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How to use to_json method in pandera

Best Python code snippet using pandera_python

test_pandas.py

Source:test_pandas.py

...65            [["a", "b"], ["c", "d"]],66            index=['index " 1', "index / 2"],67            columns=["a \\ b", "y / z"],68        )69        assert_frame_equal(df, read_json(df.to_json(orient="split"), orient="split"))70        assert_frame_equal(71            df, read_json(df.to_json(orient="columns"), orient="columns")72        )73        assert_frame_equal(df, read_json(df.to_json(orient="index"), orient="index"))74        df_unser = read_json(df.to_json(orient="records"), orient="records")75        assert_index_equal(df.columns, df_unser.columns)76        tm.assert_numpy_array_equal(df.values, df_unser.values)77    def test_frame_non_unique_index(self):78        df = DataFrame([["a", "b"], ["c", "d"]], index=[1, 1], columns=["x", "y"])79        msg = "DataFrame index must be unique for orient='index'"80        with pytest.raises(ValueError, match=msg):81            df.to_json(orient="index")82        msg = "DataFrame index must be unique for orient='columns'"83        with pytest.raises(ValueError, match=msg):84            df.to_json(orient="columns")85        assert_frame_equal(df, read_json(df.to_json(orient="split"), orient="split"))86        unser = read_json(df.to_json(orient="records"), orient="records")87        tm.assert_index_equal(df.columns, unser.columns)88        tm.assert_almost_equal(df.values, unser.values)89        unser = read_json(df.to_json(orient="values"), orient="values")90        tm.assert_numpy_array_equal(df.values, unser.values)91    def test_frame_non_unique_columns(self):92        df = DataFrame([["a", "b"], ["c", "d"]], index=[1, 2], columns=["x", "x"])93        msg = "DataFrame columns must be unique for orient='index'"94        with pytest.raises(ValueError, match=msg):95            df.to_json(orient="index")96        msg = "DataFrame columns must be unique for orient='columns'"97        with pytest.raises(ValueError, match=msg):98            df.to_json(orient="columns")99        msg = "DataFrame columns must be unique for orient='records'"100        with pytest.raises(ValueError, match=msg):101            df.to_json(orient="records")102        assert_frame_equal(103            df, read_json(df.to_json(orient="split"), orient="split", dtype=False)104        )105        unser = read_json(df.to_json(orient="values"), orient="values")106        tm.assert_numpy_array_equal(df.values, unser.values)107        # GH4377; duplicate columns not processing correctly108        df = DataFrame([["a", "b"], ["c", "d"]], index=[1, 2], columns=["x", "y"])109        result = read_json(df.to_json(orient="split"), orient="split")110        assert_frame_equal(result, df)111        def _check(df):112            result = read_json(113                df.to_json(orient="split"), orient="split", convert_dates=["x"]114            )115            assert_frame_equal(result, df)116        for o in [117            [["a", "b"], ["c", "d"]],118            [[1.5, 2.5], [3.5, 4.5]],119            [[1, 2.5], [3, 4.5]],120            [[Timestamp("20130101"), 3.5], [Timestamp("20130102"), 4.5]],121        ]:122            _check(DataFrame(o, index=[1, 2], columns=["x", "x"]))123    def test_frame_from_json_to_json(self):124        def _check_orient(125            df,126            orient,127            dtype=None,128            numpy=False,129            convert_axes=True,130            check_dtype=True,131            raise_ok=None,132            sort=None,133            check_index_type=True,134            check_column_type=True,135            check_numpy_dtype=False,136        ):137            if sort is not None:138                df = df.sort_values(sort)139            else:140                df = df.sort_index()141            # if we are not unique, then check that we are raising ValueError142            # for the appropriate orients143            if not df.index.is_unique and orient in ["index", "columns"]:144                msg = "DataFrame index must be unique for orient='{}'".format(orient)145                with pytest.raises(ValueError, match=msg):146                    df.to_json(orient=orient)147                return148            if not df.columns.is_unique and orient in ["index", "columns", "records"]:149                # TODO: not executed. fix this.150                with pytest.raises(ValueError, match="ksjkajksfjksjfkjs"):151                    df.to_json(orient=orient)152                return153            dfjson = df.to_json(orient=orient)154            try:155                unser = read_json(156                    dfjson,157                    orient=orient,158                    dtype=dtype,159                    numpy=numpy,160                    convert_axes=convert_axes,161                )162            except Exception as detail:163                if raise_ok is not None:164                    if isinstance(detail, raise_ok):165                        return166                raise167            if sort is not None and sort in unser.columns:168                unser = unser.sort_values(sort)169            else:170                unser = unser.sort_index()171            if not dtype:172                check_dtype = False173            if not convert_axes and df.index.dtype.type == np.datetime64:174                unser.index = DatetimeIndex(unser.index.values.astype("i8") * 1e6)175            if orient == "records":176                # index is not captured in this orientation177                tm.assert_almost_equal(178                    df.values, unser.values, check_dtype=check_numpy_dtype179                )180                tm.assert_index_equal(181                    df.columns, unser.columns, exact=check_column_type182                )183            elif orient == "values":184                # index and cols are not captured in this orientation185                if numpy is True and df.shape == (0, 0):186                    assert unser.shape[0] == 0187                else:188                    tm.assert_almost_equal(189                        df.values, unser.values, check_dtype=check_numpy_dtype190                    )191            elif orient == "split":192                # index and col labels might not be strings193                unser.index = [str(i) for i in unser.index]194                unser.columns = [str(i) for i in unser.columns]195                if sort is None:196                    unser = unser.sort_index()197                tm.assert_almost_equal(198                    df.values, unser.values, check_dtype=check_numpy_dtype199                )200            else:201                if convert_axes:202                    tm.assert_frame_equal(203                        df,204                        unser,205                        check_dtype=check_dtype,206                        check_index_type=check_index_type,207                        check_column_type=check_column_type,208                    )209                else:210                    tm.assert_frame_equal(211                        df, unser, check_less_precise=False, check_dtype=check_dtype212                    )213        def _check_all_orients(214            df,215            dtype=None,216            convert_axes=True,217            raise_ok=None,218            sort=None,219            check_index_type=True,220            check_column_type=True,221        ):222            # numpy=False223            if convert_axes:224                _check_orient(225                    df,226                    "columns",227                    dtype=dtype,228                    sort=sort,229                    check_index_type=False,230                    check_column_type=False,231                )232                _check_orient(233                    df,234                    "records",235                    dtype=dtype,236                    sort=sort,237                    check_index_type=False,238                    check_column_type=False,239                )240                _check_orient(241                    df,242                    "split",243                    dtype=dtype,244                    sort=sort,245                    check_index_type=False,246                    check_column_type=False,247                )248                _check_orient(249                    df,250                    "index",251                    dtype=dtype,252                    sort=sort,253                    check_index_type=False,254                    check_column_type=False,255                )256                _check_orient(257                    df,258                    "values",259                    dtype=dtype,260                    sort=sort,261                    check_index_type=False,262                    check_column_type=False,263                )264            _check_orient(df, "columns", dtype=dtype, convert_axes=False, sort=sort)265            _check_orient(df, "records", dtype=dtype, convert_axes=False, sort=sort)266            _check_orient(df, "split", dtype=dtype, convert_axes=False, sort=sort)267            _check_orient(df, "index", dtype=dtype, convert_axes=False, sort=sort)268            _check_orient(df, "values", dtype=dtype, convert_axes=False, sort=sort)269            # numpy=True and raise_ok might be not None, so ignore the error270            if convert_axes:271                _check_orient(272                    df,273                    "columns",274                    dtype=dtype,275                    numpy=True,276                    raise_ok=raise_ok,277                    sort=sort,278                    check_index_type=False,279                    