n request_data = get_request_data(request)\n\n # transactions that will do a commit have a ZODB.Connection\n # object in ``_resources``. Since the transaction has an\n # open connection we know it will be committed.\n for conn in (c for c in txn._resources if isinstance(c, Connection)):\n # ZODB.Connection objects support callbacks on close.\n # In this case we wrap the callback in another function\n # so we can also pass in the event.\n conn.onCloseCallback(__after_conn_close(request_data))","def add_commit( self\n , cl\n , mark_number\n , parent_commit_list\n , first_branch_from_branch_id\n , first_branch_from_change_number\n , dest_branch\n , branch_name):\n with Timer(OVERALL):\n with Timer(BUILD):\n self.__append(NTR('commit refs/heads/{0}\\n').format(branch_name))\n self.__append(NTR('mark : {0}\\n').format(mark_number))\n desc_info = DescInfo.from_text(cl.description)\n committer_added = False\n if desc_info:\n for key in ('author', 'committer'):\n v = desc_info[key]\n if v:\n self.__append(NTR('{key} {fullname} {email} {time} {timezone}\\n').\n format( key = key\n , fullname = v['fullname']\n , email = v['email' ]\n , time = v['time' ]\n , timezone = v['timezone']))\n committer_added = True\n desc = desc_info.clean_desc\n\n # Convoluted logic gates but avoids duplicating code. The point\n # is that we add the best possible committer data _before_\n # adding the description.\n if not committer_added:\n if desc_info:\n # old change description that lacked detailed author info,\n # deserves a warning, but otherwise push onward even if the\n # commit checksums will likely differ from the originals\n LOG.warn('commit description did not match committer regex: @{} => {}'.\n format(cl.change, desc_info.suffix))\n timezone = self.__get_timezone_offset(cl.time)\n self.__append(NTR('committer {fullname} {email} {time} {timezone}\\n').\n format(fullname=self.__full_name_for_user(cl.user),\n email=self.__email_for_user(cl.user),\n time=cl.time,\n timezone=timezone))\n desc = cl.description\n self.__add_data(desc)\n\n self._add_commit_parent_list(parent_commit_list)\n if first_branch_from_branch_id \\\n and first_branch_from_change_number:\n self.__branch_from( dest_branch\n , cl\n , first_branch_from_branch_id\n , first_branch_from_change_number)\n self.__add_files(cl.files)\n if desc_info and desc_info.gitlinks:\n self.__add_gitlinks(desc_info.gitlinks)","def commit(self):\n datastore_pre_commit.send(session=self.db.session)\n super().commit()\n datastore_post_commit.send(session=self.db.session)","def enter_transaction():\n _state.transactions = get_transactions() + 1","def test_execute_begin_ro_transaction(self):\n\n instruction = Instruction(\"BeginRO(T1)\")\n self.transaction_manager.execute(instruction)\n trans1 = self.transaction_manager.transactions[\"T1\"]\n\n self.assertTrue(\"T1\" in self.transaction_manager.transactions)\n self.assertEquals(self.transaction_manager.transactions[\"T1\"].transaction_type, TransactionType.READ_ONLY)\n\n for site in self.transaction_manager.sites.values():\n for variable_identifier in site.data_manager.variables:\n self.assertTrue(variable_identifier in self.transaction_manager.readonly_snapshots[\"T1\"])\n \n self.assertEquals(trans1.identifier, \"T1\")\n self.assertEquals(trans1.transaction_type, TransactionType.READ_ONLY)\n self.assertEquals(trans1.start_time, 1)\n self.assertIsNone(trans1.end_time)\n self.assertEquals(trans1.state, TransactionState.RUNNING)","def commit(self, _context: 'IconScoreContext', precommit_data: 'PrecommitData'):\n # Updated every block\n self.preps = precommit_data.preps\n\n # Updated every term\n if precommit_data.term is not None:\n self.term: 'Term' = precommit_data.term","def update_network_precommit(self, mech_context):\n pass","def begin_create(self):\n self.mdb.get().begin_create()","def commit(self):\n # PEP 249\n pass","def start_workunit(self, workunit):\r\n pass","def start_workunit(self, workunit):\r\n pass","def conduit_committee_id(self, conduit_committee_id):\n\n self._conduit_committee_id = conduit_committee_id","def commit(self):\n\n if not self.is_active:\n return\n\n if self.is_context_active:\n raise states.Committed(self)\n else:\n self.__do_commit()\n self._cleanup()","def commit(self, msg=None):\n self.log.debug(\"committing in git: %s\" % msg)\n completemsg = \"EasyBuild-commit from %s (time: %s, user: %s) \\n%s\" % (socket.gethostname(),\n time.strftime(\"%Y-%m-%d_%H-%M-%S\"),\n getpass.getuser(),\n msg)\n self.log.debug(\"git status: %s\" % self.client.status())\n try:\n self.client.commit('-am \"%s\"' % completemsg)\n self.log.debug(\"succesfull commit\")\n except GitCommandError, err:\n self.log.warning(\"Commit from working copy %s (msg: %s) failed, empty commit?\\n%s\" % (self.wc, msg, err))\n try:\n info = self.client.push()\n self.log.debug(\"push info: %s \" % info)\n except GitCommandError, err:\n self.log.warning(\"Push from working copy %s to remote %s (msg: %s) failed: %s\" % (self.wc,\n self.repo,\n msg,\n err))","def start(self):\n assert not self.state is CallState.finished\n\n self.state = CallState.started\n self.start_time = time()","def commit(self):\n conn = self.threadingLocal.connection\n if isinstance(conn, Transaction):\n self.threadingLocal.connection.commit()"],"string":"[\n \"def StartCommit(self, request, context):\\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)\",\n \"def StartCommit(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\\n raise NotImplementedError()\",\n \"def begin_commit(self, _stacklevel=1):\\n if self.commit_phase:\\n warnings.warn('the transaction already is on commit phase; '\\n 'begin_commit() method seems called twice or more' +\\n self.format_commit_stack(),\\n category=TransactionWarning,\\n stacklevel=1 + _stacklevel)\\n return\\n self.commit_phase = True\\n if self.session.verbose_transaction_error:\\n self.commit_stack = traceback.format_stack()\\n self.session.client.multi()\",\n \"def startTxn(self,msg=\\\"\\\"):\\n\\tif self.verbose and msg:\\n\\t message =\\\"Start transaction: \\\"+msg\\n\\t message+=\\\", commit flag=%s\\\"%self.commitFlag\\n\\t if self.dbType=='sqlite':\\n\\t message+=\\\", %s\\\"%self.db.isolation_level\\n\\t print message\\n\\t sys.__stdout__.flush()\\n\\tif self.dbType==\\\"mysql\\\":\\n\\t if self.commitFlag:\\n\\t self.updateDBAndLog(\\\"BEGIN\\\")\\n\\telif self.dbType==\\\"sqlite\\\":\\n\\t if not self.commitFlag:\\n\\t return\\n\\t if self.db.isolation_level:\\n\\t return\\n\\t counter=0\\n\\t query = \\\"BEGIN IMMEDIATE\\\"\\n\\t cu = self.db.cursor()\\n\\t while 1:\\n\\t if counter>10: break\\n\\t try:\\n\\t\\t cu.execute(query)\\n# self.cursor.execute(query)\\n\\t self.updateLog(query)\\n\\t break\\n\\t except:\\n\\t print \\\"Wait for BEGIN\\\"\\n\\t\\t gen_util.printExcept()\\n\\t\\t pass\\n\\t counter+=1\\n\\t cu.close()\\n\\t return\",\n \"def svn_fs_begin_txn2(*args):\\r\\n return _fs.svn_fs_begin_txn2(*args)\",\n \"def startTransaction(self) -> int:\\n ...\",\n \"def start_transaction(self) -> None:\\n pass\",\n \"def svn_fs_begin_txn(*args):\\r\\n return _fs.svn_fs_begin_txn(*args)\",\n \"def tpc_begin(self, transaction):\\n raise NotImplementedError\",\n \"def start_transaction(self,):\\n\\n if self.tx is not None:\\n raise OverlappedTransaction(str(self.tx.xid))\\n\\n modlogger.debug(\\\"start tx\\\")\\n opid = self.new_opid()\\n xaction = StartTxOperation(opid,opid)\\n self.tx = Transaction(opid,self.home, track_state = self.track_state)\\n self._add_operation(opid,xaction)\\n return opid\",\n \"def begin(self):\\n if self.tx_id is None:\\n self.tx_id = yield self.conn.query('*begin-tx*')\\n yield self.conn.query('START TRANSACTION WITH CONSISTENT SNAPSHOT', tx_id=self.tx_id)\",\n \"def begin(self):\\n self._in_transaction = True\\n self.execute(\\\"BEGIN\\\")\",\n \"def begin(cls):\\n db = cls.db\\n db.b_commit = False\",\n \"def commit(self) -> None:\\n trans = self._transaction\\n if trans is None:\\n trans = self._autobegin_t()\\n\\n trans.commit(_to_root=True)\",\n \"def begin(self):\\n self._in_transaction = True\",\n \"def cvmfsStart(reponame = None):\\n if reponame == None:\\n reponame = _getRepoName()\\n\\n rc = subprocess.call([\\\"cvmfs_server\\\", \\\"transaction\\\", reponame])\\n if rc != 0:\\n raise RuntimeError(\\\"Could not start CVMFS transaction\\\")\",\n \"def __gitBisectStart(self):\\n self.vcs.gitBisect(self.project.getProjectPath(), \\\"start\\\")\",\n \"def begin(transactionId, *args):\\n global _operationCount\\n # noinspection PyUnresolvedReferences\\n _log.info(\\n # \\\"%s BEGIN %s\\\" % (transactionId.hex, \\\" \\\".join(util.encode2(a) for a in args))\\n f\\\"{transactionId.hex} BEGIN {' '.join(impl.util.encode2(a) for a in args)}\\\"\\n )\\n _countLock.acquire()\\n try:\\n _operationCount += 1\\n finally:\\n _countLock.release()\",\n \"def commit():\\n query = {\\\"type\\\": \\\"commit\\\", \\\"cmd\\\": \\\"<commit></commit>\\\"}\\n\\n return _get_job_results(query)\",\n \"def run_auto_commit(self):\\n self.commit()\\n if self.auto_commit_interval not in [None, 0]:\\n Timer(self.auto_commit_interval, self.run_auto_commit).start()\",\n \"def start_transaction(self):\\n self._connection.execute_nonquery(\\\"sql\\\", \\\"START TRANSACTION\\\", True)\",\n \"def start_transaction_sql(self):\\n return \\\"BEGIN TRANSACTION\\\"\",\n \"def run_autocommit(self, autocommit):\\n # Create (or recreate) test table.\\n table = 'test_autocommit'\\n\\n self.table_drop(table)\\n\\n self.table_create(table, 'col1 integer')\\n\\n # This code is meant to test autocommit mode, so can't assume one\\n # way or the other and postgres requires that DDL activity be commited\\n # before other connections can set it, so commit the current transaction\\n # just in case.\\n\\n self.commit()\\n\\n # Get a second connection to make a change independent of the main test\\n # connection to determine whether changes made via the second\\n # connection can be seen from the main test connection.\\n\\n dbh2 = despydb.DesDbi(section=self.which_services_section())\\n\\n # Set the second connection's autocommit mode as instructed.\\n\\n if autocommit is not None:\\n dbh2.autocommit(autocommit)\\n\\n try:\\n # Insert a row without an explicit commit and try to access it\\n # from the main connection. Record the result to return to\\n # caller.\\n\\n cursor2 = dbh2.cursor()\\n\\n stmt = ('INSERT INTO %s (col1) VALUES (%s)' %\\n (table, self.get_positional_bind_string()))\\n cursor2.execute(stmt, (4, ))\\n\\n try:\\n cursor1 = self.cursor()\\n cursor1.execute('SELECT col1 FROM %s' % table)\\n res = cursor1.fetchone()\\n except Exception:\\n self.rollback()\\n raise\\n finally:\\n cursor1.close()\\n except Exception:\\n dbh2.rollback()\\n raise\\n finally:\\n cursor2.close()\\n dbh2.close()\\n self.table_drop(table)\\n self.commit()\\n\\n return res\",\n \"def prepare_for_commit(self):\",\n \"def test_commit(self):\\n # TODO: Test errors while committing and recovery\\n pass\",\n \"def commit_transaction(self,xid):\\n modlogger.debug( \\\"end tx:%s\\\"%xid)\\n if xid != self.tx.xid:\\n raise InvalidTransaction(xid)\\n\\n opid = self.new_opid()\\n xaction = EndTxOperation(opid,xid)\\n self._add_operation(xid,xaction)\\n try:\\n self.tx.commit()\\n except Exception:\\n self.tx = None\\n #There is an arguement to call abort here...\\n # but we don't because our (MysteryMachine) use\\n # of this is a bottom layer store, which means the\\n # schema should have already ensured the transactions\\n # are meaningful and a exceptio here is probably a\\n # due to local conditions (like diskspace).\\n #\\n # If we abort we would have to remove the commit record\\n # from the log, and then undo the partial tranasction.\\n # by not aborting, and re-raisig we make this the \\n # problem of a higher layer. Once the problem is resolved\\n # the journal can be replayied making ourselve consistent\\n # again.\\n #\\n # There is one way though of provoking non-recoverable behavour\\n # ad that is creating a file in a non-existant dir.\\n \\n #self.abort_transaction(xid)\\n raise\\n\\n self.tx = None\",\n \"def start_commit(self, revnum):\\n\\n assert revnum > self._youngest\\n self._youngest = revnum\\n\\n # A map {node_id : _WritableMirrorDirectoryMixin}.\\n self._new_nodes = {}\",\n \"def commit_transaction(self) -> None:\\n pass\",\n \"def start_transaction(self):\\n self._db.autocommit = False\",\n \"def commit(self) -> None:\\n self._connector.commit_transaction()\",\n \"def start_transaction_sql(self):\\n return 'START TRANSACTION;'\",\n \"def BeginTransaction(self, request, context):\\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)\",\n \"def svn_fs_commit_txn(*args):\\r\\n return _fs.svn_fs_commit_txn(*args)\",\n \"def commit(self, _context: 'IconScoreContext', precommit_data: 'PrecommitData'):\\n # Updated every block\\n self.preps = precommit_data.preps\\n\\n # Exchange a term instance for some reasons:\\n # - penalty for elected P-Reps(main, sub)\\n # - A new term is started\\n if precommit_data.term is not None:\\n self.term: 'Term' = precommit_data.term\\n\\n self.prep_address_converter: 'PRepAddressConverter' = precommit_data.prep_address_converter\",\n \"def commit(self):\\n self.cnx.commit()\",\n \"def update_port_precommit(self, mech_context):\\n LOG.debug(\\\"update_port_precommit(self: called\\\")\",\n \"def test_autocommit_on(self):\\n res = self.dbh.run_autocommit(True)\\n self.assertIsNotNone(res)\\n self.assertEqual(res[0], 4)\",\n \"def begin_transaction(self, request):\\n return self._call_method('beginTransaction', request,\\n datastore_v1_pb2.BeginTransactionResponse)\",\n \"def set_autocommit(self, conn: jaydebeapi.Connection, autocommit: bool) -> None:\\n conn.jconn.setAutoCommit(autocommit)\",\n \"def start_transaction(self):\\n raise Unsupported()\",\n \"def _Dynamic_BeginTransaction(self, request, transaction, request_id=None):\\n request.set_app(self.project_id)\\n self._RemoteSend(request, transaction, \\\"BeginTransaction\\\", request_id)\\n self.__tx_actions[transaction.handle()] = []\\n return transaction\",\n \"def setCommitFlag(self,flag=1):\\n self.commitFlag=flag\",\n \"def commit(self) -> None:\\n pass\",\n \"def commit(self, snapshot):\\n _, checkpoint_id = snapshot\\n self.chaindb.commit(checkpoint_id)\",\n \"def BeginTransaction(self, request, global_params=None):\\n config = self.GetMethodConfig('BeginTransaction')\\n return self._RunMethod(\\n config, request, global_params=global_params)\",\n \"def commitChanges(self):\\n \\n ## User is prompted that changes are being committed\\n print(\\\"Committing changes to the CRM and Mailings database...\\\")\\n db_connection.executeQuery(\\\"COMMIT;\\\")\",\n \"def commit(self):\\n if self.transaction:\\n self.conn.commit()\\n self.transaction = False\",\n \"def end(self, commit: bool) -> None:\\n ...\",\n \"def commit(self) -> None:\\n with self.lock:\\n self.wait(self._commit_gen())\",\n \"def _do_commit(self):\\n self.backend.commit()\",\n \"def svn_client_commit2(svn_client_commit_info_t_commit_info_p, apr_array_header_t_targets, svn_boolean_t_recurse, svn_boolean_t_keep_locks, svn_client_ctx_t_ctx, apr_pool_t_pool): # real signature unknown; restored from __doc__\\n pass\",\n \"def commit(self, block: 'Block') -> None:\\n # Check for block validation before commit\\n self._precommit_data_manager.validate_precommit_block(block)\\n\\n context = self._context_factory.create(IconScoreContextType.DIRECT)\\n\\n precommit_data: 'PrecommitData' = \\\\\\n self._precommit_data_manager.get(block.hash)\\n block_batch = precommit_data.block_batch\\n new_icon_score_mapper = precommit_data.score_mapper\\n if new_icon_score_mapper:\\n self._icon_score_mapper.update(new_icon_score_mapper)\\n\\n self._icx_context_db.write_batch(\\n context=context, states=block_batch)\\n\\n self._icx_storage.put_block_info(context, block_batch.block)\\n self._precommit_data_manager.commit(block_batch.block)\\n self._context_factory.destroy(context)\",\n \"def commit(self):\\n pass\",\n \"def commit(self):\\n pass\",\n \"def commit(self):\\n pass\",\n \"def commit(self):\\n pass\",\n \"def commit(self):\\n pass\",\n \"def on_start(self):\\n self.deposit(1000000)\",\n \"def set_auto_commit(self, auto_commit):\\n self.__aceQLHttpApi.set_auto_commit(auto_commit)\",\n \"def commit(self):\\n self.execute_sql(sql.commit)\\n self.under_transaction = False\",\n \"def commit( self ) :\\n self.oracle_connection.commit()\",\n \"def test_execute_begin_transaction_read_write(self):\\n\\n instruction = Instruction(\\\"Begin(T1)\\\")\\n self.transaction_manager.execute(instruction)\\n trans1 = self.transaction_manager.transactions[\\\"T1\\\"]\\n self.assertEquals(len(self.transaction_manager.transactions), 1)\\n self.assertEquals(trans1.identifier, \\\"T1\\\")\\n self.assertEquals(trans1.transaction_type, TransactionType.READ_WRITE)\\n self.assertEquals(trans1.start_time, 1)\\n self.assertIsNone(trans1.end_time)\\n self.assertEquals(trans1.state, TransactionState.RUNNING)\",\n \"def begin_transaction(self):\\r\\n self.db.commit(False)\",\n \"def test_commit(self):\\n u = stellr.UpdateCommand(TEST_HTTP, commit=True)\\n self.assertEqual(u.host, 'http://localhost:8983')\\n self.assertEqual(u._handler, '/solr/update/json?wt=json&commit=true')\\n\\n u.add_commit()\\n self.assertEqual(len(u._commands), 1)\\n self.assertEqual(('commit', {}), u._commands[0])\\n self.assertEqual(u.body, '{\\\"commit\\\": {}}')\",\n \"def commit(self):\\n self._connection.execute_nonquery(\\\"sql\\\", \\\"COMMIT\\\", True)\",\n \"def test_autocommit_default(self):\\n res = self.dbh.run_autocommit(None)\\n self.assertIsNone(res)\",\n \"def _do_commit(self):\",\n \"def commit(self):\\n\\t\\treturn Job(SDK.PrlVm_Commit(self.handle)[0])\",\n \"def commitPrivateBefore(self):\\n\\n self._log(\\\"commit-private-before\\\").debug4(\\\"%s: interface commitPrivateBefore was called\\\", self.name)\\n\\n if self.allowDynamicConfig:\\n if self.isTrxStart is True:\\n\\n adminStateChange = (self.candidateEnabled != self.runningEnabled)\\n\\n # rename device and change state up/down\\n # Note: must be before addRule() is called\\n #timeoutGuard = TimeoutGuard(self._log, '%s-commit-name-and-state' % (self.name), Interface.MAX_TIMEOUT_MILI_SEC) \\n self.commitNameAndState()\\n #timeoutGuard.checkAndLog(self.commitNameAndState)\\n \\n # ip address, route and rule\\n self.commitDynamicCfg(adminStateChange)\\n\\n self.updateCfgCache()\\n\\n if self.isFirstTrx is True:\\n\\n shouldClearCounters= self._isCountersClearPostUp() is False and self._isCountersClearPostDown() is False\\n if shouldClearCounters is True:\\n # interface counters start as non-zeros\\n # first transaction commit\\n rc = self._doClearCounters()\\n self.countersOnStart.copyDataFrom(self.countersOnClear) # copy counters snapshot\\n \\n if rc != ReturnCodes.kOk:\\n self._log(\\\"interface-counters-on-start-fail\\\").error(\\\"%s: failed retrieve rx and tx counters on start\\\", \\n self.name)\\n self.isFirstTrx = False\\n\\n self.isTrxStart = False\\n return ReturnCodes.kOk\",\n \"def commit(self):\\n return\",\n \"def endTxn(self,msg=\\\"\\\"):\\n\\tif self.dbType==\\\"mysql\\\":\\n\\t if self.commitFlag:\\n\\t self.updateDBAndLog(\\\"COMMIT\\\")\\n\\telif self.dbType==\\\"sqlite\\\":\\n\\t if self.commitFlag:\\n\\t if self.db.isolation_level:\\n\\t\\t return\\n\\t query=\\\"COMMIT\\\"\\n\\t counter=0\\n\\t cu = self.db.cursor()\\n\\t while 1:\\n\\t if counter>10: break\\n\\t\\t try:\\n self.db.commit() ## sdobbs, 4/19/14\\n#\\t\\t cu.execute(query)\\n# self.cursor.execute(query)\\n self.updateLog(query)\\n break\\n\\t except:\\n\\t\\t print \\\"Wait for COMMIT\\\"\\n\\t\\t gen_util.printExcept()\\n\\t\\t pass\\n\\t counter+=1\\n\\t cu.close()\\n\\n# self.db.commit()\\n# cu = self.db.cursor()\\n# cu.execute(query)\\n# cu.close()\\n# self.db.commit()\\n# self.updateLog(query)\\n\\t\\n\\tif self.verbose and msg:\\n\\t message = \\\" End transaction: \\\"+msg\\n\\t message+=\\\", commit flag=%s\\\"%self.commitFlag\\n\\t if self.dbType=='sqlite':\\n\\t message+=\\\", %s\\\"%self.db.isolation_level\\n\\t print message\\n\\t print\\n\\t sys.__stdout__.flush()\",\n \"def setUp(self):\\n self.instance = Commit('9b423f8c38516ed33acfa907ae56ad3868741803')\",\n \"def begin_transaction(self, project_id, transaction_options=None):\\n request_pb = _datastore_pb2.BeginTransactionRequest()\\n return _rpc(\\n self.client._http,\\n project_id,\\n \\\"beginTransaction\\\",\\n self.client._base_url,\\n self.client._client_info,\\n request_pb,\\n _datastore_pb2.BeginTransactionResponse,\\n )\",\n \"def commit(self):\\n if self._transaction is None:\\n raise TransactionNotStartedError(\\\"Cannot call commit without a transaction\\\")\\n else:\\n def _resetTxn(result):\\n self._transaction = None\\n d = self._config.commit(self._transaction)\\n d.addCallback(_resetTxn)\\n return d\",\n \"def BeginTransaction(self, request, context):\\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\\n context.set_details('Method not implemented!')\\n raise NotImplementedError('Method not implemented!')\",\n \"def begin_transaction(self, event=None):\\n assert not self._current_transaction\\n self._current_transaction = ActionStack()\",\n \"def create_subnet_precommit(self, mech_context):\\n LOG.debug(\\\"create_subnetwork_precommit: called\\\")\",\n \"def do_begin(begin):\\n if begin:\\n do_action(begin)\",\n \"def commit_block(self, block):\\n raise NotImplementedError('commit_block: Implementation of this method is required.')\",\n \"def _auto_commit(self):\\n\\n # Check if we are supposed to do an auto-commit\\n if not self.auto_commit or self.auto_commit_every_n is None:\\n return\\n\\n if self.count_since_commit >= self.auto_commit_every_n:\\n self.commit()\",\n \"def commit(self):\\n raise NotImplementedError\",\n \"def end_commit(self):\\n #scn = bpy.context.scene\\n #for pt in self.b_pts:\\n # point_obj = bpy.data.objects.new(pt.label, None)\\n # point_obj.location = pt.location\\n # scn.objects.link(point_obj)\\n #self.end_commit_post()\\n pass\",\n \"def commit(self):\\n self._pipeline.execute()\\n self.current_chunk = 0\",\n \"def handler_commit(event):\\n if not LOG_DB:\\n return\\n\\n # get the active transaction\\n txn = transaction.get()\\n\\n # get needed values now as the request contents will\\n # change after commit.\\n request = event.request\\n request_data = get_request_data(request)\\n\\n # transactions that will do a commit have a ZODB.Connection\\n # object in ``_resources``. Since the transaction has an\\n # open connection we know it will be committed.\\n for conn in (c for c in txn._resources if isinstance(c, Connection)):\\n # ZODB.Connection objects support callbacks on close.\\n # In this case we wrap the callback in another function\\n # so we can also pass in the event.\\n conn.onCloseCallback(__after_conn_close(request_data))\",\n \"def add_commit( self\\n , cl\\n , mark_number\\n , parent_commit_list\\n , first_branch_from_branch_id\\n , first_branch_from_change_number\\n , dest_branch\\n , branch_name):\\n with Timer(OVERALL):\\n with Timer(BUILD):\\n self.__append(NTR('commit refs/heads/{0}\\\\n').format(branch_name))\\n self.__append(NTR('mark : {0}\\\\n').format(mark_number))\\n desc_info = DescInfo.from_text(cl.description)\\n committer_added = False\\n if desc_info:\\n for key in ('author', 'committer'):\\n v = desc_info[key]\\n if v:\\n self.__append(NTR('{key} {fullname} {email} {time} {timezone}\\\\n').\\n format( key = key\\n , fullname = v['fullname']\\n , email = v['email' ]\\n , time = v['time' ]\\n , timezone = v['timezone']))\\n committer_added = True\\n desc = desc_info.clean_desc\\n\\n # Convoluted logic gates but avoids duplicating code. The point\\n # is that we add the best possible committer data _before_\\n # adding the description.\\n if not committer_added:\\n if desc_info:\\n # old change description that lacked detailed author info,\\n # deserves a warning, but otherwise push onward even if the\\n # commit checksums will likely differ from the originals\\n LOG.warn('commit description did not match committer regex: @{} => {}'.\\n format(cl.change, desc_info.suffix))\\n timezone = self.__get_timezone_offset(cl.time)\\n self.__append(NTR('committer {fullname} {email} {time} {timezone}\\\\n').\\n format(fullname=self.__full_name_for_user(cl.user),\\n email=self.__email_for_user(cl.user),\\n time=cl.time,\\n timezone=timezone))\\n desc = cl.description\\n self.__add_data(desc)\\n\\n self._add_commit_parent_list(parent_commit_list)\\n if first_branch_from_branch_id \\\\\\n and first_branch_from_change_number:\\n self.__branch_from( dest_branch\\n , cl\\n , first_branch_from_branch_id\\n , first_branch_from_change_number)\\n self.__add_files(cl.files)\\n if desc_info and desc_info.gitlinks:\\n self.__add_gitlinks(desc_info.gitlinks)\",\n \"def commit(self):\\n datastore_pre_commit.send(session=self.db.session)\\n super().commit()\\n datastore_post_commit.send(session=self.db.session)\",\n \"def enter_transaction():\\n _state.transactions = get_transactions() + 1\",\n \"def test_execute_begin_ro_transaction(self):\\n\\n instruction = Instruction(\\\"BeginRO(T1)\\\")\\n self.transaction_manager.execute(instruction)\\n trans1 = self.transaction_manager.transactions[\\\"T1\\\"]\\n\\n self.assertTrue(\\\"T1\\\" in self.transaction_manager.transactions)\\n self.assertEquals(self.transaction_manager.transactions[\\\"T1\\\"].transaction_type, TransactionType.READ_ONLY)\\n\\n for site in self.transaction_manager.sites.values():\\n for variable_identifier in site.data_manager.variables:\\n self.assertTrue(variable_identifier in self.transaction_manager.readonly_snapshots[\\\"T1\\\"])\\n \\n self.assertEquals(trans1.identifier, \\\"T1\\\")\\n self.assertEquals(trans1.transaction_type, TransactionType.READ_ONLY)\\n self.assertEquals(trans1.start_time, 1)\\n self.assertIsNone(trans1.end_time)\\n self.assertEquals(trans1.state, TransactionState.RUNNING)\",\n \"def commit(self, _context: 'IconScoreContext', precommit_data: 'PrecommitData'):\\n # Updated every block\\n self.preps = precommit_data.preps\\n\\n # Updated every term\\n if precommit_data.term is not None:\\n self.term: 'Term' = precommit_data.term\",\n \"def update_network_precommit(self, mech_context):\\n pass\",\n \"def begin_create(self):\\n self.mdb.get().begin_create()\",\n \"def commit(self):\\n # PEP 249\\n pass\",\n \"def start_workunit(self, workunit):\\r\\n pass\",\n \"def start_workunit(self, workunit):\\r\\n pass\",\n \"def conduit_committee_id(self, conduit_committee_id):\\n\\n self._conduit_committee_id = conduit_committee_id\",\n \"def commit(self):\\n\\n if not self.is_active:\\n return\\n\\n if self.is_context_active:\\n raise states.Committed(self)\\n else:\\n self.__do_commit()\\n self._cleanup()\",\n \"def commit(self, msg=None):\\n self.log.debug(\\\"committing in git: %s\\\" % msg)\\n completemsg = \\\"EasyBuild-commit from %s (time: %s, user: %s) \\\\n%s\\\" % (socket.gethostname(),\\n time.strftime(\\\"%Y-%m-%d_%H-%M-%S\\\"),\\n getpass.getuser(),\\n msg)\\n self.log.debug(\\\"git status: %s\\\" % self.client.status())\\n try:\\n self.client.commit('-am \\\"%s\\\"' % completemsg)\\n self.log.debug(\\\"succesfull commit\\\")\\n except GitCommandError, err:\\n self.log.warning(\\\"Commit from working copy %s (msg: %s) failed, empty commit?\\\\n%s\\\" % (self.wc, msg, err))\\n try:\\n info = self.client.push()\\n self.log.debug(\\\"push info: %s \\\" % info)\\n except GitCommandError, err:\\n self.log.warning(\\\"Push from working copy %s to remote %s (msg: %s) failed: %s\\\" % (self.wc,\\n self.repo,\\n msg,\\n err))\",\n \"def start(self):\\n assert not self.state is CallState.finished\\n\\n self.state = CallState.started\\n self.start_time = time()\",\n \"def commit(self):\\n conn = self.threadingLocal.connection\\n if isinstance(conn, Transaction):\\n self.threadingLocal.connection.commit()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.69779134","0.67022675","0.6374768","0.62052375","0.5827012","0.5754907","0.5623243","0.5612392","0.55755603","0.5503088","0.5498579","0.54919153","0.54549724","0.54370314","0.5418667","0.52956843","0.52474976","0.5242918","0.5212305","0.5158825","0.5135469","0.51310486","0.5122945","0.50896734","0.5075436","0.5054971","0.50544053","0.50458866","0.50279766","0.50240827","0.50127417","0.5004552","0.49559355","0.4927014","0.49158788","0.4914006","0.48996216","0.48826528","0.48647848","0.48487458","0.484306","0.4840691","0.48335037","0.4807886","0.48036295","0.48021132","0.4788761","0.4777464","0.47429058","0.4737069","0.47179464","0.47170344","0.4711768","0.4711768","0.4711768","0.4711768","0.4711768","0.46831828","0.46735454","0.4663667","0.46595144","0.46539435","0.46420598","0.4631705","0.46285424","0.4627074","0.4616463","0.46121976","0.4611463","0.45998544","0.45973864","0.45939514","0.4593445","0.45803156","0.45780253","0.45694718","0.45587596","0.45580816","0.45569366","0.4553392","0.4544306","0.45400053","0.45273113","0.45109302","0.45075166","0.4498018","0.4497507","0.4491575","0.44808525","0.44710878","0.44704774","0.4456226","0.4450722","0.4450722","0.44493338","0.44416484","0.44402373","0.44250998","0.44225198"],"string":"[\n \"0.69779134\",\n \"0.67022675\",\n \"0.6374768\",\n \"0.62052375\",\n \"0.5827012\",\n \"0.5754907\",\n \"0.5623243\",\n \"0.5612392\",\n \"0.55755603\",\n \"0.5503088\",\n \"0.5498579\",\n \"0.54919153\",\n \"0.54549724\",\n \"0.54370314\",\n \"0.5418667\",\n \"0.52956843\",\n \"0.52474976\",\n \"0.5242918\",\n \"0.5212305\",\n \"0.5158825\",\n \"0.5135469\",\n \"0.51310486\",\n \"0.5122945\",\n \"0.50896734\",\n \"0.5075436\",\n \"0.5054971\",\n \"0.50544053\",\n \"0.50458866\",\n \"0.50279766\",\n \"0.50240827\",\n \"0.50127417\",\n \"0.5004552\",\n \"0.49559355\",\n \"0.4927014\",\n \"0.49158788\",\n \"0.4914006\",\n \"0.48996216\",\n \"0.48826528\",\n \"0.48647848\",\n \"0.48487458\",\n \"0.484306\",\n \"0.4840691\",\n \"0.48335037\",\n \"0.4807886\",\n \"0.48036295\",\n \"0.48021132\",\n \"0.4788761\",\n \"0.4777464\",\n \"0.47429058\",\n \"0.4737069\",\n \"0.47179464\",\n \"0.47170344\",\n \"0.4711768\",\n \"0.4711768\",\n \"0.4711768\",\n \"0.4711768\",\n \"0.4711768\",\n \"0.46831828\",\n \"0.46735454\",\n \"0.4663667\",\n \"0.46595144\",\n \"0.46539435\",\n \"0.46420598\",\n \"0.4631705\",\n \"0.46285424\",\n \"0.4627074\",\n \"0.4616463\",\n \"0.46121976\",\n \"0.4611463\",\n \"0.45998544\",\n \"0.45973864\",\n \"0.45939514\",\n \"0.4593445\",\n \"0.45803156\",\n \"0.45780253\",\n \"0.45694718\",\n \"0.45587596\",\n \"0.45580816\",\n \"0.45569366\",\n \"0.4553392\",\n \"0.4544306\",\n \"0.45400053\",\n \"0.45273113\",\n \"0.45109302\",\n \"0.45075166\",\n \"0.4498018\",\n \"0.4497507\",\n \"0.4491575\",\n \"0.44808525\",\n \"0.44710878\",\n \"0.44704774\",\n \"0.4456226\",\n \"0.4450722\",\n \"0.4450722\",\n \"0.44493338\",\n \"0.44416484\",\n \"0.44402373\",\n \"0.44250998\",\n \"0.44225198\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6510619"},"document_rank":{"kind":"string","value":"2"}}},{"rowIdx":15591,"cells":{"query":{"kind":"string","value":"SetRollback marks the 2pc transaction for rollback."},"document":{"kind":"string","value":"def SetRollback(self, request, context):\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\n context.set_details('Method not implemented!')\n raise NotImplementedError('Method not implemented!')"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def SetRollback(self, request, context):\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)","def SetRollback(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\n raise NotImplementedError()","def rollback(self):\n self._rollback = True","def rollback(self, rollback_to):\n raise NotImplementedError","def rollback(self):\n raise TransactionRollback('rollback called outside of transaction')","def _do_rollback(self):\n self.backend.rollback()","def rollback(self):\n self.conn.rollback()","def rollback(self):\n self._connection.execute_nonquery(\"sql\", \"ROLLBACK\", True)","def rollback(self):\n pass","def rollback(self):\n raise NotImplementedError","def rollback(self):\n if self._transaction is None:\n raise TransactionNotStartedError(\"Cannot call rollback without a transaction\")\n else:\n def _resetTxn(result):\n self._transaction = None\n d = self._config.rollback(self._transaction)\n d.addCallback(_resetTxn)\n return d","def rollback(self) -> None:\n with self.lock:\n self.wait(self._rollback_gen())","def RollBack(self):\r\n self.conn.rollback()","def rollback(self) -> None:\n if self._transaction is None:\n pass\n else:\n self._transaction.rollback(_to_root=True)","def rollback(self):\r\n self.db.rollback()","def rollback(self):\n self.db.rollback()","def rollback(self, target_revision_id):\n url = DeckhandClient.get_path(\n DeckhandPaths.ROLLBACK\n ).format(target_revision_id)\n\n response = self._post_request(url)\n self._handle_bad_response(response)","def rollback(self, stage, enodes, exception):","def rollback(self):\n self.success = False\n self.close()","def rollback(self, mapset=None):\n if mapset is None:\n mapset = self.current_mapset","def rollback(self, project_id, transaction):\n request_pb = _datastore_pb2.RollbackRequest(\n project_id=project_id, transaction=transaction\n )\n # Response is empty (i.e. no fields) but we return it anyway.\n return _rpc(\n self.client._http,\n project_id,\n \"rollback\",\n self.client._base_url,\n self.client._client_info,\n request_pb,\n _datastore_pb2.RollbackResponse,\n )","def rollback(self):\n\n if not self.is_active:\n return\n\n if self.is_context_active:\n raise states.RolledBack(self)\n else:\n self.__do_rollback()\n self._cleanup()","def rollback(self):\n if self.dbmi.__name__ == \"psycopg2\":\n if self.connected:\n self.connection.rollback()","def rollback(self):\n try:\n if self._cur_batch:\n self._cur_batch.rollback()\n except ValueError:\n # ignore \"Batch must be in progress to rollback\" error\n pass\n self._cur_batch = None\n self._num_mutations = 0","def rollback(self):\n return self.connection.rollback","def savepoint_rollback(self, id):\n self.execute(\"ROLLBACK TO SAVEPOINT {}\".format(id))","def rollback(self, steps=1) -> None:\n raise NotImplementedError(\n \"Open transactions are currently not supported. To reset commit head, check WOQLClient.reset\"\n )","def disable_rollback(self):\n if self.args.disable_rollback is True:\n disable_rollback = self.args.disable_rollback\n else:\n disable_rollback = None\n return disable_rollback","def rollback_transaction(self, event=None):\n assert self._current_transaction\n\n # Store stacks\n undo_stack = list(self._undo_stack)\n\n erroneous_tx = self._current_transaction\n self._current_transaction = None\n try:\n with Transaction(self.event_manager):\n try:\n erroneous_tx.execute()\n except Exception as e:\n logger.error(\"Could not roolback transaction\")\n logger.error(e)\n finally:\n # Discard all data collected in the rollback \"transaction\"\n self._undo_stack = undo_stack\n\n self._action_executed()","def rollback(self):\n self._session.rollback()\n\n return True","def rollback_transaction(self):\n cursor = self._cursor()\n cursor.close()\n self._db.rollback()\n self._end_transaction()","def rollback(self, block: 'Block') -> None:\n # Check for block validation before rollback\n self._precommit_data_manager.validate_precommit_block(block)\n self._precommit_data_manager.rollback(block)","async def rollback(self):\n if not self._active:\n raise ProfileSessionInactiveError()\n await self._teardown(commit=False)\n self._active = False","def rollback(self):\n return self.connection.rollback()","def _Dynamic_Rollback(self, transaction, transaction_response,\n request_id=None):\n transaction.set_app(self.project_id)\n\n try:\n del self.__tx_actions[transaction.handle()]\n except KeyError:\n pass\n\n self._RemoteSend(transaction, transaction_response, \"Rollback\", request_id)\n \n return transaction_response","def rollback(commit_id):\n _confirm_branch()\n \n require('settings', provided_by=[production, staging])\n require('branch', provided_by=[stable, master, branch])\n \n maintenance_up()\n checkout_latest()\n git_reset(commit_id)\n gzip_assets()\n deploy_to_s3()\n maintenance_down()","def rollback(self):\n conn = self.threadingLocal.connection\n if isinstance(conn, Transaction) and not conn._obsolete:\n self.threadingLocal.connection.rollback()","def rollback(self):\n # PEP 249\n raise impala.error.NotSupportedError()","def _Rollback(failure, stopping_services, starting_services):\n def _HandleRollbackError(failure):\n \"\"\"Ignores rollback error.\"\"\"\n exc_info = (failure.type, failure.value, failure.tb)\n logging.error('Failed rolling back configuration',\n exc_info=exc_info)\n return True\n\n deferred = self.StopServices(starting_services)\n deferred.addCallback(lambda _: self.StartServices(stopping_services))\n deferred.addErrback(_HandleRollbackError)\n # Ignore result for rollback, and return the deploy failure.\n deferred.addBoth(lambda _: failure)\n return deferred","def Rollback(self, request, global_params=None):\n config = self.GetMethodConfig('Rollback')\n return self._RunMethod(\n config, request, global_params=global_params)","def Rollback(self, request, global_params=None):\n config = self.GetMethodConfig('Rollback')\n return self._RunMethod(\n config, request, global_params=global_params)","def rollback_action(args, kwargs, was_interrupted, result=None):\n raise NotImplementedError()","def disable_rollback(self) -> bool:\n return pulumi.get(self, \"disable_rollback\")","def test_rollback():","def rollback_workflow(self, execution_id):\n raise NotImplementedError","def rollback(self, dry_run=False, force=False):\n eh = SimpleErrorHandler()\n\n out = self._client.execute('rollback', n=dry_run, f=force, eh=eh)\n\n return bool(eh)","def rollback(self, context: 'IconScoreContext', _block_height: int, _block_hash: bytes):\n Logger.info(tag=ROLLBACK_LOG_TAG, msg=\"rollback() start\")\n\n self.prep_address_converter: 'PRepAddressConverter' = context.storage.meta.get_prep_address_converter(context)\n\n self.preps = self._load_preps(context)\n self.term = self._load_term(context)\n\n Logger.info(tag=ROLLBACK_LOG_TAG, msg=f\"rollback() end: {self.term}\")","def setTerminusBack(self, new_terminus) :\n self._terminusBack = new_terminus","def test_rollback(self, local_connection):\n\n users = self.tables.users\n connection = local_connection\n transaction = connection.begin()\n connection.execute(users.insert(), dict(user_id=1, user_name=\"user1\"))\n connection.execute(users.insert(), dict(user_id=2, user_name=\"user2\"))\n connection.execute(users.insert(), dict(user_id=3, user_name=\"user3\"))\n transaction.rollback()\n result = connection.exec_driver_sql(\"select * from users\")\n assert len(result.fetchall()) == 0","def rollback(migrator, database, fake=False, **kwargs):\n pass","def init_for_rollback(self, _req):\n\n # Tempoary state and will depends on prior state\n self.state = \"rollback\"\n\n if \"stack_id\" in _req.keys():\n if _req[\"stack_id\"] is not None:\n stack_id = _req[\"stack_id\"].strip()\n\n stack_id_elements = stack_id.split('/', 1)\n if len(stack_id_elements) > 1:\n self.app_id = stack_id_elements[1]\n else:\n self.app_id = stack_id\n\n self.logger.debug(\"stack_id = \" + self.app_id)\n else:\n # If the stack fails, stack_id can be null.\n self.app_id = \"none\"\n\n self.logger.debug(\"stack_id = None\")\n else:\n self.status = \"no stack_id in request\"\n return\n\n if \"suppress_rollback\" in _req.keys():\n self.suppress_rollback = _req[\"suppress_rollback\"]\n\n if \"error_message\" in _req.keys():\n # TODO(Gueyoung): analyze the error message.\n\n if _req[\"error_message\"] is None:\n self.logger.warning(\"error message from platform: none\")\n else:\n self.logger.warning(\"error message from platform:\" + _req[\"error_message\"])","def rollback_object(self, obj):\n attribute_manager.rollback(obj)\n try:\n self.dirty.remove(obj)\n except KeyError:\n pass\n try:\n self.deleted.remove(obj)\n except KeyError:\n pass","def setAbortState(*args):\n args[0].Controls.AbortState.abort_state = args[1]","def tpc_abort(self, transaction):\n raise NotImplementedError","def rollback_skill_v1(self, skill_id, create_rollback_request, **kwargs):\n # type: (str, CreateRollbackRequest_e7747a32, **Any) -> Union[ApiResponse, object, CreateRollbackResponse_5a2e8250, StandardizedError_f5106a89, BadRequestError_f854b05]\n operation_name = \"rollback_skill_v1\"\n params = locals()\n for key, val in six.iteritems(params['kwargs']):\n params[key] = val\n del params['kwargs']\n # verify the required parameter 'skill_id' is set\n if ('skill_id' not in params) or (params['skill_id'] is None):\n raise ValueError(\n \"Missing the required parameter `skill_id` when calling `\" + operation_name + \"`\")\n # verify the required parameter 'create_rollback_request' is set\n if ('create_rollback_request' not in params) or (params['create_rollback_request'] is None):\n raise ValueError(\n \"Missing the required parameter `create_rollback_request` when calling `\" + operation_name + \"`\")\n\n resource_path = '/v1/skills/{skillId}/rollbacks'\n resource_path = resource_path.replace('{format}', 'json')\n\n path_params = {} # type: Dict\n if 'skill_id' in params:\n path_params['skillId'] = params['skill_id']\n\n query_params = [] # type: List\n\n header_params = [] # type: List\n\n body_params = None\n if 'create_rollback_request' in params:\n body_params = params['create_rollback_request']\n header_params.append(('Content-type', 'application/json'))\n header_params.append(('User-Agent', self.user_agent))\n\n # Response Type\n full_response = False\n if 'full_response' in params:\n full_response = params['full_response']\n\n # Authentication setting\n access_token = self._lwa_service_client.get_access_token_from_refresh_token()\n authorization_value = \"Bearer \" + access_token\n header_params.append(('Authorization', authorization_value))\n\n error_definitions = [] # type: List\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.skill.create_rollback_response.CreateRollbackResponse\", status_code=201, message=\"Rollback request created; Returns the generated identifier to track the rollback request and returns a URL to track the status in Location header.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.bad_request_error.BadRequestError\", status_code=400, message=\"Server cannot process the request due to a client error.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\", status_code=401, message=\"The auth token is invalid/expired or doesn't have access to the resource.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.bad_request_error.BadRequestError\", status_code=403, message=\"The operation being requested is not allowed.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\", status_code=404, message=\"The resource being requested is not found.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\", status_code=409, message=\"The request could not be completed due to a conflict with the current state of the target resource.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\", status_code=429, message=\"Exceeds the permitted request limit. Throttling criteria includes total requests, per API, ClientId, and CustomerId.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\", status_code=500, message=\"Internal Server Error.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\", status_code=503, message=\"Service Unavailable.\"))\n\n api_response = self.invoke(\n method=\"POST\",\n endpoint=self._api_endpoint,\n path=resource_path,\n path_params=path_params,\n query_params=query_params,\n header_params=header_params,\n body=body_params,\n response_definitions=error_definitions,\n response_type=\"ask_smapi_model.v1.skill.create_rollback_response.CreateRollbackResponse\")\n\n if full_response:\n return api_response\n return api_response.body","def test_no_rollback_in_committed_state(self):\n\n sess = fixture_session()\n\n def fail(*arg, **kw):\n raise BaseException(\"some base exception\")\n\n with mock.patch.object(\n testing.db.dialect, \"do_rollback\", side_effect=fail\n ) as fail_mock, mock.patch.object(\n testing.db.dialect,\n \"do_commit\",\n side_effect=testing.db.dialect.do_commit,\n ) as succeed_mock:\n # sess.begin() -> commit(). why would do_rollback() be called?\n # because of connection pool finalize_fairy *after* the commit.\n # this will cause the conn.close() in session.commit() to fail,\n # but after the DB commit succeeded.\n with expect_raises_message(BaseException, \"some base exception\"):\n with sess.begin():\n conn = sess.connection()\n fairy_conn = conn.connection\n\n eq_(succeed_mock.mock_calls, [mock.call(fairy_conn)])\n eq_(fail_mock.mock_calls, [mock.call(fairy_conn)])","def rollback(self, connection):\n return self.symlink_rollback(connection)","def rollback(self):\n self.stream.seek(0)","def restore(self, restore):\n self._restore = restore","def setTransitionEffect(self, *args):\n return _libsbml.Output_setTransitionEffect(self, *args)","def rollback_one(self, migration, force=False):\n logger.info(\"Rolling back %s\", migration.id)\n self.ensure_internal_schema_updated()\n migration.process_steps(self, \"rollback\", force=force)\n self.log_migration(migration, \"rollback\")\n with self.transaction():\n self.unmark_one(migration, log=False)","def get_rollback_for_skill_v1(self, skill_id, rollback_request_id, **kwargs):\n # type: (str, str, **Any) -> Union[ApiResponse, object, StandardizedError_f5106a89, BadRequestError_f854b05, RollbackRequestStatus_71665366]\n operation_name = \"get_rollback_for_skill_v1\"\n params = locals()\n for key, val in six.iteritems(params['kwargs']):\n params[key] = val\n del params['kwargs']\n # verify the required parameter 'skill_id' is set\n if ('skill_id' not in params) or (params['skill_id'] is None):\n raise ValueError(\n \"Missing the required parameter `skill_id` when calling `\" + operation_name + \"`\")\n # verify the required parameter 'rollback_request_id' is set\n if ('rollback_request_id' not in params) or (params['rollback_request_id'] is None):\n raise ValueError(\n \"Missing the required parameter `rollback_request_id` when calling `\" + operation_name + \"`\")\n\n resource_path = '/v1/skills/{skillId}/rollbacks/{rollbackRequestId}'\n resource_path = resource_path.replace('{format}', 'json')\n\n path_params = {} # type: Dict\n if 'skill_id' in params:\n path_params['skillId'] = params['skill_id']\n if 'rollback_request_id' in params:\n path_params['rollbackRequestId'] = params['rollback_request_id']\n\n query_params = [] # type: List\n\n header_params = [] # type: List\n\n body_params = None\n header_params.append(('Content-type', 'application/json'))\n header_params.append(('User-Agent', self.user_agent))\n\n # Response Type\n full_response = False\n if 'full_response' in params:\n full_response = params['full_response']\n\n # Authentication setting\n access_token = self._lwa_service_client.get_access_token_from_refresh_token()\n authorization_value = \"Bearer \" + access_token\n header_params.append(('Authorization', authorization_value))\n\n error_definitions = [] # type: List\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.skill.rollback_request_status.RollbackRequestStatus\", status_code=200, message=\"Returns the rollback status for a given skillId and rollbackRequestId. Returns the latest rollback status if ~latest is used in place of rollbackRequestId.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.bad_request_error.BadRequestError\", status_code=400, message=\"Server cannot process the request due to a client error.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\", status_code=401, message=\"The auth token is invalid/expired or doesn't have access to the resource.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.bad_request_error.BadRequestError\", status_code=403, message=\"The operation being requested is not allowed.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\", status_code=404, message=\"The resource being requested is not found.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\", status_code=429, message=\"Exceeds the permitted request limit. Throttling criteria includes total requests, per API, ClientId, and CustomerId.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\", status_code=500, message=\"Internal Server Error.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\", status_code=503, message=\"Service Unavailable.\"))\n\n api_response = self.invoke(\n method=\"GET\",\n endpoint=self._api_endpoint,\n path=resource_path,\n path_params=path_params,\n query_params=query_params,\n header_params=header_params,\n body=body_params,\n response_definitions=error_definitions,\n response_type=\"ask_smapi_model.v1.skill.rollback_request_status.RollbackRequestStatus\")\n\n if full_response:\n return api_response\n return api_response.body","def rollback(self):\n if len(self.__stack) == 0:\n raise EmptyStackException()\n self.__current_pos = self.__stack[-1][0]\n self.line = self.__stack[-1][1]\n self.linePos = self.__stack[-1][2]\n self.__stack = self.__stack[:-1]","def rollback(obj, commit):\n copy = deepcopy(obj)\n if commit.uses_slots is False:\n copy.__dict__ = commit.state\n else:\n for k, v in commit.state.items():\n setattr(copy, k, v)\n\n return copy","def set_reviewing(self, revert=None):\n self.connection.set_reviewing(self.mturk_id, revert=revert)\n self.update()","def rollback(self):\n\t\traise GeneratorException(\"Not implemented\")","def rollback(self, snapshot):\n\n if not self.__settings:\n return\n\n _logger.debug('Performing rollback of data into '\n 'subsequent harvest period. Metric data and transaction events'\n 'will be preserved and rolled into next harvest')\n\n self.merge_metric_stats(snapshot)\n self._merge_transaction_events(snapshot, rollback=True)\n self._merge_synthetics_events(snapshot, rollback=True)\n self._merge_error_events(snapshot)\n self._merge_custom_events(snapshot, rollback=True)\n self._merge_span_events(snapshot, rollback=True)","def rollback(self, cursor):\n\t\twith warnings.catch_warnings():\n\t\t\twarnings.simplefilter(\"ignore\")\n\t\t\tconnection = cursor.connection\n\t\tconnection.rollback()\n\t\tself._close_cursor(cursor)","def __exit__(self, exception_type, exception_val, trace):\n if not exception_type:\n self.commit()\n else:\n self.rollback()\n self.close()","def cancel(self):\n self.session.rollback()","def rollback_to(cls, **filters) -> int:\n return 0","def set_trace(stop=True, **kwargs):\n Qdb(**kwargs).set_trace(sys._getframe().f_back, stop=stop)\n # We use f_back so that we start in the caller of this function.","def rollbackVirtualMachine(self,node,vmid,snapname):\n post_data = None\n data = self.connect('post',\"nodes/%s/qemu/%s/snapshot/%s/rollback\" % (node,vmid,snapname), post_data)\n return data","def test_create_namespaced_deployment_config_rollback_rollback(self):\n pass","def rollback_to(self, name):\n if not isinstance(name, str) or len(name.strip()) == 0:\n raise ProgrammingError(\"Invalid SAVEPOINT name\")\n self._connection.execute_nonquery(\n \"sql\",\n f\"ROLLBACK TO SAVEPOINT {quote_identifier(name)}\",\n True,\n )","def setUndoBlock(self, callback):\n assert not self.undoBlock, \"Cannot add multiple undo blocks (yet)\"\n self.undoBlock = callback","def restore(self, commit=True):\n self.trashed_time = None\n if commit:\n self.save()","def resume_workflow(self):\n with self._driver.session() as session:\n session.write_transaction(tx.set_workflow_state, state='RESUME')","def rollback(self):\n for db in self.values():\n db.rollback()","def begin_commit(self, _stacklevel=1):\n if self.commit_phase:\n warnings.warn('the transaction already is on commit phase; '\n 'begin_commit() method seems called twice or more' +\n self.format_commit_stack(),\n category=TransactionWarning,\n stacklevel=1 + _stacklevel)\n return\n self.commit_phase = True\n if self.session.verbose_transaction_error:\n self.commit_stack = traceback.format_stack()\n self.session.client.multi()","def Rollback(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\n raise NotImplementedError()","def rollback_unless_managed(self):\n if not self.is_managed():\n self.rollback()","def setHalt(self):\n self.set_register(REG_TYPE, SETPOINT_HALT, 'int')","def set_as_reverted(self):\n self.is_revert = False\n self.update_request.status = 'Reverted'","def _rollback_context(self, persister):\n try:\n # Rollback the job transactional context.\n persister.rollback()\n\n except _errors.DatabaseError as error:\n _LOGGER.error(\n \"Error in %s rolling back job's context.\",\n self.__action.__name__, exc_info=error\n )\n\n # Update the job status.\n self.__result = False\n message = \"Tried to execute action ({0}).\".format(\n self.__action.__name__)\n self._add_status(Job.ERROR, Job.COMPLETE, message, True)\n\n # Finish context which means mark the job as finished\n # and update procedure's information.\n self._finish_context(False)","def rollback(self, exc):\n USER.info('%s: Rolling Back Failed Build', self.recipe.name)\n cascade = False\n if isinstance(exc, AssertionError):\n logging.error('Error during verify() of %s', self.recipe.name)\n cascade = True\n if cascade or isinstance(exc, PakitLinkError):\n if not cascade:\n logging.error('Error during linking of %s', self.recipe.name)\n walk_and_unlink(self.recipe.install_dir, self.recipe.link_dir)\n cascade = True\n if cascade or (not isinstance(exc, PakitLinkError) and\n not isinstance(exc, AssertionError)):\n if not cascade:\n logging.error('Error during build() of %s', self.recipe.name)\n try:\n Command('rm -rf ' + self.recipe.install_dir).wait()\n except PakitCmdError: # pragma: no cover\n pass","def rollback(self): \r\n if self._closed:\r\n raise Error('The connection to the database has been closed.')\r\n for table in self.tables.keys():\r\n if self.tables[table].open:\r\n self.tables[table].rollback()\r\n for table in self.createdTables:\r\n if self.tables.has_key(table):\r\n if self.tables[table].open:\r\n self.tables[table]._close()\r\n del self.tables[table]\r\n for end in self.tableExtensions:\r\n if os.path.exists(self.database+os.sep+table+end):\r\n os.remove(self.database+os.sep+table+end)\r\n self.createdTables = []","def setTransitionEffect(self, *args):\n return _libsbml.Input_setTransitionEffect(self, *args)","def RollbackVdisk(self, data, vdiskid, headers=None, query_params=None, content_type=\"application/json\"):\n uri = self.client.base_url + \"/vdisks/\"+vdiskid+\"/rollback\"\n return self.client.post(uri, data, headers, query_params, content_type)","def tearDown(self):\r\n\r\n db.session.rollback()","def set_backshift(self, seconds):\n self._backshift = seconds","def rollback(tag):\n done = run_command(['git', 'tag', '-d', tag])\n if done.returncode:\n echo.bold(colors.red(str(done)))\n sys.exit(done.returncode)\n echo.cyan('Done:', done.stdout.strip())","def tearDown(self):\n\n db.session.rollback()","def tearDown(self):\n\n db.session.rollback()","def tearDown(self):\n\n db.session.rollback()","def tearDown(self):\n\n db.session.rollback()","def tearDown(self):\n\n db.session.rollback()","def tearDown(self):\n\n db.session.rollback()","def tearDown(self):\n\n db.session.rollback()"],"string":"[\n \"def SetRollback(self, request, context):\\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)\",\n \"def SetRollback(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\\n raise NotImplementedError()\",\n \"def rollback(self):\\n self._rollback = True\",\n \"def rollback(self, rollback_to):\\n raise NotImplementedError\",\n \"def rollback(self):\\n raise TransactionRollback('rollback called outside of transaction')\",\n \"def _do_rollback(self):\\n self.backend.rollback()\",\n \"def rollback(self):\\n self.conn.rollback()\",\n \"def rollback(self):\\n self._connection.execute_nonquery(\\\"sql\\\", \\\"ROLLBACK\\\", True)\",\n \"def rollback(self):\\n pass\",\n \"def rollback(self):\\n raise NotImplementedError\",\n \"def rollback(self):\\n if self._transaction is None:\\n raise TransactionNotStartedError(\\\"Cannot call rollback without a transaction\\\")\\n else:\\n def _resetTxn(result):\\n self._transaction = None\\n d = self._config.rollback(self._transaction)\\n d.addCallback(_resetTxn)\\n return d\",\n \"def rollback(self) -> None:\\n with self.lock:\\n self.wait(self._rollback_gen())\",\n \"def RollBack(self):\\r\\n self.conn.rollback()\",\n \"def rollback(self) -> None:\\n if self._transaction is None:\\n pass\\n else:\\n self._transaction.rollback(_to_root=True)\",\n \"def rollback(self):\\r\\n self.db.rollback()\",\n \"def rollback(self):\\n self.db.rollback()\",\n \"def rollback(self, target_revision_id):\\n url = DeckhandClient.get_path(\\n DeckhandPaths.ROLLBACK\\n ).format(target_revision_id)\\n\\n response = self._post_request(url)\\n self._handle_bad_response(response)\",\n \"def rollback(self, stage, enodes, exception):\",\n \"def rollback(self):\\n self.success = False\\n self.close()\",\n \"def rollback(self, mapset=None):\\n if mapset is None:\\n mapset = self.current_mapset\",\n \"def rollback(self, project_id, transaction):\\n request_pb = _datastore_pb2.RollbackRequest(\\n project_id=project_id, transaction=transaction\\n )\\n # Response is empty (i.e. no fields) but we return it anyway.\\n return _rpc(\\n self.client._http,\\n project_id,\\n \\\"rollback\\\",\\n self.client._base_url,\\n self.client._client_info,\\n request_pb,\\n _datastore_pb2.RollbackResponse,\\n )\",\n \"def rollback(self):\\n\\n if not self.is_active:\\n return\\n\\n if self.is_context_active:\\n raise states.RolledBack(self)\\n else:\\n self.__do_rollback()\\n self._cleanup()\",\n \"def rollback(self):\\n if self.dbmi.__name__ == \\\"psycopg2\\\":\\n if self.connected:\\n self.connection.rollback()\",\n \"def rollback(self):\\n try:\\n if self._cur_batch:\\n self._cur_batch.rollback()\\n except ValueError:\\n # ignore \\\"Batch must be in progress to rollback\\\" error\\n pass\\n self._cur_batch = None\\n self._num_mutations = 0\",\n \"def rollback(self):\\n return self.connection.rollback\",\n \"def savepoint_rollback(self, id):\\n self.execute(\\\"ROLLBACK TO SAVEPOINT {}\\\".format(id))\",\n \"def rollback(self, steps=1) -> None:\\n raise NotImplementedError(\\n \\\"Open transactions are currently not supported. To reset commit head, check WOQLClient.reset\\\"\\n )\",\n \"def disable_rollback(self):\\n if self.args.disable_rollback is True:\\n disable_rollback = self.args.disable_rollback\\n else:\\n disable_rollback = None\\n return disable_rollback\",\n \"def rollback_transaction(self, event=None):\\n assert self._current_transaction\\n\\n # Store stacks\\n undo_stack = list(self._undo_stack)\\n\\n erroneous_tx = self._current_transaction\\n self._current_transaction = None\\n try:\\n with Transaction(self.event_manager):\\n try:\\n erroneous_tx.execute()\\n except Exception as e:\\n logger.error(\\\"Could not roolback transaction\\\")\\n logger.error(e)\\n finally:\\n # Discard all data collected in the rollback \\\"transaction\\\"\\n self._undo_stack = undo_stack\\n\\n self._action_executed()\",\n \"def rollback(self):\\n self._session.rollback()\\n\\n return True\",\n \"def rollback_transaction(self):\\n cursor = self._cursor()\\n cursor.close()\\n self._db.rollback()\\n self._end_transaction()\",\n \"def rollback(self, block: 'Block') -> None:\\n # Check for block validation before rollback\\n self._precommit_data_manager.validate_precommit_block(block)\\n self._precommit_data_manager.rollback(block)\",\n \"async def rollback(self):\\n if not self._active:\\n raise ProfileSessionInactiveError()\\n await self._teardown(commit=False)\\n self._active = False\",\n \"def rollback(self):\\n return self.connection.rollback()\",\n \"def _Dynamic_Rollback(self, transaction, transaction_response,\\n request_id=None):\\n transaction.set_app(self.project_id)\\n\\n try:\\n del self.__tx_actions[transaction.handle()]\\n except KeyError:\\n pass\\n\\n self._RemoteSend(transaction, transaction_response, \\\"Rollback\\\", request_id)\\n \\n return transaction_response\",\n \"def rollback(commit_id):\\n _confirm_branch()\\n \\n require('settings', provided_by=[production, staging])\\n require('branch', provided_by=[stable, master, branch])\\n \\n maintenance_up()\\n checkout_latest()\\n git_reset(commit_id)\\n gzip_assets()\\n deploy_to_s3()\\n maintenance_down()\",\n \"def rollback(self):\\n conn = self.threadingLocal.connection\\n if isinstance(conn, Transaction) and not conn._obsolete:\\n self.threadingLocal.connection.rollback()\",\n \"def rollback(self):\\n # PEP 249\\n raise impala.error.NotSupportedError()\",\n \"def _Rollback(failure, stopping_services, starting_services):\\n def _HandleRollbackError(failure):\\n \\\"\\\"\\\"Ignores rollback error.\\\"\\\"\\\"\\n exc_info = (failure.type, failure.value, failure.tb)\\n logging.error('Failed rolling back configuration',\\n exc_info=exc_info)\\n return True\\n\\n deferred = self.StopServices(starting_services)\\n deferred.addCallback(lambda _: self.StartServices(stopping_services))\\n deferred.addErrback(_HandleRollbackError)\\n # Ignore result for rollback, and return the deploy failure.\\n deferred.addBoth(lambda _: failure)\\n return deferred\",\n \"def Rollback(self, request, global_params=None):\\n config = self.GetMethodConfig('Rollback')\\n return self._RunMethod(\\n config, request, global_params=global_params)\",\n \"def Rollback(self, request, global_params=None):\\n config = self.GetMethodConfig('Rollback')\\n return self._RunMethod(\\n config, request, global_params=global_params)\",\n \"def rollback_action(args, kwargs, was_interrupted, result=None):\\n raise NotImplementedError()\",\n \"def disable_rollback(self) -> bool:\\n return pulumi.get(self, \\\"disable_rollback\\\")\",\n \"def test_rollback():\",\n \"def rollback_workflow(self, execution_id):\\n raise NotImplementedError\",\n \"def rollback(self, dry_run=False, force=False):\\n eh = SimpleErrorHandler()\\n\\n out = self._client.execute('rollback', n=dry_run, f=force, eh=eh)\\n\\n return bool(eh)\",\n \"def rollback(self, context: 'IconScoreContext', _block_height: int, _block_hash: bytes):\\n Logger.info(tag=ROLLBACK_LOG_TAG, msg=\\\"rollback() start\\\")\\n\\n self.prep_address_converter: 'PRepAddressConverter' = context.storage.meta.get_prep_address_converter(context)\\n\\n self.preps = self._load_preps(context)\\n self.term = self._load_term(context)\\n\\n Logger.info(tag=ROLLBACK_LOG_TAG, msg=f\\\"rollback() end: {self.term}\\\")\",\n \"def setTerminusBack(self, new_terminus) :\\n self._terminusBack = new_terminus\",\n \"def test_rollback(self, local_connection):\\n\\n users = self.tables.users\\n connection = local_connection\\n transaction = connection.begin()\\n connection.execute(users.insert(), dict(user_id=1, user_name=\\\"user1\\\"))\\n connection.execute(users.insert(), dict(user_id=2, user_name=\\\"user2\\\"))\\n connection.execute(users.insert(), dict(user_id=3, user_name=\\\"user3\\\"))\\n transaction.rollback()\\n result = connection.exec_driver_sql(\\\"select * from users\\\")\\n assert len(result.fetchall()) == 0\",\n \"def rollback(migrator, database, fake=False, **kwargs):\\n pass\",\n \"def init_for_rollback(self, _req):\\n\\n # Tempoary state and will depends on prior state\\n self.state = \\\"rollback\\\"\\n\\n if \\\"stack_id\\\" in _req.keys():\\n if _req[\\\"stack_id\\\"] is not None:\\n stack_id = _req[\\\"stack_id\\\"].strip()\\n\\n stack_id_elements = stack_id.split('/', 1)\\n if len(stack_id_elements) > 1:\\n self.app_id = stack_id_elements[1]\\n else:\\n self.app_id = stack_id\\n\\n self.logger.debug(\\\"stack_id = \\\" + self.app_id)\\n else:\\n # If the stack fails, stack_id can be null.\\n self.app_id = \\\"none\\\"\\n\\n self.logger.debug(\\\"stack_id = None\\\")\\n else:\\n self.status = \\\"no stack_id in request\\\"\\n return\\n\\n if \\\"suppress_rollback\\\" in _req.keys():\\n self.suppress_rollback = _req[\\\"suppress_rollback\\\"]\\n\\n if \\\"error_message\\\" in _req.keys():\\n # TODO(Gueyoung): analyze the error message.\\n\\n if _req[\\\"error_message\\\"] is None:\\n self.logger.warning(\\\"error message from platform: none\\\")\\n else:\\n self.logger.warning(\\\"error message from platform:\\\" + _req[\\\"error_message\\\"])\",\n \"def rollback_object(self, obj):\\n attribute_manager.rollback(obj)\\n try:\\n self.dirty.remove(obj)\\n except KeyError:\\n pass\\n try:\\n self.deleted.remove(obj)\\n except KeyError:\\n pass\",\n \"def setAbortState(*args):\\n args[0].Controls.AbortState.abort_state = args[1]\",\n \"def tpc_abort(self, transaction):\\n raise NotImplementedError\",\n \"def rollback_skill_v1(self, skill_id, create_rollback_request, **kwargs):\\n # type: (str, CreateRollbackRequest_e7747a32, **Any) -> Union[ApiResponse, object, CreateRollbackResponse_5a2e8250, StandardizedError_f5106a89, BadRequestError_f854b05]\\n operation_name = \\\"rollback_skill_v1\\\"\\n params = locals()\\n for key, val in six.iteritems(params['kwargs']):\\n params[key] = val\\n del params['kwargs']\\n # verify the required parameter 'skill_id' is set\\n if ('skill_id' not in params) or (params['skill_id'] is None):\\n raise ValueError(\\n \\\"Missing the required parameter `skill_id` when calling `\\\" + operation_name + \\\"`\\\")\\n # verify the required parameter 'create_rollback_request' is set\\n if ('create_rollback_request' not in params) or (params['create_rollback_request'] is None):\\n raise ValueError(\\n \\\"Missing the required parameter `create_rollback_request` when calling `\\\" + operation_name + \\\"`\\\")\\n\\n resource_path = '/v1/skills/{skillId}/rollbacks'\\n resource_path = resource_path.replace('{format}', 'json')\\n\\n path_params = {} # type: Dict\\n if 'skill_id' in params:\\n path_params['skillId'] = params['skill_id']\\n\\n query_params = [] # type: List\\n\\n header_params = [] # type: List\\n\\n body_params = None\\n if 'create_rollback_request' in params:\\n body_params = params['create_rollback_request']\\n header_params.append(('Content-type', 'application/json'))\\n header_params.append(('User-Agent', self.user_agent))\\n\\n # Response Type\\n full_response = False\\n if 'full_response' in params:\\n full_response = params['full_response']\\n\\n # Authentication setting\\n access_token = self._lwa_service_client.get_access_token_from_refresh_token()\\n authorization_value = \\\"Bearer \\\" + access_token\\n header_params.append(('Authorization', authorization_value))\\n\\n error_definitions = [] # type: List\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.skill.create_rollback_response.CreateRollbackResponse\\\", status_code=201, message=\\\"Rollback request created; Returns the generated identifier to track the rollback request and returns a URL to track the status in Location header.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.bad_request_error.BadRequestError\\\", status_code=400, message=\\\"Server cannot process the request due to a client error.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\\\", status_code=401, message=\\\"The auth token is invalid/expired or doesn't have access to the resource.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.bad_request_error.BadRequestError\\\", status_code=403, message=\\\"The operation being requested is not allowed.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\\\", status_code=404, message=\\\"The resource being requested is not found.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\\\", status_code=409, message=\\\"The request could not be completed due to a conflict with the current state of the target resource.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\\\", status_code=429, message=\\\"Exceeds the permitted request limit. Throttling criteria includes total requests, per API, ClientId, and CustomerId.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\\\", status_code=500, message=\\\"Internal Server Error.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\\\", status_code=503, message=\\\"Service Unavailable.\\\"))\\n\\n api_response = self.invoke(\\n method=\\\"POST\\\",\\n endpoint=self._api_endpoint,\\n path=resource_path,\\n path_params=path_params,\\n query_params=query_params,\\n header_params=header_params,\\n body=body_params,\\n response_definitions=error_definitions,\\n response_type=\\\"ask_smapi_model.v1.skill.create_rollback_response.CreateRollbackResponse\\\")\\n\\n if full_response:\\n return api_response\\n return api_response.body\",\n \"def test_no_rollback_in_committed_state(self):\\n\\n sess = fixture_session()\\n\\n def fail(*arg, **kw):\\n raise BaseException(\\\"some base exception\\\")\\n\\n with mock.patch.object(\\n testing.db.dialect, \\\"do_rollback\\\", side_effect=fail\\n ) as fail_mock, mock.patch.object(\\n testing.db.dialect,\\n \\\"do_commit\\\",\\n side_effect=testing.db.dialect.do_commit,\\n ) as succeed_mock:\\n # sess.begin() -> commit(). why would do_rollback() be called?\\n # because of connection pool finalize_fairy *after* the commit.\\n # this will cause the conn.close() in session.commit() to fail,\\n # but after the DB commit succeeded.\\n with expect_raises_message(BaseException, \\\"some base exception\\\"):\\n with sess.begin():\\n conn = sess.connection()\\n fairy_conn = conn.connection\\n\\n eq_(succeed_mock.mock_calls, [mock.call(fairy_conn)])\\n eq_(fail_mock.mock_calls, [mock.call(fairy_conn)])\",\n \"def rollback(self, connection):\\n return self.symlink_rollback(connection)\",\n \"def rollback(self):\\n self.stream.seek(0)\",\n \"def restore(self, restore):\\n self._restore = restore\",\n \"def setTransitionEffect(self, *args):\\n return _libsbml.Output_setTransitionEffect(self, *args)\",\n \"def rollback_one(self, migration, force=False):\\n logger.info(\\\"Rolling back %s\\\", migration.id)\\n self.ensure_internal_schema_updated()\\n migration.process_steps(self, \\\"rollback\\\", force=force)\\n self.log_migration(migration, \\\"rollback\\\")\\n with self.transaction():\\n self.unmark_one(migration, log=False)\",\n \"def get_rollback_for_skill_v1(self, skill_id, rollback_request_id, **kwargs):\\n # type: (str, str, **Any) -> Union[ApiResponse, object, StandardizedError_f5106a89, BadRequestError_f854b05, RollbackRequestStatus_71665366]\\n operation_name = \\\"get_rollback_for_skill_v1\\\"\\n params = locals()\\n for key, val in six.iteritems(params['kwargs']):\\n params[key] = val\\n del params['kwargs']\\n # verify the required parameter 'skill_id' is set\\n if ('skill_id' not in params) or (params['skill_id'] is None):\\n raise ValueError(\\n \\\"Missing the required parameter `skill_id` when calling `\\\" + operation_name + \\\"`\\\")\\n # verify the required parameter 'rollback_request_id' is set\\n if ('rollback_request_id' not in params) or (params['rollback_request_id'] is None):\\n raise ValueError(\\n \\\"Missing the required parameter `rollback_request_id` when calling `\\\" + operation_name + \\\"`\\\")\\n\\n resource_path = '/v1/skills/{skillId}/rollbacks/{rollbackRequestId}'\\n resource_path = resource_path.replace('{format}', 'json')\\n\\n path_params = {} # type: Dict\\n if 'skill_id' in params:\\n path_params['skillId'] = params['skill_id']\\n if 'rollback_request_id' in params:\\n path_params['rollbackRequestId'] = params['rollback_request_id']\\n\\n query_params = [] # type: List\\n\\n header_params = [] # type: List\\n\\n body_params = None\\n header_params.append(('Content-type', 'application/json'))\\n header_params.append(('User-Agent', self.user_agent))\\n\\n # Response Type\\n full_response = False\\n if 'full_response' in params:\\n full_response = params['full_response']\\n\\n # Authentication setting\\n access_token = self._lwa_service_client.get_access_token_from_refresh_token()\\n authorization_value = \\\"Bearer \\\" + access_token\\n header_params.append(('Authorization', authorization_value))\\n\\n error_definitions = [] # type: List\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.skill.rollback_request_status.RollbackRequestStatus\\\", status_code=200, message=\\\"Returns the rollback status for a given skillId and rollbackRequestId. Returns the latest rollback status if ~latest is used in place of rollbackRequestId.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.bad_request_error.BadRequestError\\\", status_code=400, message=\\\"Server cannot process the request due to a client error.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\\\", status_code=401, message=\\\"The auth token is invalid/expired or doesn't have access to the resource.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.bad_request_error.BadRequestError\\\", status_code=403, message=\\\"The operation being requested is not allowed.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\\\", status_code=404, message=\\\"The resource being requested is not found.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\\\", status_code=429, message=\\\"Exceeds the permitted request limit. Throttling criteria includes total requests, per API, ClientId, and CustomerId.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\\\", status_code=500, message=\\\"Internal Server Error.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v1.skill.standardized_error.StandardizedError\\\", status_code=503, message=\\\"Service Unavailable.\\\"))\\n\\n api_response = self.invoke(\\n method=\\\"GET\\\",\\n endpoint=self._api_endpoint,\\n path=resource_path,\\n path_params=path_params,\\n query_params=query_params,\\n header_params=header_params,\\n body=body_params,\\n response_definitions=error_definitions,\\n response_type=\\\"ask_smapi_model.v1.skill.rollback_request_status.RollbackRequestStatus\\\")\\n\\n if full_response:\\n return api_response\\n return api_response.body\",\n \"def rollback(self):\\n if len(self.__stack) == 0:\\n raise EmptyStackException()\\n self.__current_pos = self.__stack[-1][0]\\n self.line = self.__stack[-1][1]\\n self.linePos = self.__stack[-1][2]\\n self.__stack = self.__stack[:-1]\",\n \"def rollback(obj, commit):\\n copy = deepcopy(obj)\\n if commit.uses_slots is False:\\n copy.__dict__ = commit.state\\n else:\\n for k, v in commit.state.items():\\n setattr(copy, k, v)\\n\\n return copy\",\n \"def set_reviewing(self, revert=None):\\n self.connection.set_reviewing(self.mturk_id, revert=revert)\\n self.update()\",\n \"def rollback(self):\\n\\t\\traise GeneratorException(\\\"Not implemented\\\")\",\n \"def rollback(self, snapshot):\\n\\n if not self.__settings:\\n return\\n\\n _logger.debug('Performing rollback of data into '\\n 'subsequent harvest period. Metric data and transaction events'\\n 'will be preserved and rolled into next harvest')\\n\\n self.merge_metric_stats(snapshot)\\n self._merge_transaction_events(snapshot, rollback=True)\\n self._merge_synthetics_events(snapshot, rollback=True)\\n self._merge_error_events(snapshot)\\n self._merge_custom_events(snapshot, rollback=True)\\n self._merge_span_events(snapshot, rollback=True)\",\n \"def rollback(self, cursor):\\n\\t\\twith warnings.catch_warnings():\\n\\t\\t\\twarnings.simplefilter(\\\"ignore\\\")\\n\\t\\t\\tconnection = cursor.connection\\n\\t\\tconnection.rollback()\\n\\t\\tself._close_cursor(cursor)\",\n \"def __exit__(self, exception_type, exception_val, trace):\\n if not exception_type:\\n self.commit()\\n else:\\n self.rollback()\\n self.close()\",\n \"def cancel(self):\\n self.session.rollback()\",\n \"def rollback_to(cls, **filters) -> int:\\n return 0\",\n \"def set_trace(stop=True, **kwargs):\\n Qdb(**kwargs).set_trace(sys._getframe().f_back, stop=stop)\\n # We use f_back so that we start in the caller of this function.\",\n \"def rollbackVirtualMachine(self,node,vmid,snapname):\\n post_data = None\\n data = self.connect('post',\\\"nodes/%s/qemu/%s/snapshot/%s/rollback\\\" % (node,vmid,snapname), post_data)\\n return data\",\n \"def test_create_namespaced_deployment_config_rollback_rollback(self):\\n pass\",\n \"def rollback_to(self, name):\\n if not isinstance(name, str) or len(name.strip()) == 0:\\n raise ProgrammingError(\\\"Invalid SAVEPOINT name\\\")\\n self._connection.execute_nonquery(\\n \\\"sql\\\",\\n f\\\"ROLLBACK TO SAVEPOINT {quote_identifier(name)}\\\",\\n True,\\n )\",\n \"def setUndoBlock(self, callback):\\n assert not self.undoBlock, \\\"Cannot add multiple undo blocks (yet)\\\"\\n self.undoBlock = callback\",\n \"def restore(self, commit=True):\\n self.trashed_time = None\\n if commit:\\n self.save()\",\n \"def resume_workflow(self):\\n with self._driver.session() as session:\\n session.write_transaction(tx.set_workflow_state, state='RESUME')\",\n \"def rollback(self):\\n for db in self.values():\\n db.rollback()\",\n \"def begin_commit(self, _stacklevel=1):\\n if self.commit_phase:\\n warnings.warn('the transaction already is on commit phase; '\\n 'begin_commit() method seems called twice or more' +\\n self.format_commit_stack(),\\n category=TransactionWarning,\\n stacklevel=1 + _stacklevel)\\n return\\n self.commit_phase = True\\n if self.session.verbose_transaction_error:\\n self.commit_stack = traceback.format_stack()\\n self.session.client.multi()\",\n \"def Rollback(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\\n raise NotImplementedError()\",\n \"def rollback_unless_managed(self):\\n if not self.is_managed():\\n self.rollback()\",\n \"def setHalt(self):\\n self.set_register(REG_TYPE, SETPOINT_HALT, 'int')\",\n \"def set_as_reverted(self):\\n self.is_revert = False\\n self.update_request.status = 'Reverted'\",\n \"def _rollback_context(self, persister):\\n try:\\n # Rollback the job transactional context.\\n persister.rollback()\\n\\n except _errors.DatabaseError as error:\\n _LOGGER.error(\\n \\\"Error in %s rolling back job's context.\\\",\\n self.__action.__name__, exc_info=error\\n )\\n\\n # Update the job status.\\n self.__result = False\\n message = \\\"Tried to execute action ({0}).\\\".format(\\n self.__action.__name__)\\n self._add_status(Job.ERROR, Job.COMPLETE, message, True)\\n\\n # Finish context which means mark the job as finished\\n # and update procedure's information.\\n self._finish_context(False)\",\n \"def rollback(self, exc):\\n USER.info('%s: Rolling Back Failed Build', self.recipe.name)\\n cascade = False\\n if isinstance(exc, AssertionError):\\n logging.error('Error during verify() of %s', self.recipe.name)\\n cascade = True\\n if cascade or isinstance(exc, PakitLinkError):\\n if not cascade:\\n logging.error('Error during linking of %s', self.recipe.name)\\n walk_and_unlink(self.recipe.install_dir, self.recipe.link_dir)\\n cascade = True\\n if cascade or (not isinstance(exc, PakitLinkError) and\\n not isinstance(exc, AssertionError)):\\n if not cascade:\\n logging.error('Error during build() of %s', self.recipe.name)\\n try:\\n Command('rm -rf ' + self.recipe.install_dir).wait()\\n except PakitCmdError: # pragma: no cover\\n pass\",\n \"def rollback(self): \\r\\n if self._closed:\\r\\n raise Error('The connection to the database has been closed.')\\r\\n for table in self.tables.keys():\\r\\n if self.tables[table].open:\\r\\n self.tables[table].rollback()\\r\\n for table in self.createdTables:\\r\\n if self.tables.has_key(table):\\r\\n if self.tables[table].open:\\r\\n self.tables[table]._close()\\r\\n del self.tables[table]\\r\\n for end in self.tableExtensions:\\r\\n if os.path.exists(self.database+os.sep+table+end):\\r\\n os.remove(self.database+os.sep+table+end)\\r\\n self.createdTables = []\",\n \"def setTransitionEffect(self, *args):\\n return _libsbml.Input_setTransitionEffect(self, *args)\",\n \"def RollbackVdisk(self, data, vdiskid, headers=None, query_params=None, content_type=\\\"application/json\\\"):\\n uri = self.client.base_url + \\\"/vdisks/\\\"+vdiskid+\\\"/rollback\\\"\\n return self.client.post(uri, data, headers, query_params, content_type)\",\n \"def tearDown(self):\\r\\n\\r\\n db.session.rollback()\",\n \"def set_backshift(self, seconds):\\n self._backshift = seconds\",\n \"def rollback(tag):\\n done = run_command(['git', 'tag', '-d', tag])\\n if done.returncode:\\n echo.bold(colors.red(str(done)))\\n sys.exit(done.returncode)\\n echo.cyan('Done:', done.stdout.strip())\",\n \"def tearDown(self):\\n\\n db.session.rollback()\",\n \"def tearDown(self):\\n\\n db.session.rollback()\",\n \"def tearDown(self):\\n\\n db.session.rollback()\",\n \"def tearDown(self):\\n\\n db.session.rollback()\",\n \"def tearDown(self):\\n\\n db.session.rollback()\",\n \"def tearDown(self):\\n\\n db.session.rollback()\",\n \"def tearDown(self):\\n\\n db.session.rollback()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.70415974","0.67804295","0.6566904","0.6302689","0.6279038","0.5817215","0.5795934","0.5751513","0.57504106","0.57360476","0.5729921","0.55963874","0.556732","0.5525788","0.55152684","0.5480133","0.54312456","0.5368917","0.5368417","0.5331688","0.53252345","0.53247476","0.5307641","0.53064","0.5295832","0.52442515","0.5214718","0.5206206","0.5155079","0.5119042","0.51186764","0.5110233","0.508206","0.50786537","0.50686246","0.50377417","0.50234455","0.49660474","0.49654195","0.49452353","0.49452353","0.4943898","0.49219733","0.4920471","0.48623535","0.48318514","0.4810402","0.47943866","0.47360015","0.471403","0.47068852","0.47004518","0.46833044","0.46727318","0.46695036","0.46555656","0.46553478","0.46507975","0.46027255","0.4591403","0.45682022","0.4541442","0.45338187","0.45329905","0.45227095","0.45184395","0.4483597","0.44802892","0.4476577","0.4476555","0.44709474","0.44655","0.44468915","0.44386676","0.44189513","0.43861085","0.43801904","0.4377321","0.4377024","0.43754828","0.4350515","0.43443805","0.4330141","0.43179873","0.43155864","0.431153","0.43100095","0.43036172","0.43029606","0.42720613","0.4261126","0.42520726","0.42411476","0.42411476","0.42411476","0.42411476","0.42411476","0.42411476","0.42411476"],"string":"[\n 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\"0.46507975\",\n \"0.46027255\",\n \"0.4591403\",\n \"0.45682022\",\n \"0.4541442\",\n \"0.45338187\",\n \"0.45329905\",\n \"0.45227095\",\n \"0.45184395\",\n \"0.4483597\",\n \"0.44802892\",\n \"0.4476577\",\n \"0.4476555\",\n \"0.44709474\",\n \"0.44655\",\n \"0.44468915\",\n \"0.44386676\",\n \"0.44189513\",\n \"0.43861085\",\n \"0.43801904\",\n \"0.4377321\",\n \"0.4377024\",\n \"0.43754828\",\n \"0.4350515\",\n \"0.43443805\",\n \"0.4330141\",\n \"0.43179873\",\n \"0.43155864\",\n \"0.431153\",\n \"0.43100095\",\n \"0.43036172\",\n \"0.43029606\",\n \"0.42720613\",\n \"0.4261126\",\n \"0.42520726\",\n \"0.42411476\",\n \"0.42411476\",\n \"0.42411476\",\n \"0.42411476\",\n \"0.42411476\",\n \"0.42411476\",\n \"0.42411476\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6231145"},"document_rank":{"kind":"string","value":"5"}}},{"rowIdx":15592,"cells":{"query":{"kind":"string","value":"ConcludeTransaction marks the 2pc transaction as resolved."},"document":{"kind":"string","value":"def ConcludeTransaction(self, request, context):\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\n context.set_details('Method not implemented!')\n raise NotImplementedError('Method not implemented!')"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def ConcludeTransaction(self, request, context):\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)","def ConcludeTransaction(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\n raise NotImplementedError()","def tpc_finish(self, transaction):\n raise NotImplementedError","def endTransaction(self, transactionID: int) -> None:\n ...","def tpc_abort(self, transaction):\n raise NotImplementedError","def exit_transaction():\n _state.transactions = max(get_transactions() - 1, 0)","def commit_transaction(self) -> None:\n pass","def complete_txn(self,**kwargs):\n \n sync = kwargs.get('sync',False)\n callback = kwargs.get('callback',self.callback)\n #POSIX has no IO completion event for the condition\n # which this function is design to block waiting for.\n # So we wait a reasonable amount of time in the Hope the\n # OS as already done it for us then we call fsync() as\n # a blocking operation to wait for it to do so. (and triggering\n # it early). \n #\n # By waiting we hope that the OS has already completed the\n # action - and we are not causing any additional performance\n # impact by requesting the fsync..\n #\n # We skip the wait though if the do() was called\n # synchronously - say during a log replay.\n if not sync and self.fobjs: time.sleep(self.sync_wait_time)\n for f in self.fobjs:\n fd = f.fileno()\n if fd is not None:\n os.fsync(fd)\n f.close()\n \n self.completed = True\n if callback: callback(self.opid)","def flush_transaction(self):\n self.flush_split()\n if not self.transaction_cancelled:\n if self.transaction_info.account is None and self.account_info and self.account_info.name:\n self.transaction_info.account = self.account_info.name\n if self.transaction_info.is_valid():\n self.transaction_infos.append(self.transaction_info)\n self.transaction_cancelled = False\n self.transaction_info = TransactionInfo()","def abort_transaction(self) -> None:\n pass","def endTxn(self,msg=\"\"):\n\tif self.dbType==\"mysql\":\n\t if self.commitFlag:\n\t self.updateDBAndLog(\"COMMIT\")\n\telif self.dbType==\"sqlite\":\n\t if self.commitFlag:\n\t if self.db.isolation_level:\n\t\t return\n\t query=\"COMMIT\"\n\t counter=0\n\t cu = self.db.cursor()\n\t while 1:\n\t if counter>10: break\n\t\t try:\n self.db.commit() ## sdobbs, 4/19/14\n#\t\t cu.execute(query)\n# self.cursor.execute(query)\n self.updateLog(query)\n break\n\t except:\n\t\t print \"Wait for COMMIT\"\n\t\t gen_util.printExcept()\n\t\t pass\n\t counter+=1\n\t cu.close()\n\n# self.db.commit()\n# cu = self.db.cursor()\n# cu.execute(query)\n# cu.close()\n# self.db.commit()\n# self.updateLog(query)\n\t\n\tif self.verbose and msg:\n\t message = \" End transaction: \"+msg\n\t message+=\", commit flag=%s\"%self.commitFlag\n\t if self.dbType=='sqlite':\n\t message+=\", %s\"%self.db.isolation_level\n\t print message\n\t print\n\t sys.__stdout__.flush()","def abort(self, transaction):\n raise NotImplementedError","def confirm_tend(self, before, after, tx):\n assert True","def end(self):\n conn = self.threadingLocal.connection\n if not isinstance(conn, Transaction):\n return\n if not conn._obsolete:\n conn.rollback()\n self.threadingLocal.connection = self.threadingLocal.old_conn\n del self.threadingLocal.old_conn\n self.threadingLocal.connection.cache.clear()","def finish_transaction(self, *, transaction: \"Transaction\" = None) -> \"TransactionInfo\":\n response = super().finish_transaction(transaction=transaction)\n self._set_transaction_id(\"\")\n return response","def transactionEnd(self):\n self.connection.commit()","def end_phase():\n pass","def _end_transaction(self):\n self._db.autocommit=True","def close(self):\n assert not self.closed\n if self.success:\n run(self.connection, \"COMMIT\")\n else:\n run(self.connection, \"ROLLBACK\")\n self.closed = True\n self.on_close()","def cancel(self):\n self.succeeded = False\n self.reject()","def cancel(self):\n self.succeeded = False\n self.reject()","def cancel(self):\n self.succeeded = False\n self.reject()","def cancel(self):\n self.succeeded = False\n self.reject()","def conclusion():\n\n print('Program ends')","def finish_resource_claim(self, claim):\n if self.disabled:\n return\n\n if self.claims.pop(claim.claim_id, None):\n LOG.info(_(\"Finishing claim: %s\") % claim)\n else:\n LOG.info(_(\"Can't find claim %d. It may have been 'finished' \"\n \"twice, or it has already timed out.\"), claim.claim_id)","def finish(self):\n self._release_locks()\n self._fail_out()","def finalize(self, aborted):\n pass","def complete_write_transaction(self) -> None:\n self.batch.__exit__(*sys.exc_info())\n self.batch = self.genes.batch_writer()","def __exit__(self, exc_type, exc_val, exc_tb):\n session = self.session\n # cancel pending changes\n session.rollback()\n # if self._acquire_lock:\n # # remove the lock\n # session.delete_lock()\n session.close()","def sign_transaction_essence(self, prepared_transaction_data):\n return self._call_account_method(\n 'signTransactionEssence', {\n 'preparedTransactionData': prepared_transaction_data\n }\n )","def commit_transaction(self,xid):\n modlogger.debug( \"end tx:%s\"%xid)\n if xid != self.tx.xid:\n raise InvalidTransaction(xid)\n\n opid = self.new_opid()\n xaction = EndTxOperation(opid,xid)\n self._add_operation(xid,xaction)\n try:\n self.tx.commit()\n except Exception:\n self.tx = None\n #There is an arguement to call abort here...\n # but we don't because our (MysteryMachine) use\n # of this is a bottom layer store, which means the\n # schema should have already ensured the transactions\n # are meaningful and a exceptio here is probably a\n # due to local conditions (like diskspace).\n #\n # If we abort we would have to remove the commit record\n # from the log, and then undo the partial tranasction.\n # by not aborting, and re-raisig we make this the \n # problem of a higher layer. Once the problem is resolved\n # the journal can be replayied making ourselve consistent\n # again.\n #\n # There is one way though of provoking non-recoverable behavour\n # ad that is creating a file in a non-existant dir.\n \n #self.abort_transaction(xid)\n raise\n\n self.tx = None","def begin_commit(self, _stacklevel=1):\n if self.commit_phase:\n warnings.warn('the transaction already is on commit phase; '\n 'begin_commit() method seems called twice or more' +\n self.format_commit_stack(),\n category=TransactionWarning,\n stacklevel=1 + _stacklevel)\n return\n self.commit_phase = True\n if self.session.verbose_transaction_error:\n self.commit_stack = traceback.format_stack()\n self.session.client.multi()","def end_trace(self):\n if self.__tracer is not None:\n elapsed = (datetime.datetime.now().timestamp() * 1000) - self.__start\n self.__tracer.trace(self.__correlation_id, self.__component, self.__operation, round(elapsed))","def Commit(self):\n try:\n acm.BeginTransaction()\n self.__contact.Commit()\n if FIntegrationUtils.FIntegrationUtils.get_acm_version_override() < 2015.4:\n self.__integration_utils.set_additional_info('DateOfBirth', self.__contact, self.__reg_date_of_birth)\n self.__integration_utils.set_additional_info('FirstName', self.__contact, self.__reg_first_name)\n self.__integration_utils.set_additional_info('LastName', self.__contact, self.__reg_last_name)\n self.__integration_utils.set_additional_info('NationalId', self.__contact, self.__reg_national_id)\n self.__integration_utils.set_additional_info('RegContactCrmId', self.__contact, self.__reg_crm_id)\n self.__integration_utils.set_additional_info('RegContExchangeId', self.__contact, self.__reg_exchange_id)\n self.__integration_utils.set_additional_info('UniqueName', self.__contact, self.__reg_unique_name)\n self.__integration_utils.set_additional_info('RegGeneralPartner', self.__contact, self.__is_general_partner)\n acm.CommitTransaction()\n except Exception as e:\n FRegulatoryLogger.ERROR(logger, str(e))\n FRegulatoryLogger.ERROR(logger, \"ABORTING TRANSACTION***********\")\n acm.AbortTransaction()","def test_transaction_explitic_canceling(self):\n\n proxy = self.node.get_proxy('/')\n\n # look under the hood to verify that branches are added\n # recursively\n _latest_root_rev = self.node._branches[None].latest\n adapter_node = _latest_root_rev._children['adapters'][2].node\n self.assertEqual(len(self.node._branches.keys()), 1)\n self.assertEqual(len(adapter_node._branches.keys()), 1)\n\n tx = proxy.open_transaction()\n self.assertEqual(len(self.node._branches.keys()), 2)\n self.assertEqual(len(adapter_node._branches.keys()), 1)\n\n self.make_change(tx, '/adapters/2', 'config.log_level', 4)\n\n self.assertEqual(len(self.node._branches.keys()), 2)\n self.assertEqual(len(adapter_node._branches.keys()), 2)\n\n tx.cancel()\n\n self.assertEqual(len(self.node._branches.keys()), 1)\n self.assertEqual(len(adapter_node._branches.keys()), 1)","def cancel(self):\n if not self.is_cancelled:\n self.will_change_value_for('is_cancelled')\n self.cancelled = True\n # remove our dependencies so that we're ready, properly behaved operations\n # will honor the cancel flag\n self.dependencies.clear()\n self.did_change_value_for('is_cancelled')\n \n if not self.is_executing and not self.is_finished:\n with self.changing('is_finished'):\n self.finished = True","def commit(self):\n if self._transaction is None:\n raise TransactionNotStartedError(\"Cannot call commit without a transaction\")\n else:\n def _resetTxn(result):\n self._transaction = None\n d = self._config.commit(self._transaction)\n d.addCallback(_resetTxn)\n return d","def _finish(self):\n if self.consumer:\n self.consumer.unregisterProducer()\n self.consumer = None\n\n if not self.deferred.called:\n self.deferred.callback(None)","def abort(self) -> None:\n self._connector.abort_transaction()","def closeEvent(self, event):\n if settings.IN_SYNC:\n event.ignore()\n QtGui.QMessageBox.information(self, \"Abort\", \"You are in the middle of \"\n + \"a conflicted merge. Please resolve it first.\")\n else:\n event.accept()","def CloseQueryTransaction(self, trans):\n trans.close()\n self.connections = [x for x in self.connections if x[1] != trans]","def commit(self, transaction):\n raise NotImplementedError","def abort_resource_claim(self, context, claim):\n if self.disabled:\n return\n\n # un-claim the resources:\n if self.claims.pop(claim.claim_id, None):\n LOG.info(_(\"Aborting claim: %s\") % claim)\n values = claim.undo_claim(self.compute_node)\n self.compute_node = self._update(context, values)\n else:\n # can't find the claim. this may mean the claim already timed\n # out or it was already explicitly finished/aborted.\n LOG.info(_(\"Claim %d not found. It either timed out or was \"\n \"already explicitly finished/aborted\"), claim.claim_id)","def end_transaction(self):\r\n self.db.commit(True)","def close(self,):\n if self.tx:\n self.commit_transaction(self.tx.xid)\n self.freeze()","def close(self):\n\n if self.is_context_active:\n raise errors.ExplicitTransactionContextClosing()\n\n if not self.is_active:\n return\n\n self.__do_rollback()\n self._cleanup()","def finalize(self, interrupted=False):\n pass","def incomplete(transaction):\n transaction.block_transfer = True\n transaction.response = Response()\n transaction.response.destination = transaction.request.source\n transaction.response.token = transaction.request.token\n transaction.response.code = defines.Codes.REQUEST_ENTITY_INCOMPLETE.number\n return transaction","def _complete(self,\n timed_out: bool = False,\n exception: Optional[Exception] = None) -> UseCaseResult:\n pass","def test_transaction_canceling(self):\n\n proxy = self.node.get_proxy('/')\n\n # look under the hood to verify that branches are added\n # recursively\n _latest_root_rev = self.node._branches[None].latest\n adapter_node = _latest_root_rev._children['adapters'][2].node\n self.assertEqual(len(self.node._branches.keys()), 1)\n self.assertEqual(len(adapter_node._branches.keys()), 1)\n\n tx = proxy.open_transaction()\n self.assertEqual(len(self.node._branches.keys()), 2)\n self.assertEqual(len(adapter_node._branches.keys()), 1)\n\n self.make_change(tx, '/adapters/2', 'config.log_level', 4)\n\n self.assertEqual(len(self.node._branches.keys()), 2)\n self.assertEqual(len(adapter_node._branches.keys()), 2)\n\n del tx\n\n self.assertEqual(len(self.node._branches.keys()), 1)\n self.assertEqual(len(adapter_node._branches.keys()), 1)","def abort(self):\n if self.transaction:\n token = self.transaction\n self.transaction = None\n self.client.abort(self.creds, token, self.environment)","def finish(self):\n with self._lock: # just to be tidy; lock not really needed to set a boolean\n self._done = True","def do_cancel(self):\r\n self.write({'cancelled': True})","def _finish_context(self, success):\n try:\n # Mark the job as complete.\n self.__complete = True\n\n # Update the job status within the procedure. Currently, if this\n # fails, we are not sure whether the changes have succeeded or\n # not. This is something that needs to be improved in the near\n # future.\n self.__procedure.add_executed_job(self)\n\n except _errors.DatabaseError as error:\n _LOGGER.error(\n \"Error in %s finishing job's context.\",\n self.__action.__name__, exc_info=error\n )","def Confirm(self):\r\n \r\n global references\r\n self.from_ed = self.ed_result.get(\"1.0\",'end-1c')\r\n references.append(self.from_ed)\r\n self.confirm_b.configure(state = 'disabled')\r\n self.discard_b.configure(state = 'disabled')\r\n self.finalresult.configure(state = 'normal')\r\n self.finalresult.delete('1.0', END)\r\n \r\n self.final()","def commit(self):\n self.execute_sql(sql.commit)\n self.under_transaction = False","def begin(self):\n self._in_transaction = True","def finalize(self):\r\n\r\n self._flush()\r\n self.context.close()","def test_finish_processing_i(self):\n # setup\n ledger_api_dialogue, fipa_dialogue = self._setup_fipa_ledger_api_dialogues(self)\n self.transaction_behaviour.processing = ledger_api_dialogue\n\n # operation\n self.transaction_behaviour.failed_processing(ledger_api_dialogue)\n\n # after\n assert self.transaction_behaviour.processing_time == 0.0\n assert self.transaction_behaviour.processing is None","def part_reject_contract(cid):\r\n take_passwd = request.values.get('take_passwd', '')\r\n with engine.with_session() as ss:\r\n cur_contract = ss.query(LxContract).get(cid)\r\n if not sha256_crypt.verify(take_passwd, cur_contract.take_passwd):\r\n return jsonify({'success': False, 'errorMsg': constants.ERROR_CODE[\r\n 'NO_AUTH_CUR_CONTRACT']})\r\n if cur_contract.stage != constants.CONTRACT_STAGE['OWNER_CONFIRM']:\r\n return jsonify({'success': False, 'errorMsg': constants.ERROR_CODE[\r\n 'CONTRACT_STAGE_ERROR']})\r\n # TODO reject contract send message to the owner and set stage to new\r\n # contract\r\n cur_contract.update({'stage': constants.CONTRACT_STAGE['NEW_CONTRACT']})\r\n\r\n return jsonify({'success': True, 'data': 1})","def end(self, commit: bool) -> None:\n ...","def order_finish(self):\r\n logger.info(f'Remaining qty:{self.quantity-self.filled_quantity}')\r\n self.is_active = False\r\n self.is_finished = True\r\n self.is_trading = False\r\n schedule.clear(tag=self.id)\r\n logger.info(f'Order {self.id} is finished')","def test_finishedResetsInteraction(self):\n self.session.start_interaction()\n node = self.session.resolve(\"service1\", \"1.0\")\n self.session.fail_interaction(\"OHNO\")\n self.session.finish_interaction()\n\n self.session.start_interaction()\n # Resolve same node again:\n while True:\n another_node = self.session.resolve(\"service1\", \"1.0\")\n if node.address == another_node.address:\n break\n self.session.finish_interaction()\n\n self.assertPolicyState([self.disco.failurePolicy(node)], 1, 1)","def rollback(self):\n self.success = False\n self.close()","def acknowledge_prepayment(self):\n self.acknowledge_payment()","def CloseUpdateTransaction(self, trans):\n trans.close()\n self.connections = [x for x in self.connections if x[1] != trans]","def complete():\n\n # Check if the client is connected.\n if not session.is_connected():\n return dict(ok=False, error=\"Client not connected\")\n\n # Extract the result ftom the request body.\n body = request.json or {}\n result = body.get(\"result\")\n operation = body.get(\"operation\")\n\n # Mark the operation as solved.\n if manager.solve(session.get_sid(), operation, result):\n return dict(ok=True)\n\n return dict(ok=False, error=\"Operation not queued by this client\")","def finalize(self):\n self.transaction_manager.store_new()\n self.disable_request_timeout()","def finalize_task(self, task):\n self._write_transaction(tx.set_task_state, task=task, state=\"COMPLETED\")\n self._write_transaction(tx.copy_task_outputs, task=task)","def exit(self): \n self.teo_exchange_intent = self.teo_wallet\n self.withdraw_intent = self.euro_wallet\n\n self.register_teo_exchange(self.teo_exchange_intent)\n self.register_withdraw(self.withdraw_intent)\n\n if self.teo_wallet + self.euro_wallet == 0:\n print('Agent exited: ', self.__class__.__name__)\n self.model.schedule.remove(self)","def finishSlotCallback(self):\r\n \r\n self._targetRepositoryModel.unlock(self.lockIndex)\r\n self._targetRepositoryModel.activeIndex = self.lockIndex","def test_execute_transaction_2(self):\n domain_data = test_data_utils.get_trixie_domain_data()\n statement = test_db_utils.domain_stmt(domain_data)\n statements = [statement]\n result = find_domains.execute_transaction(self.connection, statements)\n domain_table_results = test_db_utils.get_data(test_db_utils.domain_table_query)\n with self.subTest():\n self.assertEqual(len(domain_table_results), 1)\n with self.subTest():\n self.assertEqual(result, 0)","def on_cancel(self):\n self.state = CANCELED\n self._reject()","def commit(self) -> None:\n self._connector.commit_transaction()","def commitChanges(self):\n \n ## User is prompted that changes are being committed\n print(\"Committing changes to the CRM and Mailings database...\")\n db_connection.executeQuery(\"COMMIT;\")","def asyn_completed(self):\n if self.info.asyn:\n self.endAsyncWrite(pcaspy.S_casApp_success)","def finalize(self):\n self.__finalTime = self.__last_time\n if (self.__resultsPlace is not None):\n self.__trajRecord.close()\n if self.__spatially_resolved:\n # Normalize the spatial data with time.\n self.__spatial_data /= self.__last_time","def syncDone (self) :\r\n self.ongoing_sync_count -= 1","def commit(self):\n self.success = True\n self.close()","def rollback(self):\n raise TransactionRollback('rollback called outside of transaction')","def release(self, other):\n if RealVector.exact_convolution_inverse:\n self.vector = vu.exact_circular_correlation(self.vector,other.vector)\n else:\n self.vector = vu.circular_convolution(self.vector,other.involution())","def _rollback_context(self, persister):\n try:\n # Rollback the job transactional context.\n persister.rollback()\n\n except _errors.DatabaseError as error:\n _LOGGER.error(\n \"Error in %s rolling back job's context.\",\n self.__action.__name__, exc_info=error\n )\n\n # Update the job status.\n self.__result = False\n message = \"Tried to execute action ({0}).\".format(\n self.__action.__name__)\n self._add_status(Job.ERROR, Job.COMPLETE, message, True)\n\n # Finish context which means mark the job as finished\n # and update procedure's information.\n self._finish_context(False)","async def commit(self):\n if not self._active:\n raise ProfileSessionInactiveError()\n await self._teardown(commit=True)\n self._active = False","def end_commit(self):\n #scn = bpy.context.scene\n #for pt in self.b_pts:\n # point_obj = bpy.data.objects.new(pt.label, None)\n # point_obj.location = pt.location\n # scn.objects.link(point_obj)\n #self.end_commit_post()\n pass","def commit(self):\n if self.transaction:\n self.conn.commit()\n self.transaction = False","def quiesce(self):\n logger.info(\"Interchange Quiesce in progress (stopping and joining all threads)\")\n self._quiesce_event.set()\n self._task_puller_thread.join()\n self._command_thread.join()\n\n logger.info(\"Saving unacked results to disk\")\n try:\n self.results_ack_handler.persist()\n except Exception:\n logger.exception(\"Caught exception while saving unacked results\")\n logger.warning(\"Interchange will continue without saving unacked results\")\n\n # this must be called last to ensure the next interchange run will occur\n self._quiesce_event.clear()","def resume(self):\n pass\n # self.condor_object.release()","def test_after_cancel_checkout(self):\n baseline = createContentInContainer(self.folder, 'stageable_type')\n\n working_copy = self.do_checkout(baseline)\n self.do_cancel(working_copy)\n\n relation = IWCAnnotator(baseline).get_relation()\n self.assertIsNone(relation)\n self.assertIsNone(get_checkout_relation(baseline))","def rollback(self) -> None:\n with self.lock:\n self.wait(self._rollback_gen())","def conclude(self, irc, msg, args, channel, pid):\n if msg.nick in irc.state.channels[channel].ops:\n if channel in self.polls.keys():\n try:\n self.polls[channel][pid]['concluded'] = True\n self._dump(self.polls)\n irc.reply(\"Marked poll #%s (%s) as concluded.\" % (pid, self.polls[channel][pid]['question']))\n except IndexError:\n irc.error(\"'%s' does not have a poll with that index.\")\n except KeyError:\n irc.error(\"This may be a bug with the bot or poll file, please submit an issue at\\\n <https://github.com/IotaSpencer/supyplugins> with all pertinent information.\")\n else:\n irc.error(\"Access Denied.