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How to use pandas_version method in pandera
Best Python code snippet using pandera_python
test_json_table_schema_ext_dtype.py
Source:test_json_table_schema_ext_dtype.py 
1"""Tests for ExtensionDtype Table Schema integration."""2from collections import OrderedDict3import datetime as dt4import decimal5import json6import pytest7from pandas import (8 DataFrame,9 array,10)11from pandas.core.arrays.integer import Int64Dtype12from pandas.core.arrays.string_ import StringDtype13from pandas.core.series import Series14from pandas.tests.extension.date import (15 DateArray,16 DateDtype,17)18from pandas.tests.extension.decimal.array import (19 DecimalArray,20 DecimalDtype,21)22from pandas.io.json._table_schema import (23 as_json_table_type,24 build_table_schema,25)26class TestBuildSchema:27 def setup_method(self, method):28 self.da = DateArray([dt.date(2021, 10, 10)])29 self.dc = DecimalArray([decimal.Decimal(10)])30 self.sa = array(["pandas"], dtype="string")31 self.ia = array([10], dtype="Int64")32 self.df = DataFrame(33 {34 "A": self.da,35 "B": self.dc,36 "C": self.sa,37 "D": self.ia,38 }39 )40 def test_build_table_schema(self):41 result = build_table_schema(self.df, version=False)42 expected = {43 "fields": [44 {"name": "index", "type": "integer"},45 {"name": "A", "type": "any", "extDtype": "DateDtype"},46 {"name": "B", "type": "any", "extDtype": "decimal"},47 {"name": "C", "type": "any", "extDtype": "string"},48 {"name": "D", "type": "integer", "extDtype": "Int64"},49 ],50 "primaryKey": ["index"],51 }52 assert result == expected53 result = build_table_schema(self.df)54 assert "pandas_version" in result55class TestTableSchemaType:56 @pytest.mark.parametrize(57 "date_data",58 [59 DateArray([dt.date(2021, 10, 10)]),60 DateArray(dt.date(2021, 10, 10)),61 Series(DateArray(dt.date(2021, 10, 10))),62 ],63 )64 def test_as_json_table_type_ext_date_array_dtype(self, date_data):65 assert as_json_table_type(date_data.dtype) == "any"66 def test_as_json_table_type_ext_date_dtype(self):67 assert as_json_table_type(DateDtype()) == "any"68 @pytest.mark.parametrize(69 "decimal_data",70 [71 DecimalArray([decimal.Decimal(10)]),72 Series(DecimalArray([decimal.Decimal(10)])),73 ],74 )75 def test_as_json_table_type_ext_decimal_array_dtype(self, decimal_data):76 assert as_json_table_type(decimal_data.dtype) == "any"77 def test_as_json_table_type_ext_decimal_dtype(self):78 assert as_json_table_type(DecimalDtype()) == "any"79 @pytest.mark.parametrize(80 "string_data",81 [82 array(["pandas"], dtype="string"),83 Series(array(["pandas"], dtype="string")),84 ],85 )86 def test_as_json_table_type_ext_string_array_dtype(self, string_data):87 assert as_json_table_type(string_data.dtype) == "any"88 def test_as_json_table_type_ext_string_dtype(self):89 assert as_json_table_type(StringDtype()) == "any"90 @pytest.mark.parametrize(91 "integer_data",92 [93 array([10], dtype="Int64"),94 Series(array([10], dtype="Int64")),95 ],96 )97 def test_as_json_table_type_ext_integer_array_dtype(self, integer_data):98 assert as_json_table_type(integer_data.dtype) == "integer"99 def test_as_json_table_type_ext_integer_dtype(self):100 assert as_json_table_type(Int64Dtype()) == "integer"101class TestTableOrient:102 def setup_method(self, method):103 self.da = DateArray([dt.date(2021, 10, 10)])104 self.dc = DecimalArray([decimal.Decimal(10)])105 self.sa = array(["pandas"], dtype="string")106 self.ia = array([10], dtype="Int64")107 self.df = DataFrame(108 {109 "A": self.da,110 "B": self.dc,111 "C": self.sa,112 "D": self.ia,113 }114 )115 def test_build_date_series(self):116 s = Series(self.da, name="a")117 s.index.name = "id"118 result = s.to_json(orient="table", date_format="iso")119 result = json.loads(result, object_pairs_hook=OrderedDict)120 assert "pandas_version" in result["schema"]121 result["schema"].pop("pandas_version")122 fields = [123 {"name": "id", "type": "integer"},124 {"name": "a", "type": "any", "extDtype": "DateDtype"},125 ]126 schema = {"fields": fields, "primaryKey": ["id"]}127 expected = OrderedDict(128 [129 ("schema", schema),130 ("data", [OrderedDict([("id", 0), ("a", "2021-10-10T00:00:00.000Z")])]),131 ]132 )133 assert result == expected134 def test_build_decimal_series(self):135 s = Series(self.dc, name="a")136 s.index.name = "id"137 result = s.to_json(orient="table", date_format="iso")138 result = json.loads(result, object_pairs_hook=OrderedDict)139 assert "pandas_version" in result["schema"]140 result["schema"].pop("pandas_version")141 fields = [142 {"name": "id", "type": "integer"},143 {"name": "a", "type": "any", "extDtype": "decimal"},144 ]145 schema = {"fields": fields, "primaryKey": ["id"]}146 expected = OrderedDict(147 [148 ("schema", schema),149 ("data", [OrderedDict([("id", 0), ("a", 10.0)])]),150 ]151 )152 assert result == expected153 def test_build_string_series(self):154 s = Series(self.sa, name="a")155 s.index.name = "id"156 result = s.to_json(orient="table", date_format="iso")157 result = json.loads(result, object_pairs_hook=OrderedDict)158 assert "pandas_version" in result["schema"]159 result["schema"].pop("pandas_version")160 fields = [161 {"name": "id", "type": "integer"},162 {"name": "a", "type": "any", "extDtype": "string"},163 ]164 schema = {"fields": fields, "primaryKey": ["id"]}165 expected = OrderedDict(166 [167 ("schema", schema),168 ("data", [OrderedDict([("id", 0), ("a", "pandas")])]),169 ]170 )171 assert result == expected172 def test_build_int64_series(self):173 s = Series(self.ia, name="a")174 s.index.name = "id"175 result = s.to_json(orient="table", date_format="iso")176 result = json.loads(result, object_pairs_hook=OrderedDict)177 assert "pandas_version" in result["schema"]178 result["schema"].pop("pandas_version")179 fields = [180 {"name": "id", "type": "integer"},181 {"name": "a", "type": "integer", "extDtype": "Int64"},182 ]183 schema = {"fields": fields, "primaryKey": ["id"]}184 expected = OrderedDict(185 [186 ("schema", schema),187 ("data", [OrderedDict([("id", 0), ("a", 10)])]),188 ]189 )190 assert result == expected191 def test_to_json(self):192 df = self.df.copy()193 df.index.name = "idx"194 result = df.to_json(orient="table", date_format="iso")195 result = json.loads(result, object_pairs_hook=OrderedDict)196 assert "pandas_version" in result["schema"]197 result["schema"].pop("pandas_version")198 fields = [199 OrderedDict({"name": "idx", "type": "integer"}),200 OrderedDict({"name": "A", "type": "any", "extDtype": "DateDtype"}),201 OrderedDict({"name": "B", "type": "any", "extDtype": "decimal"}),202 OrderedDict({"name": "C", "type": "any", "extDtype": "string"}),203 OrderedDict({"name": "D", "type": "integer", "extDtype": "Int64"}),204 ]205 schema = OrderedDict({"fields": fields, "primaryKey": ["idx"]})206 data = [207 OrderedDict(208 [209 ("idx", 0),210 ("A", "2021-10-10T00:00:00.000Z"),211 ("B", 10.0),212 ("C", "pandas"),213 ("D", 10),214 ]215 )216 ]217 expected = OrderedDict([("schema", schema), ("data", data)])...