check_column_type=False,280                )281                _check_orient(282                    df,283                    "records",284                    dtype=dtype,285                    numpy=True,286                    raise_ok=raise_ok,287                    sort=sort,288                    check_index_type=False,289                    check_column_type=False,290                )291                _check_orient(292                    df,293                    "split",294                    dtype=dtype,295                    numpy=True,296                    raise_ok=raise_ok,297                    sort=sort,298                    check_index_type=False,299                    check_column_type=False,300                )301                _check_orient(302                    df,303                    "index",304                    dtype=dtype,305                    numpy=True,306                    raise_ok=raise_ok,307                    sort=sort,308                    check_index_type=False,309                    check_column_type=False,310                )311                _check_orient(312                    df,313                    "values",314                    dtype=dtype,315                    numpy=True,316                    raise_ok=raise_ok,317                    sort=sort,318                    check_index_type=False,319                    check_column_type=False,320                )321            _check_orient(322                df,323                "columns",324                dtype=dtype,325                numpy=True,326                convert_axes=False,327                raise_ok=raise_ok,328                sort=sort,329            )330            _check_orient(331                df,332                "records",333                dtype=dtype,334                numpy=True,335                convert_axes=False,336                raise_ok=raise_ok,337                sort=sort,338            )339            _check_orient(340                df,341                "split",342                dtype=dtype,343                numpy=True,344                convert_axes=False,345                raise_ok=raise_ok,346                sort=sort,347            )348            _check_orient(349                df,350                "index",351                dtype=dtype,352                numpy=True,353                convert_axes=False,354                raise_ok=raise_ok,355                sort=sort,356            )357            _check_orient(358                df,359                "values",360                dtype=dtype,361                numpy=True,362                convert_axes=False,363                raise_ok=raise_ok,364                sort=sort,365            )366        # basic367        _check_all_orients(self.frame)368        assert self.frame.to_json() == self.frame.to_json(orient="columns")369        _check_all_orients(self.intframe, dtype=self.intframe.values.dtype)370        _check_all_orients(self.intframe, dtype=False)371        # big one372        # index and columns are strings as all unserialised JSON object keys373        # are assumed to be strings374        biggie = DataFrame(375            np.zeros((200, 4)),376            columns=[str(i) for i in range(4)],377            index=[str(i) for i in range(200)],378        )379        _check_all_orients(biggie, dtype=False, convert_axes=False)380        # dtypes381        _check_all_orients(382            DataFrame(biggie, dtype=np.float64), dtype=np.float64, convert_axes=False383        )384        _check_all_orients(385            DataFrame(biggie, dtype=np.int), dtype=np.int, convert_axes=False386        )387        _check_all_orients(388            DataFrame(biggie, dtype="U3"),389            dtype="U3",390            convert_axes=False,391            raise_ok=ValueError,392        )393        # categorical394        _check_all_orients(self.categorical, sort="sort", raise_ok=ValueError)395        # empty396        _check_all_orients(397            self.empty_frame, check_index_type=False, check_column_type=False398        )399        # time series data400        _check_all_orients(self.tsframe)401        # mixed data402        index = pd.Index(["a", "b", "c", "d", "e"])403        data = {404            "A": [0.0, 1.0, 2.0, 3.0, 4.0],405            "B": [0.0, 1.0, 0.0, 1.0, 0.0],406            "C": ["foo1", "foo2", "foo3", "foo4", "foo5"],407            "D": [True, False, True, False, True],408        }409        df = DataFrame(data=data, index=index)410        _check_orient(df, "split", check_dtype=False)411        _check_orient(df, "records", check_dtype=False)412        _check_orient(df, "values", check_dtype=False)413        _check_orient(df, "columns", check_dtype=False)414        # index oriented is problematic as it is read back in in a transposed415        # state, so the columns are interpreted as having mixed data and416        # given object dtypes.417        # force everything to have object dtype beforehand418        _check_orient(df.transpose().transpose(), "index", dtype=False)419    def test_frame_from_json_bad_data(self):420        with pytest.raises(ValueError, match="Expected object or value"):421            read_json(StringIO('{"key":b:a:d}'))422        # too few indices423        json = StringIO(424            '{"columns":["A","B"],'425            '"index":["2","3"],'426            '"data":[[1.0,"1"],[2.0,"2"],[null,"3"]]}'427        )428        msg = r"Shape of passed values is \(3, 2\), indices imply \(2, 2\)"429        with pytest.raises(ValueError, match=msg):430            read_json(json, orient="split")431        # too many columns432        json = StringIO(433            '{"columns":["A","B","C"],'434            '"index":["1","2","3"],'435            '"data":[[1.0,"1"],[2.0,"2"],[null,"3"]]}'436        )437        msg = "3 columns passed, passed data had 2 columns"438        with pytest.raises(ValueError, match=msg):439            read_json(json, orient="split")440        # bad key441        json = StringIO(442            '{"badkey":["A","B"],'443            '"index":["2","3"],'444            '"data":[[1.0,"1"],[2.0,"2"],[null,"3"]]}'445        )446        with pytest.raises(ValueError, match=r"unexpected key\(s\): badkey"):447            read_json(json, orient="split")448    def test_frame_from_json_nones(self):449        df = DataFrame([[1, 2], [4, 5, 6]])450        unser = read_json(df.to_json())451        assert np.isnan(unser[2][0])452        df = DataFrame([["1", "2"], ["4", "5", "6"]])453        unser = read_json(df.to_json())454        assert np.isnan(unser[2][0])455        unser = read_json(df.to_json(), dtype=False)456        assert unser[2][0] is None457        unser = read_json(df.to_json(), convert_axes=False, dtype=False)458        assert unser["2"]["0"] is None459        unser = read_json(df.to_json(), numpy=False)460        assert np.isnan(unser[2][0])461        unser = read_json(df.to_json(), numpy=False, dtype=False)462        assert unser[2][0] is None463        unser = read_json(df.to_json(), numpy=False, convert_axes=False, dtype=False)464        assert unser["2"]["0"] is None465        # infinities get mapped to nulls which get mapped to NaNs during466        # deserialisation467        df = DataFrame([[1, 2], [4, 5, 6]])468        df.loc[0, 2] = np.inf469        unser = read_json(df.to_json())470        assert np.isnan(unser[2][0])471        unser = read_json(df.to_json(), dtype=False)472        assert np.isnan(unser[2][0])473        df.loc[0, 2] = np.NINF474        unser = read_json(df.to_json())475        assert np.isnan(unser[2][0])476        unser = read_json(df.to_json(), dtype=False)477        assert np.isnan(unser[2][0])478    @pytest.mark.skipif(479        is_platform_32bit(), reason="not compliant on 32-bit, xref #15865"480    )481    def test_frame_to_json_float_precision(self):482        df = pd.DataFrame([dict(a_float=0.95)])483        encoded = df.to_json(double_precision=1)484        assert encoded == '{"a_float":{"0":1.0}}'485        df = pd.DataFrame([dict(a_float=1.95)])486        encoded = df.to_json(double_precision=1)487        assert encoded == '{"a_float":{"0":2.0}}'488        df = pd.DataFrame([dict(a_float=-1.95)])489        encoded = df.to_json(double_precision=1)490        assert encoded == '{"a_float":{"0":-2.0}}'491        df = pd.DataFrame([dict(a_float=0.995)])492        encoded = df.to_json(double_precision=2)493        assert encoded == '{"a_float":{"0":1.0}}'494        df = pd.DataFrame([dict(a_float=0.9995)])495        encoded = df.to_json(double_precision=3)496        assert encoded == '{"a_float":{"0":1.0}}'497        df = pd.DataFrame([dict(a_float=0.99999999999999944)])498        encoded = df.to_json(double_precision=15)499        assert encoded == '{"a_float":{"0":1.0}}'500    def test_frame_to_json_except(self):501        df = DataFrame([1, 2, 3])502        msg = "Invalid value 'garbage' for option 'orient'"503        with pytest.raises(ValueError, match=msg):504            df.to_json(orient="garbage")505    def test_frame_empty(self):506        df = DataFrame(columns=["jim", "joe"])507        assert not df._is_mixed_type508        assert_frame_equal(509            read_json(df.to_json(), dtype=dict(df.dtypes)), df, check_index_type=False510        )511        # GH 7445512        result = pd.DataFrame({"test": []}, index=[]).to_json(orient="columns")513        expected = '{"test":{}}'514        assert result == expected515    def test_frame_empty_mixedtype(self):516        # mixed type517        df = DataFrame(columns=["jim", "joe"])518        df["joe"] = df["joe"].astype("i8")519        assert df._is_mixed_type520        assert_frame_equal(521            