def hello_world(request): """Responds to any HTTP request. Args: request (flask.Request): HTTP request object. Returns: The response text or any set of values that can be turned into a Response object using `make_response <http://flask.pocoo.org/docs/1.0/api/#flask.Flask.make_response>`. """ request_json = request.get_json() table = request_json # Converting the list of list into a pandas dataframe. query_table = [] for row in range(1, len(table)): if row != 0: query_table.append(table[row]) query_table_dataframe = pandas.DataFrame(query_table, columns=table[0]) result = date_detection.detect(query_table_dataframe) # converting enums to strings for returning to the UI for col in result.keys(): result[col]['type'] = _column_types_enum_to_str(result[col]['type']) result_json = json.dumps(result) return result_json
def test_7(): """ Detect the date columns in austin_weather.csv Here 2 date columns are present with different formats. """ table = pandas.read_csv('data_for_tests/table_7.csv') result = date_detection.detect(table) print(result) expected_result = '''{'date': {'type': <ColumnTypes.CONSINTENT: 1>, 'day_first': True}, ' date__new': {'type': <ColumnTypes.CONSINTENT: 1>, 'day_first': False}}''' assert (expected_result == str(result))
def test_6(): """ Detect the date columns in austin_weather.csv Example date present - '2013-12-21' """ table = pandas.read_csv('data_for_tests/austin_weather.csv') result = date_detection.detect(table) print(result) expected_result = '''{'Date': {'type': <ColumnTypes.CONSINTENT: 1>, 'day_first': False}}''' assert (expected_result == str(result))
def test_5(): """ Detect the date columns in orders.csv Example date present - '10/13/2010' """ table = pandas.read_csv('data_for_tests/orders.csv') result = date_detection.detect(table) print(result) expected_result = '''{'Order Date': {'type': <ColumnTypes.CONSINTENT: 1>, 'day_first': False}}''' assert (expected_result == str(result))
def test_4(): """ Detect the date columns in naukri_com.csv Example date present - '2019-07-06 09:20:22 +0000' """ table = pandas.read_csv('data_for_tests/naukri_com.csv') result = date_detection.detect(table) print(result) expected_result = '''{'Crawl Timestamp': {'type': <ColumnTypes.CONSINTENT: 1>, 'day_first': False}}''' assert (expected_result == str(result))
def test_2(): """ Detect the date columns in table_2.csv Date column name is 'da____t__e' """ table = pandas.read_csv('data_for_tests/table_2.csv') result = date_detection.detect(table) print(result) expected_result = '''{'da____t__e': {'type': <ColumnTypes.CONSINTENT: 1>, 'day_first': True}}''' assert (expected_result == str(result))
def test_1(): """ Detect the date columns in table_1.csv dates are in such format - '02-02-2001' """ table = pandas.read_csv('data_for_tests/table_1.csv') result = date_detection.detect(table) print(result) expected_result = '''{'DATE': {'type': <ColumnTypes.INCONSISTENT: 3>, 'day_first': None}}''' assert (expected_result == str(result))
def test_7(): """ Detect the date columns in austin_weather.csv Here 2 date columns are present with different formats. """ table = pandas.read_csv('data_for_tests/table_7.csv') result = date_detection.detect(table) print(result) expected_result = '''{'date': {'type': <ColumnTypes.CONSISTENT: 1>, 'day_first': True, 'min_date': {'day_first_true': '1999-12-30'}, 'max_date': {'day_first_true': '2020-12-23'}}, ' date__new': {'type': <ColumnTypes.CONSISTENT: 1>, 'day_first': False, 'min_date': {'day_first_false': '2001-02-02'}, 'max_date': {'day_first_false': '2024-07-03'}}}''' assert(expected_result == str(result))
def test_3(): """ Detect the date columns in table_3.csv Inconsistent date column is present. Two dates exists - '23-12-2020', '14-27-2016' """ table = pandas.read_csv('data_for_tests/table_3.csv') result = date_detection.detect(table) print(result) expected_result = '''{}''' assert (expected_result == str(result))