def test_all_test_methods_are_being_generated(): result = [] for city in cities: result.extend( list( auditor.generate_multiple( engine, engine.select().all().difference('SAMPLE'), city, None, None, _get_test_data_filepath))) assert len(result) == 22
def test_all_test_methods_are_being_generated(): result = [] for city in cities: result.extend(list(auditor.generate_multiple(engine, engine.select().all().difference('SAMPLE'), city, None, None, _get_test_data_filepath))) assert len(result) == 22
def _get_test_data_filename(reference, symbol=None): symbol_part = '' if not symbol else '{%s}' % symbol return '%s%s.csv' % (reference, symbol_part) def _get_test_data_filepath(reference, symbol=None): return os.path.join(config.DATASOURCE_TEST_DATA_DIR, _get_test_data_filename(reference, symbol)) auditor.generate_multiple(data_engine, data_engine .select() .all() .difference('RAW') .difference('NORMALIZATION_FACTOR:SPLITS:PCT_CHANGE(1):RAW_BOVESPA'), 'PETR4', None, None, _get_test_data_filepath, sys.modules[__name__]) auditor.generate_multiple(data_engine, data_engine.select().all().difference('RAW'), 'PETR4', d(2008, 1, 1), d(2008, 12, 31), _get_test_data_filepath, sys.modules[__name__])
@engine.for_each(engine.select('SAMPLE_IN').union('ROLLING_MEAN')) def _percentual_change_factory(source_reference): @engine.datasource('PERCENTUALT_CHANGE:%s' % source_reference, dependencies=[source_reference], lookback=1, tags=['PERCENTUALT_CHANGE']) class PctChange(object): def evaluate(self, context, symbol, start=None, end=None): return context.dependencies(source_reference).pct_change() for city in cities: auditor.generate_multiple(engine, engine.select().all().difference('SAMPLE'), city, None, None, _get_test_data_filepath, sys.modules[__name__]) auditor.generate_multiple(engine, engine.select().all().difference('SAMPLE'), city, dt(2001, 1, 1), dt(2002, 1, 1), _get_test_data_filepath, sys.modules[__name__]) def test_all_test_methods_are_being_generated(): result = [] for city in cities: result.extend( list( auditor.generate_multiple( engine, engine.select().all().difference('SAMPLE'), city, None,
@engine.datasource('PERCENTUALT_CHANGE:%s' % source_reference, dependencies=[source_reference], lookback=1, tags=['PERCENTUALT_CHANGE']) class PctChange(object): def evaluate(self, context, symbol, start=None, end=None): return context.dependencies(source_reference).pct_change() for city in cities: auditor.generate_multiple(engine, engine.select().all().difference('SAMPLE'), city, None, None, _get_test_data_filepath, sys.modules[__name__]) auditor.generate_multiple(engine, engine.select().all().difference('SAMPLE'), city, dt(2001, 1, 1), dt(2002, 1, 1), _get_test_data_filepath, sys.modules[__name__]) def test_all_test_methods_are_being_generated(): result = [] for city in cities:
import bigtempo.auditor as auditor from instances import data_engine def _get_test_data_filename(reference, symbol=None): symbol_part = '' if not symbol else '{%s}' % symbol return '%s%s.csv' % (reference, symbol_part) def _get_test_data_filepath(reference, symbol=None): return os.path.join(config.DATASOURCE_TEST_DATA_DIR, _get_test_data_filename(reference, symbol)) auditor.generate_multiple( data_engine, data_engine.select().all().difference('RAW').difference( 'NORMALIZATION_FACTOR:SPLITS:PCT_CHANGE(1):RAW_BOVESPA'), 'PETR4', None, None, _get_test_data_filepath, sys.modules[__name__]) auditor.generate_multiple(data_engine, data_engine.select().all().difference('RAW'), 'PETR4', d(2008, 1, 1), d(2008, 12, 31), _get_test_data_filepath, sys.modules[__name__]) auditor.generate_multiple( data_engine, data_engine.select( 'NORMALIZATION_FACTOR:SPLITS:PCT_CHANGE(1):RAW_BOVESPA'), 'PETR4', None, d(2013, 8, 7), _get_test_data_filepath, sys.modules[__name__])