\")","def commit(self):\n self._connection.execute_nonquery(\"sql\", \"COMMIT\", True)","def finish(self):\r\n\r\n self._is_finished = True","def post_dissect(self, s):\n if self.tls_session.triggered_prcs_commit:\n if self.tls_session.prcs is not None:\n self.tls_session.rcs = self.tls_session.prcs\n self.tls_session.prcs = None\n self.tls_session.triggered_prcs_commit = False\n return s","def refine_conflict(self):\n # Start refine conflict\n self._check_status(STATUS_IDLE)\n self._set_status(STATUS_REFINING_CONFLICT)\n self._notify_listeners_start_operation(listener.OPERATION_REFINE_CONFLICT)\n\n # Ensure cpo model is generated with all constraints named\n namecstrs = self.context.model.name_all_constraints\n if not namecstrs:\n self.context.model.name_all_constraints = True\n self.cpostr = None\n self.agent.solver.model_sent = False\n\n # Refine conflict\n msol = self.agent.refine_conflict()\n\n # Restore previous name constraints indicator\n self.context.model.name_all_constraints = namecstrs\n\n # Call listeners with conflict result\n for lstnr in self.listeners:\n lstnr.new_result(self, msol)\n\n # End refine conflict\n self._set_status(STATUS_IDLE)\n self._notify_listeners_end_operation()\n\n return msol","def test_teardown(self):\n assert self.transaction_behaviour.teardown() is None\n self.assert_quantity_in_outbox(0)","def commit_transaction(self):\n cursor = self._cursor()\n cursor.close()\n self._db.commit()\n self._end_transaction()","def stop_region(self):\n self.region_edge = None\n self.region_id = None\n self.region_model.finish_regions()","def endExecute( self ):\n self.oDialogControl.endExecute()","def _finish(self, context):\n if self._on_arrive is not None:\n context.change_state(self._on_arrive)\n else:\n context.revert_state()\n\n arrive_msg = Telegram(context.agent_id, None, MessageTypes.MSG_ARRIVAL, context.location)\n context.world.dispatch(arrive_msg)"],"string":"[\n \"def ConcludeTransaction(self, request, context):\\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)\",\n \"def ConcludeTransaction(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\\n raise NotImplementedError()\",\n \"def tpc_finish(self, transaction):\\n raise NotImplementedError\",\n \"def endTransaction(self, transactionID: int) -> None:\\n ...\",\n \"def tpc_abort(self, transaction):\\n raise NotImplementedError\",\n \"def exit_transaction():\\n _state.transactions = max(get_transactions() - 1, 0)\",\n \"def commit_transaction(self) -> None:\\n pass\",\n \"def complete_txn(self,**kwargs):\\n \\n sync = kwargs.get('sync',False)\\n callback = kwargs.get('callback',self.callback)\\n #POSIX has no IO completion event for the condition\\n # which this function is design to block waiting for.\\n # So we wait a reasonable amount of time in the Hope the\\n # OS as already done it for us then we call fsync() as\\n # a blocking operation to wait for it to do so. (and triggering\\n # it early). \\n #\\n # By waiting we hope that the OS has already completed the\\n # action - and we are not causing any additional performance\\n # impact by requesting the fsync..\\n #\\n # We skip the wait though if the do() was called\\n # synchronously - say during a log replay.\\n if not sync and self.fobjs: time.sleep(self.sync_wait_time)\\n for f in self.fobjs:\\n fd = f.fileno()\\n if fd is not None:\\n os.fsync(fd)\\n f.close()\\n \\n self.completed = True\\n if callback: callback(self.opid)\",\n \"def flush_transaction(self):\\n self.flush_split()\\n if not self.transaction_cancelled:\\n if self.transaction_info.account is None and self.account_info and self.account_info.name:\\n self.transaction_info.account = self.account_info.name\\n if self.transaction_info.is_valid():\\n self.transaction_infos.append(self.transaction_info)\\n self.transaction_cancelled = False\\n self.transaction_info = TransactionInfo()\",\n \"def abort_transaction(self) -> None:\\n pass\",\n \"def endTxn(self,msg=\\\"\\\"):\\n\\tif self.dbType==\\\"mysql\\\":\\n\\t if self.commitFlag:\\n\\t self.updateDBAndLog(\\\"COMMIT\\\")\\n\\telif self.dbType==\\\"sqlite\\\":\\n\\t if self.commitFlag:\\n\\t if self.db.isolation_level:\\n\\t\\t return\\n\\t query=\\\"COMMIT\\\"\\n\\t counter=0\\n\\t cu = self.db.cursor()\\n\\t while 1:\\n\\t if counter>10: break\\n\\t\\t try:\\n self.db.commit() ## sdobbs, 4/19/14\\n#\\t\\t cu.execute(query)\\n# self.cursor.execute(query)\\n self.updateLog(query)\\n break\\n\\t except:\\n\\t\\t print \\\"Wait for COMMIT\\\"\\n\\t\\t gen_util.printExcept()\\n\\t\\t pass\\n\\t counter+=1\\n\\t cu.close()\\n\\n# self.db.commit()\\n# cu = self.db.cursor()\\n# cu.execute(query)\\n# cu.close()\\n# self.db.commit()\\n# self.updateLog(query)\\n\\t\\n\\tif self.verbose and msg:\\n\\t message = \\\" End transaction: \\\"+msg\\n\\t message+=\\\", commit flag=%s\\\"%self.commitFlag\\n\\t if self.dbType=='sqlite':\\n\\t message+=\\\", %s\\\"%self.db.isolation_level\\n\\t print message\\n\\t print\\n\\t sys.__stdout__.flush()\",\n \"def abort(self, transaction):\\n raise NotImplementedError\",\n \"def confirm_tend(self, before, after, tx):\\n assert True\",\n \"def end(self):\\n conn = self.threadingLocal.connection\\n if not isinstance(conn, Transaction):\\n return\\n if not conn._obsolete:\\n conn.rollback()\\n self.threadingLocal.connection = self.threadingLocal.old_conn\\n del self.threadingLocal.old_conn\\n self.threadingLocal.connection.cache.clear()\",\n \"def finish_transaction(self, *, transaction: \\\"Transaction\\\" = None) -> \\\"TransactionInfo\\\":\\n response = super().finish_transaction(transaction=transaction)\\n self._set_transaction_id(\\\"\\\")\\n return response\",\n \"def transactionEnd(self):\\n self.connection.commit()\",\n \"def end_phase():\\n pass\",\n \"def _end_transaction(self):\\n self._db.autocommit=True\",\n \"def close(self):\\n assert not self.closed\\n if self.success:\\n run(self.connection, \\\"COMMIT\\\")\\n else:\\n run(self.connection, \\\"ROLLBACK\\\")\\n self.closed = True\\n self.on_close()\",\n \"def cancel(self):\\n self.succeeded = False\\n self.reject()\",\n \"def cancel(self):\\n self.succeeded = False\\n self.reject()\",\n \"def cancel(self):\\n self.succeeded = False\\n self.reject()\",\n \"def cancel(self):\\n self.succeeded = False\\n self.reject()\",\n \"def conclusion():\\n\\n print('Program ends')\",\n \"def finish_resource_claim(self, claim):\\n if self.disabled:\\n return\\n\\n if self.claims.pop(claim.claim_id, None):\\n LOG.info(_(\\\"Finishing claim: %s\\\") % claim)\\n else:\\n LOG.info(_(\\\"Can't find claim %d. It may have been 'finished' \\\"\\n \\\"twice, or it has already timed out.\\\"), claim.claim_id)\",\n \"def finish(self):\\n self._release_locks()\\n self._fail_out()\",\n \"def finalize(self, aborted):\\n pass\",\n \"def complete_write_transaction(self) -> None:\\n self.batch.__exit__(*sys.exc_info())\\n self.batch = self.genes.batch_writer()\",\n \"def __exit__(self, exc_type, exc_val, exc_tb):\\n session = self.session\\n # cancel pending changes\\n session.rollback()\\n # if self._acquire_lock:\\n # # remove the lock\\n # session.delete_lock()\\n session.close()\",\n \"def sign_transaction_essence(self, prepared_transaction_data):\\n return self._call_account_method(\\n 'signTransactionEssence', {\\n 'preparedTransactionData': prepared_transaction_data\\n }\\n )\",\n \"def commit_transaction(self,xid):\\n modlogger.debug( \\\"end tx:%s\\\"%xid)\\n if xid != self.tx.xid:\\n raise InvalidTransaction(xid)\\n\\n opid = self.new_opid()\\n xaction = EndTxOperation(opid,xid)\\n self._add_operation(xid,xaction)\\n try:\\n self.tx.commit()\\n except Exception:\\n self.tx = None\\n #There is an arguement to call abort here...\\n # but we don't because our (MysteryMachine) use\\n # of this is a bottom layer store, which means the\\n # schema should have already ensured the transactions\\n # are meaningful and a exceptio here is probably a\\n # due to local conditions (like diskspace).\\n #\\n # If we abort we would have to remove the commit record\\n # from the log, and then undo the partial tranasction.\\n # by not aborting, and re-raisig we make this the \\n # problem of a higher layer. Once the problem is resolved\\n # the journal can be replayied making ourselve consistent\\n # again.\\n #\\n # There is one way though of provoking non-recoverable behavour\\n # ad that is creating a file in a non-existant dir.\\n \\n #self.abort_transaction(xid)\\n raise\\n\\n self.tx = None\",\n \"def begin_commit(self, _stacklevel=1):\\n if self.commit_phase:\\n warnings.warn('the transaction already is on commit phase; '\\n 'begin_commit() method seems called twice or more' +\\n self.format_commit_stack(),\\n category=TransactionWarning,\\n stacklevel=1 + _stacklevel)\\n return\\n self.commit_phase = True\\n if self.session.verbose_transaction_error:\\n self.commit_stack = traceback.format_stack()\\n self.session.client.multi()\",\n \"def end_trace(self):\\n if self.__tracer is not None:\\n elapsed = (datetime.datetime.now().timestamp() * 1000) - self.__start\\n self.__tracer.trace(self.__correlation_id, self.__component, self.__operation, round(elapsed))\",\n \"def Commit(self):\\n try:\\n acm.BeginTransaction()\\n self.__contact.Commit()\\n if FIntegrationUtils.FIntegrationUtils.get_acm_version_override() < 2015.4:\\n self.__integration_utils.set_additional_info('DateOfBirth', self.__contact, self.__reg_date_of_birth)\\n self.__integration_utils.set_additional_info('FirstName', self.__contact, self.__reg_first_name)\\n self.__integration_utils.set_additional_info('LastName', self.__contact, self.__reg_last_name)\\n self.__integration_utils.set_additional_info('NationalId', self.__contact, self.__reg_national_id)\\n self.__integration_utils.set_additional_info('RegContactCrmId', self.__contact, self.__reg_crm_id)\\n self.__integration_utils.set_additional_info('RegContExchangeId', self.__contact, self.__reg_exchange_id)\\n self.__integration_utils.set_additional_info('UniqueName', self.__contact, self.__reg_unique_name)\\n self.__integration_utils.set_additional_info('RegGeneralPartner', self.__contact, self.__is_general_partner)\\n acm.CommitTransaction()\\n except Exception as e:\\n FRegulatoryLogger.ERROR(logger, str(e))\\n FRegulatoryLogger.ERROR(logger, \\\"ABORTING TRANSACTION***********\\\")\\n acm.AbortTransaction()\",\n \"def test_transaction_explitic_canceling(self):\\n\\n proxy = self.node.get_proxy('/')\\n\\n # look under the hood to verify that branches are added\\n # recursively\\n _latest_root_rev = self.node._branches[None].latest\\n adapter_node = _latest_root_rev._children['adapters'][2].node\\n self.assertEqual(len(self.node._branches.keys()), 1)\\n self.assertEqual(len(adapter_node._branches.keys()), 1)\\n\\n tx = proxy.open_transaction()\\n self.assertEqual(len(self.node._branches.keys()), 2)\\n self.assertEqual(len(adapter_node._branches.keys()), 1)\\n\\n self.make_change(tx, '/adapters/2', 'config.log_level', 4)\\n\\n self.assertEqual(len(self.node._branches.keys()), 2)\\n self.assertEqual(len(adapter_node._branches.keys()), 2)\\n\\n tx.cancel()\\n\\n self.assertEqual(len(self.node._branches.keys()), 1)\\n self.assertEqual(len(adapter_node._branches.keys()), 1)\",\n \"def cancel(self):\\n if not self.is_cancelled:\\n self.will_change_value_for('is_cancelled')\\n self.cancelled = True\\n # remove our dependencies so that we're ready, properly behaved operations\\n # will honor the cancel flag\\n self.dependencies.clear()\\n self.did_change_value_for('is_cancelled')\\n \\n if not self.is_executing and not self.is_finished:\\n with self.changing('is_finished'):\\n self.finished = True\",\n \"def commit(self):\\n if self._transaction is None:\\n raise TransactionNotStartedError(\\\"Cannot call commit without a transaction\\\")\\n else:\\n def _resetTxn(result):\\n self._transaction = None\\n d = self._config.commit(self._transaction)\\n d.addCallback(_resetTxn)\\n return d\",\n \"def _finish(self):\\n if self.consumer:\\n self.consumer.unregisterProducer()\\n self.consumer = None\\n\\n if not self.deferred.called:\\n self.deferred.callback(None)\",\n \"def abort(self) -> None:\\n self._connector.abort_transaction()\",\n \"def closeEvent(self, event):\\n if settings.IN_SYNC:\\n event.ignore()\\n QtGui.QMessageBox.information(self, \\\"Abort\\\", \\\"You are in the middle of \\\"\\n + \\\"a conflicted merge. Please resolve it first.\\\")\\n else:\\n event.accept()\",\n \"def CloseQueryTransaction(self, trans):\\n trans.close()\\n self.connections = [x for x in self.connections if x[1] != trans]\",\n \"def commit(self, transaction):\\n raise NotImplementedError\",\n \"def abort_resource_claim(self, context, claim):\\n if self.disabled:\\n return\\n\\n # un-claim the resources:\\n if self.claims.pop(claim.claim_id, None):\\n LOG.info(_(\\\"Aborting claim: %s\\\") % claim)\\n values = claim.undo_claim(self.compute_node)\\n self.compute_node = self._update(context, values)\\n else:\\n # can't find the claim. this may mean the claim already timed\\n # out or it was already explicitly finished/aborted.\\n LOG.info(_(\\\"Claim %d not found. It either timed out or was \\\"\\n \\\"already explicitly finished/aborted\\\"), claim.claim_id)\",\n \"def end_transaction(self):\\r\\n self.db.commit(True)\",\n \"def close(self,):\\n if self.tx:\\n self.commit_transaction(self.tx.xid)\\n self.freeze()\",\n \"def close(self):\\n\\n if self.is_context_active:\\n raise errors.ExplicitTransactionContextClosing()\\n\\n if not self.is_active:\\n return\\n\\n self.__do_rollback()\\n self._cleanup()\",\n \"def finalize(self, interrupted=False):\\n pass\",\n \"def incomplete(transaction):\\n transaction.block_transfer = True\\n transaction.response = Response()\\n transaction.response.destination = transaction.request.source\\n transaction.response.token = transaction.request.token\\n transaction.response.code = defines.Codes.REQUEST_ENTITY_INCOMPLETE.number\\n return transaction\",\n \"def _complete(self,\\n timed_out: bool = False,\\n exception: Optional[Exception] = None) -> UseCaseResult:\\n pass\",\n \"def test_transaction_canceling(self):\\n\\n proxy = self.node.get_proxy('/')\\n\\n # look under the hood to verify that branches are added\\n # recursively\\n _latest_root_rev = self.node._branches[None].latest\\n adapter_node = _latest_root_rev._children['adapters'][2].node\\n self.assertEqual(len(self.node._branches.keys()), 1)\\n self.assertEqual(len(adapter_node._branches.keys()), 1)\\n\\n tx = proxy.open_transaction()\\n self.assertEqual(len(self.node._branches.keys()), 2)\\n self.assertEqual(len(adapter_node._branches.keys()), 1)\\n\\n self.make_change(tx, '/adapters/2', 'config.log_level', 4)\\n\\n self.assertEqual(len(self.node._branches.keys()), 2)\\n self.assertEqual(len(adapter_node._branches.keys()), 2)\\n\\n del tx\\n\\n self.assertEqual(len(self.node._branches.keys()), 1)\\n self.assertEqual(len(adapter_node._branches.keys()), 1)\",\n \"def abort(self):\\n if self.transaction:\\n token = self.transaction\\n self.transaction = None\\n self.client.abort(self.creds, token, self.environment)\",\n \"def finish(self):\\n with self._lock: # just to be tidy; lock not really needed to set a boolean\\n self._done = True\",\n \"def do_cancel(self):\\r\\n self.write({'cancelled': True})\",\n \"def _finish_context(self, success):\\n try:\\n # Mark the job as complete.\\n self.__complete = True\\n\\n # Update the job status within the procedure. Currently, if this\\n # fails, we are not sure whether the changes have succeeded or\\n # not. This is something that needs to be improved in the near\\n # future.\\n self.__procedure.add_executed_job(self)\\n\\n except _errors.DatabaseError as error:\\n _LOGGER.error(\\n \\\"Error in %s finishing job's context.\\\",\\n self.__action.__name__, exc_info=error\\n )\",\n \"def Confirm(self):\\r\\n \\r\\n global references\\r\\n self.from_ed = self.ed_result.get(\\\"1.0\\\",'end-1c')\\r\\n references.append(self.from_ed)\\r\\n self.confirm_b.configure(state = 'disabled')\\r\\n self.discard_b.configure(state = 'disabled')\\r\\n self.finalresult.configure(state = 'normal')\\r\\n self.finalresult.delete('1.0', END)\\r\\n \\r\\n self.final()\",\n \"def commit(self):\\n self.execute_sql(sql.commit)\\n self.under_transaction = False\",\n \"def begin(self):\\n self._in_transaction = True\",\n \"def finalize(self):\\r\\n\\r\\n self._flush()\\r\\n self.context.close()\",\n \"def test_finish_processing_i(self):\\n # setup\\n ledger_api_dialogue, fipa_dialogue = self._setup_fipa_ledger_api_dialogues(self)\\n self.transaction_behaviour.processing = ledger_api_dialogue\\n\\n # operation\\n self.transaction_behaviour.failed_processing(ledger_api_dialogue)\\n\\n # after\\n assert self.transaction_behaviour.processing_time == 0.0\\n assert self.transaction_behaviour.processing is None\",\n \"def part_reject_contract(cid):\\r\\n take_passwd = request.values.get('take_passwd', '')\\r\\n with engine.with_session() as ss:\\r\\n cur_contract = ss.query(LxContract).get(cid)\\r\\n if not sha256_crypt.verify(take_passwd, cur_contract.take_passwd):\\r\\n return jsonify({'success': False, 'errorMsg': constants.ERROR_CODE[\\r\\n 'NO_AUTH_CUR_CONTRACT']})\\r\\n if cur_contract.stage != constants.CONTRACT_STAGE['OWNER_CONFIRM']:\\r\\n return jsonify({'success': False, 'errorMsg': constants.ERROR_CODE[\\r\\n 'CONTRACT_STAGE_ERROR']})\\r\\n # TODO reject contract send message to the owner and set stage to new\\r\\n # contract\\r\\n cur_contract.update({'stage': constants.CONTRACT_STAGE['NEW_CONTRACT']})\\r\\n\\r\\n return jsonify({'success': True, 'data': 1})\",\n \"def end(self, commit: bool) -> None:\\n ...\",\n \"def order_finish(self):\\r\\n logger.info(f'Remaining qty:{self.quantity-self.filled_quantity}')\\r\\n self.is_active = False\\r\\n self.is_finished = True\\r\\n self.is_trading = False\\r\\n schedule.clear(tag=self.id)\\r\\n logger.info(f'Order {self.id} is finished')\",\n \"def test_finishedResetsInteraction(self):\\n self.session.start_interaction()\\n node = self.session.resolve(\\\"service1\\\", \\\"1.0\\\")\\n self.session.fail_interaction(\\\"OHNO\\\")\\n self.session.finish_interaction()\\n\\n self.session.start_interaction()\\n # Resolve same node again:\\n while True:\\n another_node = self.session.resolve(\\\"service1\\\", \\\"1.0\\\")\\n if node.address == another_node.address:\\n break\\n self.session.finish_interaction()\\n\\n self.assertPolicyState([self.disco.failurePolicy(node)], 1, 1)\",\n \"def rollback(self):\\n self.success = False\\n self.close()\",\n \"def acknowledge_prepayment(self):\\n self.acknowledge_payment()\",\n \"def CloseUpdateTransaction(self, trans):\\n trans.close()\\n self.connections = [x for x in self.connections if x[1] != trans]\",\n \"def complete():\\n\\n # Check if the client is connected.\\n if not session.is_connected():\\n return dict(ok=False, error=\\\"Client not connected\\\")\\n\\n # Extract the result ftom the request body.\\n body = request.json or {}\\n result = body.get(\\\"result\\\")\\n operation = body.get(\\\"operation\\\")\\n\\n # Mark the operation as solved.\\n if manager.solve(session.get_sid(), operation, result):\\n return dict(ok=True)\\n\\n return dict(ok=False, error=\\\"Operation not queued by this client\\\")\",\n \"def finalize(self):\\n self.transaction_manager.store_new()\\n self.disable_request_timeout()\",\n \"def finalize_task(self, task):\\n self._write_transaction(tx.set_task_state, task=task, state=\\\"COMPLETED\\\")\\n self._write_transaction(tx.copy_task_outputs, task=task)\",\n \"def exit(self): \\n self.teo_exchange_intent = self.teo_wallet\\n self.withdraw_intent = self.euro_wallet\\n\\n self.register_teo_exchange(self.teo_exchange_intent)\\n self.register_withdraw(self.withdraw_intent)\\n\\n if self.teo_wallet + self.euro_wallet == 0:\\n print('Agent exited: ', self.__class__.__name__)\\n self.model.schedule.remove(self)\",\n \"def finishSlotCallback(self):\\r\\n \\r\\n self._targetRepositoryModel.unlock(self.lockIndex)\\r\\n self._targetRepositoryModel.activeIndex = self.lockIndex\",\n \"def test_execute_transaction_2(self):\\n domain_data = test_data_utils.get_trixie_domain_data()\\n statement = test_db_utils.domain_stmt(domain_data)\\n statements = [statement]\\n result = find_domains.execute_transaction(self.connection, statements)\\n domain_table_results = test_db_utils.get_data(test_db_utils.domain_table_query)\\n with self.subTest():\\n self.assertEqual(len(domain_table_results), 1)\\n with self.subTest():\\n self.assertEqual(result, 0)\",\n \"def on_cancel(self):\\n self.state = CANCELED\\n self._reject()\",\n \"def commit(self) -> None:\\n self._connector.commit_transaction()\",\n \"def commitChanges(self):\\n \\n ## User is prompted that changes are being committed\\n print(\\\"Committing changes to the CRM and Mailings database...\\\")\\n db_connection.executeQuery(\\\"COMMIT;\\\")\",\n \"def asyn_completed(self):\\n if self.info.asyn:\\n self.endAsyncWrite(pcaspy.S_casApp_success)\",\n \"def finalize(self):\\n self.__finalTime = self.__last_time\\n if (self.__resultsPlace is not None):\\n self.__trajRecord.close()\\n if self.__spatially_resolved:\\n # Normalize the spatial data with time.\\n self.__spatial_data /= self.__last_time\",\n \"def syncDone (self) :\\r\\n self.ongoing_sync_count -= 1\",\n \"def commit(self):\\n self.success = True\\n self.close()\",\n \"def rollback(self):\\n raise TransactionRollback('rollback called outside of transaction')\",\n \"def release(self, other):\\n if RealVector.exact_convolution_inverse:\\n self.vector = vu.exact_circular_correlation(self.vector,other.vector)\\n else:\\n self.vector = vu.circular_convolution(self.vector,other.involution())\",\n \"def _rollback_context(self, persister):\\n try:\\n # Rollback the job transactional context.\\n persister.rollback()\\n\\n except _errors.DatabaseError as error:\\n _LOGGER.error(\\n \\\"Error in %s rolling back job's context.\\\",\\n self.__action.__name__, exc_info=error\\n )\\n\\n # Update the job status.\\n self.__result = False\\n message = \\\"Tried to execute action ({0}).\\\".format(\\n self.__action.__name__)\\n self._add_status(Job.ERROR, Job.COMPLETE, message, True)\\n\\n # Finish context which means mark the job as finished\\n # and update procedure's information.\\n self._finish_context(False)\",\n \"async def commit(self):\\n if not self._active:\\n raise ProfileSessionInactiveError()\\n await self._teardown(commit=True)\\n self._active = False\",\n \"def end_commit(self):\\n #scn = bpy.context.scene\\n #for pt in self.b_pts:\\n # point_obj = bpy.data.objects.new(pt.label, None)\\n # point_obj.location = pt.location\\n # scn.objects.link(point_obj)\\n #self.end_commit_post()\\n pass\",\n \"def commit(self):\\n if self.transaction:\\n self.conn.commit()\\n self.transaction = False\",\n \"def quiesce(self):\\n logger.info(\\\"Interchange Quiesce in progress (stopping and joining all threads)\\\")\\n self._quiesce_event.set()\\n self._task_puller_thread.join()\\n self._command_thread.join()\\n\\n logger.info(\\\"Saving unacked results to disk\\\")\\n try:\\n self.results_ack_handler.persist()\\n except Exception:\\n logger.exception(\\\"Caught exception while saving unacked results\\\")\\n logger.warning(\\\"Interchange will continue without saving unacked results\\\")\\n\\n # this must be called last to ensure the next interchange run will occur\\n self._quiesce_event.clear()\",\n \"def resume(self):\\n pass\\n # self.condor_object.release()\",\n \"def test_after_cancel_checkout(self):\\n baseline = createContentInContainer(self.folder, 'stageable_type')\\n\\n working_copy = self.do_checkout(baseline)\\n self.do_cancel(working_copy)\\n\\n relation = IWCAnnotator(baseline).get_relation()\\n self.assertIsNone(relation)\\n self.assertIsNone(get_checkout_relation(baseline))\",\n \"def rollback(self) -> None:\\n with self.lock:\\n self.wait(self._rollback_gen())\",\n \"def conclude(self, irc, msg, args, channel, pid):\\n if msg.nick in irc.state.channels[channel].ops:\\n if channel in self.polls.keys():\\n try:\\n self.polls[channel][pid]['concluded'] = True\\n self._dump(self.polls)\\n irc.reply(\\\"Marked poll #%s (%s) as concluded.\\\" % (pid, self.polls[channel][pid]['question']))\\n except IndexError:\\n irc.error(\\\"'%s' does not have a poll with that index.\\\")\\n except KeyError:\\n irc.error(\\\"This may be a bug with the bot or poll file, please submit an issue at\\\\\\n <https://github.com/IotaSpencer/supyplugins> with all pertinent information.\\\")\\n else:\\n irc.error(\\\"Access Denied.\\\")\",\n \"def commit(self):\\n self._connection.execute_nonquery(\\\"sql\\\", \\\"COMMIT\\\", True)\",\n \"def finish(self):\\r\\n\\r\\n self._is_finished = True\",\n \"def post_dissect(self, s):\\n if self.tls_session.triggered_prcs_commit:\\n if self.tls_session.prcs is not None:\\n self.tls_session.rcs = self.tls_session.prcs\\n self.tls_session.prcs = None\\n self.tls_session.triggered_prcs_commit = False\\n return s\",\n \"def refine_conflict(self):\\n # Start refine conflict\\n self._check_status(STATUS_IDLE)\\n self._set_status(STATUS_REFINING_CONFLICT)\\n self._notify_listeners_start_operation(listener.OPERATION_REFINE_CONFLICT)\\n\\n # Ensure cpo model is generated with all constraints named\\n namecstrs = self.context.model.name_all_constraints\\n if not namecstrs:\\n self.context.model.name_all_constraints = True\\n self.cpostr = None\\n self.agent.solver.model_sent = False\\n\\n # Refine conflict\\n msol = self.agent.refine_conflict()\\n\\n # Restore previous name constraints indicator\\n self.context.model.name_all_constraints = namecstrs\\n\\n # Call listeners with conflict result\\n for lstnr in self.listeners:\\n lstnr.new_result(self, msol)\\n\\n # End refine conflict\\n self._set_status(STATUS_IDLE)\\n self._notify_listeners_end_operation()\\n\\n return msol\",\n \"def test_teardown(self):\\n assert self.transaction_behaviour.teardown() is None\\n self.assert_quantity_in_outbox(0)\",\n \"def commit_transaction(self):\\n cursor = self._cursor()\\n cursor.close()\\n self._db.commit()\\n self._end_transaction()\",\n \"def stop_region(self):\\n self.region_edge = None\\n self.region_id = None\\n self.region_model.finish_regions()\",\n \"def endExecute( self ):\\n self.oDialogControl.endExecute()\",\n \"def _finish(self, context):\\n if self._on_arrive is not None:\\n context.change_state(self._on_arrive)\\n else:\\n context.revert_state()\\n\\n arrive_msg = Telegram(context.agent_id, None, MessageTypes.MSG_ARRIVAL, context.location)\\n context.world.dispatch(arrive_msg)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.67960286","0.6696259","0.60833055","0.53630143","0.53046906","0.51564556","0.5111534","0.5006666","0.4965056","0.4959645","0.4903526","0.49033082","0.48385334","0.48318043","0.4801351","0.47558016","0.47272316","0.47141683","0.46993113","0.4675617","0.4675617","0.4675617","0.4675617","0.4641172","0.46187904","0.46122143","0.4600467","0.45882013","0.45730042","0.4561368","0.4561207","0.4559271","0.45544237","0.4550986","0.4543892","0.45394543","0.45293677","0.45079708","0.4505465","0.450363","0.44958124","0.44933337","0.4489702","0.44842094","0.4470277","0.44665468","0.4429723","0.44259417","0.44080377","0.43988615","0.43935856","0.4391658","0.43915802","0.4389373","0.43828633","0.4373082","0.43696535","0.43645376","0.43614885","0.43582824","0.43548745","0.43547818","0.4350363","0.43467638","0.43449718","0.43398327","0.43397936","0.43374527","0.43282467","0.43259907","0.43224233","0.43075633","0.4305137","0.43045932","0.4299486","0.42969275","0.4283779","0.42829102","0.42721626","0.42718795","0.4268613","0.42614433","0.42609197","0.42605916","0.42491823","0.4247842","0.4243307","0.42407575","0.42401034","0.42361113","0.42278436","0.42217097","0.42201775","0.42196345","0.42186627","0.4216638","0.42156243","0.4214116","0.42029408"],"string":"[\n \"0.67960286\",\n \"0.6696259\",\n \"0.60833055\",\n \"0.53630143\",\n \"0.53046906\",\n \"0.51564556\",\n \"0.5111534\",\n \"0.5006666\",\n \"0.4965056\",\n \"0.4959645\",\n \"0.4903526\",\n \"0.49033082\",\n \"0.48385334\",\n \"0.48318043\",\n \"0.4801351\",\n \"0.47558016\",\n \"0.47272316\",\n \"0.47141683\",\n \"0.46993113\",\n \"0.4675617\",\n \"0.4675617\",\n \"0.4675617\",\n \"0.4675617\",\n \"0.4641172\",\n \"0.46187904\",\n \"0.46122143\",\n \"0.4600467\",\n \"0.45882013\",\n \"0.45730042\",\n \"0.4561368\",\n \"0.4561207\",\n \"0.4559271\",\n \"0.45544237\",\n \"0.4550986\",\n \"0.4543892\",\n \"0.45394543\",\n \"0.45293677\",\n \"0.45079708\",\n \"0.4505465\",\n \"0.450363\",\n \"0.44958124\",\n \"0.44933337\",\n \"0.4489702\",\n \"0.44842094\",\n \"0.4470277\",\n \"0.44665468\",\n \"0.4429723\",\n \"0.44259417\",\n \"0.44080377\",\n \"0.43988615\",\n \"0.43935856\",\n \"0.4391658\",\n \"0.43915802\",\n \"0.4389373\",\n \"0.43828633\",\n \"0.4373082\",\n \"0.43696535\",\n \"0.43645376\",\n \"0.43614885\",\n \"0.43582824\",\n \"0.43548745\",\n \"0.43547818\",\n \"0.4350363\",\n \"0.43467638\",\n \"0.43449718\",\n \"0.43398327\",\n \"0.43397936\",\n \"0.43374527\",\n \"0.43282467\",\n \"0.43259907\",\n \"0.43224233\",\n \"0.43075633\",\n \"0.4305137\",\n \"0.43045932\",\n \"0.4299486\",\n \"0.42969275\",\n \"0.4283779\",\n \"0.42829102\",\n \"0.42721626\",\n \"0.42718795\",\n \"0.4268613\",\n \"0.42614433\",\n \"0.42609197\",\n \"0.42605916\",\n \"0.42491823\",\n \"0.4247842\",\n \"0.4243307\",\n \"0.42407575\",\n \"0.42401034\",\n \"0.42361113\",\n \"0.42278436\",\n \"0.42217097\",\n \"0.42201775\",\n \"0.42196345\",\n \"0.42186627\",\n \"0.4216638\",\n \"0.42156243\",\n \"0.4214116\",\n \"0.42029408\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6253946"},"document_rank":{"kind":"string","value":"2"}}},{"rowIdx":15593,"cells":{"query":{"kind":"string","value":"ReadTransaction returns the 2pc transaction info."},"document":{"kind":"string","value":"def ReadTransaction(self, request, context):\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\n context.set_details('Method not implemented!')\n raise NotImplementedError('Method not implemented!')"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def ReadTransaction(self, request, context):\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)","def ReadTransaction(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\n raise NotImplementedError()","def _read_transaction(self, tx_fun, **kwargs):\n # Wrapper for neo4j.Session.read_transaction\n with self._driver.session() as session:\n result = session.read_transaction(tx_fun, **kwargs)\n return result","def raw_get_transaction(cls, txid):\n r = requests.get(cls.MAIN_TX_API.format(txid), timeout=DEFAULT_TIMEOUT)\n r.raise_for_status() # pragma: no cover\n return r.json()","def get_transaction(tx):\n global INVOKE_COUNTER\n INVOKE_COUNTER = INVOKE_COUNTER + 1\n if INVOKE_COUNTER % 3 == 0:\n return \"\"\n else:\n raise_connection_error()","def getrawtransaction(self, txid, verbose=True):\n if verbose:\n return TransactionInfo(**self.proxy.getrawtransaction(txid, 1))\n return self.proxy.getrawtransaction(txid, 0)","def getTransaction(hash, config):\n platon = get_eth_obj(config)\n try:\n # 交易信息\n transaction = dict(platon.getTransaction(hash))\n HexBytes_to_str(transaction)\n # 交易回执信息\n transaction_receipt = dict(platon.getTransactionReceipt(hash))\n HexBytes_to_str(transaction_receipt)\n except Exception as e:\n cust_print('Failed to query transaction information,error message:{}.'.format(e))\n sys.exit(1)\n cust_print('query transaction information successful!', fg='g')\n info = \"transaction:\\n\"\n info += \"{}\\n\".format(json.dumps(dict(transaction), indent=2))\n info += \"\\n\\ntransaction receipt:\\n\"\n info += \"{}\".format(json.dumps(dict(transaction_receipt), indent=2))\n cust_print('{}'.format(info), fg='g')","def getTxnFromData(self, oid, back):\n h = self._read_data_header(back, oid)\n return h.tid","def gettransaction(self, txid):\n return TransactionInfo(**self.proxy.gettransaction(txid))","def get_transaction(self, transaction_id):\n url = self.base_url + 'transactions/' + str(transaction_id)\n self.session.headers.update(self.sign(url))\n resp = self.session.get(url)\n return resp.json()","def get_transaction(self, i):\n\t\treturn self.transactions[i]","def get_transaction(self, i):\n\t\treturn self.transactions[i]","def transaction(self, transaction):\n # Allow for a list of blocks..\n transaction = utils.request_type(transaction)\n\n res = r.get(self.url + self.tx_info + str(transaction))\n return self.execute(res)","def get_tx(txid):\n return requests.get(BASE+f'/api/tx/{txid}').json()","def get_transaction_detail(payload):\n response = requests.post(url, data=payload)\n return response.json()","def get_tx_info(tx):\n\n input_addresses = []\n output_addresses = []\n payments = []\n\n try:\n response = json.loads(make_request('http://tbtc.blockr.io/api/v1/tx/info/' + tx))\n except Exception as e:\n status = json.loads(e.message).get('status')\n if status in ['error', 'fail']:\n return {'from': None, 'to': None, 'amount': None, 'confirmations': 0}\n\n vins = response.get('data').get('vins')\n vouts = response.get('data').get('vouts')\n confirmations = response.get('data').get('confirmations')\n\n for i in range(len(vins)):\n if vins[i].get('address') not in input_addresses:\n input_addresses.append(vins[i].get('address'))\n for i in range(len(vouts)):\n output_addresses.append(vouts[i].get('address'))\n payments.append(vouts[i].get('amount'))\n\n return {'from': input_addresses, 'to': output_addresses, 'amount': payments, 'confirmations': confirmations}","def read_trade() -> dict:\n try:\n ddb_table.get_item(Key = data_to_get)\n except Exception as e:\n _LOGGER.error('Problem updating dynamodb trade data. {0}'.format(e))\n raise Exception('Problem updating dynamodb trade data. {0}'.format(e))","async def process_get_txn(self, int txn) -> str:\n\n return json.dumps(json.loads(await ledger.build_get_txn_request(self.did, txn))['result']['data'])","def readtrans(self, addr):\n self._start_transaction(write=False, address=addr)\n self.address.next = addr\n self.read.next = True\n to = 0\n while self.waitrequest and to < self.timeout:\n yield self.clock.posedge\n self.read.next = False\n self._end_transaction(self.readdata)","def get_transaction(self, i):\n return self.transactions[i]","def test_get_transaction_details_request(self):\n self.trans_details.get_transaction_details(\n trans_id = 123456,\n )","def Transaction(self,OutBuffer, read = 0):\n ReceiveBuffer = create_string_buffer(chr(0) * 0x80)\n TransmitBuffer= create_string_buffer(OutBuffer)\n Transaction = spi_ioc_transfer()\n Transaction.speed_hz = c_uint32(self.Speed)\n Transaction.tx_buf=addressof(TransmitBuffer)\n Transaction.rx_buf=addressof(ReceiveBuffer)\n Transaction.delay_usecs = self.Delay\n if read > 0 and self.Speed!= self.ReadSpeed: # Slow down speed for reading\n Transaction.speed_hz = self.ReadSpeed\n elif read==0 and self.Speed!=self.WriteSpeed:\n Transaction.speed_hz = self.WriteSpeed\n if self.Speed != Transaction.speed_hz:\n self.Speed = Transaction.speed_hz\n self.SetSpeed()\n if read > len(OutBuffer):\n Transaction.len=read\n else:\n Transaction.len= len(OutBuffer)\n Transaction.bits_per_word = self.Bits\n Transaction.cs_change = 0\n Transaction.pad = 0\n # print type(addressof(Transaction))\n ret = ioctl(self.File,SPI_IOC_MESSAGE(1), addressof(Transaction))\n return ret, ReceiveBuffer","def transaction(self, transaction_id: str):\n return get_from_list(self.transactions, \"id\", transaction_id)","def get_transition_details(self, account_id, transaction_id):\n endpoint = 'accounts/{0}/transactions{1}'.format(account_id,\n transaction_id)\n\n return self._api.request(endpoint)","def get_payee_transaction(payee: str) -> Any:\n entry = g.ledger.attributes.payee_transaction(payee)\n return serialise(entry) if entry else None","def get_transaction_isolation(self):\n return self.__aceQLHttpApi.get_transaction_isolation()","def test_read_with_no_locks(self):\n\n transaction = Transaction(\"T1\", TransactionType.READ_WRITE, 1)\n instruction = Instruction(\"R(T1, x2)\")\n\n self.assertEquals(self.data_manager.read(transaction, instruction), \"20\")","def get_transactions():\n\n wallet = \"TTfoWGU2M939cgZm8CksPtz1ytJRM9GiN7\"\n\n url = \"https://api.trongrid.io/v1/accounts/{}/transactions\".format(wallet)\n\n response = requests.request(\"GET\", url)\n\n print(response.text)","def jsonrpc_gettx(self, txid):\n txnw = self.node.storage.db.get(hex2b(txid))\n if txnw is None:\n return {}\n txnw = TxnWrapper.unserialize(SerializationBuffer(txnw))\n info = hex_bytes_in_dict(\n txnw.txn.to_dict())\n\n # Add blockheight\n info['blockheight'] = txnw.timestamp / TIME_MULTIPLIER\n return info","def transaction():\n data = jsonpickle.decode(request.get_data())\n address = data[\"address\"]\n amount = int(data[\"amount\"])\n keyname = data[\"keyname\"]\n\n pkplus, pkminus = wallet.keys(keyname)\n\n my_balance = p2p.query(\"/balance\", address=pkplus)[\"balance\"]\n if my_balance < amount:\n abort(404, description=\"Not enough funds.\")\n\n my_utxo = p2p.query(\"/find-utxos\", address=pkplus, amount=amount)[\"utxos\"]\n rem = sum(utxo.amount for utxo in my_utxo) - amount\n address_amount = [(address, amount)]\n\n assert rem >= 0\n\n if rem > 0:\n address_amount.append((pkplus, rem))\n\n tx = build_transaction(my_utxo, address_amount, pkminus)\n try:\n p2p.broadcast(\"/transaction-pool\", transaction=tx)\n return SUCCESSFUL_PATCH\n except UnsuccessfulPatch:\n payload = jsonpickle.encode(\n {\"message\": \"Transaction wasn't accepted by the network.\"})\n return payload, 420, {\"ContentType\": \"application/json\"}","def get_transaction(id):\n\n transaction = get_db().execute('SELECT * FROM transactions WHERE id = ?', (id, )).fetchone()\n\n if transaction is None:\n abort(404, gettext(\"transaction id %(id)d does not exist.\", id=id))\n\n return transaction","def rpc_getblockchaininfo(self) -> dict:\n return self._call_command([\"getblockchaininfo\"])","def field_2_transaction(cls):\n\n return cls._FIELD_2_TRANSACTION","def get_transaction(self, transaction_id: str) -> Transaction:\n return self.session.get_transaction(\n transaction_id=transaction_id,\n account_or_account_id=self.account_id,\n )","def get_transaction(self, excludes_list):\n response = client.get(self.url, \"transactions\", {\"exclude_hash\": excludes_list})\n if response.status == 200:\n print(\"Transaction successfully received\")\n return Transaction.parse(response.data)\n elif response.status == 404:\n # print(\"no request to be received\")\n return None\n else:\n print(\"Unknown error while requesting transaction\")\n return None","def read():\n # TODO","def get_rawtx(txid):\n return requests.get(BASE+f'/api/rawtx/{txid}').json()['rawtx']","def get_transaction_status(self, transaction_id):\n param_dict = {\n \"vid\": self.vendor_id,\n \"reference\": transaction_id,\n }\n # return with hashed key as required by the documentation\n parameters = {\n 'hash': get_hash(parse_data(param_dict), self.security_key),\n **param_dict\n }\n response = send_request(\n data=parameters,\n url=f\"{B2C_ENDPOINT}transaction/status\"\n )\n return response","def get_chain_info(self, symbol: str): \n return self.trader.fetch_chain_info(symbol)","def part_read_contract(cid):\r\n take_pass = request.values.get('take_passwd', '')\r\n with engine.with_session() as ss:\r\n cur_contract = ss.query(LxContract).get(cid)\r\n if not sha256_crypt.verify(take_pass, cur_contract.take_passwd):\r\n return jsonify({'success': False, 'errorMsg': constants.ERROR_CODE[\r\n 'WRONG_PASS_WORD']})\r\n now_version = cur_contract.version\r\n now_contract_file = cur_contract.__getattribute__(\r\n 'contract_v' + str(now_version))\r\n # print now_contract_file.fpath\r\n contract_content = file_biz.get_contract_content(\r\n now_contract_file.fpath)\r\n return jsonify({'success': True, 'data': contract_content})","def get_transactions_trc20():\n\n wallet = \"TTfoWGU2M939cgZm8CksPtz1ytJRM9GiN7\"\n\n url = \"https://api.trongrid.io/v1/accounts/{}/transactions/trc20\".format(wallet) # noqa: E501\n\n response = requests.request(\"GET\", url)\n\n print(response.text)","def exec_eth_transfer(self, timestamp=-1):\n ticker = self.ticker\n gdax_trading_account = self.trading_acc1\n cex_trading_account = self.trading_acc2\n gdax_eth_amount = gdax_trading_account.get_balance(ticker)\n cex_deposit_address = cex_trading_account.get_crypto_deposit_address(ticker)\n\n # transfer\n gdax_trading_account.transfer_crypto(ticker, cex_deposit_address, gdax_eth_amount)\n\n # audit info\n audit_info = {\n 'ticker': ticker,\n 'action_type': 'exec_eth_transfer',\n 'gdax_eth_amount': gdax_eth_amount,\n 'cex_deposit_address': cex_deposit_address\n }\n return audit_info","def database_transaction_to_rlp_transaction(transaction):\n\n nonce = transaction['nonce']\n value = parse_int(transaction['value'])\n gas = parse_int(transaction['gas'])\n gas_price = parse_int(transaction['gas_price'])\n\n tx = create_transaction(nonce=nonce, gasprice=gas_price, startgas=gas,\n to=transaction['to_address'], value=value,\n data=data_decoder(transaction['data']),\n v=parse_int(transaction['v']),\n r=parse_int(transaction['r']),\n s=parse_int(transaction['s']))\n\n return tx","def getTxDataIn(self):\n \n return self.tx_data_in","async def test_txn_get(self):\n self.stream.preset_response(transaction=Mocks.make_txns('1')[0])\n\n response = await self.get_assert_200('/transactions/1')\n self.stream.assert_valid_request_sent(transaction_id='1')\n\n self.assertNotIn('head', response)\n self.assert_has_valid_link(response, '/transactions/1')\n self.assertIn('data', response)\n self.assert_txns_well_formed(response['data'], '1')","def transaction_type(self) -> str:\n return self.chunks[2].decode(\"ascii\")","async def test_tx_metadata(self):\n data_hex = pkg_resources.resource_string(__name__, os.path.join('data', 'tx_metadata_01.txt'))\n data_bin = binascii.unhexlify(data_hex)\n reader = x.MemoryReaderWriter(bytearray(data_bin))\n ar = xmrb.Archive(reader, False, xmr.hf_versions(9))\n\n msg = xmr.PendingTransaction()\n await ar.root()\n await ar.message(msg)\n\n self.assertEqual(msg.tx_key,\n binascii.unhexlify(b'a0a50810dbc38101a79525823428b500ac936dfea613c73b4864f7260ff26a0b'))\n self.assertEqual(msg.change_dts.amount, 99972803971000)\n self.assertEqual(msg.fee, 9119110000)\n self.assertEqual(msg.construction_data.use_rct, 1)\n self.assertEqual(len(msg.construction_data.extra), 44)\n self.assertEqual(len(msg.construction_data.sources), 1)\n self.assertEqual(msg.construction_data.sources[0].amount, 100000000000000)\n self.assertEqual(msg.construction_data.sources[0].mask,\n binascii.unhexlify(b'2dea8778cf4e89a7f32b5659d674d44795a370a00f79ee9b2ea37c1fcb005c0d'))\n self.assertEqual(len(msg.construction_data.sources[0].outputs), 7)\n self.assertEqual(msg.construction_data.sources[0].outputs[6][0], 1727)\n self.assertEqual(msg.construction_data.sources[0].outputs[6][1].mask,\n binascii.unhexlify(b'2eeec82a970bfa54c35b0b740f6fb0585de14818e3c6dceed75c76fe69e3e449'))\n\n self.assertEqual(len(msg.construction_data.dests), 1)\n self.assertEqual(len(msg.construction_data.splitted_dsts), 2)\n self.assertEqual(msg.construction_data.splitted_dsts[0].amount, 18076919000)\n self.assertEqual(msg.construction_data.splitted_dsts[1].amount, 99972803971000)\n self.assertEqual(len(msg.construction_data.subaddr_indices), 1)\n\n writer = x.MemoryReaderWriter()\n ar2 = xmrb.Archive(writer, True, xmr.hf_versions(9))\n await ar2.root()\n await ar2.message(msg)\n self.assertEqual(data_bin, bytearray(writer.get_buffer()))\n\n msg.construction_data.use_bulletproofs = False\n writer = x.MemoryReaderWriter()\n ar2 = xmrb.Archive(writer, True, xmr.hf_versions(9))\n await ar2.root()\n await ar2.message(msg)","def read_transactions(filename=None):\n if not filename:\n filename = settings.TRANSACTION_FILENAME\n return pd.read_csv(filename, sep='|', parse_dates=[4])","def read(self):\n self._read_into_buffer()\n # print([hex(i) for i in self._buffer])\n\n # check packet header\n if not self._buffer[0:2] == b\"BM\":\n raise RuntimeError(\"Invalid PM2.5 header\")\n\n # check frame length\n frame_len = struct.unpack(\">H\", self._buffer[2:4])[0]\n if frame_len != 28:\n raise RuntimeError(\"Invalid PM2.5 frame length\")\n\n checksum = struct.unpack(\">H\", self._buffer[30:32])[0]\n check = sum(self._buffer[0:30])\n if check != checksum:\n raise RuntimeError(\"Invalid PM2.5 checksum\")\n\n # unpack data\n (\n self.aqi_reading[\"pm10 standard\"],\n self.aqi_reading[\"pm25 standard\"],\n self.aqi_reading[\"pm100 standard\"],\n self.aqi_reading[\"pm10 env\"],\n self.aqi_reading[\"pm25 env\"],\n self.aqi_reading[\"pm100 env\"],\n self.aqi_reading[\"particles 03um\"],\n self.aqi_reading[\"particles 05um\"],\n self.aqi_reading[\"particles 10um\"],\n self.aqi_reading[\"particles 25um\"],\n self.aqi_reading[\"particles 50um\"],\n self.aqi_reading[\"particles 100um\"],\n ) = struct.unpack(\">HHHHHHHHHHHH\", self._buffer[4:28])\n\n return self.aqi_reading","def testnet_receive_coin(self):\n try:\n datas = get_transaction_details(tx_hash=self.tx_hash,\n coin_symbol='bcy')\n except:\n raise ValidationError('Hash da transacao invalido ou nao '\n 'identificado.')\n if datas.get('error'):\n raise ValidationError('Transacao nao encontrada.')\n vals = {'name': datas.get('hash')}\n if datas.get('confirmations') >= 2:\n vals.update({'confirmation': datas.get('confirmations'),\n 'date_time': str(datas.get('confirmed')),\n 'state': 'D',\n 'satoshi': datas.get('outputs')[0].get('value')})\n self.write(vals)\n return datas.get('hash')","def coinbase_transaction(self):\n return self.txns[0]","def get_chain(self):\n app_process = sqlite3.connect('app_process::memory:', check_same_thread=False)\n app_process_cursor = app_process.cursor()\n app_process_cursor.execute(\"SELECT * FROM blockchain LIMIT 1\")\n sol = app_process_cursor.fetchall()\n app_process.commit()\n app_process.close()\n print(sol, \"in get chain\")\n return sol","def getTCData(*args):\n return args[0].Data.TCData.tc_data","def load_data():\n dataFile = open('transactions.json', 'r')\n data = json.load(dataFile)\n transactions = data['transactions']#TID\n items = data['items']#item sets\n return items, transactions","def test_obtain_read_lock_with_ro_transaction(self):\n\n transaction = Transaction(\"T1\", TransactionType.READ_ONLY, 1)\n instruction = Instruction(\"R(T1, x2)\")\n\n self.assertTrue(transaction.transaction_type == TransactionType.READ_ONLY)\n self.assertTrue(self.data_manager.obtain_read_lock(transaction, instruction))","def read_prepare(self):\n # PROTECTED REGION ID(AsyncTabata.prepare_read) ENABLED START #\n return self._prepare\n # PROTECTED REGION END # // AsyncTabata.prepare_read","def deserialize(cls, raw_transaction: bytes) -> Transaction:\n return cls.from_solders(SoldersTx.from_bytes(raw_transaction))","def get_transactions(self, block_name):\n cmd = \"\"\" SELECT * FROM %s WHERE %s = '%s'; \"\"\" %(\n TABLE_TRANSACTIONS, COL_TRANSACTION_BLOCK, block_name)\n\n self.__dbcursor.execute(cmd)\n return self.__dbcursor.fetchall()","def get_Trame(self):\n\n STATUS = 0\n while True:\n\n if STATUS == 0: # buscando comienzo de trama\n byte = self.ser.read(1) # leo byte a byte\n if byte == Parser.ESC:\n byte = self.ser.read(1)\n if byte == Parser.SOF:\n STATUS = 1\n\n if STATUS == 1: # leemos contenido de la trama\n raw = self.ser.read(1)\n LL = ord(raw) #\n raw += self.ser.read(LL-1) # leemos la totalidad del mensaje (menos acceso a puerto)\n STATUS = 0\n\n #if self.verify_CS(raw): # TODO: comprobamos que no hay errores en el checksum\n if True:\n TT = ord(raw[1]) # extraemos el tipo de mensaje para procesar\n for t, value in Parser.tipoMensaje.items():\n if value == TT: # vemos que tipo de trama es\n result = self.tipoProcesado[t](raw) # la mandamos a procesar\n return result\n\n #else: # la trama esta corrupta, leo otra\n # STATUS = 0","def read(self):\n temp = self.bus.read_i2c_block_data(self.address, 0)\n print('temp', temp)\n return_buffer = []\n for i in temp:\n return_buffer += str(chr(int(i)))\n\n return return_buffer","def get_internal_transaction_list(self,\n address: str,\n start_block: Optional[int] = None,\n end_block: Optional[int] = None) -> Tuple[Transaction, ...]:\n ...","def get_transaction_status(self, transactionId):\r\n params = {}\r\n params['TransactionId'] = transactionId\r\n \r\n response = self.make_request(\"GetTransactionStatus\", params)\r\n body = response.read()\r\n if(response.status == 200):\r\n rs = ResultSet()\r\n h = handler.XmlHandler(rs, self)\r\n xml.sax.parseString(body, h)\r\n return rs\r\n else:\r\n raise FPSResponseError(response.status, response.reason, body)","def test_execute_begin_transaction_read_write(self):\n\n instruction = Instruction(\"Begin(T1)\")\n self.transaction_manager.execute(instruction)\n trans1 = self.transaction_manager.transactions[\"T1\"]\n self.assertEquals(len(self.transaction_manager.transactions), 1)\n self.assertEquals(trans1.identifier, \"T1\")\n self.assertEquals(trans1.transaction_type, TransactionType.READ_WRITE)\n self.assertEquals(trans1.start_time, 1)\n self.assertIsNone(trans1.end_time)\n self.assertEquals(trans1.state, TransactionState.RUNNING)","def _i2c_read(self, register, bank=None):\n if bank is not None:\n self.set_bank(bank)\n return self.i2c.read_byte_data(self.address, register)","def get_transactionId(self, data):\n transactionId = data['transactionId']\n return transactionId","def load_transaction(uid, bucket=None):\n if bucket is None:\n bucket = _login_to_service_account()\n\n data = _ObjectStore.get_object_from_json(bucket, Ledger.get_key(uid))\n\n if data is None:\n raise LedgerError(\"There is no transaction recorded in the \"\n \"ledger with UID=%s (at key %s)\" %\n (uid, Ledger.get_key(uid)))\n\n return _TransactionRecord.from_data(data)","def raw_transaction(self) -> CustomRawTransaction:\n enforce(self.is_set(\"raw_transaction\"), \"'raw_transaction' content is not set.\")\n return cast(CustomRawTransaction, self.get(\"raw_transaction\"))","def fetchReadNodeInTree(node):\n readNode = checkDependencies(node, 'Read')\n return readNode","def get_transactions(self, crypto, address, confirmations=1):\n raise NotImplementedError(\n \"This service does not support getting historical transactions. \"\n \"Or rather it has no defined 'get_transactions' method.\"\n )","def get_read_version(self):\n return FutureInt64(self.capi.fdb_transaction_get_read_version(self.tpointer))","def read_transaction_journal(element=None, timeout=default_timeout): \n journal_list = []\n contents = _get_text(RCPT_JOURNAL[\"Items\"]).replace(\"\\n\", \" \")\n \n while len(contents) > 0:\n start = 0\n dollar = contents.find(\"$\")\n end = contents.find(\" \", dollar)\n item = contents[start:dollar-1]\n if end == -1:\n end = len(contents)\n price = contents[dollar:end]\n journal_list.append(item)\n journal_list.append(price)\n contents = contents[end+1:]\n\n journal_list_list = []\n i = 0\n while i < len(journal_list):\n journal_list_list.append(journal_list[i:i+2])\n i+=2\n \n if element is not None:\n if element == 0: element = 1\n return journal_list_list[element-1]\n \n return journal_list_list","def get_transaction(self, txid):\n\n return self._blocks._txns.get(txid)","def populate_transaction(\n self,\n label: dict,\n txid: int,\n read: str,\n write: str,\n transaction: list,\n action: str,\n ):\n method_that_access_table = transaction[\"stacktrace\"][-1]\n class_name_next = re.sub(\n \"/\", \".\", method_that_access_table[\"method\"].split(\", \")[1][1:]\n )\n method_name_next = (\n method_that_access_table[\"method\"].split(\", \")[2].split(\"(\")[0]\n )\n method_signature = \".\".join([class_name_next, method_name_next])\n\n the_sql_query = transaction[\"sql\"]\n\n for tx_read in read:\n if tx_read.casefold() in the_sql_query.casefold():\n self.populate_transaction_read(\n method_signature,\n txid,\n tx_read.casefold(),\n action,\n the_sql_query.casefold(),\n )\n for tx_write in write:\n if tx_write.casefold() in the_sql_query.casefold():\n self.populate_transaction_write(\n method_signature,\n txid,\n tx_write.casefold(),\n action,\n the_sql_query.casefold(),\n )","def test_obtain_read_lock_when_trans_has_exiting_lock(self):\n\n transaction = Transaction(\"T1\", TransactionType.READ_WRITE, 1)\n instruction = Instruction(\"R(T2, x2)\")\n self.assertTrue(self.data_manager.obtain_read_lock(transaction, instruction))\n\n self.assertTrue(\"x2\" in self.data_manager.locks)\n self.assertTrue(self.data_manager.obtain_read_lock(transaction, instruction))","def read(self):\n return self.block.read()","def get(self, iban):\n account = database.get_one(Accounts, iban=iban)\n all_transactions = []\n for transaction in account.transactions:\n all_transactions.append(transaction.id)\n read_account = {\n \"id\": account.id,\n \"name\": account.name,\n \"iban\": account.iban,\n \"balance\": float(account.balance),\n \"currency\": account.currency,\n \"transactions\": all_transactions\n }\n return json.dumps(read_account), 200","def runQueryRead(d, query):\n with d.session() as s:\n results = s.read_transaction(runQuery, query, True)\n return results","def get_nested_transaction(self) -> Optional[SessionTransaction]:\n\n return self._nested_transaction","def _get_transaction(self, hash_bytes: bytes) -> BaseTransaction:\n raise NotImplementedError","def test_wallets_get_transaction_list(self):\n pass","async def get_transactions(self, guild_id, user):\n doc = await self.db[str(guild_id)].find_one({'id': user.id})\n if doc is None or len(doc['transactions']) == 0:\n return -1\n else:\n return doc['transactions']","def in_transaction(self):\n # We likely just changed data - give it a second to catch up\n time.sleep(0.1) # I think I keep reading journal watermark too soon without this\n \n # Get relevant data\n water_mark = pos.read_journal_watermark()\n self.log.info(f\"Watermark: [{water_mark}]\")\n balance = pos.read_balance()['Total']\n self.log.info(f\"Balance: [{balance}]\")\n \n # Decide if we need more checks based on watermark\n if water_mark == \"TRANSACTION IN PROGRESS\":\n self.log.info(\"In Transaction: In Transaction Watermark found\")\n return True\n elif water_mark == \"TRANSACTION COMPLETE\" or water_mark == \"TRANSACTION VOIDED\":\n self.log.info(\"Not in Transaction: Transaction Complete/Voided watermarks found\")\n return False\n else:\n # No watermark - decide based on balance\n if balance == \"$0.00\":\n self.log.info(\"Not in Transaction: $0 balance with no watermark\")\n return False\n else:\n self.log.info(\"In Transaction: Non-$0 balance with no watermark\")\n return True","def send_transaction_and_return_status(self, transaction):\n self.net.send_tx(transaction)\n stati = []\n\n for status in self.net.tx_status_stream(transaction):\n stati.append(status)\n\n return stati","def __handler_get_tx_by_address(self, request, context):\n params = json.loads(request.meta)\n address = params.pop('address', None)\n index = params.pop('index', None)\n\n if address is None or index is None: # or params:\n return loopchain_pb2.Message(code=message_code.Response.fail_illegal_params)\n\n channel_stub = StubCollection().channel_stubs[request.channel]\n future = asyncio.run_coroutine_threadsafe(\n channel_stub.async_task().get_tx_by_address(address, index),\n self.peer_service.inner_service.loop\n )\n tx_list, next_index = future.result()\n tx_list_dumped = json.dumps(tx_list).encode(encoding=conf.PEER_DATA_ENCODING)\n\n return loopchain_pb2.Message(code=message_code.Response.success,\n meta=str(next_index),\n object=tx_list_dumped)","def test_get_transaction_for_identifier(self):\n # Submit a reserve, then use the PDS identifier to get the transaction record\n reserve_kwargs = {\n \"input\": join(self.input_dir, \"pds4_bundle_with_contributors.xml\"),\n \"node\": \"img\",\n \"submitter\": \"my_user@my_node.gov\",\n \"force\": True,\n }\n\n doi_label = self._reserve_action.run(**reserve_kwargs)\n\n dois, _ = self._web_parser.parse_dois_from_label(doi_label)\n doi = dois[0]\n\n transaction_record = self._list_action.transaction_for_identifier(doi.pds_identifier)\n\n self.assertIsInstance(transaction_record, dict)\n\n # Make sure the transaction record aligns with the Doi record\n self.assertEqual(doi.doi, transaction_record[\"doi\"])\n self.assertEqual(doi.pds_identifier, transaction_record[\"identifier\"])\n self.assertEqual(doi.status, transaction_record[\"status\"])\n self.assertEqual(doi.title, transaction_record[\"title\"])\n\n # Ensure we get an exception when searching for an unknown ID value\n with self.assertRaises(UnknownIdentifierException):\n self._list_action.transaction_for_identifier(\"urn:unknown_id\")","def getTransaction(self, hash):\n currBlock = self.getBlock(self.tailBlockHash)\n while currBlock != self.genesisBlock:\n for o_hash in currBlock.transactions:\n if hash == o_hash:\n return currBlock.transactions[hash]\n currBlock = self.getBlock(currBlock.prevHash)\n return None","def showTransactions(self):\n self.scanTransactions()\n txns = []\n\n # Summarize the stats\n for x in range(len(self._trans)):\n stats = self._trans[x]\n trans_time = 0\n remote_calls = 0\n for name, stat in stats:\n trans_time += stat.total_tt\n remote_calls += 1\n txns.append((x, trans_time, remote_calls))\n\n results = [\"TX#\\tTime\\tCalls\",\n \"=\" * 22]\n\n for item in txns:\n results.append(\"%3d\\t%4f\\t%5d\" % item)\n \n return \"\\n\".join(results)","def decoderawtransaction(self, hexstring):\n return dict(self.proxy.decoderawtransaction(hexstring))","def get_latest_transaction():\n\n transaction = get_db().execute('SELECT * FROM transactions ORDER BY id DESC').fetchone()\n\n return transaction","def _read_v2(self):\n return self.usb_dev.read(self.ep_in, self.rdbuf_chunksize, self.usb_rd_timeout)","def check(transaction):\n if not isinstance(transaction, Transaction):\n transaction = Transaction.objects.get(id=transaction)\n\n r = requests.post(\"https://www.blockonomics.co/api/searchhistory\",\n data=json.dumps({\"addr\": transaction.to_address}))\n try:\n history_data = json.loads(r.content.decode('utf-8'))['history'][0]\n except:\n return\n\n set_tx_details(history_data, transaction)","def readData(self, key, context):\n\n print(\"key: {}\".format(key))\n address = _make_benchcontract_address(\"key_{}\".format(key))\n print(\"address: {}\".format(address))\n data = context.get_state(\n [address],\n timeout=self.timeout)\n print(\"readData obtained {} --> {} from state\".format(key, data[\"data\"]))\n return 0","def _check_trans(self, trans, meth):\n if self._is_read_only:\n raise POSException.ReadOnlyError()\n\n try:\n buf = trans.data(self)\n except KeyError:\n buf = None\n\n if buf is None:\n raise POSException.StorageTransactionError(\n \"Transaction not committing\", meth, trans)\n\n if buf.connection_generation != self._connection_generation:\n # We were disconnected, so this one is poisoned\n raise ClientDisconnected(meth, 'on a disconnected transaction')\n\n return buf","def get_chain_data(self, symbol: str): \n return self.trader.fetch_chain_data(symbol)","def get_wallet_info(wallet: str, info: dict):\r\n\t#return if updated recently\r\n\tif 'updated' in info:\r\n\t\tif datetime.datetime.fromisoformat(info['updated']) + datetime.timedelta(days = UPDATE_INTERVAL) > datetime.datetime.now():\r\n\t\t\treturn info\r\n\r\n\t#get the amount of money received to the wallet\r\n\t#these wallets won't have collisions in tags, so it is save to overwrite old amounts\r\n\tapi_delay(info['currency'][0])\r\n\tif 'Bitcoin' in info['currency']:\r\n\t\tget_price('Bitcoin')\r\n\t\tinfo = get_Bitcoin_info(wallet, info)\r\n\tif 'Ethereum' in info['currency']:\r\n\t\tget_price('Ethereum')\r\n\t\tinfo = get_Ethereum_info(wallet, info)\r\n\tif 'Dogecoin' in info['currency']:\r\n\t\tget_price('Dogecoin')\r\n\t\tinfo = get_Dogecoin_info(wallet, info)\r\n\tif 'ReddCoin' in info['currency']:\r\n\t\tget_price('ReddCoin')\r\n\t\tinfo = get_ReddCoin_info(wallet, info)\r\n\treturn info","def get_wallet_info(rpc_user, rpc_pwd):\n data = '{\"jsonrpc\":\"2.0\",\"id\":\"1\",\"method\":\"getwalletinfo\"}'\n return call_rpc(rpc_user, rpc_pwd, data)","def getDataTransaction(self, down, up):\n if down.isDataTransaction():\n return down\n else:\n return up","def get_read_session() -> Session:\n return _read_session()","def read_metadata(self):\n return self.parent.controller.get_tag_metadata()"],"string":"[\n \"def ReadTransaction(self, request, context):\\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)\",\n \"def ReadTransaction(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\\n raise NotImplementedError()\",\n \"def _read_transaction(self, tx_fun, **kwargs):\\n # Wrapper for neo4j.Session.read_transaction\\n with self._driver.session() as session:\\n result = session.read_transaction(tx_fun, **kwargs)\\n return result\",\n \"def raw_get_transaction(cls, txid):\\n r = requests.get(cls.MAIN_TX_API.format(txid), timeout=DEFAULT_TIMEOUT)\\n r.raise_for_status() # pragma: no cover\\n return r.json()\",\n \"def get_transaction(tx):\\n global INVOKE_COUNTER\\n INVOKE_COUNTER = INVOKE_COUNTER + 1\\n if INVOKE_COUNTER % 3 == 0:\\n return \\\"\\\"\\n else:\\n raise_connection_error()\",\n \"def getrawtransaction(self, txid, verbose=True):\\n if verbose:\\n return TransactionInfo(**self.proxy.getrawtransaction(txid, 1))\\n return self.proxy.getrawtransaction(txid, 0)\",\n \"def getTransaction(hash, config):\\n platon = get_eth_obj(config)\\n try:\\n # 交易信息\\n transaction = dict(platon.getTransaction(hash))\\n HexBytes_to_str(transaction)\\n # 交易回执信息\\n transaction_receipt = dict(platon.getTransactionReceipt(hash))\\n HexBytes_to_str(transaction_receipt)\\n except Exception as e:\\n cust_print('Failed to query transaction information,error message:{}.'.format(e))\\n sys.exit(1)\\n cust_print('query transaction information successful!', fg='g')\\n info = \\\"transaction:\\\\n\\\"\\n info += \\\"{}\\\\n\\\".format(json.dumps(dict(transaction), indent=2))\\n info += \\\"\\\\n\\\\ntransaction receipt:\\\\n\\\"\\n info += \\\"{}\\\".format(json.dumps(dict(transaction_receipt), indent=2))\\n cust_print('{}'.format(info), fg='g')\",\n \"def getTxnFromData(self, oid, back):\\n h = self._read_data_header(back, oid)\\n return h.tid\",\n \"def gettransaction(self, txid):\\n return TransactionInfo(**self.proxy.gettransaction(txid))\",\n \"def get_transaction(self, transaction_id):\\n url = self.base_url + 'transactions/' + str(transaction_id)\\n self.session.headers.update(self.sign(url))\\n resp = self.session.get(url)\\n return resp.json()\",\n \"def get_transaction(self, i):\\n\\t\\treturn self.transactions[i]\",\n \"def get_transaction(self, i):\\n\\t\\treturn self.transactions[i]\",\n \"def transaction(self, transaction):\\n # Allow for a list of blocks..\\n transaction = utils.request_type(transaction)\\n\\n res = r.get(self.url + self.tx_info + str(transaction))\\n return self.execute(res)\",\n \"def get_tx(txid):\\n return requests.get(BASE+f'/api/tx/{txid}').json()\",\n \"def get_transaction_detail(payload):\\n response = requests.post(url, data=payload)\\n return response.json()\",\n \"def get_tx_info(tx):\\n\\n input_addresses = []\\n output_addresses = []\\n payments = []\\n\\n try:\\n response = json.loads(make_request('http://tbtc.blockr.io/api/v1/tx/info/' + tx))\\n except Exception as e:\\n status = json.loads(e.message).get('status')\\n if status in ['error', 'fail']:\\n return {'from': None, 'to': None, 'amount': None, 'confirmations': 0}\\n\\n vins = response.get('data').get('vins')\\n vouts = response.get('data').get('vouts')\\n confirmations = response.get('data').get('confirmations')\\n\\n for i in range(len(vins)):\\n if vins[i].get('address') not in input_addresses:\\n input_addresses.append(vins[i].get('address'))\\n for i in range(len(vouts)):\\n output_addresses.append(vouts[i].get('address'))\\n payments.append(vouts[i].get('amount'))\\n\\n return {'from': input_addresses, 'to': output_addresses, 'amount': payments, 'confirmations': confirmations}\",\n \"def read_trade() -> dict:\\n try:\\n ddb_table.get_item(Key = data_to_get)\\n except Exception as e:\\n _LOGGER.error('Problem updating dynamodb trade data. {0}'.format(e))\\n raise Exception('Problem updating dynamodb trade data. {0}'.format(e))\",\n \"async def process_get_txn(self, int txn) -> str:\\n\\n return json.dumps(json.loads(await ledger.build_get_txn_request(self.did, txn))['result']['data'])\",\n \"def readtrans(self, addr):\\n self._start_transaction(write=False, address=addr)\\n self.address.next = addr\\n self.read.next = True\\n to = 0\\n while self.waitrequest and to < self.timeout:\\n yield self.clock.posedge\\n self.read.next = False\\n self._end_transaction(self.readdata)\",\n \"def get_transaction(self, i):\\n return self.transactions[i]\",\n \"def test_get_transaction_details_request(self):\\n self.trans_details.get_transaction_details(\\n trans_id = 123456,\\n )\",\n \"def Transaction(self,OutBuffer, read = 0):\\n ReceiveBuffer = create_string_buffer(chr(0) * 0x80)\\n TransmitBuffer= create_string_buffer(OutBuffer)\\n Transaction = spi_ioc_transfer()\\n Transaction.speed_hz = c_uint32(self.Speed)\\n Transaction.tx_buf=addressof(TransmitBuffer)\\n Transaction.rx_buf=addressof(ReceiveBuffer)\\n Transaction.delay_usecs = self.Delay\\n if read > 0 and self.Speed!= self.ReadSpeed: # Slow down speed for reading\\n Transaction.speed_hz = self.ReadSpeed\\n elif read==0 and self.Speed!=self.WriteSpeed:\\n Transaction.speed_hz = self.WriteSpeed\\n if self.Speed != Transaction.speed_hz:\\n self.Speed = Transaction.speed_hz\\n self.SetSpeed()\\n if read > len(OutBuffer):\\n Transaction.len=read\\n else:\\n Transaction.len= len(OutBuffer)\\n Transaction.bits_per_word = self.Bits\\n Transaction.cs_change = 0\\n Transaction.pad = 0\\n # print type(addressof(Transaction))\\n ret = ioctl(self.File,SPI_IOC_MESSAGE(1), addressof(Transaction))\\n return ret, ReceiveBuffer\",\n \"def transaction(self, transaction_id: str):\\n return get_from_list(self.transactions, \\\"id\\\", transaction_id)\",\n \"def get_transition_details(self, account_id, transaction_id):\\n endpoint = 'accounts/{0}/transactions{1}'.format(account_id,\\n transaction_id)\\n\\n return self._api.request(endpoint)\",\n \"def get_payee_transaction(payee: str) -> Any:\\n entry = g.ledger.attributes.payee_transaction(payee)\\n return serialise(entry) if entry else None\",\n \"def get_transaction_isolation(self):\\n return self.__aceQLHttpApi.get_transaction_isolation()\",\n \"def test_read_with_no_locks(self):\\n\\n transaction = Transaction(\\\"T1\\\", TransactionType.READ_WRITE, 1)\\n instruction = Instruction(\\\"R(T1, x2)\\\")\\n\\n self.assertEquals(self.data_manager.read(transaction, instruction), \\\"20\\\")\",\n \"def get_transactions():\\n\\n wallet = \\\"TTfoWGU2M939cgZm8CksPtz1ytJRM9GiN7\\\"\\n\\n url = \\\"https://api.trongrid.io/v1/accounts/{}/transactions\\\".format(wallet)\\n\\n response = requests.request(\\\"GET\\\", url)\\n\\n print(response.text)\",\n \"def jsonrpc_gettx(self, txid):\\n txnw = self.node.storage.db.get(hex2b(txid))\\n if txnw is None:\\n return {}\\n txnw = TxnWrapper.unserialize(SerializationBuffer(txnw))\\n info = hex_bytes_in_dict(\\n txnw.txn.to_dict())\\n\\n # Add blockheight\\n info['blockheight'] = txnw.timestamp / TIME_MULTIPLIER\\n return info\",\n \"def transaction():\\n data = jsonpickle.decode(request.get_data())\\n address = data[\\\"address\\\"]\\n amount = int(data[\\\"amount\\\"])\\n keyname = data[\\\"keyname\\\"]\\n\\n pkplus, pkminus = wallet.keys(keyname)\\n\\n my_balance = p2p.query(\\\"/balance\\\", address=pkplus)[\\\"balance\\\"]\\n if my_balance < amount:\\n abort(404, description=\\\"Not enough funds.\\\")\\n\\n my_utxo = p2p.query(\\\"/find-utxos\\\", address=pkplus, amount=amount)[\\\"utxos\\\"]\\n rem = sum(utxo.amount for utxo in my_utxo) - amount\\n address_amount = [(address, amount)]\\n\\n assert rem >= 0\\n\\n if rem > 0:\\n address_amount.append((pkplus, rem))\\n\\n tx = build_transaction(my_utxo, address_amount, pkminus)\\n try:\\n p2p.broadcast(\\\"/transaction-pool\\\", transaction=tx)\\n return SUCCESSFUL_PATCH\\n except UnsuccessfulPatch:\\n payload = jsonpickle.encode(\\n {\\\"message\\\": \\\"Transaction wasn't accepted by the network.\\\"})\\n return payload, 420, {\\\"ContentType\\\": \\\"application/json\\\"}\",\n \"def get_transaction(id):\\n\\n transaction = get_db().execute('SELECT * FROM transactions WHERE id = ?', (id, )).fetchone()\\n\\n if transaction is None:\\n abort(404, gettext(\\\"transaction id %(id)d does not exist.\\\", id=id))\\n\\n return transaction\",\n \"def rpc_getblockchaininfo(self) -> dict:\\n return self._call_command([\\\"getblockchaininfo\\\"])\",\n \"def field_2_transaction(cls):\\n\\n return cls._FIELD_2_TRANSACTION\",\n \"def get_transaction(self, transaction_id: str) -> Transaction:\\n return self.session.get_transaction(\\n transaction_id=transaction_id,\\n account_or_account_id=self.account_id,\\n )\",\n \"def get_transaction(self, excludes_list):\\n response = client.get(self.url, \\\"transactions\\\", {\\\"exclude_hash\\\": excludes_list})\\n if response.status == 200:\\n print(\\\"Transaction successfully received\\\")\\n return Transaction.parse(response.data)\\n elif response.status == 404:\\n # print(\\\"no request to be received\\\")\\n return None\\n else:\\n print(\\\"Unknown error while requesting transaction\\\")\\n return None\",\n \"def read():\\n # TODO\",\n \"def get_rawtx(txid):\\n return requests.get(BASE+f'/api/rawtx/{txid}').json()['rawtx']\",\n \"def get_transaction_status(self, transaction_id):\\n param_dict = {\\n \\\"vid\\\": self.vendor_id,\\n \\\"reference\\\": transaction_id,\\n }\\n # return with hashed key as required by the documentation\\n parameters = {\\n 'hash': get_hash(parse_data(param_dict), self.security_key),\\n **param_dict\\n }\\n response = send_request(\\n data=parameters,\\n url=f\\\"{B2C_ENDPOINT}transaction/status\\\"\\n )\\n return response\",\n \"def get_chain_info(self, symbol: str): \\n return self.trader.fetch_chain_info(symbol)\",\n \"def part_read_contract(cid):\\r\\n take_pass = request.values.get('take_passwd', '')\\r\\n with engine.with_session() as ss:\\r\\n cur_contract = ss.query(LxContract).get(cid)\\r\\n if not sha256_crypt.verify(take_pass, cur_contract.take_passwd):\\r\\n return jsonify({'success': False, 'errorMsg': constants.ERROR_CODE[\\r\\n 'WRONG_PASS_WORD']})\\r\\n now_version = cur_contract.version\\r\\n now_contract_file = cur_contract.__getattribute__(\\r\\n 'contract_v' + str(now_version))\\r\\n # print now_contract_file.fpath\\r\\n contract_content = file_biz.get_contract_content(\\r\\n now_contract_file.fpath)\\r\\n return jsonify({'success': True, 'data': contract_content})\",\n \"def get_transactions_trc20():\\n\\n wallet = \\\"TTfoWGU2M939cgZm8CksPtz1ytJRM9GiN7\\\"\\n\\n url = \\\"https://api.trongrid.io/v1/accounts/{}/transactions/trc20\\\".format(wallet) # noqa: E501\\n\\n response = requests.request(\\\"GET\\\", url)\\n\\n print(response.text)\",\n \"def exec_eth_transfer(self, timestamp=-1):\\n ticker = self.ticker\\n gdax_trading_account = self.trading_acc1\\n cex_trading_account = self.trading_acc2\\n gdax_eth_amount = gdax_trading_account.get_balance(ticker)\\n cex_deposit_address = cex_trading_account.get_crypto_deposit_address(ticker)\\n\\n # transfer\\n gdax_trading_account.transfer_crypto(ticker, cex_deposit_address, gdax_eth_amount)\\n\\n # audit info\\n audit_info = {\\n 'ticker': ticker,\\n 'action_type': 'exec_eth_transfer',\\n 'gdax_eth_amount': gdax_eth_amount,\\n 'cex_deposit_address': cex_deposit_address\\n }\\n return audit_info\",\n \"def database_transaction_to_rlp_transaction(transaction):\\n\\n nonce = transaction['nonce']\\n value = parse_int(transaction['value'])\\n gas = parse_int(transaction['gas'])\\n gas_price = parse_int(transaction['gas_price'])\\n\\n tx = create_transaction(nonce=nonce, gasprice=gas_price, startgas=gas,\\n to=transaction['to_address'], value=value,\\n data=data_decoder(transaction['data']),\\n v=parse_int(transaction['v']),\\n r=parse_int(transaction['r']),\\n s=parse_int(transaction['s']))\\n\\n return tx\",\n \"def getTxDataIn(self):\\n \\n return self.tx_data_in\",\n \"async def test_txn_get(self):\\n self.stream.preset_response(transaction=Mocks.make_txns('1')[0])\\n\\n response = await self.get_assert_200('/transactions/1')\\n self.stream.assert_valid_request_sent(transaction_id='1')\\n\\n self.assertNotIn('head', response)\\n self.assert_has_valid_link(response, '/transactions/1')\\n self.assertIn('data', response)\\n self.assert_txns_well_formed(response['data'], '1')\",\n \"def transaction_type(self) -> str:\\n return self.chunks[2].decode(\\\"ascii\\\")\",\n \"async def test_tx_metadata(self):\\n data_hex = pkg_resources.resource_string(__name__, os.path.join('data', 'tx_metadata_01.txt'))\\n data_bin = binascii.unhexlify(data_hex)\\n reader = x.MemoryReaderWriter(bytearray(data_bin))\\n ar = xmrb.Archive(reader, False, xmr.hf_versions(9))\\n\\n msg = xmr.PendingTransaction()\\n await ar.root()\\n await ar.message(msg)\\n\\n self.assertEqual(msg.tx_key,\\n binascii.unhexlify(b'a0a50810dbc38101a79525823428b500ac936dfea613c73b4864f7260ff26a0b'))\\n self.assertEqual(msg.change_dts.amount, 99972803971000)\\n self.assertEqual(msg.fee, 9119110000)\\n self.assertEqual(msg.construction_data.use_rct, 1)\\n self.assertEqual(len(msg.construction_data.extra), 44)\\n self.assertEqual(len(msg.construction_data.sources), 1)\\n self.assertEqual(msg.construction_data.sources[0].amount, 100000000000000)\\n self.assertEqual(msg.construction_data.sources[0].mask,\\n binascii.unhexlify(b'2dea8778cf4e89a7f32b5659d674d44795a370a00f79ee9b2ea37c1fcb005c0d'))\\n self.assertEqual(len(msg.construction_data.sources[0].outputs), 7)\\n self.assertEqual(msg.construction_data.sources[0].outputs[6][0], 1727)\\n self.assertEqual(msg.construction_data.sources[0].outputs[6][1].mask,\\n binascii.unhexlify(b'2eeec82a970bfa54c35b0b740f6fb0585de14818e3c6dceed75c76fe69e3e449'))\\n\\n self.assertEqual(len(msg.construction_data.dests), 1)\\n self.assertEqual(len(msg.construction_data.splitted_dsts), 2)\\n self.assertEqual(msg.construction_data.splitted_dsts[0].amount, 18076919000)\\n self.assertEqual(msg.construction_data.splitted_dsts[1].amount, 99972803971000)\\n self.assertEqual(len(msg.construction_data.subaddr_indices), 1)\\n\\n writer = x.MemoryReaderWriter()\\n ar2 = xmrb.Archive(writer, True, xmr.hf_versions(9))\\n await ar2.root()\\n await ar2.message(msg)\\n self.assertEqual(data_bin, bytearray(writer.get_buffer()))\\n\\n msg.construction_data.use_bulletproofs = False\\n writer = x.MemoryReaderWriter()\\n ar2 = xmrb.Archive(writer, True, xmr.hf_versions(9))\\n await ar2.root()\\n await ar2.message(msg)\",\n \"def read_transactions(filename=None):\\n if not filename:\\n filename = settings.TRANSACTION_FILENAME\\n return pd.read_csv(filename, sep='|', parse_dates=[4])\",\n \"def read(self):\\n self._read_into_buffer()\\n # print([hex(i) for i in self._buffer])\\n\\n # check packet header\\n if not self._buffer[0:2] == b\\\"BM\\\":\\n raise RuntimeError(\\\"Invalid PM2.5 header\\\")\\n\\n # check frame length\\n frame_len = struct.unpack(\\\">H\\\", self._buffer[2:4])[0]\\n if frame_len != 28:\\n raise RuntimeError(\\\"Invalid PM2.5 frame length\\\")\\n\\n checksum = struct.unpack(\\\">H\\\", self._buffer[30:32])[0]\\n check = sum(self._buffer[0:30])\\n if check != checksum:\\n raise RuntimeError(\\\"Invalid PM2.5 checksum\\\")\\n\\n # unpack data\\n (\\n self.aqi_reading[\\\"pm10 standard\\\"],\\n self.aqi_reading[\\\"pm25 standard\\\"],\\n self.aqi_reading[\\\"pm100 standard\\\"],\\n self.aqi_reading[\\\"pm10 env\\\"],\\n self.aqi_reading[\\\"pm25 env\\\"],\\n self.aqi_reading[\\\"pm100 env\\\"],\\n self.aqi_reading[\\\"particles 03um\\\"],\\n self.aqi_reading[\\\"particles 05um\\\"],\\n self.aqi_reading[\\\"particles 10um\\\"],\\n self.aqi_reading[\\\"particles 25um\\\"],\\n self.aqi_reading[\\\"particles 50um\\\"],\\n self.aqi_reading[\\\"particles 100um\\\"],\\n ) = struct.unpack(\\\">HHHHHHHHHHHH\\\", self._buffer[4:28])\\n\\n return self.aqi_reading\",\n \"def testnet_receive_coin(self):\\n try:\\n datas = get_transaction_details(tx_hash=self.tx_hash,\\n coin_symbol='bcy')\\n except:\\n raise ValidationError('Hash da transacao invalido ou nao '\\n 'identificado.')\\n if datas.get('error'):\\n raise ValidationError('Transacao nao encontrada.')\\n vals = {'name': datas.get('hash')}\\n if datas.get('confirmations') >= 2:\\n vals.update({'confirmation': datas.get('confirmations'),\\n 'date_time': str(datas.get('confirmed')),\\n 'state': 'D',\\n 'satoshi': datas.get('outputs')[0].get('value')})\\n self.write(vals)\\n return datas.get('hash')\",\n \"def coinbase_transaction(self):\\n return self.txns[0]\",\n \"def get_chain(self):\\n app_process = sqlite3.connect('app_process::memory:', check_same_thread=False)\\n app_process_cursor = app_process.cursor()\\n app_process_cursor.execute(\\\"SELECT * FROM blockchain LIMIT 1\\\")\\n sol = app_process_cursor.fetchall()\\n app_process.commit()\\n app_process.close()\\n print(sol, \\\"in get chain\\\")\\n return sol\",\n \"def getTCData(*args):\\n return args[0].Data.TCData.tc_data\",\n \"def load_data():\\n dataFile = open('transactions.json', 'r')\\n data = json.load(dataFile)\\n transactions = data['transactions']#TID\\n items = data['items']#item sets\\n return items, transactions\",\n \"def test_obtain_read_lock_with_ro_transaction(self):\\n\\n transaction = Transaction(\\\"T1\\\", TransactionType.READ_ONLY, 1)\\n instruction = Instruction(\\\"R(T1, x2)\\\")\\n\\n self.assertTrue(transaction.transaction_type == TransactionType.READ_ONLY)\\n self.assertTrue(self.data_manager.obtain_read_lock(transaction, instruction))\",\n \"def read_prepare(self):\\n # PROTECTED REGION ID(AsyncTabata.prepare_read) ENABLED START #\\n return self._prepare\\n # PROTECTED REGION END # // AsyncTabata.prepare_read\",\n \"def deserialize(cls, raw_transaction: bytes) -> Transaction:\\n return cls.from_solders(SoldersTx.from_bytes(raw_transaction))\",\n \"def get_transactions(self, block_name):\\n cmd = \\\"\\\"\\\" SELECT * FROM %s WHERE %s = '%s'; \\\"\\\"\\\" %(\\n TABLE_TRANSACTIONS, COL_TRANSACTION_BLOCK, block_name)\\n\\n self.__dbcursor.execute(cmd)\\n return self.__dbcursor.fetchall()\",\n \"def get_Trame(self):\\n\\n STATUS = 0\\n while True:\\n\\n if STATUS == 0: # buscando comienzo de trama\\n byte = self.ser.read(1) # leo byte a byte\\n if byte == Parser.ESC:\\n byte = self.ser.read(1)\\n if byte == Parser.SOF:\\n STATUS = 1\\n\\n if STATUS == 1: # leemos contenido de la trama\\n raw = self.ser.read(1)\\n LL = ord(raw) #\\n raw += self.ser.read(LL-1) # leemos la totalidad del mensaje (menos acceso a puerto)\\n STATUS = 0\\n\\n #if self.verify_CS(raw): # TODO: comprobamos que no hay errores en el checksum\\n if True:\\n TT = ord(raw[1]) # extraemos el tipo de mensaje para procesar\\n for t, value in Parser.tipoMensaje.items():\\n if value == TT: # vemos que tipo de trama es\\n result = self.tipoProcesado[t](raw) # la mandamos a procesar\\n return result\\n\\n #else: # la trama esta corrupta, leo otra\\n # STATUS = 0\",\n \"def read(self):\\n temp = self.bus.read_i2c_block_data(self.address, 0)\\n print('temp', temp)\\n return_buffer = []\\n for i in temp:\\n return_buffer += str(chr(int(i)))\\n\\n return return_buffer\",\n \"def get_internal_transaction_list(self,\\n address: str,\\n start_block: Optional[int] = None,\\n end_block: Optional[int] = None) -> Tuple[Transaction, ...]:\\n ...\",\n \"def get_transaction_status(self, transactionId):\\r\\n params = {}\\r\\n params['TransactionId'] = transactionId\\r\\n \\r\\n response = self.make_request(\\\"GetTransactionStatus\\\", params)\\r\\n body = response.read()\\r\\n if(response.status == 200):\\r\\n rs = ResultSet()\\r\\n h = handler.XmlHandler(rs, self)\\r\\n xml.sax.parseString(body, h)\\r\\n return rs\\r\\n else:\\r\\n raise FPSResponseError(response.status, response.reason, body)\",\n \"def test_execute_begin_transaction_read_write(self):\\n\\n instruction = Instruction(\\\"Begin(T1)\\\")\\n self.transaction_manager.execute(instruction)\\n trans1 = self.transaction_manager.transactions[\\\"T1\\\"]\\n self.assertEquals(len(self.transaction_manager.transactions), 1)\\n self.assertEquals(trans1.identifier, \\\"T1\\\")\\n self.assertEquals(trans1.transaction_type, TransactionType.READ_WRITE)\\n self.assertEquals(trans1.start_time, 1)\\n self.assertIsNone(trans1.end_time)\\n self.assertEquals(trans1.state, TransactionState.RUNNING)\",\n \"def _i2c_read(self, register, bank=None):\\n if bank is not None:\\n self.set_bank(bank)\\n return self.i2c.read_byte_data(self.address, register)\",\n \"def get_transactionId(self, data):\\n transactionId = data['transactionId']\\n return transactionId\",\n \"def load_transaction(uid, bucket=None):\\n if bucket is None:\\n bucket = _login_to_service_account()\\n\\n data = _ObjectStore.get_object_from_json(bucket, Ledger.get_key(uid))\\n\\n if data is None:\\n raise LedgerError(\\\"There is no transaction recorded in the \\\"\\n \\\"ledger with UID=%s (at key %s)\\\" %\\n (uid, Ledger.get_key(uid)))\\n\\n return _TransactionRecord.from_data(data)\",\n \"def raw_transaction(self) -> CustomRawTransaction:\\n enforce(self.is_set(\\\"raw_transaction\\\"), \\\"'raw_transaction' content is not set.\\\")\\n return cast(CustomRawTransaction, self.get(\\\"raw_transaction\\\"))\",\n \"def fetchReadNodeInTree(node):\\n readNode = checkDependencies(node, 'Read')\\n return readNode\",\n \"def get_transactions(self, crypto, address, confirmations=1):\\n raise NotImplementedError(\\n \\\"This service does not support getting historical transactions. \\\"\\n \\\"Or rather it has no defined 'get_transactions' method.\\\"\\n )\",\n \"def get_read_version(self):\\n return FutureInt64(self.capi.fdb_transaction_get_read_version(self.tpointer))\",\n \"def read_transaction_journal(element=None, timeout=default_timeout): \\n journal_list = []\\n contents = _get_text(RCPT_JOURNAL[\\\"Items\\\"]).replace(\\\"\\\\n\\\", \\\" \\\")\\n \\n while len(contents) > 0:\\n start = 0\\n dollar = contents.find(\\\"$\\\")\\n end = contents.find(\\\" \\\", dollar)\\n item = contents[start:dollar-1]\\n if end == -1:\\n end = len(contents)\\n price = contents[dollar:end]\\n journal_list.append(item)\\n journal_list.append(price)\\n contents = contents[end+1:]\\n\\n journal_list_list = []\\n i = 0\\n while i < len(journal_list):\\n journal_list_list.append(journal_list[i:i+2])\\n i+=2\\n \\n if element is not None:\\n if element == 0: element = 1\\n return journal_list_list[element-1]\\n \\n return journal_list_list\",\n \"def get_transaction(self, txid):\\n\\n return self._blocks._txns.get(txid)\",\n \"def populate_transaction(\\n self,\\n label: dict,\\n txid: int,\\n read: str,\\n write: str,\\n transaction: list,\\n action: str,\\n ):\\n method_that_access_table = transaction[\\\"stacktrace\\\"][-1]\\n class_name_next = re.sub(\\n \\\"/\\\", \\\".\\\", method_that_access_table[\\\"method\\\"].split(\\\", \\\")[1][1:]\\n )\\n method_name_next = (\\n method_that_access_table[\\\"method\\\"].split(\\\", \\\")[2].split(\\\"(\\\")[0]\\n )\\n method_signature = \\\".\\\".join([class_name_next, method_name_next])\\n\\n the_sql_query = transaction[\\\"sql\\\"]\\n\\n for tx_read in read:\\n if tx_read.casefold() in the_sql_query.casefold():\\n self.populate_transaction_read(\\n method_signature,\\n txid,\\n tx_read.casefold(),\\n action,\\n the_sql_query.casefold(),\\n )\\n for tx_write in write:\\n if tx_write.casefold() in the_sql_query.casefold():\\n self.populate_transaction_write(\\n method_signature,\\n txid,\\n tx_write.casefold(),\\n action,\\n the_sql_query.casefold(),\\n )\",\n \"def test_obtain_read_lock_when_trans_has_exiting_lock(self):\\n\\n transaction = Transaction(\\\"T1\\\", TransactionType.READ_WRITE, 1)\\n instruction = Instruction(\\\"R(T2, x2)\\\")\\n self.assertTrue(self.data_manager.obtain_read_lock(transaction, instruction))\\n\\n self.assertTrue(\\\"x2\\\" in self.data_manager.locks)\\n self.assertTrue(self.data_manager.obtain_read_lock(transaction, instruction))\",\n \"def read(self):\\n return self.block.read()\",\n \"def get(self, iban):\\n account = database.get_one(Accounts, iban=iban)\\n all_transactions = []\\n for transaction in account.transactions:\\n all_transactions.append(transaction.id)\\n read_account = {\\n \\\"id\\\": account.id,\\n \\\"name\\\": account.name,\\n \\\"iban\\\": account.iban,\\n \\\"balance\\\": float(account.balance),\\n \\\"currency\\\": account.currency,\\n \\\"transactions\\\": all_transactions\\n }\\n return json.dumps(read_account), 200\",\n \"def runQueryRead(d, query):\\n with d.session() as s:\\n results = s.read_transaction(runQuery, query, True)\\n return results\",\n \"def get_nested_transaction(self) -> Optional[SessionTransaction]:\\n\\n return self._nested_transaction\",\n \"def _get_transaction(self, hash_bytes: bytes) -> BaseTransaction:\\n raise NotImplementedError\",\n \"def test_wallets_get_transaction_list(self):\\n pass\",\n \"async def get_transactions(self, guild_id, user):\\n doc = await self.db[str(guild_id)].find_one({'id': user.id})\\n if doc is None or len(doc['transactions']) == 0:\\n return -1\\n else:\\n return doc['transactions']\",\n \"def in_transaction(self):\\n # We likely just changed data - give it a second to catch up\\n time.sleep(0.1) # I think I keep reading journal watermark too soon without this\\n \\n # Get relevant data\\n water_mark = pos.read_journal_watermark()\\n self.log.info(f\\\"Watermark: [{water_mark}]\\\")\\n balance = pos.read_balance()['Total']\\n self.log.info(f\\\"Balance: [{balance}]\\\")\\n \\n # Decide if we need more checks based on watermark\\n if water_mark == \\\"TRANSACTION IN PROGRESS\\\":\\n self.log.info(\\\"In Transaction: In Transaction Watermark found\\\")\\n return True\\n elif water_mark == \\\"TRANSACTION COMPLETE\\\" or water_mark == \\\"TRANSACTION VOIDED\\\":\\n self.log.info(\\\"Not in Transaction: Transaction Complete/Voided watermarks found\\\")\\n return False\\n else:\\n # No watermark - decide based on balance\\n if balance == \\\"$0.00\\\":\\n self.log.info(\\\"Not in Transaction: $0 balance with no watermark\\\")\\n return False\\n else:\\n self.log.info(\\\"In Transaction: Non-$0 balance with no watermark\\\")\\n return True\",\n \"def send_transaction_and_return_status(self, transaction):\\n self.net.send_tx(transaction)\\n stati = []\\n\\n for status in self.net.tx_status_stream(transaction):\\n stati.append(status)\\n\\n return stati\",\n \"def __handler_get_tx_by_address(self, request, context):\\n params = json.loads(request.meta)\\n address = params.pop('address', None)\\n index = params.pop('index', None)\\n\\n if address is None or index is None: # or params:\\n return loopchain_pb2.Message(code=message_code.Response.fail_illegal_params)\\n\\n channel_stub = StubCollection().channel_stubs[request.channel]\\n future = asyncio.run_coroutine_threadsafe(\\n channel_stub.async_task().get_tx_by_address(address, index),\\n self.peer_service.inner_service.loop\\n )\\n tx_list, next_index = future.result()\\n tx_list_dumped = json.dumps(tx_list).encode(encoding=conf.PEER_DATA_ENCODING)\\n\\n return loopchain_pb2.Message(code=message_code.Response.success,\\n meta=str(next_index),\\n object=tx_list_dumped)\",\n \"def test_get_transaction_for_identifier(self):\\n # Submit a reserve, then use the PDS identifier to get the transaction record\\n reserve_kwargs = {\\n \\\"input\\\": join(self.input_dir, \\\"pds4_bundle_with_contributors.xml\\\"),\\n \\\"node\\\": \\\"img\\\",\\n \\\"submitter\\\": \\\"my_user@my_node.gov\\\",\\n \\\"force\\\": True,\\n }\\n\\n doi_label = self._reserve_action.run(**reserve_kwargs)\\n\\n dois, _ = self._web_parser.parse_dois_from_label(doi_label)\\n doi = dois[0]\\n\\n transaction_record = self._list_action.transaction_for_identifier(doi.pds_identifier)\\n\\n self.assertIsInstance(transaction_record, dict)\\n\\n # Make sure the transaction record aligns with the Doi record\\n self.assertEqual(doi.doi, transaction_record[\\\"doi\\\"])\\n self.assertEqual(doi.pds_identifier, transaction_record[\\\"identifier\\\"])\\n self.assertEqual(doi.status, transaction_record[\\\"status\\\"])\\n self.assertEqual(doi.title, transaction_record[\\\"title\\\"])\\n\\n # Ensure we get an exception when searching for an unknown ID value\\n with self.assertRaises(UnknownIdentifierException):\\n self._list_action.transaction_for_identifier(\\\"urn:unknown_id\\\")\",\n \"def getTransaction(self, hash):\\n currBlock = self.getBlock(self.tailBlockHash)\\n while currBlock != self.genesisBlock:\\n for o_hash in currBlock.transactions:\\n if hash == o_hash:\\n return currBlock.transactions[hash]\\n currBlock = self.getBlock(currBlock.prevHash)\\n return None\",\n \"def showTransactions(self):\\n self.scanTransactions()\\n txns = []\\n\\n # Summarize the stats\\n for x in range(len(self._trans)):\\n stats = self._trans[x]\\n trans_time = 0\\n remote_calls = 0\\n for name, stat in stats:\\n trans_time += stat.total_tt\\n remote_calls += 1\\n txns.append((x, trans_time, remote_calls))\\n\\n results = [\\\"TX#\\\\tTime\\\\tCalls\\\",\\n \\\"=\\\" * 22]\\n\\n for item in txns:\\n results.append(\\\"%3d\\\\t%4f\\\\t%5d\\\" % item)\\n \\n return \\\"\\\\n\\\".join(results)\",\n \"def decoderawtransaction(self, hexstring):\\n return dict(self.proxy.decoderawtransaction(hexstring))\",\n \"def get_latest_transaction():\\n\\n transaction = get_db().execute('SELECT * FROM transactions ORDER BY id DESC').fetchone()\\n\\n return transaction\",\n \"def _read_v2(self):\\n return self.usb_dev.read(self.ep_in, self.rdbuf_chunksize, self.usb_rd_timeout)\",\n \"def check(transaction):\\n if not isinstance(transaction, Transaction):\\n transaction = Transaction.objects.get(id=transaction)\\n\\n r = requests.post(\\\"https://www.blockonomics.co/api/searchhistory\\\",\\n data=json.dumps({\\\"addr\\\": transaction.to_address}))\\n try:\\n history_data = json.loads(r.content.decode('utf-8'))['history'][0]\\n except:\\n return\\n\\n set_tx_details(history_data, transaction)\",\n \"def readData(self, key, context):\\n\\n print(\\\"key: {}\\\".format(key))\\n address = _make_benchcontract_address(\\\"key_{}\\\".format(key))\\n print(\\\"address: {}\\\".format(address))\\n data = context.get_state(\\n [address],\\n timeout=self.timeout)\\n print(\\\"readData obtained {} --> {} from state\\\".format(key, data[\\\"data\\\"]))\\n return 0\",\n \"def _check_trans(self, trans, meth):\\n if self._is_read_only:\\n raise POSException.ReadOnlyError()\\n\\n try:\\n buf = trans.data(self)\\n except KeyError:\\n buf = None\\n\\n if buf is None:\\n raise POSException.StorageTransactionError(\\n \\\"Transaction not committing\\\", meth, trans)\\n\\n if buf.connection_generation != self._connection_generation:\\n # We were disconnected, so this one is poisoned\\n raise ClientDisconnected(meth, 'on a disconnected transaction')\\n\\n return buf\",\n \"def get_chain_data(self, symbol: str): \\n return self.trader.fetch_chain_data(symbol)\",\n \"def get_wallet_info(wallet: str, info: dict):\\r\\n\\t#return if updated recently\\r\\n\\tif 'updated' in info:\\r\\n\\t\\tif datetime.datetime.fromisoformat(info['updated']) + datetime.timedelta(days = UPDATE_INTERVAL) > datetime.datetime.now():\\r\\n\\t\\t\\treturn info\\r\\n\\r\\n\\t#get the amount of money received to the wallet\\r\\n\\t#these wallets won't have collisions in tags, so it is save to overwrite old amounts\\r\\n\\tapi_delay(info['currency'][0])\\r\\n\\tif 'Bitcoin' in info['currency']:\\r\\n\\t\\tget_price('Bitcoin')\\r\\n\\t\\tinfo = get_Bitcoin_info(wallet, info)\\r\\n\\tif 'Ethereum' in info['currency']:\\r\\n\\t\\tget_price('Ethereum')\\r\\n\\t\\tinfo = get_Ethereum_info(wallet, info)\\r\\n\\tif 'Dogecoin' in info['currency']:\\r\\n\\t\\tget_price('Dogecoin')\\r\\n\\t\\tinfo = get_Dogecoin_info(wallet, info)\\r\\n\\tif 'ReddCoin' in info['currency']:\\r\\n\\t\\tget_price('ReddCoin')\\r\\n\\t\\tinfo = get_ReddCoin_info(wallet, info)\\r\\n\\treturn info\",\n \"def get_wallet_info(rpc_user, rpc_pwd):\\n data = '{\\\"jsonrpc\\\":\\\"2.0\\\",\\\"id\\\":\\\"1\\\",\\\"method\\\":\\\"getwalletinfo\\\"}'\\n return call_rpc(rpc_user, rpc_pwd, data)\",\n \"def getDataTransaction(self, down, up):\\n if down.isDataTransaction():\\n return down\\n else:\\n return up\",\n \"def get_read_session() -> Session:\\n return _read_session()\",\n \"def read_metadata(self):\\n return self.parent.controller.get_tag_metadata()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.69325835","0.67596567","0.6342749","0.566911","0.56382346","0.56372833","0.55744946","0.5509677","0.544398","0.5404501","0.54030645","0.54030645","0.5399337","0.53950936","0.5383335","0.53821176","0.5373266","0.5349258","0.5288624","0.5255775","0.524392","0.5172916","0.5172783","0.5169598","0.51508236","0.5134149","0.51006746","0.50777787","0.5028039","0.5002949","0.49775884","0.49523777","0.49507385","0.49364758","0.49359933","0.49187642","0.49013144","0.4897256","0.48756057","0.4872343","0.4848679","0.48199892","0.48138905","0.48082545","0.48030373","0.47892508","0.4756693","0.47471175","0.47442067","0.473817","0.47336805","0.4723612","0.46890104","0.4685216","0.46809554","0.46807063","0.467984","0.46756458","0.46703357","0.46571246","0.464774","0.46467105","0.46404028","0.4639612","0.46324772","0.46304545","0.46154487","0.4604197","0.46013984","0.4584187","0.45831433","0.45819667","0.45723027","0.45720068","0.45690203","0.4561551","0.45544222","0.45533404","0.45491365","0.4544207","0.45400316","0.4538981","0.4538108","0.4537681","0.4534857","0.45278668","0.45209256","0.45104197","0.45087638","0.45071903","0.44945467","0.44862658","0.44807997","0.44751433","0.44749904","0.44716808","0.4465689","0.446546","0.44579893"],"string":"[\n \"0.69325835\",\n \"0.67596567\",\n \"0.6342749\",\n \"0.566911\",\n \"0.56382346\",\n \"0.56372833\",\n \"0.55744946\",\n \"0.5509677\",\n \"0.544398\",\n \"0.5404501\",\n \"0.54030645\",\n \"0.54030645\",\n \"0.5399337\",\n \"0.53950936\",\n \"0.5383335\",\n \"0.53821176\",\n \"0.5373266\",\n \"0.5349258\",\n \"0.5288624\",\n \"0.5255775\",\n \"0.524392\",\n \"0.5172916\",\n \"0.5172783\",\n \"0.5169598\",\n \"0.51508236\",\n \"0.5134149\",\n \"0.51006746\",\n \"0.50777787\",\n \"0.5028039\",\n \"0.5002949\",\n \"0.49775884\",\n \"0.49523777\",\n \"0.49507385\",\n \"0.49364758\",\n \"0.49359933\",\n \"0.49187642\",\n \"0.49013144\",\n \"0.4897256\",\n \"0.48756057\",\n \"0.4872343\",\n \"0.4848679\",\n \"0.48199892\",\n \"0.48138905\",\n \"0.48082545\",\n \"0.48030373\",\n \"0.47892508\",\n \"0.4756693\",\n \"0.47471175\",\n \"0.47442067\",\n \"0.473817\",\n \"0.47336805\",\n \"0.4723612\",\n \"0.46890104\",\n \"0.4685216\",\n \"0.46809554\",\n \"0.46807063\",\n \"0.467984\",\n \"0.46756458\",\n \"0.46703357\",\n \"0.46571246\",\n \"0.464774\",\n \"0.46467105\",\n \"0.46404028\",\n \"0.4639612\",\n \"0.46324772\",\n \"0.46304545\",\n \"0.46154487\",\n \"0.4604197\",\n \"0.46013984\",\n \"0.4584187\",\n \"0.45831433\",\n \"0.45819667\",\n \"0.45723027\",\n \"0.45720068\",\n \"0.45690203\",\n \"0.4561551\",\n \"0.45544222\",\n \"0.45533404\",\n \"0.45491365\",\n \"0.4544207\",\n \"0.45400316\",\n \"0.4538981\",\n \"0.4538108\",\n \"0.4537681\",\n \"0.4534857\",\n \"0.45278668\",\n \"0.45209256\",\n \"0.45104197\",\n \"0.45087638\",\n \"0.45071903\",\n \"0.44945467\",\n \"0.44862658\",\n \"0.44807997\",\n \"0.44751433\",\n \"0.44749904\",\n \"0.44716808\",\n \"0.4465689\",\n \"0.446546\",\n \"0.44579893\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.62335604"},"document_rank":{"kind":"string","value":"3"}}},{"rowIdx":15594,"cells":{"query":{"kind":"string","value":"BeginExecute executes a begin and the specified SQL query."},"document":{"kind":"string","value":"def BeginExecute(self, request, context):\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\n context.set_details('Method not implemented!')\n raise NotImplementedError('Method not implemented!')"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def begin(self):\n self._in_transaction = True\n self.execute(\"BEGIN\")","def start_transaction_sql(self):\n return \"BEGIN TRANSACTION\"","def start_transaction(self):\n self._connection.execute_nonquery(\"sql\", \"START TRANSACTION\", True)","def startTxn(self,msg=\"\"):\n\tif self.verbose and msg:\n\t message =\"Start transaction: \"+msg\n\t message+=\", commit flag=%s\"%self.commitFlag\n\t if self.dbType=='sqlite':\n\t message+=\", %s\"%self.db.isolation_level\n\t print message\n\t sys.__stdout__.flush()\n\tif self.dbType==\"mysql\":\n\t if self.commitFlag:\n\t self.updateDBAndLog(\"BEGIN\")\n\telif self.dbType==\"sqlite\":\n\t if not self.commitFlag:\n\t return\n\t if self.db.isolation_level:\n\t return\n\t counter=0\n\t query = \"BEGIN IMMEDIATE\"\n\t cu = self.db.cursor()\n\t while 1:\n\t if counter>10: break\n\t try:\n\t\t cu.execute(query)\n# self.cursor.execute(query)\n\t self.updateLog(query)\n\t break\n\t except:\n\t print \"Wait for BEGIN\"\n\t\t gen_util.printExcept()\n\t\t pass\n\t counter+=1\n\t cu.close()\n\t return","def execute(query):\n print query\n cursor.execute(query)","def execute(self, sql, bindvars=None, commit=False):\n\n try:\n self.cursor.execute(sql)\n except cx_Oracle.DatabaseError as e:\n # Log error as appropriate\n raise\n\n # Only commit if it-s necessary.\n if commit:\n self.db.commit()","def start_transaction_sql(self):\n return 'START TRANSACTION;'","def _start_query(self) -> PQGen[None]:\n if self._autocommit:\n return\n\n if self.pgconn.transaction_status != TransactionStatus.IDLE:\n return\n\n yield from self._exec_command(self._get_tx_start_command())","def db_execute(self, database_name, statement, params):\n with self.db_create_cursor(database_name) as cursor:\n if self.debug:\n self.logger.debug(\"Running statement: \" + statement)\n return cursor.execute(statement, params)","def execute_query(self, query, params=None):\n\n self.cursor.execute(query, params)\n self.connection.commit()","def begin(self):\n self._in_transaction = True","def execute(self, query):\n cur = self.conn.cursor()\n try:\n cur.execute(query)\n self.conn.commit()\n return cur\n except:\n self.conn.rollback()\n print(\"Error: error executing query `\" + query + \"`\")\n return False","def execute_query(self, query):\n\n cnx = self.util.get_connection()\n cursor = cnx.cursor()\n try:\n cursor.execute(query)\n handler.logHelper.log_it_query(query)\n except ProgrammingError:\n handler.logHelper.log_it_query(query, status='Fail')\n finally:\n cnx.commit()\n cursor.close()\n self.util.close_connection(cnx)","def pre_exec(self):\n \n super(MSExecutionContext_pyodbc, self).pre_exec()\n\n # don't embed the scope_identity select into an \"INSERT .. DEFAULT VALUES\"\n if self._select_lastrowid and \\\n self.dialect.use_scope_identity and \\\n len(self.parameters[0]):\n self._embedded_scope_identity = True\n \n self.statement += \"; select scope_identity()\"","def begin():\n return BeginBlock()","def _db_execute(self, cur, sql_query):\n self.ctx.dbq_count += 1\n \n try:\n a = time.time()\n query, params = self._process_query(sql_query)\n out = cur.execute(query, params)\n b = time.time()\n except:\n if self.printing:\n print >> debug, 'ERR:', str(sql_query)\n if self.ctx.transactions:\n self.ctx.transactions[-1].rollback()\n else:\n self.ctx.rollback()\n raise\n\n if self.printing:\n print >> debug, '%s (%s): %s' % (round(b-a, 2), self.ctx.dbq_count, str(sql_query))\n return out","def pre_exec(self):\n\n super(MSExecutionContext_ceodbc, self).pre_exec()\n\n # don't embed the scope_identity select into an\n # \"INSERT .. DEFAULT VALUES\"\n if self._select_lastrowid and \\\n self.dialect.use_scope_identity and \\\n len(self.parameters[0]):\n self._embedded_scope_identity = True\n\n self.statement += \"; select scope_identity()\"","def begin(cls):\n db = cls.db\n db.b_commit = False","def __execute_query(self, query: str, params: Union[None, tuple] = None) -> sqlite3.Cursor:\n if params is None:\n params = ()\n\n with self.conn:\n return self.conn.execute(query, params)","def dbExecute(con, statement, args=[], skipTrace=False):\n cursor = con.cursor()\n stmt = cursor.mogrify(statement, args);\n if not skipTrace:\n trace(\"executing:\" + str(stmt))\n cursor.execute(stmt)\n global quiet\n if not skipTrace:\n trace(\"statusmessage=\" + cursor.statusmessage + \", rowcount=\" + str(cursor.rowcount))\n return cursor","def begin(transactionId, *args):\n global _operationCount\n # noinspection PyUnresolvedReferences\n _log.info(\n # \"%s BEGIN %s\" % (transactionId.hex, \" \".join(util.encode2(a) for a in args))\n f\"{transactionId.hex} BEGIN {' '.join(impl.util.encode2(a) for a in args)}\"\n )\n _countLock.acquire()\n try:\n _operationCount += 1\n finally:\n _countLock.release()","def do_begin(begin):\n if begin:\n do_action(begin)","def execute(self, sql, parameters=None):\n if parameters is None:\n parameters = {}\n self._cursor = iter(self._hndl.execute(sql, parameters))\n return self","def execute(self, sql, *args, **kwgs):\n curr = self.conn.cursor()\n curr.execute(sql, *args, **kwgs)\n self.conn.commit()\n curr.close()","def cursorExecute(self, query):\n return self.cursor.execute(query)","def execute_transaction(self, statement, mapset=None):\n connected = False\n if not self.connected:\n self.connect()\n connected = True\n\n sql_script = \"\"\n sql_script += \"BEGIN TRANSACTION;\\n\"\n sql_script += statement\n sql_script += \"END TRANSACTION;\"\n\n try:\n if self.dbmi.__name__ == \"sqlite3\":\n self.cursor.executescript(statement)\n else:\n self.cursor.execute(statement)\n self.connection.commit()\n except:\n if connected:\n self.close()\n self.msgr.error(_(\"Unable to execute transaction:\\n %(sql)s\" %\n {\"sql\": statement}))\n raise\n\n if connected:\n self.close()","def execute(self, query):\n c_query = ctypes.c_char_p(query.encode())\n rc = self.SQLPrepare(self.cur_handle, c_query, len(query))\n if rc:\n raise Exception(\"Unable to parse sql statement\")\n self.SQLSetStmtAttr(self.cur_handle, SQL_ATTR_PARAMSET_SIZE, 1, 0)\n pointer = ctypes.c_short()\n self.SQLNumParams(self.cur_handle, ctypes.byref(pointer))\n rc = self.SQLExecute(self.cur_handle)\n if rc:\n raise Exception(\"Failed to execute query\")","def _execute_command(self):\n try:\n self.dw.execute_sql_command(self.query)\n except Exception as e:\n raise e","def test_execute_begin_ro_transaction(self):\n\n instruction = Instruction(\"BeginRO(T1)\")\n self.transaction_manager.execute(instruction)\n trans1 = self.transaction_manager.transactions[\"T1\"]\n\n self.assertTrue(\"T1\" in self.transaction_manager.transactions)\n self.assertEquals(self.transaction_manager.transactions[\"T1\"].transaction_type, TransactionType.READ_ONLY)\n\n for site in self.transaction_manager.sites.values():\n for variable_identifier in site.data_manager.variables:\n self.assertTrue(variable_identifier in self.transaction_manager.readonly_snapshots[\"T1\"])\n \n self.assertEquals(trans1.identifier, \"T1\")\n self.assertEquals(trans1.transaction_type, TransactionType.READ_ONLY)\n self.assertEquals(trans1.start_time, 1)\n self.assertIsNone(trans1.end_time)\n self.assertEquals(trans1.state, TransactionState.RUNNING)","def execute(cls, sql):\n cursor = cls.get_conn().cursor()\n cursor.execute(sql)\n return cursor","def execute(self, sql):\n\n res = self.cur.execute(sql)\n self.cxn.commit()\n\n return res","def run_query(self, sql_query='', *parameters):\n if not self.cursor:\n raise BaseException(\"Database not selected\")\n\n return self.cursor.execute(sql_query, parameters)","def DBExecute( DB, sql, *args ):\n DB.execute( sql, args )\n DB.commit()","def execute_sql(self, a_sql):\n \n sql = sqlalchemy.text(a_sql)\n \n if self._activate_timer:\n result = []\n func = self._conn.execute\n the_timer = ftimer(func, [sql], {}, result, number = 1)\n self._log.debug(\"\\nTime: %s secs \\nDatabase: %s\\nRequest: %s\\n\"%(the_timer, self._url, a_sql))\n return result[0]\n else:\n result = self._conn.execute(sql)\n return result","def execute(self, query):\n try:\n cursor = self._get_cursor()\n cursor.execute(query)\n return cursor\n except pymssql.Error as e:\n raise PluginError('Error during query execution !\\n'\n 'Query: %s' % query, e.message)","def runSqlNoTransaction(self, sql):\r\n self.c.autocommit = True\r\n cursor = self.c.cursor()\r\n cursor.execute(sql)\r\n self.c.commit()\r\n cursor.close()\r\n self.c.autocommit = False\r\n return True","def start_query_execution(QueryString=None, ClientRequestToken=None, QueryExecutionContext=None, ResultConfiguration=None):\n pass","def execute_query(self,query):\n try:\n self.cursor.execute(query)\n except Exception as error:\n raise error","def execute(self, statement):\n return self._engine.connect().execute(statement)","def begin(self):\n if self.tx_id is None:\n self.tx_id = yield self.conn.query('*begin-tx*')\n yield self.conn.query('START TRANSACTION WITH CONSISTENT SNAPSHOT', tx_id=self.tx_id)","def execute(self, stmt, params=(), **kwargs):\n if kwargs:\n params = kwargs\n # do any substitutions\n if params:\n if isinstance(params, (tuple, list, set)):\n newpar = []\n for par in params:\n newpar.append(convert_PROCEDURES(par))\n params = newpar\n elif isinstance(params, dict):\n for k, val in params.items():\n params[k] = convert_PROCEDURES(val)\n # if the statement was given do any conversions\n if stmt:\n if stmt.startswith('commit'):\n return None\n exstmt = self.replacevals(stmt)\n if exstmt is None:\n return None\n\n return super(MockCursor, self).execute(convert_PROCEDURES(exstmt), params)\n return super(MockCursor, self).execute(self._stmt, params)","def execute_statement(self, statement):\n context = self.