獲取“TypeError：無法識別輸出參數的類型：<class 'str'> " 在 Pandera 裝飾器中使用類函數時</class>

Question

我正在嘗試使用 Python 包“Pandera”中的裝飾器，但我很難讓它們使用類。

首先，我為 Pandera 創建模式：

from pandera import Column, Check
import yaml
in_ = pa.DataFrameSchema(
    {
        "Name": Column(object, nullable=True),
        "Height": Column(object, nullable=True),
    })

with open("./in_.yml", "w") as file:
    yaml.dump(in_, file)

out_ = pa.DataFrameSchema(
    {
        "Name": Column(object, nullable=True),
        "Height": Column(object, nullable=True),
    })
with open("./out_.yml", "w") as file:
    yaml.dump(out_, file)

接下來我用類創建test.py文件：

from pandera import check_io
import pandas as pd

class TransformClass():

    with open("./in_.yml", "r") as file:
        in_ = file.read()
    with open("./out_.yml", "r") as file:
        out_ = file.read()

    @staticmethod
    @check_io(df=in_, out=out_)
    def func(df: pd.DataFrame) -> pd.DataFrame:
        return df

最后我導入了這個類：

from test import TransformClass
data = {'Name': [np.nan, 'Princi', 'Gaurav', 'Anuj'],
        'Height': [5.1, 6.2, 5.1, 5.2],
        'Qualification': ['Msc', 'MA', 'Msc', 'Msc']}
df = pd.DataFrame(data)
TransformClass.func(df)

我正進入（狀態：

File C:\Anaconda3\envs\py310\lib\site-packages\pandera\decorators.py:464, in check_io.<locals>._wrapper(fn, instance, args, kwargs)
    462     out_schemas = []
    463 else:
--> 464     raise TypeError(
    465         f"type of out argument not recognized: {type(out)}"
    466     )
    468 wrapped_fn = fn
    469 for input_getter, input_schema in inputs.items():
    470     # pylint: disable=no-value-for-parameter

TypeError: type of out argument not recognized: <class 'str'>

任何幫助將不勝感激

Answer 1

check_io裝飾器需要pandera.DataFrameSchema類型的參數。 但是，它被傳遞給類型為 _out 的str因為它是_out file.read()的輸出。

Pandera 文檔解釋了check_io裝飾器期望的類型。

一個解決方案是將file.read()行的輸出傳遞給 Pandera 構造函數，可能需要進行一些轉換：

out_ = yaml.safe_load(file.read())

Answer 2

感謝@grbeazley，這里是完整的解決方案：

from pandera import Column, Check
import yaml

in_ = pa.DataFrameSchema(
    {
        "Name": Column(object, nullable=True),
        "Height": Column(object, nullable=True),
    })
with open("in_.yml", "w") as file:
    yaml.dump(in_.to_yaml(), file)

with open("./in_.yml", "r") as file:
    in_ = yaml.safe_load(file.read())

_ = pa.DataFrameSchema.from_yaml(in_)