Repository Issue Activity (beta)

#1659 Scalar return for check in polars-backed model fails on validation with `lazy=True`

#2511 Schema-level dtype cannot be serialized: to_yaml raises RepresenterError, to_json raises TypeError

#2510 Column default is dropped by to_yaml/to_json, so add_missing_columns stops accepting frames after a round trip

#2509 CI: the python-3.11 macos-latest pyspark job dies with OutOfMemoryError: unable to create native thread

#2505 `Check.unique_values_eq` cannot be serialized: to_yaml raises `RepresenterError`, to_json raises `TypeError` (frozenset)

#2503 `MultiIndex` options (`strict`, `ordered`, `coerce`, `unique`, `name`) are dropped by to_yaml/to_json/to_script, so a reloaded schema enforces different constraints

#928 AttributeError: Can't pickle local object 'Check.greater_than.<locals>._greater_than'

#1830 pa.Column(drop_invalid_rows=True) has no effect for Pandas DataFrames

#1896 Add `stacklevel=2` to all warnings and add linter rule preventing regressions in future warning calls.

#2497 Check(name=...) is documented but makes the check vanish from to_yaml/to_json/to_script, so the constraint is lost on reload

#2496 [bug] Decimal scale guard checks only the upper bound, so a negative scale leaks "Format specifier missing precision"

#2472 User-declared parsers are silently ignored on the polars backend

#1098 Lazy validation crashes for dictionary columns.

#2491 `@check_types` raises `AttributeError` on any `DataFrame[T]` annotation where `T` is a `TypeVar`

#1280 Using TypedDict on a DataFrameModel column bypasses `nullable=True`

#2293 validation on StringDtype columns allow any object

#1851 check_types argument inplace ignored

#2008 str_matches fail with "KeyError: <class 'pandera.api.pyspark.types.PysparkDataframeColumnObject'>" on pyspark dataframe

#1839 Pendulum datetime timezone bug

#2147 pandera-geopandas downgrades geopandas to version 0.9 when installing from conda-forge

#2419 Feature request: support Pydantic v2-style model_config: ConfigDict in addition to nested class Config

#868 Nullable columns in ModelSchema result in TypeError when converting to Hypothesis strategy

#2463 Polars backend: str col defaults are resolved as col references by add_missing_columns

#2482 `ShapeError` on polars pre-release

#2459 Polars backend: add_missing_columns raises ColumnNotFoundError when an optional column is absent