__context\n session = context.session()\n with session as connection:\n query_result = connection.execute(statement)\n\n return query_result","def insert_many_execute(self) -> None:\n self.connection.isolation_level = None\n self.cursor.execute('BEGIN TRANSACTION')\n for i in self.__sql_buffer.split(';'):\n self.cursor.execute(i)\n self.__sql_buffer = \"\"\n self.cursor.execute('COMMIT')","def execute(self) -> TableResult:\n self._t_env._before_execute()\n return TableResult(self._j_statement_set.execute())","def pg_execute(pg_conn, sql):\n print sql\n # XXX execute command","def create_tx(\n self,\n query: str,\n query_params: Optional[Mapping[str, Any]] = None,\n ):\n tx = self.get_session().begin_transaction()\n try:\n # logger.info(query)\n tx.run(query, parameters=query_params)\n tx.commit()\n except Exception as e:\n logger.error(e)\n finally:\n tx.close()","def dbexecute(cxn, query, payload):\n\tcursor = cxn.cursor()\n\tif not payload:\n\t\tcursor.execute(query)\n\telse:\n\t\tcursor.execute(query, payload)","def test_execute_begin_transaction_read_write(self):\n\n instruction = Instruction(\"Begin(T1)\")\n self.transaction_manager.execute(instruction)\n trans1 = self.transaction_manager.transactions[\"T1\"]\n self.assertEquals(len(self.transaction_manager.transactions), 1)\n self.assertEquals(trans1.identifier, \"T1\")\n self.assertEquals(trans1.transaction_type, TransactionType.READ_WRITE)\n self.assertEquals(trans1.start_time, 1)\n self.assertIsNone(trans1.end_time)\n self.assertEquals(trans1.state, TransactionState.RUNNING)","def execute_query(self, query):\n with self.db_engine.connect() as conn:\n try:\n result = conn.execute(query)\n\n except Exception as e:\n logger.error(e)\n\n result = None\n \n return result","def BeginTransaction(self, request, global_params=None):\n config = self.GetMethodConfig('BeginTransaction')\n return self._RunMethod(\n config, request, global_params=global_params)","def _execute(self, stmt) -> sa.engine.ResultProxy:\n return self._engine.execute(stmt)","def execute(self):\n if self.sql is None:\n self.sql = self.construct_query()\n # Only SQL strings can be split, not (e.g.) SQLAlchemy statements.\n if self.multiple_statements and isinstance(self.sql, str):\n statements = self._split_sql()\n else:\n statements = [self.sql]\n single_statement = True if len(statements) == 1 and self.filename else False\n try:\n for statement in statements:\n result_proxy = self.cm.conn.execute(statement)\n log_string = self.filename if single_statement else str(statement)[:25]\n self.logger.info(\"Executed {} against {}\".format(log_string, self.cm.db))\n if result_proxy.cursor:\n return self.fetch_results(result_proxy)\n except Exception as e:\n self.logger.exception(e)\n raise","def _Dynamic_BeginTransaction(self, request, transaction, request_id=None):\n request.set_app(self.project_id)\n self._RemoteSend(request, transaction, \"BeginTransaction\", request_id)\n self.__tx_actions[transaction.handle()] = []\n return transaction","def tpc_begin(self, transaction):\n raise NotImplementedError","async def execute(self, stmt, *args):\n with (await self.application.db.cursor()) as cur:\n await cur.execute(stmt, args)","def execute_sql(self, query, params=None):\n return self.user_con.execute_sql(query=query, params=params)","def execute(self, sql, params=None):\n if params and not isinstance(params, Mapping):\n raise TypeError(\"Expected dict or other mapping object\")\n\n cursor = self.cursor()\n sql, params = utils.change_param_style(self.driver.paramstyle, sql, params)\n cursor.execute(sql, params)\n return cursor","def commit(self):\n self._connection.execute_nonquery(\"sql\", \"COMMIT\", True)","def __execute__(self, sql, commit=True):\n cursor = None\n PDEBUG('Executing SQL: %s'%sql)\n try:\n cursor = self.conn.execute(sql)\n except sqlite3.IntegrityError as e:\n print('DUP: %s' % e)\n except Exception as e:\n print('FATAL: %s -- %s' % (e, sql))\n else:\n if commit:\n self.conn.commit()\n\n return cursor","def query(self, *sql):\n self.cursor.execute(*sql)\n self.conn.commit()","def begin_transaction(self, request):\n return self._call_method('beginTransaction', request,\n datastore_v1_pb2.BeginTransactionResponse)","def execute(self, query, *parameters, **kwparameters):\n return self._execute_lastrowid(query, *parameters, **kwparameters)","def runSql(self, sql):\r\n cursor = self.c.cursor()\r\n cursor.execute(sql)\r\n self.c.commit()\r\n cursor.close()\r\n return True","def execute(self, a_sql_obj):\n \n # if sql_obj is a string wrap it in a sqlalchemy.text\n \n if type(a_sql_obj) == type(''):\n sql = sqlalchemy.text(a_sql_obj)\n else:\n sql = a_sql_obj\n \n if self._activate_timer:\n result = []\n func = self._conn.execute\n the_timer = ftimer(func, [sql], {}, result, number = 1)\n self._log.debug(\"\\nTime: %s secs \\nDatabase: %s\\nRequest: %s\\n\"%(the_timer, self._url, sql))\n return result[0]\n else:\n result = self._conn.execute(sql)\n return result","def execute_sql(self, sql, params=None, commit=None):\n try:\n cursor = super().execute_sql(sql, params, commit)\n except pw.OperationalError:\n # If we're in a transaction or the database isn't\n # set to autoconnect, there's not much we can do,\n # so just continue to crash\n if not self.autoconnect or self.in_transaction():\n raise\n\n # Close the broken connector, if it's still open\n if not self.is_closed():\n self.close()\n\n # And then retry. This will re-open the DB because\n # we've just closed it and autoconnect is True.\n cursor = super().execute_sql(sql, params, commit)\n return cursor","def execute(self, dbname, query, username=None, commit=False):\n with self.connect(dbname, username) as node_con:\n res = node_con.execute(query)\n if commit:\n node_con.commit()\n return res","def execute(self, begin: int, end: int) -> int:\n row_number = self.row_number\n self.row_number += 1\n return row_number","def execute(self, sql, params=None):\n if params is None:\n for statement in sql.split(';'):\n self.cursor.execute(statement)\n return\n print('string parameters get escaped to guard against sql injection')\n print(\"resulting sql is \" + \\\n sql.replace(\"?\", \"'\" + params[0].replace(\"'\", \"''\") + \"'\"))\n self.cursor.execute(sql, params)","def _execute_insert(self, insertQuery, insertValues):\n with self as plasticDB:\n cursor = plasticDB.connection.cursor()\n cursor.execute(insertQuery, insertValues)\n return cursor.lastrowid","def _execute(self, *args):\n cursor = self.db.cursor()\n cursor.execute(*args)\n return cursor","def execute(\n self,\n query: Query,\n params: Optional[Params] = None,\n *,\n prepare: Optional[bool] = None,\n binary: bool = False,\n ) -> Cursor[Row]:\n cur = self.cursor()\n if binary:\n cur.format = Format.BINARY\n\n try:\n return cur.execute(query, params, prepare=prepare)\n except e.Error as ex:\n raise ex.with_traceback(None)","def _do_begin(self):\n self.backend.begin()","def execute(self, qry):\n def internal():\n print 'qry = ', qry\n self._cur = self.get_cursor()\n print 'self._cur = ', self._cur\n self._cur.execute(qry)\n # self.conn.cursor(cursor_factory=psycopg2.extras.RealDictCursor).execute(qry)\n rows = self._cur.fetchall()\n return rows\n\n return self._retry(internal)","def _exec (self, sql, **kwargs):\n\n kwargs['id'] = self.id\n cursor = self.connection.cursor ()\n cursor.execute (sql.replace ('table_name', self.table_name), kwargs)\n return cursor","def executeQuery(connection,cursor,query,query_type):\n\tif query_type =='select':\n\t\tcursor.execute(query)\n\t\tresult = cursor.fetchall()\n\t\treturn result\n\t\t\n\telif query_type in ['insert','update','delete']:\n\t\tcursor.execute(query)\n\t\tconnection.commit()\n\t\t#generate a log msg in the future","def execute(self, statement, args=None):\n connected = False\n if not self.connected:\n self.connect()\n connected = True\n try:\n if args:\n self.cursor.execute(statement, args)\n else:\n self.cursor.execute(statement)\n except:\n if connected:\n self.close()\n self.msgr.error(_(\"Unable to execute :\\n %(sql)s\" %\n {\"sql\": statement}))\n raise\n\n if connected:\n self.close()","def execute(self, sql_statement, db_name=None, **kwargs):\n # Create Connection\n engine, connection = self.create_connection(db_name)\n\n # Execute SQL\n result = connection.execute(sql_statement, **kwargs)\n\n # Close connection\n connection.close()\n\n # return metadata of query execution result\n return result","def run_query(query):\n conn = connection.get_db_connection()\n cursor = conn.cursor()\n cursor.execute(query)\n return cursor","def execute(self, sqlcmd):\n self._c.execute(sqlcmd)\n return","def db_execute_query(db_connection, query, query_args):\n cursor = db_connection.cursor()\n #datalab_logger_connections.info(\"reading database[Query. May Take Time]...\")\n cursor.execute(query, query_args)\n #datalab_logger_connections.info(\"finish to query database\")\n return cursor","def begin(self):\n return self.connection.begin()","def begin_transaction(self):\r\n self.db.commit(False)","def svn_fs_begin_txn(*args):\r\n return _fs.svn_fs_begin_txn(*args)","def execute(self, *args, **kwargs):\n return self.engine.execute(*args, **kwargs)","def execute(self, *args, **kwargs):\n return self.engine.execute(*args, **kwargs)","def execute_stored_procedure(self, proc_name, params, base):\n conn = self.connect_to_database(db=base)\n connection = conn.connect()\n result = connection.execute(proc_name, params)\n connection.close()\n return result","def start_transaction(self) -> None:\n pass","def execute_query(self, query_, return_results_=False):\n\n try:\n if return_results_:\n logging.info(\"Fetching results...\")\n self.query_results = self.cursor.execute(query_)\n else:\n self.cursor.execute(query_)\n logging.info(\"Query ran successfully.\")\n\n except Exception as e:\n if self.airflow:\n # For Airflow, forces task to fail and set it up for re-try\n raise AirflowException(\"Error running query. {}\"\n .format(str(e)))\n else:\n logging.exception(\"Error running query.\")\n raise e","def execute(self, start=0, end=0):\n base_query = self.postgres.session.query(Analysis).\\\n join(Version).\\\n join(Package).\\\n join(Ecosystem).\\\n filter(Analysis.finished_at.isnot(None)).\\\n filter(Analysis.id >= start).\\\n order_by(Analysis.id.asc())\n\n if end:\n base_query = base_query.filter(Analysis.id <= end)\n\n while True:\n self.log.info(\"Updating results, slice offset is %s\", start)\n try:\n results = base_query.slice(start, start + self.query_slice).all()\n except SQLAlchemyError:\n self.postgres.session.rollback()\n raise\n start += self.query_slice\n if not results:\n self.log.info(\"No more finished analyses => syncing to GraphDB finished\")\n break\n\n for entry in results:\n arguments = {'ecosystem': entry.version.package.ecosystem.name,\n 'name': entry.version.package.name,\n 'version': entry.version.identifier}\n try:\n self.log.info('Synchronizing {ecosystem}/{name}/{version} ...'.format(\n **arguments))\n GraphImporterTask.create_test_instance().execute(arguments)\n except Exception:\n self.log.exception('Failed to synchronize {ecosystem}/{name}/{version}'.\n format(**arguments))\n del entry","def execute_sql(conn, query):\n\ttry:\n\t\t\tc = conn.cursor()\n\t\t\tc.execute(query)\n\texcept Error as e:\n\t\t\tprint(f\"SQL error :{e}\")\n\t\t\tprint(f\"Attempted to run: {query}\")\n\t\t\t\n\treturn c","def start_transaction(self,):\n\n if self.tx is not None:\n raise OverlappedTransaction(str(self.tx.xid))\n\n modlogger.debug(\"start tx\")\n opid = self.new_opid()\n xaction = StartTxOperation(opid,opid)\n self.tx = Transaction(opid,self.home, track_state = self.track_state)\n self._add_operation(opid,xaction)\n return opid","def execute_query(self, query):\n self.recordset = self.con.execute(query)\n return self","def _ExecuteWithSQLConnection(\n self, sql_cnxn, stmt_str, stmt_args, commit=True):\n if stmt_str.startswith('INSERT') or stmt_str.startswith('REPLACE'):\n logging.info('SQL stmt_str: \\n%s', stmt_str)\n logging.info('SQL stmt_args: %r', stmt_args)\n else:\n logging.info('SQL stmt: \\n%s', (stmt_str % tuple(stmt_args)))\n\n start_time = time.time()\n cursor = sql_cnxn.cursor()\n cursor.execute('SET NAMES utf8mb4')\n logging.info('made cursor on %r in %d ms',\n sql_cnxn, int((time.time() - start_time) * 1000))\n if stmt_str.startswith('INSERT') or stmt_str.startswith('REPLACE'):\n cursor.executemany(stmt_str, stmt_args)\n duration = (time.time() - start_time) * 1000\n DB_QUERY_LATENCY.add(duration, {'type': 'write'})\n DB_QUERY_COUNT.increment({'type': 'write'})\n else:\n cursor.execute(stmt_str, args=stmt_args)\n duration = (time.time() - start_time) * 1000\n DB_QUERY_LATENCY.add(duration, {'type': 'read'})\n DB_QUERY_COUNT.increment({'type': 'read'})\n DB_RESULT_ROWS.add(cursor.rowcount)\n logging.info('%d rows in %d ms', cursor.rowcount,\n int(duration))\n\n if commit and not stmt_str.startswith('SELECT'):\n try:\n sql_cnxn.commit()\n duration = (time.time() - start_time) * 1000\n DB_COMMIT_LATENCY.add(duration)\n DB_COMMIT_COUNT.increment()\n except MySQLdb.DatabaseError:\n sql_cnxn.rollback()\n duration = (time.time() - start_time) * 1000\n DB_ROLLBACK_LATENCY.add(duration)\n DB_ROLLBACK_COUNT.increment()\n\n return cursor","def _execute_query(self, select_clause, trailing_clause=None, **kwds_filter):\n try:\n stmnt, params = self._build_query(self._table, select_clause, **kwds_filter)\n if trailing_clause:\n stmnt += '\\n' + trailing_clause\n cursor = self._connection.cursor()\n cursor.execute('PRAGMA synchronous=OFF')\n #print(stmnt, params)\n cursor.execute(stmnt, params)\n except Exception as e:\n exc_cls = e.__class__\n msg = '%s\\n query: %s\\n params: %r' % (e, stmnt, params)\n raise exc_cls(msg)\n return cursor","def BeginExecute(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\n raise NotImplementedError()","def _execute_query(db_path, query, *args):\n\n con = sql.connect(db_path)\n cur = con.cursor()\n cur.execute(query, args)\n con.commit()\n con.close()","def DBExecuteScript( DB: sqlite3.Connection, sql:str, *args ):\n assert isinstance( DB, sqlite3.Connection )\n DB.executescript( sql )\n DB.commit()","def execute_and_commit_sql(db, sql):\n conn_string = return_connection(db)\n with pg2.connect(conn_string) as conn:\n with conn.cursor() as curs:\n curs.execute(sql)\n conn.commit()","def execute_both(self, query, *parameters, **kwparameters):\n cursor = self._cursor()\n try:\n self._execute(cursor, query, parameters, kwparameters)\n return cursor.lastrowid, cursor.rowcount\n finally:\n cursor.close()","def execute(\n self, query: str, table: str = None, values: IterOpt = None\n ) -> sqlite3.Cursor:","def commit_query(conn):\r\n conn.commit()"],"string":"[\n \"def begin(self):\\n self._in_transaction = True\\n self.execute(\\\"BEGIN\\\")\",\n \"def start_transaction_sql(self):\\n return \\\"BEGIN TRANSACTION\\\"\",\n \"def start_transaction(self):\\n self._connection.execute_nonquery(\\\"sql\\\", \\\"START TRANSACTION\\\", True)\",\n \"def startTxn(self,msg=\\\"\\\"):\\n\\tif self.verbose and msg:\\n\\t message =\\\"Start transaction: \\\"+msg\\n\\t message+=\\\", commit flag=%s\\\"%self.commitFlag\\n\\t if self.dbType=='sqlite':\\n\\t message+=\\\", %s\\\"%self.db.isolation_level\\n\\t print message\\n\\t sys.__stdout__.flush()\\n\\tif self.dbType==\\\"mysql\\\":\\n\\t if self.commitFlag:\\n\\t self.updateDBAndLog(\\\"BEGIN\\\")\\n\\telif self.dbType==\\\"sqlite\\\":\\n\\t if not self.commitFlag:\\n\\t return\\n\\t if self.db.isolation_level:\\n\\t return\\n\\t counter=0\\n\\t query = \\\"BEGIN IMMEDIATE\\\"\\n\\t cu = self.db.cursor()\\n\\t while 1:\\n\\t if counter>10: break\\n\\t try:\\n\\t\\t cu.execute(query)\\n# self.cursor.execute(query)\\n\\t self.updateLog(query)\\n\\t break\\n\\t except:\\n\\t print \\\"Wait for BEGIN\\\"\\n\\t\\t gen_util.printExcept()\\n\\t\\t pass\\n\\t counter+=1\\n\\t cu.close()\\n\\t return\",\n \"def execute(query):\\n print query\\n cursor.execute(query)\",\n \"def execute(self, sql, bindvars=None, commit=False):\\n\\n try:\\n self.cursor.execute(sql)\\n except cx_Oracle.DatabaseError as e:\\n # Log error as appropriate\\n raise\\n\\n # Only commit if it-s necessary.\\n if commit:\\n self.db.commit()\",\n \"def start_transaction_sql(self):\\n return 'START TRANSACTION;'\",\n \"def _start_query(self) -> PQGen[None]:\\n if self._autocommit:\\n return\\n\\n if self.pgconn.transaction_status != TransactionStatus.IDLE:\\n return\\n\\n yield from self._exec_command(self._get_tx_start_command())\",\n \"def db_execute(self, database_name, statement, params):\\n with self.db_create_cursor(database_name) as cursor:\\n if self.debug:\\n self.logger.debug(\\\"Running statement: \\\" + statement)\\n return cursor.execute(statement, params)\",\n \"def execute_query(self, query, params=None):\\n\\n self.cursor.execute(query, params)\\n self.connection.commit()\",\n \"def begin(self):\\n self._in_transaction = True\",\n \"def execute(self, query):\\n cur = self.conn.cursor()\\n try:\\n cur.execute(query)\\n self.conn.commit()\\n return cur\\n except:\\n self.conn.rollback()\\n print(\\\"Error: error executing query `\\\" + query + \\\"`\\\")\\n return False\",\n \"def execute_query(self, query):\\n\\n cnx = self.util.get_connection()\\n cursor = cnx.cursor()\\n try:\\n cursor.execute(query)\\n handler.logHelper.log_it_query(query)\\n except ProgrammingError:\\n handler.logHelper.log_it_query(query, status='Fail')\\n finally:\\n cnx.commit()\\n cursor.close()\\n self.util.close_connection(cnx)\",\n \"def pre_exec(self):\\n \\n super(MSExecutionContext_pyodbc, self).pre_exec()\\n\\n # don't embed the scope_identity select into an \\\"INSERT .. DEFAULT VALUES\\\"\\n if self._select_lastrowid and \\\\\\n self.dialect.use_scope_identity and \\\\\\n len(self.parameters[0]):\\n self._embedded_scope_identity = True\\n \\n self.statement += \\\"; select scope_identity()\\\"\",\n \"def begin():\\n return BeginBlock()\",\n \"def _db_execute(self, cur, sql_query):\\n self.ctx.dbq_count += 1\\n \\n try:\\n a = time.time()\\n query, params = self._process_query(sql_query)\\n out = cur.execute(query, params)\\n b = time.time()\\n except:\\n if self.printing:\\n print >> debug, 'ERR:', str(sql_query)\\n if self.ctx.transactions:\\n self.ctx.transactions[-1].rollback()\\n else:\\n self.ctx.rollback()\\n raise\\n\\n if self.printing:\\n print >> debug, '%s (%s): %s' % (round(b-a, 2), self.ctx.dbq_count, str(sql_query))\\n return out\",\n \"def pre_exec(self):\\n\\n super(MSExecutionContext_ceodbc, self).pre_exec()\\n\\n # don't embed the scope_identity select into an\\n # \\\"INSERT .. DEFAULT VALUES\\\"\\n if self._select_lastrowid and \\\\\\n self.dialect.use_scope_identity and \\\\\\n len(self.parameters[0]):\\n self._embedded_scope_identity = True\\n\\n self.statement += \\\"; select scope_identity()\\\"\",\n \"def begin(cls):\\n db = cls.db\\n db.b_commit = False\",\n \"def __execute_query(self, query: str, params: Union[None, tuple] = None) -> sqlite3.Cursor:\\n if params is None:\\n params = ()\\n\\n with self.conn:\\n return self.conn.execute(query, params)\",\n \"def dbExecute(con, statement, args=[], skipTrace=False):\\n cursor = con.cursor()\\n stmt = cursor.mogrify(statement, args);\\n if not skipTrace:\\n trace(\\\"executing:\\\" + str(stmt))\\n cursor.execute(stmt)\\n global quiet\\n if not skipTrace:\\n trace(\\\"statusmessage=\\\" + cursor.statusmessage + \\\", rowcount=\\\" + str(cursor.rowcount))\\n return cursor\",\n \"def begin(transactionId, *args):\\n global _operationCount\\n # noinspection PyUnresolvedReferences\\n _log.info(\\n # \\\"%s BEGIN %s\\\" % (transactionId.hex, \\\" \\\".join(util.encode2(a) for a in args))\\n f\\\"{transactionId.hex} BEGIN {' '.join(impl.util.encode2(a) for a in args)}\\\"\\n )\\n _countLock.acquire()\\n try:\\n _operationCount += 1\\n finally:\\n _countLock.release()\",\n \"def do_begin(begin):\\n if begin:\\n do_action(begin)\",\n \"def execute(self, sql, parameters=None):\\n if parameters is None:\\n parameters = {}\\n self._cursor = iter(self._hndl.execute(sql, parameters))\\n return self\",\n \"def execute(self, sql, *args, **kwgs):\\n curr = self.conn.cursor()\\n curr.execute(sql, *args, **kwgs)\\n self.conn.commit()\\n curr.close()\",\n \"def cursorExecute(self, query):\\n return self.cursor.execute(query)\",\n \"def execute_transaction(self, statement, mapset=None):\\n connected = False\\n if not self.connected:\\n self.connect()\\n connected = True\\n\\n sql_script = \\\"\\\"\\n sql_script += \\\"BEGIN TRANSACTION;\\\\n\\\"\\n sql_script += statement\\n sql_script += \\\"END TRANSACTION;\\\"\\n\\n try:\\n if self.dbmi.__name__ == \\\"sqlite3\\\":\\n self.cursor.executescript(statement)\\n else:\\n self.cursor.execute(statement)\\n self.connection.commit()\\n except:\\n if connected:\\n self.close()\\n self.msgr.error(_(\\\"Unable to execute transaction:\\\\n %(sql)s\\\" %\\n {\\\"sql\\\": statement}))\\n raise\\n\\n if connected:\\n self.close()\",\n \"def execute(self, query):\\n c_query = ctypes.c_char_p(query.encode())\\n rc = self.SQLPrepare(self.cur_handle, c_query, len(query))\\n if rc:\\n raise Exception(\\\"Unable to parse sql statement\\\")\\n self.SQLSetStmtAttr(self.cur_handle, SQL_ATTR_PARAMSET_SIZE, 1, 0)\\n pointer = ctypes.c_short()\\n self.SQLNumParams(self.cur_handle, ctypes.byref(pointer))\\n rc = self.SQLExecute(self.cur_handle)\\n if rc:\\n raise Exception(\\\"Failed to execute query\\\")\",\n \"def _execute_command(self):\\n try:\\n self.dw.execute_sql_command(self.query)\\n except Exception as e:\\n raise e\",\n \"def test_execute_begin_ro_transaction(self):\\n\\n instruction = Instruction(\\\"BeginRO(T1)\\\")\\n self.transaction_manager.execute(instruction)\\n trans1 = self.transaction_manager.transactions[\\\"T1\\\"]\\n\\n self.assertTrue(\\\"T1\\\" in self.transaction_manager.transactions)\\n self.assertEquals(self.transaction_manager.transactions[\\\"T1\\\"].transaction_type, TransactionType.READ_ONLY)\\n\\n for site in self.transaction_manager.sites.values():\\n for variable_identifier in site.data_manager.variables:\\n self.assertTrue(variable_identifier in self.transaction_manager.readonly_snapshots[\\\"T1\\\"])\\n \\n self.assertEquals(trans1.identifier, \\\"T1\\\")\\n self.assertEquals(trans1.transaction_type, TransactionType.READ_ONLY)\\n self.assertEquals(trans1.start_time, 1)\\n self.assertIsNone(trans1.end_time)\\n self.assertEquals(trans1.state, TransactionState.RUNNING)\",\n \"def execute(cls, sql):\\n cursor = cls.get_conn().cursor()\\n cursor.execute(sql)\\n return cursor\",\n \"def execute(self, sql):\\n\\n res = self.cur.execute(sql)\\n self.cxn.commit()\\n\\n return res\",\n \"def run_query(self, sql_query='', *parameters):\\n if not self.cursor:\\n raise BaseException(\\\"Database not selected\\\")\\n\\n return self.cursor.execute(sql_query, parameters)\",\n \"def DBExecute( DB, sql, *args ):\\n DB.execute( sql, args )\\n DB.commit()\",\n \"def execute_sql(self, a_sql):\\n \\n sql = sqlalchemy.text(a_sql)\\n \\n if self._activate_timer:\\n result = []\\n func = self._conn.execute\\n the_timer = ftimer(func, [sql], {}, result, number = 1)\\n self._log.debug(\\\"\\\\nTime: %s secs \\\\nDatabase: %s\\\\nRequest: %s\\\\n\\\"%(the_timer, self._url, a_sql))\\n return result[0]\\n else:\\n result = self._conn.execute(sql)\\n return result\",\n \"def execute(self, query):\\n try:\\n cursor = self._get_cursor()\\n cursor.execute(query)\\n return cursor\\n except pymssql.Error as e:\\n raise PluginError('Error during query execution !\\\\n'\\n 'Query: %s' % query, e.message)\",\n \"def runSqlNoTransaction(self, sql):\\r\\n self.c.autocommit = True\\r\\n cursor = self.c.cursor()\\r\\n cursor.execute(sql)\\r\\n self.c.commit()\\r\\n cursor.close()\\r\\n self.c.autocommit = False\\r\\n return True\",\n \"def start_query_execution(QueryString=None, ClientRequestToken=None, QueryExecutionContext=None, ResultConfiguration=None):\\n pass\",\n \"def execute_query(self,query):\\n try:\\n self.cursor.execute(query)\\n except Exception as error:\\n raise error\",\n \"def execute(self, statement):\\n return self._engine.connect().execute(statement)\",\n \"def begin(self):\\n if self.tx_id is None:\\n self.tx_id = yield self.conn.query('*begin-tx*')\\n yield self.conn.query('START TRANSACTION WITH CONSISTENT SNAPSHOT', tx_id=self.tx_id)\",\n \"def execute(self, stmt, params=(), **kwargs):\\n if kwargs:\\n params = kwargs\\n # do any substitutions\\n if params:\\n if isinstance(params, (tuple, list, set)):\\n newpar = []\\n for par in params:\\n newpar.append(convert_PROCEDURES(par))\\n params = newpar\\n elif isinstance(params, dict):\\n for k, val in params.items():\\n params[k] = convert_PROCEDURES(val)\\n # if the statement was given do any conversions\\n if stmt:\\n if stmt.startswith('commit'):\\n return None\\n exstmt = self.replacevals(stmt)\\n if exstmt is None:\\n return None\\n\\n return super(MockCursor, self).execute(convert_PROCEDURES(exstmt), params)\\n return super(MockCursor, self).execute(self._stmt, params)\",\n \"def execute_statement(self, statement):\\n context = self.__context\\n session = context.session()\\n with session as connection:\\n query_result = connection.execute(statement)\\n\\n return query_result\",\n \"def insert_many_execute(self) -> None:\\n self.connection.isolation_level = None\\n self.cursor.execute('BEGIN TRANSACTION')\\n for i in self.__sql_buffer.split(';'):\\n self.cursor.execute(i)\\n self.__sql_buffer = \\\"\\\"\\n self.cursor.execute('COMMIT')\",\n \"def execute(self) -> TableResult:\\n self._t_env._before_execute()\\n return TableResult(self._j_statement_set.execute())\",\n \"def pg_execute(pg_conn, sql):\\n print sql\\n # XXX execute command\",\n \"def create_tx(\\n self,\\n query: str,\\n query_params: Optional[Mapping[str, Any]] = None,\\n ):\\n tx = self.get_session().begin_transaction()\\n try:\\n # logger.info(query)\\n tx.run(query, parameters=query_params)\\n tx.commit()\\n except Exception as e:\\n logger.error(e)\\n finally:\\n tx.close()\",\n \"def dbexecute(cxn, query, payload):\\n\\tcursor = cxn.cursor()\\n\\tif not payload:\\n\\t\\tcursor.execute(query)\\n\\telse:\\n\\t\\tcursor.execute(query, payload)\",\n \"def test_execute_begin_transaction_read_write(self):\\n\\n instruction = Instruction(\\\"Begin(T1)\\\")\\n self.transaction_manager.execute(instruction)\\n trans1 = self.transaction_manager.transactions[\\\"T1\\\"]\\n self.assertEquals(len(self.transaction_manager.transactions), 1)\\n self.assertEquals(trans1.identifier, \\\"T1\\\")\\n self.assertEquals(trans1.transaction_type, TransactionType.READ_WRITE)\\n self.assertEquals(trans1.start_time, 1)\\n self.assertIsNone(trans1.end_time)\\n self.assertEquals(trans1.state, TransactionState.RUNNING)\",\n \"def execute_query(self, query):\\n with self.db_engine.connect() as conn:\\n try:\\n result = conn.execute(query)\\n\\n except Exception as e:\\n logger.error(e)\\n\\n result = None\\n \\n return result\",\n \"def BeginTransaction(self, request, global_params=None):\\n config = self.GetMethodConfig('BeginTransaction')\\n return self._RunMethod(\\n config, request, global_params=global_params)\",\n \"def _execute(self, stmt) -> sa.engine.ResultProxy:\\n return self._engine.execute(stmt)\",\n \"def execute(self):\\n if self.sql is None:\\n self.sql = self.construct_query()\\n # Only SQL strings can be split, not (e.g.) SQLAlchemy statements.\\n if self.multiple_statements and isinstance(self.sql, str):\\n statements = self._split_sql()\\n else:\\n statements = [self.sql]\\n single_statement = True if len(statements) == 1 and self.filename else False\\n try:\\n for statement in statements:\\n result_proxy = self.cm.conn.execute(statement)\\n log_string = self.filename if single_statement else str(statement)[:25]\\n self.logger.info(\\\"Executed {} against {}\\\".format(log_string, self.cm.db))\\n if result_proxy.cursor:\\n return self.fetch_results(result_proxy)\\n except Exception as e:\\n self.logger.exception(e)\\n raise\",\n \"def _Dynamic_BeginTransaction(self, request, transaction, request_id=None):\\n request.set_app(self.project_id)\\n self._RemoteSend(request, transaction, \\\"BeginTransaction\\\", request_id)\\n self.__tx_actions[transaction.handle()] = []\\n return transaction\",\n \"def tpc_begin(self, transaction):\\n raise NotImplementedError\",\n \"async def execute(self, stmt, *args):\\n with (await self.application.db.cursor()) as cur:\\n await cur.execute(stmt, args)\",\n \"def execute_sql(self, query, params=None):\\n return self.user_con.execute_sql(query=query, params=params)\",\n \"def execute(self, sql, params=None):\\n if params and not isinstance(params, Mapping):\\n raise TypeError(\\\"Expected dict or other mapping object\\\")\\n\\n cursor = self.cursor()\\n sql, params = utils.change_param_style(self.driver.paramstyle, sql, params)\\n cursor.execute(sql, params)\\n return cursor\",\n \"def commit(self):\\n self._connection.execute_nonquery(\\\"sql\\\", \\\"COMMIT\\\", True)\",\n \"def __execute__(self, sql, commit=True):\\n cursor = None\\n PDEBUG('Executing SQL: %s'%sql)\\n try:\\n cursor = self.conn.execute(sql)\\n except sqlite3.IntegrityError as e:\\n print('DUP: %s' % e)\\n except Exception as e:\\n print('FATAL: %s -- %s' % (e, sql))\\n else:\\n if commit:\\n self.conn.commit()\\n\\n return cursor\",\n \"def query(self, *sql):\\n self.cursor.execute(*sql)\\n self.conn.commit()\",\n \"def begin_transaction(self, request):\\n return self._call_method('beginTransaction', request,\\n datastore_v1_pb2.BeginTransactionResponse)\",\n \"def execute(self, query, *parameters, **kwparameters):\\n return self._execute_lastrowid(query, *parameters, **kwparameters)\",\n \"def runSql(self, sql):\\r\\n cursor = self.c.cursor()\\r\\n cursor.execute(sql)\\r\\n self.c.commit()\\r\\n cursor.close()\\r\\n return True\",\n \"def execute(self, a_sql_obj):\\n \\n # if sql_obj is a string wrap it in a sqlalchemy.text\\n \\n if type(a_sql_obj) == type(''):\\n sql = sqlalchemy.text(a_sql_obj)\\n else:\\n sql = a_sql_obj\\n \\n if self._activate_timer:\\n result = []\\n func = self._conn.execute\\n the_timer = ftimer(func, [sql], {}, result, number = 1)\\n self._log.debug(\\\"\\\\nTime: %s secs \\\\nDatabase: %s\\\\nRequest: %s\\\\n\\\"%(the_timer, self._url, sql))\\n return result[0]\\n else:\\n result = self._conn.execute(sql)\\n return result\",\n \"def execute_sql(self, sql, params=None, commit=None):\\n try:\\n cursor = super().execute_sql(sql, params, commit)\\n except pw.OperationalError:\\n # If we're in a transaction or the database isn't\\n # set to autoconnect, there's not much we can do,\\n # so just continue to crash\\n if not self.autoconnect or self.in_transaction():\\n raise\\n\\n # Close the broken connector, if it's still open\\n if not self.is_closed():\\n self.close()\\n\\n # And then retry. This will re-open the DB because\\n # we've just closed it and autoconnect is True.\\n cursor = super().execute_sql(sql, params, commit)\\n return cursor\",\n \"def execute(self, dbname, query, username=None, commit=False):\\n with self.connect(dbname, username) as node_con:\\n res = node_con.execute(query)\\n if commit:\\n node_con.commit()\\n return res\",\n \"def execute(self, begin: int, end: int) -> int:\\n row_number = self.row_number\\n self.row_number += 1\\n return row_number\",\n \"def execute(self, sql, params=None):\\n if params is None:\\n for statement in sql.split(';'):\\n self.cursor.execute(statement)\\n return\\n print('string parameters get escaped to guard against sql injection')\\n print(\\\"resulting sql is \\\" + \\\\\\n sql.replace(\\\"?\\\", \\\"'\\\" + params[0].replace(\\\"'\\\", \\\"''\\\") + \\\"'\\\"))\\n self.cursor.execute(sql, params)\",\n \"def _execute_insert(self, insertQuery, insertValues):\\n with self as plasticDB:\\n cursor = plasticDB.connection.cursor()\\n cursor.execute(insertQuery, insertValues)\\n return cursor.lastrowid\",\n \"def _execute(self, *args):\\n cursor = self.db.cursor()\\n cursor.execute(*args)\\n return cursor\",\n \"def execute(\\n self,\\n query: Query,\\n params: Optional[Params] = None,\\n *,\\n prepare: Optional[bool] = None,\\n binary: bool = False,\\n ) -> Cursor[Row]:\\n cur = self.cursor()\\n if binary:\\n cur.format = Format.BINARY\\n\\n try:\\n return cur.execute(query, params, prepare=prepare)\\n except e.Error as ex:\\n raise ex.with_traceback(None)\",\n \"def _do_begin(self):\\n self.backend.begin()\",\n \"def execute(self, qry):\\n def internal():\\n print 'qry = ', qry\\n self._cur = self.get_cursor()\\n print 'self._cur = ', self._cur\\n self._cur.execute(qry)\\n # self.conn.cursor(cursor_factory=psycopg2.extras.RealDictCursor).execute(qry)\\n rows = self._cur.fetchall()\\n return rows\\n\\n return self._retry(internal)\",\n \"def _exec (self, sql, **kwargs):\\n\\n kwargs['id'] = self.id\\n cursor = self.connection.cursor ()\\n cursor.execute (sql.replace ('table_name', self.table_name), kwargs)\\n return cursor\",\n \"def executeQuery(connection,cursor,query,query_type):\\n\\tif query_type =='select':\\n\\t\\tcursor.execute(query)\\n\\t\\tresult = cursor.fetchall()\\n\\t\\treturn result\\n\\t\\t\\n\\telif query_type in ['insert','update','delete']:\\n\\t\\tcursor.execute(query)\\n\\t\\tconnection.commit()\\n\\t\\t#generate a log msg in the future\",\n \"def execute(self, statement, args=None):\\n connected = False\\n if not self.connected:\\n self.connect()\\n connected = True\\n try:\\n if args:\\n self.cursor.execute(statement, args)\\n else:\\n self.cursor.execute(statement)\\n except:\\n if connected:\\n self.close()\\n self.msgr.error(_(\\\"Unable to execute :\\\\n %(sql)s\\\" %\\n {\\\"sql\\\": statement}))\\n raise\\n\\n if connected:\\n self.close()\",\n \"def execute(self, sql_statement, db_name=None, **kwargs):\\n # Create Connection\\n engine, connection = self.create_connection(db_name)\\n\\n # Execute SQL\\n result = connection.execute(sql_statement, **kwargs)\\n\\n # Close connection\\n connection.close()\\n\\n # return metadata of query execution result\\n return result\",\n \"def run_query(query):\\n conn = connection.get_db_connection()\\n cursor = conn.cursor()\\n cursor.execute(query)\\n return cursor\",\n \"def execute(self, sqlcmd):\\n self._c.execute(sqlcmd)\\n return\",\n \"def db_execute_query(db_connection, query, query_args):\\n cursor = db_connection.cursor()\\n #datalab_logger_connections.info(\\\"reading database[Query. May Take Time]...\\\")\\n cursor.execute(query, query_args)\\n #datalab_logger_connections.info(\\\"finish to query database\\\")\\n return cursor\",\n \"def begin(self):\\n return self.connection.begin()\",\n \"def begin_transaction(self):\\r\\n self.db.commit(False)\",\n \"def svn_fs_begin_txn(*args):\\r\\n return _fs.svn_fs_begin_txn(*args)\",\n \"def execute(self, *args, **kwargs):\\n return self.engine.execute(*args, **kwargs)\",\n \"def execute(self, *args, **kwargs):\\n return self.engine.execute(*args, **kwargs)\",\n \"def execute_stored_procedure(self, proc_name, params, base):\\n conn = self.connect_to_database(db=base)\\n connection = conn.connect()\\n result = connection.execute(proc_name, params)\\n connection.close()\\n return result\",\n \"def start_transaction(self) -> None:\\n pass\",\n \"def execute_query(self, query_, return_results_=False):\\n\\n try:\\n if return_results_:\\n logging.info(\\\"Fetching results...\\\")\\n self.query_results = self.cursor.execute(query_)\\n else:\\n self.cursor.execute(query_)\\n logging.info(\\\"Query ran successfully.\\\")\\n\\n except Exception as e:\\n if self.airflow:\\n # For Airflow, forces task to fail and set it up for re-try\\n raise AirflowException(\\\"Error running query. {}\\\"\\n .format(str(e)))\\n else:\\n logging.exception(\\\"Error running query.\\\")\\n raise e\",\n \"def execute(self, start=0, end=0):\\n base_query = self.postgres.session.query(Analysis).\\\\\\n join(Version).\\\\\\n join(Package).\\\\\\n join(Ecosystem).\\\\\\n filter(Analysis.finished_at.isnot(None)).\\\\\\n filter(Analysis.id >= start).\\\\\\n order_by(Analysis.id.asc())\\n\\n if end:\\n base_query = base_query.filter(Analysis.id <= end)\\n\\n while True:\\n self.log.info(\\\"Updating results, slice offset is %s\\\", start)\\n try:\\n results = base_query.slice(start, start + self.query_slice).all()\\n except SQLAlchemyError:\\n self.postgres.session.rollback()\\n raise\\n start += self.query_slice\\n if not results:\\n self.log.info(\\\"No more finished analyses => syncing to GraphDB finished\\\")\\n break\\n\\n for entry in results:\\n arguments = {'ecosystem': entry.version.package.ecosystem.name,\\n 'name': entry.version.package.name,\\n 'version': entry.version.identifier}\\n try:\\n self.log.info('Synchronizing {ecosystem}/{name}/{version} ...'.format(\\n **arguments))\\n GraphImporterTask.create_test_instance().execute(arguments)\\n except Exception:\\n self.log.exception('Failed to synchronize {ecosystem}/{name}/{version}'.\\n format(**arguments))\\n del entry\",\n \"def execute_sql(conn, query):\\n\\ttry:\\n\\t\\t\\tc = conn.cursor()\\n\\t\\t\\tc.execute(query)\\n\\texcept Error as e:\\n\\t\\t\\tprint(f\\\"SQL error :{e}\\\")\\n\\t\\t\\tprint(f\\\"Attempted to run: {query}\\\")\\n\\t\\t\\t\\n\\treturn c\",\n \"def start_transaction(self,):\\n\\n if self.tx is not None:\\n raise OverlappedTransaction(str(self.tx.xid))\\n\\n modlogger.debug(\\\"start tx\\\")\\n opid = self.new_opid()\\n xaction = StartTxOperation(opid,opid)\\n self.tx = Transaction(opid,self.home, track_state = self.track_state)\\n self._add_operation(opid,xaction)\\n return opid\",\n \"def execute_query(self, query):\\n self.recordset = self.con.execute(query)\\n return self\",\n \"def _ExecuteWithSQLConnection(\\n self, sql_cnxn, stmt_str, stmt_args, commit=True):\\n if stmt_str.startswith('INSERT') or stmt_str.startswith('REPLACE'):\\n logging.info('SQL stmt_str: \\\\n%s', stmt_str)\\n logging.info('SQL stmt_args: %r', stmt_args)\\n else:\\n logging.info('SQL stmt: \\\\n%s', (stmt_str % tuple(stmt_args)))\\n\\n start_time = time.time()\\n cursor = sql_cnxn.cursor()\\n cursor.execute('SET NAMES utf8mb4')\\n logging.info('made cursor on %r in %d ms',\\n sql_cnxn, int((time.time() - start_time) * 1000))\\n if stmt_str.startswith('INSERT') or stmt_str.startswith('REPLACE'):\\n cursor.executemany(stmt_str, stmt_args)\\n duration = (time.time() - start_time) * 1000\\n DB_QUERY_LATENCY.add(duration, {'type': 'write'})\\n DB_QUERY_COUNT.increment({'type': 'write'})\\n else:\\n cursor.execute(stmt_str, args=stmt_args)\\n duration = (time.time() - start_time) * 1000\\n DB_QUERY_LATENCY.add(duration, {'type': 'read'})\\n DB_QUERY_COUNT.increment({'type': 'read'})\\n DB_RESULT_ROWS.add(cursor.rowcount)\\n logging.info('%d rows in %d ms', cursor.rowcount,\\n int(duration))\\n\\n if commit and not stmt_str.startswith('SELECT'):\\n try:\\n sql_cnxn.commit()\\n duration = (time.time() - start_time) * 1000\\n DB_COMMIT_LATENCY.add(duration)\\n DB_COMMIT_COUNT.increment()\\n except MySQLdb.DatabaseError:\\n sql_cnxn.rollback()\\n duration = (time.time() - start_time) * 1000\\n DB_ROLLBACK_LATENCY.add(duration)\\n DB_ROLLBACK_COUNT.increment()\\n\\n return cursor\",\n \"def _execute_query(self, select_clause, trailing_clause=None, **kwds_filter):\\n try:\\n stmnt, params = self._build_query(self._table, select_clause, **kwds_filter)\\n if trailing_clause:\\n stmnt += '\\\\n' + trailing_clause\\n cursor = self._connection.cursor()\\n cursor.execute('PRAGMA synchronous=OFF')\\n #print(stmnt, params)\\n cursor.execute(stmnt, params)\\n except Exception as e:\\n exc_cls = e.__class__\\n msg = '%s\\\\n query: %s\\\\n params: %r' % (e, stmnt, params)\\n raise exc_cls(msg)\\n return cursor\",\n \"def BeginExecute(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\\n raise NotImplementedError()\",\n \"def _execute_query(db_path, query, *args):\\n\\n con = sql.connect(db_path)\\n cur = con.cursor()\\n cur.execute(query, args)\\n con.commit()\\n con.close()\",\n \"def DBExecuteScript( DB: sqlite3.Connection, sql:str, *args ):\\n assert isinstance( DB, sqlite3.Connection )\\n DB.executescript( sql )\\n DB.commit()\",\n \"def execute_and_commit_sql(db, sql):\\n conn_string = return_connection(db)\\n with pg2.connect(conn_string) as conn:\\n with conn.cursor() as curs:\\n curs.execute(sql)\\n conn.commit()\",\n \"def execute_both(self, query, *parameters, **kwparameters):\\n cursor = self._cursor()\\n try:\\n self._execute(cursor, query, parameters, kwparameters)\\n return cursor.lastrowid, cursor.rowcount\\n finally:\\n cursor.close()\",\n \"def execute(\\n self, query: str, table: str = None, values: IterOpt = None\\n ) -> sqlite3.Cursor:\",\n \"def commit_query(conn):\\r\\n conn.commit()\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.6814344","0.6080396","0.5855154","0.58330435","0.56852597","0.56840986","0.56803703","0.5670721","0.55603486","0.55467397","0.5541032","0.5533288","0.5515175","0.5459195","0.5458255","0.54457515","0.5431761","0.5396275","0.5384897","0.53836185","0.5356652","0.5352215","0.5315183","0.5272519","0.5240518","0.5233666","0.5223163","0.52117276","0.5205077","0.5201505","0.51902133","0.51732075","0.51719344","0.51565367","0.51534456","0.5129226","0.5129221","0.5124156","0.512265","0.51192516","0.510566","0.50920105","0.5091091","0.50876427","0.50691307","0.5068712","0.5066151","0.50651705","0.5064127","0.5056717","0.5036058","0.50328","0.5026451","0.50143415","0.50128716","0.5011242","0.50007874","0.49956587","0.49941787","0.4978181","0.49541566","0.49448267","0.49222308","0.49203217","0.49171007","0.49163592","0.48937222","0.48840138","0.4880438","0.48790693","0.4875998","0.48679006","0.48676568","0.48666447","0.48665154","0.4862264","0.486031","0.48575234","0.4853003","0.4845767","0.48454905","0.484276","0.48314843","0.48298785","0.48298785","0.4829006","0.48282483","0.48224986","0.48098767","0.4805718","0.47990236","0.47929692","0.47827595","0.47793055","0.47691843","0.47653067","0.47618222","0.47605228","0.47603893","0.4756123","0.4750635"],"string":"[\n \"0.6814344\",\n \"0.6080396\",\n \"0.5855154\",\n \"0.58330435\",\n \"0.56852597\",\n \"0.56840986\",\n \"0.56803703\",\n \"0.5670721\",\n \"0.55603486\",\n \"0.55467397\",\n \"0.5541032\",\n \"0.5533288\",\n \"0.5515175\",\n \"0.5459195\",\n \"0.5458255\",\n \"0.54457515\",\n \"0.5431761\",\n \"0.5396275\",\n \"0.5384897\",\n \"0.53836185\",\n \"0.5356652\",\n \"0.5352215\",\n \"0.5315183\",\n \"0.5272519\",\n \"0.5240518\",\n \"0.5233666\",\n \"0.5223163\",\n \"0.52117276\",\n \"0.5205077\",\n \"0.5201505\",\n \"0.51902133\",\n \"0.51732075\",\n \"0.51719344\",\n \"0.51565367\",\n \"0.51534456\",\n \"0.5129226\",\n \"0.5129221\",\n \"0.5124156\",\n \"0.512265\",\n \"0.51192516\",\n \"0.510566\",\n \"0.50920105\",\n \"0.5091091\",\n \"0.50876427\",\n \"0.50691307\",\n \"0.5068712\",\n \"0.5066151\",\n \"0.50651705\",\n \"0.5064127\",\n \"0.5056717\",\n \"0.5036058\",\n \"0.50328\",\n \"0.5026451\",\n \"0.50143415\",\n \"0.50128716\",\n \"0.5011242\",\n \"0.50007874\",\n \"0.49956587\",\n \"0.49941787\",\n \"0.4978181\",\n \"0.49541566\",\n \"0.49448267\",\n \"0.49222308\",\n \"0.49203217\",\n \"0.49171007\",\n \"0.49163592\",\n \"0.48937222\",\n \"0.48840138\",\n \"0.4880438\",\n \"0.48790693\",\n \"0.4875998\",\n \"0.48679006\",\n \"0.48676568\",\n \"0.48666447\",\n \"0.48665154\",\n \"0.4862264\",\n \"0.486031\",\n \"0.48575234\",\n \"0.4853003\",\n \"0.4845767\",\n \"0.48454905\",\n \"0.484276\",\n \"0.48314843\",\n \"0.48298785\",\n \"0.48298785\",\n \"0.4829006\",\n \"0.48282483\",\n \"0.48224986\",\n \"0.48098767\",\n \"0.4805718\",\n \"0.47990236\",\n \"0.47929692\",\n \"0.47827595\",\n \"0.47793055\",\n \"0.47691843\",\n \"0.47653067\",\n \"0.47618222\",\n \"0.47605228\",\n \"0.47603893\",\n \"0.4756123\",\n \"0.4750635\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":15595,"cells":{"query":{"kind":"string","value":"BeginExecuteBatch executes a begin and a list of queries."},"document":{"kind":"string","value":"def BeginExecuteBatch(self, request, context):\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\n context.set_details('Method not implemented!')\n raise NotImplementedError('Method not implemented!')"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def BeginExecuteBatch(self, request, context):\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)","def BeginExecuteBatch(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\n raise NotImplementedError()","def insert_many_execute(self) -> None:\n self.connection.isolation_level = None\n self.cursor.execute('BEGIN TRANSACTION')\n for i in self.__sql_buffer.split(';'):\n self.cursor.execute(i)\n self.__sql_buffer = \"\"\n self.cursor.execute('COMMIT')","def batch_execute(self, conn):\n def batches(data, batch_size) -> list:\n \"\"\"Return batches of length `batch_size` from any object that\n supports iteration without knowing length.\"\"\"\n rv = []\n for idx, line in enumerate(data):\n if idx != 0 and idx % batch_size == 0:\n yield rv\n rv = []\n rv.append(line)\n yield rv\n\n columns = ColumnCollection(self.columns)\n if self.header:\n self.columns = [columns.get(h) for h in next(self.data)]\n columns = ColumnCollection(self.columns)\n\n total = 0\n query = BulkInsertQuery(self.table, columns)\n for batch in batches(self.data, self.batch_size):\n total += query.execute(conn, batch) or 0\n yield total","def batch(self, batch_identifier, begin_operation):\n logger.debug('Starting transaction...')\n self.publish(\n batch_operation=BatchOperation(\n batch_identifier=batch_identifier,\n begin_operation=begin_operation,\n ),\n )\n\n def mutation(mutation_operation):\n return self.publish(\n batch_operation=BatchOperation(\n batch_identifier=batch_identifier,\n mutation_operation=mutation_operation,\n ),\n )\n\n try:\n yield mutation\n except Exception:\n logger.debug('Attempting to publish rollback of in progress transaction...')\n self.publish(\n batch_operation=BatchOperation(\n batch_identifier=batch_identifier,\n rollback_operation=RollbackOperation(),\n ),\n )\n logger.debug('Published rollback.')\n raise\n else:\n logger.debug('Attempting to publish commit of in progress transaction...')\n self.publish(\n batch_operation=BatchOperation(\n batch_identifier=batch_identifier,\n commit_operation=CommitOperation(),\n ),\n )\n logger.debug('Published commit.')","def batch_execute(self, sql_list):\n with self.connection.cursor() as dbc:\n responses = []\n for sql in sql_list:\n dbc.execute(sql)\n responses.append(dbc.fetchall())\n return responses","def ExecuteBatch(self, request, context):\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)","def ExecuteBatch(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\n raise NotImplementedError()","def execute_query_sequence(db_cursor, all_queries):\n\n for query in all_queries:\n db_cursor.execute(query)","def execute_queries(self, queries, **format_args):\n query_len = len(queries)\n commit = False\n\n for i,query in enumerate(queries):\n q = query.format(**format_args)\n\n if i >= query_len - 1:\n commit = True\n\n self._submit_single_q(q, commit=commit)","def batched_query(self, sql):\r\n\r\n result_sets = []\r\n messages = \"\"\r\n query = []\r\n last_query=\"\"\r\n\r\n batches = re.split(\"^\\s*(GO(?:\\s+[0-9]+)?)\\s*(?:--.*)?$\",sql,flags=re.M|re.I)\r\n # print(batches)\r\n for b in batches:\r\n if b.upper() == \"GO\":\r\n # execute one\r\n query.append(last_query)\r\n continue\r\n else:\r\n match = re.match(\"^GO\\s+([0-9]+)$\",b,re.I)\r\n if match is not None:\r\n #execute many\r\n for i in range(0,int(match.group(1))):\r\n query.append(last_query)\r\n else:\r\n # not a Go statment\r\n last_query = b\r\n query.append(last_query)\r\n\r\n # print(query)\r\n for q in query:\r\n r = self.query(q)\r\n if r is not None:\r\n result_sets.extend(r)\r\n messages += self.messages\r\n\r\n self.messages = messages\r\n return result_sets","def on_batch_begin(self, batch, logs=None):","def execute_query_list(cur, conn, query_list):\n try:\n for query in query_list:\n cur.execute(query)\n conn.commit()\n except psycopg2.Error as e:\n print(\"Error executing query list\")\n print(e)","def batch(self, sql):\n return _Batch(self.conn, sql)","def batch_get_query_execution(QueryExecutionIds=None):\n pass","def ExecuteBatchQueue(self):\n\t\tself.client.ExecuteBatch(self.batch_queue, 'https://www.google.com/m8/feeds/contacts/default/full/batch')\n\t\tself.ClearBatchQueue();","def executeQuery(self, segments=None,):\n if not segments: segments = self.segments\n query =''.join(['INSERT INTO ', self.tableName, ' (',\n ', '.join(self.firstLine), ') VALUES ',\n ', '.join([segment for segment in segments]), ';'])\n try:\n self.cursorExecute(query)\n except:\n print 'Bulk query rejected, splitting into smaller queries.'\n self.handleSQLRejection(0, len(self.segments))","def produce_query_batches(self):\n pass","def _multi_query_execution(self):\n multi_query_staging = self.query.split(';')\n for query in multi_query_staging:\n self.query = query\n self._execute_command()","def execute_many(self, query, parameters):\n return self._executemany_lastrowid(query, parameters)","def executemany(self, operation, seq_of_parameters):\r\n if self._closed:\r\n raise Error('The cursor has been closed.')\r\n if self.connection._closed:\r\n raise Error('The connection to the database has been closed.')\r\n for parameters in seq_of_parameters:\r\n self.execute(operation, parameters)","def _batch_insert(bq_client, table, rows):\n total_rows = len(rows)\n inserted_rows = 0\n batch = 1\n logger.info(\"Inserting %d rows into table %s\", total_rows,\n table.full_table_id)\n while inserted_rows < total_rows:\n start = (batch - 1) * MAX_BQ_INSERT_SIZE\n end = batch * MAX_BQ_INSERT_SIZE\n batch_rows = rows[start:end]\n inserted_rows += len(batch_rows)\n errors = _insert_rows(bq_client, table, batch_rows)\n if errors:\n print_bq_insert_errors(batch_rows, errors)\n logger.error(\n \"The program has been terminated due to BigQuery insertion \"\n \"errors.\")\n exit(1)\n else:\n logger.info(\"Batch %d: inserted rows %d to %d\", batch, start + 1,\n min(end, len(rows)))\n batch += 1\n logger.info(\"All rows inserted.\")","def applyBatch(self, authority, operations):\n pass","def sql_scripts_execute(self, sql_scripts, params={}):\n ps = self.parameter_handler(params)\n log.debug('Got parameters: %s', ps)\n cursor = self._get_cursor()\n for q in sql_scripts:\n with open(q, 'r') as s:\n sql_string_formatted = s.read().format(**ps)\n cursor.execute(sql.SQL(sql_string_formatted), ps)\n self.connection.commit()\n self.connection.close()","def _batching_call(self, *args, **kw):\n b_start = kw.pop('b_start', None)\n b_size = kw.pop('b_size', None)\n results = list(self._original_call(*args, **kw))\n\n if b_start is None:\n return results\n\n if b_size is None:\n b_size = len(results)\n\n return results[b_start:b_start+b_size]","def on_test_batch_begin(self, batch, logs=None):","def flush_batch(self, batch: Sequence[TResult]) -> None:\n pass","def begin(self):\n self._in_transaction = True\n self.execute(\"BEGIN\")","def execute_many(self, query: str, args):\n return self.insert_many(query, args)","def ExecuteBatch(self, request, context):\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\n context.set_details('Method not implemented!')\n raise NotImplementedError('Method not implemented!')","def ExecuteBatch(self, request, context):\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\n context.set_details('Method not implemented!')\n raise NotImplementedError('Method not implemented!')","def _insert_bulk(self, iterable):\n self.cursor.executemany(self.INSERT, iterable)\n self.conn.commit()","def execute_queries():\n fetch_job_listings(engine)\n update_job_listing(engine)","def executemany(self, operation, seq_of_parameters):\n self._check_closed()\n\n p_statement = self._statement_cache.get_prepared_statement(operation)\n self.session.execute_batch_prepared_statement(p_statement, seq_of_parameters)","def loadbatch():\n s=\"select * from tblbatch where status='1'\"\n c.execute(s)\n data=c.fetchall()\n return data","def execute_many(self, sql, args=None):\r\n args = args or None\r\n with Executer(self) as cursor:\r\n rows = cursor.executemany(sql, args)\r\n return rows","def execute(self, start=0, end=0):\n base_query = self.postgres.session.query(Analysis).\\\n join(Version).\\\n join(Package).\\\n join(Ecosystem).\\\n filter(Analysis.finished_at.isnot(None)).\\\n filter(Analysis.id >= start).\\\n order_by(Analysis.id.asc())\n\n if end:\n base_query = base_query.filter(Analysis.id <= end)\n\n while True:\n self.log.info(\"Updating results, slice offset is %s\", start)\n try:\n results = base_query.slice(start, start + self.query_slice).all()\n except SQLAlchemyError:\n self.postgres.session.rollback()\n raise\n start += self.query_slice\n if not results:\n self.log.info(\"No more finished analyses => syncing to GraphDB finished\")\n break\n\n for entry in results:\n arguments = {'ecosystem': entry.version.package.ecosystem.name,\n 'name': entry.version.package.name,\n 'version': entry.version.identifier}\n try:\n self.log.info('Synchronizing {ecosystem}/{name}/{version} ...'.format(\n **arguments))\n GraphImporterTask.create_test_instance().execute(arguments)\n except Exception:\n self.log.exception('Failed to synchronize {ecosystem}/{name}/{version}'.\n format(**arguments))\n del entry","def run_multiple(self, sql, it):\n self.database.executemany(sql, it)","def _dispatch_batches(self, base_url, endpoint, item_list, prep_args, dataset_id=None, dataset_version=None):\n pool = ThreadPool(processes=self.pool_size)\n batch = []\n\n # Decide which _prep function to use based on the endpoint\n if endpoint == 'import' or endpoint == 'import-events':\n prep_function = Mixpanel._prep_event_for_import\n elif endpoint == 'engage' or endpoint == 'import-people':\n prep_function = Mixpanel._prep_params_for_profile\n else:\n Mixpanel.LOGGER.warning(\n 'endpoint must be \"import\", \"engage\", \"import-events\" or \"import-people\", found: ' + str(endpoint))\n return\n\n if base_url == self.BETA_IMPORT_API:\n batch_size = 1000\n else:\n batch_size = 50\n\n for item in item_list:\n if prep_args is not None:\n # Insert the given item as the first argument to be passed to the _prep function determined above\n prep_args[0] = item\n params = prep_function(*prep_args)\n if params:\n batch.append(params)\n else:\n batch.append(item)\n\n if len(batch) == batch_size:\n # Add an asynchronous call to _send_batch to the thread pool\n pool.apply_async(self._send_batch, args=(base_url, endpoint, batch, dataset_id, dataset_version),\n callback=Mixpanel._response_handler_callback)\n batch = []\n\n # If there are fewer than batch_size updates left ensure one last call is made\n if len(batch):\n # Add an asynchronous call to _send_batch to the thread pool\n pool.apply_async(self._send_batch, args=(base_url, endpoint, batch, dataset_id, dataset_version),\n callback=Mixpanel._response_handler_callback)\n pool.close()\n pool.join()","def on_batch_start(self):\n for callback in self.callbacks:\n callback.on_batch_start(self, self.get_model())","def run_multiple_sql_statements(statements, fetch=True, cur=None, conn=None, commit=True):\n\n try:\n if conn is None:\n logger.error(\"Connection cannot be None.\")\n raise ValueError(\"Connection cannot be None.\")\n\n if cur is None:\n cur = conn.cursor()\n\n if statements is None:\n logger.error(\"Sql statement list is empty\")\n raise ValueError(\"Sql statement list is empty\")\n\n for _, statement in enumerate(statements):\n logger.debug(\"Executing SQL = \" + statement)\n res = cur.execute(statement)\n if fetch:\n data = cur.fetchall()\n else:\n data = None\n if commit:\n conn.commit()\n except Exception as exception:\n logger.error(exception)\n raise exception\n\n return (res, data)","def batch_start(self, batch_idx, batch_data):\n self.batch = batch_idx","def _batcher(self, rows):\n row_count = 0\n batch = []\n batch_count = 1\n\n total_rows_modified = 0\n throttle_count = 0\n\n i = 0\n for row in rows:\n if row_count > self.batch_size - 1:\n logger.debug(f\"row_count={row_count} batch_size={self.batch_size} and batch={len(batch)}\")\n # Yield the previous batch\n yield batch\n\n # Start the new batch\n batch = []\n batch.append(row)\n row_count = 1\n\n batch_count += 1\n # break # toggle to load one batch only\n else:\n row_count += 1\n batch.append(row)\n\n # Put in a sleep timer to throttle how hard we hit the database\n if self.throttle_time and self.throttle_size and (throttle_count > self.throttle_size - 1):\n logger.info(f\"Sleeping for {self.throttle_time} seconds... row: {i}\")\n time.sleep(int(self.throttle_time))\n throttle_count = 0\n elif self.throttle_time and self.throttle_size:\n throttle_count += 1\n i += 1\n\n yield batch","def insert_result_batch(self, results):\n session = self.session_factory()\n for result in results:\n if not self._check_row_exists(pk=result.get('id')):\n session.add(PipelineRun(**result))\n if self._get_filtered_results(id=result.get('id'), status='IN_PROGRESS'):\n session.query(PipelineRun).filter_by(id=result.get('id')).update(result)\n session.commit()\n session.close()","def __insertBasicUsersQueries(self,_count,user_ids,credit,owner_id,group_id,ibs_query):\n for user_id in user_ids:\n ibs_query+=self.__insertBasicUserQuery(user_id,credit,owner_id,group_id)","def insert_many(self, query: str, args):\n cursor = self._cursor()\n try:\n cursor.execute_many(query, args)\n return cursor.lastrowid\n finally:\n cursor.close()","def runQueryWrite(d, queryList):\n for query in queryList:\n with d.session() as s:\n s.write_transaction(runQuery, query)","def _execute_deferred_queries(self):\n\n assert not self.__is_connected\n\n if not self._deferred_queries:\n return\n\n with Transaction(self.__database_name) as txn:\n while True:\n try:\n query = self._deferred_queries.popleft()\n txn.session.execute(query).close()\n except IndexError:\n break","def batch(self):\n return self._client.batch()","def commit_inserts(session, insert_statements, table, is_mysql, commit_frequency = 1000):\n if is_mysql:\n ignore_prefix = (\"IGNORE\",)\n session.execute(\"set foreign_key_checks = 0; set unique_checks = 0;\")\n session.commit()\n else:\n ignore_prefix = (\"OR IGNORE\",)\n numgroups = len(insert_statements) / commit_frequency\n for ng in range(numgroups):\n if numgroups == 0:\n break\n chunk = insert_statements[ng*commit_frequency:(ng+1)*commit_frequency]\n session.connection().execute(table.insert(prefixes=ignore_prefix), chunk)\n print \"committing chunk\",ng+1,\"of\",numgroups,\"with length\",len(chunk),\"at\",datetime.now()\n session.commit()\n last_chunk = insert_statements[numgroups*commit_frequency:]\n if last_chunk:\n print \"committing last\",len(last_chunk),\"records at\",datetime.now()\n session.connection().execute(table.insert(prefixes=ignore_prefix), last_chunk)\n session.commit()","def make_batch_request(self, batch):\n args = {}\n args['access_token'] = self.access_token\n args['batch'] = json.dumps(batch)\n args = {k.encode('utf-8'): unicode(v).encode('utf-8')\n for k, v in args.items()}\n logger.info('Making a batched request with %s' % args)\n try:\n f = urllib2.urlopen(self.api_root, urllib.urlencode(args))\n data = json.load(f)\n # For debugging\n self.data = data\n for idx, val in enumerate(data):\n data[idx] = json.loads(val['body'])\n return data\n except urllib2.HTTPError as e:\n logger.info('%s' % e)\n return json.load(e)\n except urllib2.URLError as e:\n logger.warn('URLError: %s' % e.reason)","def process_batch(sm_account_id, graph, interactions, batch_requests, p_session, processed_interactions=None,\n cutoff=None):\n with transaction.manager:\n for interaction in interactions:\n p_session.merge(interaction)\n\n if len(batch_requests) == 0 or (processed_interactions and processed_interactions >= cutoff):\n return\n\n # process batch requests\n # Number of max items in a batch request is 50\n MAX_BATCH_SIZE = 50\n batch_requests_p = [{'method': req.get('method'), 'relative_url': req.get('relative_url')} for req in\n batch_requests]\n batch_data = []\n\n interactions_new = set()\n batch_requests_new = []\n\n for i in range(math.ceil(len(batch_requests_p) / MAX_BATCH_SIZE)):\n # TODO handle connection error. attempt retries\n try:\n batch_req = json.dumps(batch_requests_p[i * MAX_BATCH_SIZE:(i * MAX_BATCH_SIZE) + (MAX_BATCH_SIZE - 1)],\n indent=1)\n batch_data += graph.request(\"\", post_args={\n 'batch': batch_req})\n\n except ConnectionError as e:\n logger.exception('unable to process batch request \\n:{}'.format(batch_req))\n for req, batch_response in zip(batch_requests, batch_data):\n parent_id = req.get('parent_id')\n if 'body' in batch_response:\n batch_response_data = json.loads(batch_response['body'])\n if 'error' in batch_response_data and batch_response_data['error'].get('code') == 1:\n # handle request failure - 'Please reduce the amount of data you are asking for, then retry your request'\n error_url = req.get('relative_url')\n parse_result = urlparse(error_url)\n query_data = urlparse.parse_qs(parse_result.query)\n old_limit = query_data.get('limit')[0]\n sm_account_id = parse_result.path.split(\"/\")[2]\n new_limit = int(float(old_limit) / 2)\n new_req = get_feed_request(sm_account_id, limit=new_limit)\n batch_requests_new.append(new_req)\n\n if 'data' in batch_response_data:\n for interaction_raw in batch_response_data['data']:\n Interactions.get_nested_interactions(sm_account_id, interaction_raw, interactions_new,\n batch_requests_new, parent_id)\n if 'paging' in batch_response_data and 'next' in batch_response_data['paging']:\n next_url = urlparse(batch_response_data['paging']['next'])\n relative_url = next_url.path + '?' + next_url.query + '&include_headers=false'\n req = {'method': 'GET', 'relative_url': relative_url, 'parent_id': parent_id}\n batch_requests_new.append(req)\n else:\n logger.info('Exception occurred while collecting posts for {} skipping this..'.format(sm_account_id))\n\n process_batch(sm_account_id, graph, interactions_new, batch_requests_new, p_session,\n processed_interactions + len(interactions), cutoff)","def update_batch(self, *args, **kwargs):\n pass","def commit(cls, sql, **kwargs):\n conn = kwargs['conn']\n\n cursor = conn.cursor(dictionary=True, buffered=False)\n if CHECKS_OFF:\n sql = TURN_CHECKS_OFF + sql\n\n for _ in cursor.execute(sql, kwargs.get('args'), multi=True):\n pass\n\n cls.close(conn, cursor)","def execute(self):\n if self.sql is None:\n self.sql = self.construct_query()\n # Only SQL strings can be split, not (e.g.) SQLAlchemy statements.\n if self.multiple_statements and isinstance(self.sql, str):\n statements = self._split_sql()\n else:\n statements = [self.sql]\n single_statement = True if len(statements) == 1 and self.filename else False\n try:\n for statement in statements:\n result_proxy = self.cm.conn.execute(statement)\n log_string = self.filename if single_statement else str(statement)[:25]\n self.logger.info(\"Executed {} against {}\".format(log_string, self.cm.db))\n if result_proxy.cursor:\n return self.fetch_results(result_proxy)\n except Exception as e:\n self.logger.exception(e)\n raise","def insert_boost(connection: DBConnection, documents: Sequence[Document]) -> None:\n max_ = len(documents)\n current = 0\n print() # print an extra line, because we will delete lines with printing \\r\n for chunk in chunks(documents):\n\n connection.execute(\"BEGIN TRANSACTION\")\n for doc in chunk:\n connection.execute(\n \"INSERT INTO boost(did, date, page) VALUES (?, ?, ?)\", (doc.id, doc.date, doc.page))\n connection.execute(\"COMMIT\")\n current += len(chunk)\n print(f\"\\r[{current}/{max_}] boost done\", end='')\n print()","def execute_batch(self, commands=()):\n if not hasattr(commands, \"__iter__\"):\n raise InvalidCommandValue(\"commands must be an iterable\")\n if self._execute_batch_fn is None:\n raise MissingFunctionDefinition(\"execute_batch method is not mapped\")\n return self._execute_batch_fn(commands)","def execute(\n self,\n query,\n count=False,\n batch_size=None,\n ttl=None,\n bind_vars=None,\n full_count=None,\n optimizer_rules=None,\n fail_on_warning=None,\n profile=None,\n max_transaction_size=None,\n max_warning_count=None,\n intermediate_commit_count=None,\n intermediate_commit_size=None,\n skip_inaccessible_collections=None,\n stream=None,\n sql=False,\n ):\n data = {\"query\": query, \"count\": count}\n if batch_size is not None:\n data[\"batchSize\"] = batch_size\n if ttl is not None:\n data[\"ttl\"] = ttl\n if bind_vars is not None:\n data[\"bindVars\"] = bind_vars\n\n options = {}\n if full_count is not None:\n options[\"fullCount\"] = full_count\n if optimizer_rules is not None:\n options[\"optimizer\"] = {\"rules\": optimizer_rules}\n if fail_on_warning is not None:\n options[\"failOnWarning\"] = fail_on_warning\n if profile is not None:\n options[\"profile\"] = profile\n if max_transaction_size is not None:\n options[\"maxTransactionSize\"] = max_transaction_size\n if max_warning_count is not None:\n options[\"maxWarningCount\"] = max_warning_count\n if intermediate_commit_count is not None:\n options[\"intermediateCommitCount\"] = intermediate_commit_count\n if intermediate_commit_size is not None:\n options[\"intermediateCommitSize\"] = intermediate_commit_size\n if skip_inaccessible_collections is not None:\n options[\"skipInaccessibleCollections\"] = skip_inaccessible_collections\n if stream is not None:\n options[\"stream\"] = stream\n if options:\n data[\"options\"] = options\n data.update(options)\n\n command = (\n \"db._query({}, {}, {}).toArray()\".format(\n dumps(query),\n dumps(bind_vars),\n dumps(data),\n )\n if self._is_transaction\n else None\n )\n\n if sql:\n end_point = \"/cursor/sql\"\n else:\n end_point = \"/cursor\"\n\n request = Request(method=\"post\", endpoint=end_point, data=data, command=command)\n\n def response_handler(resp):\n if not resp.is_success:\n raise C8QLQueryExecuteError(resp, request)\n return Cursor(self._conn, resp.body)\n\n return self._execute(request, response_handler)","def on_train_batch_begin(self, batch, logs=None):\n # For backwards compatibility\n self.on_batch_begin(batch, logs=logs)","def start_transaction_sql(self):\n return \"BEGIN TRANSACTION\"","def test_custom_query_batching(self):\n\n # Construct Batch Statement\n batch = BatchStatement(BatchType.LOGGED)\n for i in range(10):\n batch.add(SimpleStatement(\"INSERT INTO test3rf.test (k, v) VALUES (%s, %s)\"), (i, i))\n\n # Validate that various types of custom payloads are sent and received okay\n self.validate_various_custom_payloads(statement=batch)","def execute(self, limit=None, offset=None, conn=None):\n statement = self._statement\n if limit is not None:\n if offset is not None:\n statement += \"\\nLIMIT {0} OFFSET {0}\".format(limit, offset)\n else:\n statement += \"\\nLIMIT \" +str(limit)\n \n results = []\n \n manage_conn = conn is None\n if manage_conn:\n conn = self._db.pool.get()\n cur = conn.cursor()\n \n cur.execute(statement, self._params.get_dbapi_params())\n results = cur.fetchall()\n \n cur.close()\n if manage_conn:\n conn.close()\n \n return [ self._process_result(r) for r in results ]","def insertmany(cls, *args):\n return InsertQuery(cls).bulk(True).set(*args)","def _run_queries(self, persist):\n self._mark_start()\n self._run_query()\n\n # Check if we want to keep going.\n if not persist:\n self._compile_results()\n return\n\n # Get the rest of the content.\n while not self._done():\n self._run_query()\n\n # Create the actual statements.\n self._compile_results()\n\n # This is end of the loop, one way or another. Restore logging if it\n # was redirected.\n request_logger.unquiet()\n util_logger.unquiet()\n return","def execute_sql_files(connection, sql_files):\n for filename in sql_files:\n statement = resource_text(filename)\n for sub_statement in statement.split(\";\"):\n if sub_statement.strip():\n connection.execute(text(sub_statement))","def batch(self, requests):\n return AlgoliaUtils_request(self.headers, self.write_hosts, \"POST\", \"/1/indexes/*/batch\", self.timeout, {\"requests\": requests})","def _execute_query(self, query, values):\n with self as plasticDB:\n cursor = plasticDB.connection.cursor()\n cursor.execute(query,values)\n if not cursor.description:\n return []\n rs = RecordSet(initialData=cursor.fetchall(), recordType=next(zip(*cursor.description)))\n return rs","def get_all_batches(self, query, bind_vars=None, batch_size=1000):\n write_ops = [\"INSERT\", \"UPDATE\", \"REPLACE\", \"REMOVE\", \"UPSERT\"]\n if any(ele in query.upper() for ele in write_ops):\n raise C8QLGetAllBatchesError(\n \"Write operations provided in the query. Only read operations can be provided\"\n )\n\n cursor = self.execute(\n query=query, bind_vars=bind_vars, batch_size=batch_size, stream=True\n )\n while cursor.has_more():\n cursor.fetch()\n\n result = clean_doc(cursor.batch())\n return result","def do_bulk(self, args):\n pass","def _send_batch(self, base_url, endpoint, batch, dataset_id=None, dataset_version=None, retries=0):\n try:\n params = {'data': base64.b64encode(json.dumps(batch).encode()).decode()}\n if dataset_id:\n params['dataset_id'] = dataset_id\n params['token'] = self.token\n if dataset_version:\n params['dataset_version'] = dataset_version\n response = self.request(base_url, [endpoint], params, 'POST')\n msg = \"Sent \" + str(len(batch)) + \" items on \" + time.strftime(\"%Y-%m-%d %H:%M:%S\") + \"!\"\n Mixpanel.LOGGER.debug(msg)\n return response\n except BaseException as be:\n Mixpanel.LOGGER.debug('Exception in _send_batch')\n Mixpanel.LOGGER.debug(be)\n Mixpanel.LOGGER.warning(\"Failed to import batch, dumping to file import_backup.txt\")\n with open('import_backup.txt', 'a+') as backup:\n json.dump(batch, backup)\n backup.write('\\n')","def update_batch_of_entitiies(self, username, entity_batch_data):\n\t\treturn self._send_command_to_entity_server(us.SERVER_COMMAND_UPDATE_ENTITY_BATCH, username + '|' + str(entity_batch_data))","def execute(self):\n return self._batch.execute()","def execute(self):\n for coll in list(self.__bulks):\n try:\n bulkOp = self.__bulks[coll]\n curr_result = Counter(bulkOp.execute())\n self.update_results(coll, curr_result)\n except BulkWriteError as bwe:\n sys.stderr.write(str(bwe.details))","def execute(self, jobID = None, couchID = None, bulkList = None, conn = None,\n transaction = False):\n\n if isinstance(bulkList, list):\n binds = bulkList\n else:\n binds = {\"jobid\": jobID, \"couchid\": couchID}\n\n self.dbi.processData(self.sql, binds,\n conn = conn, transaction = transaction)\n return","def test_batch_by_transaction_id_multiple_txn_ids():\n # Add batch that has txn 123\n testResponder = TestResponder()\n\n transaction = transaction_pb2.Transaction(header_signature=\"123\")\n batch = batch_pb2.Batch(\n header_signature=\"abc\", transactions=[transaction])\n testResponder.completer.add_batch(batch)\n # Request transactions 123 and 456\n message = network_pb2.GossipBatchByTransactionIdRequest(\n ids=[\"123\", \"456\"],\n time_to_live=1)\n testResponder.batch_by_txn_request_handler.handle(\n \"Connection_1\", message.SerializeToString())\n testResponder.batch_request_handler.handle(\n \"Connection_1\", message.SerializeToString())\n\n # Respond with a BatchResponse for transaction 123\n\n # Broadcast a BatchByTransactionIdRequest for just 456\n after_message = \\\n network_pb2.GossipBatchByTransactionIdRequest(\n ids=[\"456\"],\n time_to_live=0)","def on_test_batch_begin(\n self, batch: int, logs: tp.Optional[tp.Dict[str, np.ndarray]] = None\n ):\n pass","def query_many(self, queries):\n assert isinstance(queries, list)\n cursor = self._cursor()\n results = []\n for query in queries:\n try:\n cursor.execute(query)\n result = cursor.fetchall()\n except Exception as e:\n print(e)\n result = []\n results.append(result)\n return results","def begin(transactionId, *args):\n global _operationCount\n # noinspection PyUnresolvedReferences\n _log.info(\n # \"%s BEGIN %s\" % (transactionId.hex, \" \".join(util.encode2(a) for a in args))\n f\"{transactionId.hex} BEGIN {' '.join(impl.util.encode2(a) for a in args)}\"\n )\n _countLock.acquire()\n try:\n _operationCount += 1\n finally:\n _countLock.release()","def ExecuteBatch(self, batch_feed, url=None, spreadsheet_key=None, \n worksheet_id=None,\n converter=gdata.spreadsheet.SpreadsheetsCellsFeedFromString):\n\n if url is None:\n url = self._GenerateCellsBatchUrl(spreadsheet_key, worksheet_id)\n return self.Post(batch_feed, url, converter=converter)","def write(self, batch):\n cursor = connection.cursor()\n while batch:\n values = [\n \"(%s, %s)\" % (\n psycopg2.Binary(k),\n psycopg2.Binary(v)\n ) for k, v in batch[:self.BATCH_SIZE]]\n sql = \"INSERT INTO %s(k,v) VALUES %s\" % (self.table, \",\".join(values))\n batch = batch[self.BATCH_SIZE:]\n cursor.execute(sql)\n cursor.execute(\"COMMIT\")","def batch_process_async(self, delete_list=[], update_list=[]):\n headers = update_dict(self.default_headers, {self.API_VERSION_HEADER: self.API_VERSIONS[\"v2\"]})\n self.request_url = \"{0}/{1}\".format(self.API_URL, self.USER_BULK_ENDPOINT)\n\n payload = {\n 'updated': update_list,\n 'deleted': delete_list,\n }\n\n r = self.requests.post(self.request_url, data=json.dumps(payload), headers=headers, timeout=30)\n\n return r.status_code, r.json()","def insert_documents(connection: DBConnection, documents: Sequence[Document]) -> None:\n max_ = len(documents)\n current = 0\n print() # print an extra line, because we will delete lines with printing \\r\n for chunk in chunks(documents):\n connection.execute(\"BEGIN TRANSACTION\")\n for doc in chunk:\n # python doesn't support prepared statements, but instead has a builtin sql cache\n connection.execute(\n \"INSERT INTO docs(did, title, url) VALUES (?, ?, ?)\", doc.convert_to_tuple())\n current += 1\n print(f\"\\r[{current}/{max_}] doc done\", end='')\n connection.execute(\"COMMIT\")","def insert_data_many(settings_filename, query_filename, data_list):\n conn = connect_to_db(settings_filename)\n cursor = conn.cursor()\n \n query = load_query(query_filename)\n cursor.prepare(query)\n logging.debug(query)\n cursor.executemany(None, data_list)\n conn.commit()\n \n cursor.close()\n conn.close()\n\n return True","def batch_delete_import_data(importTaskIds=None):\n pass","def batch(\n arguments: List[BatchArgument],\n *,\n uniform_mime_type: str,\n include_output: bool = True,\n drive_service: Optional[discovery.Resource] = None,\n) -> List[drive_api.ResourceID]:\n\n # callback will append resulting IDs in order\n result: List[drive_api.ResourceID] = []\n\n def batch_response(request_id, response, exception) -> None:\n nonlocal result\n result.append(response.get(\"id\"))\n\n requests = [\n request(\n name=argument.name,\n mime_type=uniform_mime_type,\n parent_folder_id=argument.parent_folder_id,\n drive_service=drive_service,\n )\n for argument in arguments\n ]\n kwargs = {\"requests\": requests, \"drive_service\": drive_service}\n if include_output:\n kwargs[\"callback\"] = batch_response\n drive_api.batch_command(**kwargs)\n return result","def sfdcCreateBatch(query, chunk_size=10000, **kwargs):\n api_ver = kwargs.get('api_ver', '')\n session_id = kwargs.get('session_id', '')\n instance = kwargs.get('instance', '')\n job_id = kwargs.get('job_id', '')\n sfdcXml = kwargs.get('sfdcXml', {})\n\n bodyXml = sfdcXml.get('batch', {}).get('body')\n url = sfdcXml.get('batch', {}).get('url')\n headers = sfdcXml.get('batch', {}).get('headers')\n\n bodyXml = unicode(query, \"UTF-8\")\n url = url.format(instance=instance, api_ver=api_ver,\\\n job_id=job_id)\n headers['Content-Type'] = headers.get('Content-Type', '')\\\n .format(chunk_size=chunk_size)\n headers['X-SFDC-Session'] = session_id\n\n resp = requests.post(url=url, headers=headers, data=bodyXml)\n dictResp = xmltodict.parse(resp.text)\n batch_id = str(dictResp['batchInfo']['id'])\n\n return batch_id","def FinishAllFlows(**kwargs):\n for client_id_batch in data_store.REL_DB.ReadAllClientIDs():\n for client_id in client_id_batch:\n FinishAllFlowsOnClient(client_id, **kwargs)","def _process(self, start_key, batch_size):\n\n query = self.MODEL.all()\n if start_key:\n query.filter('__key__ > ', start_key)\n\n try:\n entities = query.fetch(batch_size)\n\n if not entities:\n # all entities has already been processed\n return\n\n for entity in entities:\n try:\n self._processEntity(entity)\n except db.Error, e:\n import logging\n logging.exception(e)\n logging.error(\"Broke on %s: %s\" % (entity.key().name(), self.MODEL))\n\n # process the next batch of entities\n start_key = entities[-1].key()\n deferred.defer(self._process, start_key, batch_size)\n except DeadlineExceededError:\n # here we should probably be more careful\n deferred.defer(self._process, start_key, batch_size)","def start_transaction_sql(self):\n return 'START TRANSACTION;'","def execute_block(self, stmt: List[loxStmtAST.Stmt], environment: loxenvironment.Environment) -> None:\n previous_env: loxenvironment.Environment = self.environment\n try:\n self.environment = environment\n for statement in stmt:\n self.execute(statement)\n finally:\n self.environment = previous_env","def flush_to_disk(self):\n logger.info(\"Flushing %s queries from in-memory cache to disk\", len(self.batch_writes))\n rows = self.memory_connection.execute(f\"\"\"\n SELECT hash_id, query, raw_query, domain, intent FROM queries\n WHERE rowid IN ({\",\".join(self.batch_writes)});\n \"\"\")\n self.disk_connection.executemany(\"\"\"\n INSERT OR IGNORE into queries values (?, ?, ?, ?, ?);\n \"\"\", rows)\n self.disk_connection.commit()\n self.batch_writes = []","def commit_updates(session, update_key, update_statements, table, commit_frequency = 1000):\n primary_key = table.primary_key.columns.values()[0]\n update_key = table.columns[update_key]\n u = table.update().where(primary_key==bindparam('pk')).values({update_key: bindparam('update')})\n numgroups = len(update_statements) / commit_frequency\n for ng in range(numgroups):\n if numgroups == 0:\n break\n chunk = update_statements[ng*commit_frequency:(ng+1)*commit_frequency]\n session.connection().execute(u, *chunk)\n print \"committing chunk\",ng+1,\"of\",numgroups,\"with length\",len(chunk),\"at\",datetime.now()\n session.commit()\n last_chunk = update_statements[numgroups*commit_frequency:]\n if last_chunk:\n print \"committing last\",len(last_chunk),\"records at\",datetime.now()\n session.connection().execute(u, *last_chunk)\n session.commit()","def batch(self, reqs):\n return self.connection.batch_(reqs)","def _process(self, start_key, batch_size):\n\n query = StudentProject.all()\n if start_key:\n query.filter('__key__ > ', start_key)\n\n try:\n entities = query.fetch(batch_size)\n\n if not entities:\n # all entities has already been processed\n return\n\n for entity in entities:\n try:\n self._processEntity(entity)\n except db.Error, e:\n import logging\n logging.exception(e)\n logging.error(\"Broke on %s: %s\" % (entity.key().name(), self.MODEL))\n\n # process the next batch of entities\n start_key = entities[-1].key()\n deferred.defer(self._process, start_key, batch_size)\n except DeadlineExceededError:\n # here we should probably be more careful\n deferred.defer(self._process, start_key, batch_size)","def batch(self, batch, **kwargs):\n kwargs['_return_http_data_only'] = True\n if kwargs.get('callback'):\n return self.batch_with_http_info(batch, **kwargs)\n else:\n (data) = self.batch_with_http_info(batch, **kwargs)\n return data","def batch_process(self, delete_list=[], update_list=[]):\n self.request_url = \"{0}/{1}\".format(self.API_URL, self.USER_BULK_ENDPOINT)\n payload = {\n 'updated': update_list,\n 'deleted': delete_list,\n }\n\n r = self.requests.post(\n self.request_url,\n data=json.dumps(payload),\n headers=self.default_headers,\n timeout=30\n )\n\n return r.status_code, r.json()","async def executemany(self, operation, seq_of_parameters):\n\n count = 0\n for parameters in seq_of_parameters:\n count += await self.execute(operation, parameters)\n self.rowcount = count\n return count","def on_train_batch_start(self, batch, batch_idx, dataloader_idx):\n for callback in self.callbacks:\n callback.on_train_batch_start(self, self.get_model(), batch, batch_idx, dataloader_idx)","def batch_get_named_query(NamedQueryIds=None):\n pass"],"string":"[\n \"def BeginExecuteBatch(self, request, context):\\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)\",\n \"def BeginExecuteBatch(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\\n raise NotImplementedError()\",\n \"def insert_many_execute(self) -> None:\\n self.connection.isolation_level = None\\n self.cursor.execute('BEGIN TRANSACTION')\\n for i in self.__sql_buffer.split(';'):\\n self.cursor.execute(i)\\n self.__sql_buffer = \\\"\\\"\\n self.cursor.execute('COMMIT')\",\n \"def batch_execute(self, conn):\\n def batches(data, batch_size) -> list:\\n \\\"\\\"\\\"Return batches of length `batch_size` from any object that\\n supports iteration without knowing length.\\\"\\\"\\\"\\n rv = []\\n for idx, line in enumerate(data):\\n if idx != 0 and idx % batch_size == 0:\\n yield rv\\n rv = []\\n rv.append(line)\\n yield rv\\n\\n columns = ColumnCollection(self.columns)\\n if self.header:\\n self.columns = [columns.get(h) for h in next(self.data)]\\n columns = ColumnCollection(self.columns)\\n\\n total = 0\\n query = BulkInsertQuery(self.table, columns)\\n for batch in batches(self.data, self.batch_size):\\n total += query.execute(conn, batch) or 0\\n yield total\",\n \"def batch(self, batch_identifier, begin_operation):\\n logger.debug('Starting transaction...')\\n self.publish(\\n batch_operation=BatchOperation(\\n batch_identifier=batch_identifier,\\n begin_operation=begin_operation,\\n ),\\n )\\n\\n def mutation(mutation_operation):\\n return self.publish(\\n batch_operation=BatchOperation(\\n batch_identifier=batch_identifier,\\n mutation_operation=mutation_operation,\\n ),\\n )\\n\\n try:\\n yield mutation\\n except Exception:\\n logger.debug('Attempting to publish rollback of in progress transaction...')\\n self.publish(\\n batch_operation=BatchOperation(\\n batch_identifier=batch_identifier,\\n rollback_operation=RollbackOperation(),\\n ),\\n )\\n logger.debug('Published rollback.')\\n raise\\n else:\\n logger.debug('Attempting to publish commit of in progress transaction...')\\n self.publish(\\n batch_operation=BatchOperation(\\n batch_identifier=batch_identifier,\\n commit_operation=CommitOperation(),\\n ),\\n )\\n logger.debug('Published commit.')\",\n \"def batch_execute(self, sql_list):\\n with self.connection.cursor() as dbc:\\n responses = []\\n for sql in sql_list:\\n dbc.execute(sql)\\n responses.append(dbc.fetchall())\\n return responses\",\n \"def ExecuteBatch(self, request, context):\\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)\",\n \"def ExecuteBatch(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\\n raise NotImplementedError()\",\n \"def execute_query_sequence(db_cursor, all_queries):\\n\\n for query in all_queries:\\n db_cursor.execute(query)\",\n \"def execute_queries(self, queries, **format_args):\\n query_len = len(queries)\\n commit = False\\n\\n for i,query in enumerate(queries):\\n q = query.format(**format_args)\\n\\n if i >= query_len - 1:\\n commit = True\\n\\n self._submit_single_q(q, commit=commit)\",\n \"def batched_query(self, sql):\\r\\n\\r\\n result_sets = []\\r\\n messages = \\\"\\\"\\r\\n query = []\\r\\n last_query=\\\"\\\"\\r\\n\\r\\n batches = re.split(\\\"^\\\\s*(GO(?:\\\\s+[0-9]+)?)\\\\s*(?:--.*)?$\\\",sql,flags=re.M|re.I)\\r\\n # print(batches)\\r\\n for b in batches:\\r\\n if b.upper() == \\\"GO\\\":\\r\\n # execute one\\r\\n query.append(last_query)\\r\\n continue\\r\\n else:\\r\\n match = re.match(\\\"^GO\\\\s+([0-9]+)$\\\",b,re.I)\\r\\n if match is not None:\\r\\n #execute many\\r\\n for i in range(0,int(match.group(1))):\\r\\n query.append(last_query)\\r\\n else:\\r\\n # not a Go statment\\r\\n last_query = b\\r\\n query.append(last_query)\\r\\n\\r\\n # print(query)\\r\\n for q in query:\\r\\n r = self.query(q)\\r\\n if r is not None:\\r\\n result_sets.extend(r)\\r\\n messages += self.messages\\r\\n\\r\\n self.messages = messages\\r\\n return result_sets\",\n \"def on_batch_begin(self, batch, logs=None):\",\n \"def execute_query_list(cur, conn, query_list):\\n try:\\n for query in query_list:\\n cur.execute(query)\\n conn.commit()\\n except psycopg2.Error as e:\\n print(\\\"Error executing query list\\\")\\n print(e)\",\n \"def batch(self, sql):\\n return _Batch(self.conn, sql)\",\n \"def batch_get_query_execution(QueryExecutionIds=None):\\n pass\",\n \"def ExecuteBatchQueue(self):\\n\\t\\tself.client.ExecuteBatch(self.batch_queue, 'https://www.google.com/m8/feeds/contacts/default/full/batch')\\n\\t\\tself.ClearBatchQueue();\",\n \"def executeQuery(self, segments=None,):\\n if not segments: segments = self.segments\\n query =''.join(['INSERT INTO ', self.tableName, ' (',\\n ', '.join(self.firstLine), ') VALUES ',\\n ', '.join([segment for segment in segments]), ';'])\\n try:\\n self.cursorExecute(query)\\n except:\\n print 'Bulk query rejected, splitting into smaller queries.'\\n self.handleSQLRejection(0, len(self.segments))\",\n \"def produce_query_batches(self):\\n pass\",\n \"def _multi_query_execution(self):\\n multi_query_staging = self.query.split(';')\\n for query in multi_query_staging:\\n self.query = query\\n self._execute_command()\",\n \"def execute_many(self, query, parameters):\\n return self._executemany_lastrowid(query, parameters)\",\n \"def executemany(self, operation, seq_of_parameters):\\r\\n if self._closed:\\r\\n raise Error('The cursor has been closed.')\\r\\n if self.connection._closed:\\r\\n raise Error('The connection to the database has been closed.')\\r\\n for parameters in seq_of_parameters:\\r\\n self.execute(operation, parameters)\",\n \"def _batch_insert(bq_client, table, rows):\\n total_rows = len(rows)\\n inserted_rows = 0\\n batch = 1\\n logger.info(\\\"Inserting %d rows into table %s\\\", total_rows,\\n table.full_table_id)\\n while inserted_rows < total_rows:\\n start = (batch - 1) * MAX_BQ_INSERT_SIZE\\n end = batch * MAX_BQ_INSERT_SIZE\\n batch_rows = rows[start:end]\\n inserted_rows += len(batch_rows)\\n errors = _insert_rows(bq_client, table, batch_rows)\\n if errors:\\n print_bq_insert_errors(batch_rows, errors)\\n logger.error(\\n \\\"The program has been terminated due to BigQuery insertion \\\"\\n \\\"errors.\\\")\\n exit(1)\\n else:\\n logger.info(\\\"Batch %d: inserted rows %d to %d\\\", batch, start + 1,\\n min(end, len(rows)))\\n batch += 1\\n logger.info(\\\"All rows inserted.\\\")\",\n \"def applyBatch(self, authority, operations):\\n pass\",\n \"def sql_scripts_execute(self, sql_scripts, params={}):\\n ps = self.parameter_handler(params)\\n log.debug('Got parameters: %s', ps)\\n cursor = self._get_cursor()\\n for q in sql_scripts:\\n with open(q, 'r') as s:\\n sql_string_formatted = s.read().format(**ps)\\n cursor.execute(sql.SQL(sql_string_formatted), ps)\\n self.connection.commit()\\n self.connection.close()\",\n \"def _batching_call(self, *args, **kw):\\n b_start = kw.pop('b_start', None)\\n b_size = kw.pop('b_size', None)\\n results = list(self._original_call(*args, **kw))\\n\\n if b_start is None:\\n return results\\n\\n if b_size is None:\\n b_size = len(results)\\n\\n return results[b_start:b_start+b_size]\",\n \"def on_test_batch_begin(self, batch, logs=None):\",\n \"def flush_batch(self, batch: Sequence[TResult]) -> None:\\n pass\",\n \"def begin(self):\\n self._in_transaction = True\\n self.execute(\\\"BEGIN\\\")\",\n \"def execute_many(self, query: str, args):\\n return self.insert_many(query, args)\",\n \"def ExecuteBatch(self, request, context):\\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\\n context.set_details('Method not implemented!')\\n raise NotImplementedError('Method not implemented!')\",\n \"def ExecuteBatch(self, request, context):\\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\\n context.set_details('Method not implemented!')\\n raise NotImplementedError('Method not implemented!')\",\n \"def _insert_bulk(self, iterable):\\n self.cursor.executemany(self.INSERT, iterable)\\n self.conn.commit()\",\n \"def execute_queries():\\n fetch_job_listings(engine)\\n update_job_listing(engine)\",\n \"def executemany(self, operation, seq_of_parameters):\\n self._check_closed()\\n\\n p_statement = self._statement_cache.get_prepared_statement(operation)\\n self.session.execute_batch_prepared_statement(p_statement, seq_of_parameters)\",\n \"def loadbatch():\\n s=\\\"select * from tblbatch where status='1'\\\"\\n c.execute(s)\\n data=c.fetchall()\\n return data\",\n \"def execute_many(self, sql, args=None):\\r\\n args = args or None\\r\\n with Executer(self) as cursor:\\r\\n rows = cursor.executemany(sql, args)\\r\\n return rows\",\n \"def execute(self, start=0, end=0):\\n base_query = self.postgres.session.query(Analysis).\\\\\\n join(Version).\\\\\\n join(Package).\\\\\\n join(Ecosystem).\\\\\\n filter(Analysis.finished_at.isnot(None)).\\\\\\n filter(Analysis.id >= start).\\\\\\n order_by(Analysis.id.asc())\\n\\n if end:\\n base_query = base_query.filter(Analysis.id <= end)\\n\\n while True:\\n self.log.info(\\\"Updating results, slice offset is %s\\\", start)\\n try:\\n results = base_query.slice(start, start + self.query_slice).all()\\n except SQLAlchemyError:\\n self.postgres.session.rollback()\\n raise\\n start += self.query_slice\\n if not results:\\n self.log.info(\\\"No more finished analyses => syncing to GraphDB finished\\\")\\n break\\n\\n for entry in results:\\n arguments = {'ecosystem': entry.version.package.ecosystem.name,\\n 'name': entry.version.package.name,\\n 'version': entry.version.identifier}\\n try:\\n self.log.info('Synchronizing {ecosystem}/{name}/{version} ...'.format(\\n **arguments))\\n GraphImporterTask.create_test_instance().execute(arguments)\\n except Exception:\\n self.log.exception('Failed to synchronize {ecosystem}/{name}/{version}'.\\n format(**arguments))\\n del entry\",\n \"def run_multiple(self, sql, it):\\n self.database.executemany(sql, it)\",\n \"def _dispatch_batches(self, base_url, endpoint, item_list, prep_args, dataset_id=None, dataset_version=None):\\n pool = ThreadPool(processes=self.pool_size)\\n batch = []\\n\\n # Decide which _prep function to use based on the endpoint\\n if endpoint == 'import' or endpoint == 'import-events':\\n prep_function = Mixpanel._prep_event_for_import\\n elif endpoint == 'engage' or endpoint == 'import-people':\\n prep_function = Mixpanel._prep_params_for_profile\\n else:\\n Mixpanel.LOGGER.warning(\\n 'endpoint must be \\\"import\\\", \\\"engage\\\", \\\"import-events\\\" or \\\"import-people\\\", found: ' + str(endpoint))\\n return\\n\\n if base_url == self.BETA_IMPORT_API:\\n batch_size = 1000\\n else:\\n batch_size = 50\\n\\n for item in item_list:\\n if prep_args is not None:\\n # Insert the given item as the first argument to be passed to the _prep function determined above\\n prep_args[0] = item\\n params = prep_function(*prep_args)\\n if params:\\n batch.append(params)\\n else:\\n batch.append(item)\\n\\n if len(batch) == batch_size:\\n # Add an asynchronous call to _send_batch to the thread pool\\n pool.apply_async(self._send_batch, args=(base_url, endpoint, batch, dataset_id, dataset_version),\\n callback=Mixpanel._response_handler_callback)\\n batch = []\\n\\n # If there are fewer than batch_size updates left ensure one last call is made\\n if len(batch):\\n # Add an asynchronous call to _send_batch to the thread pool\\n pool.apply_async(self._send_batch, args=(base_url, endpoint, batch, dataset_id, dataset_version),\\n callback=Mixpanel._response_handler_callback)\\n pool.close()\\n pool.join()\",\n \"def on_batch_start(self):\\n for callback in self.callbacks:\\n callback.on_batch_start(self, self.get_model())\",\n \"def run_multiple_sql_statements(statements, fetch=True, cur=None, conn=None, commit=True):\\n\\n try:\\n if conn is None:\\n logger.error(\\\"Connection cannot be None.\\\")\\n raise ValueError(\\\"Connection cannot be None.\\\")\\n\\n if cur is None:\\n cur = conn.cursor()\\n\\n if statements is None:\\n logger.error(\\\"Sql statement list is empty\\\")\\n raise ValueError(\\\"Sql statement list is empty\\\")\\n\\n for _, statement in enumerate(statements):\\n logger.debug(\\\"Executing SQL = \\\" + statement)\\n res = cur.execute(statement)\\n if fetch:\\n data = cur.fetchall()\\n else:\\n data = None\\n if commit:\\n conn.commit()\\n except Exception as exception:\\n logger.error(exception)\\n raise exception\\n\\n return (res, data)\",\n \"def batch_start(self, batch_idx, batch_data):\\n self.batch = batch_idx\",\n \"def _batcher(self, rows):\\n row_count = 0\\n batch = []\\n batch_count = 1\\n\\n total_rows_modified = 0\\n throttle_count = 0\\n\\n i = 0\\n for row in rows:\\n if row_count > self.batch_size - 1:\\n logger.debug(f\\\"row_count={row_count} batch_size={self.batch_size} and batch={len(batch)}\\\")\\n # Yield the previous batch\\n yield batch\\n\\n # Start the new batch\\n batch = []\\n batch.append(row)\\n row_count = 1\\n\\n batch_count += 1\\n # break # toggle to load one batch only\\n else:\\n row_count += 1\\n batch.append(row)\\n\\n # Put in a sleep timer to throttle how hard we hit the database\\n if self.throttle_time and self.throttle_size and (throttle_count > self.throttle_size - 1):\\n logger.info(f\\\"Sleeping for {self.throttle_time} seconds... row: {i}\\\")\\n time.sleep(int(self.throttle_time))\\n throttle_count = 0\\n elif self.throttle_time and self.throttle_size:\\n throttle_count += 1\\n i += 1\\n\\n yield batch\",\n \"def insert_result_batch(self, results):\\n session = self.session_factory()\\n for result in results:\\n if not self._check_row_exists(pk=result.get('id')):\\n session.add(PipelineRun(**result))\\n if self._get_filtered_results(id=result.get('id'), status='IN_PROGRESS'):\\n session.query(PipelineRun).filter_by(id=result.get('id')).update(result)\\n session.commit()\\n session.close()\",\n \"def __insertBasicUsersQueries(self,_count,user_ids,credit,owner_id,group_id,ibs_query):\\n for user_id in user_ids:\\n ibs_query+=self.__insertBasicUserQuery(user_id,credit,owner_id,group_id)\",\n \"def insert_many(self, query: str, args):\\n cursor = self._cursor()\\n try:\\n cursor.execute_many(query, args)\\n return cursor.lastrowid\\n finally:\\n cursor.close()\",\n \"def runQueryWrite(d, queryList):\\n for query in queryList:\\n with d.session() as s:\\n s.write_transaction(runQuery, query)\",\n \"def _execute_deferred_queries(self):\\n\\n assert not self.__is_connected\\n\\n if not self._deferred_queries:\\n return\\n\\n with Transaction(self.__database_name) as txn:\\n while True:\\n try:\\n query = self._deferred_queries.popleft()\\n txn.session.execute(query).close()\\n except IndexError:\\n break\",\n \"def batch(self):\\n return self._client.batch()\",\n \"def commit_inserts(session, insert_statements, table, is_mysql, commit_frequency = 1000):\\n if is_mysql:\\n ignore_prefix = (\\\"IGNORE\\\",)\\n session.execute(\\\"set foreign_key_checks = 0; set unique_checks = 0;\\\")\\n session.commit()\\n else:\\n ignore_prefix = (\\\"OR IGNORE\\\",)\\n numgroups = len(insert_statements) / commit_frequency\\n for ng in range(numgroups):\\n if numgroups == 0:\\n break\\n chunk = insert_statements[ng*commit_frequency:(ng+1)*commit_frequency]\\n session.connection().execute(table.insert(prefixes=ignore_prefix), chunk)\\n print \\\"committing chunk\\\",ng+1,\\\"of\\\",numgroups,\\\"with length\\\",len(chunk),\\\"at\\\",datetime.now()\\n session.commit()\\n last_chunk = insert_statements[numgroups*commit_frequency:]\\n if last_chunk:\\n print \\\"committing last\\\",len(last_chunk),\\\"records at\\\",datetime.now()\\n session.connection().execute(table.insert(prefixes=ignore_prefix), last_chunk)\\n session.commit()\",\n \"def make_batch_request(self, batch):\\n args = {}\\n args['access_token'] = self.access_token\\n args['batch'] = json.dumps(batch)\\n args = {k.encode('utf-8'): unicode(v).encode('utf-8')\\n for k, v in args.items()}\\n logger.info('Making a batched request with %s' % args)\\n try:\\n f = urllib2.urlopen(self.api_root, urllib.urlencode(args))\\n data = json.load(f)\\n # For debugging\\n self.data = data\\n for idx, val in enumerate(data):\\n data[idx] = json.loads(val['body'])\\n return data\\n except urllib2.HTTPError as e:\\n logger.info('%s' % e)\\n return json.load(e)\\n except urllib2.URLError as e:\\n logger.warn('URLError: %s' % e.reason)\",\n \"def process_batch(sm_account_id, graph, interactions, batch_requests, p_session, processed_interactions=None,\\n cutoff=None):\\n with transaction.manager:\\n for interaction in interactions:\\n p_session.merge(interaction)\\n\\n if len(batch_requests) == 0 or (processed_interactions and processed_interactions >= cutoff):\\n return\\n\\n # process batch requests\\n # Number of max items in a batch request is 50\\n MAX_BATCH_SIZE = 50\\n batch_requests_p = [{'method': req.get('method'), 'relative_url': req.get('relative_url')} for req in\\n batch_requests]\\n batch_data = []\\n\\n interactions_new = set()\\n batch_requests_new = []\\n\\n for i in range(math.ceil(len(batch_requests_p) / MAX_BATCH_SIZE)):\\n # TODO handle connection error. attempt retries\\n try:\\n batch_req = json.dumps(batch_requests_p[i * MAX_BATCH_SIZE:(i * MAX_BATCH_SIZE) + (MAX_BATCH_SIZE - 1)],\\n indent=1)\\n batch_data += graph.request(\\\"\\\", post_args={\\n 'batch': batch_req})\\n\\n except ConnectionError as e:\\n logger.exception('unable to process batch request \\\\n:{}'.format(batch_req))\\n for req, batch_response in zip(batch_requests, batch_data):\\n parent_id = req.get('parent_id')\\n if 'body' in batch_response:\\n batch_response_data = json.loads(batch_response['body'])\\n if 'error' in batch_response_data and batch_response_data['error'].get('code') == 1:\\n # handle request failure - 'Please reduce the amount of data you are asking for, then retry your request'\\n error_url = req.get('relative_url')\\n parse_result = urlparse(error_url)\\n query_data = urlparse.parse_qs(parse_result.query)\\n old_limit = query_data.get('limit')[0]\\n sm_account_id = parse_result.path.split(\\\"/\\\")[2]\\n new_limit = int(float(old_limit) / 2)\\n new_req = get_feed_request(sm_account_id, limit=new_limit)\\n batch_requests_new.append(new_req)\\n\\n if 'data' in batch_response_data:\\n for interaction_raw in batch_response_data['data']:\\n Interactions.get_nested_interactions(sm_account_id, interaction_raw, interactions_new,\\n batch_requests_new, parent_id)\\n if 'paging' in batch_response_data and 'next' in batch_response_data['paging']:\\n next_url = urlparse(batch_response_data['paging']['next'])\\n relative_url = next_url.path + '?' + next_url.query + '&include_headers=false'\\n req = {'method': 'GET', 'relative_url': relative_url, 'parent_id': parent_id}\\n batch_requests_new.append(req)\\n else:\\n logger.info('Exception occurred while collecting posts for {} skipping this..'.format(sm_account_id))\\n\\n process_batch(sm_account_id, graph, interactions_new, batch_requests_new, p_session,\\n processed_interactions + len(interactions), cutoff)\",\n \"def update_batch(self, *args, **kwargs):\\n pass\",\n \"def commit(cls, sql, **kwargs):\\n conn = kwargs['conn']\\n\\n cursor = conn.cursor(dictionary=True, buffered=False)\\n if CHECKS_OFF:\\n sql = TURN_CHECKS_OFF + sql\\n\\n for _ in cursor.execute(sql, kwargs.get('args'), multi=True):\\n pass\\n\\n cls.close(conn, cursor)\",\n \"def execute(self):\\n if self.sql is None:\\n self.sql = self.construct_query()\\n # Only SQL strings can be split, not (e.g.) SQLAlchemy statements.\\n if self.multiple_statements and isinstance(self.sql, str):\\n statements = self._split_sql()\\n else:\\n statements = [self.sql]\\n single_statement = True if len(statements) == 1 and self.filename else False\\n try:\\n for statement in statements:\\n result_proxy = self.cm.conn.execute(statement)\\n log_string = self.filename if single_statement else str(statement)[:25]\\n self.logger.info(\\\"Executed {} against {}\\\".format(log_string, self.cm.db))\\n if result_proxy.cursor:\\n return self.fetch_results(result_proxy)\\n except Exception as e:\\n self.logger.exception(e)\\n raise\",\n \"def insert_boost(connection: DBConnection, documents: Sequence[Document]) -> None:\\n max_ = len(documents)\\n current = 0\\n print() # print an extra line, because we will delete lines with printing \\\\r\\n for chunk in chunks(documents):\\n\\n connection.execute(\\\"BEGIN TRANSACTION\\\")\\n for doc in chunk:\\n connection.execute(\\n \\\"INSERT INTO boost(did, date, page) VALUES (?, ?, ?)\\\", (doc.id, doc.date, doc.page))\\n connection.execute(\\\"COMMIT\\\")\\n current += len(chunk)\\n print(f\\\"\\\\r[{current}/{max_}] boost done\\\", end='')\\n print()\",\n \"def execute_batch(self, commands=()):\\n if not hasattr(commands, \\\"__iter__\\\"):\\n raise InvalidCommandValue(\\\"commands must be an iterable\\\")\\n if self._execute_batch_fn is None:\\n raise MissingFunctionDefinition(\\\"execute_batch method is not mapped\\\")\\n return self._execute_batch_fn(commands)\",\n \"def execute(\\n self,\\n query,\\n count=False,\\n batch_size=None,\\n ttl=None,\\n bind_vars=None,\\n full_count=None,\\n optimizer_rules=None,\\n fail_on_warning=None,\\n profile=None,\\n max_transaction_size=None,\\n max_warning_count=None,\\n intermediate_commit_count=None,\\n intermediate_commit_size=None,\\n skip_inaccessible_collections=None,\\n stream=None,\\n sql=False,\\n ):\\n data = {\\\"query\\\": query, \\\"count\\\": count}\\n if batch_size is not None:\\n data[\\\"batchSize\\\"] = batch_size\\n if ttl is not None:\\n data[\\\"ttl\\\"] = ttl\\n if bind_vars is not None:\\n data[\\\"bindVars\\\"] = bind_vars\\n\\n options = {}\\n if full_count is not None:\\n options[\\\"fullCount\\\"] = full_count\\n if optimizer_rules is not None:\\n options[\\\"optimizer\\\"] = {\\\"rules\\\": optimizer_rules}\\n if fail_on_warning is not None:\\n options[\\\"failOnWarning\\\"] = fail_on_warning\\n if profile is not None:\\n options[\\\"profile\\\"] = profile\\n if max_transaction_size is not None:\\n options[\\\"maxTransactionSize\\\"] = max_transaction_size\\n if max_warning_count is not None:\\n options[\\\"maxWarningCount\\\"] = max_warning_count\\n if intermediate_commit_count is not None:\\n options[\\\"intermediateCommitCount\\\"] = intermediate_commit_count\\n if intermediate_commit_size is not None:\\n options[\\\"intermediateCommitSize\\\"] = intermediate_commit_size\\n if skip_inaccessible_collections is not None:\\n options[\\\"skipInaccessibleCollections\\\"] = skip_inaccessible_collections\\n if stream is not None:\\n options[\\\"stream\\\"] = stream\\n if options:\\n data[\\\"options\\\"] = options\\n data.update(options)\\n\\n command = (\\n \\\"db._query({}, {}, {}).toArray()\\\".format(\\n dumps(query),\\n dumps(bind_vars),\\n dumps(data),\\n )\\n if self._is_transaction\\n else None\\n )\\n\\n if sql:\\n end_point = \\\"/cursor/sql\\\"\\n else:\\n end_point = \\\"/cursor\\\"\\n\\n request = Request(method=\\\"post\\\", endpoint=end_point, data=data, command=command)\\n\\n def response_handler(resp):\\n if not resp.is_success:\\n raise C8QLQueryExecuteError(resp, request)\\n return Cursor(self._conn, resp.body)\\n\\n return self._execute(request, response_handler)\",\n \"def on_train_batch_begin(self, batch, logs=None):\\n # For backwards compatibility\\n self.on_batch_begin(batch, logs=logs)\",\n \"def start_transaction_sql(self):\\n return \\\"BEGIN TRANSACTION\\\"\",\n \"def test_custom_query_batching(self):\\n\\n # Construct Batch Statement\\n batch = BatchStatement(BatchType.LOGGED)\\n for i in range(10):\\n batch.add(SimpleStatement(\\\"INSERT INTO test3rf.test (k, v) VALUES (%s, %s)\\\"), (i, i))\\n\\n # Validate that various types of custom payloads are sent and received okay\\n self.validate_various_custom_payloads(statement=batch)\",\n \"def execute(self, limit=None, offset=None, conn=None):\\n statement = self._statement\\n if limit is not None:\\n if offset is not None:\\n statement += \\\"\\\\nLIMIT {0} OFFSET {0}\\\".format(limit, offset)\\n else:\\n statement += \\\"\\\\nLIMIT \\\" +str(limit)\\n \\n results = []\\n \\n manage_conn = conn is None\\n if manage_conn:\\n conn = self._db.pool.get()\\n cur = conn.cursor()\\n \\n cur.execute(statement, self._params.get_dbapi_params())\\n results = cur.fetchall()\\n \\n cur.close()\\n if manage_conn:\\n conn.close()\\n \\n return [ self._process_result(r) for r in results ]\",\n \"def insertmany(cls, *args):\\n return InsertQuery(cls).bulk(True).set(*args)\",\n \"def _run_queries(self, persist):\\n self._mark_start()\\n self._run_query()\\n\\n # Check if we want to keep going.\\n if not persist:\\n self._compile_results()\\n return\\n\\n # Get the rest of the content.