def test_json_conversion_strings_with_leading_zeros():
runner_ids = np.array(['000000000' + str(x) for x in range(10)])
df = DDF({'runner_id': runner_ids})
js = df.to_json()
newdf = DDF.from_json(js)
newdf = newdf.colslice(df)
assert newdf.equals(df)
def test_to_json(df):
with pytest.raises(AssertionError):
df.to_json()
df = df.rename(lambda col: str(col))
df = df.sort('0')
json = df.to_json()
newdf = DDF.from_json(json)
newdf = newdf.sort('0')
assert newdf.equals(df)
def test_json_conversion_preserves_string_dtypes():
original_df = DDF({
'runner_id': np.array(['test', 'testing'], dtype='S7'),
'short_strings': np.array(['a', 'b'], dtype='S1'),
'more_strings': np.array(['abc', 'def'], dtype='S')
})
js = original_df.to_json()
new_df = DDF.from_json(js)
new_df = new_df.colslice(original_df)
assert new_df.equals(original_df)
for col in ['runner_id', 'short_strings', 'more_strings']:
assert new_df[col].dtype == original_df[col].dtype
def test_json_conversion_datetimes():
dates = np.array([
'2013-03-30T00:00:00.000000000', '2014-02-10T00:00:00.000000000',
'2014-05-12T00:00:00.000000000', '2014-03-17T00:00:00.000000000',
'2013-04-12T00:00:00.000000000', '2014-05-19T00:00:00.000000000',
'2014-04-09T00:00:00.000000000', '2014-05-11T00:00:00.000000000',
'2014-02-25T00:00:00.000000000', '2014-04-24T00:00:00.000000000',
'2014-05-30T00:00:00.000000000', '2014-02-09T00:00:00.000000000',
'2014-05-05T00:00:00.000000000'], dtype='<M8[ns]')
df = DDF({'time': dates})
js = df.to_json()
newdf = DDF.from_json(js)
newdf = newdf.colslice(df)
assert newdf.equals(df)