read_json(df.to_json(), dtype=dict(df.dtypes)), df, check_index_type=False522        )523    def test_frame_mixedtype_orient(self):  # GH10289524        vals = [525            [10, 1, "foo", 0.1, 0.01],526            [20, 2, "bar", 0.2, 0.02],527            [30, 3, "baz", 0.3, 0.03],528            [40, 4, "qux", 0.4, 0.04],529        ]530        df = DataFrame(531            vals, index=list("abcd"), columns=["1st", "2nd", "3rd", "4th", "5th"]532        )533        assert df._is_mixed_type534        right = df.copy()535        for orient in ["split", "index", "columns"]:536            inp = df.to_json(orient=orient)537            left = read_json(inp, orient=orient, convert_axes=False)538            assert_frame_equal(left, right)539        right.index = np.arange(len(df))540        inp = df.to_json(orient="records")541        left = read_json(inp, orient="records", convert_axes=False)542        assert_frame_equal(left, right)543        right.columns = np.arange(df.shape[1])544        inp = df.to_json(orient="values")545        left = read_json(inp, orient="values", convert_axes=False)546        assert_frame_equal(left, right)547    def test_v12_compat(self):548        df = DataFrame(549            [550                [1.56808523, 0.65727391, 1.81021139, -0.17251653],551                [-0.2550111, -0.08072427, -0.03202878, -0.17581665],552                [1.51493992, 0.11805825, 1.629455, -1.31506612],553                [-0.02765498, 0.44679743, 0.33192641, -0.27885413],554                [0.05951614, -2.69652057, 1.28163262, 0.34703478],555            ],556            columns=["A", "B", "C", "D"],557            index=pd.date_range("2000-01-03", "2000-01-07"),558        )559        df["date"] = pd.Timestamp("19920106 18:21:32.12")560        df.iloc[3, df.columns.get_loc("date")] = pd.Timestamp("20130101")561        df["modified"] = df["date"]562        df.iloc[1, df.columns.get_loc("modified")] = pd.NaT563        v12_json = os.path.join(self.dirpath, "tsframe_v012.json")564        df_unser = pd.read_json(v12_json)565        assert_frame_equal(df, df_unser)566        df_iso = df.drop(["modified"], axis=1)567        v12_iso_json = os.path.join(self.dirpath, "tsframe_iso_v012.json")568        df_unser_iso = pd.read_json(v12_iso_json)569        assert_frame_equal(df_iso, df_unser_iso)570    def test_blocks_compat_GH9037(self):571        index = pd.date_range("20000101", periods=10, freq="H")572        df_mixed = DataFrame(573            OrderedDict(574                float_1=[575                    -0.92077639,576                    0.77434435,577                    1.25234727,578                    0.61485564,579                    -0.60316077,580                    0.24653374,581                    0.28668979,582                    -2.51969012,583                    0.95748401,584                    -1.02970536,585                ],586                int_1=[587                    19680418,588                    75337055,589                    99973684,590                    65103179,591                    79373900,592                    40314334,593                    21290235,594                    4991321,595                    41903419,596                    16008365,597                ],598                str_1=[599                    "78c608f1",600                    "64a99743",601                    "13d2ff52",602                    "ca7f4af2",603                    "97236474",604                    "bde7e214",605                    "1a6bde47",606                    "b1190be5",607                    "7a669144",608                    "8d64d068",609                ],610                float_2=[611                    -0.0428278,612                    -1.80872357,613                    3.36042349,614                    -0.7573685,615                    -0.48217572,616                    0.86229683,617                    1.08935819,618                    0.93898739,619                    -0.03030452,620                    1.43366348,621                ],622                str_2=[623                    "14f04af9",624                    "d085da90",625                    "4bcfac83",626                    "81504caf",627                    "2ffef4a9",628                    "08e2f5c4",629                    "07e1af03",630                    "addbd4a7",631                    "1f6a09ba",632                    "4bfc4d87",633                ],634                int_2=[635                    86967717,636                    98098830,637                    51927505,638                    20372254,639                    12601730,640                    20884027,641                    34193846,642                    10561746,643                    24867120,644                    76131025,645                ],646            ),647            index=index,648        )649        # JSON deserialisation always creates unicode strings650        df_mixed.columns = df_mixed.columns.astype("unicode")651        df_roundtrip = pd.read_json(df_mixed.to_json(orient="split"), orient="split")652        assert_frame_equal(653            df_mixed,654            df_roundtrip,655            check_index_type=True,656            check_column_type=True,657            check_frame_type=True,658            by_blocks=True,659            check_exact=True,660        )661    def test_frame_nonprintable_bytes(self):662        # GH14256: failing column caused segfaults, if it is not the last one663        class BinaryThing:664            def __init__(self, hexed):665                self.hexed = hexed666                self.binary = bytes.fromhex(hexed)667            def __str__(self):668                return self.hexed669        hexed = "574b4454ba8c5eb4f98a8f45"670        binthing = BinaryThing(hexed)671        # verify the proper conversion of printable content672        df_printable = DataFrame({"A": [binthing.hexed]})673        assert df_printable.to_json() == '{{"A":{{"0":"{hex}"}}}}'.format(hex=hexed)674        # check if non-printable content throws appropriate Exception675        df_nonprintable = DataFrame({"A": [binthing]})676        msg = "Unsupported UTF-8 sequence length when encoding string"677        with pytest.raises(OverflowError, match=msg):678            df_nonprintable.to_json()679        # the same with multiple columns threw segfaults680        df_mixed = DataFrame({"A": [binthing], "B": [1]}, columns=["A", "B"])681        with pytest.raises(OverflowError):682            df_mixed.to_json()683        # default_handler should resolve exceptions for non-string types684        assert df_nonprintable.to_json(685            default_handler=str686        ) == '{{"A":{{"0":"{hex}"}}}}'.format(hex=hexed)687        assert df_mixed.to_json(688            default_handler=str689        ) == '{{"A":{{"0":"{hex}"}},"B":{{"0":1}}}}'.format(hex=hexed)690    def test_label_overflow(self):691        # GH14256: buffer length not checked when writing label692        df = pd.DataFrame({"bar" * 100000: [1], "foo": [1337]})693        assert df.to_json() == '{{"{bar}":{{"0":1}},"foo":{{"0":1337}}}}'.format(694            bar=("bar" * 100000)695        )696    def test_series_non_unique_index(self):697        s = Series(["a", "b"], index=[1, 1])698        msg = "Series index must be unique for orient='index'"699        with pytest.raises(ValueError, match=msg):700            s.to_json(orient="index")701        assert_series_equal(702            s, read_json(s.to_json(orient="split"), orient="split", typ="series")703        )704        unser = read_json(s.to_json(orient="records"), orient="records", typ="series")705        tm.assert_numpy_array_equal(s.values, unser.values)706    def test_series_from_json_to_json(self):707        def _check_orient(708            series, orient, dtype=None, numpy=False, check_index_type=True709        ):710            series = series.sort_index()711            unser = read_json(712                series.to_json(orient=orient),713                typ="series",714                orient=orient,715                numpy=numpy,716                dtype=dtype,717            )718            unser = unser.sort_index()719            if orient == "records" or orient == "values":720                assert_almost_equal(series.values, unser.values)721            else:722                if orient == "split":723                    assert_series_equal(724                        series, unser, check_index_type=check_index_type725                    )726                else:727                    assert_series_equal(728                        series,729                        unser,730                        check_names=False,731                        check_index_type=check_index_type,732                    )733        def _check_all_orients(series, dtype=None, check_index_type=True):734            _check_orient(735                series, "columns", dtype=dtype, check_index_type=check_index_type736            )737            _check_orient(738                series, "records", dtype=dtype, check_index_type=check_index_type739            )740            _check_orient(741                series, "split", dtype=dtype, check_index_type=check_index_type742            )743            _check_orient(744                series, "index", dtype=dtype, check_index_type=check_index_type745            )746            _check_orient(series, "values", dtype=dtype)747            _check_orient(748                series,749                "columns",750                dtype=dtype,751                numpy=True,752                check_index_type=check_index_type,753            )754            _check_orient(755                series,756                "records",757                dtype=dtype,758                numpy=True,759                