_compat.py
Source:_compat.py
1import string2import numpy as np3import pandas as pd4from packaging.version import parse as parse_version5PANDAS_VERSION = parse_version(pd.__version__)6PANDAS_GT_104 = PANDAS_VERSION >= parse_version("1.0.4")7PANDAS_GT_110 = PANDAS_VERSION >= parse_version("1.1.0")8PANDAS_GT_120 = PANDAS_VERSION >= parse_version("1.2.0")9PANDAS_GT_121 = PANDAS_VERSION >= parse_version("1.2.1")10PANDAS_GT_130 = PANDAS_VERSION >= parse_version("1.3.0")11PANDAS_GT_131 = PANDAS_VERSION >= parse_version("1.3.1")12PANDAS_GT_133 = PANDAS_VERSION >= parse_version("1.3.3")13PANDAS_GT_140 = PANDAS_VERSION >= parse_version("1.4.0")14# FIXME: Using `.release` below as versions like `1.5.0.dev0+268.gbe8d1ec880`15# are less than `1.5.0` with `packaging.version`. Update to use `parse_version("1.5.0")`16# below once `pandas=1.5.0` is released17PANDAS_GT_150 = PANDAS_VERSION.release >= (1, 5, 0)18import pandas.testing as tm19def assert_categorical_equal(left, right, *args, **kwargs):20 tm.assert_extension_array_equal(left, right, *args, **kwargs)21 assert pd.api.types.is_categorical_dtype(22 left.dtype23 ), f"{left} is not categorical dtype"24 assert pd.api.types.is_categorical_dtype(25 right.dtype26 ), f"{right} is not categorical dtype"27def assert_numpy_array_equal(left, right):28 left_na = pd.isna(left)29 right_na = pd.isna(right)30 np.testing.assert_array_equal(left_na, right_na)31 left_valid = left[~left_na]32 right_valid = right[~right_na]33 np.testing.assert_array_equal(left_valid, right_valid)34def makeDataFrame():35 data = np.random.randn(30, 4)36 index = list(string.ascii_letters)[:30]37 return pd.DataFrame(data, index=index, columns=list("ABCD"))38def makeTimeDataFrame():39 data = makeDataFrame()40 data.index = makeDateIndex()41 return data42def makeTimeSeries():43 return makeTimeDataFrame()["A"]44def makeDateIndex(k=30, freq="B"):45 return pd.date_range("2000", periods=k, freq=freq)46def makeTimedeltaIndex(k=30, freq="D"):47 return pd.timedelta_range("1 day", periods=k, freq=freq)48def makeMissingDataframe():49 df = makeDataFrame()50 data = df.values51 data = np.where(data > 1, np.nan, data)52 return pd.DataFrame(data, index=df.index, columns=df.columns)53def makeMixedDataFrame():54 df = pd.DataFrame(55 {56 "A": [0.0, 1, 2, 3, 4],57 "B": [0.0, 1, 0, 1, 0],58 "C": [f"foo{i}" for i in range(5)],59 "D": pd.date_range("2009-01-01", periods=5),60 }61 )...
_utils.py
Source:_utils.py
1import datetime as dt2from distutils.version import LooseVersion3import pandas as pd4from pandas.core.common import PandasError5from pandas import to_datetime6import requests7from requests_file import FileAdapter8import requests_ftp9requests_ftp.monkeypatch_session()10if pd.compat.PY3:11 from urllib.error import HTTPError # noqa12else:13 from urllib2 import HTTPError # noqa14PANDAS_VERSION = LooseVersion(pd.__version__)15if PANDAS_VERSION >= LooseVersion('0.19.0'):16 PANDAS_0190 = True17 from pandas.api.types import is_number # noqa18else:19 PANDAS_0190 = False20 from pandas.core.common import is_number # noqa21if PANDAS_VERSION >= LooseVersion('0.17.0'):22 PANDAS_0170 = True23else:24 PANDAS_0170 = False25if PANDAS_VERSION >= LooseVersion('0.16.0'):26 PANDAS_0160 = True27else:28 PANDAS_0160 = False29if PANDAS_VERSION >= LooseVersion('0.14.0'):30 PANDAS_0140 = True31else:32 PANDAS_0140 = False33class SymbolWarning(UserWarning):34 pass35class RemoteDataError(PandasError, IOError):36 pass37def _sanitize_dates(start, end):38 """39 Return (datetime_start, datetime_end) tuple40 if start is None - default is 2010/01/0141 if end is None - default is today42 """43 if is_number(start):44 # regard int as year45 start = dt.datetime(start, 1, 1)46 start = to_datetime(start)47 if is_number(end):48 end = dt.datetime(end, 1, 1)49 end = to_datetime(end)50 if start is None:51 start = dt.datetime(2010, 1, 1)52 if end is None:53 end = dt.datetime.today()54 return start, end55def _init_session(session, retry_count=3):56 if session is None:57 session = requests.Session()58 session.mount('file://', FileAdapter())59 # do not set requests max_retries here to support arbitrary pause...
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