\\n while not self._done():\\n self._run_query()\\n\\n # Create the actual statements.\\n self._compile_results()\\n\\n # This is end of the loop, one way or another. Restore logging if it\\n # was redirected.\\n request_logger.unquiet()\\n util_logger.unquiet()\\n return\",\n \"def execute_sql_files(connection, sql_files):\\n for filename in sql_files:\\n statement = resource_text(filename)\\n for sub_statement in statement.split(\\\";\\\"):\\n if sub_statement.strip():\\n connection.execute(text(sub_statement))\",\n \"def batch(self, requests):\\n return AlgoliaUtils_request(self.headers, self.write_hosts, \\\"POST\\\", \\\"/1/indexes/*/batch\\\", self.timeout, {\\\"requests\\\": requests})\",\n \"def _execute_query(self, query, values):\\n with self as plasticDB:\\n cursor = plasticDB.connection.cursor()\\n cursor.execute(query,values)\\n if not cursor.description:\\n return []\\n rs = RecordSet(initialData=cursor.fetchall(), recordType=next(zip(*cursor.description)))\\n return rs\",\n \"def get_all_batches(self, query, bind_vars=None, batch_size=1000):\\n write_ops = [\\\"INSERT\\\", \\\"UPDATE\\\", \\\"REPLACE\\\", \\\"REMOVE\\\", \\\"UPSERT\\\"]\\n if any(ele in query.upper() for ele in write_ops):\\n raise C8QLGetAllBatchesError(\\n \\\"Write operations provided in the query. Only read operations can be provided\\\"\\n )\\n\\n cursor = self.execute(\\n query=query, bind_vars=bind_vars, batch_size=batch_size, stream=True\\n )\\n while cursor.has_more():\\n cursor.fetch()\\n\\n result = clean_doc(cursor.batch())\\n return result\",\n \"def do_bulk(self, args):\\n pass\",\n \"def _send_batch(self, base_url, endpoint, batch, dataset_id=None, dataset_version=None, retries=0):\\n try:\\n params = {'data': base64.b64encode(json.dumps(batch).encode()).decode()}\\n if dataset_id:\\n params['dataset_id'] = dataset_id\\n params['token'] = self.token\\n if dataset_version:\\n params['dataset_version'] = dataset_version\\n response = self.request(base_url, [endpoint], params, 'POST')\\n msg = \\\"Sent \\\" + str(len(batch)) + \\\" items on \\\" + time.strftime(\\\"%Y-%m-%d %H:%M:%S\\\") + \\\"!\\\"\\n Mixpanel.LOGGER.debug(msg)\\n return response\\n except BaseException as be:\\n Mixpanel.LOGGER.debug('Exception in _send_batch')\\n Mixpanel.LOGGER.debug(be)\\n Mixpanel.LOGGER.warning(\\\"Failed to import batch, dumping to file import_backup.txt\\\")\\n with open('import_backup.txt', 'a+') as backup:\\n json.dump(batch, backup)\\n backup.write('\\\\n')\",\n \"def update_batch_of_entitiies(self, username, entity_batch_data):\\n\\t\\treturn self._send_command_to_entity_server(us.SERVER_COMMAND_UPDATE_ENTITY_BATCH, username + '|' + str(entity_batch_data))\",\n \"def execute(self):\\n return self._batch.execute()\",\n \"def execute(self):\\n for coll in list(self.__bulks):\\n try:\\n bulkOp = self.__bulks[coll]\\n curr_result = Counter(bulkOp.execute())\\n self.update_results(coll, curr_result)\\n except BulkWriteError as bwe:\\n sys.stderr.write(str(bwe.details))\",\n \"def execute(self, jobID = None, couchID = None, bulkList = None, conn = None,\\n transaction = False):\\n\\n if isinstance(bulkList, list):\\n binds = bulkList\\n else:\\n binds = {\\\"jobid\\\": jobID, \\\"couchid\\\": couchID}\\n\\n self.dbi.processData(self.sql, binds,\\n conn = conn, transaction = transaction)\\n return\",\n \"def test_batch_by_transaction_id_multiple_txn_ids():\\n # Add batch that has txn 123\\n testResponder = TestResponder()\\n\\n transaction = transaction_pb2.Transaction(header_signature=\\\"123\\\")\\n batch = batch_pb2.Batch(\\n header_signature=\\\"abc\\\", transactions=[transaction])\\n testResponder.completer.add_batch(batch)\\n # Request transactions 123 and 456\\n message = network_pb2.GossipBatchByTransactionIdRequest(\\n ids=[\\\"123\\\", \\\"456\\\"],\\n time_to_live=1)\\n testResponder.batch_by_txn_request_handler.handle(\\n \\\"Connection_1\\\", message.SerializeToString())\\n testResponder.batch_request_handler.handle(\\n \\\"Connection_1\\\", message.SerializeToString())\\n\\n # Respond with a BatchResponse for transaction 123\\n\\n # Broadcast a BatchByTransactionIdRequest for just 456\\n after_message = \\\\\\n network_pb2.GossipBatchByTransactionIdRequest(\\n ids=[\\\"456\\\"],\\n time_to_live=0)\",\n \"def on_test_batch_begin(\\n self, batch: int, logs: tp.Optional[tp.Dict[str, np.ndarray]] = None\\n ):\\n pass\",\n \"def query_many(self, queries):\\n assert isinstance(queries, list)\\n cursor = self._cursor()\\n results = []\\n for query in queries:\\n try:\\n cursor.execute(query)\\n result = cursor.fetchall()\\n except Exception as e:\\n print(e)\\n result = []\\n results.append(result)\\n return results\",\n \"def begin(transactionId, *args):\\n global _operationCount\\n # noinspection PyUnresolvedReferences\\n _log.info(\\n # \\\"%s BEGIN %s\\\" % (transactionId.hex, \\\" \\\".join(util.encode2(a) for a in args))\\n f\\\"{transactionId.hex} BEGIN {' '.join(impl.util.encode2(a) for a in args)}\\\"\\n )\\n _countLock.acquire()\\n try:\\n _operationCount += 1\\n finally:\\n _countLock.release()\",\n \"def ExecuteBatch(self, batch_feed, url=None, spreadsheet_key=None, \\n worksheet_id=None,\\n converter=gdata.spreadsheet.SpreadsheetsCellsFeedFromString):\\n\\n if url is None:\\n url = self._GenerateCellsBatchUrl(spreadsheet_key, worksheet_id)\\n return self.Post(batch_feed, url, converter=converter)\",\n \"def write(self, batch):\\n cursor = connection.cursor()\\n while batch:\\n values = [\\n \\\"(%s, %s)\\\" % (\\n psycopg2.Binary(k),\\n psycopg2.Binary(v)\\n ) for k, v in batch[:self.BATCH_SIZE]]\\n sql = \\\"INSERT INTO %s(k,v) VALUES %s\\\" % (self.table, \\\",\\\".join(values))\\n batch = batch[self.BATCH_SIZE:]\\n cursor.execute(sql)\\n cursor.execute(\\\"COMMIT\\\")\",\n \"def batch_process_async(self, delete_list=[], update_list=[]):\\n headers = update_dict(self.default_headers, {self.API_VERSION_HEADER: self.API_VERSIONS[\\\"v2\\\"]})\\n self.request_url = \\\"{0}/{1}\\\".format(self.API_URL, self.USER_BULK_ENDPOINT)\\n\\n payload = {\\n 'updated': update_list,\\n 'deleted': delete_list,\\n }\\n\\n r = self.requests.post(self.request_url, data=json.dumps(payload), headers=headers, timeout=30)\\n\\n return r.status_code, r.json()\",\n \"def insert_documents(connection: DBConnection, documents: Sequence[Document]) -> None:\\n max_ = len(documents)\\n current = 0\\n print() # print an extra line, because we will delete lines with printing \\\\r\\n for chunk in chunks(documents):\\n connection.execute(\\\"BEGIN TRANSACTION\\\")\\n for doc in chunk:\\n # python doesn't support prepared statements, but instead has a builtin sql cache\\n connection.execute(\\n \\\"INSERT INTO docs(did, title, url) VALUES (?, ?, ?)\\\", doc.convert_to_tuple())\\n current += 1\\n print(f\\\"\\\\r[{current}/{max_}] doc done\\\", end='')\\n connection.execute(\\\"COMMIT\\\")\",\n \"def insert_data_many(settings_filename, query_filename, data_list):\\n conn = connect_to_db(settings_filename)\\n cursor = conn.cursor()\\n \\n query = load_query(query_filename)\\n cursor.prepare(query)\\n logging.debug(query)\\n cursor.executemany(None, data_list)\\n conn.commit()\\n \\n cursor.close()\\n conn.close()\\n\\n return True\",\n \"def batch_delete_import_data(importTaskIds=None):\\n pass\",\n \"def batch(\\n arguments: List[BatchArgument],\\n *,\\n uniform_mime_type: str,\\n include_output: bool = True,\\n drive_service: Optional[discovery.Resource] = None,\\n) -> List[drive_api.ResourceID]:\\n\\n # callback will append resulting IDs in order\\n result: List[drive_api.ResourceID] = []\\n\\n def batch_response(request_id, response, exception) -> None:\\n nonlocal result\\n result.append(response.get(\\\"id\\\"))\\n\\n requests = [\\n request(\\n name=argument.name,\\n mime_type=uniform_mime_type,\\n parent_folder_id=argument.parent_folder_id,\\n drive_service=drive_service,\\n )\\n for argument in arguments\\n ]\\n kwargs = {\\\"requests\\\": requests, \\\"drive_service\\\": drive_service}\\n if include_output:\\n kwargs[\\\"callback\\\"] = batch_response\\n drive_api.batch_command(**kwargs)\\n return result\",\n \"def sfdcCreateBatch(query, chunk_size=10000, **kwargs):\\n api_ver = kwargs.get('api_ver', '')\\n session_id = kwargs.get('session_id', '')\\n instance = kwargs.get('instance', '')\\n job_id = kwargs.get('job_id', '')\\n sfdcXml = kwargs.get('sfdcXml', {})\\n\\n bodyXml = sfdcXml.get('batch', {}).get('body')\\n url = sfdcXml.get('batch', {}).get('url')\\n headers = sfdcXml.get('batch', {}).get('headers')\\n\\n bodyXml = unicode(query, \\\"UTF-8\\\")\\n url = url.format(instance=instance, api_ver=api_ver,\\\\\\n job_id=job_id)\\n headers['Content-Type'] = headers.get('Content-Type', '')\\\\\\n .format(chunk_size=chunk_size)\\n headers['X-SFDC-Session'] = session_id\\n\\n resp = requests.post(url=url, headers=headers, data=bodyXml)\\n dictResp = xmltodict.parse(resp.text)\\n batch_id = str(dictResp['batchInfo']['id'])\\n\\n return batch_id\",\n \"def FinishAllFlows(**kwargs):\\n for client_id_batch in data_store.REL_DB.ReadAllClientIDs():\\n for client_id in client_id_batch:\\n FinishAllFlowsOnClient(client_id, **kwargs)\",\n \"def _process(self, start_key, batch_size):\\n\\n query = self.MODEL.all()\\n if start_key:\\n query.filter('__key__ > ', start_key)\\n\\n try:\\n entities = query.fetch(batch_size)\\n\\n if not entities:\\n # all entities has already been processed\\n return\\n\\n for entity in entities:\\n try:\\n self._processEntity(entity)\\n except db.Error, e:\\n import logging\\n logging.exception(e)\\n logging.error(\\\"Broke on %s: %s\\\" % (entity.key().name(), self.MODEL))\\n\\n # process the next batch of entities\\n start_key = entities[-1].key()\\n deferred.defer(self._process, start_key, batch_size)\\n except DeadlineExceededError:\\n # here we should probably be more careful\\n deferred.defer(self._process, start_key, batch_size)\",\n \"def start_transaction_sql(self):\\n return 'START TRANSACTION;'\",\n \"def execute_block(self, stmt: List[loxStmtAST.Stmt], environment: loxenvironment.Environment) -> None:\\n previous_env: loxenvironment.Environment = self.environment\\n try:\\n self.environment = environment\\n for statement in stmt:\\n self.execute(statement)\\n finally:\\n self.environment = previous_env\",\n \"def flush_to_disk(self):\\n logger.info(\\\"Flushing %s queries from in-memory cache to disk\\\", len(self.batch_writes))\\n rows = self.memory_connection.execute(f\\\"\\\"\\\"\\n SELECT hash_id, query, raw_query, domain, intent FROM queries\\n WHERE rowid IN ({\\\",\\\".join(self.batch_writes)});\\n \\\"\\\"\\\")\\n self.disk_connection.executemany(\\\"\\\"\\\"\\n INSERT OR IGNORE into queries values (?, ?, ?, ?, ?);\\n \\\"\\\"\\\", rows)\\n self.disk_connection.commit()\\n self.batch_writes = []\",\n \"def commit_updates(session, update_key, update_statements, table, commit_frequency = 1000):\\n primary_key = table.primary_key.columns.values()[0]\\n update_key = table.columns[update_key]\\n u = table.update().where(primary_key==bindparam('pk')).values({update_key: bindparam('update')})\\n numgroups = len(update_statements) / commit_frequency\\n for ng in range(numgroups):\\n if numgroups == 0:\\n break\\n chunk = update_statements[ng*commit_frequency:(ng+1)*commit_frequency]\\n session.connection().execute(u, *chunk)\\n print \\\"committing chunk\\\",ng+1,\\\"of\\\",numgroups,\\\"with length\\\",len(chunk),\\\"at\\\",datetime.now()\\n session.commit()\\n last_chunk = update_statements[numgroups*commit_frequency:]\\n if last_chunk:\\n print \\\"committing last\\\",len(last_chunk),\\\"records at\\\",datetime.now()\\n session.connection().execute(u, *last_chunk)\\n session.commit()\",\n \"def batch(self, reqs):\\n return self.connection.batch_(reqs)\",\n \"def _process(self, start_key, batch_size):\\n\\n query = StudentProject.all()\\n if start_key:\\n query.filter('__key__ > ', start_key)\\n\\n try:\\n entities = query.fetch(batch_size)\\n\\n if not entities:\\n # all entities has already been processed\\n return\\n\\n for entity in entities:\\n try:\\n self._processEntity(entity)\\n except db.Error, e:\\n import logging\\n logging.exception(e)\\n logging.error(\\\"Broke on %s: %s\\\" % (entity.key().name(), self.MODEL))\\n\\n # process the next batch of entities\\n start_key = entities[-1].key()\\n deferred.defer(self._process, start_key, batch_size)\\n except DeadlineExceededError:\\n # here we should probably be more careful\\n deferred.defer(self._process, start_key, batch_size)\",\n \"def batch(self, batch, **kwargs):\\n kwargs['_return_http_data_only'] = True\\n if kwargs.get('callback'):\\n return self.batch_with_http_info(batch, **kwargs)\\n else:\\n (data) = self.batch_with_http_info(batch, **kwargs)\\n return data\",\n \"def batch_process(self, delete_list=[], update_list=[]):\\n self.request_url = \\\"{0}/{1}\\\".format(self.API_URL, self.USER_BULK_ENDPOINT)\\n payload = {\\n 'updated': update_list,\\n 'deleted': delete_list,\\n }\\n\\n r = self.requests.post(\\n self.request_url,\\n data=json.dumps(payload),\\n headers=self.default_headers,\\n timeout=30\\n )\\n\\n return r.status_code, r.json()\",\n \"async def executemany(self, operation, seq_of_parameters):\\n\\n count = 0\\n for parameters in seq_of_parameters:\\n count += await self.execute(operation, parameters)\\n self.rowcount = count\\n return count\",\n \"def on_train_batch_start(self, batch, batch_idx, dataloader_idx):\\n for callback in self.callbacks:\\n callback.on_train_batch_start(self, self.get_model(), batch, batch_idx, dataloader_idx)\",\n \"def batch_get_named_query(NamedQueryIds=None):\\n pass\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.68904305","0.67491","0.6390388","0.59859765","0.59389424","0.5861362","0.57830834","0.57773644","0.5732274","0.5667679","0.5549289","0.5544553","0.55342305","0.5516681","0.5435256","0.536045","0.5342036","0.53406656","0.5280119","0.52774423","0.5263082","0.5203214","0.5193329","0.51835775","0.5146847","0.51216274","0.51061356","0.5092832","0.50831556","0.5077385","0.5077385","0.50652266","0.50623506","0.5057309","0.5046965","0.5038493","0.50156504","0.5015218","0.5009869","0.50088495","0.5005118","0.4992926","0.49723116","0.49684834","0.49602085","0.49583045","0.49444345","0.4927608","0.49166772","0.49163586","0.49023744","0.489878","0.48866907","0.48836845","0.4877386","0.4854918","0.48258057","0.48178124","0.48165506","0.48076785","0.48057187","0.48001462","0.47927558","0.47887546","0.47875994","0.47657403","0.47648355","0.47628474","0.4759812","0.47563243","0.47548586","0.47509688","0.47478798","0.47452298","0.47405112","0.47389778","0.47352546","0.47247502","0.47174102","0.47130582","0.47105098","0.47042513","0.47029927","0.47028813","0.47009376","0.46969667","0.46883768","0.4687215","0.4687022","0.4682532","0.46794447","0.4679212","0.46787614","0.46778157","0.4677261","0.46715736","0.4671079","0.46695212","0.46683934"],"string":"[\n \"0.68904305\",\n \"0.67491\",\n \"0.6390388\",\n \"0.59859765\",\n \"0.59389424\",\n \"0.5861362\",\n \"0.57830834\",\n \"0.57773644\",\n \"0.5732274\",\n \"0.5667679\",\n \"0.5549289\",\n \"0.5544553\",\n \"0.55342305\",\n \"0.5516681\",\n \"0.5435256\",\n \"0.536045\",\n \"0.5342036\",\n \"0.53406656\",\n \"0.5280119\",\n \"0.52774423\",\n \"0.5263082\",\n \"0.5203214\",\n \"0.5193329\",\n \"0.51835775\",\n \"0.5146847\",\n \"0.51216274\",\n \"0.51061356\",\n \"0.5092832\",\n \"0.50831556\",\n \"0.5077385\",\n \"0.5077385\",\n \"0.50652266\",\n \"0.50623506\",\n \"0.5057309\",\n \"0.5046965\",\n \"0.5038493\",\n \"0.50156504\",\n \"0.5015218\",\n \"0.5009869\",\n \"0.50088495\",\n \"0.5005118\",\n \"0.4992926\",\n \"0.49723116\",\n \"0.49684834\",\n \"0.49602085\",\n \"0.49583045\",\n \"0.49444345\",\n \"0.4927608\",\n \"0.49166772\",\n \"0.49163586\",\n \"0.49023744\",\n \"0.489878\",\n \"0.48866907\",\n \"0.48836845\",\n \"0.4877386\",\n \"0.4854918\",\n \"0.48258057\",\n \"0.48178124\",\n \"0.48165506\",\n \"0.48076785\",\n \"0.48057187\",\n \"0.48001462\",\n \"0.47927558\",\n \"0.47887546\",\n \"0.47875994\",\n \"0.47657403\",\n \"0.47648355\",\n \"0.47628474\",\n \"0.4759812\",\n \"0.47563243\",\n \"0.47548586\",\n \"0.47509688\",\n \"0.47478798\",\n \"0.47452298\",\n \"0.47405112\",\n \"0.47389778\",\n \"0.47352546\",\n \"0.47247502\",\n \"0.47174102\",\n \"0.47130582\",\n \"0.47105098\",\n \"0.47042513\",\n \"0.47029927\",\n \"0.47028813\",\n \"0.47009376\",\n \"0.46969667\",\n \"0.46883768\",\n \"0.4687215\",\n \"0.4687022\",\n \"0.4682532\",\n \"0.46794447\",\n \"0.4679212\",\n \"0.46787614\",\n \"0.46778157\",\n \"0.4677261\",\n \"0.46715736\",\n \"0.4671079\",\n \"0.46695212\",\n \"0.46683934\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6208538"},"document_rank":{"kind":"string","value":"4"}}},{"rowIdx":15596,"cells":{"query":{"kind":"string","value":"MessageStream streams messages from a message table."},"document":{"kind":"string","value":"def MessageStream(self, request, context):\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\n context.set_details('Method not implemented!')\n raise NotImplementedError('Method not implemented!')"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def message_table(message):\r\n table = Table(['property', 'value'])\r\n table.align['property'] = 'r'\r\n table.align['value'] = 'l'\r\n\r\n table.add_row(['id', message['id']])\r\n table.add_row(['initial_entry_time', message['initial_entry_time']])\r\n table.add_row(['visibility_delay', message['visibility_delay']])\r\n table.add_row(['visibility_interval', message['visibility_interval']])\r\n table.add_row(['fields', message['fields']])\r\n return [table, message['body']]","def GetMessageTableResource(self):\n return self._wrc_stream.get_resource_by_identifier(\n self._MESSAGE_TABLE_RESOURCE_IDENTIFIER)","def event_stream(self):\n for message in self.subscribe():\n event = message_to_sse(message[\"data\"])\n yield event","def MessageStream(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\n raise NotImplementedError()","def list_messages():\n session = Session()\n messages = session.query(Message).all()\n msg_lst = []\n for message in messages:\n msg_lst.append(create_message(message))\n return msg_lst","def _seek_to_table(self, table):\n\n self.stream.seek(self.table_pointers[table])","def generate(self):\n \n privateproc = False\n if self.rowcount > 0:\n try:\n table = spss.BasePivotTable(self.tabletitle, self.omssubtype)\n except:\n StartProcedure(_(\"Messages\"), self.procname)\n privateproc = True\n table = spss.BasePivotTable(self.tabletitle, self.omssubtype)\n if self.caption:\n table.Caption(self.caption)\n # Note: Unicode strings do not work as cell values in 18.0.1 and probably back to 16\n if self.columnlabels != []:\n table.SimplePivotTable(self.rowdim, self.rowlabels, self.coldim, self.columnlabels, self.columnvalues)\n else:\n table.Append(spss.Dimension.Place.row,\"rowdim\",hideName=True,hideLabels=True)\n table.Append(spss.Dimension.Place.column,\"coldim\",hideName=True,hideLabels=True)\n colcat = spss.CellText.String(\"Message\")\n for r in self.rowlabels:\n cellr = spss.CellText.String(r)\n table[(cellr, colcat)] = cellr\n if privateproc:\n spss.EndProcedure()","def get_messages():\n dynamodb = boto3.client('dynamodb')\n messages = []\n _messages = []\n paginator = dynamodb.get_paginator('scan')\n for page in paginator.paginate(TableName=os.environ.get('MESSAGE_TABLE_NAME')):\n _messages.extend(page['Items'])\n\n if not _messages:\n return _messages\n\n for message in _messages:\n m = {\n message['timestamp']['N']: message['data']['S']\n }\n messages.append(m)\n\n # sort list of dict by timestamp\n messages = list(map(dict, sorted(list(i.items()) for i in messages)))\n\n _messages = []\n for message in messages:\n _, v = list(message.items())[0]\n _messages.append(v)\n\n return _messages","def stream(self):\n\n iterator = iter(self._stream)\n while self._state < Computation.STATE_COMPLETED:\n try:\n message = next(iterator)\n except StopIteration:\n if self._state < Computation.STATE_COMPLETED:\n self._stream = self._execute()\n iterator = iter(self._stream)\n continue\n break\n\n if isinstance(message, messages.StreamStartMessage):\n self._state = Computation.STATE_STREAM_STARTED\n continue\n\n if isinstance(message, messages.JobStartMessage):\n self._state = Computation.STATE_COMPUTATION_STARTED\n self._id = message.handle\n yield message\n continue\n\n if isinstance(message, messages.JobProgressMessage):\n yield message\n continue\n\n if isinstance(message, messages.ChannelAbortMessage):\n self._state = Computation.STATE_ABORTED\n raise errors.ComputationAborted(message.abort_info)\n\n if isinstance(message, messages.EndOfChannelMessage):\n self._state = Computation.STATE_COMPLETED\n continue\n\n # Intercept metadata messages to accumulate received metadata...\n if isinstance(message, messages.MetadataMessage):\n self._metadata[message.tsid] = message.properties\n yield message\n continue\n\n # ...as well as expired-tsid messages to clean it up.\n if isinstance(message, messages.ExpiredTsIdMessage):\n if message.tsid in self._metadata:\n del self._metadata[message.tsid]\n yield message\n continue\n\n if isinstance(message, messages.InfoMessage):\n self._process_info_message(message.message)\n self._batch_count_detected = True\n yield message\n if self._current_batch_message:\n yield self._get_batch_to_yield()\n continue\n\n # Accumulate data messages and release them when we have received\n # all batches for the same logical timestamp.\n if isinstance(message, messages.DataMessage):\n self._state = Computation.STATE_DATA_RECEIVED\n\n if not self._batch_count_detected:\n self._expected_batches += 1\n\n if not self._current_batch_message:\n self._current_batch_message = message\n self._current_batch_count = 1\n elif (message.logical_timestamp_ms ==\n self._current_batch_message.logical_timestamp_ms):\n self._current_batch_message.add_data(message.data)\n self._current_batch_count += 1\n else:\n self._batch_count_detected = True\n\n if (self._batch_count_detected and\n self._current_batch_count == self._expected_batches):\n yield self._get_batch_to_yield()\n continue\n\n if isinstance(message, messages.EventMessage):\n yield message\n continue\n\n if isinstance(message, messages.ErrorMessage):\n raise errors.ComputationFailed(message.errors)\n\n # Yield last batch, even if potentially incomplete.\n if self._current_batch_message:\n yield self._get_batch_to_yield()","def get_messages(self):\n res = self.conn.cursor().execute(\"SELECT * FROM messages\")\n return res.fetchall()","def iterate_msgs(stream):\n while True:\n item = None\n buf = bytearray()\n stall_timer = None\n\n while True:\n # read bytes until item boundary reached\n buf += stream.read(1)\n if not buf:\n # check for stall (i.e. no data for 90 seconds)\n if not stall_timer:\n stall_timer = time.time()\n elif time.time() - stall_timer > TwitterAPI.STREAMING_TIMEOUT:\n raise TwitterConnectionError(\"Twitter stream stalled\")\n elif stall_timer:\n stall_timer = None\n if buf[-2:] == b\"\\r\\n\":\n item = buf[0:-2]\n if item.isdigit():\n # use byte size to read next item\n nbytes = int(item)\n item = None\n item = stream.read(nbytes)\n yield item\n else:\n yield b\"\" # keepalive\n break","def sqs_messages(queue: str) -> Generator[Dict[str, Any], None, None]:\n\n while True:\n response = get_client(\"sqs\").receive_message(QueueUrl=queue)\n if \"Messages\" not in response:\n break\n msg = json.loads(response[\"Messages\"][0][\"Body\"])\n records = json.loads(msg[\"Message\"])\n retd = {}\n retd[\"key\"] = records[\"Records\"][0][\"s3\"][\"object\"][\"key\"]\n retd[\"bucket\"] = records[\"Records\"][0][\"s3\"][\"bucket\"][\"name\"]\n retd[\"ReceiptHandle\"] = response[\"Messages\"][0][\"ReceiptHandle\"]\n yield retd","def _streaming_service(self, service, command, transport_timeout_s=None, read_timeout_s=constants.DEFAULT_READ_TIMEOUT_S, decode=True):\n stream = self._streaming_command(service, command, transport_timeout_s, read_timeout_s, None)\n if decode:\n for line in (stream_line.decode('utf8', _DECODE_ERRORS) for stream_line in stream):\n yield line\n else:\n for line in stream:\n yield line","def __iter__(self):\n return iter([self.format_message(record) for record in self._messages])","def get_user_messages(user_id):\n return UserMessage.query.filter(user_id == UserMessage.user_id).all()","def get_messages(self, number: int):\n self.sql_lock.acquire()\n query: str = \"SELECT * FROM messages order by id desc LIMIT ?\" \n messages = []\n for item in self.cursor.execute(query,(number, )):\n text, user, id = item\n\n messages.append({\"user\": user, \"text\": f\"message- {text}\", \"id\": id})\n \n self.sql_lock.release()\n return messages","def Read(self):\n try:\n file_object = self._zip_file.open(self._stream_name, mode='r')\n except KeyError as exception:\n raise IOError(\n 'Unable to open stream with error: {0!s}'.format(exception))\n\n try:\n entry_data = file_object.read(self._TABLE_ENTRY_SIZE)\n while entry_data:\n table_entry = self._TABLE_ENTRY.parse(entry_data)\n\n self._timestamps.append(table_entry.timestamp)\n entry_data = file_object.read(self._TABLE_ENTRY_SIZE)\n\n except construct.FieldError as exception:\n raise IOError(\n 'Unable to read table entry with error: {0!s}'.format(exception))\n\n finally:\n file_object.close()","def run_message():\n import simplejson\n from ssgateway.message import main\n from yaml import load\n parser = argparse.ArgumentParser(\n description='export a table to a yaml file')\n parser.add_argument('--message', dest='message',\n help='the message to run')\n args, env = initialize_command(parser)\n\n message = simplejson.loads(args.message)\n route_config = env['registry'].settings.get('routes')\n message_router = main(load(open(route_config)))\n message_router(message)\n\n env['closer']()","def readFromStream(cls, stream):\n list_ = []\n event_id_list = []\n for tr in stream:\n if tr.stats.event.id not in event_id_list:\n list_.append(tr.stats.event)\n event_id_list.append(tr.stats.event.id)\n\n log.info('Read event information of %d events from stream %s' % (len(list_), stream.hash))\n return cls(list_)","def load_stream(self, stream):\n batches = super(ArrowStreamPandasSerializer, self).load_stream(stream)\n import pyarrow as pa\n\n for batch in batches:\n yield [self.arrow_to_pandas(c) for c in pa.Table.from_batches([batch]).itercolumns()]","def create_stream(phrase, queue):\n local = SocketIO(message_queue=queue)\n stream = Twitter().stream(phrase, timeout=30)\n\n for i in range(60):\n stream.update()\n for tweet in reversed(stream):\n sentiment = classify_tweet(tweet)\n x, y = vectorize_tweet(tweet)\n local.emit('tweet', {'id': str(i),\n 'text': str(tweet.text.encode('ascii', 'ignore')),\n 'sentiment': sentiment,\n 'x': x,\n 'y': y})\n stream.clear()\n time.sleep(1)\n\n return queue","def test_iterate_over_stream():\n archive = Archive()\n archive.commit(doc=DataFrameDocument(df=DF1))\n rows = list()\n with archive.open(version=0).open() as reader:\n for row in reader:\n rows.append(row)\n assert rows == [\n (0, 0, ['Alice', 32]),\n (1, 1, ['Bob', 45]),\n (2, 2, ['Claire', 27]),\n (3, 3, ['Alice', 23])\n ]","def stream(\n consumer: Consumer,\n count: Optional[int] = None,\n poll_timeout: Optional[float] = DEFAULT_POLL_TIMEOUT,\n timeout: Optional[float] = None,\n) -> Iterator[Message]:\n if count is not None and count <= 0:\n raise ValueError(\"count must be a positive integer.\")\n if poll_timeout is not None and poll_timeout <= 0:\n raise ValueError(\"poll_timeout must be a positive float.\")\n if timeout is not None and timeout <= 0:\n raise ValueError(\"timeout must be a positive float.\")\n\n if count is None:\n LOGGER.debug(\"Streaming messages....\")\n else:\n LOGGER.debug(\"Streaming up to %d messages....\", count)\n\n if timeout is not None:\n timeout_delta = timedelta(milliseconds=int(timeout * MILLIS_IN_SECOND))\n\n stream_duration = timedelta()\n num_messages = 0\n while count is None or num_messages < count:\n if musekafka.shutdown.is_shutting_down():\n break\n\n if timeout is not None:\n if stream_duration >= timeout_delta:\n LOGGER.debug(\"Hit stream timeout (%.3f seconds).\", timeout)\n break\n poll_timeout = min(\n poll_timeout or timeout, (timeout_delta - stream_duration).total_seconds()\n )\n\n stream_start = datetime.utcnow()\n try:\n message = poll(consumer, timeout=poll_timeout)\n except TimeoutError as e:\n LOGGER.debug(str(e))\n continue\n finally:\n stream_duration += datetime.utcnow() - stream_start\n with bind_message_ctx(message):\n yield message\n num_messages += 1\n LOGGER.debug(\"Completed streaming %d messages.\", num_messages)","def get_all_messages(self):\n cursor = self.get_cursor()\n query = 'WITH replies_query AS (SELECT replied_to, array_agg(mid) AS replies_list ' \\\n 'FROM replies INNER JOIN messages ON replies.reply = messages.mid ' \\\n 'GROUP BY replied_to), ' \\\n 'like_count AS (SELECT mid, COUNT(*) AS likes FROM vote ' \\\n 'WHERE upvote = TRUE GROUP BY mid), ' \\\n 'dislike_count AS (SELECT mid, COUNT(*) AS dislikes FROM vote ' \\\n 'WHERE upvote = FALSE GROUP BY mid) ' \\\n 'SELECT messages.mid, users.uid, cid, message, image, ' \\\n 'COALESCE(likes, 0) AS likes, COALESCE(dislikes, 0) AS dislikes, username, ' \\\n \"COALESCE(replies_list, '{}') AS replies, messages.created_on \" \\\n 'FROM messages LEFT OUTER JOIN like_count ON messages.mid = like_count.mid ' \\\n 'LEFT OUTER JOIN dislike_count ON messages.mid = dislike_count.mid ' \\\n 'LEFT OUTER JOIN photo ON messages.mid = photo.mid ' \\\n 'INNER JOIN users ON messages.uid = users.uid ' \\\n 'LEFT OUTER JOIN replies_query ON messages.mid = replies_query.replied_to ' \\\n 'ORDER BY messages.created_on DESC'\n cursor.execute(query)\n messages = cursor.fetchall()\n return messages","def handle_stream(self, stream, address):\n r = Participant(stream, self.db)\n r.wait_for_headers()","def on_messages(self, msg_list):\n self.stats.on_pack_recv(len(msg_list))\n\n for msg in msg_list:\n if self.state == OPEN:\n self.conn.on_message(msg)","def MessageStream(self, request, context):\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)","def list_messages(self):","def subscribe(self, host:str, port:str, handler:Callable, tableName:str, actionName:str=None, offset:int=-1, resub:bool=False, \n filter=None, msgAsTable:bool=False, batchSize:int=0, throttle:float=1,\n userName:str=None, password:str=None, streamDeserializer:Optional[Type[\"streamDeserializer\"]]=None) -> None:\n if not isinstance(msgAsTable, bool):\n raise ValueError(\"msgAsTable must be a bool\")\n if filter is None:\n filter = np.array([],dtype='int64')\n if actionName is None:\n actionName = \"\"\n if userName is None:\n userName = \"\"\n if password is None:\n password = \"\"\n sd=None\n if streamDeserializer is None:\n sd = ddbcpp.streamDeserializer({})\n else:\n sd = streamDeserializer.cpp\n if batchSize > 0:\n self.cpp.subscribeBatch(host, port, handler, tableName, actionName, offset, resub, filter, msgAsTable, batchSize, throttle,userName,password,sd)\n else:\n if msgAsTable:\n raise ValueError(\"msgAsTable must be False when batchSize is 0\")\n self.cpp.subscribe(host, port, handler, tableName, actionName, offset, resub, filter,userName,password,sd)","def Read(self):\n try:\n file_object = self._zip_file.open(self._stream_name, mode='r')\n except KeyError as exception:\n raise IOError(\n 'Unable to open stream with error: {0!s}'.format(exception))\n\n try:\n entry_data = file_object.read(self._TABLE_ENTRY_SIZE)\n while entry_data:\n table_entry = self._TABLE_ENTRY.parse(entry_data)\n\n self._offsets.append(table_entry.offset)\n entry_data = file_object.read(self._TABLE_ENTRY_SIZE)\n\n except construct.FieldError as exception:\n raise IOError(\n 'Unable to read table entry with error: {0!s}'.format(exception))\n\n finally:\n file_object.close()","def get_user_messages(user_id):\n pass \n # user_message_list = []\n\n # for message in sent messages:","def process_messages(self, messages):\n\n return messages","async def read_messages(id_user: int, date: Optional[datetime.datetime] = None):\n # Check if the date is given or not\n if date:\n mycursor.execute(f\"\"\"SELECT * FROM Daily_message \n WHERE id_user = {id_user}\n AND date_message = '{date}'\"\"\")\n else:\n mycursor.execute(f\"\"\"SELECT * FROM Daily_message \n WHERE id_user = {id_user}\"\"\")\n return mycursor.fetchall()","def messages(\n self,\n amount: int = 100,\n headers: Optional[Mapping[str, str]] = None,\n **parameters: str,\n ) -> Iterable[Message]:\n # We request this many messages at once\n message_bucket_size = 100\n offset = 0\n return (\n Message.from_xml(region=self.name, node=node)\n for node in self._messages_root(\n headers=headers,\n limit=str(max(message_bucket_size, amount)),\n # offset=str(offset),\n **parameters,\n )\n )","def get_messages(self, max_messages):\n raw = self.redis_client.lrange(self.message_list, 0, max_messages)\n messages = (m for m in raw if m != b\"null\")\n messages = (m.decode(\"utf-8\") for m in messages)\n yield from map(json.loads, messages)","def to_event_stream(self, event_stream):\n while self.reading_log:\n event = self.read_event()\n if event is not None:\n event_stream.append(event)","def create_message_table(self):\n sql = (\"CREATE TABLE IF NOT EXISTS message_log \"\n \"(id INT NOT NULL AUTO_INCREMENT PRIMARY KEY, \"\n \"timestamp TIMESTAMP, \"\n \"message VARCHAR(1024), \"\n \"email INT(1), \"\n \"tweet INT(1), \"\n \"status INT(1))\")\n cur = self.cursor()\n try:\n cur.execute(sql)\n except sqlc.Error as e:\n print (\"Error #{0}: {1}\\nCouldn't insert\\nsql={2}\"\n .format(e.errno, e.msg, sql))\n except Exception as e:\n print (\"Error: {0}\\nCouldn't insert\\nsql={1}\"\n .format(e.message, sql))\n finally:\n self.close()","def message_mock():\n from unittest import mock\n from sqlalchemy import Column\n from rucio.common.utils import generate_uuid\n from rucio.db.sqla.models import String, PrimaryKeyConstraint, CheckConstraint, Text, Index, GUID\n\n InMemoryMessage = __create_in_memory_db_table(\n 'message_' + generate_uuid(),\n Column('id', GUID(), default=generate_uuid),\n Column('event_type', String(256)),\n Column('payload', String(4000)),\n Column('payload_nolimit', Text),\n Column('services', String(256)),\n table_args=(PrimaryKeyConstraint('id', name='MESSAGES_ID_PK'),\n CheckConstraint('EVENT_TYPE IS NOT NULL', name='MESSAGES_EVENT_TYPE_NN'),\n CheckConstraint('PAYLOAD IS NOT NULL', name='MESSAGES_PAYLOAD_NN'),\n Index('MESSAGES_SERVICES_IDX', 'services', 'event_type'))\n )\n\n with mock.patch('rucio.core.message.Message', new=InMemoryMessage):\n yield","def create_message_queue_table(self):\n app_process = sqlite3.connect('app_process::memory:', check_same_thread=False)\n app_process_cursor = app_process.cursor()\n app_process_cursor.execute(\"SELECT count(name) FROM sqlite_master WHERE type='table' AND name='message_queue'\")\n if app_process_cursor.fetchone()[0]==1:\n return\n app_process_cursor.execute(\"\"\"\n CREATE TABLE message_queue (\n tstamp real,\n request text,\n dest_ip text,\n dest_port integer,\n next_tstamp real\n )\n \"\"\")\n app_process.commit()\n app_process.close()","async def messages(self, ctx):\n\n\t\tawait self.message_leaderboard(ctx, \"messages\")","def get_messages(self, t0, t1, nmax=100, srcid=None):\n if not (nmax < 10000): nmax = 10000\n if srcid is None:\n self.read_curs.execute(\"SELECT time,readout_id,msg FROM textlog WHERE time >= ? AND time <= ? ORDER BY time DESC LIMIT ?\", (t0, t1, nmax))\n else:\n self.read_curs.execute(\"SELECT time,readout_id,msg FROM textlog WHERE time >= ? AND time <= ? AND readout_id=? ORDER BY time DESC LIMIT ?\", (t0, t1, srcid, nmax))\n return self.read_curs.fetchall()","def get_message():\r\n conn = None\r\n try:\r\n params = config()\r\n conn = psycopg2.connect(**params)\r\n cur = conn.cursor()\r\n cur.execute(\"SELECT user_id, user_message FROM messages ORDER BY user_message\")\r\n print(\"Number of messages: \", cur.rowcount)\r\n row = cur.fetchone()\r\n\r\n while row is not None:\r\n print(row)\r\n row = cur.fetchone()\r\n\r\n cur.close()\r\n except (Exception, psycopg2.DatabaseError) as error:\r\n print(error)\r\n finally:\r\n if conn is not None:\r\n conn.close()","def get_subscriber_row(self, stream_session_info):\n\n uptime = \"unknown\"\n last_msg_time = \"unknown\"\n if (\n stream_session_info.uptime is not None\n and stream_session_info.last_msg_sent_time is not None\n ):\n uptime_str = str(\n datetime.timedelta(milliseconds=stream_session_info.uptime)\n )\n last_msg_time_str = convertTime(stream_session_info.last_msg_sent_time)\n uptime = uptime_str.split(\".\")[0]\n last_msg_time = last_msg_time_str\n\n row = [\n stream_session_info.subscriber_id,\n uptime,\n stream_session_info.total_streamed_msgs,\n last_msg_time,\n ]\n return row","def stream_for_actor(self, actor):\n return self.filter(\n actor_content_type = ContentType.objects.get_for_model(actor),\n actor_object_id = actor.pk,\n ).order_by('-timestamp')","def _get_message_groups(\n self, messages: Iterator[AirbyteMessage], schema_inferrer: SchemaInferrer, limit: int\n ) -> Iterable[Union[StreamReadPages, AirbyteLogMessage]]:\n records_count = 0\n at_least_one_page_in_group = False\n current_page_records = []\n current_slice_pages = []\n current_page_request: Optional[HttpRequest] = None\n current_page_response: Optional[HttpResponse] = None\n\n while records_count < limit and (message := next(messages, None)):\n if self._need_to_close_page(at_least_one_page_in_group, message):\n self._close_page(current_page_request, current_page_response, current_slice_pages, current_page_records)\n current_page_request = None\n current_page_response = None\n\n if at_least_one_page_in_group and message.type == Type.LOG and message.log.message.startswith(\"slice:\"):\n yield StreamReadSlices(pages=current_slice_pages)\n current_slice_pages = []\n at_least_one_page_in_group = False\n elif message.type == Type.LOG and message.log.message.startswith(\"request:\"):\n if not at_least_one_page_in_group:\n at_least_one_page_in_group = True\n current_page_request = self._create_request_from_log_message(message.log)\n elif message.type == Type.LOG and message.log.message.startswith(\"response:\"):\n current_page_response = self._create_response_from_log_message(message.log)\n elif message.type == Type.LOG:\n yield message.log\n elif message.type == Type.RECORD:\n current_page_records.append(message.record.data)\n records_count += 1\n schema_inferrer.accumulate(message.record)\n else:\n self._close_page(current_page_request, current_page_response, current_slice_pages, current_page_records)\n yield StreamReadSlices(pages=current_slice_pages)","def load_stream(self, stream):\n import pyarrow as pa\n\n dataframes_in_group = None\n\n while dataframes_in_group is None or dataframes_in_group > 0:\n dataframes_in_group = read_int(stream)\n\n if dataframes_in_group == 2:\n batch1 = [batch for batch in ArrowStreamSerializer.load_stream(self, stream)]\n batch2 = [batch for batch in ArrowStreamSerializer.load_stream(self, stream)]\n yield (\n [self.arrow_to_pandas(c) for c in pa.Table.from_batches(batch1).itercolumns()],\n [self.arrow_to_pandas(c) for c in pa.Table.from_batches(batch2).itercolumns()],\n )\n\n elif dataframes_in_group != 0:\n raise ValueError(\n \"Invalid number of pandas.DataFrames in group {0}\".format(dataframes_in_group)\n )","def send_streaming_message(self, data):\n header, data = format_msg(data)\n self.server_socket_streaming.sendto(header,\n self.client_streaming_address)\n self.server_socket_streaming.sendto(data,\n self.client_streaming_address)","def mbox_reader(stream):\n data = stream.read()\n text = data.decode(encoding=\"utf-8\", errors=\"replace\")\n return mailbox.mboxMessage(text)","def handle_stream_client(self, event):\n try:\n while True:\n client_req = self.receive_streaming_msg()\n self.choose_action(client_req[ZERO], client_req[ONE:], event)\n except socket.error as e:\n print('stream', e)","def retrieve(self) -> Iterator[SQSMessage]:\n while True:\n try:\n sqs = SQSClientFactory(boto3).from_env()\n\n res = sqs.receive_message(\n QueueUrl=self.queue_url,\n WaitTimeSeconds=3,\n MaxNumberOfMessages=10,\n )\n\n messages = res.get(\"Messages\", [])\n if not messages:\n LOGGER.info(\"queue was empty\")\n\n s3_events = [SQSMessage(msg) for msg in messages]\n for sqs_message in s3_events:\n yield sqs_message\n\n sqs.delete_message(\n QueueUrl=self.queue_url,\n ReceiptHandle=sqs_message.receipt_handle,\n )\n\n except Exception as e:\n LOGGER.error(traceback.format_exc())\n time.sleep(2)","def get_all_msgs(self):\n data = self.database.select(self.tname)\n msgs = []\n for item in data:\n msgs.append((item[0], self.data_to_msg(item)))\n return msgs","def send_to_aws_time_stream(stats, config):\n logging.info('Sending stats to Timestream (database=%s)', config['timestream_database'])\n\n region_config = Config(\n region_name=config['timestream_aws_region']\n )\n\n ts_client = boto3.client(\n 'timestream-write',\n aws_access_key_id=config['timestream_aws_access_key_id'],\n aws_secret_access_key=config['timestream_aws_secret_access_key'],\n config=region_config\n )\n\n try:\n # Attempt to validate connection to database and table\n # Error out and return if not able to access / connection isn't valid\n database = ts_client.describe_database(\n DatabaseName=config['timestream_database']\n )\n logging.debug(\"Database details = %s\" % database)\n\n table = ts_client.describe_table(\n DatabaseName=config['timestream_database'],\n TableName=config['timestream_table']\n )\n logging.debug(\"Table details = %s\" % table)\n except Exception as err:\n logging.error(err)\n return\n\n current_time = time.time_ns()\n logging.debug(\"Converting to timestream - %s\" % stats)\n\n downstream_common_attributes = {\n 'Dimensions': [{'Name': 'measurement', 'Value': 'downstream_statistics'}],\n 'Time': str(current_time),\n 'TimeUnit': 'NANOSECONDS'\n }\n downstream_records = []\n for stats_down in stats['downstream']:\n for key in stats_down:\n if key == 'channel_id':\n continue\n\n downstream_records.append({\n 'Dimensions': [\n {'Name': 'channel_id', 'Value': str(stats_down['channel_id'])},\n {'Name': 'group', 'Value': 'downstream_statistics'}\n ],\n 'MeasureName': key,\n 'MeasureValue': str(stats_down[key]),\n 'MeasureValueType': 'DOUBLE' if isinstance(stats_down[key], float) else 'BIGINT'\n })\n\n try:\n logging.debug(\"Writing common attributes: %s\" % downstream_common_attributes)\n logging.debug(\"Writing records: %s\" % downstream_records)\n result = ts_client.write_records(DatabaseName=config['timestream_database'],\n TableName=config['timestream_table'], Records=downstream_records,\n CommonAttributes=downstream_common_attributes)\n logging.info(\"Timestream response = %s\" % result)\n logging.info(\"Wrote %s records to TimeStream\" % len(downstream_records))\n except (ts_client.exceptions.RejectedRecordsException, Exception) as err:\n logging.error(err)\n\n upstream_common_attributes = {\n 'Dimensions': [{'Name': 'measurement', 'Value': 'upstream_statistics'}],\n 'Time': str(current_time),\n 'TimeUnit': 'NANOSECONDS'\n }\n upstream_records = []\n for stats_up in stats['upstream']:\n for key in stats_up:\n if key == 'channel_id':\n continue\n\n upstream_records.append({\n 'Dimensions': [\n {'Name': 'channel_id', 'Value': str(stats_up['channel_id'])},\n {'Name': 'group', 'Value': 'upstream_statistics'}\n ],\n 'MeasureName': key,\n 'MeasureValue': str(stats_up[key]),\n 'MeasureValueType': 'DOUBLE' if isinstance(stats_up[key], float) else 'BIGINT'\n })\n\n try:\n logging.debug(\"Writing common attributes: %s\" % upstream_common_attributes)\n logging.debug(\"Writing records: %s\" % upstream_records)\n result = ts_client.write_records(DatabaseName=config['timestream_database'],\n TableName=config['timestream_table'], Records=upstream_records,\n CommonAttributes=upstream_common_attributes)\n logging.info(\"Timestream response = %s\" % result)\n logging.info(\"Wrote %s records to TimeStream\" % len(upstream_records))\n except (ts_client.exceptions.RejectedRecordsException, Exception) as err:\n logging.error(err)\n return\n\n logging.info('Successfully wrote data to Timestream')","def emit(self, message):\n # handle vaping data that arrives in a list\n if isinstance(message.get(\"data\"), list):\n for row in message.get(\"data\"):\n\n\n # format filename from data\n filename = self.format_filename(message, row)\n\n # create database file if it does not exist yet\n if not os.path.exists(filename):\n self.create(filename)\n\n # update database\n self.log.debug(\"storing time:%d, %s:%s in %s\" % (\n message.get(\"ts\"), self.field, row.get(self.field, \"-\"), filename))\n self.update(filename, message.get(\"ts\"), row.get(self.field))","def create_stream_table_ui(\n streams, true_state=False, time_point=0, orient=\"columns\", precision=5\n):\n\n # Variable Types:\n class VariableTypes:\n UNFIXED = \"unfixed\"\n FIXED = \"fixed\"\n PARAMETER = \"parameter\"\n EXPRESSION = \"expression\"\n\n stream_attributes = OrderedDict()\n stream_states = stream_states_dict(streams=streams, time_point=time_point)\n full_keys = [] # List of all rows in dataframe to fill in missing data\n\n stream_attributes[\"Units\"] = {}\n\n for key, sb in stream_states.items():\n stream_attributes[key] = {}\n if true_state:\n disp_dict = sb.define_state_vars()\n else:\n disp_dict = sb.define_display_vars()\n for k in disp_dict:\n for row, i in enumerate(disp_dict[k]):\n stream_key = k if i is None else f\"{k} {i}\"\n\n # Identifying value's variable type\n var_type = None\n if isinstance(disp_dict[k][i], (_GeneralVarData, Var)):\n if disp_dict[k][i].fixed:\n var_type = VariableTypes.FIXED\n else:\n var_type = VariableTypes.UNFIXED\n elif isinstance(disp_dict[k][i], Param):\n var_type = VariableTypes.PARAMETER\n elif isinstance(disp_dict[k][i], Expression):\n var_type = VariableTypes.EXPRESSION\n\n quant = report_quantity(disp_dict[k][i])\n stream_attributes[key][stream_key] = (\n round(quant.m, precision),\n var_type,\n )\n if row == 0 or stream_key not in stream_attributes[\"Units\"]:\n stream_attributes[\"Units\"][stream_key] = quant.u\n\n if stream_key not in full_keys:\n full_keys.append(stream_key)\n\n # Check for missing rows in any stream, and fill with \"-\" if needed\n for k, v in stream_attributes.items():\n for r in full_keys:\n if r not in v.keys():\n # Missing row, fill with placeholder\n v[r] = \"-\"\n\n return DataFrame.from_dict(stream_attributes, orient=orient)","def msgs(self, schema: str, last_msg_id, block: int = None):\n raise NotImplementedError","async def process(self, msg):\n # logger.debug(\"msg:\", msg, caller=self)\n if not isinstance(msg, dict):\n return\n if msg.get(\"error\"):\n logger.error(\"msg:\", msg, caller=self)\n return\n\n table = msg.get(\"table\")\n if table == \"orderBook10\":\n await self.process_orderbook(msg[\"data\"])\n elif table == \"trade\":\n await self.process_trade(msg[\"data\"])\n elif table == \"tradeBin1m\":\n await self.process_kline(msg[\"data\"])","def request_messages(self):\n # we fetch messages from all rooms at the same time, we will route them at writing time\n base_query = (\n \"SELECT e.received_ts, j.json \"\n \"FROM events AS e \"\n \"INNER JOIN event_json AS j \"\n \"USING (event_id) \"\n \"WHERE e.room_id IN %s \"\n \"AND e.received_ts>%s \"\n \"AND e.type='m.room.message' \"\n \"ORDER BY e.received_ts;\"\n )\n\n self.read_last_ts_written()\n\n try:\n logging.info(\"Connecting to database ...\")\n with psycopg2.connect(**self.db_config) as conn:\n logging.info(\"Connected to database.\")\n with conn.cursor() as cur:\n cur.execute(\n base_query, (tuple(self.rooms.keys()), self.last_ts_written)\n )\n\n for row in cur:\n # there are two fields per row : timestamp at reception, and json data\n line = self.process_message_row(row)\n\n # we get the room nickname in the config at the room_id key\n room_name = self.rooms[line[\"room_id\"]]\n file_path = self.ts_to_filepath(\n timestamp=line[\"ts\"], room_name=room_name\n )\n\n if self.append_line(file_path, json.dumps(line)):\n logging.info(\n \"Message with timestamp {} written to {}\".format(\n line[\"ts\"], file_path\n )\n )\n self.last_ts_written = line[\"ts\"]\n else:\n logging.error(\n \"We couldn't write message {}, we will exit.\".format(\n line[\"ts\"]\n )\n )\n return False\n\n self.write_last_ts_written()\n\n logging.info(\"Disconnecting from database ...\")\n conn.close()\n logging.info(\"Disconnected from database.\")\n return True\n\n except psycopg2.OperationalError as e:\n logging.error(\n 'Could not connect to database : \"{}\"'.format(str(e).replace(\"\\n\", \"\"))\n )\n\n return False\n\n return True","def _read_stream(self):\n input_df = self.spark \\\n .readStream \\\n .format(\"kafka\") \\\n .option(\"kafka.bootstrap.servers\", \"localhost:9092\") \\\n .option(\"subscribe\", \"agro\") \\\n .option(\"startingOffsets\", \"latest\") \\\n .load()\n\n return input_df","def _messages_list(self, queue):\n\n return queue.messages()","def get_messages_sent_by(self, nodeid):\n bucket = self._buckets[nodeid]\n messages = []\n\n while not bucket.empty():\n messages.append(bucket.get_nowait())\n\n return message.MessagesSet(messages)","def create_stream_table_dataframe(\n streams, true_state=False, time_point=0, orient=\"columns\"\n):\n\n stream_attributes = OrderedDict()\n stream_states = stream_states_dict(streams=streams, time_point=time_point)\n full_keys = [] # List of all rows in dataframe to fill in missing data\n\n stream_attributes[\"Units\"] = {}\n\n for key, sb in stream_states.items():\n stream_attributes[key] = {}\n if true_state:\n disp_dict = sb.define_state_vars()\n else:\n disp_dict = sb.define_display_vars()\n for k in disp_dict:\n for row, i in enumerate(disp_dict[k]):\n stream_key = k if i is None else f\"{k} {i}\"\n quant = report_quantity(disp_dict[k][i])\n stream_attributes[key][stream_key] = quant.m\n if row == 0 or stream_key not in stream_attributes[\"Units\"]:\n stream_attributes[\"Units\"][stream_key] = quant.u\n if stream_key not in full_keys:\n full_keys.append(stream_key)\n\n # Check for missing rows in any stream, and fill with \"-\" if needed\n for k, v in stream_attributes.items():\n for r in full_keys:\n if r not in v.keys():\n # Missing row, fill with placeholder\n v[r] = \"-\"\n\n return DataFrame.from_dict(stream_attributes, orient=orient)","def copy_table_stream_settings(events: dict, context: dict):\n if 'SourceTableName' not in events:\n raise KeyError('Requires SourceTableName')\n if 'TargetTableName' not in events:\n raise KeyError('Requires TargetTableName')\n\n source_table_name = events['SourceTableName']\n description = _describe_table(table_name=source_table_name)['Table']\n stream_enabled = description\\\n .get('StreamSpecification', {})\\\n .get('StreamEnabled', False)\n if stream_enabled:\n target_table_name = events['TargetTableName']\n stream_view_type = description['StreamSpecification']['StreamViewType']\n settings = {\n \"StreamSpecification\": {\n \"StreamEnabled\": stream_enabled,\n \"StreamViewType\": stream_view_type\n }\n }\n result = _update_table(table_name=target_table_name, **settings)\n specification = result.get('StreamSpecification', {})\n return specification","def create_stream(self, tag, database, table):\n try:\n logger.info(\"About to create a firehose stream \")\n self.firehose_client.create_delivery_stream(DeliveryStreamName=self.get_stream_name(tag),\n ExtendedS3DestinationConfiguration=self.create_s3_dest_config(tag, database, table))\n except ClientError:\n logger.info(\"The firehose stream has already been created!\\n\")","def fetch_messages(self, label, size, startwith=0):\n messages = Room.objects.get(label=label).messages.order_by('-created')[startwith:size]\n messages = MessageSerializers(messages, many=True)\n return messages.data","def messages(self, request, *args, **kwargs):\n conversation = self.get_object()\n related = ['user__profile']\n related2 = ['attachments']\n messages_qs = conversation.messages.all().select_related(*related).prefetch_related(*related2)\n self.pagination_class = DateTimePagination\n page = self.paginate_queryset(messages_qs)\n\n # Only keep the messages that were not deleted by this user\n messages_ids = map(lambda m: m.id, page.object_list)\n deleted_messages_ids = request.user.deleted_messages.filter(id__in=messages_ids).values_list('id', flat=True)\n for message in page.object_list:\n if message.id in deleted_messages_ids:\n page.object_list.remove(message)\n\n serializer = MessageSerializer(page, many=True, context={'request': request})\n conversation.mark_as_read(request.user)\n return self.get_paginated_response(serializer.data)","def send_data(self, stream_id):\n send_stream = self.send_streams.get(stream_id)\n\n if not send_stream:\n # window updates trigger sending of data, but can happen after a stream\n # has been completely sent\n return\n\n if not send_stream.headers_sent:\n # don't attempt to send any data until the headers have been sent\n return\n\n try:\n window_size = self.conn.local_flow_control_window(stream_id=stream_id)\n max_frame_size = self.conn.max_outbound_frame_size\n\n for chunk in send_stream.read(window_size, max_frame_size):\n log.debug(\"sending data on stream %s: %s...\", stream_id, chunk[:100])\n\n self.conn.send_data(stream_id=stream_id, data=chunk)\n\n except StreamClosedError:\n return\n\n if send_stream.exhausted:\n log.debug(\"closing exhausted stream, stream %s\", stream_id)\n self.end_stream(stream_id)","def text(message):\n global list_messages\n room = session.get('room')\n msg = session.get('name') + ':' + message['msg']\n list_messages.append(msg)\n addNewMsg(message,session)\n print ('size of list_messages ' + str(len(list_messages)) + ', session ' + str(session))\n emit('message', {'msg': msg}, room=room)","def _dispatch_messages(self):\n while True:\n select_obj = (yield)\n if select_obj == self._message_queue.selobj:\n msg = self._message_queue.get_nowait()\n if msg is not None:\n msg_type = msg.get('type', None)\n if msg_type is not None:\n msg_handler = self._message_handlers.get(msg_type, None)\n if msg_handler is not None:\n msg_handler(msg['data'])","def process_messages(self):\n pass","def _streaming_command(self, service, command, transport_timeout_s, read_timeout_s, timeout_s):\n adb_info = self._open(b'%s:%s' % (service, command), transport_timeout_s, read_timeout_s, timeout_s)\n\n for data in self._read_until_close(adb_info):\n yield data","def stream(self, __template_id=\"*\", __query=None, *, offset=None, read_as=None):\n raise NotImplementedError","def wrap_streaming_content(self, streaming_content):\n for chunk in streaming_content:\n yield chunk","def handle_recv(self,stream,msgs):\n pass","async def _send_stream_data(\n self, request: Request, stream_id: int, data: bytes\n ) -> None:\n while data:\n max_flow = await self._wait_for_outgoing_flow(request, stream_id)\n chunk_size = min(len(data), max_flow)\n chunk, data = data[:chunk_size], data[chunk_size:]\n self._h2_state.send_data(stream_id, chunk)\n await self._write_outgoing_data(request)","def load_stream(self, stream):\n import pyarrow as pa\n\n batches = super(ArrowStreamUDFSerializer, self).load_stream(stream)\n for batch in batches:\n struct = batch.column(0)\n yield [pa.RecordBatch.from_arrays(struct.flatten(), schema=pa.schema(struct.type))]","def multiple_messages(self, messages):\n for message in messages:\n cmd = '{}serverMessage \"{}\"'.format(self.console, Commands.aquote(message))\n self.write_command(cmd)","def get_messages(self, page=0):\n endpoint = 'https://outlook.office.com/api/v2.0/me/messages'\n if page > 0:\n endpoint = endpoint + '/?%24skip=' + str(page) + '0'\n\n log.debug('Getting messages from endpoint: {} with Headers: {}'.format(endpoint, self._headers))\n\n r = requests.get(endpoint, headers=self._headers)\n\n check_response(r)\n\n return Message._json_to_messages(self, r.json())","def stream_query(self, commands):\n # The CLI transport does not support pipelining.\n if self.transport is pywatchman.CLIProcessTransport:\n raise NotImplementedError()\n\n cmd_buf = deque(command for command in reversed(commands))\n self._connect()\n\n while 1:\n # Interleave sends and receives to avoid bi-directional communication issues.\n if cmd_buf:\n item = cmd_buf.pop()\n try:\n self.sendConn.send(item)\n except pywatchman.SocketTimeout:\n cmd_buf.append(item)\n yield\n\n try:\n result = self.recvConn.receive()\n except pywatchman.SocketTimeout:\n # Socket timeout - yield runtime context.\n yield\n else:\n if 'error' in result:\n raise pywatchman.WatchmanError('error from watchman: {}'.format(result['error']))\n elif self.isUnilateralResponse(result) or 'subscribe' in result:\n yield result\n else:\n yield result\n break","def ProcessMessage(self, status_message, stream):\n self.object_report_change = False\n if isinstance(status_message, SeekAheadMessage):\n self._HandleSeekAheadMessage(status_message, stream)\n elif isinstance(status_message, ProducerThreadMessage):\n self._HandleProducerThreadMessage(status_message)\n elif isinstance(status_message, MetadataMessage):\n self._HandleMetadataMessage(status_message)\n elif isinstance(status_message, RetryableErrorMessage):\n LogRetryableError(status_message)\n elif isinstance(status_message, PerformanceSummaryMessage):\n self._HandlePerformanceSummaryMessage(status_message)\n self.old_progress.append(\n self._ThroughputInformation(self.objects_finished, status_message.time))","def callback(parsed_msg, msg_object):\n assert msg_object.stream_id == stream_id\n assert parsed_msg in msg","def stream_blocks():\n # add height\n query = iroha.blocks_query()\n ic.sign_query(query, user_private_key)\n for block in net.send_blocks_stream_query(query):\n pprint(\"The next block arrived: {}\".format(MessageToDict(block)), indent=1)","def getAllMessages(self):\n return self.db.getAllMessages()","def send_stream_to_kafka(self, df: pd.DataFrame) -> None:\n for row in df.values.tolist():\n value = dict(zip(self.get_value_structure(), row))\n key = dict(zip(self.get_key_structure(), [row[13]]))\n # key = {\"npi\": int(row[0])}\n # key = str(uuid.uuid4())\n self.producer.producer.produce(topic=self.topic_name, key=key, value=value)\n logger.info(f\"sent event to kafka with key: {key} and value: {value}\", class_name=self.__class__.__name__)","def listener(messages):\n for m in messages:\n chatid = m.chat.id\n print(str(chatid))\n if m.content_type == 'text':\n text = m.text\n tb.send_message(chatid, text)","def show_messages():\n\n messages = Message.query.all()\n # translation_list = [\"\"]\n\n for message in messages:\n # message.translation gives list of objects. All the translation for the \n # language. Here assgin it to one trans_text based on user's language\n # selection. \n message.translation = Translation.query.filter_by(language=g.user.language, \n message_id=message.message_id).first()\n\n return render_template(\"messages.html\", messages=messages, user=g.user)","def select_all_messages(conn):\n cur = conn.cursor()\n cur.execute(\"SELECT * FROM LED_MESSAGE\")\n\n rows = cur.fetchall()\n\n all_m = []\n for row in rows:\n l_m = { \n \"ts\": row[0],\n \"elapsed\": float(row[1]), \n \"font\": row[2], \n \"type\": row[3], \n \"body\": row[4], \n \"color\": row[5], \n \"behavior\": row[6]\n }\n all_m.append({ \"message\":{ \"payload\": l_m }})\n\n return all_m","def subscribe_to_stream(client, iterator, seconds_running):\n end_time = datetime.now() + timedelta(seconds=seconds_running)\n while True:\n record_response = client.get_records(ShardIterator=iterator)\n # Only run for a certain amount of time.\n # Stop looping if no data returned. This means it's done\n now = datetime.now()\n if end_time < now:\n break\n else:\n # yield data to outside calling iterator\n for record in record_response['Records']:\n data = record[\"Data\"].decode(\"utf-8\")\n timestamp = record[\"ApproximateArrivalTimestamp\"]\n record_id = record[\"SequenceNumber\"]\n tweet_record = [record_id, timestamp, data]\n yield tweet_record\n # Get next iterator for shard from previous request\n iterator = record_response['NextShardIterator']","def dump_stream(self, iterator, stream):\n\n import pandas as pd\n import pyarrow as pa\n\n def construct_state_pdf(state):\n \"\"\"\n Construct a pandas DataFrame from the state instance.\n \"\"\"\n\n state_properties = state.json().encode(\"utf-8\")\n state_key_row_as_binary = state._keyAsUnsafe\n if state.exists:\n state_object = self.pickleSer.dumps(state._value_schema.toInternal(state._value))\n else:\n state_object = None\n state_old_timeout_timestamp = state.oldTimeoutTimestamp\n\n state_dict = {\n \"properties\": [\n state_properties,\n ],\n \"keyRowAsUnsafe\": [\n state_key_row_as_binary,\n ],\n \"object\": [\n state_object,\n ],\n \"oldTimeoutTimestamp\": [\n state_old_timeout_timestamp,\n ],\n }\n\n return pd.DataFrame.from_dict(state_dict)\n\n def construct_record_batch(pdfs, pdf_data_cnt, pdf_schema, state_pdfs, state_data_cnt):\n \"\"\"\n Construct a new Arrow RecordBatch based on output pandas DataFrames and states. Each\n one matches to the single struct field for Arrow schema. We also need an extra one to\n indicate array length for data and state, so the return value of Arrow RecordBatch will\n have schema with three fields, in `count`, `data`, `state` order.\n (Readers are expected to access the field via position rather than the name. We do\n not guarantee the name of the field.)\n\n Note that Arrow RecordBatch requires all columns to have all same number of rows,\n hence this function inserts empty data for count/state/data with less elements to\n compensate.\n \"\"\"\n\n max_data_cnt = max(1, max(pdf_data_cnt, state_data_cnt))\n\n # We only use the first row in the count column, and fill other rows to be the same\n # value, hoping it is more friendly for compression, in case it is needed.\n count_dict = {\n \"dataCount\": [pdf_data_cnt] * max_data_cnt,\n \"stateCount\": [state_data_cnt] * max_data_cnt,\n }\n count_pdf = pd.DataFrame.from_dict(count_dict)\n\n empty_row_cnt_in_data = max_data_cnt - pdf_data_cnt\n empty_row_cnt_in_state = max_data_cnt - state_data_cnt\n\n empty_rows_pdf = pd.DataFrame(\n dict.fromkeys(pa.schema(pdf_schema).names),\n index=[x for x in range(0, empty_row_cnt_in_data)],\n )\n empty_rows_state = pd.DataFrame(\n columns=[\"properties\", \"keyRowAsUnsafe\", \"object\", \"oldTimeoutTimestamp\"],\n index=[x for x in range(0, empty_row_cnt_in_state)],\n )\n\n pdfs.append(empty_rows_pdf)\n state_pdfs.append(empty_rows_state)\n\n merged_pdf = pd.concat(pdfs, ignore_index=True)\n merged_state_pdf = pd.concat(state_pdfs, ignore_index=True)\n\n return self._create_batch(\n [\n (count_pdf, self.result_count_pdf_arrow_type),\n (merged_pdf, pdf_schema),\n (merged_state_pdf, self.result_state_pdf_arrow_type),\n ]\n )\n\n def serialize_batches():\n \"\"\"\n Read through an iterator of (iterator of pandas DataFrame, state), and serialize them\n to Arrow RecordBatches.\n\n This function does batching on constructing the Arrow RecordBatch; a batch will be\n serialized to the Arrow RecordBatch when the total number of records exceeds the\n configured threshold.\n \"\"\"\n # a set of variables for the state of current batch which will be converted to Arrow\n # RecordBatch.\n pdfs = []\n state_pdfs = []\n pdf_data_cnt = 0\n state_data_cnt = 0\n\n return_schema = None\n\n for data in iterator:\n # data represents the result of each call of user function\n packaged_result = data[0]\n\n # There are two results from the call of user function:\n # 1) iterator of pandas DataFrame (output)\n # 2) updated state instance\n pdf_iter = packaged_result[0][0]\n state = packaged_result[0][1]\n\n # This is static and won't change across batches.\n return_schema = packaged_result[1]\n\n for pdf in pdf_iter:\n # We ignore empty pandas DataFrame.\n if len(pdf) > 0:\n pdf_data_cnt += len(pdf)\n pdfs.append(pdf)\n\n # If the total number of records in current batch exceeds the configured\n # threshold, time to construct the Arrow RecordBatch from the batch.\n if pdf_data_cnt > self.arrow_max_records_per_batch:\n batch = construct_record_batch(\n pdfs, pdf_data_cnt, return_schema, state_pdfs, state_data_cnt\n )\n\n # Reset the variables to start with new batch for further data.\n pdfs = []\n state_pdfs = []\n pdf_data_cnt = 0\n state_data_cnt = 0\n\n yield batch\n\n # This has to be performed 'after' evaluating all elements in iterator, so that\n # the user function has been completed and the state is guaranteed to be updated.\n state_pdf = construct_state_pdf(state)\n\n state_pdfs.append(state_pdf)\n state_data_cnt += 1\n\n # processed all output, but current batch may not be flushed yet.\n if pdf_data_cnt > 0 or state_data_cnt > 0:\n batch = construct_record_batch(\n pdfs, pdf_data_cnt, return_schema, state_pdfs, state_data_cnt\n )\n\n yield batch\n\n def init_stream_yield_batches(batches):\n \"\"\"\n This function helps to ensure the requirement for Pandas UDFs - Pandas UDFs require a\n START_ARROW_STREAM before the Arrow stream is sent.\n\n START_ARROW_STREAM should be sent after creating the first record batch so in case of\n an error, it can be sent back to the JVM before the Arrow stream starts.\n \"\"\"\n should_write_start_length = True\n\n for batch in batches:\n if should_write_start_length:\n write_int(SpecialLengths.START_ARROW_STREAM, stream)\n should_write_start_length = False\n\n yield batch\n\n batches_to_write = init_stream_yield_batches(serialize_batches())\n\n return ArrowStreamSerializer.dump_stream(self, batches_to_write, stream)","def give_messages(self, messages, verbose=False, cache=False, tunnel=None, source_sock_addr=None):\n assert isinstance(messages, list)\n assert all(isinstance(message, Message.Implementation) for message in messages)\n assert isinstance(verbose, bool)\n assert isinstance(cache, bool)\n assert tunnel is None, \"TUNNEL property is set using init_socket(...)\"\n assert source_sock_addr is None or isinstance(source_sock_addr, tuple), type(source_sock_addr)\n packets = [message.packet if message.packet else self.encode_message(message) for message in messages]\n if verbose:\n logger.debug(\"giving %d messages (%d bytes)\", len(messages), sum(len(packet) for packet in packets))\n self.give_packets(packets, verbose=verbose, cache=cache, tunnel=tunnel, source_sock_addr=source_sock_addr)\n return messages","def messages(self):\n return itertools.chain.from_iterable(\n mset.messages\n for topic, partitions in iteritems(self.msets)\n for partition_id, mset in iteritems(partitions)\n )","def stream_table_dataframe_to_string(stream_table, **kwargs):\n # Set some default values for keyword arguments\n na_rep = kwargs.pop(\"na_rep\", \"-\")\n justify = kwargs.pop(\"justify\", \"center\")\n float_format = kwargs.pop(\"float_format\", lambda x: \"{:#.5g}\".format(x))\n\n # Print stream table\n return stream_table.to_string(\n na_rep=na_rep, justify=justify, float_format=float_format, **kwargs\n )","def ProcessMessage(self, status_message, stream):\n self.object_report_change = False\n if isinstance(status_message, ProducerThreadMessage):\n # ProducerThread info.\n self._HandleProducerThreadMessage(status_message)\n\n elif isinstance(status_message, SeekAheadMessage):\n # SeekAheadThread info.\n self._HandleSeekAheadMessage(status_message, stream)\n\n elif isinstance(status_message, FileMessage):\n if self._IsFile(status_message):\n # File info.\n self._HandleFileDescription(status_message)\n else:\n # Component info.\n self._HandleComponentDescription(status_message)\n LogPerformanceSummaryParams(file_message=status_message)\n\n elif isinstance(status_message, ProgressMessage):\n # Progress info.\n self._HandleProgressMessage(status_message)\n\n elif isinstance(status_message, RetryableErrorMessage):\n LogRetryableError(status_message)\n\n elif isinstance(status_message, PerformanceSummaryMessage):\n self._HandlePerformanceSummaryMessage(status_message)\n\n self.old_progress.append(\n self._ThroughputInformation(self.new_progress, status_message.time))","def get_public_messages(self):\n messages = []\n for message in self.messages:\n if message.message_id != None:\n messages.append(message)\n return messages","def data_received(self, event):\n stream_id = event.stream_id\n\n log.debug(\"data received on stream %s: %s...\", stream_id, event.data[:100])\n receive_stream = self.receive_streams.get(stream_id)\n if receive_stream is None:\n try:\n self.conn.reset_stream(stream_id, error_code=ErrorCodes.PROTOCOL_ERROR)\n except StreamClosedError:\n pass\n return\n\n receive_stream.write(event.data)\n self.conn.acknowledge_received_data(event.flow_controlled_length, stream_id)","def show_message(id):\n session = Session()\n message = session.query(Message).filter_by(id=id).one()\n msg_dct = create_message(message)\n msg_dct[\"size\"] = message.size\n msg_dct[\"recipients\"] = create_recipients(message.recipients)\n return msg_dct","def display_received_table(self, num_disp, old):\n caller = self.caller\n msgtable = PrettyTable(\n [\"{wMsg #\", \"{wSender\", \"{wIC Date\", \"{wOOC Date\", \"{wSave\"]\n )\n mess_num = 1\n old = old[:num_disp]\n for mess in old:\n try:\n name = caller.messages.get_sender_name(mess)\n except AttributeError:\n mess = reload_model_as_proxy(mess)\n print(\n \"Error: Had to reload Msg ID %s as Messenger when displaying received table.\"\n % mess.id\n )\n name = caller.messages.get_sender_name(mess)\n date = caller.messages.get_date_from_header(mess) or \"Unknown\"\n ooc_date = mess.db_date_created.strftime(\"%x\")\n saved = \"{w*{n\" if mess.preserved else \"\"\n msgtable.add_row([mess_num, name, date, ooc_date, saved])\n mess_num += 1\n self.msg(msgtable)","def publish_list(self, messages: list) -> None:","def publish_list(self, messages: list) -> None:","def store_in_sql(cache, db_handler, TABLE_NAME):\r\n if len(cache) == 0 and len(cache[0]) == 0:\r\n return\r\n\r\n # create new table for new streaming event\r\n if TABLE_NAME[0] == '':\r\n TABLE_NAME[0] = db_handler.create_table(cache[0])\r\n \r\n # write message to database\r\n for message in cache:\r\n db_handler.insert_entry(message)"],"string":"[\n \"def message_table(message):\\r\\n table = Table(['property', 'value'])\\r\\n table.align['property'] = 'r'\\r\\n table.align['value'] = 'l'\\r\\n\\r\\n table.add_row(['id', message['id']])\\r\\n table.add_row(['initial_entry_time', message['initial_entry_time']])\\r\\n table.add_row(['visibility_delay', message['visibility_delay']])\\r\\n table.add_row(['visibility_interval', message['visibility_interval']])\\r\\n table.add_row(['fields', message['fields']])\\r\\n return [table, message['body']]\",\n \"def GetMessageTableResource(self):\\n return self._wrc_stream.get_resource_by_identifier(\\n self._MESSAGE_TABLE_RESOURCE_IDENTIFIER)\",\n \"def event_stream(self):\\n for message in self.subscribe():\\n event = message_to_sse(message[\\\"data\\\"])\\n yield event\",\n \"def MessageStream(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\\n raise NotImplementedError()\",\n \"def list_messages():\\n session = Session()\\n messages = session.query(Message).all()\\n msg_lst = []\\n for message in messages:\\n msg_lst.append(create_message(message))\\n return msg_lst\",\n \"def _seek_to_table(self, table):\\n\\n self.stream.seek(self.table_pointers[table])\",\n \"def generate(self):\\n \\n privateproc = False\\n if self.rowcount > 0:\\n try:\\n table = spss.BasePivotTable(self.tabletitle, self.omssubtype)\\n except:\\n StartProcedure(_(\\\"Messages\\\"), self.procname)\\n privateproc = True\\n table = spss.BasePivotTable(self.tabletitle, self.omssubtype)\\n if self.caption:\\n table.Caption(self.caption)\\n # Note: Unicode strings do not work as cell values in 18.0.1 and probably back to 16\\n if self.columnlabels != []:\\n table.SimplePivotTable(self.rowdim, self.rowlabels, self.coldim, self.columnlabels, self.columnvalues)\\n else:\\n table.Append(spss.Dimension.Place.row,\\\"rowdim\\\",hideName=True,hideLabels=True)\\n table.Append(spss.Dimension.Place.column,\\\"coldim\\\",hideName=True,hideLabels=True)\\n colcat = spss.CellText.String(\\\"Message\\\")\\n for r in self.rowlabels:\\n cellr = spss.CellText.String(r)\\n table[(cellr, colcat)] = cellr\\n if privateproc:\\n spss.EndProcedure()\",\n \"def get_messages():\\n dynamodb = boto3.client('dynamodb')\\n messages = []\\n _messages = []\\n paginator = dynamodb.get_paginator('scan')\\n for page in paginator.paginate(TableName=os.environ.get('MESSAGE_TABLE_NAME')):\\n _messages.extend(page['Items'])\\n\\n if not _messages:\\n return _messages\\n\\n for message in _messages:\\n m = {\\n message['timestamp']['N']: message['data']['S']\\n }\\n messages.append(m)\\n\\n # sort list of dict by timestamp\\n messages = list(map(dict, sorted(list(i.items()) for i in messages)))\\n\\n _messages = []\\n for message in messages:\\n _, v = list(message.items())[0]\\n _messages.append(v)\\n\\n return _messages\",\n \"def stream(self):\\n\\n iterator = iter(self._stream)\\n while self._state < Computation.STATE_COMPLETED:\\n try:\\n message = next(iterator)\\n except StopIteration:\\n if self._state < Computation.STATE_COMPLETED:\\n self._stream = self._execute()\\n iterator = iter(self._stream)\\n continue\\n break\\n\\n if isinstance(message, messages.StreamStartMessage):\\n self._state = Computation.STATE_STREAM_STARTED\\n continue\\n\\n if isinstance(message, messages.JobStartMessage):\\n self._state = Computation.STATE_COMPUTATION_STARTED\\n self._id = message.handle\\n yield message\\n continue\\n\\n if isinstance(message, messages.JobProgressMessage):\\n yield message\\n continue\\n\\n if isinstance(message, messages.ChannelAbortMessage):\\n self._state = Computation.STATE_ABORTED\\n raise errors.ComputationAborted(message.abort_info)\\n\\n if isinstance(message, messages.EndOfChannelMessage):\\n self._state = Computation.STATE_COMPLETED\\n continue\\n\\n # Intercept metadata messages to accumulate received metadata...\\n if isinstance(message, messages.MetadataMessage):\\n self._metadata[message.tsid] = message.properties\\n yield message\\n continue\\n\\n # ...as well as expired-tsid messages to clean it up.\\n if isinstance(message, messages.ExpiredTsIdMessage):\\n if message.tsid in self._metadata:\\n del self._metadata[message.tsid]\\n yield message\\n continue\\n\\n if isinstance(message, messages.InfoMessage):\\n self._process_info_message(message.message)\\n self._batch_count_detected = True\\n yield message\\n if self._current_batch_message:\\n yield self._get_batch_to_yield()\\n continue\\n\\n # Accumulate data messages and release them when we have received\\n # all batches for the same logical timestamp.\\n if isinstance(message, messages.DataMessage):\\n self._state = Computation.STATE_DATA_RECEIVED\\n\\n if not self._batch_count_detected:\\n self._expected_batches += 1\\n\\n if not self._current_batch_message:\\n self._current_batch_message = message\\n self._current_batch_count = 1\\n elif (message.logical_timestamp_ms ==\\n self._current_batch_message.logical_timestamp_ms):\\n self._current_batch_message.add_data(message.data)\\n self._current_batch_count += 1\\n else:\\n self._batch_count_detected = True\\n\\n if (self._batch_count_detected and\\n self._current_batch_count == self._expected_batches):\\n yield self._get_batch_to_yield()\\n continue\\n\\n if isinstance(message, messages.EventMessage):\\n yield message\\n continue\\n\\n if isinstance(message, messages.ErrorMessage):\\n raise errors.ComputationFailed(message.errors)\\n\\n # Yield last batch, even if potentially incomplete.\\n if self._current_batch_message:\\n yield self._get_batch_to_yield()\",\n \"def get_messages(self):\\n res = self.conn.cursor().execute(\\\"SELECT * FROM messages\\\")\\n return res.fetchall()\",\n \"def iterate_msgs(stream):\\n while True:\\n item = None\\n buf = bytearray()\\n stall_timer = None\\n\\n while True:\\n # read bytes until item boundary reached\\n buf += stream.read(1)\\n if not buf:\\n # check for stall (i.e. no data for 90 seconds)\\n if not stall_timer:\\n stall_timer = time.time()\\n elif time.time() - stall_timer > TwitterAPI.STREAMING_TIMEOUT:\\n raise TwitterConnectionError(\\\"Twitter stream stalled\\\")\\n elif stall_timer:\\n stall_timer = None\\n if buf[-2:] == b\\\"\\\\r\\\\n\\\":\\n item = buf[0:-2]\\n if item.isdigit():\\n # use byte size to read next item\\n nbytes = int(item)\\n item = None\\n item = stream.read(nbytes)\\n yield item\\n else:\\n yield b\\\"\\\" # keepalive\\n break\",\n \"def sqs_messages(queue: str) -> Generator[Dict[str, Any], None, None]:\\n\\n while True:\\n response = get_client(\\\"sqs\\\").receive_message(QueueUrl=queue)\\n if \\\"Messages\\\" not in response:\\n break\\n msg = json.loads(response[\\\"Messages\\\"][0][\\\"Body\\\"])\\n records = json.loads(msg[\\\"Message\\\"])\\n retd = {}\\n retd[\\\"key\\\"] = records[\\\"Records\\\"][0][\\\"s3\\\"][\\\"object\\\"][\\\"key\\\"]\\n retd[\\\"bucket\\\"] = records[\\\"Records\\\"][0][\\\"s3\\\"][\\\"bucket\\\"][\\\"name\\\"]\\n retd[\\\"ReceiptHandle\\\"] = response[\\\"Messages\\\"][0][\\\"ReceiptHandle\\\"]\\n yield retd\",\n \"def _streaming_service(self, service, command, transport_timeout_s=None, read_timeout_s=constants.DEFAULT_READ_TIMEOUT_S, decode=True):\\n stream = self._streaming_command(service, command, transport_timeout_s, read_timeout_s, None)\\n if decode:\\n for line in (stream_line.decode('utf8', _DECODE_ERRORS) for stream_line in stream):\\n yield line\\n else:\\n for line in stream:\\n yield line\",\n \"def __iter__(self):\\n return iter([self.format_message(record) for record in self._messages])\",\n \"def get_user_messages(user_id):\\n return UserMessage.query.filter(user_id == UserMessage.user_id).all()\",\n \"def get_messages(self, number: int):\\n self.sql_lock.acquire()\\n query: str = \\\"SELECT * FROM messages order by id desc LIMIT ?\\\" \\n messages = []\\n for item in self.cursor.execute(query,(number, )):\\n text, user, id = item\\n\\n messages.append({\\\"user\\\": user, \\\"text\\\": f\\\"message- {text}\\\", \\\"id\\\": id})\\n \\n self.sql_lock.release()\\n return messages\",\n \"def Read(self):\\n try:\\n file_object = self._zip_file.open(self._stream_name, mode='r')\\n except KeyError as exception:\\n raise IOError(\\n 'Unable to open stream with error: {0!s}'.format(exception))\\n\\n try:\\n entry_data = file_object.read(self._TABLE_ENTRY_SIZE)\\n while entry_data:\\n table_entry = self._TABLE_ENTRY.parse(entry_data)\\n\\n self._timestamps.append(table_entry.timestamp)\\n entry_data = file_object.read(self._TABLE_ENTRY_SIZE)\\n\\n except construct.FieldError as exception:\\n raise IOError(\\n 'Unable to read table entry with error: {0!s}'.format(exception))\\n\\n finally:\\n file_object.close()\",\n \"def run_message():\\n import simplejson\\n from ssgateway.message import main\\n from yaml import load\\n parser = argparse.ArgumentParser(\\n description='export a table to a yaml file')\\n parser.add_argument('--message', dest='message',\\n help='the message to run')\\n args, env = initialize_command(parser)\\n\\n message = simplejson.loads(args.message)\\n route_config = env['registry'].settings.get('routes')\\n message_router = main(load(open(route_config)))\\n message_router(message)\\n\\n env['closer']()\",\n \"def readFromStream(cls, stream):\\n list_ = []\\n event_id_list = []\\n for tr in stream:\\n if tr.stats.event.id not in event_id_list:\\n list_.append(tr.stats.event)\\n event_id_list.append(tr.stats.event.id)\\n\\n log.info('Read event information of %d events from stream %s' % (len(list_), stream.hash))\\n return cls(list_)\",\n \"def load_stream(self, stream):\\n batches = super(ArrowStreamPandasSerializer, self).load_stream(stream)\\n import pyarrow as pa\\n\\n for batch in batches:\\n yield [self.arrow_to_pandas(c) for c in pa.Table.from_batches([batch]).itercolumns()]\",\n \"def create_stream(phrase, queue):\\n local = SocketIO(message_queue=queue)\\n stream = Twitter().stream(phrase, timeout=30)\\n\\n for i in range(60):\\n stream.update()\\n for tweet in reversed(stream):\\n sentiment = classify_tweet(tweet)\\n x, y = vectorize_tweet(tweet)\\n local.emit('tweet', {'id': str(i),\\n 'text': str(tweet.text.encode('ascii', 'ignore')),\\n 'sentiment': sentiment,\\n 'x': x,\\n 'y': y})\\n stream.clear()\\n time.sleep(1)\\n\\n return queue\",\n \"def test_iterate_over_stream():\\n archive = Archive()\\n archive.commit(doc=DataFrameDocument(df=DF1))\\n rows = list()\\n with archive.open(version=0).open() as reader:\\n for row in reader:\\n rows.append(row)\\n assert rows == [\\n (0, 0, ['Alice', 32]),\\n (1, 1, ['Bob', 45]),\\n (2, 2, ['Claire', 27]),\\n (3, 3, ['Alice', 23])\\n ]\",\n \"def stream(\\n consumer: Consumer,\\n count: Optional[int] = None,\\n poll_timeout: Optional[float] = DEFAULT_POLL_TIMEOUT,\\n timeout: Optional[float] = None,\\n) -> Iterator[Message]:\\n if count is not None and count <= 0:\\n raise ValueError(\\\"count must be a positive integer.\\\")\\n if poll_timeout is not None and poll_timeout <= 0:\\n raise ValueError(\\\"poll_timeout must be a positive float.\\\")\\n if timeout is not None and timeout <= 0:\\n raise ValueError(\\\"timeout must be a positive float.\\\")\\n\\n if count is None:\\n LOGGER.debug(\\\"Streaming messages....\\\")\\n else:\\n LOGGER.debug(\\\"Streaming up to %d messages....\\\", count)\\n\\n if timeout is not None:\\n timeout_delta = timedelta(milliseconds=int(timeout * MILLIS_IN_SECOND))\\n\\n stream_duration = timedelta()\\n num_messages = 0\\n while count is None or num_messages < count:\\n if musekafka.shutdown.is_shutting_down():\\n break\\n\\n if timeout is not None:\\n if stream_duration >= timeout_delta:\\n LOGGER.debug(\\\"Hit stream timeout (%.3f seconds).\\\", timeout)\\n break\\n poll_timeout = min(\\n poll_timeout or timeout, (timeout_delta - stream_duration).total_seconds()\\n )\\n\\n stream_start = datetime.utcnow()\\n try:\\n message = poll(consumer, timeout=poll_timeout)\\n except TimeoutError as e:\\n LOGGER.debug(str(e))\\n continue\\n finally:\\n stream_duration += datetime.utcnow() - stream_start\\n with bind_message_ctx(message):\\n yield message\\n num_messages += 1\\n LOGGER.debug(\\\"Completed streaming %d messages.\\\", num_messages)\",\n \"def get_all_messages(self):\\n cursor = self.get_cursor()\\n query = 'WITH replies_query AS (SELECT replied_to, array_agg(mid) AS replies_list ' \\\\\\n 'FROM replies INNER JOIN messages ON replies.reply = messages.mid ' \\\\\\n 'GROUP BY replied_to), ' \\\\\\n 'like_count AS (SELECT mid, COUNT(*) AS likes FROM vote ' \\\\\\n 'WHERE upvote = TRUE GROUP BY mid), ' \\\\\\n 'dislike_count AS (SELECT mid, COUNT(*) AS dislikes FROM vote ' \\\\\\n 'WHERE upvote = FALSE GROUP BY mid) ' \\\\\\n 'SELECT messages.mid, users.uid, cid, message, image, ' \\\\\\n 'COALESCE(likes, 0) AS likes, COALESCE(dislikes, 0) AS dislikes, username, ' \\\\\\n \\\"COALESCE(replies_list, '{}') AS replies, messages.created_on \\\" \\\\\\n 'FROM messages LEFT OUTER JOIN like_count ON messages.mid = like_count.mid ' \\\\\\n 'LEFT OUTER JOIN dislike_count ON messages.mid = dislike_count.mid ' \\\\\\n 'LEFT OUTER JOIN photo ON messages.mid = photo.mid ' \\\\\\n 'INNER JOIN users ON messages.uid = users.uid ' \\\\\\n 'LEFT OUTER JOIN replies_query ON messages.mid = replies_query.replied_to ' \\\\\\n 'ORDER BY messages.created_on DESC'\\n cursor.execute(query)\\n messages = cursor.fetchall()\\n return messages\",\n \"def handle_stream(self, stream, address):\\n r = Participant(stream, self.db)\\n r.wait_for_headers()\",\n \"def on_messages(self, msg_list):\\n self.stats.on_pack_recv(len(msg_list))\\n\\n for msg in msg_list:\\n if self.state == OPEN:\\n self.conn.on_message(msg)\",\n \"def MessageStream(self, request, context):\\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)\",\n \"def list_messages(self):\",\n \"def subscribe(self, host:str, port:str, handler:Callable, tableName:str, actionName:str=None, offset:int=-1, resub:bool=False, \\n filter=None, msgAsTable:bool=False, batchSize:int=0, throttle:float=1,\\n userName:str=None, password:str=None, streamDeserializer:Optional[Type[\\\"streamDeserializer\\\"]]=None) -> None:\\n if not isinstance(msgAsTable, bool):\\n raise ValueError(\\\"msgAsTable must be a bool\\\")\\n if filter is None:\\n filter = np.array([],dtype='int64')\\n if actionName is None:\\n actionName = \\\"\\\"\\n if userName is None:\\n userName = \\\"\\\"\\n if password is None:\\n password = \\\"\\\"\\n sd=None\\n if streamDeserializer is None:\\n sd = ddbcpp.streamDeserializer({})\\n else:\\n sd = streamDeserializer.cpp\\n if batchSize > 0:\\n self.cpp.subscribeBatch(host, port, handler, tableName, actionName, offset, resub, filter, msgAsTable, batchSize, throttle,userName,password,sd)\\n else:\\n if msgAsTable:\\n raise ValueError(\\\"msgAsTable must be False when batchSize is 0\\\")\\n self.cpp.subscribe(host, port, handler, tableName, actionName, offset, resub, filter,userName,password,sd)\",\n \"def Read(self):\\n try:\\n file_object = self._zip_file.open(self._stream_name, mode='r')\\n except KeyError as exception:\\n raise IOError(\\n 'Unable to open stream with error: {0!s}'.format(exception))\\n\\n try:\\n entry_data = file_object.read(self._TABLE_ENTRY_SIZE)\\n while entry_data:\\n table_entry = self._TABLE_ENTRY.parse(entry_data)\\n\\n self._offsets.append(table_entry.offset)\\n entry_data = file_object.read(self._TABLE_ENTRY_SIZE)\\n\\n except construct.FieldError as exception:\\n raise IOError(\\n 'Unable to read table entry with error: {0!s}'.format(exception))\\n\\n finally:\\n file_object.close()\",\n \"def get_user_messages(user_id):\\n pass \\n # user_message_list = []\\n\\n # for message in sent messages:\",\n \"def process_messages(self, messages):\\n\\n return messages\",\n \"async def read_messages(id_user: int, date: Optional[datetime.datetime] = None):\\n # Check if the date is given or not\\n if date:\\n mycursor.execute(f\\\"\\\"\\\"SELECT * FROM Daily_message \\n WHERE id_user = {id_user}\\n AND date_message = '{date}'\\\"\\\"\\\")\\n else:\\n mycursor.execute(f\\\"\\\"\\\"SELECT * FROM Daily_message \\n WHERE id_user = {id_user}\\\"\\\"\\\")\\n return mycursor.fetchall()\",\n \"def messages(\\n self,\\n amount: int = 100,\\n headers: Optional[Mapping[str, str]] = None,\\n **parameters: str,\\n ) -> Iterable[Message]:\\n # We request this many messages at once\\n message_bucket_size = 100\\n offset = 0\\n return (\\n Message.from_xml(region=self.name, node=node)\\n for node in self._messages_root(\\n headers=headers,\\n limit=str(max(message_bucket_size, amount)),\\n # offset=str(offset),\\n **parameters,\\n )\\n )\",\n \"def get_messages(self, max_messages):\\n raw = self.redis_client.lrange(self.message_list, 0, max_messages)\\n messages = (m for m in raw if m != b\\\"null\\\")\\n messages = (m.decode(\\\"utf-8\\\") for m in messages)\\n yield from map(json.loads, messages)\",\n \"def to_event_stream(self, event_stream):\\n while self.reading_log:\\n event = self.read_event()\\n if event is not None:\\n event_stream.append(event)\",\n \"def create_message_table(self):\\n sql = (\\\"CREATE TABLE IF NOT EXISTS message_log \\\"\\n \\\"(id INT NOT NULL AUTO_INCREMENT PRIMARY KEY, \\\"\\n \\\"timestamp TIMESTAMP, \\\"\\n \\\"message VARCHAR(1024), \\\"\\n \\\"email INT(1), \\\"\\n \\\"tweet INT(1), \\\"\\n \\\"status INT(1))\\\")\\n cur = self.cursor()\\n try:\\n cur.execute(sql)\\n except sqlc.Error as e:\\n print (\\\"Error #{0}: {1}\\\\nCouldn't insert\\\\nsql={2}\\\"\\n .format(e.errno, e.msg, sql))\\n except Exception as e:\\n print (\\\"Error: {0}\\\\nCouldn't insert\\\\nsql={1}\\\"\\n .format(e.message, sql))\\n finally:\\n self.close()\",\n \"def message_mock():\\n from unittest import mock\\n from sqlalchemy import Column\\n from rucio.common.utils import generate_uuid\\n from rucio.db.sqla.models import String, PrimaryKeyConstraint, CheckConstraint, Text, Index, GUID\\n\\n InMemoryMessage = __create_in_memory_db_table(\\n 'message_' + generate_uuid(),\\n Column('id', GUID(), default=generate_uuid),\\n Column('event_type', String(256)),\\n Column('payload', String(4000)),\\n Column('payload_nolimit', Text),\\n Column('services', String(256)),\\n table_args=(PrimaryKeyConstraint('id', name='MESSAGES_ID_PK'),\\n CheckConstraint('EVENT_TYPE IS NOT NULL', name='MESSAGES_EVENT_TYPE_NN'),\\n CheckConstraint('PAYLOAD IS NOT NULL', name='MESSAGES_PAYLOAD_NN'),\\n Index('MESSAGES_SERVICES_IDX', 'services', 'event_type'))\\n )\\n\\n with mock.patch('rucio.core.message.Message', new=InMemoryMessage):\\n yield\",\n \"def create_message_queue_table(self):\\n app_process = sqlite3.connect('app_process::memory:', check_same_thread=False)\\n app_process_cursor = app_process.cursor()\\n app_process_cursor.execute(\\\"SELECT count(name) FROM sqlite_master WHERE type='table' AND name='message_queue'\\\")\\n if app_process_cursor.fetchone()[0]==1:\\n return\\n app_process_cursor.execute(\\\"\\\"\\\"\\n CREATE TABLE message_queue (\\n tstamp real,\\n request text,\\n dest_ip text,\\n dest_port integer,\\n next_tstamp real\\n )\\n \\\"\\\"\\\")\\n app_process.commit()\\n app_process.close()\",\n \"async def messages(self, ctx):\\n\\n\\t\\tawait self.message_leaderboard(ctx, \\\"messages\\\")\",\n \"def get_messages(self, t0, t1, nmax=100, srcid=None):\\n if not (nmax < 10000): nmax = 10000\\n if srcid is None:\\n self.read_curs.execute(\\\"SELECT time,readout_id,msg FROM textlog WHERE time >= ? AND time <= ? ORDER BY time DESC LIMIT ?\\\", (t0, t1, nmax))\\n else:\\n self.read_curs.execute(\\\"SELECT time,readout_id,msg FROM textlog WHERE time >= ? AND time <= ? AND readout_id=? ORDER BY time DESC LIMIT ?\\\", (t0, t1, srcid, nmax))\\n return self.read_curs.fetchall()\",\n \"def get_message():\\r\\n conn = None\\r\\n try:\\r\\n params = config()\\r\\n conn = psycopg2.connect(**params)\\r\\n cur = conn.cursor()\\r\\n cur.execute(\\\"SELECT user_id, user_message FROM messages ORDER BY user_message\\\")\\r\\n print(\\\"Number of messages: \\\", cur.rowcount)\\r\\n row = cur.fetchone()\\r\\n\\r\\n while row is not None:\\r\\n print(row)\\r\\n row = cur.fetchone()\\r\\n\\r\\n cur.close()\\r\\n except (Exception, psycopg2.DatabaseError) as error:\\r\\n print(error)\\r\\n finally:\\r\\n if conn is not None:\\r\\n conn.close()\",\n \"def get_subscriber_row(self, stream_session_info):\\n\\n uptime = \\\"unknown\\\"\\n last_msg_time = \\\"unknown\\\"\\n if (\\n stream_session_info.uptime is not None\\n and stream_session_info.last_msg_sent_time is not None\\n ):\\n uptime_str = str(\\n datetime.timedelta(milliseconds=stream_session_info.uptime)\\n )\\n last_msg_time_str = convertTime(stream_session_info.last_msg_sent_time)\\n uptime = uptime_str.split(\\\".\\\")[0]\\n last_msg_time = last_msg_time_str\\n\\n row = [\\n stream_session_info.subscriber_id,\\n uptime,\\n stream_session_info.total_streamed_msgs,\\n last_msg_time,\\n ]\\n return row\",\n \"def stream_for_actor(self, actor):\\n return self.filter(\\n actor_content_type = ContentType.objects.get_for_model(actor),\\n actor_object_id = actor.pk,\\n ).order_by('-timestamp')\",\n \"def _get_message_groups(\\n self, messages: Iterator[AirbyteMessage], schema_inferrer: SchemaInferrer, limit: int\\n ) -> Iterable[Union[StreamReadPages, AirbyteLogMessage]]:\\n records_count = 0\\n at_least_one_page_in_group = False\\n current_page_records = []\\n current_slice_pages = []\\n current_page_request: Optional[HttpRequest] = None\\n current_page_response: Optional[HttpResponse] = None\\n\\n while records_count < limit and (message := next(messages, None)):\\n if self._need_to_close_page(at_least_one_page_in_group, message):\\n self._close_page(current_page_request, current_page_response, current_slice_pages, current_page_records)\\n current_page_request = None\\n current_page_response = None\\n\\n if at_least_one_page_in_group and message.type == Type.LOG and message.log.message.startswith(\\\"slice:\\\"):\\n yield StreamReadSlices(pages=current_slice_pages)\\n current_slice_pages = []\\n at_least_one_page_in_group = False\\n elif message.type == Type.LOG and message.log.message.startswith(\\\"request:\\\"):\\n if not at_least_one_page_in_group:\\n at_least_one_page_in_group = True\\n current_page_request = self._create_request_from_log_message(message.log)\\n elif message.type == Type.LOG and message.log.message.startswith(\\\"response:\\\"):\\n current_page_response = self._create_response_from_log_message(message.log)\\n elif message.type == Type.LOG:\\n yield message.log\\n elif message.type == Type.RECORD:\\n current_page_records.append(message.record.data)\\n records_count += 1\\n schema_inferrer.accumulate(message.record)\\n else:\\n self._close_page(current_page_request, current_page_response, current_slice_pages, current_page_records)\\n yield StreamReadSlices(pages=current_slice_pages)\",\n \"def load_stream(self, stream):\\n import pyarrow as pa\\n\\n dataframes_in_group = None\\n\\n while dataframes_in_group is None or dataframes_in_group > 0:\\n dataframes_in_group = read_int(stream)\\n\\n if dataframes_in_group == 2:\\n batch1 = [batch for batch in ArrowStreamSerializer.load_stream(self, stream)]\\n batch2 = [batch for batch in ArrowStreamSerializer.load_stream(self, stream)]\\n yield (\\n [self.arrow_to_pandas(c) for c in pa.Table.from_batches(batch1).itercolumns()],\\n [self.arrow_to_pandas(c) for c in pa.Table.from_batches(batch2).itercolumns()],\\n )\\n\\n elif dataframes_in_group != 0:\\n raise ValueError(\\n \\\"Invalid number of pandas.DataFrames in group {0}\\\".format(dataframes_in_group)\\n )\",\n \"def send_streaming_message(self, data):\\n header, data = format_msg(data)\\n self.server_socket_streaming.sendto(header,\\n self.client_streaming_address)\\n self.server_socket_streaming.sendto(data,\\n self.client_streaming_address)\",\n \"def mbox_reader(stream):\\n data = stream.read()\\n text = data.decode(encoding=\\\"utf-8\\\", errors=\\\"replace\\\")\\n return mailbox.mboxMessage(text)\",\n \"def handle_stream_client(self, event):\\n try:\\n while True:\\n client_req = self.receive_streaming_msg()\\n self.choose_action(client_req[ZERO], client_req[ONE:], event)\\n except socket.error as e:\\n print('stream', e)\",\n \"def retrieve(self) -> Iterator[SQSMessage]:\\n while True:\\n try:\\n sqs = SQSClientFactory(boto3).from_env()\\n\\n res = sqs.receive_message(\\n QueueUrl=self.queue_url,\\n WaitTimeSeconds=3,\\n MaxNumberOfMessages=10,\\n )\\n\\n messages = res.get(\\\"Messages\\\", [])\\n if not messages:\\n LOGGER.info(\\\"queue was empty\\\")\\n\\n s3_events = [SQSMessage(msg) for msg in messages]\\n for sqs_message in s3_events:\\n yield sqs_message\\n\\n sqs.delete_message(\\n QueueUrl=self.queue_url,\\n ReceiptHandle=sqs_message.receipt_handle,\\n )\\n\\n except Exception as e:\\n LOGGER.error(traceback.format_exc())\\n time.sleep(2)\",\n \"def get_all_msgs(self):\\n data = self.database.select(self.tname)\\n msgs = []\\n for item in data:\\n msgs.append((item[0], self.data_to_msg(item)))\\n return msgs\",\n \"def send_to_aws_time_stream(stats, config):\\n logging.info('Sending stats to Timestream (database=%s)', config['timestream_database'])\\n\\n region_config = Config(\\n region_name=config['timestream_aws_region']\\n )\\n\\n ts_client = boto3.client(\\n 'timestream-write',\\n aws_access_key_id=config['timestream_aws_access_key_id'],\\n aws_secret_access_key=config['timestream_aws_secret_access_key'],\\n config=region_config\\n )\\n\\n try:\\n # Attempt to validate connection to database and table\\n # Error out and return if not able to access / connection isn't valid\\n database = ts_client.describe_database(\\n DatabaseName=config['timestream_database']\\n )\\n logging.debug(\\\"Database details = %s\\\" % database)\\n\\n table = ts_client.describe_table(\\n DatabaseName=config['timestream_database'],\\n TableName=config['timestream_table']\\n )\\n logging.debug(\\\"Table details = %s\\\" % table)\\n except Exception as err:\\n logging.error(err)\\n return\\n\\n current_time = time.time_ns()\\n logging.debug(\\\"Converting to timestream - %s\\\" % stats)\\n\\n downstream_common_attributes = {\\n 'Dimensions': [{'Name': 'measurement', 'Value': 'downstream_statistics'}],\\n 'Time': str(current_time),\\n 'TimeUnit': 'NANOSECONDS'\\n }\\n downstream_records = []\\n for stats_down in stats['downstream']:\\n for key in stats_down:\\n if key == 'channel_id':\\n continue\\n\\n downstream_records.append({\\n 'Dimensions': [\\n {'Name': 'channel_id', 'Value': str(stats_down['channel_id'])},\\n {'Name': 'group', 'Value': 'downstream_statistics'}\\n ],\\n 'MeasureName': key,\\n 'MeasureValue': str(stats_down[key]),\\n 'MeasureValueType': 'DOUBLE' if isinstance(stats_down[key], float) else 'BIGINT'\\n })\\n\\n try:\\n logging.debug(\\\"Writing common attributes: %s\\\" % downstream_common_attributes)\\n logging.debug(\\\"Writing records: %s\\\" % downstream_records)\\n result = ts_client.write_records(DatabaseName=config['timestream_database'],\\n TableName=config['timestream_table'], Records=downstream_records,\\n CommonAttributes=downstream_common_attributes)\\n logging.info(\\\"Timestream response = %s\\\" % result)\\n logging.info(\\\"Wrote %s records to TimeStream\\\" % len(downstream_records))\\n except (ts_client.exceptions.RejectedRecordsException, Exception) as err:\\n logging.error(err)\\n\\n upstream_common_attributes = {\\n 'Dimensions': [{'Name': 'measurement', 'Value': 'upstream_statistics'}],\\n 'Time': str(current_time),\\n 'TimeUnit': 'NANOSECONDS'\\n }\\n upstream_records = []\\n for stats_up in stats['upstream']:\\n for key in stats_up:\\n if key == 'channel_id':\\n continue\\n\\n upstream_records.append({\\n 'Dimensions': [\\n {'Name': 'channel_id', 'Value': str(stats_up['channel_id'])},\\n {'Name': 'group', 'Value': 'upstream_statistics'}\\n ],\\n 'MeasureName': key,\\n 'MeasureValue': str(stats_up[key]),\\n 'MeasureValueType': 'DOUBLE' if isinstance(stats_up[key], float) else 'BIGINT'\\n })\\n\\n try:\\n logging.debug(\\\"Writing common attributes: %s\\\" % upstream_common_attributes)\\n logging.debug(\\\"Writing records: %s\\\" % upstream_records)\\n result = ts_client.write_records(DatabaseName=config['timestream_database'],\\n TableName=config['timestream_table'], Records=upstream_records,\\n CommonAttributes=upstream_common_attributes)\\n logging.info(\\\"Timestream response = %s\\\" % result)\\n logging.info(\\\"Wrote %s records to TimeStream\\\" % len(upstream_records))\\n except (ts_client.exceptions.RejectedRecordsException, Exception) as err:\\n logging.error(err)\\n return\\n\\n logging.info('Successfully wrote data to Timestream')\",\n \"def emit(self, message):\\n # handle vaping data that arrives in a list\\n if isinstance(message.get(\\\"data\\\"), list):\\n for row in message.get(\\\"data\\\"):\\n\\n\\n # format filename from data\\n filename = self.format_filename(message, row)\\n\\n # create database file if it does not exist yet\\n if not os.path.exists(filename):\\n self.create(filename)\\n\\n # update database\\n self.log.debug(\\\"storing time:%d, %s:%s in %s\\\" % (\\n message.get(\\\"ts\\\"), self.field, row.get(self.field, \\\"-\\\"), filename))\\n self.update(filename, message.get(\\\"ts\\\"), row.get(self.field))\",\n \"def create_stream_table_ui(\\n streams, true_state=False, time_point=0, orient=\\\"columns\\\", precision=5\\n):\\n\\n # Variable Types:\\n class VariableTypes:\\n UNFIXED = \\\"unfixed\\\"\\n FIXED = \\\"fixed\\\"\\n PARAMETER = \\\"parameter\\\"\\n EXPRESSION = \\\"expression\\\"\\n\\n stream_attributes = OrderedDict()\\n stream_states = stream_states_dict(streams=streams, time_point=time_point)\\n full_keys = [] # List of all rows in dataframe to fill in missing data\\n\\n stream_attributes[\\\"Units\\\"] = {}\\n\\n for key, sb in stream_states.items():\\n stream_attributes[key] = {}\\n if true_state:\\n disp_dict = sb.define_state_vars()\\n else:\\n disp_dict = sb.define_display_vars()\\n for k in disp_dict:\\n for row, i in enumerate(disp_dict[k]):\\n stream_key = k if i is None else f\\\"{k} {i}\\\"\\n\\n # Identifying value's variable type\\n var_type = None\\n if isinstance(disp_dict[k][i], (_GeneralVarData, Var)):\\n if disp_dict[k][i].fixed:\\n var_type = VariableTypes.FIXED\\n else:\\n var_type = VariableTypes.UNFIXED\\n elif isinstance(disp_dict[k][i], Param):\\n var_type = VariableTypes.PARAMETER\\n elif isinstance(disp_dict[k][i], Expression):\\n var_type = VariableTypes.EXPRESSION\\n\\n quant = report_quantity(disp_dict[k][i])\\n stream_attributes[key][stream_key] = (\\n round(quant.m, precision),\\n var_type,\\n )\\n if row == 0 or stream_key not in stream_attributes[\\\"Units\\\"]:\\n stream_attributes[\\\"Units\\\"][stream_key] = quant.u\\n\\n if stream_key not in full_keys:\\n full_keys.append(stream_key)\\n\\n # Check for missing rows in any stream, and fill with \\\"-\\\" if needed\\n for k, v in stream_attributes.items():\\n for r in full_keys:\\n if r not in v.keys():\\n # Missing row, fill with placeholder\\n v[r] = \\\"-\\\"\\n\\n return DataFrame.from_dict(stream_attributes, orient=orient)\",\n \"def msgs(self, schema: str, last_msg_id, block: int = None):\\n raise NotImplementedError\",\n \"async def process(self, msg):\\n # logger.debug(\\\"msg:\\\", msg, caller=self)\\n if not isinstance(msg, dict):\\n return\\n if msg.get(\\\"error\\\"):\\n logger.error(\\\"msg:\\\", msg, caller=self)\\n return\\n\\n table = msg.get(\\\"table\\\")\\n if table == \\\"orderBook10\\\":\\n await self.process_orderbook(msg[\\\"data\\\"])\\n elif table == \\\"trade\\\":\\n await self.process_trade(msg[\\\"data\\\"])\\n elif table == \\\"tradeBin1m\\\":\\n await self.process_kline(msg[\\\"data\\\"])\",\n \"def request_messages(self):\\n # we fetch messages from all rooms at the same time, we will route them at writing time\\n base_query = (\\n \\\"SELECT e.received_ts, j.json \\\"\\n \\\"FROM events AS e \\\"\\n \\\"INNER JOIN event_json AS j \\\"\\n \\\"USING (event_id) \\\"\\n \\\"WHERE e.room_id IN %s \\\"\\n \\\"AND e.received_ts>%s \\\"\\n \\\"AND e.type='m.room.message' \\\"\\n \\\"ORDER BY e.received_ts;\\\"\\n )\\n\\n self.read_last_ts_written()\\n\\n try:\\n logging.info(\\\"Connecting to database ...\\\")\\n with psycopg2.connect(**self.db_config) as conn:\\n logging.info(\\\"Connected to database.\\\")\\n with conn.cursor() as cur:\\n cur.execute(\\n base_query, (tuple(self.rooms.keys()), self.last_ts_written)\\n )\\n\\n for row in cur:\\n # there are two fields per row : timestamp at reception, and json data\\n line = self.process_message_row(row)\\n\\n # we get the room nickname in the config at the room_id key\\n room_name = self.rooms[line[\\\"room_id\\\"]]\\n file_path = self.ts_to_filepath(\\n timestamp=line[\\\"ts\\\"], room_name=room_name\\n )\\n\\n if self.append_line(file_path, json.dumps(line)):\\n logging.info(\\n \\\"Message with timestamp {} written to {}\\\".format(\\n line[\\\"ts\\\"], file_path\\n )\\n )\\n self.last_ts_written = line[\\\"ts\\\"]\\n else:\\n logging.error(\\n \\\"We couldn't write message {}, we will exit.\\\".format(\\n line[\\\"ts\\\"]\\n )\\n )\\n return False\\n\\n self.write_last_ts_written()\\n\\n logging.info(\\\"Disconnecting from database ...\\\")\\n conn.close()\\n logging.info(\\\"Disconnected from database.\\\")\\n return True\\n\\n except psycopg2.OperationalError as e:\\n logging.error(\\n 'Could not connect to database : \\\"{}\\\"'.format(str(e).replace(\\\"\\\\n\\\", \\\"\\\"))\\n )\\n\\n return False\\n\\n return True\",\n \"def _read_stream(self):\\n input_df = self.spark \\\\\\n .readStream \\\\\\n .format(\\\"kafka\\\") \\\\\\n .option(\\\"kafka.bootstrap.servers\\\", \\\"localhost:9092\\\") \\\\\\n .option(\\\"subscribe\\\", \\\"agro\\\") \\\\\\n .option(\\\"startingOffsets\\\", \\\"latest\\\") \\\\\\n .load()\\n\\n return input_df\",\n \"def _messages_list(self, queue):\\n\\n return queue.messages()\",\n \"def get_messages_sent_by(self, nodeid):\\n bucket = self._buckets[nodeid]\\n messages = []\\n\\n while not bucket.empty():\\n messages.append(bucket.get_nowait())\\n\\n return message.MessagesSet(messages)\",\n \"def create_stream_table_dataframe(\\n streams, true_state=False, time_point=0, orient=\\\"columns\\\"\\n):\\n\\n stream_attributes = OrderedDict()\\n stream_states = stream_states_dict(streams=streams, time_point=time_point)\\n full_keys = [] # List of all rows in dataframe to fill in missing data\\n\\n stream_attributes[\\\"Units\\\"] = {}\\n\\n for key, sb in stream_states.items():\\n stream_attributes[key] = {}\\n if true_state:\\n disp_dict = sb.define_state_vars()\\n else:\\n disp_dict = sb.define_display_vars()\\n for k in disp_dict:\\n for row, i in enumerate(disp_dict[k]):\\n stream_key = k if i is None else f\\\"{k} {i}\\\"\\n quant = report_quantity(disp_dict[k][i])\\n stream_attributes[key][stream_key] = quant.m\\n if row == 0 or stream_key not in stream_attributes[\\\"Units\\\"]:\\n stream_attributes[\\\"Units\\\"][stream_key] = quant.u\\n if stream_key not in full_keys:\\n full_keys.append(stream_key)\\n\\n # Check for missing rows in any stream, and fill with \\\"-\\\" if needed\\n for k, v in stream_attributes.items():\\n for r in full_keys:\\n if r not in v.keys():\\n # Missing row, fill with placeholder\\n v[r] = \\\"-\\\"\\n\\n return DataFrame.from_dict(stream_attributes, orient=orient)\",\n \"def copy_table_stream_settings(events: dict, context: dict):\\n if 'SourceTableName' not in events:\\n raise KeyError('Requires SourceTableName')\\n if 'TargetTableName' not in events:\\n raise KeyError('Requires TargetTableName')\\n\\n source_table_name = events['SourceTableName']\\n description = _describe_table(table_name=source_table_name)['Table']\\n stream_enabled = description\\\\\\n .get('StreamSpecification', {})\\\\\\n .get('StreamEnabled', False)\\n if stream_enabled:\\n target_table_name = events['TargetTableName']\\n stream_view_type = description['StreamSpecification']['StreamViewType']\\n settings = {\\n \\\"StreamSpecification\\\": {\\n \\\"StreamEnabled\\\": stream_enabled,\\n \\\"StreamViewType\\\": stream_view_type\\n }\\n }\\n result = _update_table(table_name=target_table_name, **settings)\\n specification = result.get('StreamSpecification', {})\\n return specification\",\n \"def create_stream(self, tag, database, table):\\n try:\\n logger.info(\\\"About to create a firehose stream \\\")\\n self.firehose_client.create_delivery_stream(DeliveryStreamName=self.get_stream_name(tag),\\n ExtendedS3DestinationConfiguration=self.create_s3_dest_config(tag, database, table))\\n except ClientError:\\n logger.info(\\\"The firehose stream has already been created!