pandera 0.8.0

0.8.0: Integrate with Dask, Koalas, Modin, Pydantic, Mypy

on Python PyPI

import dask.dataframe as dd
import pandas as pd
import pandera as pa

from pandera.typing import dask, koalas, modin

class Schema(pa.SchemaModel):
    state: Series[str]
    city: Series[str]
    price: Series[int] = pa.Field(in_range={"min_value": 5, "max_value": 20})

@pa.check_types
def dask_function(ddf: dask.DataFrame[Schema]) -> dask.DataFrame[Schema]:
    return ddf[ddf["state"] == "CA"]

@pa.check_types
def koalas_function(df: koalas.DataFrame[Schema]) -> koalas.DataFrame[Schema]:
    return df[df["state"] == "CA"]

@pa.check_types
def modin_function(df: modin.DataFrame[Schema]) -> modin.DataFrame[Schema]:
    return df[df["state"] == "CA"]

schema: pa.DataFrameSchema = Schema.to_schema()

schema(dask_df)
schema(modin_df)
schema(koalas_df)

import pandas as pd
import pandera as pa
from pandera.typing import DataFrame, Series
import pydantic


class SimpleSchema(pa.SchemaModel):
    str_col: Series[str] = pa.Field(unique=True)


class PydanticModel(pydantic.BaseModel):
    x: int
    df: DataFrame[SimpleSchema]


valid_df = pd.DataFrame({"str_col": ["hello", "world"]})
PydanticModel(x=1, df=valid_df)

invalid_df = pd.DataFrame({"str_col": ["hello", "hello"]})
PydanticModel(x=1, df=invalid_df)

Traceback (most recent call last):
...
ValidationError: 1 validation error for PydanticModel
df
series 'str_col' contains duplicate values:
1    hello
Name: str_col, dtype: object (type=value_error)

import pandera as pa
from pandera.typing import DataFrame, Series

class Schema(pa.SchemaModel):
    id: Series[int]
    name: Series[str]

class SchemaOut(pa.SchemaModel):
    age: Series[int]

class AnotherSchema(pa.SchemaModel):
    foo: Series[int]

def fn(df: DataFrame[Schema]) -> DataFrame[SchemaOut]:
    return df.assign(age=30).pipe(DataFrame[SchemaOut])  # mypy okay

def fn_pipe_incorrect_type(df: DataFrame[Schema]) -> DataFrame[SchemaOut]:
    return df.assign(age=30).pipe(DataFrame[AnotherSchema])  # mypy error
    # error: Argument 1 to "pipe" of "NDFrame" has incompatible type "Type[DataFrame[Any]]";
    # expected "Union[Callable[..., DataFrame[SchemaOut]], Tuple[Callable[..., DataFrame[SchemaOut]], str]]"  [arg-type]  # noqa

schema_df = DataFrame[Schema]({"id": [1], "name": ["foo"]})
pandas_df = pd.DataFrame({"id": [1], "name": ["foo"]})

fn(schema_df)  # mypy okay
fn(pandas_df)  # mypy error
# error: Argument 1 to "fn" has incompatible type "pandas.core.frame.DataFrame";
# expected "pandera.typing.pandas.DataFrame[Schema]"  [arg-type]