pandera.engines.pandas_engine.PythonTypedDict

class pandera.engines.pandas_engine.PythonTypedDict(special_type=None)

A datatype to support python generics.

Attributes

auto_coerce	Whether to force coerce to be True in all cases
coercion_model
continuous	Whether the number data type is continuous.
generic_type
special_type

Methods

__init__(special_type=None)

check(pandera_dtype, data_container=None)

Check that data container has the expected type.

Return type:

Union[bool, Iterable[bool]]

coerce(data_container)

Coerce data container to the specified data type.

Return type:

Union[Series, DataFrame]

coerce_value(value)

Coerce an value to a particular type.

Return type:

Any

try_coerce(data_container)

Coerce data container to the data type, raises a ParserError if the coercion fails :raises: ParserError: if coercion fails

Return type:

Union[Series, DataFrame]

type(fields=<sentinel>, /, *, total=True, closed=False, **kwargs)

A simple typed namespace. At runtime it is equivalent to a plain dict.

TypedDict creates a dictionary type such that a type checker will expect all instances to have a certain set of keys, where each key is associated with a value of a consistent type. This expectation is not checked at runtime.

Usage:

class Point2D(TypedDict):
    x: int
    y: int
    label: str

a: Point2D = {'x': 1, 'y': 2, 'label': 'good'}  # OK
b: Point2D = {'z': 3, 'label': 'bad'}           # Fails type check

assert Point2D(x=1, y=2, label='first') == dict(x=1, y=2, label='first')

The type info can be accessed via the Point2D.__annotations__ dict, and the Point2D.__required_keys__ and Point2D.__optional_keys__ frozensets. TypedDict supports an additional equivalent form:

Point2D = TypedDict('Point2D', {'x': int, 'y': int, 'label': str})

By default, all keys must be present in a TypedDict. It is possible to override this by specifying totality:

class Point2D(TypedDict, total=False):
    x: int
    y: int

This means that a Point2D TypedDict can have any of the keys omitted. A type checker is only expected to support a literal False or True as the value of the total argument. True is the default, and makes all items defined in the class body be required.

The Required and NotRequired special forms can also be used to mark individual keys as being required or not required:

class Point2D(TypedDict):
    x: int  # the "x" key must always be present (Required is the default)
    y: NotRequired[int]  # the "y" key can be omitted

See PEP 655 for more details on Required and NotRequired.

__call__(data_container)

Coerce data container to the data type.