\\\\n\\\")\",\n \"def fetch_messages(self, label, size, startwith=0):\\n messages = Room.objects.get(label=label).messages.order_by('-created')[startwith:size]\\n messages = MessageSerializers(messages, many=True)\\n return messages.data\",\n \"def messages(self, request, *args, **kwargs):\\n conversation = self.get_object()\\n related = ['user__profile']\\n related2 = ['attachments']\\n messages_qs = conversation.messages.all().select_related(*related).prefetch_related(*related2)\\n self.pagination_class = DateTimePagination\\n page = self.paginate_queryset(messages_qs)\\n\\n # Only keep the messages that were not deleted by this user\\n messages_ids = map(lambda m: m.id, page.object_list)\\n deleted_messages_ids = request.user.deleted_messages.filter(id__in=messages_ids).values_list('id', flat=True)\\n for message in page.object_list:\\n if message.id in deleted_messages_ids:\\n page.object_list.remove(message)\\n\\n serializer = MessageSerializer(page, many=True, context={'request': request})\\n conversation.mark_as_read(request.user)\\n return self.get_paginated_response(serializer.data)\",\n \"def send_data(self, stream_id):\\n send_stream = self.send_streams.get(stream_id)\\n\\n if not send_stream:\\n # window updates trigger sending of data, but can happen after a stream\\n # has been completely sent\\n return\\n\\n if not send_stream.headers_sent:\\n # don't attempt to send any data until the headers have been sent\\n return\\n\\n try:\\n window_size = self.conn.local_flow_control_window(stream_id=stream_id)\\n max_frame_size = self.conn.max_outbound_frame_size\\n\\n for chunk in send_stream.read(window_size, max_frame_size):\\n log.debug(\\\"sending data on stream %s: %s...\\\", stream_id, chunk[:100])\\n\\n self.conn.send_data(stream_id=stream_id, data=chunk)\\n\\n except StreamClosedError:\\n return\\n\\n if send_stream.exhausted:\\n log.debug(\\\"closing exhausted stream, stream %s\\\", stream_id)\\n self.end_stream(stream_id)\",\n \"def text(message):\\n global list_messages\\n room = session.get('room')\\n msg = session.get('name') + ':' + message['msg']\\n list_messages.append(msg)\\n addNewMsg(message,session)\\n print ('size of list_messages ' + str(len(list_messages)) + ', session ' + str(session))\\n emit('message', {'msg': msg}, room=room)\",\n \"def _dispatch_messages(self):\\n while True:\\n select_obj = (yield)\\n if select_obj == self._message_queue.selobj:\\n msg = self._message_queue.get_nowait()\\n if msg is not None:\\n msg_type = msg.get('type', None)\\n if msg_type is not None:\\n msg_handler = self._message_handlers.get(msg_type, None)\\n if msg_handler is not None:\\n msg_handler(msg['data'])\",\n \"def process_messages(self):\\n pass\",\n \"def _streaming_command(self, service, command, transport_timeout_s, read_timeout_s, timeout_s):\\n adb_info = self._open(b'%s:%s' % (service, command), transport_timeout_s, read_timeout_s, timeout_s)\\n\\n for data in self._read_until_close(adb_info):\\n yield data\",\n \"def stream(self, __template_id=\\\"*\\\", __query=None, *, offset=None, read_as=None):\\n raise NotImplementedError\",\n \"def wrap_streaming_content(self, streaming_content):\\n for chunk in streaming_content:\\n yield chunk\",\n \"def handle_recv(self,stream,msgs):\\n pass\",\n \"async def _send_stream_data(\\n self, request: Request, stream_id: int, data: bytes\\n ) -> None:\\n while data:\\n max_flow = await self._wait_for_outgoing_flow(request, stream_id)\\n chunk_size = min(len(data), max_flow)\\n chunk, data = data[:chunk_size], data[chunk_size:]\\n self._h2_state.send_data(stream_id, chunk)\\n await self._write_outgoing_data(request)\",\n \"def load_stream(self, stream):\\n import pyarrow as pa\\n\\n batches = super(ArrowStreamUDFSerializer, self).load_stream(stream)\\n for batch in batches:\\n struct = batch.column(0)\\n yield [pa.RecordBatch.from_arrays(struct.flatten(), schema=pa.schema(struct.type))]\",\n \"def multiple_messages(self, messages):\\n for message in messages:\\n cmd = '{}serverMessage \\\"{}\\\"'.format(self.console, Commands.aquote(message))\\n self.write_command(cmd)\",\n \"def get_messages(self, page=0):\\n endpoint = 'https://outlook.office.com/api/v2.0/me/messages'\\n if page > 0:\\n endpoint = endpoint + '/?%24skip=' + str(page) + '0'\\n\\n log.debug('Getting messages from endpoint: {} with Headers: {}'.format(endpoint, self._headers))\\n\\n r = requests.get(endpoint, headers=self._headers)\\n\\n check_response(r)\\n\\n return Message._json_to_messages(self, r.json())\",\n \"def stream_query(self, commands):\\n # The CLI transport does not support pipelining.\\n if self.transport is pywatchman.CLIProcessTransport:\\n raise NotImplementedError()\\n\\n cmd_buf = deque(command for command in reversed(commands))\\n self._connect()\\n\\n while 1:\\n # Interleave sends and receives to avoid bi-directional communication issues.\\n if cmd_buf:\\n item = cmd_buf.pop()\\n try:\\n self.sendConn.send(item)\\n except pywatchman.SocketTimeout:\\n cmd_buf.append(item)\\n yield\\n\\n try:\\n result = self.recvConn.receive()\\n except pywatchman.SocketTimeout:\\n # Socket timeout - yield runtime context.\\n yield\\n else:\\n if 'error' in result:\\n raise pywatchman.WatchmanError('error from watchman: {}'.format(result['error']))\\n elif self.isUnilateralResponse(result) or 'subscribe' in result:\\n yield result\\n else:\\n yield result\\n break\",\n \"def ProcessMessage(self, status_message, stream):\\n self.object_report_change = False\\n if isinstance(status_message, SeekAheadMessage):\\n self._HandleSeekAheadMessage(status_message, stream)\\n elif isinstance(status_message, ProducerThreadMessage):\\n self._HandleProducerThreadMessage(status_message)\\n elif isinstance(status_message, MetadataMessage):\\n self._HandleMetadataMessage(status_message)\\n elif isinstance(status_message, RetryableErrorMessage):\\n LogRetryableError(status_message)\\n elif isinstance(status_message, PerformanceSummaryMessage):\\n self._HandlePerformanceSummaryMessage(status_message)\\n self.old_progress.append(\\n self._ThroughputInformation(self.objects_finished, status_message.time))\",\n \"def callback(parsed_msg, msg_object):\\n assert msg_object.stream_id == stream_id\\n assert parsed_msg in msg\",\n \"def stream_blocks():\\n # add height\\n query = iroha.blocks_query()\\n ic.sign_query(query, user_private_key)\\n for block in net.send_blocks_stream_query(query):\\n pprint(\\\"The next block arrived: {}\\\".format(MessageToDict(block)), indent=1)\",\n \"def getAllMessages(self):\\n return self.db.getAllMessages()\",\n \"def send_stream_to_kafka(self, df: pd.DataFrame) -> None:\\n for row in df.values.tolist():\\n value = dict(zip(self.get_value_structure(), row))\\n key = dict(zip(self.get_key_structure(), [row[13]]))\\n # key = {\\\"npi\\\": int(row[0])}\\n # key = str(uuid.uuid4())\\n self.producer.producer.produce(topic=self.topic_name, key=key, value=value)\\n logger.info(f\\\"sent event to kafka with key: {key} and value: {value}\\\", class_name=self.__class__.__name__)\",\n \"def listener(messages):\\n for m in messages:\\n chatid = m.chat.id\\n print(str(chatid))\\n if m.content_type == 'text':\\n text = m.text\\n tb.send_message(chatid, text)\",\n \"def show_messages():\\n\\n messages = Message.query.all()\\n # translation_list = [\\\"\\\"]\\n\\n for message in messages:\\n # message.translation gives list of objects. All the translation for the \\n # language. Here assgin it to one trans_text based on user's language\\n # selection. \\n message.translation = Translation.query.filter_by(language=g.user.language, \\n message_id=message.message_id).first()\\n\\n return render_template(\\\"messages.html\\\", messages=messages, user=g.user)\",\n \"def select_all_messages(conn):\\n cur = conn.cursor()\\n cur.execute(\\\"SELECT * FROM LED_MESSAGE\\\")\\n\\n rows = cur.fetchall()\\n\\n all_m = []\\n for row in rows:\\n l_m = { \\n \\\"ts\\\": row[0],\\n \\\"elapsed\\\": float(row[1]), \\n \\\"font\\\": row[2], \\n \\\"type\\\": row[3], \\n \\\"body\\\": row[4], \\n \\\"color\\\": row[5], \\n \\\"behavior\\\": row[6]\\n }\\n all_m.append({ \\\"message\\\":{ \\\"payload\\\": l_m }})\\n\\n return all_m\",\n \"def subscribe_to_stream(client, iterator, seconds_running):\\n end_time = datetime.now() + timedelta(seconds=seconds_running)\\n while True:\\n record_response = client.get_records(ShardIterator=iterator)\\n # Only run for a certain amount of time.\\n # Stop looping if no data returned. This means it's done\\n now = datetime.now()\\n if end_time < now:\\n break\\n else:\\n # yield data to outside calling iterator\\n for record in record_response['Records']:\\n data = record[\\\"Data\\\"].decode(\\\"utf-8\\\")\\n timestamp = record[\\\"ApproximateArrivalTimestamp\\\"]\\n record_id = record[\\\"SequenceNumber\\\"]\\n tweet_record = [record_id, timestamp, data]\\n yield tweet_record\\n # Get next iterator for shard from previous request\\n iterator = record_response['NextShardIterator']\",\n \"def dump_stream(self, iterator, stream):\\n\\n import pandas as pd\\n import pyarrow as pa\\n\\n def construct_state_pdf(state):\\n \\\"\\\"\\\"\\n Construct a pandas DataFrame from the state instance.\\n \\\"\\\"\\\"\\n\\n state_properties = state.json().encode(\\\"utf-8\\\")\\n state_key_row_as_binary = state._keyAsUnsafe\\n if state.exists:\\n state_object = self.pickleSer.dumps(state._value_schema.toInternal(state._value))\\n else:\\n state_object = None\\n state_old_timeout_timestamp = state.oldTimeoutTimestamp\\n\\n state_dict = {\\n \\\"properties\\\": [\\n state_properties,\\n ],\\n \\\"keyRowAsUnsafe\\\": [\\n state_key_row_as_binary,\\n ],\\n \\\"object\\\": [\\n state_object,\\n ],\\n \\\"oldTimeoutTimestamp\\\": [\\n state_old_timeout_timestamp,\\n ],\\n }\\n\\n return pd.DataFrame.from_dict(state_dict)\\n\\n def construct_record_batch(pdfs, pdf_data_cnt, pdf_schema, state_pdfs, state_data_cnt):\\n \\\"\\\"\\\"\\n Construct a new Arrow RecordBatch based on output pandas DataFrames and states. Each\\n one matches to the single struct field for Arrow schema. We also need an extra one to\\n indicate array length for data and state, so the return value of Arrow RecordBatch will\\n have schema with three fields, in `count`, `data`, `state` order.\\n (Readers are expected to access the field via position rather than the name. We do\\n not guarantee the name of the field.)\\n\\n Note that Arrow RecordBatch requires all columns to have all same number of rows,\\n hence this function inserts empty data for count/state/data with less elements to\\n compensate.\\n \\\"\\\"\\\"\\n\\n max_data_cnt = max(1, max(pdf_data_cnt, state_data_cnt))\\n\\n # We only use the first row in the count column, and fill other rows to be the same\\n # value, hoping it is more friendly for compression, in case it is needed.\\n count_dict = {\\n \\\"dataCount\\\": [pdf_data_cnt] * max_data_cnt,\\n \\\"stateCount\\\": [state_data_cnt] * max_data_cnt,\\n }\\n count_pdf = pd.DataFrame.from_dict(count_dict)\\n\\n empty_row_cnt_in_data = max_data_cnt - pdf_data_cnt\\n empty_row_cnt_in_state = max_data_cnt - state_data_cnt\\n\\n empty_rows_pdf = pd.DataFrame(\\n dict.fromkeys(pa.schema(pdf_schema).names),\\n index=[x for x in range(0, empty_row_cnt_in_data)],\\n )\\n empty_rows_state = pd.DataFrame(\\n columns=[\\\"properties\\\", \\\"keyRowAsUnsafe\\\", \\\"object\\\", \\\"oldTimeoutTimestamp\\\"],\\n index=[x for x in range(0, empty_row_cnt_in_state)],\\n )\\n\\n pdfs.append(empty_rows_pdf)\\n state_pdfs.append(empty_rows_state)\\n\\n merged_pdf = pd.concat(pdfs, ignore_index=True)\\n merged_state_pdf = pd.concat(state_pdfs, ignore_index=True)\\n\\n return self._create_batch(\\n [\\n (count_pdf, self.result_count_pdf_arrow_type),\\n (merged_pdf, pdf_schema),\\n (merged_state_pdf, self.result_state_pdf_arrow_type),\\n ]\\n )\\n\\n def serialize_batches():\\n \\\"\\\"\\\"\\n Read through an iterator of (iterator of pandas DataFrame, state), and serialize them\\n to Arrow RecordBatches.\\n\\n This function does batching on constructing the Arrow RecordBatch; a batch will be\\n serialized to the Arrow RecordBatch when the total number of records exceeds the\\n configured threshold.\\n \\\"\\\"\\\"\\n # a set of variables for the state of current batch which will be converted to Arrow\\n # RecordBatch.\\n pdfs = []\\n state_pdfs = []\\n pdf_data_cnt = 0\\n state_data_cnt = 0\\n\\n return_schema = None\\n\\n for data in iterator:\\n # data represents the result of each call of user function\\n packaged_result = data[0]\\n\\n # There are two results from the call of user function:\\n # 1) iterator of pandas DataFrame (output)\\n # 2) updated state instance\\n pdf_iter = packaged_result[0][0]\\n state = packaged_result[0][1]\\n\\n # This is static and won't change across batches.\\n return_schema = packaged_result[1]\\n\\n for pdf in pdf_iter:\\n # We ignore empty pandas DataFrame.\\n if len(pdf) > 0:\\n pdf_data_cnt += len(pdf)\\n pdfs.append(pdf)\\n\\n # If the total number of records in current batch exceeds the configured\\n # threshold, time to construct the Arrow RecordBatch from the batch.\\n if pdf_data_cnt > self.arrow_max_records_per_batch:\\n batch = construct_record_batch(\\n pdfs, pdf_data_cnt, return_schema, state_pdfs, state_data_cnt\\n )\\n\\n # Reset the variables to start with new batch for further data.\\n pdfs = []\\n state_pdfs = []\\n pdf_data_cnt = 0\\n state_data_cnt = 0\\n\\n yield batch\\n\\n # This has to be performed 'after' evaluating all elements in iterator, so that\\n # the user function has been completed and the state is guaranteed to be updated.\\n state_pdf = construct_state_pdf(state)\\n\\n state_pdfs.append(state_pdf)\\n state_data_cnt += 1\\n\\n # processed all output, but current batch may not be flushed yet.\\n if pdf_data_cnt > 0 or state_data_cnt > 0:\\n batch = construct_record_batch(\\n pdfs, pdf_data_cnt, return_schema, state_pdfs, state_data_cnt\\n )\\n\\n yield batch\\n\\n def init_stream_yield_batches(batches):\\n \\\"\\\"\\\"\\n This function helps to ensure the requirement for Pandas UDFs - Pandas UDFs require a\\n START_ARROW_STREAM before the Arrow stream is sent.\\n\\n START_ARROW_STREAM should be sent after creating the first record batch so in case of\\n an error, it can be sent back to the JVM before the Arrow stream starts.\\n \\\"\\\"\\\"\\n should_write_start_length = True\\n\\n for batch in batches:\\n if should_write_start_length:\\n write_int(SpecialLengths.START_ARROW_STREAM, stream)\\n should_write_start_length = False\\n\\n yield batch\\n\\n batches_to_write = init_stream_yield_batches(serialize_batches())\\n\\n return ArrowStreamSerializer.dump_stream(self, batches_to_write, stream)\",\n \"def give_messages(self, messages, verbose=False, cache=False, tunnel=None, source_sock_addr=None):\\n assert isinstance(messages, list)\\n assert all(isinstance(message, Message.Implementation) for message in messages)\\n assert isinstance(verbose, bool)\\n assert isinstance(cache, bool)\\n assert tunnel is None, \\\"TUNNEL property is set using init_socket(...)\\\"\\n assert source_sock_addr is None or isinstance(source_sock_addr, tuple), type(source_sock_addr)\\n packets = [message.packet if message.packet else self.encode_message(message) for message in messages]\\n if verbose:\\n logger.debug(\\\"giving %d messages (%d bytes)\\\", len(messages), sum(len(packet) for packet in packets))\\n self.give_packets(packets, verbose=verbose, cache=cache, tunnel=tunnel, source_sock_addr=source_sock_addr)\\n return messages\",\n \"def messages(self):\\n return itertools.chain.from_iterable(\\n mset.messages\\n for topic, partitions in iteritems(self.msets)\\n for partition_id, mset in iteritems(partitions)\\n )\",\n \"def stream_table_dataframe_to_string(stream_table, **kwargs):\\n # Set some default values for keyword arguments\\n na_rep = kwargs.pop(\\\"na_rep\\\", \\\"-\\\")\\n justify = kwargs.pop(\\\"justify\\\", \\\"center\\\")\\n float_format = kwargs.pop(\\\"float_format\\\", lambda x: \\\"{:#.5g}\\\".format(x))\\n\\n # Print stream table\\n return stream_table.to_string(\\n na_rep=na_rep, justify=justify, float_format=float_format, **kwargs\\n )\",\n \"def ProcessMessage(self, status_message, stream):\\n self.object_report_change = False\\n if isinstance(status_message, ProducerThreadMessage):\\n # ProducerThread info.\\n self._HandleProducerThreadMessage(status_message)\\n\\n elif isinstance(status_message, SeekAheadMessage):\\n # SeekAheadThread info.\\n self._HandleSeekAheadMessage(status_message, stream)\\n\\n elif isinstance(status_message, FileMessage):\\n if self._IsFile(status_message):\\n # File info.\\n self._HandleFileDescription(status_message)\\n else:\\n # Component info.\\n self._HandleComponentDescription(status_message)\\n LogPerformanceSummaryParams(file_message=status_message)\\n\\n elif isinstance(status_message, ProgressMessage):\\n # Progress info.\\n self._HandleProgressMessage(status_message)\\n\\n elif isinstance(status_message, RetryableErrorMessage):\\n LogRetryableError(status_message)\\n\\n elif isinstance(status_message, PerformanceSummaryMessage):\\n self._HandlePerformanceSummaryMessage(status_message)\\n\\n self.old_progress.append(\\n self._ThroughputInformation(self.new_progress, status_message.time))\",\n \"def get_public_messages(self):\\n messages = []\\n for message in self.messages:\\n if message.message_id != None:\\n messages.append(message)\\n return messages\",\n \"def data_received(self, event):\\n stream_id = event.stream_id\\n\\n log.debug(\\\"data received on stream %s: %s...\\\", stream_id, event.data[:100])\\n receive_stream = self.receive_streams.get(stream_id)\\n if receive_stream is None:\\n try:\\n self.conn.reset_stream(stream_id, error_code=ErrorCodes.PROTOCOL_ERROR)\\n except StreamClosedError:\\n pass\\n return\\n\\n receive_stream.write(event.data)\\n self.conn.acknowledge_received_data(event.flow_controlled_length, stream_id)\",\n \"def show_message(id):\\n session = Session()\\n message = session.query(Message).filter_by(id=id).one()\\n msg_dct = create_message(message)\\n msg_dct[\\\"size\\\"] = message.size\\n msg_dct[\\\"recipients\\\"] = create_recipients(message.recipients)\\n return msg_dct\",\n \"def display_received_table(self, num_disp, old):\\n caller = self.caller\\n msgtable = PrettyTable(\\n [\\\"{wMsg #\\\", \\\"{wSender\\\", \\\"{wIC Date\\\", \\\"{wOOC Date\\\", \\\"{wSave\\\"]\\n )\\n mess_num = 1\\n old = old[:num_disp]\\n for mess in old:\\n try:\\n name = caller.messages.get_sender_name(mess)\\n except AttributeError:\\n mess = reload_model_as_proxy(mess)\\n print(\\n \\\"Error: Had to reload Msg ID %s as Messenger when displaying received table.\\\"\\n % mess.id\\n )\\n name = caller.messages.get_sender_name(mess)\\n date = caller.messages.get_date_from_header(mess) or \\\"Unknown\\\"\\n ooc_date = mess.db_date_created.strftime(\\\"%x\\\")\\n saved = \\\"{w*{n\\\" if mess.preserved else \\\"\\\"\\n msgtable.add_row([mess_num, name, date, ooc_date, saved])\\n mess_num += 1\\n self.msg(msgtable)\",\n \"def publish_list(self, messages: list) -> None:\",\n \"def publish_list(self, messages: list) -> None:\",\n \"def store_in_sql(cache, db_handler, TABLE_NAME):\\r\\n if len(cache) == 0 and len(cache[0]) == 0:\\r\\n return\\r\\n\\r\\n # create new table for new streaming event\\r\\n if TABLE_NAME[0] == '':\\r\\n TABLE_NAME[0] = db_handler.create_table(cache[0])\\r\\n \\r\\n # write message to database\\r\\n for message in cache:\\r\\n db_handler.insert_entry(message)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.5896682","0.5609692","0.56041276","0.5388515","0.53177005","0.52457964","0.5238697","0.52366567","0.52348894","0.5195175","0.5176002","0.5151693","0.51319724","0.51315767","0.5099497","0.5045646","0.50385904","0.50096095","0.5003209","0.49966025","0.4938461","0.49175888","0.49162292","0.49093398","0.49065822","0.49057323","0.49014217","0.48966283","0.4886198","0.488072","0.4875962","0.48759413","0.48722","0.48626813","0.4860965","0.48591292","0.4835408","0.48313496","0.48311883","0.48259866","0.48224056","0.48103836","0.48088568","0.47870794","0.47834334","0.47829995","0.4775143","0.47683027","0.475256","0.47373852","0.47272885","0.47238493","0.47210863","0.47160938","0.47157773","0.46991336","0.4680729","0.46554473","0.4654154","0.4650348","0.4647392","0.46460316","0.46459576","0.46459565","0.4644086","0.46418118","0.46411806","0.46382475","0.46375394","0.46353406","0.4634726","0.4634369","0.46295562","0.46285912","0.46224183","0.461861","0.46147427","0.46145996","0.4613557","0.46105272","0.4610269","0.46063605","0.46008047","0.45989987","0.45977488","0.4595958","0.45739266","0.45729154","0.45725873","0.45641056","0.4561263","0.45578587","0.4554287","0.45538267","0.45476583","0.45475885","0.45434162","0.45434162","0.45378074"],"string":"[\n \"0.5896682\",\n \"0.5609692\",\n \"0.56041276\",\n \"0.5388515\",\n \"0.53177005\",\n \"0.52457964\",\n \"0.5238697\",\n \"0.52366567\",\n \"0.52348894\",\n \"0.5195175\",\n \"0.5176002\",\n \"0.5151693\",\n \"0.51319724\",\n \"0.51315767\",\n \"0.5099497\",\n \"0.5045646\",\n \"0.50385904\",\n \"0.50096095\",\n \"0.5003209\",\n \"0.49966025\",\n \"0.4938461\",\n \"0.49175888\",\n \"0.49162292\",\n \"0.49093398\",\n \"0.49065822\",\n \"0.49057323\",\n \"0.49014217\",\n \"0.48966283\",\n \"0.4886198\",\n \"0.488072\",\n \"0.4875962\",\n \"0.48759413\",\n \"0.48722\",\n \"0.48626813\",\n \"0.4860965\",\n \"0.48591292\",\n \"0.4835408\",\n \"0.48313496\",\n \"0.48311883\",\n \"0.48259866\",\n \"0.48224056\",\n \"0.48103836\",\n \"0.48088568\",\n \"0.47870794\",\n \"0.47834334\",\n \"0.47829995\",\n \"0.4775143\",\n \"0.47683027\",\n \"0.475256\",\n \"0.47373852\",\n \"0.47272885\",\n \"0.47238493\",\n \"0.47210863\",\n \"0.47160938\",\n \"0.47157773\",\n \"0.46991336\",\n \"0.4680729\",\n \"0.46554473\",\n \"0.4654154\",\n \"0.4650348\",\n \"0.4647392\",\n \"0.46460316\",\n \"0.46459576\",\n \"0.46459565\",\n \"0.4644086\",\n \"0.46418118\",\n \"0.46411806\",\n \"0.46382475\",\n \"0.46375394\",\n \"0.46353406\",\n \"0.4634726\",\n \"0.4634369\",\n \"0.46295562\",\n \"0.46285912\",\n \"0.46224183\",\n \"0.461861\",\n \"0.46147427\",\n \"0.46145996\",\n \"0.4613557\",\n \"0.46105272\",\n \"0.4610269\",\n \"0.46063605\",\n \"0.46008047\",\n \"0.45989987\",\n \"0.45977488\",\n \"0.4595958\",\n \"0.45739266\",\n \"0.45729154\",\n \"0.45725873\",\n \"0.45641056\",\n \"0.4561263\",\n \"0.45578587\",\n \"0.4554287\",\n \"0.45538267\",\n \"0.45476583\",\n \"0.45475885\",\n \"0.45434162\",\n \"0.45434162\",\n \"0.45378074\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.47767812"},"document_rank":{"kind":"string","value":"47"}}},{"rowIdx":15597,"cells":{"query":{"kind":"string","value":"MessageAck acks messages for a table."},"document":{"kind":"string","value":"def MessageAck(self, request, context):\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\n context.set_details('Method not implemented!')\n raise NotImplementedError('Method not implemented!')"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def MessageAck(self, request, context):\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)","def MessageAck(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\n raise NotImplementedError()","def ack(self, tup_id):\n pass","async def ack(self, offset: int):","def ack(self, task_id):\n raise NotImplementedError","def acked(err, msg):\n if err is not None:\n print(\"Failed to deliver message: {}\".format(err))\n else:\n print(\"Produced record to topic {} partition [{}] @ offset {}\"\n .format(msg.topic(), msg.partition(), msg.offset()))","def ack(self):\n self.consumer.ack(self)","async def acknowledge(self, *event_messages, bus_client: \"BusClient\"):\n pass","def ack(self, tube, task_id):\n cmd = tube.cmd('ack')\n args = (task_id,)\n\n return self.tnt.call(cmd, args)","def ack(self):\n content = self._content \n log('content:'+content)\n self.__tcp_send(content)","def ackable(self, host, service, state, message):\n\n if self.act_ct == (self.list_size - 1) and self.has_rolled == False:\n self.has_rolled = True\n self.act_ct = 0\n elif self.act_ct == 0 and self.has_rolled == False:\n self.has_rolled = True\n self.act_ct = 0\n elif self.act_ct == 0 and self.has_rolled == True:\n self.act_ct = (self.act_ct + 1) % self.list_size\n elif self.act_ct > 0 or self.has_rolled == True:\n self.has_rolled = False\n self.act_ct = (self.act_ct + 1) % self.list_size\n if state == \"UNKNOWN\" or state == \"WARNING\" or state == \"CRITICAL\" or state == \"UP\" or state == \"OK\" or state == \"DOWN\" or state == \"UNREACHABLE\":\n self.ackable_list[self.act_ct] = {'host':host, 'service': service, 'state':state, 'message':message}\n #return(self.act_ct + self.list_offset)","def acknowledge(self, message: Message[ValueType]) -> Message[ValueType]:","def ackId(tupid):\n sendMsgToParent({\"command\": \"ack\", \"id\": tupid})","def on_nack(self, message: PubsubMessage, ack: Callable[[], None]):\n pass","def _send_ack(self):\n ack_packet = packet.Packet.from_data(\n 0,\n self.dest_addr,\n self.own_addr,\n ack=self._next_expected_seqnum\n )\n self._schedule_send_out_of_order(ack_packet)","def recalcAck(self):\n\t\t\n\t\t#if self.ackNo < 0:\n\t\t#\tself.ackNo = self.rSegs[0].segNo\n\t\t\n\t\t\n\t\twhile True:\n\t\t\t#Find Target segment\n\t\t\ttarget = self.ackNo + 1\n\t\t\tfound = False\n\t\t\tfor p in self.rSegs:\n\t\t\t\tif target == p.segNo:\n\t\t\t\t\tself.ackNo += 1\n\t\t\t\t\tfound = True\n\t\t\t\t\tbreak\n\t\t\t\n\t\t\t#\n\t\t\tif not found:\n\t\t\t\tbreak","def _acknowledge_message(self, app, message):\n self.client.delete_message(\n QueueUrl=self.app.settings['SQS_INBOUND_QUEUE_URL'],\n ReceiptHandle=message['ReceiptHandle'],\n )","def ack_event(self, event_id):\n return self.client.call('Notification_Occurrence_Event', 'acknowledgeNotification', id=event_id)","def acknowledgement(self, message: Message[ValueType]):","def acked(err, msg):\n if err is not None:\n print(\"failed to deliver message: {}\".format(err.str()))\n else:\n print(\"produced to: {} [{}] @ {}\".format(msg.topic(), msg.partition(), msg.offset()))","def acknowledge_many(self, messages: Iterable[Message[ValueType]]) -> None:\n for message in messages: # pragma: no cover\n self.acknowledge(message)","async def ack_event(self, envelope: Envelope, multiple: bool = False) -> None:\n await self.channel.basic_client_ack(\n delivery_tag=envelope.delivery_tag, multiple=multiple\n )","def acknowledgePacket(self, packet: Rudp.Packet):\n self.acknowledge(packet.seq)","def handle_ack(self, msg):\r\n if msg[0] == 'post':\r\n self.handle_post_frame(msg)\r\n elif msg[0] == 'sync':\r\n self.handle_sync(msg)\r\n else:\r\n raise ValueError(f'unknown ack: {msg}')","def consume_ack(self, event):\n pass","def acknowledge(self, sequence: int):\n ackPacket = Rudp.Packet(self.seq, sequence)\n frame = ackPacket.construct()\n self.seqPlusOne()\n self.socket.sendto(frame, self.client)","def mark(self, packets: list, ack:int):\n for p in packets:\n p.status = not (ack >= p.seq)","def _ack(self,cmd):\n self.get(\"ACK\",cmd,self.from_uri,self.Q,self.I)\n self.response = self.ack()\n self.deal_msg(self.response)","def test_make_ack_default(self):\n msg_helper = MessageHelper()\n event = msg_helper.make_ack()\n self.assert_message_fields(event, {\n 'event_type': 'ack',\n 'sent_message_id': event['user_message_id'],\n })","def test_read_broadcast_distribution_table_ack(self):\n if _debug: TestAnnexJCodec._debug(\"test_read_broadcast_distribution_table_ack\")\n\n # read returns an empty table\n pdu_bytes = xtob('81.03.0004')\n\n self.request(ReadBroadcastDistributionTableAck([]))\n self.indication(pduData=pdu_bytes)\n\n self.response(PDU(pdu_bytes))\n self.confirmation(ReadBroadcastDistributionTableAck, bvlciBDT=[])\n\n # read returns a table with an element\n addr = Address('192.168.0.254/24')\n pdu_bytes = xtob('81.03.000e' # bvlci\n 'c0.a8.00.fe.ba.c0 ff.ff.ff.00' # address and mask\n )\n\n self.request(ReadBroadcastDistributionTableAck([addr]))\n self.indication(pduData=pdu_bytes)\n\n self.response(PDU(pdu_bytes))\n self.confirmation(ReadBroadcastDistributionTableAck, bvlciBDT=[addr])","def ack_ids(self) -> KeysView[str]:\n return self._leased_messages.keys()","def test_acknowledge_orders(self):\n pass","def test_make_ack_with_sent_message_id(self):\n msg_helper = MessageHelper()\n event = msg_helper.make_ack(sent_message_id='abc123')\n self.assert_message_fields(event, {\n 'event_type': 'ack',\n 'sent_message_id': 'abc123',\n })","def process_ack(self, ack_message):\n processing = True\n while processing:\n sent_message, time_sent = self.awaiting_ack.get()\n if sent_message.get_message_id() == ack_message.ack_id:\n processing = False\n else:\n self.awaiting_ack.put((sent_message, time_sent))","def test_make_ack_with_message(self):\n msg_helper = MessageHelper()\n msg = msg_helper.make_outbound('test message')\n event = msg_helper.make_ack(msg)\n self.assert_message_fields(event, {\n 'event_type': 'ack',\n 'user_message_id': msg['message_id'],\n 'sent_message_id': msg['message_id'],\n })","def ack(self):\n return (self.status == self.STATUS_ACK)","def test_make_ack_with_sent_message_id(self):\n md_helper = MessageDispatchHelper(\n MessageHelper(), WorkerHelper('fooconn'))\n broker = self.setup_broker(md_helper)\n self.assertEqual(broker.get_messages('vumi', 'fooconn.event'), [])\n msg = md_helper.msg_helper.make_outbound('test message')\n event = yield md_helper.make_dispatch_ack(\n msg, sent_message_id='abc123')\n self.assertEqual(\n broker.get_messages('vumi', 'fooconn.event'), [event])\n self.assert_message_fields(event, {\n 'event_type': 'ack',\n 'user_message_id': msg['message_id'],\n 'sent_message_id': 'abc123',\n })","def ack(self):\n the_tuple = self.deque.ack(self.tube, self.task_id)\n\n self.update_from_tuple(the_tuple)\n\n return bool(self.state == 3)","def test_read_foreign_device_table_ack(self):\n if _debug: TestAnnexJCodec._debug(\"test_read_foreign_device_table_ack\")\n\n # read returns an empty table\n pdu_bytes = xtob('81.07.0004')\n\n self.request(ReadForeignDeviceTableAck([]))\n self.indication(pduData=pdu_bytes)\n\n self.response(PDU(pdu_bytes))\n self.confirmation(ReadForeignDeviceTableAck, bvlciFDT=[])\n\n # read returns a table with one entry\n fdte = FDTEntry()\n fdte.fdAddress = Address(\"192.168.0.10\")\n fdte.fdTTL = 30\n fdte.fdRemain = 15\n pdu_bytes = xtob('81.07.000e' # bvlci\n 'c0.a8.00.0a.ba.c0' # address\n '001e.000f' # ttl and remaining\n )\n\n self.request(ReadForeignDeviceTableAck([fdte]))\n self.indication(pduData=pdu_bytes)\n\n self.response(PDU(pdu_bytes))\n self.confirmation(ReadForeignDeviceTableAck, bvlciFDT=[fdte])","def create_ack_event_sequence(self, event_count=5, delay_seconds=1):\n batch_id = yield self._backend.batch_start()\n msg = self._msg_helper.make_outbound(\"pears\")\n all_keys = []\n start = datetime.utcnow().replace(microsecond=0)\n for i in xrange(event_count):\n timestamp = start - timedelta(seconds=i * delay_seconds)\n ack = self._msg_helper.make_ack(msg, timestamp=timestamp)\n yield self._backend.add_event(ack, batch_ids=[batch_id])\n\n all_keys.append((ack[\"event_id\"], # Key\n format_vumi_date(timestamp), # Timestamp\n ack[\"event_type\"])) # Status\n\n returnValue((batch_id, msg[\"message_id\"], all_keys))","def task_done(self):\n if self.message is None:\n raise Exception('no message to acknowledge')\n self.handle.delete_message(self.message)\n self.message = None","def acknowledged(self):\n ...","def acknowledge_message(self, delivery_tag):\n self.logger.info('acknowledging message %s', delivery_tag)\n self._channel.basic_ack(delivery_tag)","def expand_ack0(stmts, isig):\n stmts.append(HDLAssign(isig['ackprg'], bit_1))\n stmts.append(HDLAssign(HDLIndex(isig['ack'], 0), bit_1))","def order_submit_ack_callback(self, data):\n self.output('order submission acknowleded: %s' % repr(data))","def ACK_IN(self, pkt):\n \n #This is a function that checks whether the received ACK is within the boundaries\n def in_window(num):\n cond_1 = (self.unack + self.receiver_win) >= num >= self.unack\n cond_2 = ((self.unack + self.receiver_win) >= 2**self.n_bits) and (((self.unack + self.receiver_win) % 2**self.n_bits) >= num) \n return (cond_1 or cond_2)\n \n \"\"\"State for received ACK.\"\"\"\n # check if type is ACK\n if pkt.getlayer(GBN).type == 0:\n log.error(\"Error: data type received instead of ACK %s\", pkt)\n raise self.SEND()\n else:\n log.debug(\"Received ACK %s\", pkt.getlayer(GBN).num)\n if(self.Q_3_4):\n if(self.CWND < self.ssthresh):\n self.CWND_fp += 1.0\n self.CWND = math.floor(self.CWND_fp)\n self.effective_window = min(self.CWND,self.win,self.receiver_win)\n self.CWND_data.append(self.CWND_fp)\n log.debug(\"CWND log (from ACK_in): %s. \", self.CWND_data)\n else:\n self.CWND_fp = self.CWND_fp + (1.0 / self.CWND)\n self.CWND = math.floor(self.CWND_fp)\n self.effective_window = min(self.CWND,self.win,self.receiver_win)\n self.CWND_data.append(self.CWND_fp)\n log.debug(\"CWND log (from ACK_in): %s. \", self.CWND_data)\n #Set the receiver window size to the received window value\n self.receiver_win = pkt.getlayer(GBN).win\n #Set the ack number to the received value\n ack = pkt.getlayer(GBN).num\n if(not in_window(ack)):\n log.error(\"Error: ACK received is out-of-window %s, discard!\", pkt)\n #Create a sender buffer key list for easier manipulation\n Sender_buffer_keys = list(self.buffer.keys())\n \n #Detect the index of the key value that is ack'ed, and erase everything coming beforehand\n if ((ack-1)%2**self.n_bits) in Sender_buffer_keys:\n index = Sender_buffer_keys.index((ack-1)%2**self.n_bits)\n Sender_buffer_keys = Sender_buffer_keys[:index+1]\n log.debug(\"Packet numbers deleted from the sender buffer %s\", Sender_buffer_keys)\n for i in Sender_buffer_keys:\n del self.buffer[i]\n log.debug(\"The new sender buffer %s\", list(self.buffer.keys()))\n\n #New unack is the latest ack number\n self.unack = ack\n\n #Question 3.2, detect duplicate acks and go into the transmission state when necessary\n if(self.Q_3_2 or self.Q_3_4): \n #implement a queue for checking duplicated ack\n self.dup_ack.append(ack)\n log.debug(\"duplicated ack buffer is %s\", self.dup_ack)\n if(len(self.dup_ack) >= 3):\n if(self.dup_ack[-1] == self.dup_ack[-2] == self.dup_ack[-3]):\n self.dup_ack.clear()\n log.debug(\"Duplicate ACKs for sequence number %s\", ack)\n if(self.Q_3_2):\n self.dup_ack_hanjing = True\n self.retransmit_flag = True\n if(self.Q_3_4):\n self.ssthresh = self.CWND / 2\n self.CWND_fp = self.ssthresh\n self.CWND = math.floor(self.CWND_fp)\n self.effective_window = min(self.CWND,self.win,self.receiver_win)\n self.CWND_data.append(self.CWND_fp)\n log.debug(\"CWND log: %s. \", self.CWND_data)\n raise self.SEND()\n \n #Q3_3 optional field list construction\n if(self.SACK == 1 and (pkt.getlayer(GBN).options == 1) and (pkt.getlayer(GBN).hlen >6)):\n #Get the header length\n self.hlen = pkt.getlayer(GBN).hlen\n #Pull optional field parameters\n if(self.hlen >= 9):\n self.ledge1 = pkt.getlayer(GBN).ledge1\n self.len1 = pkt.getlayer(GBN).len1\n if(self.hlen >= 12):\n self.ledge2 = pkt.getlayer(GBN).ledge2\n self.len2 = pkt.getlayer(GBN).len2\n if(self.hlen == 15):\n self.ledge3 = pkt.getlayer(GBN).ledge3\n self.len3 = pkt.getlayer(GBN).len3\n self.retransmit_flag = True\n raise self.SEND()\n\n\n # back to SEND state\n raise self.SEND()","def test_acknowledge(client):\n g.test_authorized_for = []\n res = client.get(\"/v0/acknowledge\" + get_request_args)\n assert \"Thanks for acknowledging!\" in res.data.decode(\"utf-8\")","def acknowledge(self, subscription, project, ack_ids):\n response, content = self._http.request(\n '%s/%s/subscriptions/%s:acknowledge' % (\n PUBSUB_BASE_URL, project, subscription),\n body=json.dumps({'ackIds': ack_ids}),\n method='POST',\n )\n if response['status'] == '404':\n raise NotFoundError(response, json.loads(content))\n return json.loads(content)","def test_make_dispatch_ack_default(self):\n md_helper = MessageDispatchHelper(\n MessageHelper(), WorkerHelper('fooconn'))\n broker = self.setup_broker(md_helper)\n self.assertEqual(broker.get_messages('vumi', 'fooconn.event'), [])\n event = yield md_helper.make_dispatch_ack()\n self.assertEqual(\n broker.get_messages('vumi', 'fooconn.event'), [event])\n self.assert_message_fields(event, {\n 'event_type': 'ack',\n 'sent_message_id': event['user_message_id'],\n })","def acknowledge_message(self, delivery_tag):\n logger.info('Acknowledging message %s process %s consumer_id %s', delivery_tag, threading.current_thread, str(self.consumer_id))\n self._channel.basic_ack(delivery_tag)","def handleSent(): \n global sentAck\n sentAck = True","def transmitPollAck(): \r\n global data\r\n DW1000.newTransmit()\r\n data[0] = C.POLL_ACK\r\n DW1000.setDelay(REPLY_DELAY_TIME_US, C.MICROSECONDS)\r\n DW1000.setData(data, LEN_DATA)\r\n DW1000.startTransmit()","def handleSent(): \r\n global sentAck\r\n sentAck = True","def bidACK(dice, query):\r\n status=\"\"\r\n strDice = ','.join([str(x) for x in dice])\r\n if query == 'b' or query=='B':\r\n status = \"305 Bid ACK \" + strDice\r\n elif query == 'c' or query=='C':\r\n status = \"305 Bid ACK Challenge. Server roll: \" +strDice\r\n #print (\"TEST\", status)\r\n return status","def watch_for_acks(self):\n while True:\n ack_message = self.messages['ack'].get()\n process_ack_thread = Thread(\n target=self.process_ack, args=(ack_message,), daemon=True)\n process_ack_thread.start()","def acknowledge_message(self, channel, delivery_tag):\n logger.info('Acknowledging message %s', delivery_tag)\n channel.basic_ack(delivery_tag)","def __call__(\n self,\n request: pubsub.AcknowledgeRequest,\n *,\n retry: OptionalRetry = gapic_v1.method.DEFAULT,\n timeout: Optional[float] = None,\n metadata: Sequence[Tuple[str, str]] = (),\n ):\n\n http_options: List[Dict[str, str]] = [\n {\n \"method\": \"post\",\n \"uri\": \"/v1/{subscription=projects/*/subscriptions/*}:acknowledge\",\n \"body\": \"*\",\n },\n ]\n request, metadata = self._interceptor.pre_acknowledge(request, metadata)\n pb_request = pubsub.AcknowledgeRequest.pb(request)\n transcoded_request = path_template.transcode(http_options, pb_request)\n\n # Jsonify the request body\n\n body = json_format.MessageToJson(\n transcoded_request[\"body\"],\n including_default_value_fields=False,\n use_integers_for_enums=True,\n )\n uri = transcoded_request[\"uri\"]\n method = transcoded_request[\"method\"]\n\n # Jsonify the query params\n query_params = json.loads(\n json_format.MessageToJson(\n transcoded_request[\"query_params\"],\n including_default_value_fields=False,\n use_integers_for_enums=True,\n )\n )\n query_params.update(self._get_unset_required_fields(query_params))\n\n query_params[\"$alt\"] = \"json;enum-encoding=int\"\n\n # Send the request\n headers = dict(metadata)\n headers[\"Content-Type\"] = \"application/json\"\n response = getattr(self._session, method)(\n \"{host}{uri}\".format(host=self._host, uri=uri),\n timeout=timeout,\n headers=headers,\n params=rest_helpers.flatten_query_params(query_params, strict=True),\n data=body,\n )\n\n # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception\n # subclass.\n if response.status_code >= 400:\n raise core_exceptions.from_http_response(response)","def watch_for_ack_timeout(self):\n while True:\n sent_message, time_sent = self.awaiting_ack.get()\n timeout_time = time.time() + self.ACK_TIMEOUT\n if time_sent + self.ACK_TIMEOUT < time.time():\n sent_message.resent += 1\n if sent_message.resent < 15:\n self.send_message(sent_message)\n self._log.write_to_log(\n \"ACK\", f\"Attempt {sent_message.resent} to resend {sent_message.TYPE_STRING} message {sent_message.uuid} to {sent_message.destination_node.get_name()}\")\n else:\n self._log.write_to_log(\n \"ACK\", f\"Drop message to {sent_message.destination_node.get_name()}\")\n else:\n self.awaiting_ack.put((sent_message, time_sent))\n\n time.sleep(.3) # Ensure this thread doesn't hog the queue","def open_ack_msg(conn_id):\n return CCPMessage(CCPMessage.OPEN_CONNECTION_ACK, conn_id=conn_id)","def kafka_commit(self):\n self.kf_producer.flush()","def transmitPollAck(): \n global data\n DW1000.newTransmit()\n data[0] = C.POLL_ACK\n data[17] = anchorID #data[17] is tag Id data[18] is anchor Id\n data[18] = tagID #data[17] is tag Id data[18] is anchor Id\n DW1000.setDelay(REPLY_DELAY_TIME_US, C.MICROSECONDS)\n DW1000.setData(data, LEN_DATA)\n DW1000.startTransmit()","def acknowledge_visitor(visitor):\n visitor.acknowledged = True\n visitor.acknowledged_time = datetime.now()\n visitor.save()","def __is_ack(self, ack) -> bool:\n return ack == ['void']","def ack_message(channel, delivery_tag):\n global logger\n if channel.is_open:\n channel.basic_ack(delivery_tag)\n logger.debug(\"Channel is acked!\")\n else:\n # Channel is already closed, so we can't ACK this message;\n # log and/or do something that makes sense for your app in this case.\n logger.debug(\"Channel is closed!\")","def valid_ack(self, message: dict, addition: int = 1) -> bool:\n return self.safe_incr(self.seq_nr, addition) == message['ack_nr']","def ack_transmit(self, data, max_freq_retry=5, max_tx_retry=10):\n\t\ttransmit_success = False\n\t\tfor freq_retry in range(max_freq_retry):\n\t\t\tfor tx_retry in range(max_tx_retry):\n\t\t\t\tself.tb.transmit(data)\n\t\t\t\ttime.sleep(0.15)\n\t\t\t\tif self.ack_processor.get_last_ack() != self.seqnum:\n\t\t\t\t\tself.log(\"Warning: no ACK received, retrying\", hue.bad)\n\t\t\t\telse:\n\t\t\t\t\tself.log(\"ACK received\", hue.good)\n\t\t\t\t\ttransmit_success = True\n\t\t\t\t\treturn True\n\t\t\tself.log(\"Warning: switching frequency\", hue.bad)\n\t\t\tself.tb.frequency_switch()\n\t\treturn False","def _process_ack_packet(self, rudp_packet):\n if self._sending_window:\n self._retire_packets_with_seqnum_up_to(\n min(rudp_packet.ack, self._next_sequence_number)\n )","def test_process_packet_ack(self):\n pkt = {'type': 'ack',\n 'ackId': 140,\n 'endpoint': '',\n 'args': []}\n self.ns.process_packet(pkt)\n assert not self.environ['socketio'].error.called","def handleReceived():\r\n global receivedAck\r\n receivedAck = True","def incr_all_pkts(self, msg):\n\n\t\tself.__msg.setText(msg)\n\n\t\tself.__all += 1\n\t\tself.__all_lbl.setText(str(self.__all))","def on_ack(self, data):\n logger.debug('on_ack: %r', data)\n raise NotAccepted('Server should not be ACKed.')","def test_acknowledge_post(client):\n g.test_authorized_for = []\n res = client.post(\"/v0/acknowledge\", json=post_json_data)\n assert '{\"msg\":\"Thanks for acknowledging!\",\"status\":\"ok\"}' in res.data.decode(\"utf-8\")","async def nack_event(\n self, envelope: Envelope, multiple: bool = False, requeue: bool = True\n ) -> None:\n await self.channel.basic_client_nack(\n delivery_tag=envelope.delivery_tag, multiple=multiple, requeue=requeue\n )","def acknowledge_failure(self):\n self.append(ACK_FAILURE, response=AckFailureResponse(self))\n self.sync()","def handle_packet(self, pkt):\n logger.info('got a message:{}'.format(pkt))\n self._sock_rep_to_server.send_pyobj(packet.Ack())\n \n state = True\n extradata = {}\n \n if hasattr(self, 'handle_action'):\n _tmp = self.handle_action(pkt)\n try:\n state, data = _tmp\n extradata['extra'] = data\n except ValueError:\n extradata['extra'] = _tmp\n if extradata:\n state = False\n \n return state, extradata","def handleReceived(): \n global receivedAck\n receivedAck = True","def check_ack_queue(self):\r\n try:\r\n while True:\r\n ack = self.ack_queue.get_nowait()\r\n self.handle_ack(ack)\r\n except queue.Empty:\r\n pass","def ack_required(self):\n v = self[22]\n v = v >> 1\n return (v & 0b1) != 0","async def handle_message(self, event_msg):\n msg_logger = _utils.GEventMessageLogger(\n self._logger, {'msg_id': event_msg.msg_id})\n\n msg_logger.debug(f'Acking message.')\n # \"blocking\" method but just puts msg on a request queue that\n # google.cloud.pubsub manages with threads+grpc\n event_msg._pubsub_msg.ack()\n\n msg = 'Acknowledged message in Pub/Sub.'\n event_msg.append_to_history(msg, self.phase)\n\n msg_logger.info(f'Message is done processing.')","def test_make_nack_with_sent_message_id(self):\n md_helper = MessageDispatchHelper(\n MessageHelper(), WorkerHelper('fooconn'))\n broker = self.setup_broker(md_helper)\n self.assertEqual(broker.get_messages('vumi', 'fooconn.event'), [])\n msg = md_helper.msg_helper.make_outbound('test message')\n event = yield md_helper.make_dispatch_nack(\n msg, nack_reason='bogon emissions')\n self.assertEqual(\n broker.get_messages('vumi', 'fooconn.event'), [event])\n self.assert_message_fields(event, {\n 'event_type': 'nack',\n 'user_message_id': msg['message_id'],\n 'nack_reason': 'bogon emissions',\n })","def ticket_submit_ack_callback(self, data):\n self.output('staged order ticket submission acknowledged: %s' % repr(data))","def acknowledge_chat_message_with_http_info(self, id, **kwargs):\n\n all_params = ['id', 'read_count']\n all_params.append('async')\n all_params.append('_return_http_data_only')\n all_params.append('_preload_content')\n all_params.append('_request_timeout')\n\n params = locals()\n for key, val in iteritems(params['kwargs']):\n if key not in all_params:\n raise TypeError(\n \"Got an unexpected keyword argument '%s'\"\n \" to method acknowledge_chat_message\" % key\n )\n params[key] = val\n del params['kwargs']\n # verify the required parameter 'id' is set\n if ('id' not in params) or (params['id'] is None):\n raise ValueError(\"Missing the required parameter `id` when calling `acknowledge_chat_message`\")\n\n\n collection_formats = {}\n\n path_params = {}\n if 'id' in params:\n path_params['id'] = params['id']\n\n query_params = []\n\n header_params = {}\n\n form_params = []\n local_var_files = {}\n\n body_params = None\n if 'read_count' in params:\n body_params = params['read_count']\n # HTTP header `Accept`\n header_params['Accept'] = self.api_client.\\\n select_header_accept(['application/json'])\n\n # HTTP header `Content-Type`\n header_params['Content-Type'] = self.api_client.\\\n select_header_content_type(['application/json'])\n\n # Authentication setting\n auth_settings = ['oauth2_client_credentials_grant', 'oauth2_password_grant']\n\n return self.api_client.call_api('/chat/threads/{id}/acknowledge', 'PUT',\n path_params,\n query_params,\n header_params,\n body=body_params,\n post_params=form_params,\n files=local_var_files,\n response_type=None,\n auth_settings=auth_settings,\n async=params.get('async'),\n _return_http_data_only=params.get('_return_http_data_only'),\n _preload_content=params.get('_preload_content', True),\n _request_timeout=params.get('_request_timeout'),\n collection_formats=collection_formats)","def write_ack(self, mid, data=''):\n __nTry_max = 50\n\n for ite in range(__nTry_max):\n self.write_msg(mid, data)\n data_ack = self.read_msg(chr(ord(mid)+1))\n\n if not data_ack == -1:\n return data_ack\n\n rospy.loginfo(\"Fail to find a valid Mid_ACK: %d\" % (ord(mid)+1))\n return -1","def ack(self, other, city):\n pass","def check_ack_or_nak(message):\n value = message.body[-1]\n\n if value == 0x06:\n return\n elif value == 0x15:\n raise CommandFailure(command_code=message.command_code)\n else:\n raise RuntimeError(\"Unexpected ACK/NAK value (0x%02x)\" % value)","def encode_ack(b_public):\n\n return 'ACK;%i' % (b_public)","def process_syn_ack(ts_delta, acks, nb_acks, connections, tcp, ip, saddr, daddr, sport, dport, black_list, inverse_conns, ts_syn_timeout, ts_timeout):\n # The sender of the SYN/ACK is the server\n if (daddr, dport, saddr, sport) in acks and ((ts_delta - acks[daddr, dport, saddr, sport][co.TIMESTAMP][CLIENT]).total_seconds() < ts_timeout\n and acks[daddr, dport, saddr, sport][co.C2S] == -1):\n # Better to check, if not seen, maybe uncomplete TCP connection\n acks[daddr, dport, saddr, sport][co.C2S] = tcp.ack\n acks[daddr, dport, saddr, sport][SEQ_S2C].add(tcp.seq)\n acks[daddr, dport, saddr, sport][HSEQ_S2C][tcp.seq] = [ts_delta, ts_delta]\n acks[daddr, dport, saddr, sport][co.TIMESTAMP][SERVER] = ts_delta\n\n elif (daddr, dport, saddr, sport) in acks and ((ts_delta - acks[daddr, dport, saddr, sport][co.TIMESTAMP][CLIENT]).total_seconds() < ts_timeout\n and tcp.seq in acks[daddr, dport, saddr, sport][SEQ_S2C]):\n # SYN/ACK retransmission!\n conn_id = acks[daddr, dport, saddr, sport][co.CONN_ID]\n connections[conn_id].flow.attr[co.S2C][co.TIMESTAMP_RETRANS].append((ts_delta,\n ts_delta - acks[daddr, dport, saddr, sport][HSEQ_S2C][tcp.seq][0],\n ts_delta - acks[daddr, dport, saddr, sport][HSEQ_S2C][tcp.seq][1],\n ts_delta - acks[daddr, dport, saddr, sport][co.TIMESTAMP][CLIENT]))\n acks[daddr, dport, saddr, sport][HSEQ_S2C][tcp.seq][1] = ts_delta\n acks[daddr, dport, saddr, sport][co.TIMESTAMP][SERVER] = ts_delta","def abort_hsdpa_ack_meas(self):\r\r\n loggerCmw = logging.getLogger('abort_hsdpa_ack_meas')\r\r\n self.write('ABORt:WCDMa:SIGN:HACK')\r\r\n loggerCmw.info(\"Aborting HSDPA ACK measurement\")\r\r\n time.sleep(1)","def RETRANSMIT(self):\n\n ##############################################\n # retransmit all the unacknowledged packets #\n # (all the packets currently in self.buffer) #\n ##############################################\n \n if(self.timeout_hanjing):\n #If we are coming from the timeout state, retransmit all the buffer\n for k,v in self.buffer.items():\n if(self.SACK == 0):\n header_GBN = GBN(type = 'data', len = len(v), hlen = 6, num = k, win = self.win)\n else:\n header_GBN = GBN(type = 'data', options = 1, len = len(v), hlen = 6, num = k, win = self.win)\n send(IP(src = self.sender, dst = self.receiver) / header_GBN / v)\n log.debug(\"Sending packet number: %s\", k)\n \n if ((self.Q_3_2 == 1) and (self.dup_ack_hanjing == True) and (self.timeout_hanjing == False)):\n #just retransmit the packet that has been ack'ed 3 times consequtively\n header_GBN = GBN(type = 'data', len = len(self.buffer[self.unack]), hlen = 6, num = self.unack, win = self.win)\n send(IP(src = self.sender, dst = self.receiver) / header_GBN / self.buffer[self.unack])\n log.debug(\"Sending packet number: %s\", self.unack)\n \n #Question 3.3\n if(self.SACK == 1 and (self.timeout_hanjing == False) and (self.hlen > 6)):\n if(self.hlen == 9):\n optionalHeader_list = list(range(self.ledge1, self.ledge1 + self.len1)) \n if(self.hlen == 12):\n optionalHeader_list = list(range(self.ledge1, self.ledge1 + self.len1)) + list(range(self.ledge2, self.ledge2 + self.len2)) \n if(self.hlen == 15):\n optionalHeader_list = list(range(self.ledge1, self.ledge1 + self.len1)) + list(range(self.ledge2, self.ledge2 + self.len2)) + list(range(self.ledge3, self.ledge3 + self.len3)) \n \n for i in optionalHeader_list:\n optionalHeader_list[optionalHeader_list.index(i)] = i % 2**self.n_bits\n \n #We need to find the difference between the sender buffer, and the optionalHeader_list\n Sender_buffer_keys = list(self.buffer.keys()) \n log.debug(\"The sender buffer: %s\", Sender_buffer_keys)\n #Trimmed_sender_buffer includes the buffer list only up to the last packet number in the optional header list)\n trimmed_sender_buffer = Sender_buffer_keys[:Sender_buffer_keys.index(optionalHeader_list[-1])+1]\n #Retrans_list is the list of keys to be retransmitted\n log.debug(\"Trimmed Sender Buffer: %s\", trimmed_sender_buffer)\n log.debug(\"Optional Header List: %s\", optionalHeader_list)\n Retrans_list = [item for item in trimmed_sender_buffer if item not in optionalHeader_list]\n log.debug(\"SACK: packets should be retransmitted: %s\", Retrans_list)\n for i in Retrans_list:\n header_GBN = GBN(type = 'data', options = 1 , len = len(self.buffer[i]), hlen = 6, num = i, win = self.win)\n send(IP(src = self.sender, dst = self.receiver) / header_GBN / self.buffer[i])\n log.debug(\"SACK Retransmission: Sending packet number: %s\", i)\n # back to SEND state\n self.dup_ack_hanjing = False\n self.timeout_hanjing = False\n raise self.SEND()","def test_make_nack_with_message(self):\n msg_helper = MessageHelper()\n msg = msg_helper.make_outbound('test message')\n event = msg_helper.make_nack(msg)\n self.assert_message_fields(event, {\n 'event_type': 'nack',\n 'user_message_id': msg['message_id'],\n 'nack_reason': 'sunspots',\n })","def test_make_nack_with_nack_reason(self):\n msg_helper = MessageHelper()\n event = msg_helper.make_nack(nack_reason='bogon emissions')\n self.assert_message_fields(event, {\n 'event_type': 'nack',\n 'nack_reason': 'bogon emissions',\n })","def RollDiceACK(dice):\r\n #strDice = ','.join([str(x) for x in dice])\r\n #status = \"205 Roll Dice ACK \" + strDice\r\n status = \"205 Roll Dice ACK \" + dice\r\n return status","def on_publish(self, mqtt_client, userdata, mid):\n logging.debug(\"DEBUG - publish ack received\")","def test_make_nack_default(self):\n msg_helper = MessageHelper()\n event = msg_helper.make_nack()\n self.assert_message_fields(event, {\n 'event_type': 'nack',\n 'nack_reason': 'sunspots',\n })","def process_mptcp_syn_ack(ts_delta, acks, conn_acks, mptcp_connections, tcp, ip, saddr, daddr, sport, dport, black_list, fast_conns, ts_syn_timeout, ts_timeout):\n # The sender of the SYN/ACK is the server\n if (daddr, dport, saddr, sport) in acks and ((ts_delta - acks[daddr, dport, saddr, sport][co.TIMESTAMP][CLIENT]).total_seconds() < ts_timeout\n and acks[daddr, dport, saddr, sport][co.C2S] == -1):\n # Better to check, if not seen, maybe uncomplete TCP connection\n acks[daddr, dport, saddr, sport][co.C2S] = tcp.ack\n acks[daddr, dport, saddr, sport][co.TIMESTAMP][SERVER] = ts_delta\n conn_acks[acks[daddr, dport, saddr, sport][co.CONN_ID]][co.TIMESTAMP][SERVER] = ts_delta\n\n elif (daddr, dport, saddr, sport) in acks and ((ts_delta - acks[daddr, dport, saddr, sport][co.TIMESTAMP][CLIENT]).total_seconds() < ts_timeout\n and tcp.ack == acks[daddr, dport, saddr, sport][co.C2S]):\n # SYN/ACK retransmission! But don't do anything special\n acks[daddr, dport, saddr, sport][co.TIMESTAMP][SERVER] = ts_delta\n conn_acks[acks[daddr, dport, saddr, sport][co.CONN_ID]][co.TIMESTAMP][SERVER] = ts_delta","def ack_frame(self, frame_nb, result):\n #!!170514:VG:Remove the frame only if ACK OK\n if frame_nb in self.frames:\n if not result:\n self.log.error(\"ACK frame error '%s'\" % self.frames[frame_nb])\n else:\n self.frames.pop(frame_nb)","def acknowledge_prepayment(self):\n self.acknowledge_payment()","def nack(self, visibility_timeout_seconds=None):\n self.consumer.nack(self, visibility_timeout_seconds)","def start_lease_expiry_timer(self, ack_ids: Iterable[str]) -> None:\n with self._add_remove_lock:\n for ack_id in ack_ids:\n lease_info = self._leased_messages.get(ack_id)\n # Lease info might not exist for this ack_id because it has already\n # been removed by remove().\n if lease_info:\n self._leased_messages[ack_id] = lease_info._replace(\n sent_time=time.time()\n )"],"string":"[\n \"def MessageAck(self, request, context):\\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)\",\n \"def MessageAck(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\\n raise NotImplementedError()\",\n \"def ack(self, tup_id):\\n pass\",\n \"async def ack(self, offset: int):\",\n \"def ack(self, task_id):\\n raise NotImplementedError\",\n \"def acked(err, msg):\\n if err is not None:\\n print(\\\"Failed to deliver message: {}\\\".format(err))\\n else:\\n print(\\\"Produced record to topic {} partition [{}] @ offset {}\\\"\\n .format(msg.topic(), msg.partition(), msg.offset()))\",\n \"def ack(self):\\n self.consumer.ack(self)\",\n \"async def acknowledge(self, *event_messages, bus_client: \\\"BusClient\\\"):\\n pass\",\n \"def ack(self, tube, task_id):\\n cmd = tube.cmd('ack')\\n args = (task_id,)\\n\\n return self.tnt.call(cmd, args)\",\n \"def ack(self):\\n content = self._content \\n log('content:'+content)\\n self.__tcp_send(content)\",\n \"def ackable(self, host, service, state, message):\\n\\n if self.act_ct == (self.list_size - 1) and self.has_rolled == False:\\n self.has_rolled = True\\n self.act_ct = 0\\n elif self.act_ct == 0 and self.has_rolled == False:\\n self.has_rolled = True\\n self.act_ct = 0\\n elif self.act_ct == 0 and self.has_rolled == True:\\n self.act_ct = (self.act_ct + 1) % self.list_size\\n elif self.act_ct > 0 or self.has_rolled == True:\\n self.has_rolled = False\\n self.act_ct = (self.act_ct + 1) % self.list_size\\n if state == \\\"UNKNOWN\\\" or state == \\\"WARNING\\\" or state == \\\"CRITICAL\\\" or state == \\\"UP\\\" or state == \\\"OK\\\" or state == \\\"DOWN\\\" or state == \\\"UNREACHABLE\\\":\\n self.ackable_list[self.act_ct] = {'host':host, 'service': service, 'state':state, 'message':message}\\n #return(self.act_ct + self.list_offset)\",\n \"def acknowledge(self, message: Message[ValueType]) -> Message[ValueType]:\",\n \"def ackId(tupid):\\n sendMsgToParent({\\\"command\\\": \\\"ack\\\", \\\"id\\\": tupid})\",\n \"def on_nack(self, message: PubsubMessage, ack: Callable[[], None]):\\n pass\",\n \"def _send_ack(self):\\n ack_packet = packet.Packet.from_data(\\n 0,\\n self.dest_addr,\\n self.own_addr,\\n ack=self._next_expected_seqnum\\n )\\n self._schedule_send_out_of_order(ack_packet)\",\n \"def recalcAck(self):\\n\\t\\t\\n\\t\\t#if self.ackNo < 0:\\n\\t\\t#\\tself.ackNo = self.rSegs[0].segNo\\n\\t\\t\\n\\t\\t\\n\\t\\twhile True:\\n\\t\\t\\t#Find Target segment\\n\\t\\t\\ttarget = self.ackNo + 1\\n\\t\\t\\tfound = False\\n\\t\\t\\tfor p in self.rSegs:\\n\\t\\t\\t\\tif target == p.segNo:\\n\\t\\t\\t\\t\\tself.ackNo += 1\\n\\t\\t\\t\\t\\tfound = True\\n\\t\\t\\t\\t\\tbreak\\n\\t\\t\\t\\n\\t\\t\\t#\\n\\t\\t\\tif not found:\\n\\t\\t\\t\\tbreak\",\n \"def _acknowledge_message(self, app, message):\\n self.client.delete_message(\\n QueueUrl=self.app.settings['SQS_INBOUND_QUEUE_URL'],\\n ReceiptHandle=message['ReceiptHandle'],\\n )\",\n \"def ack_event(self, event_id):\\n return self.client.call('Notification_Occurrence_Event', 'acknowledgeNotification', id=event_id)\",\n \"def acknowledgement(self, message: Message[ValueType]):\",\n \"def acked(err, msg):\\n if err is not None:\\n print(\\\"failed to deliver message: {}\\\".format(err.str()))\\n else:\\n print(\\\"produced to: {} [{}] @ {}\\\".format(msg.topic(), msg.partition(), msg.offset()))\",\n \"def acknowledge_many(self, messages: Iterable[Message[ValueType]]) -> None:\\n for message in messages: # pragma: no cover\\n self.acknowledge(message)\",\n \"async def ack_event(self, envelope: Envelope, multiple: bool = False) -> None:\\n await self.channel.basic_client_ack(\\n delivery_tag=envelope.delivery_tag, multiple=multiple\\n )\",\n \"def acknowledgePacket(self, packet: Rudp.Packet):\\n self.acknowledge(packet.seq)\",\n \"def handle_ack(self, msg):\\r\\n if msg[0] == 'post':\\r\\n self.handle_post_frame(msg)\\r\\n elif msg[0] == 'sync':\\r\\n self.handle_sync(msg)\\r\\n else:\\r\\n raise ValueError(f'unknown ack: {msg}')\",\n \"def consume_ack(self, event):\\n pass\",\n \"def acknowledge(self, sequence: int):\\n ackPacket = Rudp.Packet(self.seq, sequence)\\n frame = ackPacket.construct()\\n self.seqPlusOne()\\n self.socket.sendto(frame, self.client)\",\n \"def mark(self, packets: list, ack:int):\\n for p in packets:\\n p.status = not (ack >= p.seq)\",\n \"def _ack(self,cmd):\\n self.get(\\\"ACK\\\",cmd,self.from_uri,self.Q,self.I)\\n self.response = self.ack()\\n self.deal_msg(self.response)\",\n \"def test_make_ack_default(self):\\n msg_helper = MessageHelper()\\n event = msg_helper.make_ack()\\n self.assert_message_fields(event, {\\n 'event_type': 'ack',\\n 'sent_message_id': event['user_message_id'],\\n })\",\n \"def test_read_broadcast_distribution_table_ack(self):\\n if _debug: TestAnnexJCodec._debug(\\\"test_read_broadcast_distribution_table_ack\\\")\\n\\n # read returns an empty table\\n pdu_bytes = xtob('81.03.0004')\\n\\n self.request(ReadBroadcastDistributionTableAck([]))\\n self.indication(pduData=pdu_bytes)\\n\\n self.response(PDU(pdu_bytes))\\n self.confirmation(ReadBroadcastDistributionTableAck, bvlciBDT=[])\\n\\n # read returns a table with an element\\n addr = Address('192.168.0.254/24')\\n pdu_bytes = xtob('81.03.000e' # bvlci\\n 'c0.a8.00.fe.ba.c0 ff.ff.ff.00' # address and mask\\n )\\n\\n self.request(ReadBroadcastDistributionTableAck([addr]))\\n self.indication(pduData=pdu_bytes)\\n\\n self.response(PDU(pdu_bytes))\\n self.confirmation(ReadBroadcastDistributionTableAck, bvlciBDT=[addr])\",\n \"def ack_ids(self) -> KeysView[str]:\\n return self._leased_messages.keys()\",\n \"def test_acknowledge_orders(self):\\n pass\",\n \"def test_make_ack_with_sent_message_id(self):\\n msg_helper = MessageHelper()\\n event = msg_helper.make_ack(sent_message_id='abc123')\\n self.assert_message_fields(event, {\\n 'event_type': 'ack',\\n 'sent_message_id': 'abc123',\\n })\",\n \"def process_ack(self, ack_message):\\n processing = True\\n while processing:\\n sent_message, time_sent = self.awaiting_ack.get()\\n if sent_message.get_message_id() == ack_message.ack_id:\\n processing = False\\n else:\\n self.awaiting_ack.put((sent_message, time_sent))\",\n \"def test_make_ack_with_message(self):\\n msg_helper = MessageHelper()\\n msg = msg_helper.make_outbound('test message')\\n event = msg_helper.make_ack(msg)\\n self.assert_message_fields(event, {\\n 'event_type': 'ack',\\n 'user_message_id': msg['message_id'],\\n 'sent_message_id': msg['message_id'],\\n })\",\n \"def ack(self):\\n return (self.status == self.STATUS_ACK)\",\n \"def test_make_ack_with_sent_message_id(self):\\n md_helper = MessageDispatchHelper(\\n MessageHelper(), WorkerHelper('fooconn'))\\n broker = self.setup_broker(md_helper)\\n self.assertEqual(broker.get_messages('vumi', 'fooconn.event'), [])\\n msg = md_helper.msg_helper.make_outbound('test message')\\n event = yield md_helper.make_dispatch_ack(\\n msg, sent_message_id='abc123')\\n self.assertEqual(\\n broker.get_messages('vumi', 'fooconn.event'), [event])\\n self.assert_message_fields(event, {\\n 'event_type': 'ack',\\n 'user_message_id': msg['message_id'],\\n 'sent_message_id': 'abc123',\\n })\",\n \"def ack(self):\\n the_tuple = self.deque.ack(self.tube, self.task_id)\\n\\n self.update_from_tuple(the_tuple)\\n\\n return bool(self.state == 3)\",\n \"def test_read_foreign_device_table_ack(self):\\n if _debug: TestAnnexJCodec._debug(\\\"test_read_foreign_device_table_ack\\\")\\n\\n # read returns an empty table\\n pdu_bytes = xtob('81.07.0004')\\n\\n self.request(ReadForeignDeviceTableAck([]))\\n self.indication(pduData=pdu_bytes)\\n\\n self.response(PDU(pdu_bytes))\\n self.confirmation(ReadForeignDeviceTableAck, bvlciFDT=[])\\n\\n # read returns a table with one entry\\n fdte = FDTEntry()\\n fdte.fdAddress = Address(\\\"192.168.0.10\\\")\\n fdte.fdTTL = 30\\n fdte.fdRemain = 15\\n pdu_bytes = xtob('81.07.000e' # bvlci\\n 'c0.a8.00.0a.ba.c0' # address\\n '001e.000f' # ttl and remaining\\n )\\n\\n self.request(ReadForeignDeviceTableAck([fdte]))\\n self.indication(pduData=pdu_bytes)\\n\\n self.response(PDU(pdu_bytes))\\n self.confirmation(ReadForeignDeviceTableAck, bvlciFDT=[fdte])\",\n \"def create_ack_event_sequence(self, event_count=5, delay_seconds=1):\\n batch_id = yield self._backend.batch_start()\\n msg = self._msg_helper.make_outbound(\\\"pears\\\")\\n all_keys = []\\n start = datetime.utcnow().replace(microsecond=0)\\n for i in xrange(event_count):\\n timestamp = start - timedelta(seconds=i * delay_seconds)\\n ack = self._msg_helper.make_ack(msg, timestamp=timestamp)\\n yield self._backend.add_event(ack, batch_ids=[batch_id])\\n\\n all_keys.append((ack[\\\"event_id\\\"], # Key\\n format_vumi_date(timestamp), # Timestamp\\n ack[\\\"event_type\\\"])) # Status\\n\\n returnValue((batch_id, msg[\\\"message_id\\\"], all_keys))\",\n \"def task_done(self):\\n if self.message is None:\\n raise Exception('no message to acknowledge')\\n self.handle.delete_message(self.message)\\n self.message = None\",\n \"def acknowledged(self):\\n ...\",\n \"def acknowledge_message(self, delivery_tag):\\n self.logger.info('acknowledging message %s', delivery_tag)\\n self._channel.basic_ack(delivery_tag)\",\n \"def expand_ack0(stmts, isig):\\n stmts.append(HDLAssign(isig['ackprg'], bit_1))\\n stmts.append(HDLAssign(HDLIndex(isig['ack'], 0), bit_1))\",\n \"def order_submit_ack_callback(self, data):\\n self.output('order submission acknowleded: %s' % repr(data))\",\n \"def ACK_IN(self, pkt):\\n \\n #This is a function that checks whether the received ACK is within the boundaries\\n def in_window(num):\\n cond_1 = (self.unack + self.receiver_win) >= num >= self.unack\\n cond_2 = ((self.unack + self.receiver_win) >= 2**self.n_bits) and (((self.unack + self.receiver_win) % 2**self.n_bits) >= num) \\n return (cond_1 or cond_2)\\n \\n \\\"\\\"\\\"State for received ACK.\\\"\\\"\\\"\\n # check if type is ACK\\n if pkt.getlayer(GBN).type == 0:\\n log.error(\\\"Error: data type received instead of ACK %s\\\", pkt)\\n raise self.SEND()\\n else:\\n log.debug(\\\"Received ACK %s\\\", pkt.getlayer(GBN).num)\\n if(self.Q_3_4):\\n if(self.CWND < self.ssthresh):\\n self.CWND_fp += 1.0\\n self.CWND = math.floor(self.CWND_fp)\\n self.effective_window = min(self.CWND,self.win,self.receiver_win)\\n self.CWND_data.append(self.CWND_fp)\\n log.debug(\\\"CWND log (from ACK_in): %s. \\\", self.CWND_data)\\n else:\\n self.CWND_fp = self.CWND_fp + (1.0 / self.CWND)\\n self.CWND = math.floor(self.CWND_fp)\\n self.effective_window = min(self.CWND,self.win,self.receiver_win)\\n self.CWND_data.append(self.CWND_fp)\\n log.debug(\\\"CWND log (from ACK_in): %s. \\\", self.CWND_data)\\n #Set the receiver window size to the received window value\\n self.receiver_win = pkt.getlayer(GBN).win\\n #Set the ack number to the received value\\n ack = pkt.getlayer(GBN).num\\n if(not in_window(ack)):\\n log.error(\\\"Error: ACK received is out-of-window %s, discard!\\\", pkt)\\n #Create a sender buffer key list for easier manipulation\\n Sender_buffer_keys = list(self.buffer.keys())\\n \\n #Detect the index of the key value that is ack'ed, and erase everything coming beforehand\\n if ((ack-1)%2**self.n_bits) in Sender_buffer_keys:\\n index = Sender_buffer_keys.index((ack-1)%2**self.n_bits)\\n Sender_buffer_keys = Sender_buffer_keys[:index+1]\\n log.debug(\\\"Packet numbers deleted from the sender buffer %s\\\", Sender_buffer_keys)\\n for i in Sender_buffer_keys:\\n del self.buffer[i]\\n log.debug(\\\"The new sender buffer %s\\\", list(self.buffer.keys()))\\n\\n #New unack is the latest ack number\\n self.unack = ack\\n\\n #Question 3.2, detect duplicate acks and go into the transmission state when necessary\\n if(self.Q_3_2 or self.Q_3_4): \\n #implement a queue for checking duplicated ack\\n self.dup_ack.append(ack)\\n log.debug(\\\"duplicated ack buffer is %s\\\", self.dup_ack)\\n if(len(self.dup_ack) >= 3):\\n if(self.dup_ack[-1] == self.dup_ack[-2] == self.dup_ack[-3]):\\n self.dup_ack.clear()\\n log.debug(\\\"Duplicate ACKs for sequence number %s\\\", ack)\\n if(self.Q_3_2):\\n self.dup_ack_hanjing = True\\n self.retransmit_flag = True\\n if(self.Q_3_4):\\n self.ssthresh = self.CWND / 2\\n self.CWND_fp = self.ssthresh\\n self.CWND = math.floor(self.CWND_fp)\\n self.effective_window = min(self.CWND,self.win,self.receiver_win)\\n self.CWND_data.append(self.CWND_fp)\\n log.debug(\\\"CWND log: %s. \\\", self.CWND_data)\\n raise self.SEND()\\n \\n #Q3_3 optional field list construction\\n if(self.SACK == 1 and (pkt.getlayer(GBN).options == 1) and (pkt.getlayer(GBN).hlen >6)):\\n #Get the header length\\n self.hlen = pkt.getlayer(GBN).hlen\\n #Pull optional field parameters\\n if(self.hlen >= 9):\\n self.ledge1 = pkt.getlayer(GBN).ledge1\\n self.len1 = pkt.getlayer(GBN).len1\\n if(self.hlen >= 12):\\n self.ledge2 = pkt.getlayer(GBN).ledge2\\n self.len2 = pkt.getlayer(GBN).len2\\n if(self.hlen == 15):\\n self.ledge3 = pkt.getlayer(GBN).ledge3\\n self.len3 = pkt.getlayer(GBN).len3\\n self.retransmit_flag = True\\n raise self.SEND()\\n\\n\\n # back to SEND state\\n raise self.SEND()\",\n \"def test_acknowledge(client):\\n g.test_authorized_for = []\\n res = client.get(\\\"/v0/acknowledge\\\" + get_request_args)\\n assert \\\"Thanks for acknowledging!\\\" in res.data.decode(\\\"utf-8\\\")\",\n \"def acknowledge(self, subscription, project, ack_ids):\\n response, content = self._http.request(\\n '%s/%s/subscriptions/%s:acknowledge' % (\\n PUBSUB_BASE_URL, project, subscription),\\n body=json.dumps({'ackIds': ack_ids}),\\n method='POST',\\n )\\n if response['status'] == '404':\\n raise NotFoundError(response, json.loads(content))\\n return json.loads(content)\",\n \"def test_make_dispatch_ack_default(self):\\n md_helper = MessageDispatchHelper(\\n MessageHelper(), WorkerHelper('fooconn'))\\n broker = self.setup_broker(md_helper)\\n self.assertEqual(broker.get_messages('vumi', 'fooconn.event'), [])\\n event = yield md_helper.make_dispatch_ack()\\n self.assertEqual(\\n broker.get_messages('vumi', 'fooconn.event'), [event])\\n self.assert_message_fields(event, {\\n 'event_type': 'ack',\\n 'sent_message_id': event['user_message_id'],\\n })\",\n \"def acknowledge_message(self, delivery_tag):\\n logger.info('Acknowledging message %s process %s consumer_id %s', delivery_tag, threading.current_thread, str(self.consumer_id))\\n self._channel.basic_ack(delivery_tag)\",\n \"def handleSent(): \\n global sentAck\\n sentAck = True\",\n \"def transmitPollAck(): \\r\\n global data\\r\\n DW1000.newTransmit()\\r\\n data[0] = C.POLL_ACK\\r\\n DW1000.setDelay(REPLY_DELAY_TIME_US, C.MICROSECONDS)\\r\\n DW1000.setData(data, LEN_DATA)\\r\\n DW1000.startTransmit()\",\n \"def handleSent(): \\r\\n global sentAck\\r\\n sentAck = True\",\n \"def bidACK(dice, query):\\r\\n status=\\\"\\\"\\r\\n strDice = ','.join([str(x) for x in dice])\\r\\n if query == 'b' or query=='B':\\r\\n status = \\\"305 Bid ACK \\\" + strDice\\r\\n elif query == 'c' or query=='C':\\r\\n status = \\\"305 Bid ACK Challenge. Server roll: \\\" +strDice\\r\\n #print (\\\"TEST\\\", status)\\r\\n return status\",\n \"def watch_for_acks(self):\\n while True:\\n ack_message = self.messages['ack'].get()\\n process_ack_thread = Thread(\\n target=self.process_ack, args=(ack_message,), daemon=True)\\n process_ack_thread.start()\",\n \"def acknowledge_message(self, channel, delivery_tag):\\n logger.info('Acknowledging message %s', delivery_tag)\\n channel.basic_ack(delivery_tag)\",\n \"def __call__(\\n self,\\n request: pubsub.AcknowledgeRequest,\\n *,\\n retry: OptionalRetry = gapic_v1.method.DEFAULT,\\n timeout: Optional[float] = None,\\n metadata: Sequence[Tuple[str, str]] = (),\\n ):\\n\\n http_options: List[Dict[str, str]] = [\\n {\\n \\\"method\\\": \\\"post\\\",\\n \\\"uri\\\": \\\"/v1/{subscription=projects/*/subscriptions/*}:acknowledge\\\",\\n \\\"body\\\": \\\"*\\\",\\n },\\n ]\\n request, metadata = self._interceptor.pre_acknowledge(request, metadata)\\n pb_request = pubsub.AcknowledgeRequest.pb(request)\\n transcoded_request = path_template.transcode(http_options, pb_request)\\n\\n # Jsonify the request body\\n\\n body = json_format.MessageToJson(\\n transcoded_request[\\\"body\\\"],\\n including_default_value_fields=False,\\n use_integers_for_enums=True,\\n )\\n uri = transcoded_request[\\\"uri\\\"]\\n method = transcoded_request[\\\"method\\\"]\\n\\n # Jsonify the query params\\n query_params = json.loads(\\n json_format.MessageToJson(\\n transcoded_request[\\\"query_params\\\"],\\n including_default_value_fields=False,\\n use_integers_for_enums=True,\\n )\\n )\\n query_params.update(self._get_unset_required_fields(query_params))\\n\\n query_params[\\\"$alt\\\"] = \\\"json;enum-encoding=int\\\"\\n\\n # Send the request\\n headers = dict(metadata)\\n headers[\\\"Content-Type\\\"] = \\\"application/json\\\"\\n response = getattr(self._session, method)(\\n \\\"{host}{uri}\\\".format(host=self._host, uri=uri),\\n timeout=timeout,\\n headers=headers,\\n params=rest_helpers.flatten_query_params(query_params, strict=True),\\n data=body,\\n )\\n\\n # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception\\n # subclass.\\n if response.status_code >= 400:\\n raise core_exceptions.from_http_response(response)\",\n \"def watch_for_ack_timeout(self):\\n while True:\\n sent_message, time_sent = self.awaiting_ack.get()\\n timeout_time = time.time() + self.ACK_TIMEOUT\\n if time_sent + self.ACK_TIMEOUT < time.time():\\n sent_message.resent += 1\\n if sent_message.resent < 15:\\n self.send_message(sent_message)\\n self._log.write_to_log(\\n \\\"ACK\\\", f\\\"Attempt {sent_message.resent} to resend {sent_message.TYPE_STRING} message {sent_message.uuid} to {sent_message.destination_node.get_name()}\\\")\\n else:\\n self._log.write_to_log(\\n \\\"ACK\\\", f\\\"Drop message to {sent_message.destination_node.get_name()}\\\")\\n else:\\n self.awaiting_ack.put((sent_message, time_sent))\\n\\n time.sleep(.3) # Ensure this thread doesn't hog the queue\",\n \"def open_ack_msg(conn_id):\\n return CCPMessage(CCPMessage.OPEN_CONNECTION_ACK, conn_id=conn_id)\",\n \"def kafka_commit(self):\\n self.kf_producer.flush()\",\n \"def transmitPollAck(): \\n global data\\n DW1000.newTransmit()\\n data[0] = C.POLL_ACK\\n data[17] = anchorID #data[17] is tag Id data[18] is anchor Id\\n data[18] = tagID #data[17] is tag Id data[18] is anchor Id\\n DW1000.setDelay(REPLY_DELAY_TIME_US, C.MICROSECONDS)\\n DW1000.setData(data, LEN_DATA)\\n DW1000.startTransmit()\",\n \"def acknowledge_visitor(visitor):\\n visitor.acknowledged = True\\n visitor.acknowledged_time = datetime.now()\\n visitor.save()\",\n \"def __is_ack(self, ack) -> bool:\\n return ack == ['void']\",\n \"def ack_message(channel, delivery_tag):\\n global logger\\n if channel.is_open:\\n channel.basic_ack(delivery_tag)\\n logger.debug(\\\"Channel is acked!\\\")\\n else:\\n # Channel is already closed, so we can't ACK this message;\\n # log and/or do something that makes sense for your app in this case.\\n logger.debug(\\\"Channel is closed!\\\")\",\n \"def valid_ack(self, message: dict, addition: int = 1) -> bool:\\n return self.safe_incr(self.seq_nr, addition) == message['ack_nr']\",\n \"def ack_transmit(self, data, max_freq_retry=5, max_tx_retry=10):\\n\\t\\ttransmit_success = False\\n\\t\\tfor freq_retry in range(max_freq_retry):\\n\\t\\t\\tfor tx_retry in range(max_tx_retry):\\n\\t\\t\\t\\tself.tb.transmit(data)\\n\\t\\t\\t\\ttime.sleep(0.15)\\n\\t\\t\\t\\tif self.ack_processor.get_last_ack() != self.seqnum:\\n\\t\\t\\t\\t\\tself.log(\\\"Warning: no ACK received, retrying\\\", hue.bad)\\n\\t\\t\\t\\telse:\\n\\t\\t\\t\\t\\tself.log(\\\"ACK received\\\", hue.good)\\n\\t\\t\\t\\t\\ttransmit_success = True\\n\\t\\t\\t\\t\\treturn True\\n\\t\\t\\tself.log(\\\"Warning: switching frequency\\\", hue.bad)\\n\\t\\t\\tself.tb.frequency_switch()\\n\\t\\treturn False\",\n \"def _process_ack_packet(self, rudp_packet):\\n if self._sending_window:\\n self._retire_packets_with_seqnum_up_to(\\n min(rudp_packet.ack, self._next_sequence_number)\\n )\",\n \"def test_process_packet_ack(self):\\n pkt = {'type': 'ack',\\n 'ackId': 140,\\n 'endpoint': '',\\n 'args': []}\\n self.ns.process_packet(pkt)\\n assert not self.environ['socketio'].error.called\",\n \"def handleReceived():\\r\\n global receivedAck\\r\\n receivedAck = True\",\n \"def incr_all_pkts(self, msg):\\n\\n\\t\\tself.__msg.setText(msg)\\n\\n\\t\\tself.__all += 1\\n\\t\\tself.__all_lbl.setText(str(self.__all))\",\n \"def on_ack(self, data):\\n logger.debug('on_ack: %r', data)\\n raise NotAccepted('Server should not be ACKed.')\",\n \"def test_acknowledge_post(client):\\n g.test_authorized_for = []\\n res = client.post(\\\"/v0/acknowledge\\\", json=post_json_data)\\n assert '{\\\"msg\\\":\\\"Thanks for acknowledging!\\\",\\\"status\\\":\\\"ok\\\"}' in res.data.decode(\\\"utf-8\\\")\",\n \"async def nack_event(\\n self, envelope: Envelope, multiple: bool = False, requeue: bool = True\\n ) -> None:\\n await self.channel.basic_client_nack(\\n delivery_tag=envelope.delivery_tag, multiple=multiple, requeue=requeue\\n )\",\n \"def acknowledge_failure(self):\\n self.append(ACK_FAILURE, response=AckFailureResponse(self))\\n self.sync()\",\n \"def handle_packet(self, pkt):\\n logger.info('got a message:{}'.format(pkt))\\n self._sock_rep_to_server.send_pyobj(packet.Ack())\\n \\n state = True\\n extradata = {}\\n \\n if hasattr(self, 'handle_action'):\\n _tmp = self.handle_action(pkt)\\n try:\\n state, data = _tmp\\n extradata['extra'] = data\\n except ValueError:\\n extradata['extra'] = _tmp\\n if extradata:\\n state = False\\n \\n return state, extradata\",\n \"def handleReceived(): \\n global receivedAck\\n receivedAck = True\",\n \"def check_ack_queue(self):\\r\\n try:\\r\\n while True:\\r\\n ack = self.ack_queue.get_nowait()\\r\\n self.handle_ack(ack)\\r\\n except queue.Empty:\\r\\n pass\",\n \"def ack_required(self):\\n v = self[22]\\n v = v >> 1\\n return (v & 0b1) != 0\",\n \"async def handle_message(self, event_msg):\\n msg_logger = _utils.GEventMessageLogger(\\n self._logger, {'msg_id': event_msg.msg_id})\\n\\n msg_logger.debug(f'Acking message.')\\n # \\\"blocking\\\" method but just puts msg on a request queue that\\n # google.cloud.pubsub manages with threads+grpc\\n event_msg._pubsub_msg.ack()\\n\\n msg = 'Acknowledged message in Pub/Sub.'\\n event_msg.append_to_history(msg, self.phase)\\n\\n msg_logger.info(f'Message is done processing.')\",\n \"def test_make_nack_with_sent_message_id(self):\\n md_helper = MessageDispatchHelper(\\n MessageHelper(), WorkerHelper('fooconn'))\\n broker = self.setup_broker(md_helper)\\n self.assertEqual(broker.get_messages('vumi', 'fooconn.event'), [])\\n msg = md_helper.msg_helper.make_outbound('test message')\\n event = yield md_helper.make_dispatch_nack(\\n msg, nack_reason='bogon emissions')\\n self.assertEqual(\\n broker.get_messages('vumi', 'fooconn.event'), [event])\\n self.assert_message_fields(event, {\\n 'event_type': 'nack',\\n 'user_message_id': msg['message_id'],\\n 'nack_reason': 'bogon emissions',\\n })\",\n \"def ticket_submit_ack_callback(self, data):\\n self.output('staged order ticket submission acknowledged: %s' % repr(data))\",\n \"def acknowledge_chat_message_with_http_info(self, id, **kwargs):\\n\\n all_params = ['id', 'read_count']\\n all_params.append('async')\\n all_params.append('_return_http_data_only')\\n all_params.append('_preload_content')\\n all_params.append('_request_timeout')\\n\\n params = locals()\\n for key, val in iteritems(params['kwargs']):\\n if key not in all_params:\\n raise TypeError(\\n \\\"Got an unexpected keyword argument '%s'\\\"\\n \\\" to method acknowledge_chat_message\\\" % key\\n )\\n params[key] = val\\n del params['kwargs']\\n # verify the required parameter 'id' is set\\n if ('id' not in params) or (params['id'] is None):\\n raise ValueError(\\\"Missing the required parameter `id` when calling `acknowledge_chat_message`\\\")\\n\\n\\n collection_formats = {}\\n\\n path_params = {}\\n if 'id' in params:\\n path_params['id'] = params['id']\\n\\n query_params = []\\n\\n header_params = {}\\n\\n form_params = []\\n local_var_files = {}\\n\\n body_params = None\\n if 'read_count' in params:\\n body_params = params['read_count']\\n # HTTP header `Accept`\\n header_params['Accept'] = self.api_client.\\\\\\n select_header_accept(['application/json'])\\n\\n # HTTP header `Content-Type`\\n header_params['Content-Type'] = self.api_client.\\\\\\n select_header_content_type(['application/json'])\\n\\n # Authentication setting\\n auth_settings = ['oauth2_client_credentials_grant', 'oauth2_password_grant']\\n\\n return self.api_client.call_api('/chat/threads/{id}/acknowledge', 'PUT',\\n path_params,\\n query_params,\\n header_params,\\n body=body_params,\\n post_params=form_params,\\n files=local_var_files,\\n response_type=None,\\n auth_settings=auth_settings,\\n async=params.get('async'),\\n _return_http_data_only=params.get('_return_http_data_only'),\\n _preload_content=params.get('_preload_content', True),\\n _request_timeout=params.get('_request_timeout'),\\n collection_formats=collection_formats)\",\n \"def write_ack(self, mid, data=''):\\n __nTry_max = 50\\n\\n for ite in range(__nTry_max):\\n self.write_msg(mid, data)\\n data_ack = self.read_msg(chr(ord(mid)+1))\\n\\n if not data_ack == -1:\\n return data_ack\\n\\n rospy.loginfo(\\\"Fail to find a valid Mid_ACK: %d\\\" % (ord(mid)+1))\\n return -1\",\n \"def ack(self, other, city):\\n pass\",\n \"def check_ack_or_nak(message):\\n value = message.body[-1]\\n\\n if value == 0x06:\\n return\\n elif value == 0x15:\\n raise CommandFailure(command_code=message.command_code)\\n else:\\n raise RuntimeError(\\\"Unexpected ACK/NAK value (0x%02x)\\\" % value)\",\n \"def encode_ack(b_public):\\n\\n return 'ACK;%i' % (b_public)\",\n \"def process_syn_ack(ts_delta, acks, nb_acks, connections, tcp, ip, saddr, daddr, sport, dport, black_list, inverse_conns, ts_syn_timeout, ts_timeout):\\n # The sender of the SYN/ACK is the server\\n if (daddr, dport, saddr, sport) in acks and ((ts_delta - acks[daddr, dport, saddr, sport][co.TIMESTAMP][CLIENT]).total_seconds() < ts_timeout\\n and acks[daddr, dport, saddr, sport][co.C2S] == -1):\\n # Better to check, if not seen, maybe uncomplete TCP connection\\n acks[daddr, dport, saddr, sport][co.C2S] = tcp.ack\\n acks[daddr, dport, saddr, sport][SEQ_S2C].add(tcp.seq)\\n acks[daddr, dport, saddr, sport][HSEQ_S2C][tcp.seq] = [ts_delta, ts_delta]\\n acks[daddr, dport, saddr, sport][co.TIMESTAMP][SERVER] = ts_delta\\n\\n elif (daddr, dport, saddr, sport) in acks and ((ts_delta - acks[daddr, dport, saddr, sport][co.TIMESTAMP][CLIENT]).total_seconds() < ts_timeout\\n and tcp.seq in acks[daddr, dport, saddr, sport][SEQ_S2C]):\\n # SYN/ACK retransmission!\\n conn_id = acks[daddr, dport, saddr, sport][co.CONN_ID]\\n connections[conn_id].flow.attr[co.S2C][co.TIMESTAMP_RETRANS].append((ts_delta,\\n ts_delta - acks[daddr, dport, saddr, sport][HSEQ_S2C][tcp.seq][0],\\n ts_delta - acks[daddr, dport, saddr, sport][HSEQ_S2C][tcp.seq][1],\\n ts_delta - acks[daddr, dport, saddr, sport][co.TIMESTAMP][CLIENT]))\\n acks[daddr, dport, saddr, sport][HSEQ_S2C][tcp.seq][1] = ts_delta\\n acks[daddr, dport, saddr, sport][co.TIMESTAMP][SERVER] = ts_delta\",\n \"def abort_hsdpa_ack_meas(self):\\r\\r\\n loggerCmw = logging.getLogger('abort_hsdpa_ack_meas')\\r\\r\\n self.write('ABORt:WCDMa:SIGN:HACK')\\r\\r\\n loggerCmw.info(\\\"Aborting HSDPA ACK measurement\\\")\\r\\r\\n time.sleep(1)\",\n \"def RETRANSMIT(self):\\n\\n ##############################################\\n # retransmit all the unacknowledged packets #\\n # (all the packets currently in self.buffer) #\\n ##############################################\\n \\n if(self.timeout_hanjing):\\n #If we are coming from the timeout state, retransmit all the buffer\\n for k,v in self.buffer.items():\\n if(self.SACK == 0):\\n header_GBN = GBN(type = 'data', len = len(v), hlen = 6, num = k, win = self.win)\\n else:\\n header_GBN = GBN(type = 'data', options = 1, len = len(v), hlen = 6, num = k, win = self.win)\\n send(IP(src = self.sender, dst = self.receiver) / header_GBN / v)\\n log.debug(\\\"Sending packet number: %s\\\", k)\\n \\n if ((self.Q_3_2 == 1) and (self.dup_ack_hanjing == True) and (self.timeout_hanjing == False)):\\n #just retransmit the packet that has been ack'ed 3 times consequtively\\n header_GBN = GBN(type = 'data', len = len(self.buffer[self.unack]), hlen = 6, num = self.unack, win = self.win)\\n send(IP(src = self.sender, dst = self.receiver) / header_GBN / self.buffer[self.unack])\\n log.debug(\\\"Sending packet number: %s\\\", self.unack)\\n \\n #Question 3.3\\n if(self.SACK == 1 and (self.timeout_hanjing == False) and (self.hlen > 6)):\\n if(self.hlen == 9):\\n optionalHeader_list = list(range(self.ledge1, self.ledge1 + self.len1)) \\n if(self.hlen == 12):\\n optionalHeader_list = list(range(self.ledge1, self.ledge1 + self.len1)) + list(range(self.ledge2, self.ledge2 + self.len2)) \\n if(self.hlen == 15):\\n optionalHeader_list = list(range(self.ledge1, self.ledge1 + self.len1)) + list(range(self.ledge2, self.ledge2 + self.len2)) + list(range(self.ledge3, self.ledge3 + self.len3)) \\n \\n for i in optionalHeader_list:\\n optionalHeader_list[optionalHeader_list.index(i)] = i % 2**self.n_bits\\n \\n #We need to find the difference between the sender buffer, and the optionalHeader_list\\n Sender_buffer_keys = list(self.buffer.keys()) \\n log.debug(\\\"The sender buffer: %s\\\", Sender_buffer_keys)\\n #Trimmed_sender_buffer includes the buffer list only up to the last packet number in the optional header list)\\n trimmed_sender_buffer = Sender_buffer_keys[:Sender_buffer_keys.index(optionalHeader_list[-1])+1]\\n #Retrans_list is the list of keys to be retransmitted\\n log.debug(\\\"Trimmed Sender Buffer: %s\\\", trimmed_sender_buffer)\\n log.debug(\\\"Optional Header List: %s\\\", optionalHeader_list)\\n Retrans_list = [item for item in trimmed_sender_buffer if item not in optionalHeader_list]\\n log.debug(\\\"SACK: packets should be retransmitted: %s\\\", Retrans_list)\\n for i in Retrans_list:\\n header_GBN = GBN(type = 'data', options = 1 , len = len(self.buffer[i]), hlen = 6, num = i, win = self.win)\\n send(IP(src = self.sender, dst = self.receiver) / header_GBN / self.buffer[i])\\n log.debug(\\\"SACK Retransmission: Sending packet number: %s\\\", i)\\n # back to SEND state\\n self.dup_ack_hanjing = False\\n self.timeout_hanjing = False\\n raise self.SEND()\",\n \"def test_make_nack_with_message(self):\\n msg_helper = MessageHelper()\\n msg = msg_helper.make_outbound('test message')\\n event = msg_helper.make_nack(msg)\\n self.assert_message_fields(event, {\\n 'event_type': 'nack',\\n 'user_message_id': msg['message_id'],\\n 'nack_reason': 'sunspots',\\n })\",\n \"def test_make_nack_with_nack_reason(self):\\n msg_helper = MessageHelper()\\n event = msg_helper.make_nack(nack_reason='bogon emissions')\\n self.assert_message_fields(event, {\\n 'event_type': 'nack',\\n 'nack_reason': 'bogon emissions',\\n })\",\n \"def RollDiceACK(dice):\\r\\n #strDice = ','.join([str(x) for x in dice])\\r\\n #status = \\\"205 Roll Dice ACK \\\" + strDice\\r\\n status = \\\"205 Roll Dice ACK \\\" + dice\\r\\n return status\",\n \"def on_publish(self, mqtt_client, userdata, mid):\\n logging.debug(\\\"DEBUG - publish ack received\\\")\",\n \"def test_make_nack_default(self):\\n msg_helper = MessageHelper()\\n event = msg_helper.make_nack()\\n self.assert_message_fields(event, {\\n 'event_type': 'nack',\\n 'nack_reason': 'sunspots',\\n })\",\n \"def process_mptcp_syn_ack(ts_delta, acks, conn_acks, mptcp_connections, tcp, ip, saddr, daddr, sport, dport, black_list, fast_conns, ts_syn_timeout, ts_timeout):\\n # The sender of the SYN/ACK is the server\\n if (daddr, dport, saddr, sport) in acks and ((ts_delta - acks[daddr, dport, saddr, sport][co.TIMESTAMP][CLIENT]).total_seconds() < ts_timeout\\n and acks[daddr, dport, saddr, sport][co.C2S] == -1):\\n # Better to check, if not seen, maybe uncomplete TCP connection\\n acks[daddr, dport, saddr, sport][co.C2S] = tcp.ack\\n acks[daddr, dport, saddr, sport][co.TIMESTAMP][SERVER] = ts_delta\\n conn_acks[acks[daddr, dport, saddr, sport][co.CONN_ID]][co.TIMESTAMP][SERVER] = ts_delta\\n\\n elif (daddr, dport, saddr, sport) in acks and ((ts_delta - acks[daddr, dport, saddr, sport][co.TIMESTAMP][CLIENT]).total_seconds() < ts_timeout\\n and tcp.ack == acks[daddr, dport, saddr, sport][co.C2S]):\\n # SYN/ACK retransmission! But don't do anything special\\n acks[daddr, dport, saddr, sport][co.TIMESTAMP][SERVER] = ts_delta\\n conn_acks[acks[daddr, dport, saddr, sport][co.CONN_ID]][co.TIMESTAMP][SERVER] = ts_delta\",\n \"def ack_frame(self, frame_nb, result):\\n #!!170514:VG:Remove the frame only if ACK OK\\n if frame_nb in self.frames:\\n if not result:\\n self.log.error(\\\"ACK frame error '%s'\\\" % self.frames[frame_nb])\\n else:\\n self.frames.pop(frame_nb)\",\n \"def acknowledge_prepayment(self):\\n self.acknowledge_payment()\",\n \"def nack(self, visibility_timeout_seconds=None):\\n self.consumer.nack(self, visibility_timeout_seconds)\",\n \"def start_lease_expiry_timer(self, ack_ids: Iterable[str]) -> None:\\n with self._add_remove_lock:\\n for ack_id in ack_ids:\\n lease_info = self._leased_messages.get(ack_id)\\n # Lease info might not exist for this ack_id because it has already\\n # been removed by remove().\\n if lease_info:\\n self._leased_messages[ack_id] = lease_info._replace(\\n sent_time=time.time()\\n )\"\n]","isConversational":false},"negative_scores":{"kind":"list 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\"0.64959633\",\n \"0.64412004\",\n \"0.62590575\",\n \"0.6091653\",\n \"0.5954156\",\n \"0.58493274\",\n \"0.5831551\",\n \"0.57382613\",\n \"0.57264817\",\n \"0.56786704\",\n \"0.5646465\",\n \"0.5615886\",\n \"0.56138206\",\n \"0.5597098\",\n \"0.54789007\",\n \"0.5456883\",\n \"0.5329339\",\n \"0.53248435\",\n \"0.53145635\",\n \"0.5300762\",\n \"0.528037\",\n \"0.5273431\",\n \"0.51988655\",\n \"0.51764405\",\n \"0.51158834\",\n \"0.5102013\",\n \"0.50912184\",\n \"0.5054997\",\n \"0.5031492\",\n \"0.5024358\",\n \"0.49769774\",\n \"0.4965822\",\n \"0.4965754\",\n \"0.4960454\",\n \"0.49529654\",\n \"0.49004182\",\n \"0.48830482\",\n \"0.4857843\",\n \"0.47893128\",\n \"0.47851327\",\n \"0.47366884\",\n \"0.47004098\",\n \"0.46942452\",\n \"0.46896914\",\n \"0.4665736\",\n \"0.46627688\",\n \"0.46576697\",\n \"0.46537897\",\n \"0.46437\",\n \"0.4630193\",\n \"0.46261373\",\n \"0.462057\",\n \"0.46075588\",\n \"0.45901006\",\n \"0.4564267\",\n \"0.4550599\",\n \"0.45499822\",\n \"0.45279184\",\n \"0.45191813\",\n \"0.45125404\",\n \"0.44996855\",\n \"0.44982243\",\n \"0.44713455\",\n \"0.44686258\",\n \"0.44365406\",\n \"0.4435106\",\n \"0.44125584\",\n \"0.43987477\",\n \"0.4389684\",\n \"0.4372284\",\n \"0.436581\",\n \"0.436061\",\n \"0.4354174\",\n \"0.43468732\",\n \"0.43442714\",\n \"0.43372494\",\n \"0.4322548\",\n \"0.43200928\",\n \"0.4315183\",\n \"0.43140692\",\n \"0.43046874\",\n \"0.43043134\",\n \"0.4283668\",\n \"0.42466405\",\n \"0.42457512\",\n \"0.421531\",\n \"0.42066008\",\n \"0.41851342\",\n \"0.41718996\",\n \"0.41351444\",\n \"0.41328695\",\n \"0.41270363\",\n \"0.409013\",\n \"0.40785053\",\n \"0.4073515\",\n \"0.4072487\",\n \"0.40558183\",\n \"0.40465903\",\n \"0.40421385\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6130686"},"document_rank":{"kind":"string","value":"4"}}},{"rowIdx":15598,"cells":{"query":{"kind":"string","value":"SplitQuery is the API to facilitate MapReducetype iterations over large data sets (like full table dumps)."},"document":{"kind":"string","value":"def SplitQuery(self, request, context):\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\n context.set_details('Method not implemented!')\n raise NotImplementedError('Method not implemented!')"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def SplitQuery(self, request, context):\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)","def SplitQuery(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\n raise NotImplementedError()","def get_splits(datastore, query, num_splits, partition=None):\n\n # Validate that the number of splits is not out of bounds.\n if num_splits < 1:\n raise ValueError('The number of splits must be greater than 0.')\n\n if num_splits == 1:\n return [query]\n\n _validate_query(query)\n\n splits = []\n scatter_keys = _get_scatter_keys(datastore, query, num_splits, partition)\n last_key = None\n for next_key in _get_split_key(scatter_keys, num_splits):\n splits.append(_create_split(last_key, next_key, query))\n last_key = next_key\n\n splits.append(_create_split(last_key, None, query))\n return splits","def _create_split(last_key, next_key, query):\n if not (last_key or next_key):\n return query\n\n split_query = query_pb2.Query()\n split_query.CopyFrom(query)\n composite_filter = split_query.filter.composite_filter\n composite_filter.op = CompositeFilter.AND\n\n if query.HasField('filter'):\n composite_filter.filters.add().CopyFrom(query.filter)\n\n if last_key:\n lower_bound = composite_filter.filters.add()\n lower_bound.property_filter.property.name = KEY_PROPERTY_NAME\n lower_bound.property_filter.op = PropertyFilter.GREATER_THAN_OR_EQUAL\n lower_bound.property_filter.value.key_value.CopyFrom(last_key)\n\n if next_key:\n upper_bound = composite_filter.filters.add()\n upper_bound.property_filter.property.name = KEY_PROPERTY_NAME\n upper_bound.property_filter.op = PropertyFilter.LESS_THAN\n upper_bound.property_filter.value.key_value.CopyFrom(next_key)\n\n return split_query","def produce_query_batches(self):\n pass","def support_query_split(datasets, query_size):\n support_datasets = {}\n query_datasets = {}\n for task, dataset in datasets.items():\n support_query_split = dataset.train_test_split(test_size=query_size)\n support_datasets[task] = support_query_split[\"train\"]\n query_datasets[task] = support_query_split[\"test\"]\n return support_datasets, query_datasets","def split_datasets(ql_file, nl_question_file, output_dir, split):\n\n with io.open(ql_file, encoding='utf-8') as query_org, \\\n io.open(nl_question_file, encoding='utf8') as nl_org:\n ql = query_org.readlines()\n nl = nl_org.readlines()\n\n split = split / 100\n\n train_ql, val_ql, train_nl, val_nl = train_test_split(ql, nl,\n train_size=split,\n random_state=42,\n shuffle=True)\n\n with io.open(output_dir + \"-train.ql\", 'w', encoding='utf-8') \\\n as ql_train, \\\n io.open(output_dir + \"-val.ql\", 'w', encoding='utf-8') \\\n as ql_val, \\\n io.open(output_dir + \"-train.nl\", 'w', encoding='utf-8') \\\n as nl_train, \\\n io.open(output_dir + \"-val.nl\", 'w', encoding='utf-8') \\\n as nl_val:\n ql_train.writelines(train_ql)\n ql_val.writelines(val_ql)\n nl_train.writelines(train_nl)\n nl_val.writelines(val_nl)","def test_split_queries(self):\n la_provider = self.la_provider\n\n start = datetime.utcnow() - pd.Timedelta(\"5H\")\n end = datetime.utcnow() + pd.Timedelta(\"5min\")\n delta = pd.Timedelta(\"1H\")\n\n ranges = QueryProvider._calc_split_ranges(start, end, delta)\n result_queries = la_provider.all_queries.list_alerts(\n \"print\", start=start, end=end, split_query_by=\"1H\"\n )\n queries = result_queries.split(\"\\n\\n\")\n self.assertEqual(len(queries), 5)\n\n for idx, (st_time, e_time) in enumerate(ranges):\n self.assertIn(st_time.isoformat(sep=\"T\") + \"Z\", queries[idx])\n self.assertIn(e_time.isoformat(sep=\"T\") + \"Z\", queries[idx])\n self.assertIn(start.isoformat(sep=\"T\") + \"Z\", queries[0])\n self.assertIn(end.isoformat(sep=\"T\") + \"Z\", queries[-1])","def multiquery(self, query_chunks, **kwargs):\n return query.multiquery(self._host, self._session, query_chunks, **kwargs)","def mapped_split(reddit_dir, data_set_name, mapped_col, result_col, num_splits):\n\n table_files = os.listdir(os.path.join(reddit_dir, data_set_name))\n args_list = [\n (reddit_dir, data_set_name, table_fname, mapped_col, result_col, num_splits)\n for table_fname in table_files\n ]\n\n process = psutil.Process(os.getpid())\n logger.debug(\"PID: %d, Memory usage: %.1f GB\" % (process.pid, process.memory_info().rss / 1e9))\n\n logger.debug(\"PID: %d, forking...\" % process.pid)\n pool = mp.Pool(pool_size)\n pool.map(unpack_mapped_split_core, args_list)","def queries_iter(self, input):\n\n queries = self._split(input)\n while queries:\n for sql in queries:\n delimiter = self._delimiter\n sql = queries.pop(0)\n if sql.endswith(delimiter):\n trailing_delimiter = True\n sql = sql.strip(delimiter)\n else:\n trailing_delimiter = False\n\n yield sql\n\n # if the delimiter was changed by the last command,\n # re-split everything, and if we previously stripped\n # the delimiter, append it to the end\n if self._delimiter != delimiter:\n combined_statement = ' '.join([sql] + queries)\n if trailing_delimiter:\n combined_statement += delimiter\n queries = self._split(combined_statement)[1:]","def chunk_queries(queries: List) -> List[List]:\n chunks: List[List] = []\n # Octopart can only handle 20 queries per request, so split into chunks.\n for chunk in chunked(queries):\n chunks.extend(split_chunk(chunk))\n return chunks","def batched_query(self, sql):\r\n\r\n result_sets = []\r\n messages = \"\"\r\n query = []\r\n last_query=\"\"\r\n\r\n batches = re.split(\"^\\s*(GO(?:\\s+[0-9]+)?)\\s*(?:--.*)?$\",sql,flags=re.M|re.I)\r\n # print(batches)\r\n for b in batches:\r\n if b.upper() == \"GO\":\r\n # execute one\r\n query.append(last_query)\r\n continue\r\n else:\r\n match = re.match(\"^GO\\s+([0-9]+)$\",b,re.I)\r\n if match is not None:\r\n #execute many\r\n for i in range(0,int(match.group(1))):\r\n query.append(last_query)\r\n else:\r\n # not a Go statment\r\n last_query = b\r\n query.append(last_query)\r\n\r\n # print(query)\r\n for q in query:\r\n r = self.query(q)\r\n if r is not None:\r\n result_sets.extend(r)\r\n messages += self.messages\r\n\r\n self.messages = messages\r\n return result_sets","def chunk(self, shape, split) -> NotImplementedError:\n raise NotImplementedError()","def mapped_split(reddit_directory, data_set_name, mapped_col, result_col, num_splits):\n\n table_files = os.listdir(os.path.join(reddit_directory, data_set_name))\n args_list = [\n (reddit_directory, data_set_name, table_fname, mapped_col, result_col, num_splits)\n for table_fname in table_files\n ]\n\n pool = mp.Pool(pool_size)\n pool.map(unpack_mapped_split_core, args_list)","def _multi_query_execution(self):\n multi_query_staging = self.query.split(';')\n for query in multi_query_staging:\n self.query = query\n self._execute_command()","def _chunked_query(self, model_class, chunk_field, items, chunk_size=500, **kwargs):\r\n res = chain.from_iterable(\r\n self._query(model_class, **dict([(chunk_field, chunk)] + kwargs.items()))\r\n for chunk in chunks(items, chunk_size)\r\n )\r\n return res","def split_data(basedir, data_split=0.80):\n manip = data_manipulator(basedir)\n manip.train_test_split(data_split=data_split)","def split_data_set(reddit_path, data_set_name, on, num_splits, target_directories, map_columns=None):\n targets = {}\n for i in range(num_splits):\n targets[i] = os.path.join(target_directories[i], data_set_name)\n mkdir(targets[i])\n\n full_sub_data_path = os.path.join(reddit_path, data_set_name)\n data_files = map(lambda f: os.path.join(full_sub_data_path, f), os.listdir(full_sub_data_path))\n args_list = [(on, table_file, targets, num_splits, map_columns) for table_file in data_files]\n\n pool = mp.Pool(pool_size)\n pool.map(unpack_split_file_with_map, args_list)","def split(self, params):\n\n if \"train_df\" in params.keys():\n self.df = params[\"train_df\"]\n if \"test_df\" in params.keys():\n self.df = pd.concat([self.df, params[\"test_df\"]])\n if \"n_splits\" in params.keys():\n self.n_splits = params[\"n_splits\"]\n if \"shuffle\" in params.keys():\n self.shuffle = params[\"shuffle\"]\n if \"random_state\" in params.keys():\n self.random_state = params[\"random_state\"]\n\n self.__validate_input()\n\n n_samples = num_of_samples(self.df)\n\n if self.n_splits > n_samples:\n raise ValueError(\n f\"Cannot have number of splits {self.n_splits} > number of\"\n f\" samples {n_samples}\"\n )\n\n indices = np.arange(n_samples)\n for test_indices in self.__iter_test_indices(n_samples):\n train_indices = indices[np.logical_not(test_indices)]\n test_indices = indices[test_indices]\n yield train_indices, test_indices","def split(input, output, fields, delimiter, encoding, verbose, format_in, zipfile, gzipfile, chunksize, filter):\n if verbose:\n enableVerbose()\n options = {}\n options['delimiter'] = delimiter\n options['fields'] = fields\n options['output'] = output\n options['encoding'] = encoding\n options['format_in'] = format_in\n options['zipfile'] = zipfile\n options['gzipfile'] = gzipfile\n options['chunksize'] = chunksize\n options['filter'] = filter\n acmd = Selector()\n acmd.split(input, options)\n pass","def paginate_query_new(\n self,\n node,\n project_id=None,\n props=[],\n args=None,\n chunk_size=5000,\n offset=0,\n format=\"json\",\n ):\n props = list(set([\"id\", \"submitter_id\"] + props))\n properties = \" \".join(map(str, props))\n\n if project_id != None:\n outname = \"query_{}_{}.tsv\".format(project_id, node)\n if args == None:\n query_txt = \"\"\"{%s (first: %s, offset: %s, project_id:\"%s\"){%s}}\"\"\" % (\n node,\n chunk_size,\n offset,\n project_id,\n properties,\n )\n else:\n query_txt = (\n \"\"\"{%s (first: %s, offset: %s, project_id:\"%s\", %s){%s}}\"\"\"\n % (node, chunk_size, offset, project_id, args, properties)\n )\n else:\n outname = \"query_{}.tsv\".format(node)\n if args == None:\n query_txt = \"\"\"{%s (first: %s, offset: %s){%s}}\"\"\" % (\n node,\n chunk_size,\n offset,\n properties,\n )\n else:\n query_txt = \"\"\"{%s (first: %s, offset: %s, %s){%s}}\"\"\" % (\n node,\n chunk_size,\n offset,\n args,\n properties,\n )\n\n total = {}\n total[\"data\"] = {}\n total[\"data\"][node] = []\n\n records = list(range(chunk_size))\n while len(records) == chunk_size:\n\n res = self.sub.query(query_txt)\n\n if \"data\" in res:\n records = res[\"data\"][node]\n total[\"data\"][node] += records # res['data'][node] should be a list\n offset += chunk_size\n\n elif \"error\" in res:\n print(res[\"error\"])\n if chunk_size > 1:\n chunk_size = int(chunk_size / 2)\n print(\"\\tHalving chunk_size to: {}.\".format(chunk_size))\n else:\n print(\"\\tQuery timing out with chunk_size of 1!\")\n exit(1)\n\n else:\n print(\"Query Error: {}\".format(res))\n\n print(\"\\tTotal records retrieved: {}\".format(len(total[\"data\"][node])))\n\n if format == \"tsv\":\n df = json_normalize(total[\"data\"][node])\n df.to_csv(outname, sep=\"\\t\", index=False)\n return df\n else:\n return total","def split(self):\n st = time()\n tokens = self._build_args.tokens\n\n for token_split in IStorage._tokens_partitions(tokens, config.min_number_of_tokens,\n config.number_of_partitions):\n storage_id = uuid.uuid4()\n log.debug('assigning to %s %d tokens', str(storage_id), len(token_split))\n new_args = self._build_args._replace(tokens=token_split, storage_id=storage_id)\n self.__class__._store_meta(new_args)\n\n yield self.__class__.build_remotely(new_args)\n log.debug('completed split of %s in %f', self.__class__.__name__, time() - st)","async def split_large_groups_impl(config):\n async with create_sessionmaker(config)() as dbsession:\n progress = ClickIndeterminate(\"Splitting large groups\")\n progress.start()\n splitting = True\n stmt = select(Group).options(selectinload(Group.items), selectinload(Group.children))\n while splitting:\n splitting = False\n result = await dbsession.execute(stmt)\n for group in result.scalars():\n if len(group.children) == 0:\n if len(group.items) > 120 and len(group.items) < 300: # noqa: PLR2004\n if split_by_year(config, dbsession, group):\n splitting = True\n else:\n split_by_similarity(dbsession, group)\n splitting = True\n elif len(group.items) >= 300: # noqa: PLR2004\n if split_by_attribute(dbsession, group, \"concepts\"):\n splitting = True\n elif split_by_attribute(dbsession, group, \"subjects\"):\n splitting = True\n elif split_by_attribute(dbsession, group, \"materials\"):\n splitting = True\n elif split_by_attribute(dbsession, group, \"techniques\"):\n splitting = True\n elif split_by_year(config, dbsession, group):\n splitting = True\n else:\n split_by_similarity(dbsession, group)\n splitting = True\n await dbsession.commit()\n progress.stop()","def readDBchunks(self, tablename, orderField, chunksize=50000,\n selectOptions=None, limit=None, filterOptions=None, verbose=False):\n\n if limit:\n remaining = limit\n next_chunk = min(remaining, chunksize)\n else:\n next_chunk = chunksize\n\n cont = 0\n \n selectOptions = selectOptions + ', ' + orderField\n\n df = self.readDBtable(tablename, limit=next_chunk, selectOptions=selectOptions,\n filterOptions = filterOptions, orderOptions=orderField)\n\n while (len(df)):\n cont = cont+len(df)\n if verbose:\n print('[DBManager (readDBchunks)] Number of rows read so far:', cont)\n if limit:\n remaining = limit - cont\n next_chunk = min(remaining, chunksize)\n else:\n next_chunk = chunksize\n yield df.iloc[:,:-1]\n\n #Next we need to start from last retrieved element\n filtercondition = orderField + '>' + str(df.iloc[:,-1][len(df)-1])\n if filterOptions:\n filtercondition = filtercondition + ' AND ' + filterOptions\n \n if next_chunk>0:\n df = self.readDBtable(tablename, limit=next_chunk, selectOptions=selectOptions,\n filterOptions = filtercondition, orderOptions=orderField)\n else:\n #If maximum number of records has been reached, set df to empty list to exit\n df = []","def _split(self, split, randomise=False, **kwargs):\r\n # Copy split to prevent modifying outside arguments\r\n split = split.copy()\r\n # Compute total\r\n total = sum(split.values())\r\n # If split contains floats, convert to integers\r\n if isinstance(total, float):\r\n assert_msg = 'Not enough data! ' \\\r\n + f'Split requires a total of {total*100}%. ' \\\r\n + 'Split should not exceed 100%.'