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How to use handle_stat_dtype method in pandera

Best Python code snippet using pandera_python

io.py

Source:io.py

...27def _get_qualified_name(cls: type) -> str:28    return f"{cls.__module__}.{cls.__qualname__}"29def _serialize_check_stats(check_stats, dtype=None):30    """Serialize check statistics into json/yaml-compatible format."""31    def handle_stat_dtype(stat):32        if pandas_engine.Engine.dtype(dtypes.DateTime).check(33            dtype34        ) and hasattr(stat, "strftime"):35            # try serializing stat as a string if it's datetime-like,36            # otherwise return original value37            return stat.strftime(DATETIME_FORMAT)38        elif pandas_engine.Engine.dtype(dtypes.Timedelta).check(39            dtype40        ) and hasattr(stat, "delta"):41            # try serializing stat into an int in nanoseconds if it's42            # timedelta-like, otherwise return original value43            return stat.delta44        return stat45    # for unary checks, return a single value instead of a dictionary46    if len(check_stats) == 1:47        return handle_stat_dtype(list(check_stats.values())[0])48    # otherwise return a dictionary of keyword args needed to create the Check49    serialized_check_stats = {}50    for arg, stat in check_stats.items():51        serialized_check_stats[arg] = handle_stat_dtype(stat)52    return serialized_check_stats53def _serialize_dataframe_stats(dataframe_checks):54    """55    Serialize global dataframe check statistics into json/yaml-compatible56    format.57    """58    serialized_checks = {}59    for check_name, check_stats in dataframe_checks.items():60        # The case that `check_name` is not registered is handled in61        # `parse_checks` so we know that `check_name` exists.62        # infer dtype of statistics and serialize them63        serialized_checks[check_name] = _serialize_check_stats(check_stats)64    return serialized_checks65def _serialize_component_stats(component_stats):66    """67    Serialize column or index statistics into json/yaml-compatible format.68    """69    serialized_checks = None70    if component_stats["checks"] is not None:71        serialized_checks = {}72        for check_name, check_stats in component_stats["checks"].items():73            serialized_checks[check_name] = _serialize_check_stats(74                check_stats, component_stats["dtype"]75            )76    dtype = component_stats.get("dtype")77    if dtype:78        dtype = str(dtype)79    return {80        "dtype": dtype,81        "nullable": component_stats["nullable"],82        "checks": serialized_checks,83        **{84            key: component_stats.get(key)85            for key in [86                "name",87                "unique",88                "coerce",89                "required",90                "regex",91            ]92            if key in component_stats93        },94    }95def _serialize_schema(dataframe_schema):96    """Serialize dataframe schema into into json/yaml-compatible format."""97    from pandera import __version__  # pylint: disable=import-outside-toplevel98    statistics = get_dataframe_schema_statistics(dataframe_schema)99    columns, index, checks = None, None, None100    if statistics["columns"] is not None:101        columns = {102            col_name: _serialize_component_stats(column_stats)103            for col_name, column_stats in statistics["columns"].items()104        }105    if statistics["index"] is not None:106        index = [107            _serialize_component_stats(index_stats)108            for index_stats in statistics["index"]109        ]110    if statistics["checks"] is not None:111        checks = _serialize_dataframe_stats(statistics["checks"])112    return {113        "schema_type": "dataframe",114        "version": __version__,115        "columns": columns,116        "checks": checks,117        "index": index,118        "coerce": dataframe_schema.coerce,119        "strict": dataframe_schema.strict,120        "unique": dataframe_schema.unique,121    }122def _deserialize_check_stats(check, serialized_check_stats, dtype=None):123    def handle_stat_dtype(stat):124        try:125            if pandas_engine.Engine.dtype(dtypes.DateTime).check(dtype):126                return pd.to_datetime(stat, format=DATETIME_FORMAT)127            elif pandas_engine.Engine.dtype(dtypes.Timedelta).check(dtype):128                # serialize to int in nanoseconds129                return pd.to_timedelta(stat, unit="ns")130        except (TypeError, ValueError):131            return stat132        return stat133    if isinstance(serialized_check_stats, dict):134        # handle case where serialized check stats are in the form of a135        # dictionary mapping Check arg names to values.136        check_stats = {}137        for arg, stat in serialized_check_stats.items():138            check_stats[arg] = handle_stat_dtype(stat)139        return check(**check_stats)140    # otherwise assume unary check function signature141    return check(handle_stat_dtype(serialized_check_stats))142def _deserialize_component_stats(serialized_component_stats):143    dtype = serialized_component_stats.get("dtype")144    if dtype:145        dtype = pandas_engine.Engine.dtype(dtype)146    checks = serialized_component_stats.get("checks")147    if checks is not None:148        checks = [149            _deserialize_check_stats(150                getattr(Check, check_name), check_stats, dtype151            )152            for check_name, check_stats in checks.items()153        ]154    return {155        "dtype": dtype,...

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