check_index_type=check_index_type,760            )761            _check_orient(762                series,763                "split",764                dtype=dtype,765                numpy=True,766                check_index_type=check_index_type,767            )768            _check_orient(769                series,770                "index",771                dtype=dtype,772                numpy=True,773                check_index_type=check_index_type,774            )775            _check_orient(776                series,777                "values",778                dtype=dtype,779                numpy=True,780                check_index_type=check_index_type,781            )782        # basic783        _check_all_orients(self.series)784        assert self.series.to_json() == self.series.to_json(orient="index")785        objSeries = Series(786            [str(d) for d in self.objSeries],787            index=self.objSeries.index,788            name=self.objSeries.name,789        )790        _check_all_orients(objSeries, dtype=False)791        # empty_series has empty index with object dtype792        # which cannot be revert793        assert self.empty_series.index.dtype == np.object_794        _check_all_orients(self.empty_series, check_index_type=False)795        _check_all_orients(self.ts)796        # dtype797        s = Series(range(6), index=["a", "b", "c", "d", "e", "f"])798        _check_all_orients(Series(s, dtype=np.float64), dtype=np.float64)799        _check_all_orients(Series(s, dtype=np.int), dtype=np.int)800    def test_series_to_json_except(self):801        s = Series([1, 2, 3])802        msg = "Invalid value 'garbage' for option 'orient'"803        with pytest.raises(ValueError, match=msg):804            s.to_json(orient="garbage")805    def test_series_from_json_precise_float(self):806        s = Series([4.56, 4.56, 4.56])807        result = read_json(s.to_json(), typ="series", precise_float=True)808        assert_series_equal(result, s, check_index_type=False)809    def test_series_with_dtype(self):810        # GH 21986811        s = Series([4.56, 4.56, 4.56])812        result = read_json(s.to_json(), typ="series", dtype=np.int64)813        expected = Series([4] * 3)814        assert_series_equal(result, expected)815    def test_frame_from_json_precise_float(self):816        df = DataFrame([[4.56, 4.56, 4.56], [4.56, 4.56, 4.56]])817        result = read_json(df.to_json(), precise_float=True)818        assert_frame_equal(result, df, check_index_type=False, check_column_type=False)819    def test_typ(self):820        s = Series(range(6), index=["a", "b", "c", "d", "e", "f"], dtype="int64")821        result = read_json(s.to_json(), typ=None)822        assert_series_equal(result, s)823    def test_reconstruction_index(self):824        df = DataFrame([[1, 2, 3], [4, 5, 6]])825        result = read_json(df.to_json())826        assert_frame_equal(result, df)827        df = DataFrame({"a": [1, 2, 3], "b": [4, 5, 6]}, index=["A", "B", "C"])828        result = read_json(df.to_json())829        assert_frame_equal(result, df)830    def test_path(self):831        with ensure_clean("test.json") as path:832            for df in [833                self.frame,834                self.frame2,835                self.intframe,836                self.tsframe,837                self.mixed_frame,838            ]:839                df.to_json(path)840                read_json(path)841    def test_axis_dates(self):842        # frame843        json = self.tsframe.to_json()844        result = read_json(json)845        assert_frame_equal(result, self.tsframe)846        # series847        json = self.ts.to_json()848        result = read_json(json, typ="series")849        assert_series_equal(result, self.ts, check_names=False)850        assert result.name is None851    def test_convert_dates(self):852        # frame853        df = self.tsframe.copy()854        df["date"] = Timestamp("20130101")855        json = df.to_json()856        result = read_json(json)857        assert_frame_equal(result, df)858        df["foo"] = 1.0859        json = df.to_json(date_unit="ns")860        result = read_json(json, convert_dates=False)861        expected = df.copy()862        expected["date"] = expected["date"].values.view("i8")863        expected["foo"] = expected["foo"].astype("int64")864        assert_frame_equal(result, expected)865        # series866        ts = Series(Timestamp("20130101"), index=self.ts.index)867        json = ts.to_json()868        result = read_json(json, typ="series")869        assert_series_equal(result, ts)870    def test_convert_dates_infer(self):871        # GH10747872        from pandas.io.json import dumps873        infer_words = [874            "trade_time",875            "date",876            "datetime",877            "sold_at",878            "modified",879            "timestamp",880            "timestamps",881        ]882        for infer_word in infer_words:883            data = [{"id": 1, infer_word: 1036713600000}, {"id": 2}]884            expected = DataFrame(885                [[1, Timestamp("2002-11-08")], [2, pd.NaT]], columns=["id", infer_word]886            )887            result = read_json(dumps(data))[["id", infer_word]]888            assert_frame_equal(result, expected)889    def test_date_format_frame(self):890        df = self.tsframe.copy()891        def test_w_date(date, date_unit=None):892            df["date"] = Timestamp(date)893            df.iloc[1, df.columns.get_loc("date")] = pd.NaT894            df.iloc[5, df.columns.get_loc("date")] = pd.NaT895            if date_unit:896                json = df.to_json(date_format="iso", date_unit=date_unit)897            else:898                json = df.to_json(date_format="iso")899            result = read_json(json)900            expected = df.copy()901            expected.index = expected.index.tz_localize("UTC")902            expected["date"] = expected["date"].dt.tz_localize("UTC")903            assert_frame_equal(result, expected)904        test_w_date("20130101 20:43:42.123")905        test_w_date("20130101 20:43:42", date_unit="s")906        test_w_date("20130101 20:43:42.123", date_unit="ms")907        test_w_date("20130101 20:43:42.123456", date_unit="us")908        test_w_date("20130101 20:43:42.123456789", date_unit="ns")909        msg = "Invalid value 'foo' for option 'date_unit'"910        with pytest.raises(ValueError, match=msg):911            df.to_json(date_format="iso", date_unit="foo")912    def test_date_format_series(self):913        def test_w_date(date, date_unit=None):914            ts = Series(Timestamp(date), index=self.ts.index)915            ts.iloc[1] = pd.NaT916            ts.iloc[5] = pd.NaT917            if date_unit:918                json = ts.to_json(date_format="iso", date_unit=date_unit)919            else:920                json = ts.to_json(date_format="iso")921            result = read_json(json, typ="series")922            expected = ts.copy()923            expected.index = expected.index.tz_localize("UTC")924            expected = expected.dt.tz_localize("UTC")925            assert_series_equal(result, expected)926        test_w_date("20130101 20:43:42.123")927        test_w_date("20130101 20:43:42", date_unit="s")928        test_w_date("20130101 20:43:42.123", date_unit="ms")929        test_w_date("20130101 20:43:42.123456", date_unit="us")930        test_w_date("20130101 20:43:42.123456789", date_unit="ns")931        ts = Series(Timestamp("20130101 20:43:42.123"), index=self.ts.index)932        msg = "Invalid value 'foo' for option 'date_unit'"933        with pytest.raises(ValueError, match=msg):934            ts.to_json(date_format="iso", date_unit="foo")935    def test_date_unit(self):936        df = self.tsframe.copy()937        df["date"] = Timestamp("20130101 20:43:42")938        dl = df.columns.get_loc("date")939        df.iloc[1, dl] = Timestamp("19710101 20:43:42")940        df.iloc[2, dl] = Timestamp("21460101 20:43:42")941        df.iloc[4, dl] = pd.NaT942        for unit in ("s", "ms", "us", "ns"):943            json = df.to_json(date_format="epoch", date_unit=unit)944            # force date unit945            result = read_json(json, date_unit=unit)946            assert_frame_equal(result, df)947            # detect date unit948            result = read_json(json, date_unit=None)949            assert_frame_equal(result, df)950    def test_weird_nested_json(self):951        # this used to core dump the parser952        s = r"""{953        "status": "success",954        "data": {955        "posts": [956            {957            "id": 1,958            "title": "A blog post",959            "body": "Some useful content"960            },961            {962            "id": 2,963            "title": "Another blog post",964            "body": "More content"965            }966           ]967          }968        }"""969        read_json(s)970    def test_doc_example(self):971        dfj2 = DataFrame(np.random.randn(5, 2), columns=list("AB"))972        dfj2["date"] = Timestamp("20130101")973        dfj2["ints"] = range(5)974        dfj2["bools"] = True975        dfj2.index = pd.date_range("20130101", periods=5)976        json = dfj2.to_json()977        result = read_json(json, dtype={"ints": np.int64, "bools": np.bool_})978        assert_frame_equal(result, result)979    def test_misc_example(self):980        # parsing unordered input fails981        result = read_json('[{"a": 1, "b": 2}, {"b":2, "a" :1}]', numpy=True)982        expected = DataFrame([[1, 2], [1, 2]], columns=["a", "b"])983        error_msg = """DataFrame\\.index are different984DataFrame\\.index values are different \\(100\\.0 %\\)985\\[left\\]:  Index\\(\\['a', 