\r\n assert total <= 1, assert_msg\r\n # Add 'rest' subset if not all data is used in split\r\n if total < 1:\r\n split['rest'] = 1 - total\r\n split = self._float_split_to_int(split)\r\n total = sum(split.values())\r\n # Create subsets based off integer values\r\n if isinstance(total, int):\r\n assert_msg = 'Not enough data! ' \\\r\n + f'Split requires a total of {total} data entries ' \\\r\n + f'but only {len(self.data)} are available.'\r\n assert total <= len(self.data), assert_msg\r\n # Add 'rest' subset if not all data is used in split\r\n if total < len(self.data):\r\n split['rest'] = len(self.data) - total\r\n # Create subsets\r\n index = 0\r\n for name, length in split.items():\r\n subset_name = f'{self.name}.{name}'\r\n subset_data = self.data[index:index + length]\r\n subset_seed = self.seed\r\n if self.seed is not None:\r\n subset_seed += sum([ord(c) for c in name]) + length\r\n subset = self._make_subset(subset_name,\r\n subset_data,\r\n randomise=randomise,\r\n seed=subset_seed,\r\n **kwargs\r\n )\r\n setattr(self, name, subset)\r\n index += length\r\n # Replace data with references to subsets\r\n self.data = []\r\n for name in split.keys():\r\n self.data.append(getattr(self, name, None))\r\n # Indicate that this is a superset\r\n self.is_superset = True","def run_query(\n self, project_id, partition_id, read_options=None, query=None, gql_query=None\n ):\n request_pb = _datastore_pb2.RunQueryRequest(\n project_id=project_id,\n partition_id=partition_id,\n read_options=read_options,\n query=query,\n gql_query=gql_query,\n )\n return _rpc(\n self.client._http,\n project_id,\n \"runQuery\",\n self.client._base_url,\n self.client._client_info,\n request_pb,\n _datastore_pb2.RunQueryResponse,\n )","def split(self) -> GQASplit:\n return self._split","def mapped_split_core(reddit_path, data_set_name, table_file_name, mapped_col, result_col, num_splits):\n\n logger.info(\"Processing: %s\" % data_set_name)\n table_file_path = os.path.join(reddit_path, data_set_name, table_file_name)\n\n logger.debug(\"Reading: %s\" % table_file_name)\n df = pd.read_csv(table_file_path, engine='python')\n\n process = psutil.Process(os.getpid())\n logger.debug(\"PID: %d, Memory usage: %.1f GB\" % (process.pid, process.memory_info().rss / 1e9))\n\n def get_base_submission(target_fullname):\n if target_fullname in comment_post_mapping:\n return comment_post_mapping[target_fullname]\n else:\n return target_fullname\n\n def get_base_from_cpp(target_fullname):\n if libdict.contains(target_fullname) == \"True\":\n return libdict.get_value(target_fullname)\n return target_fullname\n\n logger.debug(\"Mapping column: %s\" % table_file_name)\n # df[result_col] = df[mapped_col].apply(get_base_submission) # The vanilla version\n df[result_col] = df[mapped_col].apply(get_base_from_cpp) # the CPP version\n df[result_col].fillna(\"missing\", inplace=True)\n\n # Make a map of output files for each of the splits as well as creating the\n # directories that they belong in\n output_file_map = {}\n for i in target_directories:\n target_sub_dir = os.path.join(target_directories[i], data_set_name)\n mkdir(target_sub_dir)\n\n output_file_map[i] = os.path.join(target_sub_dir, table_file_name)\n\n logger.debug(\"Splitting: %s\" % table_file_name)\n split_data_frame(df, result_col, lambda s: hash(s) % num_splits, output_file_map)","def _query_iterator(result, chunksize, columns, index_col=None, coerce_float=True, parse_dates=None):\n\n while True:\n data = result.fetchmany(chunksize)\n if not data:\n break\n else:\n yield _wrap_result(data, columns, index_col=index_col,\n coerce_float=coerce_float,\n parse_dates=parse_dates)","def load_data(base_path, experiment_name, train_split_fraction, no_operators, no_sample_tuples, expansion_factor,\n dim_predicate_embedding, size_threshold):\n filename_prefix = path.join(base_path, \"data\", experiment_name)\n parser = Parser(no_operators, no_sample_tuples, dim_predicate_embedding)\n table_rows = pd.read_csv(filename_prefix + \".csv\")['tablerows']\n table_sizes_kb = pd.read_csv(filename_prefix + \".csv\")['tablesizekb']\n queries, num_colums, num_tables, tables_to_columns = parser.parse_file(filename_prefix + \".json\")\n\n # Shuffle for train-test-split -- queries based on the same plan can only end in train or test set\n random.shuffle(queries)\n\n # Postprocess Queries\n expanded_queries = []\n for query in queries:\n q_operator_node, q_runtime, q_index = query\n\n # Only consider tables with size over a certain threshold\n if table_sizes_kb[q_index] >= size_threshold:\n # Normalize runtime by table sizes otherwise it does not work\n query = (q_operator_node, q_runtime / table_rows[q_index], q_index)\n\n # Expand/vary queries\n for i in range(expansion_factor):\n query_copy = deepcopy(query)\n vary_query(query_copy[0], num_colums, tables_to_columns)\n expanded_queries.append(query_copy)\n\n split_point = int(len(expanded_queries) * train_split_fraction)\n return expanded_queries[:split_point], expanded_queries[split_point:], num_colums, num_tables","def split_input(self):\n namenode = self.runner.namenode\n splitter = Splitter(RECORDS_PER_BLOCK)\n results = []\n input_files = []\n for fname in self.inputs:\n input_files.append(RecordFile(fname, namenode))\n\n taskid = 0\n for block in splitter.split(input_files):\n fname = map_input(self.id, taskid)\n taskid += 1\n namenode.create_file(fname)\n\n bytes_written = 0\n for record in block:\n bytes_written += namenode.write_file(fname, bytes_written,\n record)\n\n namenode.close_file(fname)\n results.append(fname)\n self.open_files.append(fname)\n\n for file_ in input_files:\n file_.close()\n\n return results","def iterate_minibatches(*to_split, **kwargs):\n batchsize=1\n shuffle=False\n if 'batchsize' in kwargs:\n batchsize = kwargs['batchsize']\n \n if 'shuffle' in kwargs:\n shuffle = kwargs['shuffle']\n\n res = [np.array(x) for x in to_split]\n size = res[0].shape[0]\n for x in res:\n assert x.shape[0] == size\n if shuffle:\n indices = np.arange(size)\n np.random.shuffle(indices)\n for start_idx in range(0, size, batchsize):\n if shuffle:\n excerpt = indices[start_idx:start_idx + batchsize]\n else:\n excerpt = slice(start_idx, start_idx + batchsize)\n yield [x[excerpt] for x in res] if len(res) != 1 else x[excerpt]","def run(self):\n # pylint: disable=too-many-locals\n loop_start = time.clock()\n partitions = []\n for item in self._results:\n partitions.append(\n Partition(item.name, item.dataframe, self.PARTITION_SIZE)\n )\n if item.name == self._primary_dataset:\n primary_dataset = partitions[-1]\n\n index = 0\n while index < self.PARTITION_SIZE:\n merge_sets = []\n combination = ['\\033[1m{0}\\033[0m'.format(self._mappings[self._primary_dataset])]\n for partition in partitions:\n if partition.name != self._primary_dataset:\n merge_sets.append({'name': partition.name, 'data': partition.next()})\n combination.append(self._mappings[partition.name])\n\n Logger().info(\n 'Running data extraction. Index {0} of {1} partitions, (combination: {2}, queries: {3})'.format(\n index,\n self.PARTITION_SIZE,\n ''.join(combination),\n len(self._queries)\n )\n )\n\n for size in range(self.PARTITION_SIZE):\n self._running = []\n q_start = time.clock()\n merge_table = self.merge(\n merge_sets + [{'name': primary_dataset.name, 'data': primary_dataset.next()}]\n )\n m_end = '{0:.2f}'.format(float(time.clock() - q_start))\n Logger().debug(\n 'Combination {0} merge table completed in {1} seconds ({2} rows)'.format(\n ''.join(combination),\n m_end,\n len(merge_table.index)\n )\n )\n for query in self._queries:\n self._running.append(\n DataThreader(merge_table, query, self._unique_columns)\n )\n\n self.monitor()\n times = [item.duration for item in self._running]\n message = '{4}\\n Combination {0}, Index {5}/{1}'\n message += ', merge_table size: {2}.\\n Average time per query {3}'\n Logger().debug(\n message.format(\n ''.join(combination),\n index,\n len(merge_table.index),\n times,\n [len(query.results.index) for query in self._queries],\n size\n )\n )\n del times\n del merge_table\n del self._running\n\n end_time = math.floor(time.clock() - loop_start)\n Logger().info('=========================================================================================')\n Logger().info(\n 'Completed partition {0} in {1} seconds. {2} queries, combination: {3}'.format(\n index,\n end_time,\n len(self._queries),\n ''.join(combination)\n )\n )\n Logger().info('=========================================================================================')\n primary_dataset.reset()\n index += 1\n\n Logger().info('Completed data extraction')\n self._complete = True","def _paginate_query_across_partitioned_databases(model_class, q_expression, load_source):\n from corehq.messaging.scheduling.scheduling_partitioned.models import (\n CaseAlertScheduleInstance,\n CaseTimedScheduleInstance,\n )\n\n if model_class not in (CaseAlertScheduleInstance, CaseTimedScheduleInstance):\n raise TypeError(\"Expected CaseAlertScheduleInstance or CaseTimedScheduleInstance\")\n\n db_names = get_db_aliases_for_partitioned_query()\n for db_name in db_names:\n for row in _paginate_query(db_name, model_class, q_expression, load_source):\n yield row","def split(self, place_leaf_splitted):\n raise NotImplementedError","def split_data_set(data_set, index, value, part=0):\n # save the subdataset\n res_data_set = []\n \n for entry in data_set:\n # find the data set to the left of the partition point\n if part == 0 and float(entry[index])<= value: #求划分点左侧的数据集\n reduced_entry = entry[:index]\n # after partitioning, the value of the index column in the data is removed\n reduced_entry.extend(entry[index + 1:]) \n res_data_set.append(reduced_entry)\n # find the data set to the right of the partition point\n if part ==1 and float(entry[index])> value: \n reduced_entry = entry[:index]\n reduced_entry.extend(entry[index + 1:])\n res_data_set.append(reduced_entry)\n return res_data_set","def get_all_batches(self, query, bind_vars=None, batch_size=1000):\n write_ops = [\"INSERT\", \"UPDATE\", \"REPLACE\", \"REMOVE\", \"UPSERT\"]\n if any(ele in query.upper() for ele in write_ops):\n raise C8QLGetAllBatchesError(\n \"Write operations provided in the query. Only read operations can be provided\"\n )\n\n cursor = self.execute(\n query=query, bind_vars=bind_vars, batch_size=batch_size, stream=True\n )\n while cursor.has_more():\n cursor.fetch()\n\n result = clean_doc(cursor.batch())\n return result","def split_chunks(\n key: core.ChunkKey,\n dataset: xarray.Dataset,\n target_chunks: Mapping[str, int],\n) -> Iterator[Tuple[core.ChunkKey, xarray.Dataset]]:\n # This function splits consolidated arrays into blocks of new sizes, e.g.,\n # ⌈x_00 x_01 ...⌉ ⌈⌈x_00⌉ ⌈x_01⌉ ...⌉\n # X = |x_10 x_11 ...| = ||x_10| |x_11| ...|\n # |x_20 x_21 ...| |⌊x_20⌋ ⌊x_21⌋ ...|\n # ⌊ ... ... ...⌋ ⌊ ... ... ...⌋\n # and emits them as (ChunkKey, xarray.Dataset) pairs.\n all_bounds = []\n for dim, chunk_size in target_chunks.items():\n start = key.get(dim, 0)\n stop = start + dataset.sizes[dim]\n all_bounds.append(_split_chunk_bounds(start, stop, chunk_size))\n\n for bounds in itertools.product(*all_bounds):\n offsets = dict(key)\n slices = {}\n for dim, (start, stop) in zip(target_chunks, bounds):\n base = key.get(dim, 0)\n offsets[dim] = start\n slices[dim] = slice(start - base, stop - base)\n\n new_key = core.ChunkKey(offsets)\n new_chunk = dataset.isel(slices)\n yield new_key, new_chunk","def split(self, splits, catchall=False):\r\n raise NotImplementedError()","def Run(self):\n results = []\n count = 1\n log_level = logging.DEBUG - 1\n for bound_query in self.__bound_queries:\n logging.log(log_level, 'Running query #%i' % count)\n results.append(bound_query.Run())\n count += 1\n\n def IterateResults(results):\n \"\"\"Iterator function to return all results in sorted order.\n\n Iterate over the array of results, yielding the next element, in\n sorted order. This function is destructive (results will be empty\n when the operation is complete).\n\n Args:\n results: list of result iterators to merge and iterate through\n\n Yields:\n The next result in sorted order.\n \"\"\"\n result_heap = []\n for result in results:\n heap_value = MultiQuery.SortOrderEntity(result, self.__orderings)\n if heap_value.GetEntity():\n heapq.heappush(result_heap, heap_value)\n\n used_keys = set()\n\n while result_heap:\n top_result = heapq.heappop(result_heap)\n\n results_to_push = []\n if top_result.GetEntity().key() not in used_keys:\n yield top_result.GetEntity()\n else:\n pass\n\n used_keys.add(top_result.GetEntity().key())\n\n results_to_push = []\n while result_heap:\n next = heapq.heappop(result_heap)\n if cmp(top_result, next):\n results_to_push.append(next)\n break\n else:\n results_to_push.append(next.GetNext())\n results_to_push.append(top_result.GetNext())\n\n for popped_result in results_to_push:\n if popped_result.GetEntity():\n heapq.heappush(result_heap, popped_result)\n\n return IterateResults(results)","def mapped_split_core(reddit_directory, data_set_name, table_fname, mapped_col, result_col, num_splits):\n\n table_file_path = os.path.join(reddit_directory, data_set_name, table_fname)\n logger.debug(\"Loading: %s\" % table_fname)\n df = pd.read_csv(table_file_path, engine='python')\n\n logger.debug(\"Mapping column \\\"%s\\\" from Redis ...\" % mapped_col)\n redis_db = get_redis_db(redis_pool)\n df[result_col] = get_values_from_redis(redis_db, df[mapped_col], num_chunks=7)\n df[result_col].fillna(df[mapped_col], inplace=True)\n\n # Make a map of output files for each of the splits as well as creating the\n # directories that they belong in\n output_file_map = {}\n for i in target_directories:\n target_sub_dir = os.path.join(target_directories[i], data_set_name)\n mkdir(target_sub_dir)\n output_file_map[i] = os.path.join(target_sub_dir, table_fname)\n\n logger.debug(\"Splitting: %s\" % table_fname)\n split_data_frame(df, result_col, lambda s: hash(s) % num_splits, output_file_map)","def _split_chunk(self, collection_name: str, key: int):\n def split_command():\n self._mongo_client.admin.command('split', collection_name, middle={SHARD_KEY: key})\n self._try_until_done(split_command)\n self._chunks[collection_name][key] = MAIN_MONGO_SHARD_NAME\n logging.info(f\"MongoAgent: Split chunk of {collection_name} at {key}\")","def execute_query(self):\n query_sum = self.initialize_totals()\n data = []\n\n with tenant_context(self.tenant):\n query = self.query_table.objects.filter(self.query_filter)\n query_data = query.annotate(**self.annotations)\n group_by_value = self._get_group_by()\n\n query_group_by = [\"date\"] + group_by_value\n query_order_by = [\"-date\"]\n query_order_by.extend([self.order]) # add implicit ordering\n\n query_data = query_data.values(*query_group_by).annotate(**self.report_annotations)\n\n if self._limit and query_data:\n query_data = self._group_by_ranks(query, query_data)\n if not self.parameters.get(\"order_by\"):\n # override implicit ordering when using ranked ordering.\n query_order_by[-1] = \"rank\"\n\n # Populate the 'total' section of the API response\n if query.exists():\n aggregates = self._mapper.report_type_map.get(\"aggregates\")\n metric_sum = query.aggregate(**aggregates)\n query_sum = {key: metric_sum.get(key) for key in aggregates}\n\n query_data, total_capacity = self.get_cluster_capacity(query_data)\n if total_capacity:\n query_sum.update(total_capacity)\n\n if self._delta:\n query_data = self.add_deltas(query_data, query_sum)\n is_csv_output = self.parameters.accept_type and \"text/csv\" in self.parameters.accept_type\n\n query_data = self.order_by(query_data, query_order_by)\n\n if is_csv_output:\n if self._limit:\n data = self._ranked_list(list(query_data))\n else:\n data = list(query_data)\n else:\n # Pass in a copy of the group by without the added\n # tag column name prefix\n groups = copy.deepcopy(query_group_by)\n groups.remove(\"date\")\n data = self._apply_group_by(list(query_data), groups)\n data = self._transform_data(query_group_by, 0, data)\n\n sum_init = {\"cost_units\": self._mapper.cost_units_key}\n if self._mapper.usage_units_key:\n sum_init[\"usage_units\"] = self._mapper.usage_units_key\n query_sum.update(sum_init)\n\n ordered_total = {\n total_key: query_sum[total_key] for total_key in self.report_annotations.keys() if total_key in query_sum\n }\n ordered_total.update(query_sum)\n\n self.query_sum = ordered_total\n self.query_data = data\n return self._format_query_response()","def splitQuery(query):\n triples = list()\n bgp = re.search('WHERE {(.*)}', query).group(1)\n for triple in bgp.split(' . '):\n triples.append(triple.strip())\n return triples","def kb_train_test_split(test_size, random_state):\n\n cnxn_path = \"/polyaxon-data/goldenretriever/db_cnxn_str.txt\"\n conn = pyodbc.connect(open(cnxn_path, 'r').read())\n\n SQL_Query = pd.read_sql_query('''SELECT dbo.query_labels.id, dbo.query_db.query_string, \\\n dbo.kb_clauses.processed_string, dbo.kb_raw.kb_name, dbo.kb_raw.type FROM dbo.query_labels \\\n JOIN dbo.query_db ON dbo.query_labels.query_id = dbo.query_db.id \\\n JOIN dbo.kb_clauses ON dbo.query_labels.clause_id = dbo.kb_clauses.id \\\n JOIN dbo.kb_raw ON dbo.kb_clauses.raw_id = dbo.kb_raw.id''', conn)\n\n df = pd.DataFrame(SQL_Query).set_index('id')\n kb_names = df['kb_name'].unique()\n\n train_dict = dict()\n test_dict = dict()\n\n train_idx_all = []\n test_idx_all = []\n\n for kb_name in kb_names:\n kb_id = df[df['kb_name'] == kb_name].index.values\n train_idx, test_idx = train_test_split(kb_id, test_size=test_size,\n random_state=random_state)\n \n train_dict[kb_name] = train_idx\n test_dict[kb_name] = test_idx\n \n for k,v in train_dict.items():\n for idx in v:\n train_idx_all.append(idx)\n \n for k,v in test_dict.items():\n for idx in v:\n test_idx_all.append(idx)\n \n return df, train_dict, test_dict, train_idx_all, test_idx_all","def batch_split(self) -> np.array:\n pass","def test_split(range_size, partition_size):\n dump = Mock()\n\n iterable = list(range(range_size))\n\n list(_split(partition_size=partition_size, dump=dump, iterable=iterable))\n expected_call_count = (range_size // partition_size) + int(bool(range_size % partition_size))\n\n assert dump.call_count == expected_call_count","def splitData(df, split):\n train = df.iloc[:int(len(df)*split)]\n test = df.iloc[int(len(df)*split):]\n \n return train, test","def __prepare_query(self, query, stopwords=[], stemming_func=None):\n pass","def split_into_batches_of_size(self, batch_size: int) -> Iterator[List]:\n if batch_size >= len(self):\n yield type(self)(self)\n else:\n for run in range(0, len(self), batch_size):\n yield self[run:run + batch_size]","def produce_query_batches(self):\n self.__generate_queries()\n return self.__bobs","def split(self, test_size=0.25, random_state=None):\n self.train_index, self.test_index = ms.train_test_split(\n self.data.index, test_size=test_size, random_state=random_state)","def test_split(self):\n array = np.arange(1000)\n df = DataFlow.from_numpy(array)\n\n # first, test throw errors on invalid arguments\n def assert_invalid_arg(**kwargs):\n with self.assertRaises(ValueError):\n df.split(**kwargs)\n assert_invalid_arg(partitions=[])\n assert_invalid_arg(partitions=[1000, 1])\n assert_invalid_arg(partitions=[1000, -1])\n assert_invalid_arg(partitions=[1, 2])\n assert_invalid_arg(portions=[])\n assert_invalid_arg(portions=[1.0, 0.1])\n assert_invalid_arg(portions=[1.0, -1])\n assert_invalid_arg(portions=[0.1, 0.2])\n\n # next, test split without shuffling\n df1, df2, df3 = df.split(partitions=[700, 200, 100])\n np.testing.assert_array_equal(df1.all()[0], array[:700])\n np.testing.assert_array_equal(df2.all()[0], array[700:900])\n np.testing.assert_array_equal(df3.all()[0], array[900:1000])\n df1, df2, df3 = df.split(portions=[-1, 0.2, 0.1])\n np.testing.assert_array_equal(df1.all()[0], array[:700])\n np.testing.assert_array_equal(df2.all()[0], array[700:900])\n np.testing.assert_array_equal(df3.all()[0], array[900:1000])\n\n # finally, test split with shuffling\n df1, df2 = df.split(portions=[0.5, -1], shuffle=True)\n self.assertEquals(len(df1), 500)\n self.assertEquals(len(df2), 500)\n df_array = np.concatenate([df1.all()[0], df2.all()[0]], axis=0)\n self.assertFalse(np.all(df_array == array))\n np.testing.assert_array_equal(np.sort(df_array), array)","def ArraySplit(array_to_split, bucket_size):\n return [array_to_split[i:i+bucket_size]\n for i in xrange(0, len(array_to_split), bucket_size)]","def _query_iterator(self, result, chunksize, columns, coerce_float=True, parse_dates=None):\n\n while True:\n data = result.fetchmany(chunksize)\n if not data:\n break\n else:\n self.frame = DataFrame.from_records(\n data, columns=columns, coerce_float=coerce_float)\n\n self._harmonize_columns(parse_dates=parse_dates)\n\n if self.index is not None:\n self.frame.set_index(self.index, inplace=True)\n\n yield self.frame","def dataset_splits(self):\n return [{\n \"split\": problem.DatasetSplit.TRAIN,\n \"shards\": 80,\n }, {\n \"split\": problem.DatasetSplit.EVAL,\n \"shards\": 2,\n }]","def query(self, qid):\r\n connection = self.getConnection()\r\n cursor = connection.cursor()\r\n lst = []\r\n\r\n #========================================================================\r\n # Preparation\r\n #========================================================================\r\n whereStatement, ranges, morPrep, insert, Levels, rangeTab = self.prepareQuery(qid)\r\n lst.append(round(morPrep, 6)) # preparation\r\n lst.append(round(insert, 6)) # insert ranges into table\r\n lst.append(ranges) #number of ranges\r\n lst.append(Levels) #depth of the tree\r\n\r\n #========================================================================\r\n # First approximation of query region\r\n #========================================================================\r\n\r\n if whereStatement is not '':\r\n if rangeTab is not None:\r\n query = \"SELECT \" + ora.getHintStatement(['USE_NL (t r)', ora.getParallelStringQuery(self.numProcesses)]) + \\\r\n\" \" + ', '.join(['t.'+ i for i in self.columnNames]) + \"\"\"\r\nFROM \"\"\" + self.iotTableName + \" t, \" + rangeTab + \"\"\" r \r\n\"\"\" + whereStatement\r\n\r\n else:\r\n query = \"SELECT \"+ ora.getHintStatement([ora.getParallelStringQuery(self.numProcesses)]) + ', '.join(self.columnNames) + \"\"\" \r\nFROM \"\"\" + self.iotTableName + \"\"\" \r\n\"\"\" + whereStatement\r\n\r\n start1 = time.time()\r\n ora.mogrifyExecute(cursor, query)\r\n result = cursor.fetchall()\r\n\r\n lst.append(round(time.time() - start1, 10)) # fetching\r\n \r\n if (self.integration == 'loose' and self.qtype.lower() != 'time') or self.integration == 'deep':\r\n qTable = self.queryTable + '_temp_' + qid\r\n else: \r\n qTable = self.queryTable + '_' + qid\r\n \r\n start1 = time.time()\r\n decoded = self.decodeSpaceTime(result)\r\n lst.append(round(time.time() - start1, 6)) #decoding\r\n\r\n start1 = time.time()\r\n res = self.storeQuery(qTable, self.queryColumns, decoded, True)\r\n lst.append(round(time.time() - start1, 6)) #storing\r\n if res != []:\r\n ptsInTemp = res\r\n lst.append(res) #approximate points\r\n else:\r\n ptsInTemp = 0\r\n \r\n #==================================================================\r\n # Secondary filtering of query region\r\n #==================================================================\r\n\r\n if (self.qtype.lower() == 'time' and self.integration == 'loose') or res == []:\r\n # no data returned or it is a time query in the loose integration\r\n lst.append(ptsInTemp) #approximate points\r\n lst.append(0) # point in polygon time\r\n return lst\r\n else:\r\n \r\n if self.integration.lower() == 'deep' and self.qtype.lower() == 'time':\r\n queryTab = self.iotTableName + '_res_' + str(qid)\r\n timeWhere = whereClause.addTimeCondition(getTime(self.granularity, self.start_date, self.end_date), 'TIME', self.timeType)\r\n zWhere = whereClause.addZCondition([self.ozmin, self.ozmax], 'Z')\r\n whereValue = whereClause.getWhereStatement([timeWhere, zWhere])\r\n \r\n \r\n if self.granularity == 'day':\r\n query = \"CREATE TABLE \" + queryTab + \"\"\"\r\n\"\"\" + ora.getTableSpaceString(self.tableSpace) + \"\"\"\r\nAS SELECT * \r\nFROM (\r\n SELECT \"\"\" + ora.getHintStatement([ora.getParallelStringQuery(self.numProcesses)]) + \\\r\n \"\"\" X, Y, Z, TO_DATE(TIME, 'yyyy/mm/dd') as TIME \r\n FROM \"\"\" + qTable +\"\"\"\r\n ) \r\n\"\"\" + whereValue\r\n else:\r\n query = \"CREATE TABLE \" + queryTab + \"\"\"\r\n\"\"\" + ora.getTableSpaceString(self.tableSpace) + \"\"\" \r\n AS SELECT \"\"\" + ora.getHintStatement([ora.getParallelStringQuery(self.numProcesses)]) + \\\r\n \"\"\" X, Y, Z, TIME \r\n FROM \"\"\"+ qTable + \"\"\"\" \r\n \"\"\" + whereValue\r\n \r\n start1 = time.time()\r\n cursor.execute(query)\r\n end = round(time.time() - start1, 2)\r\n\r\n ora.dropTable(cursor, qTable, False)\r\n final = ora.getNumPoints(connection, cursor, queryTab)\r\n lst.append(final) #final points\r\n lst.append(end) #point in polygon time\r\n return lst\r\n \r\n else:\r\n final, end = self.pointInPolygon(qTable, qid, True)\r\n \r\n lst.append(final) #final points\r\n lst.append(end) #point in polygon time\r\n return lst\r\n else:\r\n print 'No data returned'\r\n return [lst[0], lst[1], '-', '-', '-','-','-','-']","def split_data(self, model_data, tuning=True):\n pass","def batch_qs(qs: QuerySet, batch_size=1000):\n total = qs.count()\n for start in range(0, total, batch_size):\n end = min(start + batch_size, total)\n yield (qs[start:end], start, end, total)","def in_memory_rechunk(\n inputs: List[Tuple[core.ChunkKey, xarray.Dataset]],\n target_chunks: Mapping[str, int],\n) -> Iterator[Tuple[core.ChunkKey, xarray.Dataset]]:\n key, dataset = consolidate_chunks(inputs)\n yield from split_chunks(key, dataset, target_chunks)","def split(self):\n \n spl = self.which('split')\n if spl:\n self.__tmp = \"/tmp\"\n self.__tmpout = \"/tmp/output\"\n if not os.path.exists(self.__tmpout):\n os.makedirs(self.__tmpout)\n #os.chdir(\"/tmp\")\n '''\n assume split prog overwrites existing files if\n there is a conflict in file names\n '''\n #thecommand = \"%s -a 3 -b 500k %s %s/%s\" % (spl, self.__filename, self.__tmpout, self.__filename + self.__postfix)\n thecommand = \"%s -a 3 -b 10m %s %s/%s\" % (spl, self.__filename, self.__tmpout, self.__filename + self.__postfix)\n os.system(thecommand)\n dirList=os.listdir(self.__tmpout)\n #self.constructCat(dirList)\n for chunkfilename in dirList:\n #print chunkfilename \n #self.__cat += self.__remotepath + \"/\" + chunkfilename + \" \"\n #print self.__cat\n self.__flist.append(self.__tmpout + \"/\" + chunkfilename)\n #print self.__flist\n self.writeLog(chunkfilename, self.md5(fileName=self.__tmpout + \"/\" + chunkfilename))\n self.__numchunks = len([item for item in os.listdir(self.__tmpout) if os.path.isfile(self.__tmpout + \"/\" + item)])\n else:\n try:\n f = open(self.__filename, 'rb')\n except (OSError, IOError), e:\n raise FileSplitterException, str(e)\n \n bname = (os.path.split(self.__filename))[1]\n # Get the file size\n fsize = os.path.getsize(self.__filename)\n # dynamically calculate number of chunks\n strfsize = str(fsize)\n '''\n in MB's\n 8 - teens\n 9 - hundreds\n 10 - gigabytes\n '''\n if len(strfsize) == 8:\n #self.__numchunks = fsize/100000\n self.__numchunks = fsize/50000\n elif len(strfsize) == 9:\n #self.__numchunks = fsize/1000000\n self.__numchunks = fsize/500000\n elif len(strfsize) == 10:\n #self.__numchunks = fsize/10000000\n self.__numchunks = fsize/5000000\n #print '\\nSplitting file %s into %d chunks' % (self.__filename, self.__numchunks)\n # Get size of each chunk\n self.__chunksize = int(float(fsize)/float(self.__numchunks))\n \n chunksz = self.__chunksize\n total_bytes = 0\n \n for x in range(self.__numchunks):\n #chunkfilename = bname + '-' + str(x+1) + self.__postfix\n chunkfilename = bname + ('-%03d' % (x+1)) + self.__postfix\n # kill residual file if it exists\n if os.path.exists(chunkfilename):\n os.remove(chunkfilename)\n \"\"\"\n if reading the last section, calculate correct\n chunk size.\n \"\"\"\n if x == self.__numchunks - 1:\n chunksz = fsize - total_bytes\n \n try:\n if self.__debug:\n print 'Writing file chunk: %s' % chunkfilename\n data = f.read(chunksz)\n total_bytes += len(data)\n chunkf = file(chunkfilename, 'wb')\n chunkf.write(data)\n chunkf.close()\n #self.__cat += self.__remotepath + \"/\" + chunkfilename + \" \"\n self.__flist.append(chunkfilename)\n self.writeLog(chunkfilename, self.md5(fileName=chunkfilename))\n except (OSError, IOError), e:\n print e\n continue\n except EOFError, e:\n print e\n break\n\n print '\\nSplit complete on file: %s into %d chunks\\n' % (self.__filename, self.__numchunks)\n self.__logfhandle.close()\n #self.__cat += \"> \" + self.__remotepath + \"/\" + self.__filename\n self.set_cat_statement()","def _split(self, sql):\n\n placeholder = \"\\ufffc\" # unicode object replacement character\n\n if self._delimiter == ';':\n return sqlparse.split(sql)\n\n # We must find a string that original sql does not contain.\n # Most likely, our placeholder is enough, but if not, keep looking\n while placeholder in sql:\n placeholder += placeholder[0]\n sql = sql.replace(';', placeholder)\n sql = sql.replace(self._delimiter, ';')\n\n split = sqlparse.split(sql)\n\n return [\n stmt.replace(';', self._delimiter).replace(placeholder, ';')\n for stmt in split\n ]","def add_split(self, split_dim, value, split_size=\"\", num_split=0, name=None):\n if num_split > 0:\n return self._build_op(\n 'Split', [split_dim, value], name=name, attr={'num_split': num_split})\n else:\n return self._build_op('SplitV', [value, split_size, split_dim], name=name)","def query(self, query, **params):\n chunksize = params.pop(\"chunksize\", 100000)\n to_pandas = params.pop(\"to_pandas\", True)\n with self._cursor() as cursor:\n params = {k: v for k, v in params.items() if k in getargs(cursor.execute).args}\n cursor.execute(query, **params)\n fields = [i[0] for i in cursor.description]\n res = []\n while True:\n result = cursor.fetchmany(chunksize)\n if not result:\n break\n res.append(Frame(result))\n frame = rbind(res, bynames=False)\n if frame.shape == (0, 0):\n frame = Frame({n: [] for n in fields})\n else:\n frame.names = fields\n if to_pandas:\n frame = frame.to_pandas()\n return frame","def splits(cls, search_query = 'all', max_results = 300, start = 0, reduced_words=1000, savepath='.data', split_ratio=0.7, stratified=False, strata_field='abstract',\n random_state=None, **kwargs):\n\n # initialize text field\n text_field = torchtext.data.Field(tokenize=get_tokenizer(\"spacy\"), init_token='<sos>', eos_token='<eos>', lower=True)\n fields = [('abstract', text_field), ('paper', text_field)]\n examples = []\n\n # Create new dataset by downloading from arxiv or open dataset from folder\n if not os.path.exists(savepath):\n os.mkdir(savepath)\n # create directories for saving the data set\n if not os.path.exists(os.path.join(savepath, 'temp')):\n os.mkdir(os.path.join(savepath, 'temp'))\n if not os.path.exists(os.path.join(savepath, 'abstracts')):\n os.mkdir(os.path.join(savepath, 'abstracts'))\n if not os.path.exists(os.path.join(savepath, 'paper')):\n os.mkdir(os.path.join(savepath, 'paper'))\n data = cls.download(search_query=search_query, max_results=max_results)\n abstracts, papers = cls.extract_paper_and_abstract(data, savepath=savepath)\n\n # generate all examples\n for i, (abstract, paper) in enumerate(zip(abstracts, papers)):\n paper_tokenized = []\n abstract_tokenized = []\n # rdeduce the number of words with the textrank approach\n textranked_paper = summarizer.summarize(paper, words=reduced_words)\n # add start and end token\n paper_tokenized += [u'<sos>'] + text_field.preprocess(textranked_paper) + [u'<eos>']\n abstract_tokenized += [u'<sos>'] + text_field.preprocess(abstract) + [u'<eos>']\n # initialize examples\n examples.append(torchtext.data.Example.fromlist([abstract_tokenized, paper_tokenized], fields))\n\n # save data samples in txt files\n with open(os.path.join(savepath,'abstracts','abstract_' + str(i) + '.txt'), 'w+', encoding='utf-8') as abstr:\n csvwriter = csv.writer(abstr, delimiter=' ')\n csvwriter.writerow(abstract_tokenized)\n with open(os.path.join(savepath,'paper','paper_' + str(i) + '.txt'), 'w+', encoding='utf-8') as pap:\n csvwriter = csv.writer(pap, delimiter=' ')\n csvwriter.writerow(paper_tokenized)\n\n else:\n # read all files in saved data path\n paper_files = os.listdir(os.path.join(savepath,'paper'))\n abstract_files = os.listdir(os.path.join(savepath,'abstracts'))\n data = [[paper, abstract] for paper, abstract in zip(paper_files, abstract_files)]\n papers_tokenized = []\n abstracts_tokenized = []\n # read paper and abstracts from files\n for paper, abstract in data:\n with open(os.path.join(savepath, 'paper', paper), encoding='utf-8') as csvfile:\n paper = csv.reader(csvfile, delimiter=' ')\n for pap in paper:\n if pap:\n papers_tokenized.append(pap)\n with open(os.path.join(savepath, 'abstracts', abstract), encoding='utf-8') as csvfile:\n abstract = csv.reader(csvfile, delimiter=' ')\n for abstr in abstract:\n if abstr:\n abstracts_tokenized.append(abstr)\n \n # generate all examples\n for abstract_tokenized, paper_tokenized in zip(abstracts_tokenized, papers_tokenized):\n examples.append(torchtext.data.Example.fromlist([abstract_tokenized, paper_tokenized], fields))\n\n # create initial dataset\n dataset = PaperAbstractDataset(examples, fields)\n # split dataset\n splits = dataset.split(split_ratio=split_ratio, stratified=stratified, strata_field=strata_field,\n random_state=random_state)\n # initialize vocabulary\n pre_trained_vector_type = 'glove.6B.300d'\n for d in splits:\n for name, field in d.fields.items():\n field.build_vocab(splits[0], vectors=pre_trained_vector_type)\n d.filter_examples(['abstract', 'paper'])\n return splits","def _get_scatter_keys(datastore, query, num_splits, partition):\n scatter_point_query = _create_scatter_query(query, num_splits)\n\n key_splits = []\n while True:\n req = datastore_pb2.RunQueryRequest()\n if partition:\n req.partition_id.CopyFrom(partition)\n\n req.query.CopyFrom(scatter_point_query)\n\n resp = datastore.run_query(req)\n for entity_result in resp.batch.entity_results:\n key_splits.append(entity_result.entity.key)\n\n if resp.batch.more_results != query_pb2.QueryResultBatch.NOT_FINISHED:\n break\n\n scatter_point_query.start_cursor = resp.batch.end_cursor\n scatter_point_query.limit.value -= len(resp.batch.entity_results)\n\n key_splits.sort(helper.key_comparator)\n return key_splits","def get_chunks_result(self, data_keys: List[str], fetch_only: bool = False) -> List:","def __split_dataset(self):\n self.train, self.valid, _, _ = train_test_split(self.data, self.data, test_size=0.2)\n self.valid, self.test, _, _ = train_test_split(self.valid, self.valid, test_size=0.5)","def batch(self, sql):\n return _Batch(self.conn, sql)","def split_data(df, split_method='fo', test_size=.2, random_state=42):\n if split_method == 'fo':\n train_set, test_set = _split_fo(df,\n test_size=test_size,\n random_state=random_state)\n elif split_method == 'tfo':\n train_set, test_set = _split_tfo(df, test_size=test_size)\n elif split_method == 'ufo':\n train_set, test_set = _split_ufo(df,\n test_size=test_size,\n random_state=random_state)\n elif split_method == 'utfo':\n train_set, test_set = _split_utfo(df, test_size=test_size)\n else:\n raise HuitreError('Invalid data_split value, expect: ufo, utfo')\n train_set = train_set.reset_index(drop=True)\n test_set = test_set.reset_index(drop=True)\n return train_set, test_set","def split_dataset(self, split):\n trunk_pos_size = math.ceil((1 - split) * len(self.Pos))\n trunk_neg_size = math.ceil((1 - split) * len(self.Neg))\n trunk_num = int(1 / (1 - split))\n pos_temp = list()\n neg_temp = list()\n for index in range(trunk_num):\n pos_temp.append(self.Pos[index * trunk_pos_size:(index + 1) *\n trunk_pos_size])\n neg_temp.append(self.Neg[index * trunk_neg_size:(index + 1) *\n trunk_neg_size])\n self.test = pos_temp.pop(2) + neg_temp.pop(2)\n # self.train = [i for item in pos_temp + neg_temp for i in item]\n self.train = []\n for item in pos_temp + neg_temp:\n for i in item:\n self.train.append(i)\n\n random.shuffle(self.train)\n random.shuffle(self.test)","def fetch_things2(query, chunk_size = 100, batch_fn = None):\r\n orig_rules = deepcopy(query._rules)\r\n query._limit = chunk_size\r\n items = list(query)\r\n done = False\r\n while items and not done:\r\n #don't need to query again at the bottom if we didn't get enough\r\n if len(items) < chunk_size:\r\n done = True\r\n\r\n if batch_fn:\r\n items = batch_fn(items)\r\n\r\n for i in items:\r\n yield i\r\n\r\n if not done:\r\n query._rules = deepcopy(orig_rules)\r\n query._after(i)\r\n items = list(query)","def make_splits(self):\n # produce fold/portion splits of the training indexes: these output indexes to the tr. indexes themselves\n if self.folds is not None:\n meta_trainval_idx = kfold_split(self.train_idx, self.folds, self.seed, self.labels, self.label_info)\n elif self.portion is not None:\n meta_trainval_idx = portion_split(self.train_idx, self.portion, self.seed, self.labels, self.label_info)\n else:\n meta_trainval_idx = [(np.arange(len(self.train_idx)), np.arange(0, dtype=np.int32))]\n # \"dereference\" the metaindexes to point to the data themselves\n self.trainval_idx = []\n for (tidx, vidx) in meta_trainval_idx:\n self.trainval_idx.append((self.train_idx[tidx], self.train_idx[vidx]))","def executeQuery(self, segments=None,):\n if not segments: segments = self.segments\n query =''.join(['INSERT INTO ', self.tableName, ' (',\n ', '.join(self.firstLine), ') VALUES ',\n ', '.join([segment for segment in segments]), ';'])\n try:\n self.cursorExecute(query)\n except:\n print 'Bulk query rejected, splitting into smaller queries.'\n self.handleSQLRejection(0, len(self.segments))","def _split_query(query):\n\n\tqq = query.split(' ')\n\tkeywords = []\n\taccum = None\n\tfor kw in qq: \n\t\tif accum is None: \n\t\t\tif kw.startswith('\"'):\n\t\t\t\taccum = kw[1:]\n\t\t\telif kw: \n\t\t\t\tkeywords.append(kw)\n\t\telse:\n\t\t\taccum += ' ' + kw\n\t\t\tif kw.endswith('\"'):\n\t\t\t\tkeywords.append(accum[0:-1])\n\t\t\t\taccum = None\n\tif accum is not None:\n\t\tkeywords.append(accum)\n\treturn [kw.strip() for kw in keywords if kw.strip()]","def split(self, sep=None, maxsplit=None):\n return split(self, sep, maxsplit)","def split_dataset(self, test_size=0.20):\n\t\t(self.training_data, self.test_data, self.training_labels, self.test_labels) = train_test_split(self.training_data, self.training_labels, test_size=test_size)","def _create_scatter_query(query, num_splits):\n\n scatter_query = query_pb2.Query()\n for kind in query.kind:\n scatter_kind = scatter_query.kind.add()\n scatter_kind.CopyFrom(kind)\n\n # ascending order\n datastore_helper.add_property_orders(scatter_query, SCATTER_PROPERTY_NAME)\n\n # There is a split containing entities before and after each scatter entity:\n # ||---*------*------*------*------*------*------*---|| * = scatter entity\n # If we represent each split as a region before a scatter entity, there is an\n # extra region following the last scatter point. Thus, we do not need the\n # scatter entity for the last region.\n scatter_query.limit.value = (num_splits - 1) * KEYS_PER_SPLIT\n datastore_helper.add_projection(scatter_query, KEY_PROPERTY_NAME)\n\n return scatter_query","def run(self, query, project=\"odyssey-193217\"):\n\t\tfrom google.cloud import bigquery\n\t\tjob_config = bigquery.QueryJobConfig()\n\t\tclient = bigquery.Client(project=project)\n\t\tresult = client.query(query,job_config=job_config)\n\t\tjob_config.allowLargeResults = True\n\t\tresult.__done_timeout = 99999999\n\t\treturn list(result)","def dataset_splits(self):\n # 10% evaluation data\n return [{\n \"split\": problem.DatasetSplit.TRAIN,\n \"shards\": 799,\n }, {\n \"split\": problem.DatasetSplit.EVAL,\n \"shards\": 1,\n }]","def split(self):\n\n # FIXME: user should be able to change the default behavior of\n # this function (for instance user may require one filter not\n # to split the content of the input file and the same input \n # to be used by the next filter.\n \n utils.split_file(self.files['hit_ids'],\n self.files['input'],\n self.files['filtered_reads'],\n self.files['survived_reads'])","def _split_on_chunks(self, iterable, size):\n return utils.split_on_chunks(iterable, size)","def test_partition_on_very_large_vertex_than_has_to_be_split(self):\n self.setup()\n large_vertex = TestVertex(500, \"Large vertex\")\n self.assertEqual(large_vertex._model_based_max_atoms_per_core, 256)\n self.graph = ApplicationGraph(\n \"Graph with large vertex\", [large_vertex], [])\n graph, mapper = self.bp.partition(self.graph, self.machine)\n self.assertEqual(large_vertex._model_based_max_atoms_per_core, 256)\n self.assertGreater(len(graph.vertices), 1)","def batch_split(self, batch_text, threads=8):\n pass","def split(self):\n return self.dataset_split","def search(self, queries, results, unique_columns):\n names = [item.name for item in results]\n for index, item in enumerate(results):\n item.dataframe.columns = [\n column\n if column == unique_columns\n else '{0}_{1}'.format(column, names[index])\n for column in item.dataframe.columns\n ]\n\n for index, item in enumerate(results):\n self._runners.append(\n PartitionRunner(self, index, queries, results, item.name, unique_columns)\n )","def prepareQuery(self, qid):\r\n \r\n connection = self.getConnection()\r\n cursor = connection.cursor()\r\n\r\n if self.granularity == 'day':\r\n extractTime = \"TO_CHAR(t.START_DATE, 'yyyy,mm,dd'), TO_CHAR(t.END_DATE, 'yyyy,mm,dd')\"\r\n elif self.granularity == 'year':\r\n extractTime = \"EXTRACT(YEAR FROM t.START_DATE), EXTRACT(YEAR FROM t.END_DATE)\"\r\n \r\n cursor.execute(\"SELECT t.TYPE, t.GEOMETRY.Get_WKT(), \" + extractTime + \",\" + \\\r\n\"t.DATE_TYPE, t.Z_MIN, t.Z_MAX FROM \" + self.queriesTable + \"\"\" t \r\nWHERE id = \"\"\" + qid + \"\"\" AND dataset = '\"\"\" + self.dataset.lower() + \"'\")\r\n\r\n self.qtype, self.wkt, self.start_date, self.end_date, self.timeType, self.ozmin, self.ozmax = cursor.fetchall()[0]\r\n\r\n if self.wkt is not None:\r\n self.wkt = str(self.wkt)\r\n connection.close()\r\n \r\n # Setting up the missing variables along with transformations to the time encoding. \r\n if self.granularity == 'day':\r\n if self.start_date is None and self.end_date is None:\r\n times = [[self.mint * self.scale, self.maxt * self.scale]]\r\n elif self.start_date is not None and self.end_date is not None:\r\n self.start_date = map(int, self.start_date.split(','))\r\n self.end_date = map(int, self.end_date.split(','))\r\n times = [[reader.daySinceEpoch(self.start_date[0], \r\n self.start_date[1], self.start_date[2]) * self.scale, \r\n reader.daySinceEpoch(self.end_date[0], \r\n self.end_date[1], self.end_date[2]) * self.scale]]\r\n elif self.end_date is None:\r\n self.start_date = map(int, self.start_date.split(','))\r\n times = [[reader.daySinceEpoch(self.start_date[0], self.start_date[1], self.start_date[2]) * self.scale, None]]\r\n else:\r\n if self.start_date is None and self.end_date is None:\r\n times = [[self.mint * self.scale, self.maxt * self.scale]]\r\n elif self.start_date is not None and self.end_date is not None:\r\n times = [[self.start_date * self.scale, self.end_date * self.scale]]\r\n elif self.end_date is None:\r\n times = [[self.start_date * self.scale, None]]\r\n\r\n if self.ozmin is None or self.ozmax is None: #no selectivity on z\r\n zmin = int(round((self.minz - self.offz)/self.scalez, 0))\r\n zmax = int(round((self.maxz - self.offz)/self.scalez, 0))\r\n else:\r\n zmin = int(round((self.ozmin - self.offz)/self.scalez, 0))\r\n zmax = int(round((self.ozmax - self.offz)/self.scalez, 0))\r\n\r\n # Preparing the different types of queries: Space and space - time\r\n continuous = True\r\n if self.wkt:\r\n if self.qtype.replace(' ', '').lower() != 'nn-search':\r\n ordinates = list(loads(self.wkt).exterior.coords)\r\n else:\r\n ordinates = list(loads(self.wkt).coords)\r\n \r\n if self.case == 1: #lxyt\r\n geometry = Polygon(self.list2ScaleOffset(ordinates)).wkt\r\n if self.qtype.lower() == 'space':\r\n coarser = self.params[0] #0, 0\r\n else:\r\n coarser = self.params[1] #4, 4\r\n \r\n elif self.case == 2: #lxyzt\r\n geometry = Polygon3D(Polygon(self.list2ScaleOffset(ordinates)), zmin, zmax)\r\n\r\n if self.qtype.lower() == 'space':\r\n coarser = self.params[2] #4, 4\r\n else:\r\n coarser = self.params[3] #3, 3\r\n\r\n elif self.case == 3: #dxyt\r\n geom = Polygon(self.list2ScaleOffset(ordinates)) \r\n if times[0][1] is None:\r\n continuous = False\r\n times[0][1] = times[0][0]\r\n coarser = self.params[4] #1, 8\r\n elif self.qtype.lower() == 'space':\r\n if times[0][0] == times[0][1]:\r\n continuous = False\r\n coarser = self.params[5] #-2, 1\r\n else:\r\n coarser = self.params[5] - 7\r\n elif self.timeType == 'continuous':\r\n coarser = self.params[6] #0, 2\r\n elif self.timeType == 'discrete':\r\n coarser = self.params[7] #3, 8\r\n \r\n if self.timeType == 'discrete' and (self.start_date is not None) and (self.end_date is not None):\r\n geometry = [dynamicPolygon(geom, times[0][0], times[0][0]),\r\n dynamicPolygon(geom, times[0][1], times[0][1])]\r\n else:\r\n geometry = dynamicPolygon(geom, times[0][0], times[0][1]) \r\n \r\n elif self.case == 4: #dxyzt\r\n geom = Polygon(self.list2ScaleOffset(ordinates))\r\n if times[0][1] == None:\r\n continuous = False\r\n coarser = self.params[8] #4, 9\r\n times[0][1] = times[0][0]\r\n elif self.qtype.lower() == 'space':\r\n if times[0][0] == times[0][1]:\r\n coarser = self.params[9] #0, 2\r\n else:\r\n coarser = self.params[9] - 4\r\n elif self.timeType == 'continuous':\r\n coarser = self.params[10] #0, 2\r\n elif self.timeType == 'discrete':\r\n coarser = self.params[11] #4, 9\r\n \r\n if self.timeType == 'discrete' and self.start_date is not None and self.end_date is not None:\r\n geometry = [Polygon4D(geom, zmin, zmax, times[0][0], times[0][0]),\r\n Polygon4D(geom, zmin, zmax, times[0][1], times[0][1])]\r\n else:\r\n geometry = Polygon4D(geom, zmin, zmax, times[0][0], times[0][1])\r\n \r\n else: #time queries\r\n if self.case == 1:\r\n geometry = []\r\n \r\n elif self.case == 2:\r\n geometry = []\r\n \r\n elif self.case == 3:\r\n temp_geom = self.list2ScaleOffset([(self.minx, self.miny), (self.maxx, self.maxy)])\r\n geom = box(temp_geom[0][0], temp_geom[0][1], temp_geom[1][0], temp_geom[1][1])\r\n \r\n if times[0][1] is None:\r\n times[0][1] = times[0][0]\r\n coarser = self.params[12] #3, 7\r\n continuous = False\r\n elif self.timeType == 'continuous':\r\n coarser = self.params[13] #0, 3\r\n else:\r\n coarser = self.params[14] #3, 8\r\n \r\n if self.timeType == 'discrete' and self.start_date is not None and self.end_date is not None:\r\n geometry = [dynamicPolygon(geom, times[0][0], times[0][0]),\r\n dynamicPolygon(geom, times[0][1], times[0][1])]\r\n else:\r\n geometry = dynamicPolygon(geom, times[0][0], times[0][1])\r\n\r\n elif self.case == 4:\r\n temp_geom = self.list2ScaleOffset([(self.minx, self.miny),(self.maxx, self.maxy)])\r\n geom = box(temp_geom[0][0], temp_geom[0][1], temp_geom[1][0], temp_geom[1][1])\r\n if times[0][1] is None:\r\n times[0][1] = times[0][0]\r\n coarser = self.params[15] #4, 12\r\n continuous = False\r\n elif self.timeType == 'continuous':\r\n coarser = self.params[16] #1, 3\r\n elif self.timeType == 'discrete':\r\n coarser = self.params[17] #4, 11\r\n \r\n if self.timeType == 'discrete' and self.start_date is not None and self.end_date is not None:\r\n geometry = [Polygon4D(geom, zmin, zmax, times[0][0], times[0][0]),\r\n Polygon4D(geom, zmin, zmax, times[0][1], times[0][1])]\r\n else: \r\n geometry = Polygon4D(geom, zmin, zmax, times[0][0], times[0][1])\r\n \r\n\r\n \"\"\"The final lines have to do with the way of posing the query to the \r\n database. Two options are possible:\r\n (a) sql: A SQL query is posed to the database. The number of ranges is\r\n limited by a maximum number.\r\n (b) join: The table is joined explicitly with a table containing the \r\n ranges.\"\"\"\r\n if geometry == []:\r\n mortonWhere, self.mortonJoinWhere, ranges, rangeTab, morPrep, insert, Levels = ('', '', 0, None, 0, 0, 0)\r\n else:\r\n if self.method == 'join':\r\n rangeTab = (self.rangeTable + qid).upper()\r\n ranges, morPrep, insert, Levels = self.join(geometry, coarser, rangeTab, continuous)\r\n mortonWhere = self.mortonJoinWhere\r\n elif self.method == 'sql':\r\n rangeTab, insert = None, 0\r\n mortonWhere, ranges, morPrep, Levels = self.sql(geometry, coarser, continuous)\r\n \r\n # if deep the time is in the morton code\r\n if self.integration == 'deep' or (self.start_date is None and self.end_date is None and self.integration == 'loose'): \r\n timeWhere = ''\r\n elif self.integration == 'loose': \r\n timeWhere = whereClause.addTimeCondition(times, 'time', self.timeType)\r\n \r\n return whereClause.getWhereStatement([timeWhere, mortonWhere]), ranges, morPrep, insert, Levels, rangeTab","def split(self, num_or_size_splits, shuffle=False):\n raise NotImplementedError","def split_dataframe(df, size=10*1024*1024):\n \n # size of each row\n row_size = df.memory_usage().sum() / len(df)\n # maximum number of rows in each segment\n row_limit = int(size // row_size)\n # number of segments\n seg_num = (len(df)+row_limit-1)//row_limit\n # split df into segments\n segments = [df.iloc[i*row_limit : (i+1)*row_limit] for i in range(seg_num)]\n\n return segments","def make_splits(input_pkl, test_split=0.1, val_split=0.1):\n if (test_split > 1) or (val_split > 1) or (test_split + val_split > 1) or (test_split <= 0) or (val_split <= 0):\n logging.warning('Check the input for make splits, quitting')\n exit()\n\n main_dict = load_pickle(input_pkl)\n data, labels = main_dict['data'], main_dict['labels']\n idx_arr = np.random.choice(len(data), len(data))\n data, labels = data[idx_arr], labels[idx_arr]\n print(len(data[0][-1]))\n # Find the split sizes\n val_split = int(len(data) * val_split)\n test_split = val_split + int(len(data) * test_split)\n\n # Make and save the splits\n save_pickle({'data': data[:val_split], 'labels': labels[:val_split]}, 'data/val.pkl')\n save_pickle({'data': data[val_split:test_split], 'labels': labels[val_split:test_split]}, 'data/test.pkl')\n save_pickle({'data': data[test_split:], 'labels': labels[test_split:]}, 'data/train.pkl')","def process(self, lists, subqueries):\n pass","def test_split_ranges(self):\n start = datetime.utcnow() - pd.Timedelta(\"5H\")\n end = datetime.utcnow() + pd.Timedelta(\"5min\")\n delta = pd.Timedelta(\"1H\")\n\n ranges = QueryProvider._calc_split_ranges(start, end, delta)\n self.assertEqual(len(ranges), 5)\n self.assertEqual(ranges[0][0], start)\n self.assertEqual(ranges[-1][1], end)\n\n st_times = [start_tm[0] for start_tm in ranges]\n for end_time in (end_tm[1] for end_tm in ranges):\n self.assertNotIn(end_time, st_times)\n\n end = end + pd.Timedelta(\"20min\")\n ranges = QueryProvider._calc_split_ranges(start, end, delta)\n self.assertEqual(len(ranges), 5)\n self.assertEqual(ranges[0][0], start)\n self.assertEqual(ranges[-1][1], end)","def split_data(self, val_size=0.1, test_size=0.5):\n df = pd.read_csv(self.csv_path, delimiter=';')\n train, val = train_test_split(df, test_size=val_size)\n val, test = train_test_split(df, test_size=test_size)\n return train, val, test","def qids_to_splits(qids):\n qidmap = {}\n i = 0\n for qid in qids:\n if not qid in qidmap:\n qidmap[qid] = i\n i+=1\n new_qids = []\n for qid in qids:\n new_qids.append(qidmap[qid])\n qidcount = np.max(new_qids)+1\n splits = [[] for i in range(qidcount)]\n for i, qid in enumerate(new_qids):\n splits[qid].append(i) \n return splits","def split_all(self):\n for domino in self.dominoes[:]:\n self.split(domino)","def query_and_return(project_id, dataset_id, table_id, query, legacy=False):\n if not legacy:\n # Rename any legacy-style table references to use standard\n # SQL dialect. Because we use a mixture of both, we\n # standardise on only using the legacy style for the time\n # being.\n query = re.sub(r'\\[(.+?):(.+?)\\.(.+?)\\]', r'\\1.\\2.\\3', query)\n payload = {\n \"configuration\": {\n \"query\": {\n \"query\": query,\n \"flattenResuts\": False,\n \"allowLargeResults\": True,\n \"timeoutMs\": 100000,\n \"useQueryCache\": True,\n \"useLegacySql\": legacy,\n \"destinationTable\": {\n \"projectId\": project_id,\n \"tableId\": table_id,\n \"datasetId\": dataset_id\n },\n \"createDisposition\": \"CREATE_IF_NEEDED\",\n \"writeDisposition\": \"WRITE_TRUNCATE\"\n }\n }\n }\n # We've started using the google-cloud library since first\n # writing this. TODO: decide if we can use that throughout\n bq = get_bq_service()\n logger.info(\"Writing to bigquery table %s\" % table_id)\n start = datetime.datetime.now()\n response = bq.jobs().insert(\n projectId=project_id,\n body=payload).execute()\n counter = 0\n job_id = response['jobReference']['jobId']\n while True:\n time.sleep(1)\n response = bq.jobs().get(\n projectId=project_id,\n jobId=job_id).execute()\n counter += 1\n if response['status']['state'] == 'DONE':\n if 'errors' in response['status']:\n query = str(response['configuration']['query']['query'])\n for i, l in enumerate(query.split(\"\\n\")):\n # print SQL query with line numbers for debugging\n print \"{:>3}: {}\".format(i + 1, l)\n raise StandardError(\n json.dumps(response['status']['errors'], indent=2))\n else:\n break\n bytes_billed = float(\n response['statistics']['query']['totalBytesBilled'])\n gb_processed = round(bytes_billed / 1024 / 1024 / 1024, 2)\n est_cost = round(bytes_billed / 1e+12 * 5.0, 2)\n # Add our own metadata\n elapsed = (datetime.datetime.now() - start).total_seconds()\n response['openp'] = {'query': query,\n 'est_cost': est_cost,\n 'time': elapsed,\n 'gb_processed': gb_processed}\n logger.info(\"Time %ss, cost $%s\" % (elapsed, est_cost))\n return response","def split_file(self, input_file):\r\n file_list = [] \r\n with open(input_file, 'r', encoding='GB18030', errors='ignore') as f_in:\r\n data = f_in.readlines()\r\n lines_num = len(data)\r\n size = lines_num // self.num_workers # lines splitted in a chunk\r\n start = 0\r\n end = size\r\n w_path = \"../data/\"\r\n for i in range(lines_num//size):\r\n chunk_name = \"chunk_\" + str(i) + \".dat\"\r\n with open(w_path + chunk_name, 'w', encoding='utf-8') as f_out:\r\n f_out.write(''.join(data[start:end]))\r\n start = start + size\r\n end = end + size\r\n file_list.append(\"../data/chunk_\" + str(i) + \".dat\")\r\n \r\n print(f\"File splitted into {self.num_workers} chunks.\")\r\n return file_list, size","def fit_train(self, train_filename=\"data/train.tsv\", chunksize=500, sep=\"\\t\",n_jobs=cpu_count):\n all_result_maps = []\n\n for chunk in pd.read_csv(train_filename, chunksize=chunksize, sep=sep):\n chunk_split = np.array_split(chunk.values, n_jobs)\n pool = Pool(n_jobs)\n result_map = pool.map(self._preprocess_chunk_for_train, chunk_split)\n pool.close()\n pool.join()\n\n all_result_maps.extend(result_map)\n\n result_df = pd.DataFrame(all_result_maps)\n self._calculate_statistics(result_df)"],"string":"[\n \"def SplitQuery(self, request, context):\\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)\",\n \"def SplitQuery(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\\n raise NotImplementedError()\",\n \"def get_splits(datastore, query, num_splits, partition=None):\\n\\n # Validate that the number of splits is not out of bounds.\\n if num_splits < 1:\\n raise ValueError('The number of splits must be greater than 0.')\\n\\n if num_splits == 1:\\n return [query]\\n\\n _validate_query(query)\\n\\n splits = []\\n scatter_keys = _get_scatter_keys(datastore, query, num_splits, partition)\\n last_key = None\\n for next_key in _get_split_key(scatter_keys, num_splits):\\n splits.append(_create_split(last_key, next_key, query))\\n last_key = next_key\\n\\n splits.append(_create_split(last_key, None, query))\\n return splits\",\n \"def _create_split(last_key, next_key, query):\\n if not (last_key or next_key):\\n return query\\n\\n split_query = query_pb2.Query()\\n split_query.CopyFrom(query)\\n composite_filter = split_query.filter.composite_filter\\n composite_filter.op = CompositeFilter.AND\\n\\n if query.HasField('filter'):\\n composite_filter.filters.add().CopyFrom(query.filter)\\n\\n if last_key:\\n lower_bound = composite_filter.filters.add()\\n lower_bound.property_filter.property.name = KEY_PROPERTY_NAME\\n lower_bound.property_filter.op = PropertyFilter.GREATER_THAN_OR_EQUAL\\n lower_bound.property_filter.value.key_value.CopyFrom(last_key)\\n\\n if next_key:\\n upper_bound = composite_filter.filters.add()\\n upper_bound.property_filter.property.name = KEY_PROPERTY_NAME\\n upper_bound.property_filter.op = PropertyFilter.LESS_THAN\\n upper_bound.property_filter.value.key_value.CopyFrom(next_key)\\n\\n return split_query\",\n \"def produce_query_batches(self):\\n pass\",\n \"def support_query_split(datasets, query_size):\\n support_datasets = {}\\n query_datasets = {}\\n for task, dataset in datasets.items():\\n support_query_split = dataset.train_test_split(test_size=query_size)\\n support_datasets[task] = support_query_split[\\\"train\\\"]\\n query_datasets[task] = support_query_split[\\\"test\\\"]\\n return support_datasets, query_datasets\",\n \"def split_datasets(ql_file, nl_question_file, output_dir, split):\\n\\n with io.open(ql_file, encoding='utf-8') as query_org, \\\\\\n io.open(nl_question_file, encoding='utf8') as nl_org:\\n ql = query_org.readlines()\\n nl = nl_org.readlines()\\n\\n split = split / 100\\n\\n train_ql, val_ql, train_nl, val_nl = train_test_split(ql, nl,\\n train_size=split,\\n random_state=42,\\n shuffle=True)\\n\\n with io.open(output_dir + \\\"-train.ql\\\", 'w', encoding='utf-8') \\\\\\n as ql_train, \\\\\\n io.open(output_dir + \\\"-val.ql\\\", 'w', encoding='utf-8') \\\\\\n as ql_val, \\\\\\n io.open(output_dir + \\\"-train.nl\\\", 'w', encoding='utf-8') \\\\\\n as nl_train, \\\\\\n io.open(output_dir + \\\"-val.nl\\\", 'w', encoding='utf-8') \\\\\\n as nl_val:\\n ql_train.writelines(train_ql)\\n ql_val.writelines(val_ql)\\n nl_train.writelines(train_nl)\\n nl_val.writelines(val_nl)\",\n \"def test_split_queries(self):\\n la_provider = self.la_provider\\n\\n start = datetime.utcnow() - pd.Timedelta(\\\"5H\\\")\\n end = datetime.utcnow() + pd.Timedelta(\\\"5min\\\")\\n delta = pd.Timedelta(\\\"1H\\\")\\n\\n ranges = QueryProvider._calc_split_ranges(start, end, delta)\\n result_queries = la_provider.all_queries.list_alerts(\\n \\\"print\\\", start=start, end=end, split_query_by=\\\"1H\\\"\\n )\\n queries = result_queries.split(\\\"\\\\n\\\\n\\\")\\n self.assertEqual(len(queries), 5)\\n\\n for idx, (st_time, e_time) in enumerate(ranges):\\n self.assertIn(st_time.isoformat(sep=\\\"T\\\") + \\\"Z\\\", queries[idx])\\n self.assertIn(e_time.isoformat(sep=\\\"T\\\") + \\\"Z\\\", queries[idx])\\n self.assertIn(start.isoformat(sep=\\\"T\\\") + \\\"Z\\\", queries[0])\\n self.assertIn(end.isoformat(sep=\\\"T\\\") + \\\"Z\\\", queries[-1])\",\n \"def multiquery(self, query_chunks, **kwargs):\\n return query.multiquery(self._host, self._session, query_chunks, **kwargs)\",\n \"def mapped_split(reddit_dir, data_set_name, mapped_col, result_col, num_splits):\\n\\n table_files = os.listdir(os.path.join(reddit_dir, data_set_name))\\n args_list = [\\n (reddit_dir, data_set_name, table_fname, mapped_col, result_col, num_splits)\\n for table_fname in table_files\\n ]\\n\\n process = psutil.Process(os.getpid())\\n logger.debug(\\\"PID: %d, Memory usage: %.1f GB\\\" % (process.pid, process.memory_info().rss / 1e9))\\n\\n logger.debug(\\\"PID: %d, forking...\\\" % process.pid)\\n pool = mp.Pool(pool_size)\\n pool.map(unpack_mapped_split_core, args_list)\",\n \"def queries_iter(self, input):\\n\\n queries = self._split(input)\\n while queries:\\n for sql in queries:\\n delimiter = self._delimiter\\n sql = queries.pop(0)\\n if sql.endswith(delimiter):\\n trailing_delimiter = True\\n sql = sql.strip(delimiter)\\n else:\\n trailing_delimiter = False\\n\\n yield sql\\n\\n # if the delimiter was changed by the last command,\\n # re-split everything, and if we previously stripped\\n # the delimiter, append it to the end\\n if self._delimiter != delimiter:\\n combined_statement = ' '.join([sql] + queries)\\n if trailing_delimiter:\\n combined_statement += delimiter\\n queries = self._split(combined_statement)[1:]\",\n \"def chunk_queries(queries: List) -> List[List]:\\n chunks: List[List] = []\\n # Octopart can only handle 20 queries per request, so split into chunks.\\n for chunk in chunked(queries):\\n chunks.extend(split_chunk(chunk))\\n return chunks\",\n \"def batched_query(self, sql):\\r\\n\\r\\n result_sets = []\\r\\n messages = \\\"\\\"\\r\\n query = []\\r\\n last_query=\\\"\\\"\\r\\n\\r\\n batches = re.split(\\\"^\\\\s*(GO(?:\\\\s+[0-9]+)?)\\\\s*(?:--.*)?$\\\",sql,flags=re.M|re.I)\\r\\n # print(batches)\\r\\n for b in batches:\\r\\n if b.upper() == \\\"GO\\\":\\r\\n # execute one\\r\\n query.append(last_query)\\r\\n continue\\r\\n else:\\r\\n match = re.match(\\\"^GO\\\\s+([0-9]+)$\\\",b,re.I)\\r\\n if match is not None:\\r\\n #execute many\\r\\n for i in range(0,int(match.group(1))):\\r\\n query.append(last_query)\\r\\n else:\\r\\n # not a Go statment\\r\\n last_query = b\\r\\n query.append(last_query)\\r\\n\\r\\n # print(query)\\r\\n for q in query:\\r\\n r = self.query(q)\\r\\n if r is not None:\\r\\n result_sets.extend(r)\\r\\n messages += self.messages\\r\\n\\r\\n self.messages = messages\\r\\n return result_sets\",\n \"def chunk(self, shape, split) -> NotImplementedError:\\n raise NotImplementedError()\",\n \"def mapped_split(reddit_directory, data_set_name, mapped_col, result_col, num_splits):\\n\\n table_files = os.listdir(os.path.join(reddit_directory, data_set_name))\\n args_list = [\\n (reddit_directory, data_set_name, table_fname, mapped_col, result_col, num_splits)\\n for table_fname in table_files\\n ]\\n\\n pool = mp.Pool(pool_size)\\n pool.map(unpack_mapped_split_core, args_list)\",\n \"def _multi_query_execution(self):\\n multi_query_staging = self.query.split(';')\\n for query in multi_query_staging:\\n self.query = query\\n self._execute_command()\",\n \"def _chunked_query(self, model_class, chunk_field, items, chunk_size=500, **kwargs):\\r\\n res = chain.from_iterable(\\r\\n self._query(model_class, **dict([(chunk_field, chunk)] + kwargs.items()))\\r\\n for chunk in chunks(items, chunk_size)\\r\\n )\\r\\n return res\",\n \"def split_data(basedir, data_split=0.80):\\n manip = data_manipulator(basedir)\\n manip.train_test_split(data_split=data_split)\",\n \"def split_data_set(reddit_path, data_set_name, on, num_splits, target_directories, map_columns=None):\\n targets = {}\\n for i in range(num_splits):\\n targets[i] = os.path.join(target_directories[i], data_set_name)\\n mkdir(targets[i])\\n\\n full_sub_data_path = os.path.join(reddit_path, data_set_name)\\n data_files = map(lambda f: os.path.join(full_sub_data_path, f), os.listdir(full_sub_data_path))\\n args_list = [(on, table_file, targets, num_splits, map_columns) for table_file in data_files]\\n\\n pool = mp.Pool(pool_size)\\n pool.map(unpack_split_file_with_map, args_list)\",\n \"def split(self, params):\\n\\n if \\\"train_df\\\" in params.keys():\\n self.df = params[\\\"train_df\\\"]\\n if \\\"test_df\\\" in params.keys():\\n self.df = pd.concat([self.df, params[\\\"test_df\\\"]])\\n if \\\"n_splits\\\" in params.keys():\\n self.n_splits = params[\\\"n_splits\\\"]\\n if \\\"shuffle\\\" in params.keys():\\n self.shuffle = params[\\\"shuffle\\\"]\\n if \\\"random_state\\\" in params.keys():\\n self.random_state = params[\\\"random_state\\\"]\\n\\n self.__validate_input()\\n\\n n_samples = num_of_samples(self.df)\\n\\n if self.n_splits > n_samples:\\n raise ValueError(\\n f\\\"Cannot have number of splits {self.n_splits} > number of\\\"\\n f\\\" samples {n_samples}\\\"\\n )\\n\\n indices = np.arange(n_samples)\\n for test_indices in self.__iter_test_indices(n_samples):\\n train_indices = indices[np.logical_not(test_indices)]\\n test_indices = indices[test_indices]\\n yield train_indices, test_indices\",\n \"def split(input, output, fields, delimiter, encoding, verbose, format_in, zipfile, gzipfile, chunksize, filter):\\n if verbose:\\n enableVerbose()\\n options = {}\\n options['delimiter'] = delimiter\\n options['fields'] = fields\\n options['output'] = output\\n options['encoding'] = encoding\\n options['format_in'] = format_in\\n options['zipfile'] = zipfile\\n options['gzipfile'] = gzipfile\\n options['chunksize'] = chunksize\\n options['filter'] = filter\\n acmd = Selector()\\n acmd.split(input, options)\\n pass\",\n \"def paginate_query_new(\\n self,\\n node,\\n project_id=None,\\n props=[],\\n args=None,\\n chunk_size=5000,\\n offset=0,\\n format=\\\"json\\\",\\n ):\\n props = list(set([\\\"id\\\", \\\"submitter_id\\\"] + props))\\n properties = \\\" \\\".join(map(str, props))\\n\\n if project_id != None:\\n outname = \\\"query_{}_{}.tsv\\\".format(project_id, node)\\n if args == None:\\n query_txt = \\\"\\\"\\\"{%s (first: %s, offset: %s, project_id:\\\"%s\\\"){%s}}\\\"\\\"\\\" % (\\n node,\\n chunk_size,\\n offset,\\n project_id,\\n properties,\\n )\\n else:\\n query_txt = (\\n \\\"\\\"\\\"{%s (first: %s, offset: %s, project_id:\\\"%s\\\", %s){%s}}\\\"\\\"\\\"\\n % (node, chunk_size, offset, project_id, args, properties)\\n )\\n else:\\n outname = \\\"query_{}.tsv\\\".format(node)\\n if args == None:\\n query_txt = \\\"\\\"\\\"{%s (first: %s, offset: %s){%s}}\\\"\\\"\\\" % (\\n node,\\n chunk_size,\\n offset,\\n properties,\\n )\\n else:\\n query_txt = \\\"\\\"\\\"{%s (first: %s, offset: %s, %s){%s}}\\\"\\\"\\\" % (\\n node,\\n chunk_size,\\n offset,\\n args,\\n properties,\\n )\\n\\n total = {}\\n total[\\\"data\\\"] = {}\\n total[\\\"data\\\"][node] = []\\n\\n records = list(range(chunk_size))\\n while len(records) == chunk_size:\\n\\n res = self.sub.query(query_txt)\\n\\n if \\\"data\\\" in res:\\n records = res[\\\"data\\\"][node]\\n total[\\\"data\\\"][node] += records # res['data'][node] should be a list\\n offset += chunk_size\\n\\n elif \\\"error\\\" in res:\\n print(res[\\\"error\\\"])\\n if chunk_size > 1:\\n chunk_size = int(chunk_size / 2)\\n print(\\\"\\\\tHalving chunk_size to: {}.\\\".format(chunk_size))\\n else:\\n print(\\\"\\\\tQuery timing out with chunk_size of 1!\\\")\\n exit(1)\\n\\n else:\\n print(\\\"Query Error: {}\\\".format(res))\\n\\n print(\\\"\\\\tTotal records retrieved: {}\\\".format(len(total[\\\"data\\\"][node])))\\n\\n if format == \\\"tsv\\\":\\n df = json_normalize(total[\\\"data\\\"][node])\\n df.to_csv(outname, sep=\\\"\\\\t\\\", index=False)\\n return df\\n else:\\n return total\",\n \"def split(self):\\n st = time()\\n tokens = self._build_args.tokens\\n\\n for token_split in IStorage._tokens_partitions(tokens, config.min_number_of_tokens,\\n config.number_of_partitions):\\n storage_id = uuid.uuid4()\\n log.debug('assigning to %s %d tokens', str(storage_id), len(token_split))\\n new_args = self._build_args._replace(tokens=token_split, storage_id=storage_id)\\n self.__class__._store_meta(new_args)\\n\\n yield self.__class__.build_remotely(new_args)\\n log.debug('completed split of %s in %f', self.__class__.__name__, time() - st)\",\n \"async def split_large_groups_impl(config):\\n async with create_sessionmaker(config)() as dbsession:\\n progress = ClickIndeterminate(\\\"Splitting large groups\\\")\\n progress.start()\\n splitting = True\\n stmt = select(Group).options(selectinload(Group.items), selectinload(Group.children))\\n while splitting:\\n splitting = False\\n result = await dbsession.execute(stmt)\\n for group in result.scalars():\\n if len(group.children) == 0:\\n if len(group.items) > 120 and len(group.items) < 300: # noqa: PLR2004\\n if split_by_year(config, dbsession, group):\\n splitting = True\\n else:\\n split_by_similarity(dbsession, group)\\n splitting = True\\n elif len(group.items) >= 300: # noqa: PLR2004\\n if split_by_attribute(dbsession, group, \\\"concepts\\\"):\\n splitting = True\\n elif split_by_attribute(dbsession, group, \\\"subjects\\\"):\\n splitting = True\\n elif split_by_attribute(dbsession, group, \\\"materials\\\"):\\n splitting = True\\n elif split_by_attribute(dbsession, group, \\\"techniques\\\"):\\n splitting = True\\n elif split_by_year(config, dbsession, group):\\n splitting = True\\n else:\\n split_by_similarity(dbsession, group)\\n splitting = True\\n await dbsession.commit()\\n progress.stop()\",\n \"def readDBchunks(self, tablename, orderField, chunksize=50000,\\n selectOptions=None, limit=None, filterOptions=None, verbose=False):\\n\\n if limit:\\n remaining = limit\\n next_chunk = min(remaining, chunksize)\\n else:\\n next_chunk = chunksize\\n\\n cont = 0\\n \\n selectOptions = selectOptions + ', ' + orderField\\n\\n df = self.readDBtable(tablename, limit=next_chunk, selectOptions=selectOptions,\\n filterOptions = filterOptions, orderOptions=orderField)\\n\\n while (len(df)):\\n cont = cont+len(df)\\n if verbose:\\n print('[DBManager (readDBchunks)] Number of rows read so far:', cont)\\n if limit:\\n remaining = limit - cont\\n next_chunk = min(remaining, chunksize)\\n else:\\n next_chunk = chunksize\\n yield df.iloc[:,:-1]\\n\\n #Next we need to start from last retrieved element\\n filtercondition = orderField + '>' + str(df.iloc[:,-1][len(df)-1])\\n if filterOptions:\\n filtercondition = filtercondition + ' AND ' + filterOptions\\n \\n if next_chunk>0:\\n df = self.readDBtable(tablename, limit=next_chunk, selectOptions=selectOptions,\\n filterOptions = filtercondition, orderOptions=orderField)\\n else:\\n #If maximum number of records has been reached, set df to empty list to exit\\n df = []\",\n \"def _split(self, split, randomise=False, **kwargs):\\r\\n # Copy split to prevent modifying outside arguments\\r\\n split = split.copy()\\r\\n # Compute total\\r\\n total = sum(split.values())\\r\\n # If split contains floats, convert to integers\\r\\n if isinstance(total, float):\\r\\n assert_msg = 'Not enough data! ' \\\\\\r\\n + f'Split requires a total of {total*100}%. ' \\\\\\r\\n + 'Split should not exceed 100%.'\\r\\n assert total <= 1, assert_msg\\r\\n # Add 'rest' subset if not all data is used in split\\r\\n if total < 1:\\r\\n split['rest'] = 1 - total\\r\\n split = self._float_split_to_int(split)\\r\\n total = sum(split.values())\\r\\n # Create subsets based off integer values\\r\\n if isinstance(total, int):\\r\\n assert_msg = 'Not enough data! ' \\\\\\r\\n + f'Split requires a total of {total} data entries ' \\\\\\r\\n + f'but only {len(self.data)} are available.'\\r\\n assert total <= len(self.data), assert_msg\\r\\n # Add 'rest' subset if not all data is used in split\\r\\n if total < len(self.data):\\r\\n split['rest'] = len(self.data) - total\\r\\n # Create subsets\\r\\n index = 0\\r\\n for name, length in split.items():\\r\\n subset_name = f'{self.name}.{name}'\\r\\n subset_data = self.data[index:index + length]\\r\\n subset_seed = self.seed\\r\\n if self.seed is not None:\\r\\n subset_seed += sum([ord(c) for c in name]) + length\\r\\n subset = self._make_subset(subset_name,\\r\\n subset_data,\\r\\n randomise=randomise,\\r\\n seed=subset_seed,\\r\\n **kwargs\\r\\n )\\r\\n setattr(self, name, subset)\\r\\n index += length\\r\\n # Replace data with references to subsets\\r\\n self.data = []\\r\\n for name in split.keys():\\r\\n self.data.append(getattr(self, name, None))\\r\\n # Indicate that this is a superset\\r\\n self.is_superset = True\",\n \"def run_query(\\n self, project_id, partition_id, read_options=None, query=None, gql_query=None\\n ):\\n request_pb = _datastore_pb2.RunQueryRequest(\\n project_id=project_id,\\n partition_id=partition_id,\\n read_options=read_options,\\n query=query,\\n gql_query=gql_query,\\n )\\n return _rpc(\\n self.client._http,\\n project_id,\\n \\\"runQuery\\\",\\n self.client._base_url,\\n self.client._client_info,\\n request_pb,\\n _datastore_pb2.RunQueryResponse,\\n )\",\n \"def split(self) -> GQASplit:\\n return self._split\",\n \"def mapped_split_core(reddit_path, data_set_name, table_file_name, mapped_col, result_col, num_splits):\\n\\n logger.info(\\\"Processing: %s\\\" % data_set_name)\\n table_file_path = os.path.join(reddit_path, data_set_name, table_file_name)\\n\\n logger.debug(\\\"Reading: %s\\\" % table_file_name)\\n df = pd.read_csv(table_file_path, engine='python')\\n\\n process = psutil.Process(os.getpid())\\n logger.debug(\\\"PID: %d, Memory usage: %.1f GB\\\" % (process.pid, process.memory_info().rss / 1e9))\\n\\n def get_base_submission(target_fullname):\\n if target_fullname in comment_post_mapping:\\n return comment_post_mapping[target_fullname]\\n else:\\n return target_fullname\\n\\n def get_base_from_cpp(target_fullname):\\n if libdict.contains(target_fullname) == \\\"True\\\":\\n return libdict.get_value(target_fullname)\\n return target_fullname\\n\\n logger.debug(\\\"Mapping column: %s\\\" % table_file_name)\\n # df[result_col] = df[mapped_col].apply(get_base_submission) # The vanilla version\\n df[result_col] = df[mapped_col].apply(get_base_from_cpp) # the CPP version\\n df[result_col].fillna(\\\"missing\\\", inplace=True)\\n\\n # Make a map of output files for each of the splits as well as creating the\\n # directories that they belong in\\n output_file_map = {}\\n for i in target_directories:\\n target_sub_dir = os.path.join(target_directories[i], data_set_name)\\n mkdir(target_sub_dir)\\n\\n output_file_map[i] = os.path.join(target_sub_dir, table_file_name)\\n\\n logger.debug(\\\"Splitting: %s\\\" % table_file_name)\\n split_data_frame(df, result_col, lambda s: hash(s) % num_splits, output_file_map)\",\n \"def _query_iterator(result, chunksize, columns, index_col=None, coerce_float=True, parse_dates=None):\\n\\n while True:\\n data = result.fetchmany(chunksize)\\n if not data:\\n break\\n else:\\n yield _wrap_result(data, columns, index_col=index_col,\\n coerce_float=coerce_float,\\n parse_dates=parse_dates)\",\n \"def load_data(base_path, experiment_name, train_split_fraction, no_operators, no_sample_tuples, expansion_factor,\\n dim_predicate_embedding, size_threshold):\\n filename_prefix = path.join(base_path, \\\"data\\\", experiment_name)\\n parser = Parser(no_operators, no_sample_tuples, dim_predicate_embedding)\\n table_rows = pd.read_csv(filename_prefix + \\\".csv\\\")['tablerows']\\n table_sizes_kb = pd.read_csv(filename_prefix + \\\".csv\\\")['tablesizekb']\\n queries, num_colums, num_tables, tables_to_columns = parser.parse_file(filename_prefix + \\\".json\\\")\\n\\n # Shuffle for train-test-split -- queries based on the same plan can only end in train or test set\\n random.shuffle(queries)\\n\\n # Postprocess Queries\\n expanded_queries = []\\n for query in queries:\\n q_operator_node, q_runtime, q_index = query\\n\\n # Only consider tables with size over a certain threshold\\n if table_sizes_kb[q_index] >= size_threshold:\\n # Normalize runtime by table sizes otherwise it does not work\\n query = (q_operator_node, q_runtime / table_rows[q_index], q_index)\\n\\n # Expand/vary queries\\n for i in range(expansion_factor):\\n query_copy = deepcopy(query)\\n vary_query(query_copy[0], num_colums, tables_to_columns)\\n expanded_queries.append(query_copy)\\n\\n split_point = int(len(expanded_queries) * train_split_fraction)\\n return expanded_queries[:split_point], expanded_queries[split_point:], num_colums, num_tables\",\n \"def split_input(self):\\n namenode = self.runner.namenode\\n splitter = Splitter(RECORDS_PER_BLOCK)\\n results = []\\n input_files = []\\n for fname in self.inputs:\\n input_files.append(RecordFile(fname, namenode))\\n\\n taskid = 0\\n for block in splitter.split(input_files):\\n fname = map_input(self.id, taskid)\\n taskid += 1\\n namenode.create_file(fname)\\n\\n bytes_written = 0\\n for record in block:\\n bytes_written += namenode.write_file(fname, bytes_written,\\n record)\\n\\n namenode.close_file(fname)\\n results.append(fname)\\n self.open_files.append(fname)\\n\\n for file_ in input_files:\\n file_.close()\\n\\n return results\",\n \"def iterate_minibatches(*to_split, **kwargs):\\n batchsize=1\\n shuffle=False\\n if 'batchsize' in kwargs:\\n batchsize = kwargs['batchsize']\\n \\n if 'shuffle' in kwargs:\\n shuffle = kwargs['shuffle']\\n\\n res = [np.array(x) for x in to_split]\\n size = res[0].shape[0]\\n for x in res:\\n assert x.shape[0] == size\\n if shuffle:\\n indices = np.arange(size)\\n np.random.shuffle(indices)\\n for start_idx in range(0, size, batchsize):\\n if shuffle:\\n excerpt = indices[start_idx:start_idx + batchsize]\\n else:\\n excerpt = slice(start_idx, start_idx + batchsize)\\n yield [x[excerpt] for x in res] if len(res) != 1 else x[excerpt]\",\n \"def run(self):\\n # pylint: disable=too-many-locals\\n loop_start = time.clock()\\n partitions = []\\n for item in self._results:\\n partitions.append(\\n Partition(item.name, item.dataframe, self.PARTITION_SIZE)\\n )\\n if item.name == self._primary_dataset:\\n primary_dataset = partitions[-1]\\n\\n index = 0\\n while index < self.PARTITION_SIZE:\\n merge_sets = []\\n combination = ['\\\\033[1m{0}\\\\033[0m'.format(self._mappings[self._primary_dataset])]\\n for partition in partitions:\\n if partition.name != self._primary_dataset:\\n merge_sets.append({'name': partition.name, 'data': partition.next()})\\n combination.append(self._mappings[partition.name])\\n\\n Logger().info(\\n 'Running data extraction. Index {0} of {1} partitions, (combination: {2}, queries: {3})'.format(\\n index,\\n self.PARTITION_SIZE,\\n ''.join(combination),\\n len(self._queries)\\n )\\n )\\n\\n for size in range(self.PARTITION_SIZE):\\n self._running = []\\n q_start = time.clock()\\n merge_table = self.merge(\\n merge_sets + [{'name': primary_dataset.name, 'data': primary_dataset.next()}]\\n )\\n m_end = '{0:.2f}'.format(float(time.clock() - q_start))\\n Logger().debug(\\n 'Combination {0} merge table completed in {1} seconds ({2} rows)'.format(\\n ''.join(combination),\\n m_end,\\n len(merge_table.index)\\n )\\n )\\n for query in self._queries:\\n self._running.append(\\n DataThreader(merge_table, query, self._unique_columns)\\n )\\n\\n self.monitor()\\n times = [item.duration for item in self._running]\\n message = '{4}\\\\n Combination {0}, Index {5}/{1}'\\n message += ', merge_table size: {2}.\\\\n Average time per query {3}'\\n Logger().debug(\\n message.format(\\n ''.join(combination),\\n index,\\n len(merge_table.index),\\n times,\\n [len(query.results.index) for query in self._queries],\\n size\\n )\\n )\\n del times\\n del merge_table\\n del self._running\\n\\n end_time = math.floor(time.clock() - loop_start)\\n Logger().info('=========================================================================================')\\n Logger().info(\\n 'Completed partition {0} in {1} seconds. {2} queries, combination: {3}'.format(\\n index,\\n end_time,\\n len(self._queries),\\n ''.join(combination)\\n )\\n )\\n Logger().info('=========================================================================================')\\n primary_dataset.reset()\\n index += 1\\n\\n Logger().info('Completed data extraction')\\n self._complete = True\",\n \"def _paginate_query_across_partitioned_databases(model_class, q_expression, load_source):\\n from corehq.messaging.scheduling.scheduling_partitioned.models import (\\n CaseAlertScheduleInstance,\\n CaseTimedScheduleInstance,\\n )\\n\\n if model_class not in (CaseAlertScheduleInstance, CaseTimedScheduleInstance):\\n raise TypeError(\\\"Expected CaseAlertScheduleInstance or CaseTimedScheduleInstance\\\")\\n\\n db_names = get_db_aliases_for_partitioned_query()\\n for db_name in db_names:\\n for row in _paginate_query(db_name, model_class, q_expression, load_source):\\n yield row\",\n \"def split(self, place_leaf_splitted):\\n raise NotImplementedError\",\n \"def split_data_set(data_set, index, value, part=0):\\n # save the subdataset\\n res_data_set = []\\n \\n for entry in data_set:\\n # find the data set to the left of the partition point\\n if part == 0 and float(entry[index])<= value: #求划分点左侧的数据集\\n reduced_entry = entry[:index]\\n # after partitioning, the value of the index column in the data is removed\\n reduced_entry.extend(entry[index + 1:]) \\n res_data_set.append(reduced_entry)\\n # find the data set to the right of the partition point\\n if part ==1 and float(entry[index])> value: \\n reduced_entry = entry[:index]\\n reduced_entry.extend(entry[index + 1:])\\n res_data_set.append(reduced_entry)\\n return res_data_set\",\n \"def get_all_batches(self, query, bind_vars=None, batch_size=1000):\\n write_ops = [\\\"INSERT\\\", \\\"UPDATE\\\", \\\"REPLACE\\\", \\\"REMOVE\\\", \\\"UPSERT\\\"]\\n if any(ele in query.upper() for ele in write_ops):\\n raise C8QLGetAllBatchesError(\\n \\\"Write operations provided in the query. Only read operations can be provided\\\"\\n )\\n\\n cursor = self.execute(\\n query=query, bind_vars=bind_vars, batch_size=batch_size, stream=True\\n )\\n while cursor.has_more():\\n cursor.fetch()\\n\\n result = clean_doc(cursor.batch())\\n return result\",\n \"def split_chunks(\\n key: core.ChunkKey,\\n dataset: xarray.Dataset,\\n target_chunks: Mapping[str, int],\\n) -> Iterator[Tuple[core.ChunkKey, xarray.Dataset]]:\\n # This function splits consolidated arrays into blocks of new sizes, e.g.,\\n # ⌈x_00 x_01 ...⌉ ⌈⌈x_00⌉ ⌈x_01⌉ ...⌉\\n # X = |x_10 x_11 ...| = ||x_10| |x_11| ...|\\n # |x_20 x_21 ...| |⌊x_20⌋ ⌊x_21⌋ ...|\\n # ⌊ ... ... ...⌋ ⌊ ... ... ...⌋\\n # and emits them as (ChunkKey, xarray.Dataset) pairs.\\n all_bounds = []\\n for dim, chunk_size in target_chunks.items():\\n start = key.get(dim, 0)\\n stop = start + dataset.sizes[dim]\\n all_bounds.append(_split_chunk_bounds(start, stop, chunk_size))\\n\\n for bounds in itertools.product(*all_bounds):\\n offsets = dict(key)\\n slices = {}\\n for dim, (start, stop) in zip(target_chunks, bounds):\\n base = key.get(dim, 0)\\n offsets[dim] = start\\n slices[dim] = slice(start - base, stop - base)\\n\\n new_key = core.ChunkKey(offsets)\\n new_chunk = dataset.isel(slices)\\n yield new_key, new_chunk\",\n \"def split(self, splits, catchall=False):\\r\\n raise NotImplementedError()\",\n \"def Run(self):\\n results = []\\n count = 1\\n log_level = logging.DEBUG - 1\\n for bound_query in self.__bound_queries:\\n logging.log(log_level, 'Running query #%i' % count)\\n results.append(bound_query.Run())\\n count += 1\\n\\n def IterateResults(results):\\n \\\"\\\"\\\"Iterator function to return all results in sorted order.\\n\\n Iterate over the array of results, yielding the next element, in\\n sorted order. This function is destructive (results will be empty\\n when the operation is complete).\\n\\n Args:\\n results: list of result iterators to merge and iterate through\\n\\n Yields:\\n The next result in sorted order.\\n \\\"\\\"\\\"\\n result_heap = []\\n for result in results:\\n heap_value = MultiQuery.SortOrderEntity(result, self.__orderings)\\n if heap_value.GetEntity():\\n heapq.heappush(result_heap, heap_value)\\n\\n used_keys = set()\\n\\n while result_heap:\\n top_result = heapq.heappop(result_heap)\\n\\n results_to_push = []\\n if top_result.GetEntity().key() not in used_keys:\\n yield top_result.GetEntity()\\n else:\\n pass\\n\\n used_keys.add(top_result.GetEntity().key())\\n\\n results_to_push = []\\n while result_heap:\\n next = heapq.heappop(result_heap)\\n if cmp(top_result, next):\\n results_to_push.append(next)\\n break\\n else:\\n results_to_push.append(next.GetNext())\\n results_to_push.append(top_result.GetNext())\\n\\n for popped_result in results_to_push:\\n if popped_result.GetEntity():\\n heapq.heappush(result_heap, popped_result)\\n\\n return IterateResults(results)\",\n \"def mapped_split_core(reddit_directory, data_set_name, table_fname, mapped_col, result_col, num_splits):\\n\\n table_file_path = os.path.join(reddit_directory, data_set_name, table_fname)\\n logger.debug(\\\"Loading: %s\\\" % table_fname)\\n df = pd.read_csv(table_file_path, engine='python')\\n\\n logger.debug(\\\"Mapping column \\\\\\\"%s\\\\\\\" from Redis ...\\\" % mapped_col)\\n redis_db = get_redis_db(redis_pool)\\n df[result_col] = get_values_from_redis(redis_db, df[mapped_col], num_chunks=7)\\n df[result_col].fillna(df[mapped_col], inplace=True)\\n\\n # Make a map of output files for each of the splits as well as creating the\\n # directories that they belong in\\n output_file_map = {}\\n for i in target_directories:\\n target_sub_dir = os.path.join(target_directories[i], data_set_name)\\n mkdir(target_sub_dir)\\n output_file_map[i] = os.path.join(target_sub_dir, table_fname)\\n\\n logger.debug(\\\"Splitting: %s\\\" % table_fname)\\n split_data_frame(df, result_col, lambda s: hash(s) % num_splits, output_file_map)\",\n \"def _split_chunk(self, collection_name: str, key: int):\\n def split_command():\\n self._mongo_client.admin.command('split', collection_name, middle={SHARD_KEY: key})\\n self._try_until_done(split_command)\\n self._chunks[collection_name][key] = MAIN_MONGO_SHARD_NAME\\n logging.info(f\\\"MongoAgent: Split chunk of {collection_name} at {key}\\\")\",\n \"def execute_query(self):\\n query_sum = self.initialize_totals()\\n data = []\\n\\n with tenant_context(self.tenant):\\n query = self.query_table.objects.filter(self.query_filter)\\n query_data = query.annotate(**self.annotations)\\n group_by_value = self._get_group_by()\\n\\n query_group_by = [\\\"date\\\"] + group_by_value\\n query_order_by = [\\\"-date\\\"]\\n query_order_by.extend([self.order]) # add implicit ordering\\n\\n query_data = query_data.values(*query_group_by).annotate(**self.report_annotations)\\n\\n if self._limit and query_data:\\n query_data = self._group_by_ranks(query, query_data)\\n if not self.parameters.get(\\\"order_by\\\"):\\n # override implicit ordering when using ranked ordering.\\n query_order_by[-1] = \\\"rank\\\"\\n\\n # Populate the 'total' section of the API response\\n if query.exists():\\n aggregates = self._mapper.report_type_map.get(\\\"aggregates\\\")\\n metric_sum = query.aggregate(**aggregates)\\n query_sum = {key: metric_sum.get(key) for key in aggregates}\\n\\n query_data, total_capacity = self.get_cluster_capacity(query_data)\\n if total_capacity:\\n query_sum.update(total_capacity)\\n\\n if self._delta:\\n query_data = self.add_deltas(query_data, query_sum)\\n is_csv_output = self.parameters.accept_type and \\\"text/csv\\\" in self.parameters.accept_type\\n\\n query_data = self.order_by(query_data, query_order_by)\\n\\n if is_csv_output:\\n if self._limit:\\n data = self._ranked_list(list(query_data))\\n else:\\n data = list(query_data)\\n else:\\n # Pass in a copy of the group by without the added\\n # tag column name prefix\\n groups = copy.deepcopy(query_group_by)\\n groups.remove(\\\"date\\\")\\n data = self._apply_group_by(list(query_data), groups)\\n data = self._transform_data(query_group_by, 0, data)\\n\\n sum_init = {\\\"cost_units\\\": self._mapper.cost_units_key}\\n if self._mapper.usage_units_key:\\n sum_init[\\\"usage_units\\\"] = self._mapper.usage_units_key\\n query_sum.update(sum_init)\\n\\n ordered_total = {\\n total_key: query_sum[total_key] for total_key in self.report_annotations.keys() if total_key in query_sum\\n }\\n ordered_total.update(query_sum)\\n\\n self.query_sum = ordered_total\\n self.query_data = data\\n return self._format_query_response()\",\n \"def splitQuery(query):\\n triples = list()\\n bgp = re.search('WHERE {(.*)}', query).group(1)\\n for triple in bgp.split(' . '):\\n triples.append(triple.strip())\\n return triples\",\n \"def kb_train_test_split(test_size, random_state):\\n\\n cnxn_path = \\\"/polyaxon-data/goldenretriever/db_cnxn_str.txt\\\"\\n conn = pyodbc.connect(open(cnxn_path, 'r').read())\\n\\n SQL_Query = pd.read_sql_query('''SELECT dbo.query_labels.id, dbo.query_db.query_string, \\\\\\n dbo.kb_clauses.processed_string, dbo.kb_raw.kb_name, dbo.kb_raw.type FROM dbo.query_labels \\\\\\n JOIN dbo.query_db ON dbo.query_labels.query_id = dbo.query_db.id \\\\\\n JOIN dbo.kb_clauses ON dbo.query_labels.clause_id = dbo.kb_clauses.id \\\\\\n JOIN dbo.kb_raw ON dbo.kb_clauses.raw_id = dbo.kb_raw.id''', conn)\\n\\n df = pd.DataFrame(SQL_Query).set_index('id')\\n kb_names = df['kb_name'].unique()\\n\\n train_dict = dict()\\n test_dict = dict()\\n\\n train_idx_all = []\\n test_idx_all = []\\n\\n for kb_name in kb_names:\\n kb_id = df[df['kb_name'] == kb_name].index.values\\n train_idx, test_idx = train_test_split(kb_id, test_size=test_size,\\n random_state=random_state)\\n \\n train_dict[kb_name] = train_idx\\n test_dict[kb_name] = test_idx\\n \\n for k,v in train_dict.items():\\n for idx in v:\\n train_idx_all.append(idx)\\n \\n for k,v in test_dict.items():\\n for idx in v:\\n test_idx_all.append(idx)\\n \\n return df, train_dict, test_dict, train_idx_all, test_idx_all\",\n \"def batch_split(self) -> np.array:\\n pass\",\n \"def test_split(range_size, partition_size):\\n dump = Mock()\\n\\n iterable = list(range(range_size))\\n\\n list(_split(partition_size=partition_size, dump=dump, iterable=iterable))\\n expected_call_count = (range_size // partition_size) + int(bool(range_size % partition_size))\\n\\n assert dump.call_count == expected_call_count\",\n \"def splitData(df, split):\\n train = df.iloc[:int(len(df)*split)]\\n test = df.iloc[int(len(df)*split):]\\n \\n return train, test\",\n \"def __prepare_query(self, query, stopwords=[], stemming_func=None):\\n pass\",\n \"def split_into_batches_of_size(self, batch_size: int) -> Iterator[List]:\\n if batch_size >= len(self):\\n yield type(self)(self)\\n else:\\n for run in range(0, len(self), batch_size):\\n yield self[run:run + batch_size]\",\n \"def produce_query_batches(self):\\n self.__generate_queries()\\n return self.__bobs\",\n \"def split(self, test_size=0.25, random_state=None):\\n self.train_index, self.test_index = ms.train_test_split(\\n self.data.index, test_size=test_size, random_state=random_state)\",\n \"def test_split(self):\\n array = np.arange(1000)\\n df = DataFlow.from_numpy(array)\\n\\n # first, test throw errors on invalid arguments\\n def assert_invalid_arg(**kwargs):\\n with self.assertRaises(ValueError):\\n df.split(**kwargs)\\n assert_invalid_arg(partitions=[])\\n assert_invalid_arg(partitions=[1000, 1])\\n assert_invalid_arg(partitions=[1000, -1])\\n assert_invalid_arg(partitions=[1, 2])\\n assert_invalid_arg(portions=[])\\n assert_invalid_arg(portions=[1.0, 0.1])\\n assert_invalid_arg(portions=[1.0, -1])\\n assert_invalid_arg(portions=[0.1, 0.2])\\n\\n # next, test split without shuffling\\n df1, df2, df3 = df.split(partitions=[700, 200, 100])\\n np.testing.assert_array_equal(df1.all()[0], array[:700])\\n np.testing.assert_array_equal(df2.all()[0], array[700:900])\\n np.testing.assert_array_equal(df3.all()[0], array[900:1000])\\n df1, df2, df3 = df.split(portions=[-1, 0.2, 0.1])\\n np.testing.assert_array_equal(df1.all()[0], array[:700])\\n np.testing.assert_array_equal(df2.all()[0], array[700:900])\\n np.testing.assert_array_equal(df3.all()[0], array[900:1000])\\n\\n # finally, test split with shuffling\\n df1, df2 = df.split(portions=[0.5, -1], shuffle=True)\\n self.assertEquals(len(df1), 500)\\n self.assertEquals(len(df2), 500)\\n df_array = np.concatenate([df1.all()[0], df2.all()[0]], axis=0)\\n self.assertFalse(np.all(df_array == array))\\n np.testing.assert_array_equal(np.sort(df_array), array)\",\n \"def ArraySplit(array_to_split, bucket_size):\\n return [array_to_split[i:i+bucket_size]\\n for i in xrange(0, len(array_to_split), bucket_size)]\",\n \"def _query_iterator(self, result, chunksize, columns, coerce_float=True, parse_dates=None):\\n\\n while True:\\n data = result.fetchmany(chunksize)\\n if not data:\\n break\\n else:\\n self.frame = DataFrame.from_records(\\n data, columns=columns, coerce_float=coerce_float)\\n\\n self._harmonize_columns(parse_dates=parse_dates)\\n\\n if self.index is not None:\\n self.frame.set_index(self.index, inplace=True)\\n\\n yield self.frame\",\n \"def dataset_splits(self):\\n return [{\\n \\\"split\\\": problem.DatasetSplit.TRAIN,\\n \\\"shards\\\": 80,\\n }, {\\n \\\"split\\\": problem.DatasetSplit.EVAL,\\n \\\"shards\\\": 2,\\n }]\",\n \"def query(self, qid):\\r\\n connection = self.getConnection()\\r\\n cursor = connection.cursor()\\r\\n lst = []\\r\\n\\r\\n #========================================================================\\r\\n # Preparation\\r\\n #========================================================================\\r\\n whereStatement, ranges, morPrep, insert, Levels, rangeTab = self.prepareQuery(qid)\\r\\n lst.append(round(morPrep, 6)) # preparation\\r\\n lst.append(round(insert, 6)) # insert ranges into table\\r\\n lst.append(ranges) #number of ranges\\r\\n lst.append(Levels) #depth of the tree\\r\\n\\r\\n #========================================================================\\r\\n # First approximation of query region\\r\\n #========================================================================\\r\\n\\r\\n if whereStatement is not '':\\r\\n if rangeTab is not None:\\r\\n query = \\\"SELECT \\\" + ora.getHintStatement(['USE_NL (t r)', ora.getParallelStringQuery(self.numProcesses)]) + \\\\\\r\\n\\\" \\\" + ', '.join(['t.'+ i for i in self.columnNames]) + \\\"\\\"\\\"\\r\\nFROM \\\"\\\"\\\" + self.iotTableName + \\\" t, \\\" + rangeTab + \\\"\\\"\\\" r \\r\\n\\\"\\\"\\\" + whereStatement\\r\\n\\r\\n else:\\r\\n query = \\\"SELECT \\\"+ ora.getHintStatement([ora.getParallelStringQuery(self.numProcesses)]) + ', '.join(self.columnNames) + \\\"\\\"\\\" \\r\\nFROM \\\"\\\"\\\" + self.iotTableName + \\\"\\\"\\\" \\r\\n\\\"\\\"\\\" + whereStatement\\r\\n\\r\\n start1 = time.time()\\r\\n ora.mogrifyExecute(cursor, query)\\r\\n result = cursor.fetchall()\\r\\n\\r\\n lst.append(round(time.time() - start1, 10)) # fetching\\r\\n \\r\\n if (self.integration == 'loose' and self.qtype.lower() != 'time') or self.integration == 'deep':\\r\\n qTable = self.queryTable + '_temp_' + qid\\r\\n else: \\r\\n qTable = self.queryTable + '_' + qid\\r\\n \\r\\n start1 = time.time()\\r\\n decoded = self.decodeSpaceTime(result)\\r\\n lst.append(round(time.time() - start1, 6)) #decoding\\r\\n\\r\\n start1 = time.time()\\r\\n res = self.storeQuery(qTable, self.queryColumns, decoded, True)\\r\\n lst.append(round(time.time() - start1, 6)) #storing\\r\\n if res != []:\\r\\n ptsInTemp = res\\r\\n lst.append(res) #approximate points\\r\\n else:\\r\\n ptsInTemp = 0\\r\\n \\r\\n #==================================================================\\r\\n # Secondary filtering of query region\\r\\n #==================================================================\\r\\n\\r\\n if (self.qtype.lower() == 'time' and self.integration == 'loose') or res == []:\\r\\n # no data returned or it is a time query in the loose integration\\r\\n lst.append(ptsInTemp) #approximate points\\r\\n lst.append(0) # point in polygon time\\r\\n return lst\\r\\n else:\\r\\n \\r\\n if self.integration.lower() == 'deep' and self.qtype.lower() == 'time':\\r\\n queryTab = self.iotTableName + '_res_' + str(qid)\\r\\n timeWhere = whereClause.addTimeCondition(getTime(self.granularity, self.start_date, self.end_date), 'TIME', self.timeType)\\r\\n zWhere = whereClause.addZCondition([self.ozmin, self.ozmax], 'Z')\\r\\n whereValue = whereClause.getWhereStatement([timeWhere, zWhere])\\r\\n \\r\\n \\r\\n if self.granularity == 'day':\\r\\n query = \\\"CREATE TABLE \\\" + queryTab + \\\"\\\"\\\"\\r\\n\\\"\\\"\\\" + ora.getTableSpaceString(self.tableSpace) + \\\"\\\"\\\"\\r\\nAS SELECT * \\r\\nFROM (\\r\\n SELECT \\\"\\\"\\\" + ora.getHintStatement([ora.getParallelStringQuery(self.numProcesses)]) + \\\\\\r\\n \\\"\\\"\\\" X, Y, Z, TO_DATE(TIME, 'yyyy/mm/dd') as TIME \\r\\n FROM \\\"\\\"\\\" + qTable +\\\"\\\"\\\"\\r\\n ) \\r\\n\\\"\\\"\\\" + whereValue\\r\\n else:\\r\\n query = \\\"CREATE TABLE \\\" + queryTab + \\\"\\\"\\\"\\r\\n\\\"\\\"\\\" + ora.getTableSpaceString(self.tableSpace) + \\\"\\\"\\\" \\r\\n AS SELECT \\\"\\\"\\\" + ora.getHintStatement([ora.getParallelStringQuery(self.numProcesses)]) + \\\\\\r\\n \\\"\\\"\\\" X, Y, Z, TIME \\r\\n FROM \\\"\\\"\\\"+ qTable + \\\"\\\"\\\"\\\" \\r\\n \\\"\\\"\\\" + whereValue\\r\\n \\r\\n start1 = time.time()\\r\\n cursor.execute(query)\\r\\n end = round(time.time() - start1, 2)\\r\\n\\r\\n ora.dropTable(cursor, qTable, False)\\r\\n final = ora.getNumPoints(connection, cursor, queryTab)\\r\\n lst.append(final) #final points\\r\\n lst.append(end) #point in polygon time\\r\\n return lst\\r\\n \\r\\n else:\\r\\n final, end = self.pointInPolygon(qTable, qid, True)\\r\\n \\r\\n lst.append(final) #final points\\r\\n lst.append(end) #point in polygon time\\r\\n return lst\\r\\n else:\\r\\n print 'No data returned'\\r\\n return [lst[0], lst[1], '-', '-', '-','-','-','-']\",\n \"def split_data(self, model_data, tuning=True):\\n pass\",\n \"def batch_qs(qs: QuerySet, batch_size=1000):\\n total = qs.count()\\n for start in range(0, total, batch_size):\\n end = min(start + batch_size, total)\\n yield (qs[start:end], start, end, total)\",\n \"def in_memory_rechunk(\\n inputs: List[Tuple[core.ChunkKey, xarray.Dataset]],\\n target_chunks: Mapping[str, int],\\n) -> Iterator[Tuple[core.ChunkKey, xarray.Dataset]]:\\n key, dataset = consolidate_chunks(inputs)\\n yield from split_chunks(key, dataset, target_chunks)\",\n \"def split(self):\\n \\n spl = self.which('split')\\n if spl:\\n self.__tmp = \\\"/tmp\\\"\\n self.__tmpout = \\\"/tmp/output\\\"\\n if not os.path.exists(self.__tmpout):\\n os.makedirs(self.__tmpout)\\n #os.chdir(\\\"/tmp\\\")\\n '''\\n assume split prog overwrites existing files if\\n there is a conflict in file names\\n '''\\n #thecommand = \\\"%s -a 3 -b 500k %s %s/%s\\\" % (spl, self.__filename, self.__tmpout, self.__filename + self.__postfix)\\n thecommand = \\\"%s -a 3 -b 10m %s %s/%s\\\" % (spl, self.__filename, self.__tmpout, self.__filename + self.__postfix)\\n os.system(thecommand)\\n dirList=os.listdir(self.__tmpout)\\n #self.constructCat(dirList)\\n for chunkfilename in dirList:\\n #print chunkfilename \\n #self.__cat += self.__remotepath + \\\"/\\\" + chunkfilename + \\\" \\\"\\n #print self.__cat\\n self.__flist.append(self.__tmpout + \\\"/\\\" + chunkfilename)\\n #print self.__flist\\n self.writeLog(chunkfilename, self.md5(fileName=self.__tmpout + \\\"/\\\" + chunkfilename))\\n self.__numchunks = len([item for item in os.listdir(self.__tmpout) if os.path.isfile(self.__tmpout + \\\"/\\\" + item)])\\n else:\\n try:\\n f = open(self.__filename, 'rb')\\n except (OSError, IOError), e:\\n raise FileSplitterException, str(e)\\n \\n bname = (os.path.split(self.__filename))[1]\\n # Get the file size\\n fsize = os.path.getsize(self.__filename)\\n # dynamically calculate number of chunks\\n strfsize = str(fsize)\\n '''\\n in MB's\\n 8 - teens\\n 9 - hundreds\\n 10 - gigabytes\\n '''\\n if len(strfsize) == 8:\\n #self.__numchunks = fsize/100000\\n self.__numchunks = fsize/50000\\n elif len(strfsize) == 9:\\n #self.__numchunks = fsize/1000000\\n self.__numchunks = fsize/500000\\n elif len(strfsize) == 10:\\n #self.__numchunks = fsize/10000000\\n self.__numchunks = fsize/5000000\\n #print '\\\\nSplitting file %s into %d chunks' % (self.__filename, self.__numchunks)\\n # Get size of each chunk\\n self.__chunksize = int(float(fsize)/float(self.__numchunks))\\n \\n chunksz = self.__chunksize\\n total_bytes = 0\\n \\n for x in range(self.__numchunks):\\n #chunkfilename = bname + '-' + str(x+1) + self.__postfix\\n chunkfilename = bname + ('-%03d' % (x+1)) + self.__postfix\\n # kill residual file if it exists\\n if os.path.exists(chunkfilename):\\n os.remove(chunkfilename)\\n \\\"\\\"\\\"\\n if reading the last section, calculate correct\\n chunk size.\\n \\\"\\\"\\\"\\n if x == self.__numchunks - 1:\\n chunksz = fsize - total_bytes\\n \\n try:\\n if self.__debug:\\n print 'Writing file chunk: %s' % chunkfilename\\n data = f.read(chunksz)\\n total_bytes += len(data)\\n chunkf = file(chunkfilename, 'wb')\\n chunkf.write(data)\\n chunkf.close()\\n #self.__cat += self.__remotepath + \\\"/\\\" + chunkfilename + \\\" \\\"\\n self.__flist.append(chunkfilename)\\n self.writeLog(chunkfilename, self.md5(fileName=chunkfilename))\\n except (OSError, IOError), e:\\n print e\\n continue\\n except EOFError, e:\\n print e\\n break\\n\\n print '\\\\nSplit complete on file: %s into %d chunks\\\\n' % (self.__filename, self.__numchunks)\\n self.__logfhandle.close()\\n #self.__cat += \\\"> \\\" + self.__remotepath + \\\"/\\\" + self.__filename\\n self.set_cat_statement()\",\n \"def _split(self, sql):\\n\\n placeholder = \\\"\\\\ufffc\\\" # unicode object replacement character\\n\\n if self._delimiter == ';':\\n return sqlparse.split(sql)\\n\\n # We must find a string that original sql does not contain.