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from __future__ import absolute_import, division, unicode_literals
import datetime
import pytest
try:
import numpy as np
import pandas as pd
from pandas.testing import (
assert_frame_equal,
assert_index_equal,
assert_series_equal,
)
except ImportError:
pytest.skip('numpy is not available', allow_module_level=True)
import jsonpickle
import jsonpickle.ext.pandas
@pytest.fixture(scope='module', autouse=True)
def pandas_extension():
"""Initialize the numpy extension for this test module"""
jsonpickle.ext.pandas.register_handlers()
yield # control to the test function.
jsonpickle.ext.pandas.unregister_handlers()
def roundtrip(obj):
return jsonpickle.decode(jsonpickle.encode(obj))
def test_series_roundtrip():
ser = pd.Series(
{
'an_int': np.int_(1),
'a_float': np.float_(2.5),
'a_nan': np.nan,
'a_minus_inf': -np.inf,
'an_inf': np.inf,
'a_str': np.str_('foo'),
'a_unicode': np.unicode_('bar'),
'date': np.datetime64('2014-01-01'),
'complex': np.complex_(1 - 2j),
# TODO: the following dtypes are not currently supported.
# 'object': np.object_({'a': 'b'}),
}
)
decoded_ser = roundtrip(ser)
assert_series_equal(decoded_ser, ser)
def test_dataframe_roundtrip():
df = pd.DataFrame(
{
'an_int': np.int_([1, 2, 3]),
'a_float': np.float_([2.5, 3.5, 4.5]),
'a_nan': np.array([np.nan] * 3),
'a_minus_inf': np.array([-np.inf] * 3),
'an_inf': np.array([np.inf] * 3),
'a_str': np.str_('foo'),
'a_unicode': np.unicode_('bar'),
'date': np.array([np.datetime64('2014-01-01')] * 3),
'complex': np.complex_([1 - 2j, 2 - 1.2j, 3 - 1.3j]),
# TODO: the following dtypes are not currently supported.
# 'object': np.object_([{'a': 'b'}]*3),
}
)
decoded_df = roundtrip(df)
assert_frame_equal(decoded_df, df)
def test_multindex_dataframe_roundtrip():
df = pd.DataFrame(
{
'idx_lvl0': ['a', 'b', 'c'],
'idx_lvl1': np.int_([1, 1, 2]),
'an_int': np.int_([1, 2, 3]),
'a_float': np.float_([2.5, 3.5, 4.5]),
'a_nan': np.array([np.nan] * 3),
'a_minus_inf': np.array([-np.inf] * 3),
'an_inf': np.array([np.inf] * 3),
'a_str': np.str_('foo'),
'a_unicode': np.unicode_('bar'),
}
)
df = df.set_index(['idx_lvl0', 'idx_lvl1'])
decoded_df = roundtrip(df)
assert_frame_equal(decoded_df, df)
def test_dataframe_with_interval_index_roundtrip():
df = pd.DataFrame(
{'a': [1, 2], 'b': [3, 4]}, index=pd.IntervalIndex.from_breaks([1, 2, 4])
)
decoded_df = roundtrip(df)
assert_frame_equal(decoded_df, df)
def test_index_roundtrip():
idx = pd.Index(range(5, 10))
decoded_idx = roundtrip(idx)
assert_index_equal(decoded_idx, idx)
def test_datetime_index_roundtrip():
idx = pd.date_range(start='2019-01-01', end='2019-02-01', freq='D')
decoded_idx = roundtrip(idx)
assert_index_equal(decoded_idx, idx)
def test_ragged_datetime_index_roundtrip():
idx = pd.DatetimeIndex(['2019-01-01', '2019-01-02', '2019-01-05'])
decoded_idx = roundtrip(idx)
assert_index_equal(decoded_idx, idx)
def test_timedelta_index_roundtrip():
idx = pd.timedelta_range(start='1 day', periods=4, closed='right')
decoded_idx = roundtrip(idx)
assert_index_equal(decoded_idx, idx)
def test_period_index_roundtrip():
idx = pd.period_range(start='2017-01-01', end='2018-01-01', freq='M')
decoded_idx = roundtrip(idx)
assert_index_equal(decoded_idx, idx)
def test_int64_index_roundtrip():
idx = pd.Index([-1, 0, 3, 4], dtype=np.int64)
decoded_idx = roundtrip(idx)
assert_index_equal(decoded_idx, idx)
def test_uint64_index_roundtrip():
idx = pd.Index([0, 3, 4], dtype=np.uint64)
decoded_idx = roundtrip(idx)
assert_index_equal(decoded_idx, idx)
def test_float64_index_roundtrip():
idx = pd.Index([0.1, 3.7, 4.2], dtype=np.float64)
decoded_idx = roundtrip(idx)
assert_index_equal(decoded_idx, idx)
def test_interval_index_roundtrip():
idx = pd.IntervalIndex.from_breaks(range(5))
decoded_idx = roundtrip(idx)
assert_index_equal(decoded_idx, idx)
def test_datetime_interval_index_roundtrip():
idx = pd.IntervalIndex.from_breaks(pd.date_range('2019-01-01', '2019-01-10'))
decoded_idx = roundtrip(idx)
assert_index_equal(decoded_idx, idx)
def test_multi_index_roundtrip():
idx = pd.MultiIndex.from_product(((1, 2, 3), ('a', 'b')))
decoded_idx = roundtrip(idx)
assert_index_equal(decoded_idx, idx)
def test_timestamp_roundtrip():
obj = pd.Timestamp('2019-01-01')