'b'\\], dtype='object'\\)986\\[right\\]: RangeIndex\\(start=0, stop=2, step=1\\)"""987        with pytest.raises(AssertionError, match=error_msg):988            assert_frame_equal(result, expected, check_index_type=False)989        result = read_json('[{"a": 1, "b": 2}, {"b":2, "a" :1}]')990        expected = DataFrame([[1, 2], [1, 2]], columns=["a", "b"])991        assert_frame_equal(result, expected)992    @network993    @pytest.mark.single994    def test_round_trip_exception_(self):995        # GH 3867996        csv = "https://raw.github.com/hayd/lahman2012/master/csvs/Teams.csv"997        df = pd.read_csv(csv)998        s = df.to_json()999        result = pd.read_json(s)1000        assert_frame_equal(result.reindex(index=df.index, columns=df.columns), df)1001    @network1002    @pytest.mark.single1003    @pytest.mark.parametrize(1004        "field,dtype",1005        [1006            ["created_at", pd.DatetimeTZDtype(tz="UTC")],1007            ["closed_at", "datetime64[ns]"],1008            ["updated_at", pd.DatetimeTZDtype(tz="UTC")],1009        ],1010    )1011    def test_url(self, field, dtype):1012        url = "https://api.github.com/repos/pandas-dev/pandas/issues?per_page=5"  # noqa1013        result = read_json(url, convert_dates=True)1014        assert result[field].dtype == dtype1015    def test_timedelta(self):1016        converter = lambda x: pd.to_timedelta(x, unit="ms")1017        s = Series([timedelta(23), timedelta(seconds=5)])1018        assert s.dtype == "timedelta64[ns]"1019        result = pd.read_json(s.to_json(), typ="series").apply(converter)1020        assert_series_equal(result, s)1021        s = Series([timedelta(23), timedelta(seconds=5)], index=pd.Index([0, 1]))1022        assert s.dtype == "timedelta64[ns]"1023        result = pd.read_json(s.to_json(), typ="series").apply(converter)1024        assert_series_equal(result, s)1025        frame = DataFrame([timedelta(23), timedelta(seconds=5)])1026        assert frame[0].dtype == "timedelta64[ns]"1027        assert_frame_equal(frame, pd.read_json(frame.to_json()).apply(converter))1028        frame = DataFrame(1029            {1030                "a": [timedelta(days=23), timedelta(seconds=5)],1031                "b": [1, 2],1032                "c": pd.date_range(start="20130101", periods=2),1033            }1034        )1035        result = pd.read_json(frame.to_json(date_unit="ns"))1036        result["a"] = pd.to_timedelta(result.a, unit="ns")1037        result["c"] = pd.to_datetime(result.c)1038        assert_frame_equal(frame, result)1039    def test_mixed_timedelta_datetime(self):1040        frame = DataFrame(1041            {"a": [timedelta(23), pd.Timestamp("20130101")]}, dtype=object1042        )1043        expected = DataFrame(1044            {"a": [pd.Timedelta(frame.a[0]).value, pd.Timestamp(frame.a[1]).value]}1045        )1046        result = pd.read_json(frame.to_json(date_unit="ns"), dtype={"a": "int64"})1047        assert_frame_equal(result, expected, check_index_type=False)1048    def test_default_handler(self):1049        value = object()1050        frame = DataFrame({"a": [7, value]})1051        expected = DataFrame({"a": [7, str(value)]})1052        result = pd.read_json(frame.to_json(default_handler=str))1053        assert_frame_equal(expected, result, check_index_type=False)1054    def test_default_handler_indirect(self):1055        from pandas.io.json import dumps1056        def default(obj):1057            if isinstance(obj, complex):1058                return [("mathjs", "Complex"), ("re", obj.real), ("im", obj.imag)]1059            return str(obj)1060        df_list = [1061            9,1062            DataFrame(1063                {"a": [1, "STR", complex(4, -5)], "b": [float("nan"), None, "N/A"]},1064                columns=["a", "b"],1065            ),1066        ]1067        expected = (1068            '[9,[[1,null],["STR",null],[[["mathjs","Complex"],'1069            '["re",4.0],["im",-5.0]],"N\\/A"]]]'1070        )1071        assert dumps(df_list, default_handler=default, orient="values") == expected1072    def test_default_handler_numpy_unsupported_dtype(self):1073        # GH12554 to_json raises 'Unhandled numpy dtype 15'1074        df = DataFrame(1075            {"a": [1, 2.3, complex(4, -5)], "b": [float("nan"), None, complex(1.2, 0)]},1076            columns=["a", "b"],1077        )1078        expected = (1079            '[["(1+0j)","(nan+0j)"],'1080            '["(2.3+0j)","(nan+0j)"],'1081            '["(4-5j)","(1.2+0j)"]]'1082        )1083        assert df.to_json(default_handler=str, orient="values") == expected1084    def test_default_handler_raises(self):1085        msg = "raisin"1086        def my_handler_raises(obj):1087            raise TypeError(msg)1088        with pytest.raises(TypeError, match=msg):1089            DataFrame({"a": [1, 2, object()]}).to_json(1090                default_handler=my_handler_raises1091            )1092        with pytest.raises(TypeError, match=msg):1093            DataFrame({"a": [1, 2, complex(4, -5)]}).to_json(1094                default_handler=my_handler_raises1095            )1096    def test_categorical(self):1097        # GH4377 df.to_json segfaults with non-ndarray blocks1098        df = DataFrame({"A": ["a", "b", "c", "a", "b", "b", "a"]})1099        df["B"] = df["A"]1100        expected = df.to_json()1101        df["B"] = df["A"].astype("category")1102        assert expected == df.to_json()1103        s = df["A"]1104        sc = df["B"]1105        assert s.to_json() == sc.to_json()1106    def test_datetime_tz(self):1107        # GH4377 df.to_json segfaults with non-ndarray blocks1108        tz_range = pd.date_range("20130101", periods=3, tz="US/Eastern")1109        tz_naive = tz_range.tz_convert("utc").tz_localize(None)1110        df = DataFrame({"A": tz_range, "B": pd.date_range("20130101", periods=3)})1111        df_naive = df.copy()1112        df_naive["A"] = tz_naive1113        expected = df_naive.to_json()1114        assert expected == df.to_json()1115        stz = Series(tz_range)1116        s_naive = Series(tz_naive)1117        assert stz.to_json() == s_naive.to_json()1118    @pytest.mark.filterwarnings("ignore:Sparse:FutureWarning")1119    @pytest.mark.filterwarnings("ignore:DataFrame.to_sparse:FutureWarning")1120    @pytest.mark.filterwarnings("ignore:Series.to_sparse:FutureWarning")1121    def test_sparse(self):1122        # GH4377 df.to_json segfaults with non-ndarray blocks1123        df = pd.DataFrame(np.random.randn(10, 4))1124        df.loc[:8] = np.nan1125        sdf = df.to_sparse()1126        expected = df.to_json()1127        assert expected == sdf.to_json()1128        s = pd.Series(np.random.randn(10))1129        s.loc[:8] = np.nan1130        ss = s.to_sparse()1131        expected = s.to_json()1132        assert expected == ss.to_json()1133    def test_tz_is_utc(self):1134        from pandas.io.json import dumps1135        exp = '"2013-01-10T05:00:00.000Z"'1136        ts = Timestamp("2013-01-10 05:00:00Z")1137        assert dumps(ts, iso_dates=True) == exp1138        dt = ts.to_pydatetime()1139        assert dumps(dt, iso_dates=True) == exp1140        ts = Timestamp("2013-01-10 00:00:00", tz="US/Eastern")1141        assert dumps(ts, iso_dates=True) == exp1142        dt = ts.to_pydatetime()1143        assert dumps(dt, iso_dates=True) == exp1144        ts = Timestamp("2013-01-10 00:00:00-0500")1145        assert dumps(ts, iso_dates=True) == exp1146        dt = ts.to_pydatetime()1147        assert dumps(dt, iso_dates=True) == exp1148    def test_tz_range_is_utc(self):1149        from pandas.io.json import dumps1150        exp = '["2013-01-01T05:00:00.000Z","2013-01-02T05:00:00.000Z"]'1151        dfexp = (1152            '{"DT":{'1153            '"0":"2013-01-01T05:00:00.000Z",'1154            '"1":"2013-01-02T05:00:00.000Z"}}'1155        )1156        tz_range = pd.date_range("2013-01-01 05:00:00Z", periods=2)1157        assert dumps(tz_range, iso_dates=True) == exp1158        dti = pd.DatetimeIndex(tz_range)1159        assert dumps(dti, iso_dates=True) == exp1160        df = DataFrame({"DT": dti})1161        result = dumps(df, iso_dates=True)1162        assert result == dfexp1163        tz_range = pd.date_range("2013-01-01 00:00:00", periods=2, tz="US/Eastern")1164        assert dumps(tz_range, iso_dates=True) == exp1165        dti = pd.DatetimeIndex(tz_range)1166        assert dumps(dti, iso_dates=True) == exp1167        df = DataFrame({"DT": dti})1168        assert dumps(df, iso_dates=True) == dfexp1169        tz_range = pd.date_range("2013-01-01 00:00:00-0500", periods=2)1170        assert dumps(tz_range, iso_dates=True) == exp1171        dti = pd.DatetimeIndex(tz_range)1172        assert dumps(dti, iso_dates=True) == exp1173        df = DataFrame({"DT": dti})1174        assert dumps(df, iso_dates=True) == dfexp1175    def test_read_inline_jsonl(self):1176        # GH91801177        result = read_json('{"a": 1, "b": 2}\n{"b":2, "a" :1}\n', lines=True)1178        expected = DataFrame([[1, 2], [1, 2]], columns=["a", "b"])1179        assert_frame_equal(result, expected)1180    @td.skip_if_not_us_locale1181    def test_read_s3_jsonl(self, s3_resource):1182        # GH172001183        result = read_json("s3n://pandas-test/items.jsonl", lines=True)1184        expected = DataFrame([[1, 2], [1, 2]], columns=["a", "b"])1185        assert_frame_equal(result, expected)1186    def test_read_local_jsonl(self):1187        # GH172001188        with ensure_clean("tmp_items.json") as path:1189            with open(path, "w") as infile:1190                infile.write('{"a": 1, "b": 2}\n{"b":2, "a" :1}\n')1191            result = read_json(path, lines=True)1192            expected = DataFrame([[1, 