pandera-tool 0.1.0

Tool for pandera.

Pandera-Tool

Pandera-Tool is a package for pandera.

• DataFrame type definition
• Validation
• Type coerce

Installation

pip install pandera-tool

Example

DataFrame type definition

from io import StringIO
from typing import Tuple
import pandas as pd
from pandera import Field, SchemaModel
from pandera.errors import SchemaError
from pandera.typing import Series
from pandera_tool import check_annotations, dtype, to_dataframe, to_schema

@to_dataframe
class DataFrameIn(SchemaModel):
    Name: Series[str] = Field()

    class Config:
        strict = True

@to_dataframe
class DataFrameOut(to_schema(DataFrameIn)):
    Age: Series[int] = Field()

    class Config:
        strict = True

Validation

@check_annotations
def func_ok(df: DataFrameIn) -> DataFrameOut:
    return df.assign(Age=2)

@check_annotations
def func_err(df: DataFrameIn) -> DataFrameOut:
    return df.assign(Age="")

@check_annotations
def func_err_output_tuple(df: DataFrameIn) -> Tuple[DataFrameOut]:
    return (df.assign(Age=""),)

df_ok = pd.DataFrame({"Name": ["1"]})
df_ng = pd.DataFrame({"Name": [1]})

func_ok(df_ok)  # OK

try:
    func_ok(df_ng)  # Input error
except SchemaError as e:
    print(e)

try:
    func_err(df_ok)  # Output error
except SchemaError as e:
    print(e)

try:
    func_err_output_tuple(df_ok)  # Output error
except SchemaError as e:
    print(e)

Type coerce

df1 = pd.read_csv(StringIO("Name\n1"))
try:
    func_ok(df1)  # Input error
except SchemaError as e:
    print(e)

df2 = pd.read_csv(StringIO("Name\n1"), dtype=dtype(DataFrameIn))
func_ok(df2)  # OK

df3 = df_ng.astype(dtype(DataFrameIn))
func_ok(df3)  # OK