获取“TypeError：无法识别输出参数的类型：<class 'str'> " 在 Pandera 装饰器中使用类函数时</class>

Question

我正在尝试使用 Python 包“Pandera”中的装饰器，但我很难让它们使用类。

首先，我为 Pandera 创建模式：

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)

接下来我用类创建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

最后我导入了这个类：

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)

我正进入（状态：

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'>

任何帮助将不胜感激

Answer 1

check_io装饰器需要pandera.DataFrameSchema类型的参数。 但是，它被传递给类型为 _out 的str因为它是_out file.read()的输出。

Pandera 文档解释了check_io装饰器期望的类型。

一个解决方案是将file.read()行的输出传递给 Pandera 构造函数，可能需要进行一些转换：

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

Answer 2

感谢@grbeazley，这里是完整的解决方案：

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_)