\\n # Most likely, our placeholder is enough, but if not, keep looking\\n while placeholder in sql:\\n placeholder += placeholder[0]\\n sql = sql.replace(';', placeholder)\\n sql = sql.replace(self._delimiter, ';')\\n\\n split = sqlparse.split(sql)\\n\\n return [\\n stmt.replace(';', self._delimiter).replace(placeholder, ';')\\n for stmt in split\\n ]\",\n \"def add_split(self, split_dim, value, split_size=\\\"\\\", num_split=0, name=None):\\n if num_split > 0:\\n return self._build_op(\\n 'Split', [split_dim, value], name=name, attr={'num_split': num_split})\\n else:\\n return self._build_op('SplitV', [value, split_size, split_dim], name=name)\",\n \"def query(self, query, **params):\\n chunksize = params.pop(\\\"chunksize\\\", 100000)\\n to_pandas = params.pop(\\\"to_pandas\\\", True)\\n with self._cursor() as cursor:\\n params = {k: v for k, v in params.items() if k in getargs(cursor.execute).args}\\n cursor.execute(query, **params)\\n fields = [i[0] for i in cursor.description]\\n res = []\\n while True:\\n result = cursor.fetchmany(chunksize)\\n if not result:\\n break\\n res.append(Frame(result))\\n frame = rbind(res, bynames=False)\\n if frame.shape == (0, 0):\\n frame = Frame({n: [] for n in fields})\\n else:\\n frame.names = fields\\n if to_pandas:\\n frame = frame.to_pandas()\\n return frame\",\n \"def splits(cls, search_query = 'all', max_results = 300, start = 0, reduced_words=1000, savepath='.data', split_ratio=0.7, stratified=False, strata_field='abstract',\\n random_state=None, **kwargs):\\n\\n # initialize text field\\n text_field = torchtext.data.Field(tokenize=get_tokenizer(\\\"spacy\\\"), init_token='<sos>', eos_token='<eos>', lower=True)\\n fields = [('abstract', text_field), ('paper', text_field)]\\n examples = []\\n\\n # Create new dataset by downloading from arxiv or open dataset from folder\\n if not os.path.exists(savepath):\\n os.mkdir(savepath)\\n # create directories for saving the data set\\n if not os.path.exists(os.path.join(savepath, 'temp')):\\n os.mkdir(os.path.join(savepath, 'temp'))\\n if not os.path.exists(os.path.join(savepath, 'abstracts')):\\n os.mkdir(os.path.join(savepath, 'abstracts'))\\n if not os.path.exists(os.path.join(savepath, 'paper')):\\n os.mkdir(os.path.join(savepath, 'paper'))\\n data = cls.download(search_query=search_query, max_results=max_results)\\n abstracts, papers = cls.extract_paper_and_abstract(data, savepath=savepath)\\n\\n # generate all examples\\n for i, (abstract, paper) in enumerate(zip(abstracts, papers)):\\n paper_tokenized = []\\n abstract_tokenized = []\\n # rdeduce the number of words with the textrank approach\\n textranked_paper = summarizer.summarize(paper, words=reduced_words)\\n # add start and end token\\n paper_tokenized += [u'<sos>'] + text_field.preprocess(textranked_paper) + [u'<eos>']\\n abstract_tokenized += [u'<sos>'] + text_field.preprocess(abstract) + [u'<eos>']\\n # initialize examples\\n examples.append(torchtext.data.Example.fromlist([abstract_tokenized, paper_tokenized], fields))\\n\\n # save data samples in txt files\\n with open(os.path.join(savepath,'abstracts','abstract_' + str(i) + '.txt'), 'w+', encoding='utf-8') as abstr:\\n csvwriter = csv.writer(abstr, delimiter=' ')\\n csvwriter.writerow(abstract_tokenized)\\n with open(os.path.join(savepath,'paper','paper_' + str(i) + '.txt'), 'w+', encoding='utf-8') as pap:\\n csvwriter = csv.writer(pap, delimiter=' ')\\n csvwriter.writerow(paper_tokenized)\\n\\n else:\\n # read all files in saved data path\\n paper_files = os.listdir(os.path.join(savepath,'paper'))\\n abstract_files = os.listdir(os.path.join(savepath,'abstracts'))\\n data = [[paper, abstract] for paper, abstract in zip(paper_files, abstract_files)]\\n papers_tokenized = []\\n abstracts_tokenized = []\\n # read paper and abstracts from files\\n for paper, abstract in data:\\n with open(os.path.join(savepath, 'paper', paper), encoding='utf-8') as csvfile:\\n paper = csv.reader(csvfile, delimiter=' ')\\n for pap in paper:\\n if pap:\\n papers_tokenized.append(pap)\\n with open(os.path.join(savepath, 'abstracts', abstract), encoding='utf-8') as csvfile:\\n abstract = csv.reader(csvfile, delimiter=' ')\\n for abstr in abstract:\\n if abstr:\\n abstracts_tokenized.append(abstr)\\n \\n # generate all examples\\n for abstract_tokenized, paper_tokenized in zip(abstracts_tokenized, papers_tokenized):\\n examples.append(torchtext.data.Example.fromlist([abstract_tokenized, paper_tokenized], fields))\\n\\n # create initial dataset\\n dataset = PaperAbstractDataset(examples, fields)\\n # split dataset\\n splits = dataset.split(split_ratio=split_ratio, stratified=stratified, strata_field=strata_field,\\n random_state=random_state)\\n # initialize vocabulary\\n pre_trained_vector_type = 'glove.6B.300d'\\n for d in splits:\\n for name, field in d.fields.items():\\n field.build_vocab(splits[0], vectors=pre_trained_vector_type)\\n d.filter_examples(['abstract', 'paper'])\\n return splits\",\n \"def _get_scatter_keys(datastore, query, num_splits, partition):\\n scatter_point_query = _create_scatter_query(query, num_splits)\\n\\n key_splits = []\\n while True:\\n req = datastore_pb2.RunQueryRequest()\\n if partition:\\n req.partition_id.CopyFrom(partition)\\n\\n req.query.CopyFrom(scatter_point_query)\\n\\n resp = datastore.run_query(req)\\n for entity_result in resp.batch.entity_results:\\n key_splits.append(entity_result.entity.key)\\n\\n if resp.batch.more_results != query_pb2.QueryResultBatch.NOT_FINISHED:\\n break\\n\\n scatter_point_query.start_cursor = resp.batch.end_cursor\\n scatter_point_query.limit.value -= len(resp.batch.entity_results)\\n\\n key_splits.sort(helper.key_comparator)\\n return key_splits\",\n \"def get_chunks_result(self, data_keys: List[str], fetch_only: bool = False) -> List:\",\n \"def __split_dataset(self):\\n self.train, self.valid, _, _ = train_test_split(self.data, self.data, test_size=0.2)\\n self.valid, self.test, _, _ = train_test_split(self.valid, self.valid, test_size=0.5)\",\n \"def batch(self, sql):\\n return _Batch(self.conn, sql)\",\n \"def split_data(df, split_method='fo', test_size=.2, random_state=42):\\n if split_method == 'fo':\\n train_set, test_set = _split_fo(df,\\n test_size=test_size,\\n random_state=random_state)\\n elif split_method == 'tfo':\\n train_set, test_set = _split_tfo(df, test_size=test_size)\\n elif split_method == 'ufo':\\n train_set, test_set = _split_ufo(df,\\n test_size=test_size,\\n random_state=random_state)\\n elif split_method == 'utfo':\\n train_set, test_set = _split_utfo(df, test_size=test_size)\\n else:\\n raise HuitreError('Invalid data_split value, expect: ufo, utfo')\\n train_set = train_set.reset_index(drop=True)\\n test_set = test_set.reset_index(drop=True)\\n return train_set, test_set\",\n \"def split_dataset(self, split):\\n trunk_pos_size = math.ceil((1 - split) * len(self.Pos))\\n trunk_neg_size = math.ceil((1 - split) * len(self.Neg))\\n trunk_num = int(1 / (1 - split))\\n pos_temp = list()\\n neg_temp = list()\\n for index in range(trunk_num):\\n pos_temp.append(self.Pos[index * trunk_pos_size:(index + 1) *\\n trunk_pos_size])\\n neg_temp.append(self.Neg[index * trunk_neg_size:(index + 1) *\\n trunk_neg_size])\\n self.test = pos_temp.pop(2) + neg_temp.pop(2)\\n # self.train = [i for item in pos_temp + neg_temp for i in item]\\n self.train = []\\n for item in pos_temp + neg_temp:\\n for i in item:\\n self.train.append(i)\\n\\n random.shuffle(self.train)\\n random.shuffle(self.test)\",\n \"def fetch_things2(query, chunk_size = 100, batch_fn = None):\\r\\n orig_rules = deepcopy(query._rules)\\r\\n query._limit = chunk_size\\r\\n items = list(query)\\r\\n done = False\\r\\n while items and not done:\\r\\n #don't need to query again at the bottom if we didn't get enough\\r\\n if len(items) < chunk_size:\\r\\n done = True\\r\\n\\r\\n if batch_fn:\\r\\n items = batch_fn(items)\\r\\n\\r\\n for i in items:\\r\\n yield i\\r\\n\\r\\n if not done:\\r\\n query._rules = deepcopy(orig_rules)\\r\\n query._after(i)\\r\\n items = list(query)\",\n \"def make_splits(self):\\n # produce fold/portion splits of the training indexes: these output indexes to the tr. indexes themselves\\n if self.folds is not None:\\n meta_trainval_idx = kfold_split(self.train_idx, self.folds, self.seed, self.labels, self.label_info)\\n elif self.portion is not None:\\n meta_trainval_idx = portion_split(self.train_idx, self.portion, self.seed, self.labels, self.label_info)\\n else:\\n meta_trainval_idx = [(np.arange(len(self.train_idx)), np.arange(0, dtype=np.int32))]\\n # \\\"dereference\\\" the metaindexes to point to the data themselves\\n self.trainval_idx = []\\n for (tidx, vidx) in meta_trainval_idx:\\n self.trainval_idx.append((self.train_idx[tidx], self.train_idx[vidx]))\",\n \"def executeQuery(self, segments=None,):\\n if not segments: segments = self.segments\\n query =''.join(['INSERT INTO ', self.tableName, ' (',\\n ', '.join(self.firstLine), ') VALUES ',\\n ', '.join([segment for segment in segments]), ';'])\\n try:\\n self.cursorExecute(query)\\n except:\\n print 'Bulk query rejected, splitting into smaller queries.'\\n self.handleSQLRejection(0, len(self.segments))\",\n \"def _split_query(query):\\n\\n\\tqq = query.split(' ')\\n\\tkeywords = []\\n\\taccum = None\\n\\tfor kw in qq: \\n\\t\\tif accum is None: \\n\\t\\t\\tif kw.startswith('\\\"'):\\n\\t\\t\\t\\taccum = kw[1:]\\n\\t\\t\\telif kw: \\n\\t\\t\\t\\tkeywords.append(kw)\\n\\t\\telse:\\n\\t\\t\\taccum += ' ' + kw\\n\\t\\t\\tif kw.endswith('\\\"'):\\n\\t\\t\\t\\tkeywords.append(accum[0:-1])\\n\\t\\t\\t\\taccum = None\\n\\tif accum is not None:\\n\\t\\tkeywords.append(accum)\\n\\treturn [kw.strip() for kw in keywords if kw.strip()]\",\n \"def split(self, sep=None, maxsplit=None):\\n return split(self, sep, maxsplit)\",\n \"def split_dataset(self, test_size=0.20):\\n\\t\\t(self.training_data, self.test_data, self.training_labels, self.test_labels) = train_test_split(self.training_data, self.training_labels, test_size=test_size)\",\n \"def _create_scatter_query(query, num_splits):\\n\\n scatter_query = query_pb2.Query()\\n for kind in query.kind:\\n scatter_kind = scatter_query.kind.add()\\n scatter_kind.CopyFrom(kind)\\n\\n # ascending order\\n datastore_helper.add_property_orders(scatter_query, SCATTER_PROPERTY_NAME)\\n\\n # There is a split containing entities before and after each scatter entity:\\n # ||---*------*------*------*------*------*------*---|| * = scatter entity\\n # If we represent each split as a region before a scatter entity, there is an\\n # extra region following the last scatter point. Thus, we do not need the\\n # scatter entity for the last region.\\n scatter_query.limit.value = (num_splits - 1) * KEYS_PER_SPLIT\\n datastore_helper.add_projection(scatter_query, KEY_PROPERTY_NAME)\\n\\n return scatter_query\",\n \"def run(self, query, project=\\\"odyssey-193217\\\"):\\n\\t\\tfrom google.cloud import bigquery\\n\\t\\tjob_config = bigquery.QueryJobConfig()\\n\\t\\tclient = bigquery.Client(project=project)\\n\\t\\tresult = client.query(query,job_config=job_config)\\n\\t\\tjob_config.allowLargeResults = True\\n\\t\\tresult.__done_timeout = 99999999\\n\\t\\treturn list(result)\",\n \"def dataset_splits(self):\\n # 10% evaluation data\\n return [{\\n \\\"split\\\": problem.DatasetSplit.TRAIN,\\n \\\"shards\\\": 799,\\n }, {\\n \\\"split\\\": problem.DatasetSplit.EVAL,\\n \\\"shards\\\": 1,\\n }]\",\n \"def split(self):\\n\\n # FIXME: user should be able to change the default behavior of\\n # this function (for instance user may require one filter not\\n # to split the content of the input file and the same input \\n # to be used by the next filter.\\n \\n utils.split_file(self.files['hit_ids'],\\n self.files['input'],\\n self.files['filtered_reads'],\\n self.files['survived_reads'])\",\n \"def _split_on_chunks(self, iterable, size):\\n return utils.split_on_chunks(iterable, size)\",\n \"def test_partition_on_very_large_vertex_than_has_to_be_split(self):\\n self.setup()\\n large_vertex = TestVertex(500, \\\"Large vertex\\\")\\n self.assertEqual(large_vertex._model_based_max_atoms_per_core, 256)\\n self.graph = ApplicationGraph(\\n \\\"Graph with large vertex\\\", [large_vertex], [])\\n graph, mapper = self.bp.partition(self.graph, self.machine)\\n self.assertEqual(large_vertex._model_based_max_atoms_per_core, 256)\\n self.assertGreater(len(graph.vertices), 1)\",\n \"def batch_split(self, batch_text, threads=8):\\n pass\",\n \"def split(self):\\n return self.dataset_split\",\n \"def search(self, queries, results, unique_columns):\\n names = [item.name for item in results]\\n for index, item in enumerate(results):\\n item.dataframe.columns = [\\n column\\n if column == unique_columns\\n else '{0}_{1}'.format(column, names[index])\\n for column in item.dataframe.columns\\n ]\\n\\n for index, item in enumerate(results):\\n self._runners.append(\\n PartitionRunner(self, index, queries, results, item.name, unique_columns)\\n )\",\n \"def prepareQuery(self, qid):\\r\\n \\r\\n connection = self.getConnection()\\r\\n cursor = connection.cursor()\\r\\n\\r\\n if self.granularity == 'day':\\r\\n extractTime = \\\"TO_CHAR(t.START_DATE, 'yyyy,mm,dd'), TO_CHAR(t.END_DATE, 'yyyy,mm,dd')\\\"\\r\\n elif self.granularity == 'year':\\r\\n extractTime = \\\"EXTRACT(YEAR FROM t.START_DATE), EXTRACT(YEAR FROM t.END_DATE)\\\"\\r\\n \\r\\n cursor.execute(\\\"SELECT t.TYPE, t.GEOMETRY.Get_WKT(), \\\" + extractTime + \\\",\\\" + \\\\\\r\\n\\\"t.DATE_TYPE, t.Z_MIN, t.Z_MAX FROM \\\" + self.queriesTable + \\\"\\\"\\\" t \\r\\nWHERE id = \\\"\\\"\\\" + qid + \\\"\\\"\\\" AND dataset = '\\\"\\\"\\\" + self.dataset.lower() + \\\"'\\\")\\r\\n\\r\\n self.qtype, self.wkt, self.start_date, self.end_date, self.timeType, self.ozmin, self.ozmax = cursor.fetchall()[0]\\r\\n\\r\\n if self.wkt is not None:\\r\\n self.wkt = str(self.wkt)\\r\\n connection.close()\\r\\n \\r\\n # Setting up the missing variables along with transformations to the time encoding. \\r\\n if self.granularity == 'day':\\r\\n if self.start_date is None and self.end_date is None:\\r\\n times = [[self.mint * self.scale, self.maxt * self.scale]]\\r\\n elif self.start_date is not None and self.end_date is not None:\\r\\n self.start_date = map(int, self.start_date.split(','))\\r\\n self.end_date = map(int, self.end_date.split(','))\\r\\n times = [[reader.daySinceEpoch(self.start_date[0], \\r\\n self.start_date[1], self.start_date[2]) * self.scale, \\r\\n reader.daySinceEpoch(self.end_date[0], \\r\\n self.end_date[1], self.end_date[2]) * self.scale]]\\r\\n elif self.end_date is None:\\r\\n self.start_date = map(int, self.start_date.split(','))\\r\\n times = [[reader.daySinceEpoch(self.start_date[0], self.start_date[1], self.start_date[2]) * self.scale, None]]\\r\\n else:\\r\\n if self.start_date is None and self.end_date is None:\\r\\n times = [[self.mint * self.scale, self.maxt * self.scale]]\\r\\n elif self.start_date is not None and self.end_date is not None:\\r\\n times = [[self.start_date * self.scale, self.end_date * self.scale]]\\r\\n elif self.end_date is None:\\r\\n times = [[self.start_date * self.scale, None]]\\r\\n\\r\\n if self.ozmin is None or self.ozmax is None: #no selectivity on z\\r\\n zmin = int(round((self.minz - self.offz)/self.scalez, 0))\\r\\n zmax = int(round((self.maxz - self.offz)/self.scalez, 0))\\r\\n else:\\r\\n zmin = int(round((self.ozmin - self.offz)/self.scalez, 0))\\r\\n zmax = int(round((self.ozmax - self.offz)/self.scalez, 0))\\r\\n\\r\\n # Preparing the different types of queries: Space and space - time\\r\\n continuous = True\\r\\n if self.wkt:\\r\\n if self.qtype.replace(' ', '').lower() != 'nn-search':\\r\\n ordinates = list(loads(self.wkt).exterior.coords)\\r\\n else:\\r\\n ordinates = list(loads(self.wkt).coords)\\r\\n \\r\\n if self.case == 1: #lxyt\\r\\n geometry = Polygon(self.list2ScaleOffset(ordinates)).wkt\\r\\n if self.qtype.lower() == 'space':\\r\\n coarser = self.params[0] #0, 0\\r\\n else:\\r\\n coarser = self.params[1] #4, 4\\r\\n \\r\\n elif self.case == 2: #lxyzt\\r\\n geometry = Polygon3D(Polygon(self.list2ScaleOffset(ordinates)), zmin, zmax)\\r\\n\\r\\n if self.qtype.lower() == 'space':\\r\\n coarser = self.params[2] #4, 4\\r\\n else:\\r\\n coarser = self.params[3] #3, 3\\r\\n\\r\\n elif self.case == 3: #dxyt\\r\\n geom = Polygon(self.list2ScaleOffset(ordinates)) \\r\\n if times[0][1] is None:\\r\\n continuous = False\\r\\n times[0][1] = times[0][0]\\r\\n coarser = self.params[4] #1, 8\\r\\n elif self.qtype.lower() == 'space':\\r\\n if times[0][0] == times[0][1]:\\r\\n continuous = False\\r\\n coarser = self.params[5] #-2, 1\\r\\n else:\\r\\n coarser = self.params[5] - 7\\r\\n elif self.timeType == 'continuous':\\r\\n coarser = self.params[6] #0, 2\\r\\n elif self.timeType == 'discrete':\\r\\n coarser = self.params[7] #3, 8\\r\\n \\r\\n if self.timeType == 'discrete' and (self.start_date is not None) and (self.end_date is not None):\\r\\n geometry = [dynamicPolygon(geom, times[0][0], times[0][0]),\\r\\n dynamicPolygon(geom, times[0][1], times[0][1])]\\r\\n else:\\r\\n geometry = dynamicPolygon(geom, times[0][0], times[0][1]) \\r\\n \\r\\n elif self.case == 4: #dxyzt\\r\\n geom = Polygon(self.list2ScaleOffset(ordinates))\\r\\n if times[0][1] == None:\\r\\n continuous = False\\r\\n coarser = self.params[8] #4, 9\\r\\n times[0][1] = times[0][0]\\r\\n elif self.qtype.lower() == 'space':\\r\\n if times[0][0] == times[0][1]:\\r\\n coarser = self.params[9] #0, 2\\r\\n else:\\r\\n coarser = self.params[9] - 4\\r\\n elif self.timeType == 'continuous':\\r\\n coarser = self.params[10] #0, 2\\r\\n elif self.timeType == 'discrete':\\r\\n coarser = self.params[11] #4, 9\\r\\n \\r\\n if self.timeType == 'discrete' and self.start_date is not None and self.end_date is not None:\\r\\n geometry = [Polygon4D(geom, zmin, zmax, times[0][0], times[0][0]),\\r\\n Polygon4D(geom, zmin, zmax, times[0][1], times[0][1])]\\r\\n else:\\r\\n geometry = Polygon4D(geom, zmin, zmax, times[0][0], times[0][1])\\r\\n \\r\\n else: #time queries\\r\\n if self.case == 1:\\r\\n geometry = []\\r\\n \\r\\n elif self.case == 2:\\r\\n geometry = []\\r\\n \\r\\n elif self.case == 3:\\r\\n temp_geom = self.list2ScaleOffset([(self.minx, self.miny), (self.maxx, self.maxy)])\\r\\n geom = box(temp_geom[0][0], temp_geom[0][1], temp_geom[1][0], temp_geom[1][1])\\r\\n \\r\\n if times[0][1] is None:\\r\\n times[0][1] = times[0][0]\\r\\n coarser = self.params[12] #3, 7\\r\\n continuous = False\\r\\n elif self.timeType == 'continuous':\\r\\n coarser = self.params[13] #0, 3\\r\\n else:\\r\\n coarser = self.params[14] #3, 8\\r\\n \\r\\n if self.timeType == 'discrete' and self.start_date is not None and self.end_date is not None:\\r\\n geometry = [dynamicPolygon(geom, times[0][0], times[0][0]),\\r\\n dynamicPolygon(geom, times[0][1], times[0][1])]\\r\\n else:\\r\\n geometry = dynamicPolygon(geom, times[0][0], times[0][1])\\r\\n\\r\\n elif self.case == 4:\\r\\n temp_geom = self.list2ScaleOffset([(self.minx, self.miny),(self.maxx, self.maxy)])\\r\\n geom = box(temp_geom[0][0], temp_geom[0][1], temp_geom[1][0], temp_geom[1][1])\\r\\n if times[0][1] is None:\\r\\n times[0][1] = times[0][0]\\r\\n coarser = self.params[15] #4, 12\\r\\n continuous = False\\r\\n elif self.timeType == 'continuous':\\r\\n coarser = self.params[16] #1, 3\\r\\n elif self.timeType == 'discrete':\\r\\n coarser = self.params[17] #4, 11\\r\\n \\r\\n if self.timeType == 'discrete' and self.start_date is not None and self.end_date is not None:\\r\\n geometry = [Polygon4D(geom, zmin, zmax, times[0][0], times[0][0]),\\r\\n Polygon4D(geom, zmin, zmax, times[0][1], times[0][1])]\\r\\n else: \\r\\n geometry = Polygon4D(geom, zmin, zmax, times[0][0], times[0][1])\\r\\n \\r\\n\\r\\n \\\"\\\"\\\"The final lines have to do with the way of posing the query to the \\r\\n database. Two options are possible:\\r\\n (a) sql: A SQL query is posed to the database. The number of ranges is\\r\\n limited by a maximum number.\\r\\n (b) join: The table is joined explicitly with a table containing the \\r\\n ranges.\\\"\\\"\\\"\\r\\n if geometry == []:\\r\\n mortonWhere, self.mortonJoinWhere, ranges, rangeTab, morPrep, insert, Levels = ('', '', 0, None, 0, 0, 0)\\r\\n else:\\r\\n if self.method == 'join':\\r\\n rangeTab = (self.rangeTable + qid).upper()\\r\\n ranges, morPrep, insert, Levels = self.join(geometry, coarser, rangeTab, continuous)\\r\\n mortonWhere = self.mortonJoinWhere\\r\\n elif self.method == 'sql':\\r\\n rangeTab, insert = None, 0\\r\\n mortonWhere, ranges, morPrep, Levels = self.sql(geometry, coarser, continuous)\\r\\n \\r\\n # if deep the time is in the morton code\\r\\n if self.integration == 'deep' or (self.start_date is None and self.end_date is None and self.integration == 'loose'): \\r\\n timeWhere = ''\\r\\n elif self.integration == 'loose': \\r\\n timeWhere = whereClause.addTimeCondition(times, 'time', self.timeType)\\r\\n \\r\\n return whereClause.getWhereStatement([timeWhere, mortonWhere]), ranges, morPrep, insert, Levels, rangeTab\",\n \"def split(self, num_or_size_splits, shuffle=False):\\n raise NotImplementedError\",\n \"def split_dataframe(df, size=10*1024*1024):\\n \\n # size of each row\\n row_size = df.memory_usage().sum() / len(df)\\n # maximum number of rows in each segment\\n row_limit = int(size // row_size)\\n # number of segments\\n seg_num = (len(df)+row_limit-1)//row_limit\\n # split df into segments\\n segments = [df.iloc[i*row_limit : (i+1)*row_limit] for i in range(seg_num)]\\n\\n return segments\",\n \"def make_splits(input_pkl, test_split=0.1, val_split=0.1):\\n if (test_split > 1) or (val_split > 1) or (test_split + val_split > 1) or (test_split <= 0) or (val_split <= 0):\\n logging.warning('Check the input for make splits, quitting')\\n exit()\\n\\n main_dict = load_pickle(input_pkl)\\n data, labels = main_dict['data'], main_dict['labels']\\n idx_arr = np.random.choice(len(data), len(data))\\n data, labels = data[idx_arr], labels[idx_arr]\\n print(len(data[0][-1]))\\n # Find the split sizes\\n val_split = int(len(data) * val_split)\\n test_split = val_split + int(len(data) * test_split)\\n\\n # Make and save the splits\\n save_pickle({'data': data[:val_split], 'labels': labels[:val_split]}, 'data/val.pkl')\\n save_pickle({'data': data[val_split:test_split], 'labels': labels[val_split:test_split]}, 'data/test.pkl')\\n save_pickle({'data': data[test_split:], 'labels': labels[test_split:]}, 'data/train.pkl')\",\n \"def process(self, lists, subqueries):\\n pass\",\n \"def test_split_ranges(self):\\n start = datetime.utcnow() - pd.Timedelta(\\\"5H\\\")\\n end = datetime.utcnow() + pd.Timedelta(\\\"5min\\\")\\n delta = pd.Timedelta(\\\"1H\\\")\\n\\n ranges = QueryProvider._calc_split_ranges(start, end, delta)\\n self.assertEqual(len(ranges), 5)\\n self.assertEqual(ranges[0][0], start)\\n self.assertEqual(ranges[-1][1], end)\\n\\n st_times = [start_tm[0] for start_tm in ranges]\\n for end_time in (end_tm[1] for end_tm in ranges):\\n self.assertNotIn(end_time, st_times)\\n\\n end = end + pd.Timedelta(\\\"20min\\\")\\n ranges = QueryProvider._calc_split_ranges(start, end, delta)\\n self.assertEqual(len(ranges), 5)\\n self.assertEqual(ranges[0][0], start)\\n self.assertEqual(ranges[-1][1], end)\",\n \"def split_data(self, val_size=0.1, test_size=0.5):\\n df = pd.read_csv(self.csv_path, delimiter=';')\\n train, val = train_test_split(df, test_size=val_size)\\n val, test = train_test_split(df, test_size=test_size)\\n return train, val, test\",\n \"def qids_to_splits(qids):\\n qidmap = {}\\n i = 0\\n for qid in qids:\\n if not qid in qidmap:\\n qidmap[qid] = i\\n i+=1\\n new_qids = []\\n for qid in qids:\\n new_qids.append(qidmap[qid])\\n qidcount = np.max(new_qids)+1\\n splits = [[] for i in range(qidcount)]\\n for i, qid in enumerate(new_qids):\\n splits[qid].append(i) \\n return splits\",\n \"def split_all(self):\\n for domino in self.dominoes[:]:\\n self.split(domino)\",\n \"def query_and_return(project_id, dataset_id, table_id, query, legacy=False):\\n if not legacy:\\n # Rename any legacy-style table references to use standard\\n # SQL dialect. Because we use a mixture of both, we\\n # standardise on only using the legacy style for the time\\n # being.\\n query = re.sub(r'\\\\[(.+?):(.+?)\\\\.(.+?)\\\\]', r'\\\\1.\\\\2.\\\\3', query)\\n payload = {\\n \\\"configuration\\\": {\\n \\\"query\\\": {\\n \\\"query\\\": query,\\n \\\"flattenResuts\\\": False,\\n \\\"allowLargeResults\\\": True,\\n \\\"timeoutMs\\\": 100000,\\n \\\"useQueryCache\\\": True,\\n \\\"useLegacySql\\\": legacy,\\n \\\"destinationTable\\\": {\\n \\\"projectId\\\": project_id,\\n \\\"tableId\\\": table_id,\\n \\\"datasetId\\\": dataset_id\\n },\\n \\\"createDisposition\\\": \\\"CREATE_IF_NEEDED\\\",\\n \\\"writeDisposition\\\": \\\"WRITE_TRUNCATE\\\"\\n }\\n }\\n }\\n # We've started using the google-cloud library since first\\n # writing this. TODO: decide if we can use that throughout\\n bq = get_bq_service()\\n logger.info(\\\"Writing to bigquery table %s\\\" % table_id)\\n start = datetime.datetime.now()\\n response = bq.jobs().insert(\\n projectId=project_id,\\n body=payload).execute()\\n counter = 0\\n job_id = response['jobReference']['jobId']\\n while True:\\n time.sleep(1)\\n response = bq.jobs().get(\\n projectId=project_id,\\n jobId=job_id).execute()\\n counter += 1\\n if response['status']['state'] == 'DONE':\\n if 'errors' in response['status']:\\n query = str(response['configuration']['query']['query'])\\n for i, l in enumerate(query.split(\\\"\\\\n\\\")):\\n # print SQL query with line numbers for debugging\\n print \\\"{:>3}: {}\\\".format(i + 1, l)\\n raise StandardError(\\n json.dumps(response['status']['errors'], indent=2))\\n else:\\n break\\n bytes_billed = float(\\n response['statistics']['query']['totalBytesBilled'])\\n gb_processed = round(bytes_billed / 1024 / 1024 / 1024, 2)\\n est_cost = round(bytes_billed / 1e+12 * 5.0, 2)\\n # Add our own metadata\\n elapsed = (datetime.datetime.now() - start).total_seconds()\\n response['openp'] = {'query': query,\\n 'est_cost': est_cost,\\n 'time': elapsed,\\n 'gb_processed': gb_processed}\\n logger.info(\\\"Time %ss, cost $%s\\\" % (elapsed, est_cost))\\n return response\",\n \"def split_file(self, input_file):\\r\\n file_list = [] \\r\\n with open(input_file, 'r', encoding='GB18030', errors='ignore') as f_in:\\r\\n data = f_in.readlines()\\r\\n lines_num = len(data)\\r\\n size = lines_num // self.num_workers # lines splitted in a chunk\\r\\n start = 0\\r\\n end = size\\r\\n w_path = \\\"../data/\\\"\\r\\n for i in range(lines_num//size):\\r\\n chunk_name = \\\"chunk_\\\" + str(i) + \\\".dat\\\"\\r\\n with open(w_path + chunk_name, 'w', encoding='utf-8') as f_out:\\r\\n f_out.write(''.join(data[start:end]))\\r\\n start = start + size\\r\\n end = end + size\\r\\n file_list.append(\\\"../data/chunk_\\\" + str(i) + \\\".dat\\\")\\r\\n \\r\\n print(f\\\"File splitted into {self.num_workers} chunks.\\\")\\r\\n return file_list, size\",\n \"def fit_train(self, train_filename=\\\"data/train.tsv\\\", chunksize=500, sep=\\\"\\\\t\\\",n_jobs=cpu_count):\\n all_result_maps = []\\n\\n for chunk in pd.read_csv(train_filename, chunksize=chunksize, sep=sep):\\n chunk_split = np.array_split(chunk.values, n_jobs)\\n pool = Pool(n_jobs)\\n result_map = pool.map(self._preprocess_chunk_for_train, chunk_split)\\n pool.close()\\n pool.join()\\n\\n all_result_maps.extend(result_map)\\n\\n result_df = pd.DataFrame(all_result_maps)\\n self._calculate_statistics(result_df)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.69221485","0.65455127","0.6398275","0.5844143","0.58412147","0.5747338","0.5668508","0.5646011","0.56448406","0.5368807","0.53658277","0.53620774","0.5309061","0.5297343","0.5291058","0.52775466","0.5261138","0.52405804","0.5234456","0.519282","0.5162029","0.51531166","0.5119127","0.5115571","0.50713575","0.5068621","0.50579876","0.5056491","0.5032128","0.49864757","0.4972239","0.49708173","0.49664328","0.49568433","0.49444896","0.49405617","0.49393272","0.49270615","0.49115568","0.4907825","0.4901987","0.4899477","0.48985183","0.48876348","0.48786286","0.4875249","0.48724726","0.4865253","0.48596048","0.48434287","0.48358527","0.4832636","0.48321748","0.4830451","0.48223463","0.48078558","0.48073643","0.48059687","0.48004872","0.47988513","0.47980592","0.479428","0.47917664","0.4788295","0.47736815","0.47727853","0.47710603","0.47697312","0.47647068","0.475796","0.47509623","0.47472325","0.47395346","0.473071","0.47301355","0.4725344","0.4724061","0.47229695","0.47176224","0.47111177","0.470251","0.46965548","0.46954745","0.46932775","0.46916062","0.46809524","0.46771348","0.4676351","0.46699545","0.46672353","0.46617335","0.4661476","0.46583995","0.46551153","0.46495652","0.46459123","0.46406654","0.4639739","0.46315858"],"string":"[\n \"0.69221485\",\n \"0.65455127\",\n \"0.6398275\",\n \"0.5844143\",\n \"0.58412147\",\n \"0.5747338\",\n \"0.5668508\",\n \"0.5646011\",\n \"0.56448406\",\n \"0.5368807\",\n \"0.53658277\",\n \"0.53620774\",\n \"0.5309061\",\n \"0.5297343\",\n \"0.5291058\",\n \"0.52775466\",\n \"0.5261138\",\n \"0.52405804\",\n \"0.5234456\",\n \"0.519282\",\n \"0.5162029\",\n \"0.51531166\",\n \"0.5119127\",\n \"0.5115571\",\n \"0.50713575\",\n \"0.5068621\",\n \"0.50579876\",\n \"0.5056491\",\n \"0.5032128\",\n \"0.49864757\",\n \"0.4972239\",\n \"0.49708173\",\n \"0.49664328\",\n \"0.49568433\",\n \"0.49444896\",\n \"0.49405617\",\n \"0.49393272\",\n \"0.49270615\",\n \"0.49115568\",\n \"0.4907825\",\n \"0.4901987\",\n \"0.4899477\",\n \"0.48985183\",\n \"0.48876348\",\n \"0.48786286\",\n \"0.4875249\",\n \"0.48724726\",\n \"0.4865253\",\n \"0.48596048\",\n \"0.48434287\",\n \"0.48358527\",\n \"0.4832636\",\n \"0.48321748\",\n \"0.4830451\",\n \"0.48223463\",\n \"0.48078558\",\n \"0.48073643\",\n \"0.48059687\",\n \"0.48004872\",\n \"0.47988513\",\n \"0.47980592\",\n \"0.479428\",\n \"0.47917664\",\n \"0.4788295\",\n \"0.47736815\",\n \"0.47727853\",\n \"0.47710603\",\n \"0.47697312\",\n \"0.47647068\",\n \"0.475796\",\n \"0.47509623\",\n \"0.47472325\",\n \"0.47395346\",\n \"0.473071\",\n \"0.47301355\",\n \"0.4725344\",\n \"0.4724061\",\n \"0.47229695\",\n \"0.47176224\",\n \"0.47111177\",\n \"0.470251\",\n \"0.46965548\",\n \"0.46954745\",\n \"0.46932775\",\n \"0.46916062\",\n \"0.46809524\",\n \"0.46771348\",\n \"0.4676351\",\n \"0.46699545\",\n \"0.46672353\",\n \"0.46617335\",\n \"0.4661476\",\n \"0.46583995\",\n \"0.46551153\",\n \"0.46495652\",\n \"0.46459123\",\n \"0.46406654\",\n \"0.4639739\",\n \"0.46315858\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.6370883"},"document_rank":{"kind":"string","value":"4"}}},{"rowIdx":15599,"cells":{"query":{"kind":"string","value":"StreamHealth runs a streaming RPC to the tablet, that returns the current health of the tablet on a regular basis."},"document":{"kind":"string","value":"def StreamHealth(self, request, context):\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\n context.set_details('Method not implemented!')\n raise NotImplementedError('Method not implemented!')"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def StreamHealth(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\n raise NotImplementedError()","def StreamHealth(self, request, context):\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)","async def health(self):\n\n request = telemetry_pb2.SubscribeHealthRequest()\n health_stream = self._stub.SubscribeHealth(request)\n\n try:\n async for response in health_stream:\n \n\n \n yield Health.translate_from_rpc(response.health)\n finally:\n health_stream.cancel()","def poll_health():\n global timesCalled\n\n # Poll /health\n session = requests.Session()\n retry = Retry(connect=3, backoff_factor=0.5)\n adapter = HTTPAdapter(max_retries=retry)\n session.mount('http://', adapter)\n response = session.get(health_url)\n\n # Check HTTP status code\n status_code = response.status_code\n if status_code != status_ok:\n exit(1)\n\n # Get metrics values\n metrics = response.json()['metrics']\n requestLatencyValues.append(metrics['requestLatency'])\n dbLatencyValues.append(metrics['dbLatency'])\n cacheLatencyValues.append(metrics['cacheLatency'])\n\n # If 60 seconds has passed, send data to STDOUT\n timesCalled += 1\n if timesCalled == 6:\n output_data()\n\n timesCalled = 0\n requestLatencyValues.clear()\n dbLatencyValues.clear()\n cacheLatencyValues.clear()","def Stream():\r\n \r\n config = config_create()\r\n CONSUMER_KEY = config.get('Auth', 'CONSUMER_KEY') \r\n CONSUMER_SECRET = config.get('Auth', 'CONSUMER_SECRET')\r\n ACCESS_KEY = config.get('Auth', 'ACCESS_KEY')\r\n ACCESS_SECRET = config.get('Auth', 'ACCESS_SECRET')\r\n searchterm = config.get('Filter','search')\r\n name = multiprocessing.current_process().name\r\n \"\"\"Function that will manage doing the twitter stream\"\"\"\r\n stream = MyStreamer(CONSUMER_KEY, CONSUMER_SECRET, ACCESS_KEY, ACCESS_SECRET)\r\n stream.statuses.filter(track= searchterm)","def waspstat():\n\n\trespond = send_command('waspstat')\n\n\treturn respond","def get_health(self):\n return self.bot_client.send_command(_Command.GetHealth)","def _retrieve_health_data(self):\n return self._client.request('_cluster/health', query={'level': 'shards'}).data","def get_stream_stats(self, stream, isCollectionStream=False, local=False):\n if isCollectionStream is False:\n if local is True:\n stream = \"c8locals.\" + stream\n else:\n stream = \"c8globals.\" + stream\n if local is True:\n endpoint = '{}/{}/stats?global=False'.format(ENDPOINT, stream)\n elif local is False:\n endpoint = '{}/{}/stats?global=True'.format(ENDPOINT, stream)\n\n request = Request(method='get', endpoint=endpoint)\n\n def response_handler(resp):\n code = resp.status_code\n if resp.is_success:\n return json.loads(resp.body['result'])\n elif code == 403:\n raise ex.StreamPermissionError(resp, request)\n raise ex.StreamConnectionError(resp, request)\n\n return self._execute(request, response_handler)","async def health(self) -> Health:\n response = await self._http_requests.get(build_url(Paths.HEALTH))\n return Health(**response.json())","def StreamExecute(self, request, context):\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)","def TemperatureStream(self, request, context):\n logging.info(\"Temperature Stream Request\") # Log\n length = request.length\n metadata = [(b'device', b'Thermometer'), (b'version',\n b'0.1'), (b'precision', b'1 decimal')]\n context.send_initial_metadata(metadata)\n context.add_callback(self.stream_callback)\n try:\n for i in range(0, length):\n time.sleep(1)\n datapoint = device_pb2.Datapoint()\n val = 20 + random.normalvariate(0, 2) # Fake values\n datapoint.value = val\n datapoint.unit = 0\n logging.info('Sending data')\n yield datapoint\n except Exception as e:\n logging.exception(str(e))","def health():\n return jsonify(hostname=hostname, uptime=uptime(), \\\n cpu_percent=int(cpu_percent(interval=None, percpu=False)))","def getDeviceHealthReport(self, df: str = None, ts: str = None, cursor: str = None, pageSize: int = None):\n params = {\n 'df': df,\n 'ts': ts,\n 'cursor': cursor,\n 'pageSize': pageSize\n }\n return self.api_get_request(f'{self.NINJA_API_QUERIES_DEVICE_HEALTH}', params=params)","def GetHealthStatus(self, request, context):\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\n context.set_details('Method not implemented!')\n raise NotImplementedError('Method not implemented!')","def meter_stats():\n current_time = time.time()\n r = requests.get('http://localhost:8080/stats/flow/1')\n r.raise_for_status()\n data = r.json()\n bytes_tx = 0\n for stat in data['1']:\n if stat['match'].get('dl_src') == '00:00:00:00:00:01':\n bytes_tx += stat['byte_count']\n global LAST_TIME\n global LAST_BYTES_TX\n time_diff = current_time - LAST_TIME\n byte_diff = bytes_tx - LAST_BYTES_TX\n LAST_TIME = current_time\n LAST_BYTES_TX = bytes_tx\n transfer_rate = byte_diff / time_diff / 1024\n # We need to accomodate the dropping of our rule with the hard timeout\n return jsonify({'transfer_rate': transfer_rate})","def subscribe_to_host_statistics(self):\n\t\treturn Job(SDK.PrlSrv_SubscribeToHostStatistics(self.handle)[0])","async def health(request):\n\n r = dict(\n health='green'\n )\n\n return json(r)","def stats(containerids, stream):\n click.echo('*** MONITORING IS INITIATED')\n if(stream):\n while True:\n for x in containerids:\n index = slice(12)\n monitoring(containerid=x[index])\n else:\n for x in containerids:\n index = slice(12)\n monitoring(containerid=x[index])","async def health(request):\n return web.Response(text=\"ok\")","async def test_health():\n response = health()\n assert response\n assert {'status': 'ok'} == response","def get_realtime_stream(self):\n ws = 0\n url = WS_URL % (self.sense_monitor_id, self.sense_access_token)\n try:\n ws = create_connection(url, timeout=self.wss_timeout, sslopt={'ciphers': 'DEFAULT@SECLEVEL=1'})\n while True: # hello, features, [updates,] data\n result = json.loads(ws.recv())\n if result.get('type') == 'realtime_update':\n data = result['payload']\n self.set_realtime(data)\n yield data\n except WebSocketTimeoutException:\n raise SenseAPITimeoutException(\"API websocket timed out\")\n finally:\n if ws: ws.close()","def StreamExecute(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\n raise NotImplementedError()","def squares_streaming_get():\n \n return 'do some magic!'","def stream_status_event(self, event):\r\n pass","def get(self):\n log.debug('/x-tree/FSMonitor.html: invoked')\n try:\n log.info('application health check...')\n host_name = socket.gethostname()\n url = \"http://localhost:8086/query\"\n querystring = {\"pretty\": \"true\", \"db\": \"IOT\",\n \"q\": \"SELECT count(*) FROM \\\"ttd_devices\\\" \"}\n response = requests.request(\"GET\", url, params=querystring)\n D=json.loads(response.text)\n total_recs=str(max(D['results'][0]['series'][0]['values'][0][1:]))\n except:\n result = {}\n log.exception('Exception while doing HealthCheck')\n return Response ('<html><body>THE SERVER IS DOWN</body></html>', mimetype=\"text/html\", status=500)\n return Response('<html><body>INFLUX DB <p/> Count:' + total_recs + '</body></html>', mimetype=\"text/html\")","def StreamExecute(self, request, context):\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\n context.set_details('Method not implemented!')\n raise NotImplementedError('Method not implemented!')","def StreamExecute(self, request, context):\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\n context.set_details('Method not implemented!')\n raise NotImplementedError('Method not implemented!')","def health():\n global _is_healthy\n template = render_template('health.html', healthy=_is_healthy)\n return make_response(template, 200 if _is_healthy else 500)","def get_health_info(handle, timeout):\n health = dict()\n\n health['stat'] = ceph_mon_command(handle, 'health' , timeout)\n # TODO command not known with ceph_mon_command\n #health['detail'] = ceph_mon_command(handle, 'health detail', timeout)\n health['detail'] = shell_command('ceph health detail') + b'\\n'\n health['df'] = ceph_mon_command(handle, 'df' , timeout)\n health['report'] = ceph_mon_command(handle, 'report' , timeout)\n\n return health","def open_twitter_sample_stream():\n twitter_sample_parameters = {'stall_warnings': 'true', }\n\n r = requests.post('https://stream.twitter.com/1.1/statuses/sample.json',\n data=twitter_sample_parameters,\n auth=oauth_credentials,\n stream=True,\n timeout=300)\n\n if r.status_code != 200:\n received_error(r)\n return None\n\n if r.encoding is None:\n r.encoding = 'utf-8'\n\n return r","def send_to_aws_time_stream(stats, config):\n logging.info('Sending stats to Timestream (database=%s)', config['timestream_database'])\n\n region_config = Config(\n region_name=config['timestream_aws_region']\n )\n\n ts_client = boto3.client(\n 'timestream-write',\n aws_access_key_id=config['timestream_aws_access_key_id'],\n aws_secret_access_key=config['timestream_aws_secret_access_key'],\n config=region_config\n )\n\n try:\n # Attempt to validate connection to database and table\n # Error out and return if not able to access / connection isn't valid\n database = ts_client.describe_database(\n DatabaseName=config['timestream_database']\n )\n logging.debug(\"Database details = %s\" % database)\n\n table = ts_client.describe_table(\n DatabaseName=config['timestream_database'],\n TableName=config['timestream_table']\n )\n logging.debug(\"Table details = %s\" % table)\n except Exception as err:\n logging.error(err)\n return\n\n current_time = time.time_ns()\n logging.debug(\"Converting to timestream - %s\" % stats)\n\n downstream_common_attributes = {\n 'Dimensions': [{'Name': 'measurement', 'Value': 'downstream_statistics'}],\n 'Time': str(current_time),\n 'TimeUnit': 'NANOSECONDS'\n }\n downstream_records = []\n for stats_down in stats['downstream']:\n for key in stats_down:\n if key == 'channel_id':\n continue\n\n downstream_records.append({\n 'Dimensions': [\n {'Name': 'channel_id', 'Value': str(stats_down['channel_id'])},\n {'Name': 'group', 'Value': 'downstream_statistics'}\n ],\n 'MeasureName': key,\n 'MeasureValue': str(stats_down[key]),\n 'MeasureValueType': 'DOUBLE' if isinstance(stats_down[key], float) else 'BIGINT'\n })\n\n try:\n logging.debug(\"Writing common attributes: %s\" % downstream_common_attributes)\n logging.debug(\"Writing records: %s\" % downstream_records)\n result = ts_client.write_records(DatabaseName=config['timestream_database'],\n TableName=config['timestream_table'], Records=downstream_records,\n CommonAttributes=downstream_common_attributes)\n logging.info(\"Timestream response = %s\" % result)\n logging.info(\"Wrote %s records to TimeStream\" % len(downstream_records))\n except (ts_client.exceptions.RejectedRecordsException, Exception) as err:\n logging.error(err)\n\n upstream_common_attributes = {\n 'Dimensions': [{'Name': 'measurement', 'Value': 'upstream_statistics'}],\n 'Time': str(current_time),\n 'TimeUnit': 'NANOSECONDS'\n }\n upstream_records = []\n for stats_up in stats['upstream']:\n for key in stats_up:\n if key == 'channel_id':\n continue\n\n upstream_records.append({\n 'Dimensions': [\n {'Name': 'channel_id', 'Value': str(stats_up['channel_id'])},\n {'Name': 'group', 'Value': 'upstream_statistics'}\n ],\n 'MeasureName': key,\n 'MeasureValue': str(stats_up[key]),\n 'MeasureValueType': 'DOUBLE' if isinstance(stats_up[key], float) else 'BIGINT'\n })\n\n try:\n logging.debug(\"Writing common attributes: %s\" % upstream_common_attributes)\n logging.debug(\"Writing records: %s\" % upstream_records)\n result = ts_client.write_records(DatabaseName=config['timestream_database'],\n TableName=config['timestream_table'], Records=upstream_records,\n CommonAttributes=upstream_common_attributes)\n logging.info(\"Timestream response = %s\" % result)\n logging.info(\"Wrote %s records to TimeStream\" % len(upstream_records))\n except (ts_client.exceptions.RejectedRecordsException, Exception) as err:\n logging.error(err)\n return\n\n logging.info('Successfully wrote data to Timestream')","def UpdateStream(self, request, context):\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)","def process_stream(self, sid, f):\n http_response = wavehttp.get(\"/wave/wfe/channel?VER=6&RID=rpc&SID=\"+sid+\n \"&CI=0&AID=0&TYPE=xmlhttp&zx=\"+self.zx()+\"&t=1\")\n http_data = http_response.read(120)\n print http_data\n exit()\n connection.close()","def test_is_streaming(fprime_test_api):\n results = fprime_test_api.assert_telemetry_count(5, timeout=10)\n for result in results:\n msg = \"received channel {} update: {}\".format(result.get_id(), result.get_str())\n print(msg)\n fprime_test_api.assert_telemetry(\n \"sendBuffComp.SendState\", value=\"SEND_IDLE\", timeout=3\n )","def get_host_stats(self, refresh=False):","def _send_health_txn(self,\r\n txn_type=None,\r\n txn_id=None,\r\n data=None,\r\n state=None,\r\n url=None,\r\n txn_date=None):\r\n #serialization is just a delimited utf-8 encoded strings\r\n if txn_type == 'commit':\r\n payload = \",\".join([txn_type, txn_id, data, state, url]).encode()\r\n elif txn_type == 'health':\r\n payload = \",\".join([txn_type, txn_id, data, state, str(txn_date)]).encode()\r\n\r\n pprint(\"payload: {}\".format(payload))######################################## pprint\r\n\r\n #construct the address\r\n address = self._get_address(txn_id)\r\n\r\n #construct header\r\n header = TransactionHeader(\r\n signer_public_key=self._signer.get_public_key().as_hex(),\r\n family_name=\"health\",\r\n family_version=\"0.1\",\r\n inputs=[address],\r\n outputs=[address],\r\n dependencies=[],\r\n payload_sha512=_sha512(payload),\r\n batcher_public_key=self._signer.get_public_key().as_hex(),\r\n nonce=hex(random.randint(0, 2**64))\r\n ).SerializeToString()\r\n\r\n signature = self._signer.sign(header)\r\n\r\n #create transaction\r\n transaction = Transaction(\r\n header=header,\r\n payload=payload,\r\n header_signature=signature\r\n )\r\n\r\n #create batch list, suserum policy: one transaction per batch\r\n batch_list = self._create_batch_list([transaction])\r\n\r\n return self._send_request(\r\n \"batches\",\r\n batch_list.SerializeToString(),\r\n 'application/octet-stream')","def statistics(target):\n worker=current_worker()\n if (not is_worker_thread()) or (not worker) or (not worker.isopen) or (worker.index<0):\n logging.warning(\"statistics can only be called from activated worker thread\")\n return\n with worker.statistics_lock:\n return target(worker.statistics_data)","def health(self) -> Union[int, float]:\n return self.proto.health","def health(self) -> Union[int, float]:\n return self.proto.health","def health_check():\n app.logger.info(\"Health Check!\")\n return Response(\"All Good!\", status=200)","def hourly_sm_reading_histogram():\r\n cursor = connections[\"ldc\"].cursor()\r\n cursor.execute(\"select smr.Reading \" \r\n \"from essex_annotated.SmartMeterReadings smr \" \r\n \"inner join Meters m on m.MeterID = smr.MeterID \" \r\n \" and m.`Phase` = 1 \" \r\n \"left join meter_data_quality_flag mdqf \" \r\n \" on smr.MeterID = mdqf.MeterID \" \r\n \" and mdqf.applicability_start_date <= '2011-05-01' \" \r\n \" and mdqf.applicability_end_date >= '2012-10-31' \" \r\n \"where smr.MeterID >= 20000 and smr.MeterID < 20100 \" \r\n \"and mdqf.MeterID is null \" \r\n \"and smr.ReadDate >= '2011-05-01' \" \r\n \"and smr.ReadDate <= '2011-10-31'\")\r\n # Create a list of hourly reading values\r\n readings = [row[0] for row in cursor.fetchall()]\r\n \r\n # Create histogram\r\n sample_size = len(readings)\r\n trim_p = 0.0005\r\n p_title = \"Histogram of Hourly Readings \\n\" \\\r\n \"(Summer 2011, sample: \" + str(sample_size) + \" readings, \" \\\r\n \"right trim:\" + str(trim_p * 100.0) + \"%)\"\r\n p_xlabel = \"Hourly Reading (kW)\"\r\n p_ylabel = \"Occurrences\"\r\n create_histogram(readings, trim_p, 0.1, p_title, p_ylabel, p_xlabel, \r\n \"hourly_sm_reading_histogram_summer2011\", 1, \"right\")","def stream_call(self):\n pass","def get_health(self):\n return self.health","def Gethealth(self):\n return self.health","def stats(short_url):\n stats = get_stats(short_url)\n click.echo(stats)","async def async_realtime_stream(self, callback=None, single=False):\n url = WS_URL % (self.sense_monitor_id, self.sense_access_token)\n # hello, features, [updates,] data\n async with websockets.connect(url, ssl=self.ssl_context) as ws:\n while True:\n try:\n async with asyncio_timeout(self.wss_timeout):\n message = await ws.recv()\n except asyncio.TimeoutError as ex:\n raise SenseAPITimeoutException(\"API websocket timed out\") from ex\n\n result = orjson.loads(message)\n if result.get(\"type\") == \"realtime_update\":\n data = result[\"payload\"]\n self._set_realtime(data)\n if callback:\n callback(data)\n if single:\n return\n elif result.get(\"type\") == \"error\":\n data = result[\"payload\"]\n if not data[\"authorized\"]:\n raise SenseAuthenticationException(\"Web Socket Unauthorized\")\n raise SenseWebsocketException(data[\"error_reason\"])","def get_health(self):\n return self.__health","async def check_health():\n return {\"healthy\": True}","def get_health(self):\n return {'status': 'ok'}","def handle_health():\n return flask.jsonify(status=\"up\")","async def twitter_status(self, ctx):\n server_channels = set(c.id for c in ctx.message.server.channels)\n\n followed_count = 0\n displayed_count = 0\n for chan_conf in self.conf.follows:\n # Check if this channel is displayed in the server\n if set(c.id for c in chan_conf.discord_channels) & server_channels:\n followed_count += 1\n displayed_count += sum(c.received_count for c in chan_conf.discord_channels if c.id in server_channels)\n\n # Calculate the average tweets processed per minute\n minutes = (time.time() - self.bot.start_time) / 60\n processed_average = self.processed_tweets / minutes\n processed_average = '< 1' if processed_average < 1 else round(processed_average)\n tweets_processed = '{} (avg {} / min)'.format(self.processed_tweets, processed_average)\n\n # Display the info\n if self.stream.running:\n embed = discord.Embed(title='Stream status', description='Online', colour=0x00ff00)\n else:\n embed = discord.Embed(title='Stream status', description='Offline', colour=0xff0000)\n embed.add_field(name='Tweets processed since startup', value=tweets_processed, inline=False)\n embed.add_field(name='Channels followed', value=followed_count)\n embed.add_field(name='Tweets displayed', value=displayed_count)\n\n await self.bot.say(embed=embed)","def stream():\n return flask.Response(event_stream(flask.request.access_route[0]),\n mimetype='text/event-stream')","async def stream(self, ctx, streamer=None, *, stream_title=None):\n # [p]set stream <streamer> <stream_title>\n\n server = ctx.message.server\n\n current_status = server.me.status if server is not None else None\n\n if stream_title:\n stream_title = stream_title.strip()\n if \"twitch.tv/\" not in streamer:\n streamer = \"https://www.twitch.tv/\" + streamer\n game = discord.Game(type=1, url=streamer, name=stream_title)\n await self.bot.change_presence(game=game, status=current_status)\n log.debug('Owner has set streaming status and url to \"{}\" and {}'.format(stream_title, streamer))\n elif streamer is not None:\n await send_command_help(ctx)\n return\n else:\n await self.bot.change_presence(game=None, status=current_status)\n log.debug('stream cleared by owner')\n await self.bot.say(\"Done.\")","def healthcheck():\n return make_response(jsonify(status=200, message='Healthy'), status.HTTP_200_OK)","def update(self):\n try:\n response = self.client.describe_stream(StreamName=self.stream)\n except Exception as exc:\n logger.exception(f'Failure trying to get stream: \"{self.stream}\".', exc)\n else:\n if response['ResponseMetadata']['HTTPStatusCode'] != 200:\n logger.error(f'Failure to describe stream \"{self.stream}\": {response}')\n else:\n self.description = response['StreamDescription']","def health(self):\n return self._health","def health(self):\n return self._health","def get_health_check(self):\n return util.create_response(output=\"OK\")","def stats(self, **kwargs):\n return stats.stats(self._host, self._session, **kwargs)","def query_stats(self, **kwargs):\n return stats.query(self._host, self._session, **kwargs)","async def handle_ping(request):\n return web.Response(text=f\"OK {datetime.now().isoformat()}\\n\", headers={'Content-Type': 'text/event-stream'})","def test_simple_health_check(self):\n response = self.client.open(\n '/awadallah/VaultsManager/1.0.0/health',\n method='GET')\n self.assert200(response,\n 'Response body is : ' + response.data.decode('utf-8'))","def __process_health(self) -> None:\n status = self.metrics.get(\"Status\", None)\n if status:\n health = status.get(\"Health\", None)\n measurement = \"Health\"\n if health == \"Warning\":\n value = 1\n datapoint = self.__gen_datapoint(measurement, self.label, value)\n self.datapoints.append(datapoint)\n elif health == \"Critical\":\n value = 2\n datapoint = self.__gen_datapoint(measurement, self.label, value)\n self.datapoints.append(datapoint)\n return","def get_humidity(intent, session):\n\n session_attributes = {}\n reprompt_text = None\n\n humidity = get_thing_state(\"MegaIf1\", \"Humidity%\")\n speech_output = \"The humidity is \" + humidity + \" percent. \" \\\n \". Goodbye.\"\n should_end_session = True\n \n return build_response(session_attributes, build_speechlet_response(\n intent['name'], speech_output, reprompt_text, should_end_session))","def stream_tweets(bearer_token):\n print(\"Streaming tweets...\")\n\n oauth2 = osometweet.OAuth2(\n bearer_token=bearer_token,\n manage_rate_limits=False\n )\n ot = osometweet.OsomeTweet(oauth2)\n\n # Add all tweet fields\n all_tweet_fields = osometweet.TweetFields(everything=True)\n\n # Add streaming rules\n rules = [{\"value\": \"coronavirus\", \"tag\": \"all coronavirus tweets\"},\n {\"value\": \"indiana\", \"tag\": \"all indiana tweets\"}]\n add_rules = {\"add\": rules}\n response = ot.set_filtered_stream_rule(rules=add_rules)\n print(f\"API response from adding two rules:\\n{response}\\n\")\n\n # Retrieve active streaming rules\n current_rules = ot.get_filtered_stream_rule()\n print(f'The current filtered stream rules are:\\n{current_rules}\\n')\n\n # Remove a streaming rule by using it's tag\n indiana_rule = [\n rule[\"id\"] for rule in current_rules[\"data\"]\n if 'all indiana tweets' in rule[\"tag\"]\n ]\n delete_rule = {'delete': {'ids': indiana_rule}}\n response = ot.set_filtered_stream_rule(rules=delete_rule)\n print(f\"API response from deleting one rule:\\n{response}\\n\")\n\n # Get today's date\n today = dt.strftime(dt.today(), \"%Y-%m-%d_%H-%M\")\n\n # Open two files. One for good data, the other for tweet errors.\n with open(f\"tweet_stream--{today}.json\", \"a\") as data_file:\n # stream is a Generator\n stream = ot.filtered_stream(fields=all_tweet_fields)\n # We have to iterate over the stream to fetch streamed tweets\n for tweet in stream.iter_lines():\n # Get data and errors\n try:\n data = json.loads(tweet).get(\"data\")\n\n # When data is found, we write it to the open file\n if data:\n json.dump(data, data_file)\n data_file.write(\"\\n\")\n except json.JSONDecodeError:\n pass","def GetStats(self):\r\n\t\tArg1 = self.href\r\n\t\treturn self._execute('GetStats', payload=locals(), response_object=None)","def _request_stats(self, datapath):\n self.logger.debug('send stats request: %016x', datapath.id)\n ofproto = datapath.ofproto\n parser = datapath.ofproto_parser\n\n req = parser.OFPPortDescStatsRequest(datapath, 0)\n datapath.send_msg(req)\n\n req = parser.OFPPortStatsRequest(datapath, 0, ofproto.OFPP_ANY)\n datapath.send_msg(req)\n\n req = parser.OFPFlowStatsRequest(datapath)\n datapath.send_msg(req)","def get_statistics(self):\n\t\treturn Job(SDK.PrlSrv_GetStatistics(self.handle)[0])","def handle_health(data: bytes) -> Tuple[bytes, str]:\n actor_id, hp = struct.unpack('Ih', data[:6])\n return data[6:], f'Actor {actor_id} has {hp} HP'","def GetHealthz(self, request, context):\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\n context.set_details('Method not implemented!')\n raise NotImplementedError('Method not implemented!')","def api_health(self):\n return messages.SUCCESS_JSON, 200","def test_health_stuff(request, historian, client_agent):\n global alert_publishes\n\n DEVICES_ALL_TOPIC = \"devices/Building/LAB/Device/all\"\n\n print(\"\\n** test_basic_function for {}**\".format(\n request.keywords.node.name))\n\n # Publish fake data. The format mimics the format used by VOLTTRON drivers.\n # Make some random readings. Randome readings are going to be\n # within the tolerance here.\n format_spec = \"{0:.13f}\"\n oat_reading = random.uniform(30, 100)\n mixed_reading = oat_reading + random.uniform(-5, 5)\n damper_reading = random.uniform(0, 100)\n\n float_meta = {'units': 'F', 'tz': 'UTC', 'type': 'float'}\n percent_meta = {'units': '%', 'tz': 'UTC', 'type': 'float'}\n\n # Create a message for all points.\n all_message = [{'OutsideAirTemperature': oat_reading,\n 'MixedAirTemperature': mixed_reading,\n 'DamperSignal': damper_reading},\n {'OutsideAirTemperature': float_meta,\n 'MixedAirTemperature': float_meta,\n 'DamperSignal': percent_meta\n }]\n\n # Create timestamp\n now = utils.format_timestamp( datetime.utcnow() )\n\n # now = '2015-12-02T00:00:00'\n headers = {\n headers_mod.DATE: now, headers_mod.TIMESTAMP: now\n }\n print(\"Published time in header: \" + now)\n\n for _ in range(10):\n client_agent.vip.pubsub.publish('pubsub',\n DEVICES_ALL_TOPIC,\n headers=headers,\n message=all_message).get(timeout=10)\n\n gevent.sleep(2.0)\n\n status = client_agent.vip.rpc.call(\"platform.historian\", \"health.get_status\").get(timeout=10)\n\n assert status[\"status\"] == STATUS_GOOD\n assert status[\"context\"][STATUS_KEY_PUBLISHING]\n assert not status[\"context\"][STATUS_KEY_BACKLOGGED]\n assert not status[\"context\"][STATUS_KEY_CACHE_FULL]\n assert not bool(status[\"context\"][STATUS_KEY_CACHE_COUNT])\n\n # Test publish failure\n client_agent.vip.pubsub.subscribe(\"pubsub\", \"alerts/BasicHistorian\", message_handler)\n\n historian.publish_fail = True\n\n for _ in range(10):\n client_agent.vip.pubsub.publish('pubsub',\n DEVICES_ALL_TOPIC,\n headers=headers,\n message=all_message).get(timeout=10)\n\n\n gevent.sleep(0.2)\n\n status = client_agent.vip.rpc.call(\"platform.historian\", \"health.get_status\").get(timeout=10)\n\n alert_publish = alert_publishes[0]\n\n alert_publishes = []\n\n assert status[\"status\"] == STATUS_BAD\n assert not status[\"context\"][STATUS_KEY_PUBLISHING]\n\n assert alert_publish.status == STATUS_BAD\n\n historian.publish_fail = False\n\n gevent.sleep(1.0)\n\n status = client_agent.vip.rpc.call(\"platform.historian\", \"health.get_status\").get(timeout=10)\n\n assert status[\"status\"] == STATUS_GOOD\n assert status[\"context\"][STATUS_KEY_PUBLISHING]\n assert not status[\"context\"][STATUS_KEY_BACKLOGGED]\n assert not status[\"context\"][STATUS_KEY_CACHE_FULL]\n assert not bool(status[\"context\"][STATUS_KEY_CACHE_COUNT])\n\n #Test publish slow or backlogged\n\n historian.publish_sleep = 0.75\n\n for _ in range(1000):\n client_agent.vip.pubsub.publish('pubsub',\n DEVICES_ALL_TOPIC,\n headers=headers,\n message=all_message).get(timeout=10)\n\n gevent.sleep(2.0)\n\n status = client_agent.vip.rpc.call(\"platform.historian\", \"health.get_status\").get(timeout=10)\n\n assert status[\"status\"] == STATUS_BAD\n assert status[\"context\"][STATUS_KEY_BACKLOGGED]\n assert status[\"context\"][STATUS_KEY_CACHE_COUNT] > 0\n alert_publish = alert_publishes[-1]\n assert alert_publish.status == STATUS_BAD\n context = alert_publish.context\n assert context[STATUS_KEY_CACHE_FULL]\n assert status[\"context\"][STATUS_KEY_CACHE_FULL]\n\n historian.publish_sleep = 0\n\n gevent.sleep(2.0)\n\n status = client_agent.vip.rpc.call(\"platform.historian\", \"health.get_status\").get(timeout=10)\n\n assert status[\"status\"] == STATUS_GOOD\n assert status[\"context\"][STATUS_KEY_PUBLISHING]\n assert not status[\"context\"][STATUS_KEY_BACKLOGGED]\n assert not status[\"context\"][STATUS_KEY_CACHE_FULL]\n assert not bool(status[\"context\"][STATUS_KEY_CACHE_COUNT])","def health(self, new_health: int) -> None:","def test_health(self) -> None:\n self._response = self._app.get('/health')\n\n self.assertEqual(self._response.status, '200 OK')","async def status(self, ctx):\n self.logger.info(misolog.format_log(ctx, f\"\"))\n up_time = time.time() - self.start_time\n m, s = divmod(up_time, 60)\n h, m = divmod(m, 60)\n d, h = divmod(h, 24)\n uptime_string = \"%d days %d hours %d minutes %d seconds\" % (d, h, m, s)\n\n stime = time.time() - psutil.boot_time()\n m, s = divmod(stime, 60)\n h, m = divmod(m, 60)\n d, h = divmod(h, 24)\n system_uptime_string = \"%d days %d hours %d minutes %d seconds\" % (d, h, m, s)\n\n mem = psutil.virtual_memory()\n\n pid = os.getpid()\n memory_use = psutil.Process(pid).memory_info()[0]\n\n content = discord.Embed(title=f\"Miso Bot | version {main.version}\")\n content.set_thumbnail(url=self.client.user.avatar_url)\n\n content.add_field(name=\"Bot process uptime\", value=uptime_string)\n content.add_field(name=\"System CPU Usage\", value=f\"{psutil.cpu_percent()}%\")\n content.add_field(name=\"System uptime\", value=system_uptime_string)\n\n content.add_field(name=\"System RAM Usage\", value=f\"{mem.percent}%\")\n content.add_field(name=\"Bot memory usage\", value=f\"{memory_use/math.pow(1024, 2):.2f}MB\")\n\n await ctx.send(embed=content)","def execute(self, stream):\n pass","def streamTest():\n timer = StoreTimer(store, duration=2.0)\n bottle.response.set_header('Content-Type', 'text/event-stream') #text\n bottle.response.set_header('Cache-Control', 'no-cache')\n # Set client-side auto-reconnect timeout, ms.\n yield 'retry: 1000\\n\\n'\n i = 0\n yield 'id: {0}\\n'.format(i)\n i += 1\n yield 'data: START\\n\\n'\n n = 1\n while not timer.expired:\n yield 'id: {0}\\n'.format(i)\n i += 1\n yield 'data: {0}\\n\\n'.format(n)\n n += 1\n yield \"data: END\\n\\n\"","def realtimestreaming(self, **kwargs):\n url_path = 'realtimestreaming'\n self.logger.debug(f\"Get Realtime Streaming report data\")\n body = self._make_body(kwargs)\n return self._common_post(request_path=url_path, body=body)","def test_health_get(self):\n pass","def on_get(self, req, resp):\n hc = HealthCheckCombined(state_manager=self.state_manager,\n orchestrator=self.orchestrator,\n extended=False)\n return hc.get(req, resp)","def health(self, health):\n\n self._health = health","def health(self, health):\n\n self._health = health","def health(self, health):\n\n self._health = health","def health(self, health):\n\n self._health = health","def on_get(self, req, resp):\n hc = HealthCheckCombined(state_manager=self.state_manager,\n orchestrator=self.orchestrator,\n extended=True)\n return hc.get(req, resp)","def get_health(self):\n return {\n 'api_name': 'BrightHive Master Client Index API',\n 'current_time': str(datetime.utcnow()),\n 'current_api_version': '1.0.0',\n 'api_status': 'OK'\n }, 200","def main():\n SOCKET = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\n SOCKET.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)\n SOCKET.bind(settings.STASH_ADDRESS)\n SOCKET.listen(1)\n\n while 1:\n connection, address = SOCKET.accept()\n command, key, value = pickle.loads(connection.recv(4096).decode())\n\n if command == 'STATS':\n response = handle_stats()\n elif command in ('GET', 'INCREMENT', 'DELETE'):\n response = COMMAND_HANDLERS[command](key)\n elif command in ('PUT', 'APPEND'):\n response = COMMAND_HANDLERS[command](key, value)\n else:\n response = (False, 'Unknown command type [{}]'.format(command))\n\n update_stats(command, response[0])\n connection.sendall(pickle.dumps(response))\n connection.close()\n\n SOCKET.shutdown(socket.SHUT_RDWR)\n SOCKET.close()","def stream_shm():\n return flask.render_template('stream.html')","def statistics():\n return render_template('statistics.html'), 200","def display_health(self) -> None:\n\n print(self.player.hp)","def handle_stat(module):\n system, host = get_sys_host(module)\n\n host_name = module.params['host']\n if not host:\n module.fail_json(msg='Host {0} not found'.format(host_name))\n\n field_dict = get_port_fields(module, system, host)\n result = dict(\n changed=False,\n msg='Host {0} ports found'.format(host_name),\n )\n result = merge_two_dicts(result, field_dict)\n module.exit_json(**result)","def test_get_healthz(self):\n response = self.client.open(\n '/v1/healthz',\n method='GET')\n self.assert200(response,\n 'Response body is : ' + response.data.decode('utf-8'))","def UpdateStream(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\n raise NotImplementedError()","def health_check(self, *, scope: Scope) -> HealthCheckStatus:","def _process_health_check_stats_response(self, buf, len):\n\t\t\n\t\tself.pcpResInfo.pcp_add_json_result('command_status', 'success')\n\t\tvalue, index = self._getNextString(buf, 0)\n\n\t\tif value and value == 'CommandComplete':\n\t\t\tindex += 1\n\t\t\t\n\t\t\tstats = POOL_HEALTH_CHECK_STATS()\n\n\t\t\tfor attrib in stats.attrib_list:\n\t\t\t\tvalue, index = self._getNextString(buf, index)\n\t\t\t\tif value:\n\t\t\t\t\tstats.add_stat(attrib, value)\n\t\t\t\tindex += 1\n\n\t\t\tself.pcpResInfo.pcp_add_json_result('health_check_stats', stats.get_json())\n\t\t\tself._setResultData(self.pcpResInfo, stats)\n\t\t\tself._setCommandSuccessful()\n\t\telse:\n\t\t\tself.pcp_internal_error(f'command failed with reason: \"{buf}\"')\n\t\t\tself.pcpResInfo.pcp_add_json_result('command_status', 'failed')\n\t\t\tself._setResultStatus(ResultStateType.BAD_RESPONSE)","def get_system_health(self):\n HealthTotal_mo = self.moDir.lookupByDn('topology/health')\n return HealthTotal_mo.cur","def run(self, stream):\n pass","def statistics(username, root_wf_id, wf_id):\n dashboard = Dashboard(g.master_db_url, root_wf_id, wf_id)\n summary_times = dashboard.workflow_summary_stats(wf_id)\n\n for key, value in summary_times.items():\n summary_times[key] = filters.time_to_str(value)\n\n workflow_stats = dashboard.workflow_stats()\n\n return render_template('workflow/statistics.html', root_wf_id=root_wf_id, wf_id=wf_id, summary_stats=summary_times, workflow_stats=workflow_stats)"],"string":"[\n \"def StreamHealth(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\\n raise NotImplementedError()\",\n \"def StreamHealth(self, request, context):\\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)\",\n \"async def health(self):\\n\\n request = telemetry_pb2.SubscribeHealthRequest()\\n health_stream = self._stub.SubscribeHealth(request)\\n\\n try:\\n async for response in health_stream:\\n \\n\\n \\n yield Health.translate_from_rpc(response.health)\\n finally:\\n health_stream.cancel()\",\n \"def poll_health():\\n global timesCalled\\n\\n # Poll /health\\n session = requests.Session()\\n retry = Retry(connect=3, backoff_factor=0.5)\\n adapter = HTTPAdapter(max_retries=retry)\\n session.mount('http://', adapter)\\n response = session.get(health_url)\\n\\n # Check HTTP status code\\n status_code = response.status_code\\n if status_code != status_ok:\\n exit(1)\\n\\n # Get metrics values\\n metrics = response.json()['metrics']\\n requestLatencyValues.append(metrics['requestLatency'])\\n dbLatencyValues.append(metrics['dbLatency'])\\n cacheLatencyValues.append(metrics['cacheLatency'])\\n\\n # If 60 seconds has passed, send data to STDOUT\\n timesCalled += 1\\n if timesCalled == 6:\\n output_data()\\n\\n timesCalled = 0\\n requestLatencyValues.clear()\\n dbLatencyValues.clear()\\n cacheLatencyValues.clear()\",\n \"def Stream():\\r\\n \\r\\n config = config_create()\\r\\n CONSUMER_KEY = config.get('Auth', 'CONSUMER_KEY') \\r\\n CONSUMER_SECRET = config.get('Auth', 'CONSUMER_SECRET')\\r\\n ACCESS_KEY = config.get('Auth', 'ACCESS_KEY')\\r\\n ACCESS_SECRET = config.get('Auth', 'ACCESS_SECRET')\\r\\n searchterm = config.get('Filter','search')\\r\\n name = multiprocessing.current_process().name\\r\\n \\\"\\\"\\\"Function that will manage doing the twitter stream\\\"\\\"\\\"\\r\\n stream = MyStreamer(CONSUMER_KEY, CONSUMER_SECRET, ACCESS_KEY, ACCESS_SECRET)\\r\\n stream.statuses.filter(track= searchterm)\",\n \"def waspstat():\\n\\n\\trespond = send_command('waspstat')\\n\\n\\treturn respond\",\n \"def get_health(self):\\n return self.bot_client.send_command(_Command.GetHealth)\",\n \"def _retrieve_health_data(self):\\n return self._client.request('_cluster/health', query={'level': 'shards'}).data\",\n \"def get_stream_stats(self, stream, isCollectionStream=False, local=False):\\n if isCollectionStream is False:\\n if local is True:\\n stream = \\\"c8locals.\\\" + stream\\n else:\\n stream = \\\"c8globals.\\\" + stream\\n if local is True:\\n endpoint = '{}/{}/stats?global=False'.format(ENDPOINT, stream)\\n elif local is False:\\n endpoint = '{}/{}/stats?global=True'.format(ENDPOINT, stream)\\n\\n request = Request(method='get', endpoint=endpoint)\\n\\n def response_handler(resp):\\n code = resp.status_code\\n if resp.is_success:\\n return json.loads(resp.body['result'])\\n elif code == 403:\\n raise ex.StreamPermissionError(resp, request)\\n raise ex.StreamConnectionError(resp, request)\\n\\n return self._execute(request, response_handler)\",\n \"async def health(self) -> Health:\\n response = await self._http_requests.get(build_url(Paths.HEALTH))\\n return Health(**response.json())\",\n \"def StreamExecute(self, request, context):\\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)\",\n \"def TemperatureStream(self, request, context):\\n logging.info(\\\"Temperature Stream Request\\\") # Log\\n length = request.length\\n metadata = [(b'device', b'Thermometer'), (b'version',\\n b'0.1'), (b'precision', b'1 decimal')]\\n context.send_initial_metadata(metadata)\\n context.add_callback(self.stream_callback)\\n try:\\n for i in range(0, length):\\n time.sleep(1)\\n datapoint = device_pb2.Datapoint()\\n val = 20 + random.normalvariate(0, 2) # Fake values\\n datapoint.value = val\\n datapoint.unit = 0\\n logging.info('Sending data')\\n yield datapoint\\n except Exception as e:\\n logging.exception(str(e))\",\n \"def health():\\n return jsonify(hostname=hostname, uptime=uptime(), \\\\\\n cpu_percent=int(cpu_percent(interval=None, percpu=False)))\",\n \"def getDeviceHealthReport(self, df: str = None, ts: str = None, cursor: str = None, pageSize: int = None):\\n params = {\\n 'df': df,\\n 'ts': ts,\\n 'cursor': cursor,\\n 'pageSize': pageSize\\n }\\n return self.api_get_request(f'{self.NINJA_API_QUERIES_DEVICE_HEALTH}', params=params)\",\n \"def GetHealthStatus(self, request, context):\\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\\n context.set_details('Method not implemented!')\\n raise NotImplementedError('Method not implemented!')\",\n \"def meter_stats():\\n current_time = time.time()\\n r = requests.get('http://localhost:8080/stats/flow/1')\\n r.raise_for_status()\\n data = r.json()\\n bytes_tx = 0\\n for stat in data['1']:\\n if stat['match'].get('dl_src') == '00:00:00:00:00:01':\\n bytes_tx += stat['byte_count']\\n global LAST_TIME\\n global LAST_BYTES_TX\\n time_diff = current_time - LAST_TIME\\n byte_diff = bytes_tx - LAST_BYTES_TX\\n LAST_TIME = current_time\\n LAST_BYTES_TX = bytes_tx\\n transfer_rate = byte_diff / time_diff / 1024\\n # We need to accomodate the dropping of our rule with the hard timeout\\n return jsonify({'transfer_rate': transfer_rate})\",\n \"def subscribe_to_host_statistics(self):\\n\\t\\treturn Job(SDK.PrlSrv_SubscribeToHostStatistics(self.handle)[0])\",\n \"async def health(request):\\n\\n r = dict(\\n health='green'\\n )\\n\\n return json(r)\",\n \"def stats(containerids, stream):\\n click.echo('*** MONITORING IS INITIATED')\\n if(stream):\\n while True:\\n for x in containerids:\\n index = slice(12)\\n monitoring(containerid=x[index])\\n else:\\n for x in containerids:\\n index = slice(12)\\n monitoring(containerid=x[index])\",\n \"async def health(request):\\n return web.Response(text=\\\"ok\\\")\",\n \"async def test_health():\\n response = health()\\n assert response\\n assert {'status': 'ok'} == response\",\n \"def get_realtime_stream(self):\\n ws = 0\\n url = WS_URL % (self.sense_monitor_id, self.sense_access_token)\\n try:\\n ws = create_connection(url, timeout=self.wss_timeout, sslopt={'ciphers': 'DEFAULT@SECLEVEL=1'})\\n while True: # hello, features, [updates,] data\\n result = json.loads(ws.recv())\\n if result.get('type') == 'realtime_update':\\n data = result['payload']\\n self.set_realtime(data)\\n yield data\\n except WebSocketTimeoutException:\\n raise SenseAPITimeoutException(\\\"API websocket timed out\\\")\\n finally:\\n if ws: ws.close()\",\n \"def StreamExecute(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\\n raise NotImplementedError()\",\n \"def squares_streaming_get():\\n \\n return 'do some magic!'\",\n \"def stream_status_event(self, event):\\r\\n pass\",\n \"def get(self):\\n log.debug('/x-tree/FSMonitor.html: invoked')\\n try:\\n log.info('application health check...')\\n host_name = socket.gethostname()\\n url = \\\"http://localhost:8086/query\\\"\\n querystring = {\\\"pretty\\\": \\\"true\\\", \\\"db\\\": \\\"IOT\\\",\\n \\\"q\\\": \\\"SELECT count(*) FROM \\\\\\\"ttd_devices\\\\\\\" \\\"}\\n response = requests.request(\\\"GET\\\", url, params=querystring)\\n D=json.loads(response.text)\\n total_recs=str(max(D['results'][0]['series'][0]['values'][0][1:]))\\n except:\\n result = {}\\n log.exception('Exception while doing HealthCheck')\\n return Response ('<html><body>THE SERVER IS DOWN</body></html>', mimetype=\\\"text/html\\\", status=500)\\n return Response('<html><body>INFLUX DB <p/> Count:' + total_recs + '</body></html>', mimetype=\\\"text/html\\\")\",\n \"def StreamExecute(self, request, context):\\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\\n context.set_details('Method not implemented!')\\n raise NotImplementedError('Method not implemented!')\",\n \"def StreamExecute(self, request, context):\\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\\n context.set_details('Method not implemented!')\\n raise NotImplementedError('Method not implemented!')\",\n \"def health():\\n global _is_healthy\\n template = render_template('health.html', healthy=_is_healthy)\\n return make_response(template, 200 if _is_healthy else 500)\",\n \"def get_health_info(handle, timeout):\\n health = dict()\\n\\n health['stat'] = ceph_mon_command(handle, 'health' , timeout)\\n # TODO command not known with ceph_mon_command\\n #health['detail'] = ceph_mon_command(handle, 'health detail', timeout)\\n health['detail'] = shell_command('ceph health detail') + b'\\\\n'\\n health['df'] = ceph_mon_command(handle, 'df' , timeout)\\n health['report'] = ceph_mon_command(handle, 'report' , timeout)\\n\\n return health\",\n \"def open_twitter_sample_stream():\\n twitter_sample_parameters = {'stall_warnings': 'true', }\\n\\n r = requests.post('https://stream.twitter.com/1.1/statuses/sample.json',\\n data=twitter_sample_parameters,\\n auth=oauth_credentials,\\n stream=True,\\n timeout=300)\\n\\n if r.status_code != 200:\\n received_error(r)\\n return None\\n\\n if r.encoding is None:\\n r.encoding = 'utf-8'\\n\\n return r\",\n \"def send_to_aws_time_stream(stats, config):\\n logging.info('Sending stats to Timestream (database=%s)', config['timestream_database'])\\n\\n region_config = Config(\\n region_name=config['timestream_aws_region']\\n )\\n\\n ts_client = boto3.client(\\n 'timestream-write',\\n aws_access_key_id=config['timestream_aws_access_key_id'],\\n aws_secret_access_key=config['timestream_aws_secret_access_key'],\\n config=region_config\\n )\\n\\n try:\\n # Attempt to validate connection to database and table\\n # Error out and return if not able to access / connection isn't valid\\n database = ts_client.describe_database(\\n DatabaseName=config['timestream_database']\\n )\\n logging.debug(\\\"Database details = %s\\\" % database)\\n\\n table = ts_client.describe_table(\\n DatabaseName=config['timestream_database'],\\n TableName=config['timestream_table']\\n )\\n logging.debug(\\\"Table details = %s\\\" % table)\\n except Exception as err:\\n logging.error(err)\\n return\\n\\n current_time = time.time_ns()\\n logging.debug(\\\"Converting to timestream - %s\\\" % stats)\\n\\n downstream_common_attributes = {\\n 'Dimensions': [{'Name': 'measurement', 'Value': 'downstream_statistics'}],\\n 'Time': str(current_time),\\n 'TimeUnit': 'NANOSECONDS'\\n }\\n downstream_records = []\\n for stats_down in stats['downstream']:\\n for key in stats_down:\\n if key == 'channel_id':\\n continue\\n\\n downstream_records.append({\\n 'Dimensions': [\\n {'Name': 'channel_id', 'Value': str(stats_down['channel_id'])},\\n {'Name': 'group', 'Value': 'downstream_statistics'}\\n ],\\n 'MeasureName': key,\\n 'MeasureValue': str(stats_down[key]),\\n 'MeasureValueType': 'DOUBLE' if isinstance(stats_down[key], float) else 'BIGINT'\\n })\\n\\n try:\\n logging.debug(\\\"Writing common attributes: %s\\\" % downstream_common_attributes)\\n logging.debug(\\\"Writing records: %s\\\" % downstream_records)\\n result = ts_client.write_records(DatabaseName=config['timestream_database'],\\n TableName=config['timestream_table'], Records=downstream_records,\\n CommonAttributes=downstream_common_attributes)\\n logging.info(\\\"Timestream response = %s\\\" % result)\\n logging.info(\\\"Wrote %s records to TimeStream\\\" % len(downstream_records))\\n except (ts_client.exceptions.RejectedRecordsException, Exception) as err:\\n logging.error(err)\\n\\n upstream_common_attributes = {\\n 'Dimensions': [{'Name': 'measurement', 'Value': 'upstream_statistics'}],\\n 'Time': str(current_time),\\n 'TimeUnit': 'NANOSECONDS'\\n }\\n upstream_records = []\\n for stats_up in stats['upstream']:\\n for key in stats_up:\\n if key == 'channel_id':\\n continue\\n\\n upstream_records.append({\\n 'Dimensions': [\\n {'Name': 'channel_id', 'Value': str(stats_up['channel_id'])},\\n {'Name': 'group', 'Value': 'upstream_statistics'}\\n ],\\n 'MeasureName': key,\\n 'MeasureValue': str(stats_up[key]),\\n 'MeasureValueType': 'DOUBLE' if isinstance(stats_up[key], float) else 'BIGINT'\\n })\\n\\n try:\\n logging.debug(\\\"Writing common attributes: %s\\\" % upstream_common_attributes)\\n logging.debug(\\\"Writing records: %s\\\" % upstream_records)\\n result = ts_client.write_records(DatabaseName=config['timestream_database'],\\n TableName=config['timestream_table'], Records=upstream_records,\\n CommonAttributes=upstream_common_attributes)\\n logging.info(\\\"Timestream response = %s\\\" % result)\\n logging.info(\\\"Wrote %s records to TimeStream\\\" % len(upstream_records))\\n except (ts_client.exceptions.RejectedRecordsException, Exception) as err:\\n logging.error(err)\\n return\\n\\n logging.info('Successfully wrote data to Timestream')\",\n \"def UpdateStream(self, request, context):\\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)\",\n \"def process_stream(self, sid, f):\\n http_response = wavehttp.get(\\\"/wave/wfe/channel?VER=6&RID=rpc&SID=\\\"+sid+\\n \\\"&CI=0&AID=0&TYPE=xmlhttp&zx=\\\"+self.zx()+\\\"&t=1\\\")\\n http_data = http_response.read(120)\\n print http_data\\n exit()\\n connection.close()\",\n \"def test_is_streaming(fprime_test_api):\\n results = fprime_test_api.assert_telemetry_count(5, timeout=10)\\n for result in results:\\n msg = \\\"received channel {} update: {}\\\".format(result.get_id(), result.get_str())\\n print(msg)\\n fprime_test_api.assert_telemetry(\\n \\\"sendBuffComp.SendState\\\", value=\\\"SEND_IDLE\\\", timeout=3\\n )\",\n \"def get_host_stats(self, refresh=False):\",\n \"def _send_health_txn(self,\\r\\n txn_type=None,\\r\\n txn_id=None,\\r\\n data=None,\\r\\n state=None,\\r\\n url=None,\\r\\n txn_date=None):\\r\\n #serialization is just a delimited utf-8 encoded strings\\r\\n if txn_type == 'commit':\\r\\n payload = \\\",\\\".join([txn_type, txn_id, data, state, url]).encode()\\r\\n elif txn_type == 'health':\\r\\n payload = \\\",\\\".join([txn_type, txn_id, data, state, str(txn_date)]).encode()\\r\\n\\r\\n pprint(\\\"payload: {}\\\".format(payload))######################################## pprint\\r\\n\\r\\n #construct the address\\r\\n address = self._get_address(txn_id)\\r\\n\\r\\n #construct header\\r\\n header = TransactionHeader(\\r\\n signer_public_key=self._signer.get_public_key().as_hex(),\\r\\n family_name=\\\"health\\\",\\r\\n family_version=\\\"0.1\\\",\\r\\n inputs=[address],\\r\\n outputs=[address],\\r\\n dependencies=[],\\r\\n payload_sha512=_sha512(payload),\\r\\n batcher_public_key=self._signer.get_public_key().as_hex(),\\r\\n nonce=hex(random.randint(0, 2**64))\\r\\n ).SerializeToString()\\r\\n\\r\\n signature = self._signer.sign(header)\\r\\n\\r\\n #create transaction\\r\\n transaction = Transaction(\\r\\n header=header,\\r\\n payload=payload,\\r\\n header_signature=signature\\r\\n )\\r\\n\\r\\n #create batch list, suserum policy: one transaction per batch\\r\\n batch_list = self._create_batch_list([transaction])\\r\\n\\r\\n return self._send_request(\\r\\n \\\"batches\\\",\\r\\n batch_list.SerializeToString(),\\r\\n 'application/octet-stream')\",\n \"def statistics(target):\\n worker=current_worker()\\n if (not is_worker_thread()) or (not worker) or (not worker.isopen) or (worker.index<0):\\n logging.warning(\\\"statistics can only be called from activated worker thread\\\")\\n return\\n with worker.statistics_lock:\\n return target(worker.statistics_data)\",\n \"def health(self) -> Union[int, float]:\\n return self.proto.health\",\n \"def health(self) -> Union[int, float]:\\n return self.proto.health\",\n \"def health_check():\\n app.logger.info(\\\"Health Check!\\\")\\n return Response(\\\"All Good!\\\", status=200)\",\n \"def hourly_sm_reading_histogram():\\r\\n cursor = connections[\\\"ldc\\\"].cursor()\\r\\n cursor.execute(\\\"select smr.Reading \\\" \\r\\n \\\"from essex_annotated.SmartMeterReadings smr \\\" \\r\\n \\\"inner join Meters m on m.MeterID = smr.MeterID \\\" \\r\\n \\\" and m.`Phase` = 1 \\\" \\r\\n \\\"left join meter_data_quality_flag mdqf \\\" \\r\\n \\\" on smr.MeterID = mdqf.MeterID \\\" \\r\\n \\\" and mdqf.applicability_start_date <= '2011-05-01' \\\" \\r\\n \\\" and mdqf.applicability_end_date >= '2012-10-31' \\\" \\r\\n \\\"where smr.MeterID >= 20000 and smr.MeterID < 20100 \\\" \\r\\n \\\"and mdqf.MeterID is null \\\" \\r\\n \\\"and smr.ReadDate >= '2011-05-01' \\\" \\r\\n \\\"and smr.ReadDate <= '2011-10-31'\\\")\\r\\n # Create a list of hourly reading values\\r\\n readings = [row[0] for row in cursor.fetchall()]\\r\\n \\r\\n # Create histogram\\r\\n sample_size = len(readings)\\r\\n trim_p = 0.0005\\r\\n p_title = \\\"Histogram of Hourly Readings \\\\n\\\" \\\\\\r\\n \\\"(Summer 2011, sample: \\\" + str(sample_size) + \\\" readings, \\\" \\\\\\r\\n \\\"right trim:\\\" + str(trim_p * 100.0) + \\\"%)\\\"\\r\\n p_xlabel = \\\"Hourly Reading (kW)\\\"\\r\\n p_ylabel = \\\"Occurrences\\\"\\r\\n create_histogram(readings, trim_p, 0.1, p_title, p_ylabel, p_xlabel, \\r\\n \\\"hourly_sm_reading_histogram_summer2011\\\", 1, \\\"right\\\")\",\n \"def stream_call(self):\\n pass\",\n \"def get_health(self):\\n return self.health\",\n \"def Gethealth(self):\\n return self.health\",\n \"def stats(short_url):\\n stats = get_stats(short_url)\\n click.echo(stats)\",\n \"async def async_realtime_stream(self, callback=None, single=False):\\n url = WS_URL % (self.sense_monitor_id, self.sense_access_token)\\n # hello, features, [updates,] data\\n async with websockets.connect(url, ssl=self.ssl_context) as ws:\\n while True:\\n try:\\n async with asyncio_timeout(self.wss_timeout):\\n message = await ws.recv()\\n except asyncio.TimeoutError as ex:\\n raise SenseAPITimeoutException(\\\"API websocket timed out\\\") from ex\\n\\n result = orjson.loads(message)\\n if result.get(\\\"type\\\") == \\\"realtime_update\\\":\\n data = result[\\\"payload\\\"]\\n self._set_realtime(data)\\n if callback:\\n callback(data)\\n if single:\\n return\\n elif result.get(\\\"type\\\") == \\\"error\\\":\\n data = result[\\\"payload\\\"]\\n if not data[\\\"authorized\\\"]:\\n raise SenseAuthenticationException(\\\"Web Socket Unauthorized\\\")\\n raise SenseWebsocketException(data[\\\"error_reason\\\"])\",\n \"def get_health(self):\\n return self.__health\",\n \"async def check_health():\\n return {\\\"healthy\\\": True}\",\n \"def get_health(self):\\n return {'status': 'ok'}\",\n \"def handle_health():\\n return flask.jsonify(status=\\\"up\\\")\",\n \"async def twitter_status(self, ctx):\\n server_channels = set(c.id for c in ctx.message.server.channels)\\n\\n followed_count = 0\\n displayed_count = 0\\n for chan_conf in self.conf.follows:\\n # Check if this channel is displayed in the server\\n if set(c.id for c in chan_conf.discord_channels) & server_channels:\\n followed_count += 1\\n displayed_count += sum(c.received_count for c in chan_conf.discord_channels if c.id in server_channels)\\n\\n # Calculate the average tweets processed per minute\\n minutes = (time.time() - self.bot.start_time) / 60\\n processed_average = self.processed_tweets / minutes\\n processed_average = '< 1' if processed_average < 1 else round(processed_average)\\n tweets_processed = '{} (avg {} / min)'.format(self.processed_tweets, processed_average)\\n\\n # Display the info\\n if self.stream.running:\\n embed = discord.Embed(title='Stream status', description='Online', colour=0x00ff00)\\n else:\\n embed = discord.Embed(title='Stream status', description='Offline', colour=0xff0000)\\n embed.add_field(name='Tweets processed since startup', value=tweets_processed, inline=False)\\n embed.add_field(name='Channels followed', value=followed_count)\\n embed.add_field(name='Tweets displayed', value=displayed_count)\\n\\n await self.bot.say(embed=embed)\",\n \"def stream():\\n return flask.Response(event_stream(flask.request.access_route[0]),\\n mimetype='text/event-stream')\",\n \"async def stream(self, ctx, streamer=None, *, stream_title=None):\\n # [p]set stream <streamer> <stream_title>\\n\\n server = ctx.message.server\\n\\n current_status = server.me.status if server is not None else None\\n\\n if stream_title:\\n stream_title = stream_title.strip()\\n if \\\"twitch.tv/\\\" not in streamer:\\n streamer = \\\"https://www.twitch.tv/\\\" + streamer\\n game = discord.Game(type=1, url=streamer, name=stream_title)\\n await self.bot.change_presence(game=game, status=current_status)\\n log.debug('Owner has set streaming status and url to \\\"{}\\\" and {}'.format(stream_title, streamer))\\n elif streamer is not None:\\n await send_command_help(ctx)\\n return\\n else:\\n await self.bot.change_presence(game=None, status=current_status)\\n log.debug('stream cleared by owner')\\n await self.bot.say(\\\"Done.\\\")\",\n \"def healthcheck():\\n return make_response(jsonify(status=200, message='Healthy'), status.HTTP_200_OK)\",\n \"def update(self):\\n try:\\n response = self.client.describe_stream(StreamName=self.stream)\\n except Exception as exc:\\n logger.exception(f'Failure trying to get stream: \\\"{self.stream}\\\".', exc)\\n else:\\n if response['ResponseMetadata']['HTTPStatusCode'] != 200:\\n logger.error(f'Failure to describe stream \\\"{self.stream}\\\": {response}')\\n else:\\n self.description = response['StreamDescription']\",\n \"def health(self):\\n return self._health\",\n \"def health(self):\\n return self._health\",\n \"def get_health_check(self):\\n return util.create_response(output=\\\"OK\\\")\",\n \"def stats(self, **kwargs):\\n return stats.stats(self._host, self._session, **kwargs)\",\n \"def query_stats(self, **kwargs):\\n return stats.query(self._host, self._session, **kwargs)\",\n \"async def handle_ping(request):\\n return web.Response(text=f\\\"OK {datetime.now().isoformat()}\\\\n\\\", headers={'Content-Type': 'text/event-stream'})\",\n \"def test_simple_health_check(self):\\n response = self.client.open(\\n '/awadallah/VaultsManager/1.0.0/health',\\n method='GET')\\n self.assert200(response,\\n 'Response body is : ' + response.data.decode('utf-8'))\",\n \"def __process_health(self) -> None:\\n status = self.metrics.get(\\\"Status\\\", None)\\n if status:\\n health = status.get(\\\"Health\\\", None)\\n measurement = \\\"Health\\\"\\n if health == \\\"Warning\\\":\\n value = 1\\n datapoint = self.__gen_datapoint(measurement, self.label, value)\\n self.datapoints.append(datapoint)\\n elif health == \\\"Critical\\\":\\n value = 2\\n datapoint = self.__gen_datapoint(measurement, self.label, value)\\n self.datapoints.append(datapoint)\\n return\",\n \"def get_humidity(intent, session):\\n\\n session_attributes = {}\\n reprompt_text = None\\n\\n humidity = get_thing_state(\\\"MegaIf1\\\", \\\"Humidity%\\\")\\n speech_output = \\\"The humidity is \\\" + humidity + \\\" percent. \\\" \\\\\\n \\\". Goodbye.\\\"\\n should_end_session = True\\n \\n return build_response(session_attributes, build_speechlet_response(\\n intent['name'], speech_output, reprompt_text, should_end_session))\",\n \"def stream_tweets(bearer_token):\\n print(\\\"Streaming tweets...\\\")\\n\\n oauth2 = osometweet.OAuth2(\\n bearer_token=bearer_token,\\n manage_rate_limits=False\\n )\\n ot = osometweet.OsomeTweet(oauth2)\\n\\n # Add all tweet fields\\n all_tweet_fields = osometweet.TweetFields(everything=True)\\n\\n # Add streaming rules\\n rules = [{\\\"value\\\": \\\"coronavirus\\\", \\\"tag\\\": \\\"all coronavirus tweets\\\"},\\n {\\\"value\\\": \\\"indiana\\\", \\\"tag\\\": \\\"all indiana tweets\\\"}]\\n add_rules = {\\\"add\\\": rules}\\n response = ot.set_filtered_stream_rule(rules=add_rules)\\n print(f\\\"API response from adding two rules:\\\\n{response}\\\\n\\\")\\n\\n # Retrieve active streaming rules\\n current_rules = ot.get_filtered_stream_rule()\\n print(f'The current filtered stream rules are:\\\\n{current_rules}\\\\n')\\n\\n # Remove a streaming rule by using it's tag\\n indiana_rule = [\\n rule[\\\"id\\\"] for rule in current_rules[\\\"data\\\"]\\n if 'all indiana tweets' in rule[\\\"tag\\\"]\\n ]\\n delete_rule = {'delete': {'ids': indiana_rule}}\\n response = ot.set_filtered_stream_rule(rules=delete_rule)\\n print(f\\\"API response from deleting one rule:\\\\n{response}\\\\n\\\")\\n\\n # Get today's date\\n today = dt.strftime(dt.today(), \\\"%Y-%m-%d_%H-%M\\\")\\n\\n # Open two files. One for good data, the other for tweet errors.\\n with open(f\\\"tweet_stream--{today}.json\\\", \\\"a\\\") as data_file:\\n # stream is a Generator\\n stream = ot.filtered_stream(fields=all_tweet_fields)\\n # We have to iterate over the stream to fetch streamed tweets\\n for tweet in stream.iter_lines():\\n # Get data and errors\\n try:\\n data = json.loads(tweet).get(\\\"data\\\")\\n\\n # When data is found, we write it to the open file\\n if data:\\n json.dump(data, data_file)\\n data_file.write(\\\"\\\\n\\\")\\n except json.JSONDecodeError:\\n pass\",\n \"def GetStats(self):\\r\\n\\t\\tArg1 = self.href\\r\\n\\t\\treturn self._execute('GetStats', payload=locals(), response_object=None)\",\n \"def _request_stats(self, datapath):\\n self.logger.debug('send stats request: %016x', datapath.id)\\n ofproto = datapath.ofproto\\n parser = datapath.ofproto_parser\\n\\n req = parser.OFPPortDescStatsRequest(datapath, 0)\\n datapath.send_msg(req)\\n\\n req = parser.OFPPortStatsRequest(datapath, 0, ofproto.OFPP_ANY)\\n datapath.send_msg(req)\\n\\n req = parser.OFPFlowStatsRequest(datapath)\\n datapath.send_msg(req)\",\n \"def get_statistics(self):\\n\\t\\treturn Job(SDK.PrlSrv_GetStatistics(self.handle)[0])\",\n \"def handle_health(data: bytes) -> Tuple[bytes, str]:\\n actor_id, hp = struct.unpack('Ih', data[:6])\\n return data[6:], f'Actor {actor_id} has {hp} HP'\",\n \"def GetHealthz(self, request, context):\\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\\n context.set_details('Method not implemented!')\\n raise NotImplementedError('Method not implemented!')\",\n \"def api_health(self):\\n return messages.SUCCESS_JSON, 200\",\n \"def test_health_stuff(request, historian, client_agent):\\n global alert_publishes\\n\\n DEVICES_ALL_TOPIC = \\\"devices/Building/LAB/Device/all\\\"\\n\\n print(\\\"\\\\n** test_basic_function for {}**\\\".format(\\n request.keywords.node.name))\\n\\n # Publish fake data. The format mimics the format used by VOLTTRON drivers.\\n # Make some random readings. Randome readings are going to be\\n # within the tolerance here.\\n format_spec = \\\"{0:.13f}\\\"\\n oat_reading = random.uniform(30, 100)\\n mixed_reading = oat_reading + random.uniform(-5, 5)\\n damper_reading = random.uniform(0, 100)\\n\\n float_meta = {'units': 'F', 'tz': 'UTC', 'type': 'float'}\\n percent_meta = {'units': '%', 'tz': 'UTC', 'type': 'float'}\\n\\n # Create a message for all points.\\n all_message = [{'OutsideAirTemperature': oat_reading,\\n 'MixedAirTemperature': mixed_reading,\\n 'DamperSignal': damper_reading},\\n {'OutsideAirTemperature': float_meta,\\n 'MixedAirTemperature': float_meta,\\n 'DamperSignal': percent_meta\\n }]\\n\\n # Create timestamp\\n now = utils.format_timestamp( datetime.utcnow() )\\n\\n # now = '2015-12-02T00:00:00'\\n headers = {\\n headers_mod.DATE: now, headers_mod.TIMESTAMP: now\\n }\\n print(\\\"Published time in header: \\\" + now)\\n\\n for _ in range(10):\\n client_agent.vip.pubsub.publish('pubsub',\\n DEVICES_ALL_TOPIC,\\n headers=headers,\\n message=all_message).get(timeout=10)\\n\\n gevent.sleep(2.0)\\n\\n status = client_agent.vip.rpc.call(\\\"platform.historian\\\", \\\"health.get_status\\\").get(timeout=10)\\n\\n assert status[\\\"status\\\"] == STATUS_GOOD\\n assert status[\\\"context\\\"][STATUS_KEY_PUBLISHING]\\n assert not status[\\\"context\\\"][STATUS_KEY_BACKLOGGED]\\n assert not status[\\\"context\\\"][STATUS_KEY_CACHE_FULL]\\n assert not bool(status[\\\"context\\\"][STATUS_KEY_CACHE_COUNT])\\n\\n # Test publish failure\\n client_agent.vip.pubsub.subscribe(\\\"pubsub\\\", \\\"alerts/BasicHistorian\\\", message_handler)\\n\\n historian.publish_fail = True\\n\\n for _ in range(10):\\n client_agent.vip.pubsub.publish('pubsub',\\n DEVICES_ALL_TOPIC,\\n headers=headers,\\n message=all_message).get(timeout=10)\\n\\n\\n gevent.sleep(0.2)\\n\\n status = client_agent.vip.rpc.call(\\\"platform.historian\\\", \\\"health.get_status\\\").get(timeout=10)\\n\\n alert_publish = alert_publishes[0]\\n\\n alert_publishes = []\\n\\n assert status[\\\"status\\\"] == STATUS_BAD\\n assert not status[\\\"context\\\"][STATUS_KEY_PUBLISHING]\\n\\n assert alert_publish.status == STATUS_BAD\\n\\n historian.publish_fail = False\\n\\n gevent.sleep(1.0)\\n\\n status = client_agent.vip.rpc.call(\\\"platform.historian\\\", \\\"health.get_status\\\").get(timeout=10)\\n\\n assert status[\\\"status\\\"] == STATUS_GOOD\\n assert status[\\\"context\\\"][STATUS_KEY_PUBLISHING]\\n assert not status[\\\"context\\\"][STATUS_KEY_BACKLOGGED]\\n assert not status[\\\"context\\\"][STATUS_KEY_CACHE_FULL]\\n assert not bool(status[\\\"context\\\"][STATUS_KEY_CACHE_COUNT])\\n\\n #Test publish slow or backlogged\\n\\n historian.publish_sleep = 0.75\\n\\n for _ in range(1000):\\n client_agent.vip.pubsub.publish('pubsub',\\n DEVICES_ALL_TOPIC,\\n headers=headers,\\n message=all_message).get(timeout=10)\\n\\n gevent.sleep(2.0)\\n\\n status = client_agent.vip.rpc.call(\\\"platform.historian\\\", \\\"health.get_status\\\").get(timeout=10)\\n\\n assert status[\\\"status\\\"] == STATUS_BAD\\n assert status[\\\"context\\\"][STATUS_KEY_BACKLOGGED]\\n assert status[\\\"context\\\"][STATUS_KEY_CACHE_COUNT] > 0\\n alert_publish = alert_publishes[-1]\\n assert alert_publish.status == STATUS_BAD\\n context = alert_publish.context\\n assert context[STATUS_KEY_CACHE_FULL]\\n assert status[\\\"context\\\"][STATUS_KEY_CACHE_FULL]\\n\\n historian.publish_sleep = 0\\n\\n gevent.sleep(2.0)\\n\\n status = client_agent.vip.rpc.call(\\\"platform.historian\\\", \\\"health.get_status\\\").get(timeout=10)\\n\\n assert status[\\\"status\\\"] == STATUS_GOOD\\n assert status[\\\"context\\\"][STATUS_KEY_PUBLISHING]\\n assert not status[\\\"context\\\"][STATUS_KEY_BACKLOGGED]\\n assert not status[\\\"context\\\"][STATUS_KEY_CACHE_FULL]\\n assert not bool(status[\\\"context\\\"][STATUS_KEY_CACHE_COUNT])\",\n \"def health(self, new_health: int) -> None:\",\n \"def test_health(self) -> None:\\n self._response = self._app.get('/health')\\n\\n self.assertEqual(self._response.status, '200 OK')\",\n \"async def status(self, ctx):\\n self.logger.info(misolog.format_log(ctx, f\\\"\\\"))\\n up_time = time.time() - self.start_time\\n m, s = divmod(up_time, 60)\\n h, m = divmod(m, 60)\\n d, h = divmod(h, 24)\\n uptime_string = \\\"%d days %d hours %d minutes %d seconds\\\" % (d, h, m, s)\\n\\n stime = time.time() - psutil.boot_time()\\n m, s = divmod(stime, 60)\\n h, m = divmod(m, 60)\\n d, h = divmod(h, 24)\\n system_uptime_string = \\\"%d days %d hours %d minutes %d seconds\\\" % (d, h, m, s)\\n\\n mem = psutil.virtual_memory()\\n\\n pid = os.getpid()\\n memory_use = psutil.Process(pid).memory_info()[0]\\n\\n content = discord.Embed(title=f\\\"Miso Bot | version {main.version}\\\")\\n content.set_thumbnail(url=self.client.user.avatar_url)\\n\\n content.add_field(name=\\\"Bot process uptime\\\", value=uptime_string)\\n content.add_field(name=\\\"System CPU Usage\\\", value=f\\\"{psutil.cpu_percent()}%\\\")\\n content.add_field(name=\\\"System uptime\\\", value=system_uptime_string)\\n\\n content.add_field(name=\\\"System RAM Usage\\\", value=f\\\"{mem.percent}%\\\")\\n content.add_field(name=\\\"Bot memory usage\\\", value=f\\\"{memory_use/math.pow(1024, 2):.2f}MB\\\")\\n\\n await ctx.send(embed=content)\",\n \"def execute(self, stream):\\n pass\",\n \"def streamTest():\\n timer = StoreTimer(store, duration=2.0)\\n bottle.response.set_header('Content-Type', 'text/event-stream') #text\\n bottle.response.set_header('Cache-Control', 'no-cache')\\n # Set client-side auto-reconnect timeout, ms.\\n yield 'retry: 1000\\\\n\\\\n'\\n i = 0\\n yield 'id: {0}\\\\n'.format(i)\\n i += 1\\n yield 'data: START\\\\n\\\\n'\\n n = 1\\n while not timer.expired:\\n yield 'id: {0}\\\\n'.format(i)\\n i += 1\\n yield 'data: {0}\\\\n\\\\n'.format(n)\\n n += 1\\n yield \\\"data: END\\\\n\\\\n\\\"\",\n \"def realtimestreaming(self, **kwargs):\\n url_path = 'realtimestreaming'\\n self.logger.debug(f\\\"Get Realtime Streaming report data\\\")\\n body = self._make_body(kwargs)\\n return self._common_post(request_path=url_path, body=body)\",\n \"def test_health_get(self):\\n pass\",\n \"def on_get(self, req, resp):\\n hc = HealthCheckCombined(state_manager=self.state_manager,\\n orchestrator=self.orchestrator,\\n extended=False)\\n return hc.get(req, resp)\",\n \"def health(self, health):\\n\\n self._health = health\",\n \"def health(self, health):\\n\\n self._health = health\",\n \"def health(self, health):\\n\\n self._health = health\",\n \"def health(self, health):\\n\\n self._health = health\",\n \"def on_get(self, req, resp):\\n hc = HealthCheckCombined(state_manager=self.state_manager,\\n orchestrator=self.orchestrator,\\n extended=True)\\n return hc.get(req, resp)\",\n \"def get_health(self):\\n return {\\n 'api_name': 'BrightHive Master Client Index API',\\n 'current_time': str(datetime.utcnow()),\\n 'current_api_version': '1.0.0',\\n 'api_status': 'OK'\\n }, 200\",\n \"def main():\\n SOCKET = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\\n SOCKET.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)\\n SOCKET.bind(settings.STASH_ADDRESS)\\n SOCKET.listen(1)\\n\\n while 1:\\n connection, address = SOCKET.accept()\\n command, key, value = pickle.loads(connection.recv(4096).decode())\\n\\n if command == 'STATS':\\n response = handle_stats()\\n elif command in ('GET', 'INCREMENT', 'DELETE'):\\n response = COMMAND_HANDLERS[command](key)\\n elif command in ('PUT', 'APPEND'):\\n response = COMMAND_HANDLERS[command](key, value)\\n else:\\n response = (False, 'Unknown command type [{}]'.format(command))\\n\\n update_stats(command, response[0])\\n connection.sendall(pickle.dumps(response))\\n connection.close()\\n\\n SOCKET.shutdown(socket.SHUT_RDWR)\\n SOCKET.close()\",\n \"def stream_shm():\\n return flask.render_template('stream.html')\",\n \"def statistics():\\n return render_template('statistics.html'), 200\",\n \"def display_health(self) -> None:\\n\\n print(self.player.hp)\",\n \"def handle_stat(module):\\n system, host = get_sys_host(module)\\n\\n host_name = module.params['host']\\n if not host:\\n module.fail_json(msg='Host {0} not found'.format(host_name))\\n\\n field_dict = get_port_fields(module, system, host)\\n result = dict(\\n changed=False,\\n msg='Host {0} ports found'.format(host_name),\\n )\\n result = merge_two_dicts(result, field_dict)\\n module.exit_json(**result)\",\n \"def test_get_healthz(self):\\n response = self.client.open(\\n '/v1/healthz',\\n method='GET')\\n self.assert200(response,\\n 'Response body is : ' + response.data.decode('utf-8'))\",\n \"def UpdateStream(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\\n raise NotImplementedError()\",\n \"def health_check(self, *, scope: Scope) -> HealthCheckStatus:\",\n \"def _process_health_check_stats_response(self, buf, len):\\n\\t\\t\\n\\t\\tself.pcpResInfo.pcp_add_json_result('command_status', 'success')\\n\\t\\tvalue, index = self._getNextString(buf, 0)\\n\\n\\t\\tif value and value == 'CommandComplete':\\n\\t\\t\\tindex += 1\\n\\t\\t\\t\\n\\t\\t\\tstats = POOL_HEALTH_CHECK_STATS()\\n\\n\\t\\t\\tfor attrib in stats.attrib_list:\\n\\t\\t\\t\\tvalue, index = self._getNextString(buf, index)\\n\\t\\t\\t\\tif value:\\n\\t\\t\\t\\t\\tstats.add_stat(attrib, value)\\n\\t\\t\\t\\tindex += 1\\n\\n\\t\\t\\tself.pcpResInfo.pcp_add_json_result('health_check_stats', stats.get_json())\\n\\t\\t\\tself._setResultData(self.pcpResInfo, stats)\\n\\t\\t\\tself._setCommandSuccessful()\\n\\t\\telse:\\n\\t\\t\\tself.pcp_internal_error(f'command failed with reason: \\\"{buf}\\\"')\\n\\t\\t\\tself.pcpResInfo.pcp_add_json_result('command_status', 'failed')\\n\\t\\t\\tself._setResultStatus(ResultStateType.BAD_RESPONSE)\",\n \"def get_system_health(self):\\n HealthTotal_mo = self.moDir.lookupByDn('topology/health')\\n return HealthTotal_mo.cur\",\n \"def run(self, stream):\\n pass\",\n \"def statistics(username, root_wf_id, wf_id):\\n dashboard = Dashboard(g.master_db_url, root_wf_id, wf_id)\\n summary_times = dashboard.workflow_summary_stats(wf_id)\\n\\n for key, value in summary_times.items():\\n summary_times[key] = filters.time_to_str(value)\\n\\n workflow_stats = dashboard.workflow_stats()\\n\\n return render_template('workflow/statistics.html', root_wf_id=root_wf_id, wf_id=wf_id, summary_stats=summary_times, workflow_stats=workflow_stats)\"\n]","isConversational":false},"negative_scores":{"kind":"list like","value":["0.7608533","0.7594466","0.65876895","0.596237","0.5666134","0.5444123","0.5427727","0.54094017","0.5407425","0.53967756","0.53581214","0.53127843","0.52864975","0.5257775","0.5237875","0.523024","0.5206512","0.5199296","0.5146353","0.51393175","0.51260155","0.51084095","0.5093145","0.50748277","0.5058684","0.5035958","0.5035283","0.5035283","0.50272554","0.50203294","0.50148714","0.5004935","0.4999425","0.4997245","0.4980358","0.49604464","0.49564245","0.49525228","0.49443358","0.49443358","0.49412543","0.492928","0.49280277","0.49249828","0.49210256","0.49134105","0.49133423","0.48954225","0.48940903","0.48820007","0.48781243","0.4864381","0.48564833","0.48460594","0.4840769","0.48351017","0.4831621","0.4831621","0.4824616","0.4821233","0.48075807","0.4806709","0.47994104","0.47803617","0.47799477","0.47666404","0.47599384","0.4757573","0.475397","0.47523642","0.47522795","0.47485816","0.47392324","0.4733473","0.47308978","0.47250688","0.4719174","0.47129318","0.47127855","0.47055718","0.47027975","0.46992978","0.46992978","0.46992978","0.46992978","0.4695004","0.4693808","0.4689164","0.46814933","0.46793845","0.46792215","0.46749878","0.46711102","0.46711007","0.46700776","0.4665877","0.46616724","0.46568325","0.46560678"],"string":"[\n \"0.7608533\",\n \"0.7594466\",\n \"0.65876895\",\n \"0.596237\",\n \"0.5666134\",\n \"0.5444123\",\n \"0.5427727\",\n \"0.54094017\",\n \"0.5407425\",\n \"0.53967756\",\n \"0.53581214\",\n \"0.53127843\",\n \"0.52864975\",\n \"0.5257775\",\n \"0.5237875\",\n \"0.523024\",\n \"0.5206512\",\n \"0.5199296\",\n \"0.5146353\",\n \"0.51393175\",\n \"0.51260155\",\n \"0.51084095\",\n \"0.5093145\",\n \"0.50748277\",\n \"0.5058684\",\n \"0.5035958\",\n \"0.5035283\",\n \"0.5035283\",\n \"0.50272554\",\n \"0.50203294\",\n \"0.50148714\",\n \"0.5004935\",\n \"0.4999425\",\n \"0.4997245\",\n \"0.4980358\",\n \"0.49604464\",\n \"0.49564245\",\n \"0.49525228\",\n \"0.49443358\",\n \"0.49443358\",\n \"0.49412543\",\n \"0.492928\",\n \"0.49280277\",\n \"0.49249828\",\n \"0.49210256\",\n \"0.49134105\",\n \"0.49133423\",\n \"0.48954225\",\n \"0.48940903\",\n \"0.48820007\",\n \"0.48781243\",\n \"0.4864381\",\n \"0.48564833\",\n \"0.48460594\",\n \"0.4840769\",\n \"0.48351017\",\n \"0.4831621\",\n \"0.4831621\",\n \"0.4824616\",\n \"0.4821233\",\n \"0.48075807\",\n \"0.4806709\",\n \"0.47994104\",\n \"0.47803617\",\n \"0.47799477\",\n \"0.47666404\",\n \"0.47599384\",\n \"0.4757573\",\n \"0.475397\",\n \"0.47523642\",\n \"0.47522795\",\n \"0.47485816\",\n \"0.47392324\",\n \"0.4733473\",\n \"0.47308978\",\n \"0.47250688\",\n \"0.4719174\",\n \"0.47129318\",\n \"0.47127855\",\n \"0.47055718\",\n \"0.47027975\",\n \"0.46992978\",\n \"0.46992978\",\n \"0.46992978\",\n \"0.46992978\",\n \"0.4695004\",\n \"0.4693808\",\n \"0.4689164\",\n \"0.46814933\",\n \"0.46793845\",\n \"0.46792215\",\n \"0.46749878\",\n \"0.46711102\",\n \"0.46711007\",\n \"0.46700776\",\n \"0.4665877\",\n \"0.46616724\",\n \"0.46568325\",\n \"0.46560678\"\n]","isConversational":false},"document_score":{"kind":"string","value":"0.7317585"},"document_rank":{"kind":"string","value":"3"}}}],"truncated":false,"partial":true},"paginationData":{"pageIndex":155,"numItemsPerPage":100,"numTotalItems":95772,"offset":15500,"length":100}},"jwt":"eyJhbGciOiJFZERTQSIsImtpZCI6IjVHZDBvd0g5MTM2eDZjc1FvbE1zcktNWUZoRVFoUm5PVVVybEpjOUhaUEEifQ.eyJyZWFkIjp0cnVlLCJwZXJtaXNzaW9ucyI6eyJyZXBvLmNvbnRlbnQucmVhZCI6dHJ1ZX0sImlhdCI6MTc4NjExMzY3OSwianRpIjoiYzEzNmJiMmUtMzY4ZS00ZDhmLWFjNzgtOGI1MTk4Y2VhNmMwIiwic3ViIjoiL2RhdGFzZXRzL25vbWljLWFpL2Nvcm5zdGFjay1weXRob24tdjEiLCJleHAiOjE3ODYxMTcyNzksImlzcyI6Imh0dHBzOi8vaHVnZ2luZ2ZhY2UuY28ifQ.-CZCPlbGXeC9lCi9x4A1l_mlHnAIIcuf9Kj-Aq-yEdUEuE1Pf1q0ivCv6ZfLt6bBV3sfVJUqpGsaoE9PnwU0BA","displayUrls":true,"splitSizeSummaries":[{"config":"default","split":"train","numRows":95772,"numBytesParquet":1928375891}]},"discussionsStats":{"closed":1,"open":1,"total":2},"fullWidth":true,"hasGatedAccess":true,"hasFullAccess":true,"isEmbedded":false,"savedQueries":{"community":[],"user":[]}}">
query stringlengths 9 3.4k | document stringlengths 9 87.4k | metadata dict | negatives listlengths 4 101 | negative_scores listlengths 4 101 | document_score stringlengths 3 10 | document_rank stringclasses 102
values |
|---|---|---|---|---|---|---|
Creates a convex line segment between two points. In the context of polygon creation, desc_y is set to True if we are building the top left or top right corner. Desc_X is set to True if we are building the top right or bottom right corner. This impacts the order we accept points and how we interpret the direction of po... | def convex_line_segment(point_list:list, desc_y:bool=False, desc_x:bool=False)->list:
if len(point_list) < 3:
return point_list
line = []
x_extrema = None
# Since the list is sorted by x second, the last point is actually the
# first point of the last block of y values in the list (if more t... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def addRevLineSeg(self, x1, y1, x2, y2):\n # tip triangles\n if np.allclose(x1, 0.0):\n a = [x1, y1, 0.0]\n for (sa1, ca1), (sa2, ca2) in self._mesh.sincos:\n r = x2\n b = [r * sa2, y2, r * ca2]\n c = [r * sa1, y2, r * ca1]\n ... | [
"0.61220574",
"0.5985634",
"0.58928055",
"0.586802",
"0.5844202",
"0.5812266",
"0.5790249",
"0.57509595",
"0.5726299",
"0.5695145",
"0.5691318",
"0.56896853",
"0.5685234",
"0.5680852",
"0.56595385",
"0.563459",
"0.5601871",
"0.5600169",
"0.5596646",
"0.55840945",
"0.5568787",... | 0.74640554 | 0 |
Determines if a line segment described by d_y, d_x, and b is right of a point. | def intersects_right(point:tuple, line:tuple, d_y:float, d_x:float, b:float, include_top:bool=False, inclusive:bool=False)->bool:
min_y, max_y = line[0][1], line[1][1]
if min_y > max_y:
min_y, max_y = max_y, min_y
if not between(point[1], min_y, max_y):
# The point is above or below the line... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def point_on_line(point:tuple, line:tuple, d_y:float, d_x:float, b:float)->bool:\n if not near_segment(point, line):\n # Fast fail to handle cases where the point isn't in the bounding rectangle of the line segment.\n return False\n if b == None and point[0] == line[0][0]:\n return True\... | [
"0.779486",
"0.6765233",
"0.6753991",
"0.6690972",
"0.66500854",
"0.65380234",
"0.65158004",
"0.64917606",
"0.6466559",
"0.64534605",
"0.63823503",
"0.63814336",
"0.6377494",
"0.6278903",
"0.62738436",
"0.6271943",
"0.62362576",
"0.6226385",
"0.6216552",
"0.62099683",
"0.6205... | 0.7685959 | 1 |
Determines if a point is on the segment. | def point_on_line(point:tuple, line:tuple, d_y:float, d_x:float, b:float)->bool:
if not near_segment(point, line):