2], [1, 2]], columns=["a", "b"])1193            assert_frame_equal(result, expected)1194    def test_read_jsonl_unicode_chars(self):1195        # GH15132: non-ascii unicode characters1196        # \u201d == RIGHT DOUBLE QUOTATION MARK1197        # simulate file handle1198        json = '{"a": "fooâ", "b": "bar"}\n{"a": "foo", "b": "bar"}\n'1199        json = StringIO(json)1200        result = read_json(json, lines=True)1201        expected = DataFrame([["foo\u201d", "bar"], ["foo", "bar"]], columns=["a", "b"])1202        assert_frame_equal(result, expected)1203        # simulate string1204        json = '{"a": "fooâ", "b": "bar"}\n{"a": "foo", "b": "bar"}\n'1205        result = read_json(json, lines=True)1206        expected = DataFrame([["foo\u201d", "bar"], ["foo", "bar"]], columns=["a", "b"])1207        assert_frame_equal(result, expected)1208    def test_read_json_large_numbers(self):1209        # GH188421210        json = '{"articleId": "1404366058080022500245"}'1211        json = StringIO(json)1212        result = read_json(json, typ="series")1213        expected = Series(1.404366e21, index=["articleId"])1214        assert_series_equal(result, expected)1215        json = '{"0": {"articleId": "1404366058080022500245"}}'1216        json = StringIO(json)1217        result = read_json(json)1218        expected = DataFrame(1.404366e21, index=["articleId"], columns=[0])1219        assert_frame_equal(result, expected)1220    def test_to_jsonl(self):1221        # GH91801222        df = DataFrame([[1, 2], [1, 2]], columns=["a", "b"])1223        result = df.to_json(orient="records", lines=True)1224        expected = '{"a":1,"b":2}\n{"a":1,"b":2}'1225        assert result == expected1226        df = DataFrame([["foo}", "bar"], ['foo"', "bar"]], columns=["a", "b"])1227        result = df.to_json(orient="records", lines=True)1228        expected = '{"a":"foo}","b":"bar"}\n{"a":"foo\\"","b":"bar"}'1229        assert result == expected1230        assert_frame_equal(pd.read_json(result, lines=True), df)1231        # GH15096: escaped characters in columns and data1232        df = DataFrame([["foo\\", "bar"], ['foo"', "bar"]], columns=["a\\", "b"])1233        result = df.to_json(orient="records", lines=True)1234        expected = '{"a\\\\":"foo\\\\","b":"bar"}\n' '{"a\\\\":"foo\\"","b":"bar"}'1235        assert result == expected1236        assert_frame_equal(pd.read_json(result, lines=True), df)1237    # TODO: there is a near-identical test for pytables; can we share?1238    def test_latin_encoding(self):1239        # GH 137741240        pytest.skip("encoding not implemented in .to_json(), xref #13774")1241        values = [1242            [b"E\xc9, 17", b"", b"a", b"b", b"c"],1243            [b"E\xc9, 17", b"a", b"b", b"c"],1244            [b"EE, 17", b"", b"a", b"b", b"c"],1245            [b"E\xc9, 17", b"\xf8\xfc", b"a", b"b", b"c"],1246            [b"", b"a", b"b", b"c"],1247            [b"\xf8\xfc", b"a", b"b", b"c"],1248            [b"A\xf8\xfc", b"", b"a", b"b", b"c"],1249            [np.nan, b"", b"b", b"c"],1250            [b"A\xf8\xfc", np.nan, b"", b"b", b"c"],1251        ]1252        def _try_decode(x, encoding="latin-1"):1253            try:1254                return x.decode(encoding)1255            except AttributeError:1256                return x1257        # not sure how to remove latin-1 from code in python 2 and 31258        values = [[_try_decode(x) for x in y] for y in values]1259        examples = []1260        for dtype in ["category", object]:1261            for val in values:1262                examples.append(Series(val, dtype=dtype))1263        def roundtrip(s, encoding="latin-1"):1264            with ensure_clean("test.json") as path:1265                s.to_json(path, encoding=encoding)1266                retr = read_json(path, encoding=encoding)1267                assert_series_equal(s, retr, check_categorical=False)1268        for s in examples:1269            roundtrip(s)1270    def test_data_frame_size_after_to_json(self):1271        # GH153441272        df = DataFrame({"a": [str(1)]})1273        size_before = df.memory_usage(index=True, deep=True).sum()1274        df.to_json()1275        size_after = df.memory_usage(index=True, deep=True).sum()1276        assert size_before == size_after1277    @pytest.mark.parametrize(1278        "index", [None, [1, 2], [1.0, 2.0], ["a", "b"], ["1", "2"], ["1.", "2."]]1279    )1280    @pytest.mark.parametrize("columns", [["a", "b"], ["1", "2"], ["1.", "2."]])1281    def test_from_json_to_json_table_index_and_columns(self, index, columns):1282        # GH25433 GH254351283        expected = DataFrame([[1, 2], [3, 4]], index=index, columns=columns)1284        dfjson = expected.to_json(orient="table")1285        result = pd.read_json(dfjson, orient="table")1286        assert_frame_equal(result, expected)1287    def test_from_json_to_json_table_dtypes(self):1288        # GH213451289        expected = pd.DataFrame({"a": [1, 2], "b": [3.0, 4.0], "c": ["5", "6"]})1290        dfjson = expected.to_json(orient="table")1291        result = pd.read_json(dfjson, orient="table")1292        assert_frame_equal(result, expected)1293    @pytest.mark.parametrize("dtype", [True, {"b": int, "c": int}])1294    def test_read_json_table_dtype_raises(self, dtype):1295        # GH213451296        df = pd.DataFrame({"a": [1, 2], "b": [3.0, 4.0], "c": ["5", "6"]})1297        dfjson = df.to_json(orient="table")1298        msg = "cannot pass both dtype and orient='table'"1299        with pytest.raises(ValueError, match=msg):1300            pd.read_json(dfjson, orient="table", dtype=dtype)1301    def test_read_json_table_convert_axes_raises(self):1302        # GH25433 GH254351303        df = DataFrame([[1, 2], [3, 4]], index=[1.0, 2.0], columns=["1.", "2."])1304        dfjson = df.to_json(orient="table")1305        msg = "cannot pass both convert_axes and orient='table'"1306        with pytest.raises(ValueError, match=msg):1307            pd.read_json(dfjson, orient="table", convert_axes=True)1308    @pytest.mark.parametrize(1309        "data, expected",1310        [1311            (1312                DataFrame([[1, 2], [4, 5]], columns=["a", "b"]),1313                {"columns": ["a", "b"], "data": [[1, 2], [4, 5]]},1314            ),1315            (1316                DataFrame([[1, 2], [4, 5]], columns=["a", "b"]).rename_axis("foo"),1317                {"columns": ["a", "b"], "data": [[1, 2], [4, 5]]},1318            ),1319            (1320                DataFrame(1321                    [[1, 2], [4, 5]], columns=["a", "b"], index=[["a", "b"], ["c", "d"]]1322                ),1323                {"columns": ["a", "b"], "data": [[1, 2], [4, 5]]},1324            ),1325            (Series([1, 2, 3], name="A"), {"name": "A", "data": [1, 2, 3]}),1326            (1327                Series([1, 2, 3], name="A").rename_axis("foo"),1328                {"name": "A", "data": [1, 2, 3]},1329            ),1330            (1331                Series([1, 2], name="A", index=[["a", "b"], ["c", "d"]]),1332                {"name": "A", "data": [1, 2]},1333            ),1334        ],1335    )1336    def test_index_false_to_json_split(self, data, expected):1337        # GH 173941338        # Testing index=False in to_json with orient='split'1339        result = data.to_json(orient="split", index=False)1340        result = json.loads(result)1341        assert result == expected1342    @pytest.mark.parametrize(1343        "data",1344        [1345            (DataFrame([[1, 2], [4, 5]], columns=["a", "b"])),1346            (DataFrame([[1, 2], [4, 5]], columns=["a", "b"]).rename_axis("foo")),1347            (1348                DataFrame(1349                    [[1, 2], [4, 5]], columns=["a", "b"], index=[["a", "b"], ["c", "d"]]1350                )1351            ),1352            (Series([1, 2, 3], name="A")),1353            (Series([1, 2, 3], name="A").rename_axis("foo")),1354            (Series([1, 2], name="A", index=[["a", "b"], ["c", "d"]])),1355        ],1356    )1357    def test_index_false_to_json_table(self, data):1358        # GH 173941359        # Testing index=False in to_json with orient='table'1360        result = data.to_json(orient="table", index=False)1361        result = json.loads(result)1362        expected = {1363            "schema": pd.io.json.build_table_schema(data, index=False),1364            "data": DataFrame(data).to_dict(orient="records"),1365        }1366        assert result == expected1367    @pytest.mark.parametrize("orient", ["records", "index", "columns", "values"])1368    def test_index_false_error_to_json(self, orient):1369        # GH 173941370        # Testing error message from to_json with index=False1371        df = pd.DataFrame([[1, 2], [4, 5]], columns=["a", "b"])1372        msg = "'index=False' is only valid when 'orient' is 'split' or 'table'"1373        with pytest.raises(ValueError, match=msg):1374            df.to_json(orient=orient, index=False)1375    @pytest.mark.parametrize("orient", ["split", "table"])1376    @pytest.mark.parametrize("index", [True, False])1377    def test_index_false_from_json_to_json(self, orient, index):1378        # GH251701379        # Test index=False in from_json to_json1380        expected = DataFrame({"a": [1, 2], "b": [3, 4]})1381        dfjson = expected.to_json(orient=orient, index=index)1382        result = read_json(dfjson, orient=orient)1383        assert_frame_equal(result, expected)1384    def test_read_timezone_information(self):1385        # GH 255461386        result = read_json(1387            '{"2019-01-01T11:00:00.000Z":88}', typ="series", orient="index"1388        )1389        expected = Series([88], index=DatetimeIndex(["2019-01-01 11:00:00"], tz="UTC"))...

