Unlock 30% off on Manual Testing Annual Plans this Holiday Season.

Copied to Clipboard!

How to use to_json method in keyboard

Best Python code snippet using keyboard

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):...

Automation Testing Tutorials

Learn to execute automation testing from scratch with LambdaTest Learning Hub. Right from setting up the prerequisites to run your first automation test, to following best practices and diving deeper into advanced test scenarios. LambdaTest Learning Hubs compile a list of step-by-step guides to help you be proficient with different test automation frameworks i.e. Selenium, Cypress, TestNG etc.