# Fast fail to handle cases where the point isn't in the bounding rectangle of the line segment.
return False
if b == None and point[0] == line[0][0]:
return True
return... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def pointInSegment(point, segmentPoint1, segmentPoint2):\n\t\tx = point[0]\n\t\ty = point[1]\n\n\t\tif x < segmentPoint1[0] and x < segmentPoint2[0]:\n\t\t\treturn False\n\t\t\n\t\tif x > segmentPoint1[0] and x > segmentPoint2[0]:\n\t\t\treturn False\n\t\t\n\t\tif y < segmentPoint1[1] and y < segmentPoint2[1]:\n\t... | [
"0.7799579",
"0.76022875",
"0.76022875",
"0.7578741",
"0.755237",
"0.750448",
"0.7461112",
"0.74219817",
"0.7264109",
"0.7250185",
"0.7214966",
"0.7196955",
"0.7158082",
"0.71503884",
"0.71443844",
"0.7110474",
"0.7107299",
"0.70606035",
"0.7057359",
"0.70439357",
"0.7029545"... | 0.69189537 | 27 |
Determines the crossing number of a horizontal positive ray from point with a polygon defined in edges. | def crossing_number(point:tuple, edges:list, include_edges:bool=True)->int:
crossing_number = 0
for edge in edges:
d_y, d_x, b = line_equation(edge)
if include_edges and point_on_line(point, edge, d_y, d_x, b):
return 1
if is_horizontal(edge):
continue
if ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def winding_number(x, y, primitive):\n\n wn = 0\n\n edges = zip(primitive[\"vertices\"][-1:] + primitive[\"vertices\"][:-1],\n primitive[\"vertices\"])\n for edge in edges:\n # check if cuts y parallel line at (x, y) &&\n if (edge[0][0] > x) != (edge[1][0] > x):\n #... | [
"0.6319946",
"0.628875",
"0.61075354",
"0.6013507",
"0.5910155",
"0.56875455",
"0.5654235",
"0.56247514",
"0.5608675",
"0.5508915",
"0.54895514",
"0.54782134",
"0.5462136",
"0.54489154",
"0.54295504",
"0.54053026",
"0.5375274",
"0.5368317",
"0.5356745",
"0.5355982",
"0.534888... | 0.76824135 | 0 |
Determines if a point is in a polygon using crossingnumber method. | def pinp_crossing(point:tuple, edges:list, include_edges:bool=True)->bool:
return crossing_number(point, edges, include_edges) % 2 == 1 | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def is_in_polygon(self, point):\n reference_point = self.get_reference_point()\n \n reference_segment = DirectedEdge(point, reference_point)\n\n num_crossings = 0\n \n left_idx = 0\n while left_idx != len(self):\n right_idx = (left_idx + 1) % len(self)\n ... | [
"0.823988",
"0.78379107",
"0.7658638",
"0.75398535",
"0.75207394",
"0.7450259",
"0.7434018",
"0.74160594",
"0.7403389",
"0.7377856",
"0.73732316",
"0.7357391",
"0.73370737",
"0.7325637",
"0.72021",
"0.7176894",
"0.70702785",
"0.6982318",
"0.6976491",
"0.6976491",
"0.6949547",... | 0.66881317 | 32 |
Determines which points are inside a polygon defined by edges. Points are streamed to callers. This is an adaptation of the above algorithm optimized for many points by only doing the slope and intercept calculations once per edge. | def pinp_multiple_crossing(points, edges, include_edges = True):
crossing_number = []
initialized = False
for edge in edges:
d_y, d_x, b = line_equation(edge)
index = -1
for point in points:
index += 1
if not initialized:
crossing_number.append... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def points_inside_poly(points, all_verts):\n return Path(all_verts, close=True).contains_points(points)",
"def polygon_contains(self, poly_outer, poly_inner):\n inner_list = self.poly_to_list(poly_inner, \"Global\")\n contain_list = []\n\n # Loop over all points in the inner polygon to se... | [
"0.6561789",
"0.63151556",
"0.6271785",
"0.6117632",
"0.6092992",
"0.60631436",
"0.6012318",
"0.6011012",
"0.5953818",
"0.58825284",
"0.580966",
"0.58055735",
"0.5803588",
"0.57825583",
"0.57565135",
"0.5723604",
"0.5716897",
"0.5709425",
"0.5709039",
"0.5676375",
"0.5661738"... | 0.57207507 | 16 |
An implementation of Graham's scan using inplace sorting to quickly build a convex hull. | def graham_scan(points):
if len(points) <= 3:
return points
pointList = ExtendedTupleList(points)
complete_range = pointList.range_within(0, 1)
first_point = (complete_range[1]["min"][1], complete_range[1]["min"][0])
newPoints = ExtendedTupleList([])
for point in pointList:
squar... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def graham_scan(points):\n\n # Find point with smallest y coordinate\n # If two points have equal y coordinates, select the one with the lower x-coordinate\n smallest = points[0]\n for p in points:\n if p[1] < smallest[1]:\n smallest = p\n elif p[1] == smallest[1]:\n ... | [
"0.70704556",
"0.7060805",
"0.67267764",
"0.64879376",
"0.6486455",
"0.640975",
"0.61319625",
"0.60088277",
"0.57791483",
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"0.5443114",
"0.5408968",
"0.5403702",
"0.5362627",
"0.5359406",
"0.5355959",
"0.5330... | 0.67683274 | 2 |
My own homegrown algorithm for building the convex hull. | def convex_hull(points):
pointList = ExtendedTupleList(points)
complete_ranges = pointList.range_within(0, 1)
# Filters for four quadrants
filters = [
((0, complete_ranges[1]["max"][2], ">="), (1, complete_ranges[0]["max"][2], ">=")), #Q1
((0, complete_ranges[1]["max"][1], "<="), (1, com... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def convex_hull(l):\n\tpass",
"def convex_hull(points):\n\n # Sort the points lexicographically (tuples are compared lexicographically).\n # Remove duplicates to detect the case we have just one unique point.\n points = sorted(set(points))\n\n # Boring case: no points or a single point, possibly repe... | [
"0.80086",
"0.78709483",
"0.75600183",
"0.745202",
"0.7436891",
"0.7415585",
"0.7319434",
"0.7194905",
"0.71566576",
"0.70986134",
"0.70718306",
"0.7056313",
"0.7040411",
"0.70237267",
"0.7002169",
"0.6926358",
"0.6903651",
"0.6885412",
"0.68636125",
"0.686115",
"0.6727542",
... | 0.75075173 | 3 |
Select the longest edge from hull that doesn't start with a point in ignore_left_points, with minimum length. Returns | def select_longest_edge(hull:list, ignore_left_points:list, min_sqr_length:int=0)->tuple:
max_sqr_length = None
selected = None
for k in range(0, len(hull) - 1):
if hull[k] in ignore_left_points:
continue
edge_sqr_length = point_sqr_distance(hull[k], hull[k+1])
if edge_sq... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def sort_hull(hull):\n max_unproc_edge = hull[np.lexsort((-hull.length, hull.is_processed))][0]\n idx = np.where(hull == max_unproc_edge)[0][0]\n\n # shift convex hull to have the longest edge at the beginning\n hull = np.roll(hull, -idx, axis=0)\n\n return hull, max_unproc_edge.length",
"def conc... | [
"0.5784756",
"0.5722361",
"0.57186353",
"0.571596",
"0.561899",
"0.5575985",
"0.5559472",
"0.5450202",
"0.5366452",
"0.5360122",
"0.53597206",
"0.53502905",
"0.53324366",
"0.5321323",
"0.5316823",
"0.5307588",
"0.5303187",
"0.5294098",
"0.52727485",
"0.5253577",
"0.5250945",
... | 0.8255255 | 0 |
Determines if the new edge would intersect the hull at any point. | def segments_intersects_hull(new_edges:list, hull:list, current_edge:tuple)->bool:
new_edge_extent = extent(new_edges[0][0], new_edges[0][1], new_edges[1][1])
for k in range(0, len(hull) - 1):
if new_edges[0][0] == hull[k] or new_edges[0][0] == hull[k+1]:
continue
elif new_edges[0][1... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def is_new(self):\n c_up = self.upper_binary_tree().single_edge_cut_shapes()\n c_down = self.lower_binary_tree().single_edge_cut_shapes()\n return not any(x in c_up for x in c_down)",
"def check_inside_hull(hull, instance):\n for face in hull:\n if not check_inside(face=face, insta... | [
"0.6484378",
"0.63872766",
"0.62879694",
"0.6258108",
"0.6223334",
"0.62019885",
"0.6185283",
"0.6149708",
"0.6138869",
"0.61183757",
"0.6070646",
"0.60460234",
"0.6039633",
"0.6038786",
"0.6038608",
"0.6034174",
"0.5997268",
"0.59944534",
"0.59907645",
"0.5983716",
"0.597896... | 0.7658259 | 0 |
Selects the point that meets the conditions to become part of a concave hull. | def select_candidate_point(edge:tuple, points:list, hull:list, min_cosine:float=-1)->tuple:
min_sqr_distance = None
selected = None
for point in points:
nearest_point = closest_line_point(point, edge)
if not near_segment(nearest_point, edge):
# We ignore points that wouldn't be a... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def teselado(self,points):\n #muestrea todo el espacio de la envolvente para conseguir las fronteras de decision a intervalos regulares \n #get_hull\n area = boundingbox(points)\n #(min_x,min_y),(max_x,min_y),(max_x,max_y),(min_x,max_y)\n #sample inside hull\n lat_sample =... | [
"0.63103765",
"0.63064873",
"0.61816275",
"0.6154425",
"0.61095697",
"0.60735637",
"0.59671175",
"0.5935509",
"0.5914783",
"0.5901849",
"0.5872185",
"0.5870017",
"0.58488506",
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"0.5792759",
"0.5779052",
"0.57423526",
"0.57101136",
"0.56947124",
"0.5675157",
"0.566... | 0.6182271 | 2 |
Creates a concave hull. | def concave_hull(hull:list, points:list, max_iterations:int=None, min_length_fraction:float=0, min_angle:float=90)->list:
tweet.info("Creating concave hull; minimum side length {}% of average, minimum_angle {}".format(min_length_fraction * 100, min_angle))
test_points = set(points)
ignore_points = []
av... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def convex_hull(self):\n return self._geomgen(capi.geom_convex_hull)",
"def convex_hull(points):\n\n # Sort the points lexicographically (tuples are compared lexicographically).\n # Remove duplicates to detect the case we have just one unique point.\n points = sorted(set(points))\n\n # Boring ... | [
"0.7206272",
"0.71888036",
"0.71256506",
"0.7085061",
"0.7075677",
"0.7031924",
"0.69883245",
"0.6819022",
"0.68025535",
"0.67614084",
"0.6739058",
"0.6691165",
"0.667362",
"0.6638784",
"0.65221596",
"0.6512171",
"0.646188",
"0.64251655",
"0.6401495",
"0.6394388",
"0.6354288"... | 0.7279524 | 0 |
Returns (None, specific set of required operands or None). | def Rewrite(self, expression, defaults=None, keys=None):
self._keys = keys or {}
_, operands = super(FilterScopeRewriter, self).Rewrite(
expression, defaults=defaults)
if isinstance(operands, six.string_types):
operands = set([operands])
return None, operands | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def try_fold_arithmetic_binop(\n op: ast.ops.Operator, left: irast.Set, right: irast.Set, *,\n ctx: context.ContextLevel) -> typing.Optional[irast.Set]:\n schema = ctx.schema\n\n real_t = schema.get('std::anyreal')\n float_t = schema.get('std::anyfloat')\n int_t = schema.get('std::anyint'... | [
"0.554483",
"0.55098975",
"0.54648745",
"0.54308915",
"0.5397291",
"0.53851604",
"0.53750557",
"0.53668904",
"0.534204",
"0.5338202",
"0.5331988",
"0.5327878",
"0.53219956",
"0.5321779",
"0.5303595",
"0.5287829",
"0.52522546",
"0.5238614",
"0.52210104",
"0.521642",
"0.521374"... | 0.0 | -1 |
Punt on negation. Only the caller knows the operand universe. | def RewriteNOT(self, expr):
return None | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _negation_op(spec, expression):",
"def __neg__(self):\n return type(self)(self.parent(), self._simplify(-self._express))",
"def __neg__(self):\n return self.__mul__(-1)",
"def neg(a):\n return prod(a, -1)",
"def __neg__(self):\n return self.negated()",
"def neg(a):\n return... | [
"0.73435956",
"0.699165",
"0.682434",
"0.6806528",
"0.6806039",
"0.67607474",
"0.6726903",
"0.67132604",
"0.6632549",
"0.66181093",
"0.66095734",
"0.65735376",
"0.6505464",
"0.64757454",
"0.6429829",
"0.6410526",
"0.64044005",
"0.6384057",
"0.6345979",
"0.63177085",
"0.629151... | 0.57410866 | 75 |
OR keeps all operands in play. | def RewriteOR(self, left, right):
return None | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __or__(self, other: Any) -> Operators:\n return self.operate(or_, other)",
"def or_(a, b):",
"def or_filter(self):\n return self.__or",
"def __or__(self, other):\n return self.fam.c_binop('or', self, other)",
"def __or__(self, other):\n return self.or_(other)",
"def _or(se... | [
"0.7526833",
"0.748305",
"0.72272426",
"0.7208705",
"0.7124411",
"0.711627",
"0.711627",
"0.711627",
"0.711627",
"0.711627",
"0.7092017",
"0.70893234",
"0.70513535",
"0.7031522",
"0.7018625",
"0.70110357",
"0.7006967",
"0.6979673",
"0.69745207",
"0.6944217",
"0.6928026",
"0... | 0.73900056 | 2 |
Rewrites restrictions for keys in self._keys. | def RewriteTerm(self, key, op, operand, key_type):
if key not in self._keys or op != '=':
return None
return operand | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _constrain_keys(self, dictionary):\n\n constrained = { k: dictionary[k] for k in self._keys if k in dictionary }\n return constrained",
"def harmonize_keys(self):\n self._data.key_regex_replacements = _key_regex_replacements\n self._data.key_replacements = _key_replacements",
"d... | [
"0.69033045",
"0.6338012",
"0.6272551",
"0.6123107",
"0.5859973",
"0.5691391",
"0.5625764",
"0.5609194",
"0.5576054",
"0.5485195",
"0.5455576",
"0.53918344",
"0.5368339",
"0.5357722",
"0.5356005",
"0.5309407",
"0.5308894",
"0.53055555",
"0.53029096",
"0.5256986",
"0.5244978",... | 0.0 | -1 |
Returns a string representation | def __str__(self):
return "[Square] (" + str(self.id) + ") " + str(
self.x) + "/" + str(self.y) + " - " + str(
self.width) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def to_str(self) -> str:",
"def toString():",
"def toString(self) -> str:\n raise NotImplementedError",
"def to_string(self):\r\n return self.__str__()",
"def to_str(self):\n return pformat(self.to_dict())",
"def to_str(self):\n return pformat(self.to_dict())",
"def to_str(s... | [
"0.8396673",
"0.82936347",
"0.80012363",
"0.7915748",
"0.77012867",
"0.77012867",
"0.77012867",
"0.77012867",
"0.77012867",
"0.77012867",
"0.77012867",
"0.77012867",
"0.77012867",
"0.77012867",
"0.77012867",
"0.77012867",
"0.77012867",
"0.77012867",
"0.77012867",
"0.77012867",
... | 0.0 | -1 |
Assign an argument to each attributes | def update(self, *args, **kwargs):
attributes = ["id", "size", "x", "y"]
if len(args) > 0:
for i in range(len(args)):
setattr(self, attributes[i], args[i])
else:
self.id = kwargs.get("id", self.id)
self.size = kwargs.get("size", self.size)
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def setAttributes(self, args):\n for atr in self.defaultAttributes:\n if args.has_key(atr):\n # convert atr to proper type\n objAttr = getattr(self, atr)\n myType = type(args[atr])\n if type(objAttr) == types.IntType and myType <> types.... | [
"0.74129784",
"0.7253339",
"0.7120195",
"0.7037738",
"0.6990127",
"0.6990127",
"0.6990127",
"0.6990127",
"0.6990127",
"0.6990127",
"0.6990127",
"0.6990127",
"0.6990127",
"0.6990127",
"0.6990127",
"0.6990127",
"0.6990127",
"0.6990127",
"0.6990127",
"0.6990127",
"0.6990127",
... | 0.64679074 | 43 |
returns the dictionary representation of a Rectangle | def to_dictionary(self):
return {"id": self.id, "x": self.x,
"size": self.size, "y": self.y} | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def rectangledict(self):\n return rectangledict(self.rectangles)",
"def to_dictionary(self):\n rect = {\n \"x\": self.x,\n \"y\": self.y,\n \"id\": self.id,\n \"height\": self.height,\n \"width\": self.width\n }\n return(rect)",
... | [
"0.8602724",
"0.8201665",
"0.8108615",
"0.8052318",
"0.79804254",
"0.774604",
"0.7632502",
"0.7477445",
"0.73376447",
"0.7333853",
"0.7112657",
"0.68645644",
"0.67418987",
"0.6740587",
"0.67366946",
"0.671641",
"0.6686742",
"0.6686742",
"0.6638892",
"0.6613355",
"0.66103834",... | 0.626603 | 32 |
Nose will execute this function before executing the tests. Remove all the files generated during previous test runs, create necessary directories and run the prepare data function | def setup_class(cls):
self = cls()
self.remove_files_created_during_previous_runs()
if not os.path.exists(self.plaintext_directory):
os.makedirs(self.plaintext_directory)
if not os.path.exists(self.training_path):
os.makedirs(self.training_path)
if not o... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def setUp(self):\n self.tearDown()\n utils.mkdir_p(TMP_BASENAME_DIR)",
"def setUp(self):\r\n super(TestImport, self).setUp()\r\n self.content_dir = path(tempfile.mkdtemp())\r\n self.addCleanup(shutil.rmtree, self.content_dir)\r\n\r\n # Create good course xml\r\n s... | [
"0.73244756",
"0.72804755",
"0.7233866",
"0.7178239",
"0.71641874",
"0.7157685",
"0.71102923",
"0.71080315",
"0.7104167",
"0.7100945",
"0.70877147",
"0.7069167",
"0.7059233",
"0.7031363",
"0.7018821",
"0.7005832",
"0.6993371",
"0.6931856",
"0.6929316",
"0.69214904",
"0.691219... | 0.0 | -1 |
Nose will execute this function after executing all the tests. Remove files generated during test runs | def teardown_class(cls):
self = cls()
self.remove_files_created_during_previous_runs() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def tearDown(self):\n self.remove_test_files()",
"def tearDown(self):\n testing_dir = os.path.split(os.path.realpath(__file__))[0]\n for f in glob.glob(os.path.join(testing_dir, \"*\")):\n if f.split(\".\")[-1] in [\"o\", \"out\", \"pyc\", \"log\"]:\n subprocess.cal... | [
"0.79564494",
"0.7922551",
"0.7731818",
"0.7725066",
"0.7597718",
"0.7541712",
"0.75238997",
"0.7476529",
"0.7441866",
"0.7432386",
"0.74241424",
"0.74227935",
"0.7406666",
"0.7307176",
"0.7307176",
"0.7307176",
"0.73070675",
"0.7299069",
"0.72886336",
"0.72333694",
"0.723083... | 0.0 | -1 |
Method to get a reference to a class that specifies the input data for class cls. @ In, cls, the class for which we are retrieving the specification @ Out, inputSpecification, InputData.ParameterInput, class to use for specifying input of cls. | def getInputSpecification(cls):
inputSpecification = super(Metropolis, cls).getInputSpecification()
return inputSpecification | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def getInputSpecification(cls):\n inputSpecification = InputData.parameterInputFactory(cls.__name__, ordered=True, baseNode=None)\n\n StatePartInput = InputData.parameterInputFactory(\"state\", contentType=InputTypes.StringType)\n StatePartInput.addParam(\"outcome\", InputTypes.FloatType, True)\n State... | [
"0.6275034",
"0.60379297",
"0.5730839",
"0.5726884",
"0.56846875",
"0.5625551",
"0.55976015",
"0.5574512",
"0.55434084",
"0.5535107",
"0.55097574",
"0.5491663",
"0.5483585",
"0.5470132",
"0.5409276",
"0.54024297",
"0.5361116",
"0.53348005",
"0.53283894",
"0.53078043",
"0.5294... | 0.59754 | 2 |
Default Constructor that will initialize member variables with reasonable defaults or empty lists/dictionaries where applicable. @ In, None @ Out, None | def __init__(self):
MCMC.__init__(self) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __init__(self, **kwds):\n raise NotImplementedError",
"def __init__(self, *args, **kwargs) -> None:\n pass",
"def __init__(self, *args, **kwargs) -> None:\n pass",
"def __init__(self) -> None:\n # TODO: Provide the complete constructor for this object",
"def __init__(self, *... | [
"0.72449476",
"0.70512044",
"0.70512044",
"0.7036811",
"0.7014676",
"0.69895023",
"0.6976433",
"0.6954044",
"0.695061",
"0.6948332",
"0.6934927",
"0.6900211",
"0.68901324",
"0.68901324",
"0.68901324",
"0.6817234",
"0.67974657",
"0.67517906",
"0.6742774",
"0.6742774",
"0.67427... | 0.0 | -1 |
Read input specs @ In, paramInput, InputData.ParameterInput, parameter specs interpreted @ Out, None | def handleInput(self, paramInput):
MCMC.handleInput(self, paramInput) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _handleInput(self, paramInput):\n pass",
"def read_input(self, specs, mode, comp_name):\n self.raiseADebug(' ... loading interaction \"{}\"'.format(self.tag))\n self._dispatchable = specs.parameterValues['dispatch']\n for item in specs.subparts:\n name = '_' + item.getName()\n if name i... | [
"0.65148056",
"0.6373364",
"0.6224871",
"0.6187908",
"0.61549926",
"0.6142404",
"0.61416185",
"0.61400414",
"0.61288595",
"0.6105816",
"0.60883975",
"0.6038212",
"0.6015596",
"0.59900856",
"0.5985972",
"0.5976563",
"0.587159",
"0.58707494",
"0.58549327",
"0.58468914",
"0.5834... | 0.61994773 | 3 |
This function should be called every time a clean MCMC is needed. Called before takeAstep in @ In, externalSeeding, int, optional, external seed @ In, solutionExport, DataObject, optional, a PointSet to hold the solution @ Out, None | def initialize(self, externalSeeding=None, solutionExport=None):
MCMC.initialize(self, externalSeeding=externalSeeding, solutionExport=solutionExport)
if not self._correlated:
for var in self._updateValues:
if var in self.distDict:
dist = self.distDict[var]
dim = dist.getDimens... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def clean_up(self) -> None:\n print('Doing some clean-up work...')",
"def trial_clean_up(self):\n pass",
"def cleanUp():\n pass",
"def clean(self):\n self.iiter = 0\n print(colored('Finished patch %s' % self.image_name, 'yellow'))\n torch.cuda.empty_cache()\n self... | [
"0.5972903",
"0.5940058",
"0.57677114",
"0.5659115",
"0.56506276",
"0.5642487",
"0.56210417",
"0.56102026",
"0.5481459",
"0.54640925",
"0.5445583",
"0.5422247",
"0.540909",
"0.5407289",
"0.5386823",
"0.53828806",
"0.53821695",
"0.5377255",
"0.5371626",
"0.5362387",
"0.5349434... | 0.0 | -1 |
Provides the next sample to take. After this method is called, the self.inputInfo should be ready to be sent to the model @ In, model, model instance, an instance of a model @ In, myInput, list, a list of the original needed inputs for the model (e.g. list of files, etc.) @ Out, None | def localGenerateInput(self, model, myInput):
if self.counter < 2:
MCMC.localGenerateInput(self, model, myInput)
else:
self._localReady = False
for key, value in self._updateValues.items():
# update value based on proposal distribution
newVal = value + self._proposal[key].rvs()... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def input(self):\n try:\n return self.inputs[-1]\n except IndexError:\n pass\n raise ValueError(\"The sample method has not been called\")",
"def test_prepare_sample_to_forward(self):\n sample = [\n {\"src\": \"ola mundo\", \"ref\": \"hi world\", \"mt\... | [
"0.70868576",
"0.6604615",
"0.65657943",
"0.6411239",
"0.6372315",
"0.63269866",
"0.62161213",
"0.61675435",
"0.6153169",
"0.6153169",
"0.61334926",
"0.6080559",
"0.607126",
"0.5985408",
"0.59807396",
"0.5938614",
"0.5915001",
"0.5886959",
"0.5884955",
"0.58460677",
"0.582307... | 0.6721474 | 1 |
General function (available to all samplers) that finalize the sampling calculation just ended. In this case, The function is aimed to check if all the batch calculations have been performed @ In, jobObject, instance, an instance of a JobHandler @ In, model, model instance, it is the instance of a RAVEN model @ In, myI... | def localFinalizeActualSampling(self, jobObject, model, myInput):
MCMC.localFinalizeActualSampling(self, jobObject, model, myInput) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def can_finalize_job_record(self):\n pass",
"def has_full_batch(self) -> bool:",
"def finalize(self):\n\t\tself.logger.info(\"Please wait while finalizing the operation.. Thank you\")\n\t\tself.save_checkpoint()\n\t\tself.summary_writer.export_scalars_to_json(\"{}all_scalars.json\".format(self.config.su... | [
"0.6187927",
"0.5795619",
"0.5728285",
"0.56815076",
"0.56358445",
"0.5633501",
"0.5633048",
"0.5577172",
"0.55352855",
"0.55237323",
"0.5502523",
"0.5490598",
"0.54837555",
"0.54806143",
"0.5472647",
"0.5471663",
"0.5465032",
"0.5452882",
"0.54441124",
"0.54441124",
"0.54441... | 0.6751163 | 0 |
Used to feedback the collected runs within the sampler @ In, newRlz, dict, new generated realization @ In, currentRlz, dict, the current existing realization @ Out, netLogPosterior, float, the accepted probabilty | def _useRealization(self, newRlz, currentRlz):
netLogPosterior = 0
# compute net log prior
for var in self._updateValues:
newVal = newRlz[var]
currVal = currentRlz[var]
if var in self.distDict:
dist = self.distDict[var]
netLogPrior = dist.logPdf(newVal) - dist.logPdf(currVa... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def inference_spa(flow_lik,\n flow_post,\n prior,\n simulator,\n optimizer_lik,\n optimizer_post,\n decay_rate_post,\n x_o,\n x_o_batch_post,\n dim_post,\n ... | [
"0.6228127",
"0.61634594",
"0.6074014",
"0.6050275",
"0.6050275",
"0.59674543",
"0.5956656",
"0.5953617",
"0.58580154",
"0.58394265",
"0.5830465",
"0.5820498",
"0.57669336",
"0.5730289",
"0.5701165",
"0.5655382",
"0.56536853",
"0.56534696",
"0.56493",
"0.5646722",
"0.56436014... | 0.73664874 | 0 |
Determines if sampler is prepared to provide another input. If not, and if jobHandler is finished, this will end sampling. @ In, ready, bool, a boolean representing whether the caller is prepared for another input. @ Out, ready, bool, a boolean representing whether the caller is prepared for another input. | def localStillReady(self, ready):
ready = self._localReady and MCMC.localStillReady(self, ready)
return ready | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def has_buffered_inputs(self):",
"def is_prepared(self):\n try:\n ret = (\n self.is_prepared_for_input_socket() and\n self.is_prepared_for_setting() and\n self.is_prepared_for_hoge()\n )\n except CheckPreparedException as e:\n ... | [
"0.558299",
"0.5549085",
"0.5531201",
"0.5440989",
"0.5403814",
"0.53479713",
"0.5329904",
"0.53009325",
"0.523241",
"0.5161378",
"0.50855684",
"0.5058236",
"0.50328124",
"0.502983",
"0.50063264",
"0.49893746",
"0.49873114",
"0.49788696",
"0.4978666",
"0.4960595",
"0.49489564... | 0.49407262 | 21 |
Forward pass for prediction aggregator | def forward(self, encodings: Dict) -> Union[Dict, torch.Tensor]:
raise NotImplementedError() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def forward_train(self, *args, **kwargs):\n pass",
"def forward_propagation(self):\n pred_y = argmax(self.model.predict(train_x), axis=1)\n\n accuracy_func = Accuracy()\n accuracy_func.update_state(pred_y, train_y)\n self.accuracy = accuracy_func.result().numpy()",
"def forwa... | [
"0.74012876",
"0.7157714",
"0.7145412",
"0.7046437",
"0.7015131",
"0.6985374",
"0.6952822",
"0.69475394",
"0.6920287",
"0.68856066",
"0.6870751",
"0.6853668",
"0.684333",
"0.6823695",
"0.6816687",
"0.68037724",
"0.6794375",
"0.6794375",
"0.67894006",
"0.67894006",
"0.67894006... | 0.0 | -1 |
Lifecycle a model defined in Swagger | def __init__(self, applicable_job_statuses=None, action_time=None, action=None, type=None):
self.swagger_types = {
'applicable_job_statuses': 'list[str]',
'action_time': 'datetime',
'action': 'str',
'type': 'str'
}
self.attribute_map = {
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __init__(self):\n self.swagger_types = {\n 'ids': 'list[str]',\n 'consumer': 'str',\n 'entity_type': 'str',\n 'start_date': 'datetime',\n 'end_date': 'datetime',\n 'created_date': 'datetime',\n 'updated_date': 'datetime',\n ... | [
"0.57578397",
"0.57171565",
"0.5694597",
"0.56923044",
"0.56630313",
"0.56269646",
"0.55970424",
"0.5569859",
"0.5567609",
"0.55565476",
"0.5546851",
"0.5546806",
"0.5544655",
"0.5544655",
"0.5544655",
"0.5544655",
"0.55091864",
"0.5480632",
"0.54442686",
"0.54442686",
"0.544... | 0.0 | -1 |
Gets the applicable_job_statuses of this Lifecycle. Job status needs to be in this list in order for the action to be performed! | def applicable_job_statuses(self):
return self._applicable_job_statuses | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def applicable_job_statuses(self, applicable_job_statuses):\n allowed_values = []\n if applicable_job_statuses not in allowed_values:\n raise ValueError(\n \"Invalid value for `applicable_job_statuses` ({0}), must be one of {1}\"\n .format(applicable_job_statu... | [
"0.6967596",
"0.6617357",
"0.6617357",
"0.61123466",
"0.5901221",
"0.58656716",
"0.5798119",
"0.5798119",
"0.5790288",
"0.57691395",
"0.57252294",
"0.5707428",
"0.5665692",
"0.5640539",
"0.5625412",
"0.55947644",
"0.55841506",
"0.5555595",
"0.5541644",
"0.5536113",
"0.552849"... | 0.8614955 | 0 |
Sets the applicable_job_statuses of this Lifecycle. Job status needs to be in this list in order for the action to be performed! | def applicable_job_statuses(self, applicable_job_statuses):
allowed_values = []
if applicable_job_statuses not in allowed_values:
raise ValueError(
"Invalid value for `applicable_job_statuses` ({0}), must be one of {1}"
.format(applicable_job_statuses, allowed... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def applicable_job_statuses(self):\n return self._applicable_job_statuses",
"def __init__(self, applicable_job_statuses=None, action_time=None, action=None, type=None):\n self.swagger_types = {\n 'applicable_job_statuses': 'list[str]',\n 'action_time': 'datetime',\n ... | [
"0.6695411",
"0.5844042",
"0.5563415",
"0.5545432",
"0.5485883",
"0.5475218",
"0.5449763",
"0.5404465",
"0.5384887",
"0.53246635",
"0.53229064",
"0.5294377",
"0.52781755",
"0.52380747",
"0.5186252",
"0.5116745",
"0.50967646",
"0.5069076",
"0.50412786",
"0.502424",
"0.4990202"... | 0.8249736 | 0 |
Gets the action_time of this Lifecycle. The time at which the job and files will be deleted, regardless of whether it has been retrieved or not. Maximal time is 1 day from job creation | def action_time(self):
return self._action_time | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def time_consumed(self) -> int:\n if not self.actions:\n return 0\n else:\n return self.actions[-1].time_end",
"def delete_time(self) -> str:\n return pulumi.get(self, \"delete_time\")",
"def delete_time(self) -> str:\n return pulumi.get(self, \"delete_time\")"... | [
"0.6351681",
"0.6334942",
"0.6334942",
"0.6254808",
"0.62357366",
"0.615849",
"0.61072457",
"0.6091936",
"0.6077282",
"0.60503584",
"0.59982574",
"0.5907601",
"0.5900668",
"0.58995885",
"0.5868122",
"0.5856616",
"0.5840132",
"0.57963824",
"0.57763684",
"0.57763684",
"0.577636... | 0.78159416 | 0 |
Sets the action_time of this Lifecycle. The time at which the job and files will be deleted, regardless of whether it has been retrieved or not. Maximal time is 1 day from job creation | def action_time(self, action_time):
self._action_time = action_time | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def action_time(self):\n return self._action_time",
"def on_action_time_changed(self, content):\n time = parse_iso_dt(content['time']).time()\n self.set_guarded(time=time)",
"def action(self, action):\n allowed_values = [\"DELETE\", \"NONE\"]\n if action not in allowed_values... | [
"0.60692436",
"0.6039037",
"0.5710749",
"0.55339384",
"0.55339384",
"0.55339384",
"0.55339384",
"0.55339384",
"0.55339384",
"0.55339384",
"0.55339384",
"0.55339384",
"0.55339384",
"0.55103743",
"0.5410098",
"0.53928286",
"0.53928286",
"0.5351073",
"0.5344618",
"0.53365284",
"... | 0.7611136 | 0 |
Gets the action of this Lifecycle. The action to perform. Currently only delete is supported | def action(self):
return self._action | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def get_action(self):\n return self.__action",
"def get_action(self):\n return self.current_action",
"def action(self):\n return self._get_field(\"action\")",
"def action(self) -> Optional[str]:\n return pulumi.get(self, \"action\")",
"def action(self) -> Optional[str]:\n ... | [
"0.7956197",
"0.7459488",
"0.7432588",
"0.7238182",
"0.7238182",
"0.7238182",
"0.7208887",
"0.71846193",
"0.71716344",
"0.71587044",
"0.7045301",
"0.70392245",
"0.6941939",
"0.6926468",
"0.68683374",
"0.6690194",
"0.6672939",
"0.6605948",
"0.65702957",
"0.64770836",
"0.645596... | 0.7538712 | 5 |
Sets the action of this Lifecycle. The action to perform. Currently only delete is supported | def action(self, action):
allowed_values = ["DELETE", "NONE"]
if action not in allowed_values:
raise ValueError(
"Invalid value for `action` ({0}), must be one of {1}"
.format(action, allowed_values)
)
self._action = action | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def set_action(self, action):\n self._action = action\n return self",
"def setAction(self, action):\n self.action = action\n return self",
"def set_action(self, action):\n self.action = action",
"def set_action(self, action):\n self.action = action",
"def set_actio... | [
"0.798209",
"0.7937381",
"0.78521293",
"0.78521293",
"0.77787465",
"0.7659929",
"0.7434554",
"0.7401559",
"0.73724025",
"0.7369807",
"0.72310543",
"0.72310543",
"0.72310543",
"0.72310543",
"0.72310543",
"0.72310543",
"0.70674974",
"0.699461",
"0.6960725",
"0.6901665",
"0.6726... | 0.7996904 | 0 |
Gets the type of this Lifecycle. Determine when to delete the job and associated files. RETRIEVAL means delete directly after retrieving the PDF file. When the file has not been retrieved before the action time, it will be deleted regardless. Time means, delete on specific time, regardless of whether it has been proces... | def type(self):
return self._type | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def ExpireType(self):\n if self.force_auto_sync:\n self.get('ExpireType')\n return self._ExpireType",
"def delete_time(self) -> str:\n return pulumi.get(self, \"delete_time\")",
"def delete_time(self) -> str:\n return pulumi.get(self, \"delete_time\")",
"def deleted_tim... | [
"0.5974232",
"0.54896796",
"0.54896796",
"0.51819205",
"0.5125803",
"0.49722493",
"0.4905789",
"0.4882752",
"0.47758582",
"0.47730514",
"0.47563097",
"0.4699075",
"0.46979105",
"0.4691771",
"0.4682157",
"0.4674297",
"0.4623792",
"0.46149534",
"0.46005246",
"0.4593693",
"0.458... | 0.4375041 | 85 |
Sets the type of this Lifecycle. Determine when to delete the job and associated files. RETRIEVAL means delete directly after retrieving the PDF file. When the file has not been retrieved before the action time, it will be deleted regardless. Time means, delete on specific time, regardless of whether it has been proces... | def type(self, type):
allowed_values = ["RETRIEVAL", "TIME"]
if type not in allowed_values:
raise ValueError(
"Invalid value for `type` ({0}), must be one of {1}"
.format(type, allowed_values)
)
self._type = type | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __init__(__self__, *,\n duration: pulumi.Input[str],\n object_type: pulumi.Input[str]):\n pulumi.set(__self__, \"duration\", duration)\n pulumi.set(__self__, \"object_type\", 'AbsoluteDeleteOption')",
"def ExpireType(self):\n if self.force_auto_sync:\n ... | [
"0.55426234",
"0.54422",
"0.54303664",
"0.5243352",
"0.5130753",
"0.51242626",
"0.49633163",
"0.49580863",
"0.4862699",
"0.4837523",
"0.48264766",
"0.47609124",
"0.47609124",
"0.47589472",
"0.47226307",
"0.4716207",
"0.4709835",
"0.46772438",
"0.46732327",
"0.46732327",
"0.46... | 0.5637675 | 0 |
Returns the model properties as a dict | def to_dict(self):
result = {}
for attr, _ in iteritems(self.swagger_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map(
lambda x: x.to_dict() if hasattr(x, "to_dict") else x,
value
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def to_dict(self):\n return self.properties",
"def to_dict(self):\n return self.properties",
"def get_properties(self):\n return self.properties",
"def asdict(self):\n return self._prop_dict",
"def json(self):\n rv = {\n prop: getattr(self, prop)\n f... | [
"0.7751993",
"0.7751993",
"0.73391134",
"0.7334895",
"0.7297356",
"0.727818",
"0.7159078",
"0.71578115",
"0.71494967",
"0.71494967",
"0.71283495",
"0.71275014",
"0.7122587",
"0.71079814",
"0.7060394",
"0.7043251",
"0.7034103",
"0.70233124",
"0.69635814",
"0.69586295",
"0.6900... | 0.0 | -1 |
Returns the string representation of the model | def to_str(self):
return pformat(self.to_dict()) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __str__(self):\n return super().__str__() + self.model.__str__()",
"def __str__(self) -> str:\n # noinspection PyUnresolvedReferences\n opts = self._meta\n if self.name_field:\n result = str(opts.get_field(self.name_field).value_from_object(self))\n else:\n ... | [
"0.85856134",
"0.7814518",
"0.77898884",
"0.7751367",
"0.7751367",
"0.7712228",
"0.76981676",
"0.76700574",
"0.7651133",
"0.7597206",
"0.75800353",
"0.7568254",
"0.7538184",
"0.75228703",
"0.7515832",
"0.7498764",
"0.74850684",
"0.74850684",
"0.7467648",
"0.74488163",
"0.7442... | 0.0 | -1 |
For `print` and `pprint` | def __repr__(self):
return self.to_str() | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def pprint(*args, **kwargs):\n if PRINTING:\n print(*args, **kwargs)",
"def print_out():\n pass",
"def custom_print(*objects):\n print(*objects, sep=OFS, end=ORS)",
"def _print(self, *args):\n return _ida_hexrays.vd_printer_t__print(self, *args)",
"def _printable(self):\n ... | [
"0.75577796",
"0.73381156",
"0.6987731",
"0.6985827",
"0.69452065",
"0.6924739",
"0.68991655",
"0.6898615",
"0.681538",
"0.6807118",
"0.6752345",
"0.67502004",
"0.674556",
"0.67000055",
"0.6690762",
"0.66755",
"0.66583294",
"0.66100985",
"0.6608339",
"0.6602482",
"0.6563445",... | 0.0 | -1 |
Returns true if both objects are equal | def __eq__(self, other):
return self.__dict__ == other.__dict__ | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __eq__(self, other):\n return are_equal(self, other)",
"def __eq__(self, other):\n return are_equal(self, other)",
"def __eq__(self,other):\n try: return self.object==other.object and isinstance(self,type(other))\n except: return False",
"def __eq__(self, other):\n if i... | [
"0.8088132",
"0.8088132",
"0.8054589",
"0.7982687",
"0.7961088",
"0.7961088",
"0.79433626",
"0.79303336",
"0.7926563",
"0.7897525",
"0.78826123",
"0.78826123",
"0.78806067",
"0.7872423",
"0.7868354",
"0.78668815",
"0.7825702",
"0.7819993",
"0.78162885",
"0.78078854",
"0.78068... | 0.79670393 | 45 |
Returns true if both objects are not equal | def __ne__(self, other):
return not self == other | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __ne__(self, other: object) -> bool:\n if self.__eq__(other):\n return False\n return True",
"def __ne__(self, other: object) -> bool:\n return not self.__eq__(other)",
"def __ne__(self, other) -> bool:\n return not self.__eq__(other)",
"def __eq__(self, other):\n ... | [
"0.845611",
"0.8391477",
"0.8144138",
"0.81410587",
"0.8132492",
"0.8093973",
"0.80920255",
"0.80920255",
"0.80920255",
"0.8085325",
"0.8085325",
"0.8076365",
"0.8076365",
"0.8065748"
] | 0.0 | -1 |
Method generates temporary population, which will be reproduced | def generate_T(self):
T = np.empty([self.lmbd, self.d * 2])
# loop for sampling with replacement
for i in range(self.lmbd):
random_id = np.random.randint(low=0, high=self.mi-1)
T[i, :] = self.P[random_id, :]
return T | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def genPopulation(self):\r\n self.population_list = []\r\n for i in xrange(0, self.pop_size):\r\n individual = bitarray(self.indv_size)\r\n # Loop for randomizing the 'individual' string.\r\n for j in xrange(0, self.board_size):\r\n vert_pos = random.ra... | [
"0.7213548",
"0.71295714",
"0.7119022",
"0.70341957",
"0.6996263",
"0.6936632",
"0.6900848",
"0.68596786",
"0.68436706",
"0.67404014",
"0.6738945",
"0.67345905",
"0.67268467",
"0.67135733",
"0.66405267",
"0.6623459",
"0.6619895",
"0.658391",
"0.65606153",
"0.6538149",
"0.6520... | 0.0 | -1 |
Method creates new individuals from T by mutation | def reproduce(self, T):
R = np.empty([self.lmbd, self.d * 2])
for i in range(0, self.lmbd):
R[i, :] = self.mutate(T[i])
return R | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def mutatation(self, indiv: Tour) -> Tour:\n n = indiv.size()\n for i in range(n):\n if random.random() < self.mutation_rate:\n j = int(random.random() * n)\n\n # Swap 2 genes (cities)\n indiv.tour_ids[i], indiv.tour_ids[j] = indiv.tour_ids[j], ... | [
"0.6567575",
"0.6517559",
"0.6228159",
"0.6022811",
"0.58399093",
"0.58164763",
"0.57760966",
"0.5718301",
"0.5622647",
"0.5590459",
"0.55880195",
"0.5586507",
"0.5582022",
"0.55698514",
"0.55439436",
"0.5483295",
"0.5431505",
"0.5415131",
"0.53600824",
"0.533807",
"0.5329494... | 0.50152284 | 47 |
Method creates new population by choosing mi best individuals from children and current population | def choose_mi_best(self, R):
population = np.empty([self.P.shape[0] + R.shape[0], 2*self.d + 1])
i = 0
for individual in np.vstack([self.P, R]):
population[i, 0] = -self.J(individual[0:self.d], self.nCEC)
population[i, 1:] = individual
i = i+1
sorted_... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create_new_population(self):\n self.check_for_generation_cap()\n pop_container = list()\n for chromosome in self.population:\n partner = bm.select_partner(\n self.fitness_scores, self.population)\n child = bm.mutate(bm.crossover(chromosome, partner))\n ... | [
"0.72537977",
"0.7044384",
"0.6994038",
"0.6913278",
"0.6836467",
"0.68160486",
"0.6813089",
"0.6794303",
"0.66997755",
"0.6687283",
"0.6557448",
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"0.6468302",
"0.64377743",
"0.6427576",
"0.64246714",
"0.63853765",
"0.6369065",
"0.6355021",
"0.6325369",
"0.6313070... | 0.0 | -1 |
One iteration of unmodified evolutionary algorithm | def iteration(self):
T = self.generate_T()
R = self.reproduce(T)
self.P = self.choose_mi_best(R)
#print(self.P) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def algorithm_loop(self):",
"def illuminator_of_elfes():\n\n\t# Alpha - simplified by taking out the i by multiplying the outerproduct by 2i\n\talpha1i = np.matrix([[0, 0, 0, 2], [0, 0, 2, 0], [0, -2, 0, 0], [-2, 0, 0, 0]])\n\talpha2i = np.matrix([[0, 2, 0, 0], [-2, 0, 0, 0], [0, 0, 0, 2], [0, 0, -2, 0]])\n\talp... | [
"0.6418409",
"0.64113474",
"0.6084446",
"0.6018408",
"0.5965569",
"0.58419895",
"0.58355474",
"0.5834112",
"0.5818233",
"0.58062494",
"0.57600445",
"0.57425374",
"0.57184786",
"0.57096803",
"0.56773627",
"0.56721646",
"0.56531054",
"0.56517786",
"0.56475276",
"0.5627075",
"0.... | 0.0 | -1 |
Method makes new individual from another individual by mutation | def mutate(self, x):
ksi = np.random.normal(0, 1)
mutated_x = np.zeros(len(x))
for i in range(self.d):
ksi_i = np.random.normal(0, 1)
mutated_x[self.d + i] = x[self.d + i] * np.exp(self.tau * ksi + self.tau_prim * ksi_i)
for i in range(self.d):
v_i =... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def create_individual(self):\n pass",
"def copy_as_new(self) -> \"Individual\":\n return Individual(self.main_node.copy(), to_pipeline=self._to_pipeline)",
"def mutate(self, individual):\n bulbs_on = self.decode(individual)\n x = np.random.randint(0, self.width, (self.width,))\n ... | [
"0.67647445",
"0.6372697",
"0.62912905",
"0.62885576",
"0.6243023",
"0.6224085",
"0.616013",
"0.6096474",
"0.6072597",
"0.59859306",
"0.596885",
"0.59619415",
"0.5945391",
"0.5942911",
"0.5937435",
"0.5925736",
"0.59109753",
"0.59108746",
"0.58518016",
"0.58446056",
"0.583830... | 0.0 | -1 |
initialize a player and associated symbol. | def __init__(
self,
symbol: int,
lr: float = 0.2,
exp_rate: float = 0.4,
discount_factor: float = 0.1,
) -> None:
self.symbol = symbol
self.lr = lr
self.exp_rate = exp_rate
self.discount_factor = discount_factor
self.states: Dict[str, f... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __init__(self, player_name):\n self._player_name = player_name\n self._hand = Deck() \n self._coder = Deck()",
"def __init__(self, player):\n\t\tself.player = player",
"def __init__(self, symbol, row, col, player, king):\n self.symbol = symbol\n self.row = row\n ... | [
"0.7044783",
"0.6994902",
"0.6952127",
"0.6900736",
"0.69004774",
"0.68714845",
"0.6831614",
"0.67411584",
"0.6740048",
"0.67184275",
"0.66184455",
"0.65796345",
"0.6571856",
"0.65473825",
"0.6523081",
"0.64922744",
"0.6482463",
"0.647235",
"0.6465849",
"0.6444604",
"0.643477... | 0.0 | -1 |
checks if move has been made before. if not, initialize in move dictionary. otherwise, return current value of making that move. | def _get_values(self, hash: str) -> float:
if hash not in self.states:
values = 0.0
else:
values = self.states[hash]
return values | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def makeMove(self, move):\n\t\ttry:\n\t\t\tif (self.board[int(move) - 1] is Piece.BLANK):\n\t\t\t\tself.board[int(move) - 1] = self.current\n\t\t\t\treturn 1\n\t\t\telse:\n\t\t\t\treturn 0\n\t\texcept:\n\t\t\treturn 0",
"def forecast_move(self, move):\n if move not in get_legal_moves(self):\n r... | [
"0.6581317",
"0.64663315",
"0.6350605",
"0.6310733",
"0.62825227",
"0.6280581",
"0.6211462",
"0.618281",
"0.61476415",
"0.6136375",
"0.61113304",
"0.6085092",
"0.60824883",
"0.6075988",
"0.6072908",
"0.60634327",
"0.60537124",
"0.60463786",
"0.60163736",
"0.6004055",
"0.59900... | 0.0 | -1 |
add move to front of the list. | def update_move_history(self, board_hash: str) -> None:
self.moves_taken.insert(0, board_hash) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def add_front(self, item):\n\n self.items.insert(0, item)",
"def addFront(self, item, clock):\n temp = Node2Way(item, clock)\n temp.setPrevious(self._front)\n \n if self._size == 0:\n self._rear = temp\n else:\n self._front.setNext(temp)\n ... | [
"0.74281985",
"0.7051179",
"0.6917639",
"0.68836725",
"0.6876215",
"0.6802277",
"0.67820287",
"0.67804265",
"0.672873",
"0.66930217",
"0.66753036",
"0.66617584",
"0.6631564",
"0.6548123",
"0.63872343",
"0.6376272",
"0.6376272",
"0.62471837",
"0.6227319",
"0.6203899",
"0.61776... | 0.0 | -1 |
back to square one. | def reset(self) -> None:
self.moves_taken = [] | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def square(l):\n for i in range(4):\n forward(l)\n left(90)",
"def walk_down(self):\n if self.col_num == len(self.master_grid.matrix[0])-1 and self.row_num == len(self.master_grid.matrix)-1:\n return None\n if self.row_num == len(self.master_grid.matrix)-1:\n ... | [
"0.6398951",
"0.61307216",
"0.60816234",
"0.6041529",
"0.59746027",
"0.58239824",
"0.57904434",
"0.5785858",
"0.5785107",
"0.5766752",
"0.57411844",
"0.5710696",
"0.5701157",
"0.56979847",
"0.56743014",
"0.56705886",
"0.5663607",
"0.56095517",
"0.558232",
"0.5569058",
"0.5557... | 0.0 | -1 |
Return FP, FN, TP for each class in the image | def compare_with_annot(last_pred, last_annot, iou_thres = 0.5):
classes_results = {}
for class_idx, pred_dict in last_pred.items():
classes_results[class_idx] = {}
classes_results[class_idx]['N'] = len(last_annot[class_idx]['bboxes'])
hits = 0
for bbox_annot in last_annot[class_i... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def tp_tn_fp_fn(accuracy_foreach_class_dict):\n tp = accuracy_foreach_class_dict[\"anomaly\"][1]\n tn = accuracy_foreach_class_dict[\"normal\"][1]\n fp = accuracy_foreach_class_dict[\"normal\"][2]\n fn = accuracy_foreach_class_dict[\"anomaly\"][2]\n return tp, tn, fp, fn",
"def extract_feat(self, ... | [
"0.686146",
"0.6137188",
"0.6137188",
"0.6093621",
"0.6043819",
"0.60024786",
"0.59570175",
"0.5947353",
"0.59439754",
"0.59368724",
"0.5914622",
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"0.5902004",
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"0.58622044",
"0.58407634",
"0.58253527",
"0.57962793",
"0.572621",
"0.5714585",
"0.57066804... | 0.0 | -1 |
Selects the best bounding box out of NUMBER_OF_BBOX possible bboxes and calculates the average IOU if consider_class is true then predicted_class has to be equal to annotated class to consider de IOU | def get_IOUs_enhanced(annotations, predictions, n_classes, consider_class = True):
NUMBER_OF_BBOX = annotations.shape[-2]
obj_indexes = np.where(annotations[:,:,:,:,0] == 1)
annotated_bboxes = annotations[obj_indexes][:][:,n_classes+1:n_classes+1+4]
bboxes_iou = np.zeros([annotated_bboxes.shape[0], NUMB... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def nms(bboxes, iou_threshold, sigma = 0.3, method = 'nms'):\n \"\"\" takes bboxes with the shape of (num_of_box, 6), where 6 => (xmin, ymin, xmax, ymax, score, class) \"\"\"\n \n # remove duplicates in classes\n classes_in_img = list(set(bboxes[:, 5]))\n \n # initialise list to store best bboxes... | [
"0.6985329",
"0.6839801",
"0.6732569",
"0.6646707",
"0.66217047",
"0.65684223",
"0.6531683",
"0.64877915",
"0.6476494",
"0.64743674",
"0.6451059",
"0.64403445",
"0.6401157",
"0.63813376",
"0.63734615",
"0.6373079",
"0.6362368",
"0.6344149",
"0.6338288",
"0.6330694",
"0.631954... | 0.64803255 | 8 |
Basic test for findService parsing with a civic address. | def test_findservice_civic_address(self):
xml = """
<findService xmlns="urn:ietf:params:xml:ns:lost1" serviceBoundary="reference">
<location id="ce152f4b-2ade-4e37-9741-b6649e2d87a6" profile="civic">
<civ:civicAddress xmlns:civ="urn:ietf:params:xml:ns:pidf:geopri... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def test_client_address_retrieve(self):\n pass",
"def test_ipam_services_read(self):\n pass",
"def test_get_service_string(self):\n pass",
"def test_get_virtual_service(self):\n pass",
"def testParse(self):\n services = self._getServices()",
"def test_ipam_services_list... | [
"0.64207476",
"0.62982064",
"0.62926865",
"0.62176013",
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"0.5928941",
"0.5896843",
"0.58331347",
"0.57547104",
"0.5736013",
"0.56428236",
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"0.5606168",
"0.55707866",
"0.5561389",
"0.5544311",
"0.55386513",
"0.5505321",
"0.545... | 0.7775548 | 0 |
Compare tone with OpenSMILE returns 0 score with error message if error occured | def comparePhoneticSimilarity(audioFile, featureFile, verbose=False, profile=False):
if (profile): start = time.time()
assert(".wav" in audioFile), "Expected .wav as audioFile"
configFile = 'databuilder/configs/prosodyShs.conf'
error = ""
if not (os.path.exists(configFile) and os.path.exists(audioFi... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def no_match():\n S1=Spectrum.Spectrum()\n S1.add_peak(50.7,234)\n S1.add_peak(54.6,585)\n S1.add_peak(60.7,773)\n S1.add_peak(65.6,387)\n S1.add_peak(87.7,546)\n S1.add_peak(104.6,598)\n S1.pep_mass=100\n S1.euclidean_scale()\n\n S2=Spectrum.Spectrum()\n S2.add_peak(50.2,234)\n ... | [
"0.601301",
"0.5996349",
"0.597326",
"0.59076625",
"0.5871764",
"0.5788689",
"0.5727182",
"0.56832933",
"0.5633397",
"0.56301457",
"0.5597745",
"0.5586412",
"0.5571524",
"0.5533426",
"0.5515297",
"0.55130965",
"0.5483196",
"0.5480128",
"0.5478033",
"0.5466535",
"0.5452381",
... | 0.51855856 | 46 |
Returns the dialogueIDth caption from vttFile | def getCaptionFromVTTcaptionFile(vttFile, dialogueID):
import webvtt
return webvtt.read(vttFile)[dialogueID].text | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def caption(self):\n return self._caption",
"def get_caption(self):\n try:\n return self.canvas.getID()\n except (TypeError, AttributeError):\n return self.id",
"def __load_dialogue_ids(self, filename):\n with open(filename, \"r\") as file:\n return ... | [
"0.59000456",
"0.58283216",
"0.5773122",
"0.55387735",
"0.54730004",
"0.54553735",
"0.53017414",
"0.52924526",
"0.52771646",
"0.5201588",
"0.5136322",
"0.51156497",
"0.51120484",
"0.50966525",
"0.5068463",
"0.5060997",
"0.50441873",
"0.50228816",
"0.49699327",
"0.49609575",
"... | 0.8716171 | 0 |
Requests contentDB for data using urllib | def getProcessedFromContentDB(netflixWatchID, dialogueID, profile=False):
if (profile): start = time.time()
featureFileURL = ''
emotion = ''
originalCaption = '' # dialogueID-th dialogue from captionFile
# construct json
reqdict = {
"netflixWatchID" : netflixWatchID,
"dialogueID... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def fetch():\n req_data= request.get_json()\n \n ## ddb uses text files, using this as to eat my own dogfoor and improve\n ## no service sql client. No daemon, low cpu.\n\n\n e=load_db()\n try:\n res=e.query(req_data['query'])\n \n serialized = jsonpickle.encode( res,\n ... | [
"0.5862957",
"0.57975626",
"0.5705349",
"0.56556296",
"0.5587389",
"0.5567929",
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"0.55234325",
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"0.53842735",
"0.53804666",
"0.53761894",
"0.5364374",
"0.5359499",
"0.5359499",
"0.5359... | 0.0 | -1 |
returns True (if same emotion) | def compareEmotionSimilarity(audioFile, emotion, emoPredictor, verbose=False, profile=False):
error = ""
if (profile): start = time.time()
# from speech_to_emotion.emotion_classifier_nn import livePredictions
# emoPredictor = livePredictions(path='speech_to_emotion/Emotion_Voice_Detection_Model.h5', fil... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def is_equivalence(self) -> bool:",
"def is_duplicate(self, other):\n if self.att != other.att or self.pol != other.pol:\n return False\n similarity = F.cosine_similarity(self.emb.unsqueeze(0),\n other.emb.unsqueeze(0))\n return similarity >... | [
"0.66043097",
"0.6126945",
"0.5980369",
"0.5870635",
"0.5852156",
"0.58448535",
"0.5837227",
"0.5769008",
"0.5768744",
"0.57412714",
"0.5719944",
"0.5682366",
"0.5676539",
"0.56701696",
"0.56568533",
"0.56337667",
"0.5630597",
"0.556876",
"0.5558811",
"0.55464154",
"0.5519768... | 0.62601924 | 1 |
Convert audioFile to text and compares against originalCaption string Returns 0 if an error occured | def compareLyricalSimilarity(userTranscript, originalCaption, verbose=False, profile=False):
error = ""
if (profile): start = time.time()
# cmp = compareToDialogue(audioFile, originalCaption, verbose=verbose)
cmp = similar(userTranscript, originalCaption)
if (profile):
end = time.time()
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def convert_text(self):\n if msg.askyesno(message=\"Do you want to save audio file?\"):\n text = self.textbox.get(\"1.0\", tk.END)\n self.file.text = text\n files = [('Sound', '*.mp3')]\n mp3_file = asksaveasfile(title=\"Save your mp3 file\", filetypes=files, defa... | [
"0.64471585",
"0.61322695",
"0.60957986",
"0.6042997",
"0.5996542",
"0.5938845",
"0.57494444",
"0.5700308",
"0.5667412",
"0.5630515",
"0.56009644",
"0.5593606",
"0.5548273",
"0.5531259",
"0.5517921",
"0.5501903",
"0.5478674",
"0.5471566",
"0.54637545",
"0.54493004",
"0.543375... | 0.5649577 | 9 |
Log any errors / updates worth consideration to `logFile.txt` | def _logToFile(logsLst, resultJSON=None, logFile="logFile.txt"):
if not LOGGING_TO_FILE: return
with open(logFile, "a+") as file:
message = "\n".join(logsLst)
file.write("------------------Logging--------------------\n")
file.write(str(datetime.datetime.now()) + "\n")
# file.writ... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def log(self, txt):\n if self.logfile:\n self.logfile.write(txt)",
"def log(self, *lst):\n self.print2file(self.logfile, self.debug, True, *lst)\n if 'Error' in '\\n'.join([str(x) for x in lst]):\n self.caught_error = '\\n'.join([str(x) for x in lst])",
"def logsave(self):\n... | [
"0.68882483",
"0.6652503",
"0.6550226",
"0.6489648",
"0.64801645",
"0.6474686",
"0.6437777",
"0.6369502",
"0.6365998",
"0.6261356",
"0.62492037",
"0.62482655",
"0.6248004",
"0.62204903",
"0.62183195",
"0.62150043",
"0.62097436",
"0.62011856",
"0.6189739",
"0.61854243",
"0.616... | 0.58193773 | 65 |
Perform comparison $ python compareAudio.py audioFile(.webm), netflixWatchID(str), dialogueID(number), gameID(str) | def performThreeComparisons(netflixWatchID, dialogueID, audioFile, gameID, userTranscript, emoPredictor, verbose=False, profile=False, logErrors=True):
logFile = "logFile.txt"
errorsLst = []
resultDICT = {"gameID" : gameID, "dialogueID" : dialogueID, "error" : "", "success" : True}
overallscore = 0.0
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def compare(file1, file2):\n process = subprocess.Popen([PBWT_BIN, 'compare', file1, file2],\n stdout=subprocess.PIPE)\n process_results(str(process.communicate()[0]))",
"def same_file(wavecar1, wavecar2, wavecar3):\n same = False\n if (filecmp.cmp(wavecar1, wavecar2, sh... | [
"0.5997795",
"0.5918491",
"0.5860667",
"0.5591653",
"0.5559069",
"0.5415558",
"0.537906",
"0.53485507",
"0.53323954",
"0.5326343",
"0.5321445",
"0.52875805",
"0.526904",
"0.5242733",
"0.5236806",
"0.52278113",
"0.5217617",
"0.5208304",
"0.51605356",
"0.5155278",
"0.51301885",... | 0.6617059 | 0 |
Build agent's function approximators | def build_graph(self):
pass | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def make_function(self):\n result = {}\n x0 = 0\n for i, x in enumerate(self.step_vals):\n vals_range = xrange(x0, x)\n for k in vals_range:\n result[k] = i\n x0 = x\n self.function = result",
"def _build_expression(self):\n # Get... | [
"0.6071946",
"0.58984506",
"0.58775413",
"0.58521664",
"0.5732764",
"0.5710692",
"0.5704847",
"0.5697908",
"0.5696569",
"0.5598104",
"0.5588668",
"0.5572613",
"0.55401134",
"0.5528618",
"0.55070966",
"0.5493993",
"0.54565287",
"0.54370886",
"0.5425819",
"0.54256546",
"0.54068... | 0.0 | -1 |
Build graph for the logging procedure | def build_logger(self):
pass | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _build_graph(self):\n pass",
"def build_graph(self):\n pass",
"def build_graph(self):\n raise NotImplementedError",
"def gen_graph(self):",
"def log_init(self):\n\t\tlayer_id = \"Data\"\n\t\tself.graph[layer_id] = layer_id\n\t\tself.bottoms[layer_id] = None\n\t\tself.output_shape[l... | [
"0.716409",
"0.70692104",
"0.65841585",
"0.65536815",
"0.6370009",
"0.63324153",
"0.6261546",
"0.6247608",
"0.6217703",
"0.6187986",
"0.61408377",
"0.6097877",
"0.6089329",
"0.6065247",
"0.6061484",
"0.60463005",
"0.60370535",
"0.6012218",
"0.596317",
"0.59546924",
"0.5934546... | 0.6071812 | 13 |
Initialize the variables of the model | def initialize_model(self):
pass | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def initialisation(self):\n self.create_variables()\n self.create_placeholders()\n self.build_model()\n self.reset_lr(None, True)\n self.build_loss()\n self.initialised = True",
"def initialize_variables(self):\n self.sess.run(self.init)",
"def init_model(self):... | [
"0.79028624",
"0.76701003",
"0.7357904",
"0.7299997",
"0.7258896",
"0.7204345",
"0.7200145",
"0.7173436",
"0.7050764",
"0.7028793",
"0.7026541",
"0.6996758",
"0.6944324",
"0.6934423",
"0.6934076",
"0.6934076",
"0.6931822",
"0.6903529",
"0.68874097",
"0.68786246",
"0.6864961",... | 0.7493104 | 2 |
Train the neural network with the trajectories | def train(self):
pass | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def trainNet():",
"def train(self):\r\n raw_dataset = pd.read_csv(self.datafile, sep = ',', header = 0,\r\n na_values = '?', comment = '\\t',\r\n skipinitialspace = True)\r\n\r\n dataset = raw_dataset.copy()\r\n dataset.tail()... | [
"0.84238064",
"0.78679293",
"0.76970464",
"0.76484424",
"0.7647099",
"0.75862604",
"0.7565016",
"0.7514085",
"0.7514085",
"0.7475018",
"0.7415142",
"0.7370216",
"0.7369993",
"0.7343511",
"0.73250616",
"0.7298394",
"0.72868323",
"0.7273052",
"0.7260297",
"0.72523785",
"0.72279... | 0.709416 | 41 |
Evaluate the trained network with simulations (This is seperated from simulation since exploration is not necessary) | def play(self):
pass | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def evaluate():\n\tmodel.eval()\n\tstddev = 1 # And mean=0\n\tfor batch_idx, (data, _) in enumerate(syn_test_loader):\n\t\tdata = data.cuda()\n\t\tif batch_idx == 0:\n\t\t\tnoise = torch.autograd.Variable(torch.randn(batch_size, bottleneck).cuda() * stddev)\n\t\t\tsample_representation(\"orig_nat\", data, noise)\... | [
"0.7049329",
"0.6991395",
"0.6920516",
"0.68952745",
"0.67432266",
"0.67410535",
"0.6698653",
"0.6678496",
"0.6621551",
"0.66032165",
"0.6575123",
"0.6570769",
"0.6531601",
"0.650734",
"0.6446003",
"0.643147",
"0.6360606",
"0.63559276",
"0.63241136",
"0.63096213",
"0.6277143"... | 0.0 | -1 |
Init constructor of HID. | def __init__(self, vendor_id: int = 0x2C97, hid_path: Optional[bytes] = None) -> None:
if hid is None:
raise ImportError("hidapi is not installed, try: "
"'pip install ledgercomm[hid]'")
self.device = hid.device()
self.path: Optional[bytes] = hid_path
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def __init__(self, device_handle):\n\n self.device_handle = device_handle",
"def __init__(self):\n self._device_info = None",
"def __init__(self, Interface=\"USB\", Number=DRIVER_NUM):\n self.bib = CDLL(\"delib64\") # this will NOT fail...\n self.interface = Interface\n self.... | [
"0.6862138",
"0.6743291",
"0.67000437",
"0.66972363",
"0.6555643",
"0.6550871",
"0.65466005",
"0.65423924",
"0.6522224",
"0.6498889",
"0.64774984",
"0.64688903",
"0.64580566",
"0.6452935",
"0.6445795",
"0.6438601",
"0.6433724",
"0.64092666",
"0.6399368",
"0.63911164",
"0.6384... | 0.7098126 | 0 |
Open connection to the HID device. Returns None | def open(self) -> None:
if not self.__opened:
if self.path is None:
self.path = HID.enumerate_devices(self.vendor_id)[0]
self.device.open_path(self.path)
self.device.set_nonblocking(True)
self.__opened = True | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def init():\n try:\n h = hid.device()\n h.open(USB_VID, USB_PID)\n h.set_nonblocking(1)\n except IOError as ex:\n print('ERROR: could not establish connection to device')\n print(ex)\n return None\n return h",
"def performOpen(self, options={}):\n self._l... | [
"0.76332617",
"0.6955843",
"0.69416445",
"0.68056446",
"0.6553122",
"0.65466124",
"0.6523534",
"0.6514852",
"0.6506754",
"0.64412344",
"0.6438013",
"0.6406292",
"0.6384707",
"0.63268006",
"0.62957555",
"0.6287522",
"0.6280608",
"0.6214638",
"0.62089825",
"0.6192919",
"0.61830... | 0.75960964 | 1 |
Enumerate HID devices to find Nano S/X. | def enumerate_devices(vendor_id: int = 0x2C97) -> List[bytes]:
devices: List[bytes] = []
for hid_device in hid.enumerate(vendor_id, 0):
if (hid_device.get("interface_number") == 0 or
# MacOS specific
hid_device.get("usage_page") == 0xffa0):
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def enumerate_devices():\n devices = list(\n map(XInputJoystick, list(range(XInputJoystick.max_devices))))\n return [device for device in devices if device.is_connected()]",
"def listUsbHidDevices():\n \n for d in hid.enumerate():\n keys = list(d.keys())\n keys.sort()... | [
"0.669791",
"0.65644383",
"0.62645656",
"0.62418604",
"0.62051696",
"0.6056922",
"0.5982882",
"0.5976185",
"0.58864295",
"0.58860993",
"0.5870821",
"0.5814101",
"0.57680804",
"0.5751848",
"0.572239",
"0.57181394",
"0.56890416",
"0.5645336",
"0.5617422",
"0.5617189",
"0.561115... | 0.60071063 | 6 |
Send `data` through HID device `self.device`. | def send(self, data: bytes) -> int:
if not data:
raise Exception("Can't send empty data!")
LOG.debug("=> %s", data.hex())
data = int.to_bytes(len(data), 2, byteorder="big") + data
offset: int = 0
seq_idx: int = 0
length: int = 0
while offset < len(d... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def Send(self, data):\n # TODO(josephsih): should have a method to check the connection status.\n # Currently, once RN-42 is connected to a remote host, all characters\n # except chr(0) transmitted through the serial port are interpreted\n # as characters to send to the remote host.\n logging.debug(... | [
"0.8114699",
"0.74745846",
"0.72835046",
"0.7225305",
"0.7079121",
"0.69480795",
"0.686888",
"0.68374884",
"0.6755113",
"0.6726118",
"0.66238755",
"0.66056156",
"0.6604241",
"0.6583607",
"0.6567921",
"0.65530527",
"0.65352786",
"0.64986926",
"0.6492017",
"0.64563245",
"0.6445... | 0.6496641 | 18 |
Receive data through HID device `self.device`. Blocking IO. Returns Tuple[int, bytes] A pair (sw, rdata) containing the status word and response data. | def recv(self) -> Tuple[int, bytes]:
seq_idx: int = 0
self.device.set_nonblocking(False)
data_chunk: bytes = bytes(self.device.read(64 + 1))
self.device.set_nonblocking(True)
assert data_chunk[:2] == b"\x01\x01"
assert data_chunk[2] == 5
assert data_chunk[3:5] ==... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def receive_data(self):\n chunks = []\n bytes_recd = 0\n while bytes_recd < 8:\n #I'm reading my data in byte chunks\n try:\n chunk = self.sockfd.recv(min(8 - bytes_recd, 4))\n chunks.append(chunk)\n bytes_recd = bytes_recd + l... | [
"0.65270954",
"0.6320771",
"0.62461853",
"0.6179725",
"0.616269",
"0.60660446",
"0.6049839",
"0.59986186",
"0.59340626",
"0.59284836",
"0.59060866",
"0.5892542",
"0.5891193",
"0.5879894",
"0.5854489",
"0.58111537",
"0.5801802",
"0.579307",
"0.57675236",
"0.5746004",
"0.572689... | 0.67547876 | 0 |
Exchange (send + receive) with `self.device`. | def exchange(self, data: bytes) -> Tuple[int, bytes]:
self.send(data)
return self.recv() # blocking IO | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def _ExchangeMessage( self, rx_bytes ) :\r\n \r\n if ( self.handle == None ) : \r\n self._open_device()\r\n if ( self.handle == None ) :\r\n self.Raise( \"USB device not found\" ) \r\n \r\n tx_bytes = self.hand... | [
"0.6672568",
"0.6610441",
"0.64421993",
"0.60326284",
"0.6002608",
"0.59985787",
"0.5998004",
"0.59948575",
"0.59585065",
"0.5938672",
"0.5900946",
"0.5900208",
"0.5843479",
"0.5816089",
"0.5791394",
"0.57508886",
"0.57472557",
"0.57411444",
"0.57379746",
"0.5736334",
"0.5731... | 0.60813767 | 3 |
Close connection to HID device `self.device`. Returns None | def close(self) -> None:
if self.__opened:
self.device.close()
self.__opened = False | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def close(self):\n self.device.close()",
"def close(self):\n self.device.disconnect()",
"def close_device(self):\n\t\t\n\t\t# reset DigitalIO instrument\n\t\tdwf.FDwfDigitalIOReset()\n\n\t\t#reset DigitalIn instrument\n\t\tdwf.FDwfDigitalInReset(ad_utils.interface_handler)\n\n\t\tdwf.FDwfDeviceCl... | [
"0.7689541",
"0.76033694",
"0.7488144",
"0.7346484",
"0.7259698",
"0.7257906",
"0.7236381",
"0.71463615",
"0.7126705",
"0.7120404",
"0.7090371",
"0.6978015",
"0.6959391",
"0.6923237",
"0.69071007",
"0.68967503",
"0.68130153",
"0.6735064",
"0.6725293",
"0.672066",
"0.665815",
... | 0.7241656 | 6 |
Search through the provided list of devices to find the one with the matching usage_page and usage. | def find_device(devices, *, usage_page, usage):
if hasattr(devices, "send_report"):
devices = [devices]
for device in devices:
if (
device.usage_page == usage_page
and device.usage == usage
and hasattr(device, "send_report")
):
return devic... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def find_devices (devicelist):\n vprint(\"\\nFind known devices:\")\n for device in devicelist:\n if find_device(device) is not None :\n vprint(\"\\tFound :\", device)\n else:\n vprint(\"\\tNOT found:\", device )\n vprint(\"..........\") \n return",
"def ... | [
"0.6269344",
"0.5997133",
"0.59589404",
"0.588711",
"0.5793125",
"0.57546246",
"0.568376",
"0.56786346",
"0.55943453",
"0.550942",
"0.55043346",
"0.54662585",
"0.54382575",
"0.5410512",
"0.54044867",
"0.5389828",
"0.5379705",
"0.5365242",
"0.53301144",
"0.5328609",
"0.5327337... | 0.7825975 | 0 |
Suffix tree contains empty string at root node. | def __init__(self):
Tree.__init__(self, "") | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def hasSuffix(self, s):\n node, off = self.followPath(s)\n if node is None:\n return False # fell off the tree\n if off is None:\n # finished on top of a node\n return '$' in node.out\n else:\n # finished at offset 'off' within an edge leading... | [
"0.6829639",
"0.6604397",
"0.6604397",
"0.653885",
"0.6506044",
"0.64041114",
"0.620266",
"0.6085274",
"0.6077728",
"0.6068",
"0.60575527",
"0.605403",
"0.60514796",
"0.6047121",
"0.60298663",
"0.60246706",
"0.6022461",
"0.60204464",
"0.59820855",
"0.5976126",
"0.59737945",
... | 0.0 | -1 |
Insert prefix into current tree. | def insert_suffix(self, prefix, idx):
parent_pos = self.path_to_matching_prefix(prefix)[-1]
has_inserted = False
for child_pos in self.children(parent_pos):
if child_pos.element()._label[0] == prefix[0]:
# Intermediate node is added between parent and child.
... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def insert(self, prefix: str):\n leaf = self.root\n for level in range(len(prefix)):\n letter = prefix[level]\n\n # if current character is not present\n if letter not in leaf.children:\n leaf.children[letter] = self.get_node()\n leaf = leaf.... | [
"0.824454",
"0.6702643",
"0.6659329",
"0.65441847",
"0.65267813",
"0.6520331",
"0.64193934",
"0.6335701",
"0.6227362",
"0.6089401",
"0.6089401",
"0.60877794",
"0.60377556",
"0.6022887",
"0.6006063",
"0.59953064",
"0.5995097",
"0.59828734",
"0.5922838",
"0.59098965",
"0.590850... | 0.5517972 | 76 |
A O(n^2) algorithm to construct a suffix tree for string with length n. Creates a new tree | def naive_construction(self, string):
if not self.is_empty():
Tree.__init__(self, self._SuffixNode(None, -1))
# ensure string ends with '$' character (termination.)
if not string.endswith('$'):
string += '$'
# Insert all prefixes.
for i in range(len(stri... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def build_suffix_tree(text):\n tree = dict()\n tree[0] = {}\n head_node = 1\n\n # 例えば、ABC$ という文字列の場合、ABC$, BC$, C$, $ の順に処理\n for p in range(len(text)):\n suffix = text[p:]\n current_node = 0\n\n # サブ文字列の先頭から一文字ずつ処理\n i = 0\n while i < len(suffix):\n c = suffix[i]\n cur_str = suffix[i... | [
"0.76870435",
"0.6643681",
"0.6568005",
"0.65335166",
"0.62937254",
"0.614511",
"0.61273575",
"0.598203",
"0.5965032",
"0.5751854",
"0.56694895",
"0.5659555",
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"0.55916727",
"0.55526924",
"0.55391175",
"0.5462947",
"0.54626524",
"0.5446805",
"0.54132... | 0.6463355 | 4 |
Calculate the great circle distance between two points on the earth (specified in decimal degrees) by default, between the center of the earh and anypoint | def haversine( coordsA, coordsB = {'lat': 0, 'long': 0} ) -> int:
# convert decimal degrees to radians
if type( coordsA ) == dict:
[lat1, lon1] = [coordsA['lat'], coordsA['long']]
elif type( coordsA ) == str:
[lat1, lon1] = coordsA.split(",")
elif type( coordsA ) == list:
[lat1,... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def great_circle(lat_1, long_1, lat_2, long_2):\n long_1 = m.radians(long_1)\n lat_1 = m.radians(lat_1)\n long_2 = m.radians(long_2)\n lat_2 = m.radians(lat_2)\n\n d = 2 * 6367.45 * m.asin(\n m.sqrt(haversine(lat_2 - lat_1)\n + m.cos(lat_1)*m.cos(lat_2) *\n haversine(long... | [
"0.76905084",
"0.72814983",
"0.7257619",
"0.7141139",
"0.71320075",
"0.6970445",
"0.69449705",
"0.6929295",
"0.6892779",
"0.6889518",
"0.68526417",
"0.68168545",
"0.6815274",
"0.68049467",
"0.67489856",
"0.6743163",
"0.67333126",
"0.6712626",
"0.66993904",
"0.66911364",
"0.66... | 0.0 | -1 |
function to convert contribs collection items to edges ones edge doc {_id, name_1, name_2, tags [{name, urls[]}]} =========================================================== if src in srcs then skip if name_1 and name_2 not found then insert new doc if tag.name not found then insert new tag if tag.url not found then in... | def contribs2edges():
client = mongo.MongoClient(config["MONGO_URI"])
db = client.links
db.edges.remove()
edges = dict()
for contrib in db.contribs.find():
for item in contrib["data"]:
id = u"{} {}".format(item["name_1"], item["name_2"]).replace(" ", "_")
edge... | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def construct_edge_list(cong):\n usr_to_src = []\n list_to_exclude = [\n 'twitter',\n 'youtu',\n 'fllwrs',\n 'unfollowspy',\n 'livetv',\n 'pscp',\n 'live',\n 'ln.is',\n 'tinyurl',\n 'facebook',\n 'bit.ly',\n 'goo.gl',\n ... | [
"0.5155826",
"0.5116931",
"0.502896",
"0.48469794",
"0.4804909",
"0.47966293",
"0.47729138",
"0.47717592",
"0.47354752",
"0.4730931",
"0.47188097",
"0.47089943",
"0.4695777",
"0.46924073",
"0.4670455",
"0.4657417",
"0.46162593",
"0.46076247",
"0.45932865",
"0.45638296",
"0.45... | 0.7434294 | 0 |
Bootstrap resample an array_like | def bootstrap_resample(self, X, n=None):
if n == None:
n = len(X)
resample_i = np.floor(np.random.rand(n)*len(X)).astype(int)
X_resample = X.iloc[resample_i, :]
return X_resample | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def bootstrap_resample(X, n=None):\r\n if n == None:\r\n n = len(X)\r\n \r\n resample_i = np.floor(np.random.rand(n)*len(X)).astype(int)\r\n X_resample = X[resample_i]\r\n return X_resample",
"def bootstrap_resample(X, n=None):\r\n if n == None:\r\n n = len(X)\r\n\r\n resam... | [
"0.7452041",
"0.7263313",
"0.71732163",
"0.6405318",
"0.63510484",
"0.63177764",
"0.6304294",
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"0.62305534",
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"0.61665726",
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"0.60844344",
"0.6076023",
"0.60429317",
"0.6033939",
"0.6027019",
"0.60022396",
"0.595... | 0.7123745 | 3 |
Emit overrides the abstract logging.Handler logRecord emit method records the log | def emit(self, record):
print(record.__dict__) | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def emit(self, record):\n try:\n msg = self.format(record)\n log_level = record.levelno\n self.write_log(msg, log_level)\n except Exception:\n self.handleError(record)",
"def emit(self, record):\n try:\n msg = self.format(record)\n ... | [
"0.81659305",
"0.80186856",
"0.7616163",
"0.753549",
"0.74377483",
"0.74377483",
"0.7402443",
"0.7399078",
"0.73509914",
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"0.71083254",
"0.7105942",
"0.7044156",
"0.7007883",
"0.6835894",
"0.6824077",
"0.68092453"... | 0.7213005 | 11 |
Execute executes the specified SQL query (might be in a transaction context, if Query.transaction_id is set). | def Execute(self, request, context):
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def execute_statement(self, statement):\n context = self.__context\n session = context.session()\n with session as connection:\n query_result = connection.execute(statement)\n\n return query_result",
"def execute_query(self, query):\n with self.db_engine.connect() as... | [
"0.7590123",
"0.7247031",
"0.7169071",
"0.7088199",
"0.70669395",
"0.7059763",
"0.70256394",
"0.698615",
"0.6926175",
"0.6868136",
"0.6859177",
"0.6851325",
"0.6851325",
"0.6835212",
"0.6789023",
"0.6758888",
"0.6758811",
"0.67554",
"0.6754189",
"0.6751403",
"0.6685197",
"0... | 0.0 | -1 |
ExecuteBatch executes a list of queries, and returns the result for each query. | def ExecuteBatch(self, request, context):
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def batch_execute(self, sql_list):\n with self.connection.cursor() as dbc:\n responses = []\n for sql in sql_list:\n dbc.execute(sql)\n responses.append(dbc.fetchall())\n return responses",
"def execute_many(self, sql, args=None):\r\n a... | [
"0.78971225",
"0.7297311",
"0.7183084",
"0.6912823",
"0.68590426",
"0.68088025",
"0.67924225",
"0.6742135",
"0.67240494",
"0.6717273",
"0.6667804",
"0.6663774",
"0.6625337",
"0.65395296",
"0.6484512",
"0.64706194",
"0.646509",
"0.6462636",
"0.64610827",
"0.6405896",
"0.639893... | 0.58510387 | 56 |
StreamExecute executes a streaming query. Use this method if the query returns a large number of rows. The first QueryResult will contain the Fields, subsequent QueryResult messages will contain the rows. | def StreamExecute(self, request, context):
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def execute(self, query):\n with self.conn.cursor() as cur:\n # Execute the query\n try:\n cur.execute(query)\n except Exception as exc:\n print(\"Unable to execute query. Error was {0}\".format(str(exc)))\n exit()\n ro... | [
"0.61123246",
"0.6092492",
"0.5998644",
"0.5964264",
"0.5893205",
"0.587983",
"0.5879137",
"0.5836698",
"0.5732992",
"0.5697595",
"0.5687175",
"0.5622964",
"0.5613709",
"0.55874527",
"0.5575201",
"0.5553297",
"0.5541185",
"0.55186146",
"0.5512491",
"0.54958117",
"0.548273",
... | 0.0 | -1 |
Prepare preares a transaction. | def Prepare(self, request, context):
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def prepare(self) -> None:\n trans = self._transaction\n if trans is None:\n trans = self._autobegin_t()\n\n trans.prepare()",
"def prepare_for_commit(self):",
"def prepare(self):\n pass",
"def prepare(self):\n pass",
"def prepare(self):\n pass",
"def ... | [
"0.8410679",
"0.7001432",
"0.6574274",
"0.6574274",
"0.6574274",
"0.64655685",
"0.63754845",
"0.6311319",
"0.6223688",
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"0.61802596",
"0.61802596",
"0.61754274",
"0.61486727",
"0.6050652",
"0.60368794",
"0.6... | 0.0 | -1 |
CommitPrepared commits a prepared transaction. | def CommitPrepared(self, request, context):
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def CommitPrepared(self, request, context):\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)",
"def CommitPrepared(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\n raise NotImplementedError()",
"def post_prepared_commit(self, key, prepared):\n docs = ... | [
"0.69002336",
"0.68232703",
"0.677715",
"0.567485",
"0.5660226",
"0.5630717",
"0.5601845",
"0.55818135",
"0.55588466",
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"0.52796453",
"0.5208319",
"0.5195262",
"0.5135492",
"0.5135492",
"0.50988245",
"0.5068812"... | 0.62075883 | 3 |
RollbackPrepared rolls back a prepared transaction. | def RollbackPrepared(self, request, context):
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def RollbackPrepared(self, request, context):\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)",
"def RollbackPrepared(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\n raise NotImplementedError()",
"def rollback(self):\n self._connection.execute_nonquery(\"... | [
"0.65784436",
"0.6450222",
"0.6257658",
"0.5932248",
"0.5872741",
"0.5795709",
"0.5696239",
"0.5617441",
"0.55968213",
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"0.5419659",
"0.5336303",
"0.5319498",
"0.5277183",
"0.52744156",
"0.52693737",
"0.5252406... | 0.58695024 | 6 |
CreateTransaction creates the metadata for a 2pc transaction. | def CreateTransaction(self, request, context):
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def CreateTransaction(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\n raise NotImplementedError()",
"def CreateTransaction(self, request, context):\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)",
"def create_transaction(self, receiver, amount, comment=\"\"):\n... | [
"0.7027417",
"0.65196544",
"0.64316773",
"0.62087923",
"0.60003686",
"0.59858954",
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"0.5629838",
"0.56017053",
"0.55468065",
"0.55460596",
"0.5519897",
"0.5475936",
"0.54... | 0.62451214 | 3 |
StartCommit initiates a commit for a 2pc transaction. | def StartCommit(self, request, context):
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def StartCommit(self, request, context):\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)",
"def StartCommit(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\n raise NotImplementedError()",
"def begin_commit(self, _stacklevel=1):\n if self.commit_phase:\n ... | [
"0.69779134",
"0.67022675",
"0.6374768",
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"0.52956843",
"0.52474976",
"0.5242918",
"0.5212305",
"0.5158825",
"0.5135... | 0.6510619 | 2 |
SetRollback marks the 2pc transaction for rollback. | def SetRollback(self, request, context):
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def SetRollback(self, request, context):\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)",
"def SetRollback(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\n raise NotImplementedError()",
"def rollback(self):\n self._rollback = True",
"def rollback(self, ... | [
"0.70415974",
"0.67804295",
"0.6566904",
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"0.5480133",
"0.54312456",
"0.5368917",
"0.5368417",
"0.5331688",
"0.5325234... | 0.6231145 | 5 |
ConcludeTransaction marks the 2pc transaction as resolved. | def ConcludeTransaction(self, request, context):
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def ConcludeTransaction(self, request, context):\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)",
"def ConcludeTransaction(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\n raise NotImplementedError()",
"def tpc_finish(self, transaction):\n raise NotImplem... | [
"0.67960286",
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"0.60833055",
"0.53630143",
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"0.5006666",
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"0.47558016",
"0.47272316",
"0.47141683",
"0.46993113",
"0.4675617",
"0.4... | 0.6253946 | 2 |
ReadTransaction returns the 2pc transaction info. | def ReadTransaction(self, request, context):
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def ReadTransaction(self, request, context):\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)",
"def ReadTransaction(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\n raise NotImplementedError()",
"def _read_transaction(self, tx_fun, **kwargs):\n # Wrapper f... | [
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"0.67596567",
"0.6342749",
"0.566911",
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"0.56372833",
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"0.5509677",
"0.544398",
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"0.5383335",
"0.53821176",
"0.5373266",
"0.5349258",
"0.5288624",
"0.5255775",
"0.524392... | 0.62335604 | 3 |
BeginExecute executes a begin and the specified SQL query. | def BeginExecute(self, request, context):
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def begin(self):\n self._in_transaction = True\n self.execute(\"BEGIN\")",
"def start_transaction_sql(self):\n return \"BEGIN TRANSACTION\"",
"def start_transaction(self):\n self._connection.execute_nonquery(\"sql\", \"START TRANSACTION\", True)",
"def startTxn(self,msg=\"\"):\n\t... | [
"0.6814344",
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"0.5670721",
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"0.54457515",
"0.5431761",
"0.5396275",
"0.5384897",
"0.53836185",
"0.53566... | 0.0 | -1 |
BeginExecuteBatch executes a begin and a list of queries. | def BeginExecuteBatch(self, request, context):
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def BeginExecuteBatch(self, request, context):\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)",
"def BeginExecuteBatch(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\n raise NotImplementedError()",
"def insert_many_execute(self) -> None:\n self.connection... | [
"0.68904305",
"0.67491",
"0.6390388",
"0.59859765",
"0.59389424",
"0.5861362",
"0.57830834",
"0.57773644",
"0.5732274",
"0.5667679",
"0.5549289",
"0.5544553",
"0.55342305",
"0.5516681",
"0.5435256",
"0.536045",
"0.5342036",
"0.53406656",
"0.5280119",
"0.52774423",
"0.5263082"... | 0.6208538 | 4 |
MessageStream streams messages from a message table. | def MessageStream(self, request, context):
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def message_table(message):\r\n table = Table(['property', 'value'])\r\n table.align['property'] = 'r'\r\n table.align['value'] = 'l'\r\n\r\n table.add_row(['id', message['id']])\r\n table.add_row(['initial_entry_time', message['initial_entry_time']])\r\n table.add_row(['visibility_delay', messag... | [
"0.5896682",
"0.5609692",
"0.56041276",
"0.5388515",
"0.53177005",
"0.52457964",
"0.5238697",
"0.52366567",
"0.52348894",
"0.5195175",
"0.5176002",
"0.5151693",
"0.51319724",
"0.51315767",
"0.5099497",
"0.5045646",
"0.50385904",
"0.50096095",
"0.5003209",
"0.49966025",
"0.493... | 0.47767812 | 47 |
MessageAck acks messages for a table. | def MessageAck(self, request, context):
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def MessageAck(self, request, context):\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)",
"def MessageAck(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\n raise NotImplementedError()",
"def ack(self, tup_id):\n pass",
"async def ack(self, offset: int):",
"... | [
"0.64959633",
"0.64412004",
"0.62590575",
"0.6091653",
"0.5954156",
"0.58493274",
"0.5831551",
"0.57382613",
"0.57264817",
"0.56786704",
"0.5646465",
"0.5615886",
"0.56138206",
"0.5597098",
"0.54789007",
"0.5456883",
"0.5329339",
"0.53248435",
"0.53145635",
"0.5300762",
"0.52... | 0.6130686 | 4 |
SplitQuery is the API to facilitate MapReducetype iterations over large data sets (like full table dumps). | def SplitQuery(self, request, context):
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def SplitQuery(self, request, context):\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)",
"def SplitQuery(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\n raise NotImplementedError()",
"def get_splits(datastore, query, num_splits, partition=None):\n\n # Validate... | [
"0.69221485",
"0.65455127",
"0.6398275",
"0.5844143",
"0.58412147",
"0.5747338",
"0.5668508",
"0.5646011",
"0.56448406",
"0.5368807",
"0.53658277",
"0.53620774",
"0.5309061",
"0.5297343",
"0.5291058",
"0.52775466",
"0.5261138",
"0.52405804",
"0.5234456",
"0.519282",
"0.516202... | 0.6370883 | 4 |
StreamHealth runs a streaming RPC to the tablet, that returns the current health of the tablet on a regular basis. | def StreamHealth(self, request, context):
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!') | {
"objective": {
"self": [],
"paired": [],
"triplet": [
[
"query",
"document",
"negatives"
]
]
}
} | [
"def StreamHealth(self, request, timeout, metadata=None, with_call=False, protocol_options=None):\n raise NotImplementedError()",
"def StreamHealth(self, request, context):\n context.code(beta_interfaces.StatusCode.UNIMPLEMENTED)",
"async def health(self):\n\n request = telemetry_pb2.SubscribeHealt... | [
"0.7608533",
"0.7594466",
"0.65876895",
"0.596237",
"0.5666134",
"0.5444123",
"0.5427727",
"0.54094017",
"0.5407425",
"0.53967756",
"0.53581214",
"0.53127843",
"0.52864975",
"0.5257775",
"0.5237875",
"0.523024",
"0.5206512",
"0.5199296",
"0.5146353",
"0.51393175",
"0.51260155... | 0.7317585 | 3 |
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