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How to use print_queries method in autotest

Best Python code snippet using autotest_python

list.py

Source:list.py

1"""2Functions to support list script.3"""4from sqlalchemy import create_engine5from sqlalchemy.orm import sessionmaker6from sqlalchemy import func7import sqlparse8from modelmeta import DataFile, DataFileVariable, Ensemble, TimeSet9# argument parser helpers10def strtobool(string):11    return string.lower() in {'true', 't', 'yes', '1'}12main_arg_names = '''13    print_queries14    count15    ensemble16    multi_variable17    multi_year_mean18    mym_concatenated19'''.split()20def print_query(title, query):21    print('--', title)22    compiled_query = str(23        query.statement.compile(compile_kwargs={'literal_binds': True})24    )25    formatted_query = sqlparse.format(26        compiled_query, reindent=True, keyword_case='upper')27    print(formatted_query)28    print()29def list_information(query, template, count=False):30    if count:31        print(query.count())32    else:33        results = query.all()34        for row in results:35            print(template.format(row=row))36def data_file_query(37        session,38        print_queries=False,39        ensemble=None,40        multi_variable=None,41        multi_year_mean=None,42        mym_concatenated=None,43):44    """45    Select DataFiles matching selection criteria46    :param session:47    :param print_queries:48    :param ensemble:49    :param multi_variable:50    :param multi_year_mean:51    :param mym_concatenated:52    :return:53    """54    query = session.query(DataFile.id)55    if ensemble:56        query = (57            query.join(DataFile.data_file_variables)58                .join(DataFileVariable.ensembles)59                .filter(Ensemble.name == ensemble)60        )61    if multi_variable is not None:62        query = (63            query.join(DataFile.data_file_variables)64                .group_by(DataFile.id)65        )66        if multi_variable:67            query = query.having(func.count(DataFileVariable.id) > 1)68        else:69            query = query.having(func.count(DataFileVariable.id) == 1)70    if multi_year_mean is not None:71        query = (72            query.join(TimeSet)73                .filter(TimeSet.multi_year_mean == multi_year_mean)74        )75    if mym_concatenated is not None:76        query = (77            query.join(TimeSet)78                .filter(TimeSet.multi_year_mean == True)79        )80        if mym_concatenated:81            query = query.filter(TimeSet.num_times.in_((5, 13, 16, 17)))82        else:83            query = query.filter(TimeSet.num_times.in_((1, 4, 12)))84    if print_queries:85        print_query('Data file query', query)86    return query87def _list_filepaths(88        session,89        print_queries=False,90        count=False,91        ensemble=None,92        multi_variable=None,93        multi_year_mean=None,94        mym_concatenated=None,95        list_ensembles = None,96):97    df_query = data_file_query(98        session,99        print_queries=print_queries,100        ensemble=ensemble,101        multi_variable=multi_variable,102        multi_year_mean=multi_year_mean,103        mym_concatenated=mym_concatenated,104    )105    if list_ensembles:106        if count:107            info_query = (108                session.query(109                    Ensemble.name.label('ensemble_name'),110                    func.count(DataFile.id).label('number')111                )112                    .filter(DataFile.id.in_(df_query))113                    .join(DataFile.data_file_variables)114                    .join(DataFileVariable.ensembles)115                    .group_by(Ensemble.name)116            )117        else:118            info_query = (119                session.query(120                    DataFile.filename,121                    func.string_agg(Ensemble.name, ',').label('ensemble_names')122                )123                    .filter(DataFile.id.in_(df_query))124                    .join(DataFile.data_file_variables)125                    .join(DataFileVariable.ensembles)126                    .group_by(DataFile.id)127            )128    else:129        info_query = df_query.add_columns(DataFile.filename)130    if print_queries:131        print_query('Info query', info_query)132    if list_ensembles:133        template = '{row.filename}\t{row.ensemble_names}'134    else:135        template = '{row.filename}'136    list_information(info_query, template, count=count)137def _list_dirpaths(138        session,139        print_queries=False,140        count=False,141        ensemble=None,142        multi_variable=None,143        multi_year_mean=None,144        mym_concatenated=None,145        depth=999,146):147    df_query = data_file_query(148        session,149        print_queries=print_queries,150        ensemble=ensemble,151        multi_variable=multi_variable,152        multi_year_mean=multi_year_mean,153        mym_concatenated=mym_concatenated,154    )155    info_query = (156        session.query(157            func.regexp_replace(158                DataFile.filename,159                r'^((/.[^/]+){{1,{}}}/).+$'.format(depth),160                r'\1'161            ).label('dir_path'),162            func.count().label('number')163        )164            .filter(DataFile.id.in_(df_query))165            .group_by('dir_path')166            .order_by('dir_path')167    )168    if print_queries:169        print_query('Info query', info_query)170    template = '{row.dir_path} ({row.number})'171    list_information(info_query, template, count=count)172def list_filepaths(args):173    arg_names = main_arg_names + '''174        list_ensembles175    '''.split()176    engine = create_engine(args.dsn)177    session = sessionmaker(bind=engine)()178    _list_filepaths(session, **{key: getattr(args, key) for key in arg_names})179def list_dirpaths(args):180    arg_names = main_arg_names + '''181        depth182    '''.split()183    engine = create_engine(args.dsn)184    session = sessionmaker(bind=engine)()...