decoded_obj = roundtrip(obj)
assert decoded_obj == obj
def test_period_roundtrip():
obj = pd.Timestamp('2019-01-01')
decoded_obj = roundtrip(obj)
assert decoded_obj == obj
def test_interval_roundtrip():
obj = pd.Interval(2, 4, closed=str('left'))
decoded_obj = roundtrip(obj)
assert decoded_obj == obj
def test_b64():
"""Test the binary encoding"""
# array of substantial size is stored as b64
a = np.random.rand(20, 10)
index = ['Row' + str(i) for i in range(1, a.shape[0] + 1)]
columns = ['Col' + str(i) for i in range(1, a.shape[1] + 1)]
df = pd.DataFrame(a, index=index, columns=columns)
decoded_df = roundtrip(df)
assert_frame_equal(decoded_df, df)
def test_series_list_index():
"""Test pandas using series with a list index"""
expect = pd.Series(0, index=[1, 2, 3])
actual = roundtrip(expect)
assert expect.values[0] == actual.values[0]
assert 0 == actual.values[0]
assert expect.index[0] == actual.index[0]
assert expect.index[1] == actual.index[1]
assert expect.index[2] == actual.index[2]
def test_series_multi_index():
"""Test pandas using series with a multi-index"""
expect = pd.Series(0, index=[[1], [2], [3]])
actual = roundtrip(expect)
assert expect.values[0] == actual.values[0]
assert 0 == actual.values[0]
assert expect.index[0] == actual.index[0]
assert expect.index[0][0] == actual.index[0][0]
assert expect.index[0][1] == actual.index[0][1]
assert expect.index[0][2] == actual.index[0][2]
def test_series_multi_index_strings():
"""Test multi-index with strings"""
lets = ['A', 'B', 'C']
nums = ['1', '2', '3']
midx = pd.MultiIndex.from_product([lets, nums])
expect = pd.Series(0, index=midx)
actual = roundtrip(expect)
assert expect.values[0] == actual.values[0]
assert 0 == actual.values[0]
assert expect.index[0] == actual.index[0]
assert expect.index[1] == actual.index[1]
assert expect.index[2] == actual.index[2]
assert expect.index[3] == actual.index[3]
assert expect.index[4] == actual.index[4]
assert expect.index[5] == actual.index[5]
assert expect.index[6] == actual.index[6]
assert expect.index[7] == actual.index[7]
assert expect.index[8] == actual.index[8]
assert ('A', '1') == actual.index[0]
assert ('A', '2') == actual.index[1]
assert ('A', '3') == actual.index[2]
assert ('B', '1') == actual.index[3]
assert ('B', '2') == actual.index[4]
assert ('B', '3') == actual.index[5]
assert ('C', '1') == actual.index[6]
assert ('C', '2') == actual.index[7]
assert ('C', '3') == actual.index[8]
def test_dataframe_with_timedelta64_dtype():
data_frame = pd.DataFrame(
{
'Start': [
'2020/12/14 00:00:01',
'2020/12/14 00:00:04',
'2020/12/14 00:00:06',
],
'End': [
'2020/12/14 00:00:04',
'2020/12/14 00:00:06',
'2020/12/14 00:00:09',
],
}
)
data_frame['Start'] = pd.to_datetime(data_frame['Start'])
data_frame['End'] = pd.to_datetime(data_frame['End'])
data_frame['Duration'] = data_frame['End'] - data_frame['Start']
encoded = jsonpickle.encode(data_frame)
actual = jsonpickle.decode(encoded)
assert isinstance(actual, pd.DataFrame)
assert data_frame['Start'][0] == actual['Start'][0]
assert data_frame['Start'][1] == actual['Start'][1]
assert data_frame['Start'][2] == actual['Start'][2]
assert data_frame['End'][0] == actual['End'][0]
assert data_frame['End'][1] == actual['End'][1]
assert data_frame['End'][2] == actual['End'][2]
assert isinstance(actual['Duration'][0], datetime.timedelta)
assert isinstance(actual['Duration'][1], datetime.timedelta)
assert isinstance(actual['Duration'][2], datetime.timedelta)
assert data_frame['Duration'][0] == actual['Duration'][0]
assert data_frame['Duration'][1] == actual['Duration'][1]
assert data_frame['Duration'][2] == actual['Duration'][2]
def test_multilevel_columns():
iterables = [['inj', 'prod'], ['hourly', 'cumulative']]
names = ['first', 'second']
# transform it to tuples
columns = pd.MultiIndex.from_product(iterables, names=names)
# build a multi-index from it
data_frame = pd.DataFrame(
np.random.randn(3, 4), index=['A', 'B', 'C'], columns=columns
)
encoded = jsonpickle.encode(data_frame)
cloned_data_frame = jsonpickle.decode(encoded)
assert isinstance(cloned_data_frame, pd.DataFrame)
assert data_frame.columns.names == cloned_data_frame.columns.names
assert_frame_equal(data_frame, cloned_data_frame)
if __name__ == '__main__':
pytest.main([__file__])
|