streamlined_syntax.py

Source:streamlined_syntax.py

...14		if (type(value)) == str:15			value = int(value)16		assert(type(value) == int and value >= 0)17		self.hv = Test(Switch(value))18	def to_json(self):19		return self.hv.to_json()20class PortEq(Pred):21	def __init__(self, value):22		if (type(value)) == str:23			value = int(value)24		assert(type(value) == int and value >= 0)25		self.hv = Test(Location(Physical(value)))26	def to_json(self):27		return self.hv.to_json()28class EthSrcEq(Pred):29	def __init__(self, value):30		assert(type(value) == str or type(value == unicode))31		self.hv = Test(EthSrc(value))32	def to_json(self):33		return self.hv.to_json()34class EthDstEq(Pred):35	def __init__(self, value):36		assert(type(value) == str or type(value == unicode))37		self.hv = Test(EthDst(value))38	def to_json(self):39		return self.hv.to_json()40class VlanEq(Pred):41	def __init__(self, value):42		if (type(value)) == str:43			value = int(value)44		assert(type(value) == int and value >= 0)45		self.hv = Test(Vlan(value))46	def to_json(self):47		return self.hv.to_json()48class VlanPcpEq(Pred):49	def __init__(self, value):50		if (type(value)) == str:51			value = int(value)52		assert(type(value) == int and value >= 0)53		self.hv = Test(VlanPcp(value))54	def to_json(self):55		return self.hv.to_json()56class EthTypeEq(Pred):57	def __init__(self, value):58		if (type(value)) == str:59			value = int(value)60		assert(type(value) == int and value >= 0)61		self.hv = Test(EthType(value))62	def to_json(self):63		return self.hv.to_json()64class IPProtoEq(Pred):65	def __init__(self, value):66		if (type(value)) == str:67			value = int(value)68		assert(type(value) == int and value >= 0)69		self.hv = Test(IPProto(value))70	def to_json(self):71		return self.hv.to_json()72class IP4SrcEq(Pred):73	def __init__(self, value, mask = None):74		assert(type(value) == str or type(value == unicode))75		if mask != None:76			assert type(mask) == int77		self.hv = Test(IP4Src(value, mask))78	def to_json(self):79		return self.hv.to_json()80class IP4DstEq(Pred):81	def __init__(self, value, mask = None):82		assert(type(value) == str or type(value == unicode))83		if mask != None:84			assert type(mask) == int85		self.hv = Test(IP4Dst(value, mask))86	def to_json(self):87		return self.hv.to_json()88class TCPSrcPortEq(Pred):89	def __init__(self, value):90		if (type(value)) == str:91			value = int(value)92		assert(type(value) == int and value >= 0)93		self.hv = Test(IPProto(value))94	def to_json(self):95		return self.hv.to_json()96class TCPDstPortEq(Pred):97	def __init__(self, value):98		if (type(value)) == str:99			value = int(value)100		assert(type(value) == int and value >= 0)101		self.hv = Test(IPProto(value))102	def to_json(self):103		return self.hv.to_json()104########## ___NotEq105class SwitchNotEq(Pred):106	def __init__(self, value):107		if (type(value)) == str:108			value = int(value)109		assert(type(value) == int and value >= 0)110		self.hv = Not(Test(Switch(value)))111	def to_json(self):112		return self.hv.to_json()113class PortNotEq(Pred):114	def __init__(self, value):115		if (type(value)) == str:116			value = int(value)117		assert(type(value) == int and value >= 0)118		self.hv = Not(Test(Location(Physical(value))))119	def to_json(self):120		return self.hv.to_json()121class EthSrcNotEq(Pred):122	def __init__(self, value):123		assert(type(value) == str or type(value == unicode))124		self.hv = Not(Test(EthSrc(value)))125	def to_json(self):126		return self.hv.to_json()127class EthDstNotEq(Pred):128	def __init__(self, value):129		assert(type(value) == str or type(value == unicode))130		self.hv = Not(Test(EthDst(value)))131	def to_json(self):132		return self.hv.to_json()133class VlanNotEq(Pred):134	def __init__(self, value):135		if (type(value)) == str:136			value = int(value)137		assert(type(value) == int and value >= 0)138		self.hv = Not(Test(Vlan(value)))139	def to_json(self):140		return self.hv.to_json()141class VlanPcpNotEq(Pred):142	def __init__(self, value):143		if (type(value)) == str:144			value = int(value)145		assert(type(value) == int and value >= 0)146		self.hv = Not(Test(VlanPcp(value)))147	def to_json(self):148		return self.hv.to_json()149class EthTypeNotEq(Pred):150	def __init__(self, value):151		if (type(value)) == str:152			value = int(value)153		assert(type(value) == int and value >= 0)154		self.hv = Not(Test(EthType(value)))155	def to_json(self):156		return self.hv.to_json()157class IPProtoNotEq(Pred):158	def __init__(self, value):159		if (type(value)) == str:160			value = int(value)161		assert(type(value) == int and value >= 0)162		self.hv = Not(Test(IPProto(value)))163	def to_json(self):164		return self.hv.to_json()165class IP4SrcNotEq(Pred):166	def __init__(self, value, mask = None):167		assert(type(value) == str or type(value == unicode))168		if mask != None:169			assert type(mask) == int170		self.hv = Not(Test(IP4Src(value, mask)))171	def to_json(self):172		return self.hv.to_json()173class IP4DstNotEq(Pred):174	def __init__(self, value, mask = None):175		assert(type(value) == str or type(value == unicode))176		if mask != None:177			assert type(mask) == int178		self.hv = Not(Test(IP4Dst(value, mask)))179	def to_json(self):180		return self.hv.to_json()181class TCPSrcPortNotEq(Pred):182	def __init__(self, value):183		if (type(value)) == str:184			value = int(value)185		assert(type(value) == int and value >= 0)186		self.hv = Not(Test(IPProto(value)))187	def to_json(self):188		return self.hv.to_json()189class TCPDstPortNotEq(Pred):190	def __init__(self, value):191		if (type(value)) == str:192			value = int(value)193		assert(type(value) == int and value >= 0)194		self.hv = Not(Test(IPProto(value)))195	def to_json(self):196		return self.hv.to_json()197########## Set___198class SetEthSrc(Policy):199	def __init__(self, value):200		assert(type(value) == str or type(value == unicode))201		self.hv = Mod(EthSrc(value))202	def to_json(self):203		return self.hv.to_json()204class SetEthDst(Policy):205	def __init__(self, value):206		assert(type(value) == str or type(value == unicode))207		self.hv = Mod(EthDst(value))208	def to_json(self):209		return self.hv.to_json()210class SetVlan(Policy):211	def __init__(self, value):212		if (type(value)) == str:213			value = int(value)214		assert(type(value) == int and value >= 0)215		self.hv = Mod(Vlan(value))216	def to_json(self):217		return self.hv.to_json()218class SetVlanPcp(Policy):219	def __init__(self, value):220		if (type(value)) == str:221			value = int(value)222		assert(type(value) == int and value >= 0)223		self.hv = Mod(VlanPcp(value))224	def to_json(self):225		return self.hv.to_json()226class SetEthType(Policy):227	def __init__(self, value):228		if (type(value)) == str:229			value = int(value)230		assert(type(value) == int and value >= 0)231		self.hv = Mod(EthType(value))232	def to_json(self):233		return self.hv.to_json()234class SetIPProto(Policy):235	def __init__(self, value):236		if (type(value)) == str:237			value = int(value)238		assert(type(value) == int and value >= 0)239		self.hv = Mod(IPProto(value))240	def to_json(self):241		return self.hv.to_json()242class SetIP4Src(Policy):243	def __init__(self, value, mask = None):244		assert(type(value) == str or type(value == unicode))245		if mask != None:246			assert type(mask) == int247		self.hv = Mod(IP4Src(value, mask))248	def to_json(self):249		return self.hv.to_json()250class SetIP4Dst(Policy):251	def __init__(self, value, mask = None):252		assert(type(value) == str or type(value == unicode))253		if mask != None:254			assert type(mask) == int255		self.hv = Mod(IP4Dst(value, mask))256	def to_json(self):257		return self.hv.to_json()258class SetTCPSrcPort(Policy):259	def __init__(self, value):260		if (type(value)) == str:261			value = int(value)262		assert(type(value) == int and value >= 0)263		self.hv = Mod(IPProto(value))264	def to_json(self):265		return self.hv.to_json()266class SetTCPDstPort(Policy):267	def __init__(self, value):268		if (type(value)) == str:269			value = int(value)270		assert(type(value) == int and value >= 0)271		self.hv = Mod(IPProto(value))272	def to_json(self):273		return self.hv.to_json()274############### Misc.275class Send(Policy):276	def __init__(self, value):277		if (type(value)) == str:278			value = int(value)279		assert(type(value) == int and value >= 1 and value <= 65535)280		self.hv = Mod(Location(Physical(value)))281	def to_json(self):282		return self.hv.to_json()283class SendToController(Policy):284	def __init__(self, value):285		assert(type(value) == str or type(value == unicode))286		self.hv = Mod(Location(Pipe(value)))287	def to_json(self):...