aws.py

Source:aws.py

1"""2Production configuration for grading controller3"""4import json5import os6from .logsettings import get_logger_config7from .settings import *8import logging9######################################################################10#General config11######################################################################12#Allow to specify a prefix for env/auth configuration files13SERVICE_VARIANT = os.environ.get('SERVICE_VARIANT', '')14if SERVICE_VARIANT:15    CONFIG_PREFIX = SERVICE_VARIANT + "."16#Read config from json file17with open(ENV_ROOT / CONFIG_PREFIX + "env.json") as env_file:18    ENV_TOKENS = json.load(env_file)19#Debug20DEBUG = ENV_TOKENS.get('DEBUG', False)21if isinstance(DEBUG,basestring):22    DEBUG= DEBUG.lower()=="true"23TEMPLATE_DEBUG = ENV_TOKENS.get('TEMPLATE_DEBUG', False)24if isinstance(TEMPLATE_DEBUG,basestring):25    TEMPLATE_DEBUG= TEMPLATE_DEBUG.lower()=="true"26PRINT_QUERIES = ENV_TOKENS.get('PRINT_QUERIES', False)27if isinstance(PRINT_QUERIES,basestring):28    PRINT_QUERIES= PRINT_QUERIES.lower()=="true"29#General30REQUESTS_TIMEOUT = int(ENV_TOKENS.get('REQUESTS_TIMEOUT', REQUESTS_TIMEOUT))31TIME_BETWEEN_XQUEUE_PULLS = int(TIME_BETWEEN_XQUEUE_PULLS)32TIME_BETWEEN_EXPIRED_CHECKS = int(ENV_TOKENS.get('TIME_BETWEEN_EXPIRED_CHECKS', TIME_BETWEEN_EXPIRED_CHECKS))33GRADER_SETTINGS_DIRECTORY = ENV_TOKENS.get('GRADER_SETTINGS_DIRECTORY')34MAX_NUMBER_OF_TIMES_TO_RETRY_GRADING = int(ENV_TOKENS.get('MAX_NUMBER_OF_TIMES_TO_RETRY_GRADING'))35DEFAULT_ESTIMATED_GRADING_TIME = int(ENV_TOKENS.get('DEFAULT_ESTIMATED_GRADING_TIME', DEFAULT_ESTIMATED_GRADING_TIME))36COURSE_DATA_PATH = ENV_TOKENS.get('COURSE_DATA_PATH', COURSE_DATA_PATH)37#ML38MIN_TO_USE_ML = int(ENV_TOKENS.get('MIN_TO_USE_ML', MIN_TO_USE_ML))39ML_MODEL_PATH = os.path.join(ENV_ROOT, ENV_TOKENS.get('ML_MODEL_PATH'))40TIME_BETWEEN_ML_CREATOR_CHECKS = int(ENV_TOKENS.get('TIME_BETWEEN_ML_CREATOR_CHECKS', TIME_BETWEEN_ML_CREATOR_CHECKS))41TIME_BETWEEN_ML_GRADER_CHECKS = int(TIME_BETWEEN_ML_GRADER_CHECKS)42USE_S3_TO_STORE_MODELS= ENV_TOKENS.get('USE_S3_TO_STORE_MODELS', USE_S3_TO_STORE_MODELS)43if isinstance(USE_S3_TO_STORE_MODELS,basestring):44    USE_S3_TO_STORE_MODELS= USE_S3_TO_STORE_MODELS.lower()=="true"45S3_BUCKETNAME=ENV_TOKENS.get('S3_BUCKETNAME',"OpenEnded")46#Peer47MIN_TO_USE_PEER = int(ENV_TOKENS.get('MIN_TO_USE_PEER', MIN_TO_USE_PEER))48PEER_GRADER_COUNT = int(ENV_TOKENS.get('PEER_GRADER_COUNT', PEER_GRADER_COUNT))49PEER_GRADER_MINIMUM_TO_CALIBRATE = int(ENV_TOKENS.get("PEER_GRADER_MINIMUM_TO_CALIBRATE", PEER_GRADER_MINIMUM_TO_CALIBRATE))50PEER_GRADER_MAXIMUM_TO_CALIBRATE = int(ENV_TOKENS.get("PEER_GRADER_MAXIMUM_TO_CALIBRATE", PEER_GRADER_MAXIMUM_TO_CALIBRATE))51PEER_GRADER_MIN_NORMALIZED_CALIBRATION_ERROR = float(ENV_TOKENS.get("PEER_GRADER_MIN_NORMALIZED_CALIBRATION_ERROR", PEER_GRADER_MIN_NORMALIZED_CALIBRATION_ERROR))52PEER_GRADE_FINISHED_SUBMISSIONS_WHEN_NONE_PENDING = ENV_TOKENS.get("PEER_GRADE_FINISHED_SUBMISSIONS_WHEN_NONE_PENDING",53                                                                   PEER_GRADE_FINISHED_SUBMISSIONS_WHEN_NONE_PENDING)54#Submission Expiration55EXPIRE_SUBMISSIONS_AFTER = int(ENV_TOKENS.get('EXPIRE_SUBMISSIONS_AFTER', EXPIRE_SUBMISSIONS_AFTER))56RESET_SUBMISSIONS_AFTER = int(ENV_TOKENS.get('RESET_SUBMISSIONS_AFTER', RESET_SUBMISSIONS_AFTER))57GENERATE_COURSE_DATA_EVERY = int(ENV_TOKENS.get('GENERATE_COURSE_DATA_EVERY', 12 * 60 * 60))58#Time zone (shows up in logs)59TIME_ZONE = ENV_TOKENS.get('TIME_ZONE', TIME_ZONE)60local_loglevel = ENV_TOKENS.get('LOCAL_LOGLEVEL', 'INFO')61LOG_DIR = ENV_TOKENS.get("LOG_DIR", ENV_ROOT / "log")62LOGGING = get_logger_config(debug=DEBUG)63######################################################################64# Read secure config65with open(ENV_ROOT / CONFIG_PREFIX + "auth.json") as auth_file:66    AUTH_TOKENS = json.load(auth_file)67XQUEUE_INTERFACE = AUTH_TOKENS['XQUEUE_INTERFACE']68GRADING_CONTROLLER_INTERFACE = AUTH_TOKENS['GRADING_CONTROLLER_INTERFACE']69DATABASES = AUTH_TOKENS['DATABASES']70AWS_ACCESS_KEY_ID = AUTH_TOKENS.get("AWS_ACCESS_KEY_ID","")...

learn_db.py

Source:learn_db.py

...17            price_case=Case(low_price_case, high_price_case, output_field=TextField())18        ).annotate(19            discount_price=Case(low_price, high_price, output_field=DecimalField())20        ).order_by('category_id', 'name').select_related('category')21        print(print_queries('SELECT', connection.queries))22        t_list = PrettyTable(["ÐÐ°ÑÐµÐ³Ð¾ÑÐ¸Ñ", "Ð¢Ð¾Ð²Ð°Ñ", "ÐÐºÑÐ¸Ñ", 'Ð¦ÐµÐ½Ð°', 'Ð¦ÐµÐ½Ð° ÑÐ¾ ÑÐºÐ¸Ð´ÐºÐ¾Ð¹'])23        t_list.align = 'l'24        i = 025        for product in filter_products:26            t_list.add_row([f'{product.category.name:15}', f'{product.name:15}', f'{product.price_case:5}',27                            f'{product.price:6.0f}',28                            f'{product.discount_price:6.0f}'])29            if i == 0:30                print(print_queries('SELECT', connection.queries))31                i += 1...

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