pandera.extensions#
Extensions module, for backwards compatibility.
- class pandera.extensions.CheckType(value)[source]#
Bases:
enum.Enum
Check types for registered check methods.
- VECTORIZED = 1#
Check applied to a Series or DataFrame
- ELEMENT_WISE = 2#
Check applied to an element of a Series or DataFrame
- GROUPBY = 3#
Check applied to dictionary of Series or DataFrames.
- pandera.extensions.register_builtin_check(fn=None, strategy=None, _check_cls=<class 'pandera.api.checks.Check'>, **outer_kwargs)[source]#
Register a check method to the Check namespace.
This is the primary way for extending the Check api to define additional built-in checks.
- pandera.extensions.register_check_method(check_fn=None, *, statistics=None, supported_types=(<class 'pandas.core.frame.DataFrame'>, <class 'pandas.core.series.Series'>), check_type='vectorized', strategy=None)[source]#
Registers a function as a
Check
method.See the user guide for more details.
- Parameters
check_fn – check function to register. The function should take one positional argument for the object to validate and additional keyword-only arguments for the check statistics.
statistics (
Optional
[List
[str
]]) – list of keyword-only arguments in thecheck_fn
, which serve as the statistics needed to serialize/de-serialize the check and generate data if astrategy
function is provided.supported_types (
Union
[type
,Tuple
,List
]) – the pandas type(s) supported by the check function. Valid values arepd.DataFrame
,pd.Series
, or a list/tuple of(pa.DataFrame, pa.Series)
if both types are supported.check_type (
Union
[CheckType
,str
]) –the expected input of the check function. Valid values are
CheckType
enums or{"vectorized", "element_wise", "groupby"}
. The input signature ofcheck_fn
is determined by this argument:if
vectorized
, the first positional argument ofcheck_fn
should be one of thesupported_types
.if
element_wise
, the first positional argument ofcheck_fn
should be a single scalar element in the pandas Series or DataFrame.if
groupby
, the first positional argument ofcheck_fn
should be a dictionary mapping group names to subsets of the Series or DataFrame.
strategy – data-generation strategy associated with the check function.
- Returns
register check function wrapper.