How to use the dataflows.set_type function in dataflows

def test_example_4():
    from dataflows import Flow, set_type

    f = Flow(
        country_population(),
        set_type('population', type='number', groupChar=',')
    )
    data, dp, _ = f.results()

def test_dump_to_path_use_titles():
    from dataflows import Flow, dump_to_path, set_type
    import tabulator

    Flow(
        [{'hello': 'world', 'hola': 'mundo'}, {'hello': 'עולם', 'hola': 'عالم'}],
        *(set_type(name, resources=['res_1'], title=title) for name, title
          in (('hello', 'שלום'), ('hola', 'aloha'))),
        dump_to_path('out/dump_with_titles', use_titles=True)
    ).process()

    with tabulator.Stream('out/dump_with_titles/res_1.csv') as stream:
        assert stream.read() == [['שלום',   'aloha'],
                                 ['world',  'mundo'],
                                 ['עולם',   'عالم']]

def test_set_type_regex():
    from dataflows import load, set_type
    flow = Flow(
        load('data/regex.csv'),
        set_type('city', type='string'),
        set_type('temperature (24h)', type='integer', regex=False),
    )
    data = flow.results()[0]
    assert data == [[
        {'city': 'london', 'temperature (24h)': 23},
        {'city': 'paris', 'temperature (24h)': 26},
        {'city': 'rome', 'temperature (24h)': 21},
    ]]

def test_set_type_resources():
    from dataflows import Flow, set_type, validate

    f = Flow(
        [dict(a=str(i)) for i in range(10)],
        [dict(b=str(i)) for i in range(10)],
        [dict(c='0_' + str(i)) for i in range(10)],
        set_type('a', resources='res_[1]', type='integer'),
        set_type('b', resources=['res_2'], type='integer'),
        set_type('[cd]', resources=-1, type='number', groupChar='_'),
        validate()
    )
    results, dp, stats = f.results()
    print(dp.descriptor)
    assert results[0][1]['a'] == 1
    assert results[1][3]['b'] == 3
    assert results[2][8]['c'] == 8.0

def test_save_load_dates():
    from dataflows import Flow, dump_to_path, load, set_type, printer
    import datetime

    Flow(
        [{'id': 1, 'ts': datetime.datetime.now()},
         {'id': 2, 'ts': datetime.datetime.now()}],
        set_type('ts', type='datetime', format='%Y-%m-%d/%H:%M:%S'),
        dump_to_path('out/test_save_load_dates')
    ).process()

    res, _, _ = Flow(
        load('out/test_save_load_dates/datapackage.json'),
        printer()
    ).results()

def run_flow(datetime_format=None):
        Flow(
            [{'today': str(_today), 'now': str(_now)}],
            set_type('today', type='date'),
            set_type('now', type='datetime', format=datetime_format),
            dump_to_path('out/dump_dates')
        ).process()

handler = on_error_fields()
    res, *_ = Flow(
        data,
        set_type('b', type='integer', on_error=ignore),
        validate(on_error=handler)
    ).results()
    assert len(res[0]) == 3
    assert handler.bad_row == {'a': 4, 'b': 'a'}
    assert handler.bad_index == 3
    assert handler.bad_field.name == 'b'

    # Field validator
    handler = on_error()
    res, *_ = Flow(
        data,
        set_type('b', type='integer', on_error=ignore),
        validate('a', lambda v: v < 4, on_error=handler)
    ).results()
    assert len(res[0]) == 3
    assert handler.bad_row == {'a': 4, 'b': 'a'}
    assert handler.bad_index == 3

    # Row validator
    handler = on_error()
    res, *_ = Flow(
        data,
        set_type('b', type='integer', on_error=ignore),
        validate(lambda v: v['a'] < 4, on_error=handler)
    ).results()
    assert len(res[0]) == 3
    assert handler.bad_row == {'a': 4, 'b': 'a'}
    assert handler.bad_index == 3

def run_flow(datetime_format=None):
        Flow(
            [{'today': str(_today), 'now': str(_now)}],
            set_type('today', type='date'),
            set_type('now', type='datetime', format=datetime_format),
            dump_to_path('out/dump_dates')
        ).process()

def test_example_5():
    from dataflows import Flow, set_type, dump_to_path

    f = Flow(
        country_population(),
        set_type('population', type='number', groupChar=','),
        dump_to_path('out/country_population')
    )
    _ = f.process()

format='xls',
        sheet=2,
        skip_rows=[1,2,3,-1],
        headers=['Date', 'Price'],
        name='daily'
    ),
    load(
        load_source='http://www.eia.gov/dnav/ng/hist_xls/RNGWHHDm.xls',
        format='xls',
        sheet=2,
        skip_rows=[1,2,3,-1],
        headers=['Month', 'Price'],
        name='monthly'
    ),
    format_date,
    set_type('Date', resources='daily', type='date'),
    set_type('Month',resources='monthly', type='yearmonth'),
    update_resource('daily', **{'path':'data/daily.csv', 'dpp:streaming': True}),
    update_resource('monthly', **{'path':'data/monthly.csv', 'dpp:streaming': True}),
    validate()
)


def flow(parameters, datapackage, resources, stats):
    return natural_gas


if __name__ == '__main__':
    natural_gas.process()