graphql_inputs.py

Source:graphql_inputs.py

...25    province: str26    postalCode: str27    unitNumber: str28    poBox: str29    def to_json(self):30        return {31            "streetNumber": self.streetNumber,32            "streetName": self.streetName,33            "city": self.city,34            "province": self.province,35            "postalCode": self.postalCode,36            "unitNumber": self.unitNumber,37            "poBox": self.poBox38        }39 40@strawberry.input41class EmailInput:42    email: str43    def to_json(self): 44        return  {45            "email": self.email46        }47@strawberry.input48class ContactInfoInput:49    contact: str50    def to_json(self): 51        return  {52            "contact": self.contact53        }54@strawberry.input55class LandlordInfoInput:56    fullName: str57    receiveDocumentsByEmail: bool58    emails: List[EmailInput]59    contactInfo: bool60    contacts: List[ContactInfoInput]61    def to_json(self): 62        return  {63            "fullName": self.fullName,64            "receiveDocumentsByEmail": self.receiveDocumentsByEmail,65            "contactInfo": self.contactInfo,66            "contacts": [contact.to_json() for contact in self.contacts],67            "emails": [email.to_json() for email in self.emails]68        }69@strawberry.input70class ParkingDescriptionInput:71    description: str72    def to_json(self): 73        return {74            "description": self.description75        }76@strawberry.input77class RentalAddressInput:78    streetNumber: str79    streetName: str80    city: str81    province: str82    postalCode: str83    unitName: str84    isCondo: bool85    parkingDescriptions: List[ParkingDescriptionInput]86    def to_json(self):87        return {88            "streetNumber": self.streetNumber,89            "streetName": self.streetName,90            "city": self.city,91            "province": self.province,92            "postalCode": self.postalCode,93            "unitName": self.unitName,94            "isCondo": self.isCondo,95            "parkingDescriptions": [parkingDescription.to_json() for parkingDescription in self.parkingDescriptions]96        }97@strawberry.input98class RentServiceInput:99    name: str100    amount: str101    def to_json(self):102        return {103            "name": self.name,104            "amount": self.amount105        }106@strawberry.input107class PaymentOptionInput:108    name: str109    def to_json(self):110        return {111            "name": self.name112        }113@strawberry.input114class RentInput:115    baseRent: str116    rentMadePayableTo: str117    rentServices: List[RentServiceInput]118    paymentOptions: List[PaymentOptionInput]119    def to_json(self):120        return {121            "baseRent": self.baseRent,122            "rentMadePayableTo": self.rentMadePayableTo,123            "rentServices": [rentService.to_json() for rentService in self.rentServices],124            "paymentOptions": [paymentOption.to_json() for paymentOption in self.paymentOptions]125        }126@strawberry.input127class RentalPeriodInput:128    rentalPeriod: str129    endDate: str130    def to_json(self):131        return {132            "rentalPeriod": self.rentalPeriod,133            "endDate": self.endDate134        }135@strawberry.input136class PartialPeriodInput:137    amount: str138    dueDate: str139    startDate: str140    endDate: str141    isEnabled: bool142    def to_json(self):143        return {144            "amount": self.amount,145            "dueDate": self.dueDate,146            "startDate": self.startDate,147            "endDate": self.endDate,148            "isEnabled": self.isEnabled149        }150@strawberry.input151class TenancyTermsInput:152    rentalPeriod: RentalPeriodInput153    startDate: str154    rentDueDate: str155    paymentPeriod: str156    partialPeriod: PartialPeriodInput157    def to_json(self):158        return {159            "startDate": self.startDate,160            "rentDueDate": self.rentDueDate,161            "paymentPeriod": self.paymentPeriod,162            "rentalPeriod": self.rentalPeriod.to_json(),163            "partialPeriod": self.partialPeriod.to_json()164        }165    166@strawberry.input167class DetailInput:168    detail: str169    def to_json(self):170        return {171            "detail": self.detail.replace("$", "\$")172        }173@strawberry.input174class ServiceInput:175    name: str176    isIncludedInRent: bool177    isPayPerUse: Optional[bool]178    details: List[DetailInput]179    def to_json(self):180        return {181            "name": self.name,182            "isIncludedInRent": self.isIncludedInRent,183            "isPayPerUse": self.isPayPerUse,184            "details": [detail.to_json() for detail in self.details]185        }186@strawberry.input187class UtilityInput:188    name: str189    responsibility: str190    details: List[DetailInput]191    def to_json(self):192        return {193            "name": self.name,194            "responsibility": self.responsibility,195            "details": [detail.to_json() for detail in self.details]196        }197@strawberry.input198class RentDiscoutInput:199    name: str200    amount: str201    details: List[DetailInput]202    def to_json(self):203        return {204            "name": self.name,205            "amount": self.amount,206            "details": [detail.to_json() for detail in self.details]207        }208@strawberry.input209class RentDepositInput:210    name: str211    amount: str212    details: List[DetailInput]213    def to_json(self):214        return {215            "name": self.name,216            "amount": self.amount,217            "details": [detail.to_json() for detail in self.details]218        }219@strawberry.input220class AdditionalTermInput:221    name: str 222    details: List[DetailInput]223    def to_json(self):224        return {225            "name": self.name,226            "details": [detail.to_json() for detail in self.details]227        }228    229@strawberry.input230class TenantNameInput:231    name: str232    def to_json(self):233        return {234            "name": self.name235        }236@strawberry.input237class LeaseInput:238    landlordInfo: LandlordInfoInput239    landlordAddress: LandlordAddressInput240    rentalAddress: RentalAddressInput241    rent: RentInput242    tenancyTerms: TenancyTermsInput243    services: List[ServiceInput]244    utilities: List[UtilityInput]245    rentDeposits: List[RentDepositInput]246    rentDiscounts: List[RentDiscoutInput]247    additionalTerms: List[AdditionalTermInput]248    tenantNames: List[TenantNameInput]249    def to_json(self):250        return {251            "landlordInfo": self.landlordInfo.to_json(),252            "landlordAddress": self.landlordAddress.to_json(),253            "rentalAddress": self.rentalAddress.to_json(),254            "rent": self.rent.to_json(),255            "tenancyTerms": self.tenancyTerms.to_json(),256            "services": [service.to_json() for service in self.services],257            "utilities": [utility.to_json() for utility in self.utilities],258            "rentDiscounts": [rentDiscount.to_json() for rentDiscount in self.rentDiscounts],259            "rentDeposits": [rentDeposit.to_json() for rentDeposit in self.rentDeposits],260            "additionalTerms": [additionalTerm.to_json() for additionalTerm in self.additionalTerms],261            "tenantNames": [tenantName.to_json() for tenantName in self.tenantNames]262        }263  264@strawberry.input265class HouseInput:266    firebaseId: str...

constraint.py

Source:constraint.py

1from .version import Version2class Constraint(object):3  def __init__(self) -> None:4    super().__init__()5  def to_json(self):6    pass7class ConstraintExactly(Constraint):8  def __init__(self, v: Version) -> None:9    super().__init__()10    self.v = v11  def to_json(self):12    return {"exactly": self.v.to_json()}13class ConstraintGeq(Constraint):14  def __init__(self, v: Version) -> None:15    super().__init__()16    self.v = v17  def to_json(self):18    return {"geq": self.v.to_json()}19class ConstraintGt(Constraint):20  def __init__(self, v: Version) -> None:21    super().__init__()22    self.v = v23  def to_json(self):24    return {"gt": self.v.to_json()}25class ConstraintLeq(Constraint):26  def __init__(self, v: Version) -> None:27    super().__init__()28    self.v = v29  def to_json(self):30    return {"leq": self.v.to_json()}31class ConstraintLt(Constraint):32  def __init__(self, v: Version) -> None:33    super().__init__()34    self.v = v35  def to_json(self):36    return {"lt": self.v.to_json()}37class ConstraintCaret(Constraint):38  def __init__(self, v: Version) -> None:39    super().__init__()40    self.v = v41  def to_json(self):42    return {"caret": self.v.to_json()}43class ConstraintTilde(Constraint):44  def __init__(self, v: Version) -> None:45    super().__init__()46    self.v = v47  def to_json(self):48    return {"tilde": self.v.to_json()}49class ConstraintAnd(Constraint):50  def __init__(self, left: Constraint, right: Constraint) -> None:51    super().__init__()52    self.left = left53    self.right = right54  def to_json(self):55    return {"and": {"left": self.left.to_json(), "right": self.right.to_json()}}56class ConstraintOr(Constraint):57  def __init__(self, left: Constraint, right: Constraint) -> None:58    super().__init__()59    self.left = left60    self.right = right61  def to_json(self):62    return {"or": {"left": self.left.to_json(), "right": self.right.to_json()}}63  64class ConstraintWildcardBug(Constraint):65  def __init__(self, major: int, minor: int) -> None:66    super().__init__()67    self.major = major68    self.minor = minor69  def to_json(self):70    return {"wildcardBug": {"major": self.major, "minor": self.minor}}71class ConstraintWildcardMinor(Constraint):72  def __init__(self, major: int) -> None:73    super().__init__()74    self.major = major75  76  def to_json(self):77    return {"wildcardMinor": {"major": self.major}}78class ConstraintWildcardMajor(Constraint):79  def __init__(self) -> None:80    super().__init__()81  def to_json(self):82    return {"wildcardMajor": None}83class ConstraintNot(Constraint):84  def __init__(self, c: Constraint) -> None:85    super().__init__()86    self.c = c87  88  def to_json(self):...

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