pandas 熊猫的 Pythonic 类型提示？
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Pythonic type hints with pandas?
提问by dangom
Let's take a simple function that takes a str and returns a dataframe:
让我们看一个简单的函数，它接受一个 str 并返回一个数据帧：
import pandas as pd
def csv_to_df(path):
return pd.read_csv(path, skiprows=1, sep='\t', comment='#')
What is the recommended pythonic way of adding type hints to this function?
向此函数添加类型提示的推荐 Pythonic 方法是什么？
If I ask python for the type of a DataFrame it returns pandas.core.frame.DataFrame.
The following won't work though, as it'll tell me that pandas is not defined.
如果我向 python 询问 DataFrame 的类型，它返回pandas.core.frame.DataFrame. 但是，以下内容不起作用，因为它会告诉我未定义Pandas。
def csv_to_df(path: str) -> pandas.core.frame.DataFrame:
return pd.read_csv(path, skiprows=1, sep='\t', comment='#')
回答by Georgy
Why not just use pd.DataFrame?
为什么不直接使用pd.DataFrame？
import pandas as pd
def csv_to_df(path: str) -> pd.DataFrame:
return pd.read_csv(path, skiprows=1, sep='\t', comment='#')
Result is the same:
结果是一样的：
> help(csv_to_df)
Help on function csv_to_df in module __main__:
csv_to_df(path:str) -> pandas.core.frame.DataFrame
回答by dangom
I'm currently doing the following:
我目前正在做以下事情：
from typing import TypeVar
PandasDataFrame = TypeVar('pandas.core.frame.DataFrame')
def csv_to_df(path: str) -> PandasDataFrame:
return pd.read_csv(path, skiprows=1, sep='\t', comment='#')
Which gives:
这使：
> help(csv_to_df)
Help on function csv_to_df in module __main__:
csv_to_df(path:str) -> ~pandas.core.frame.DataFrame
Don't know how pythonic that is, but it's understandable enough as a type hint, I find.
不知道那是多么pythonic，但我发现它作为类型提示是可以理解的。
回答by Keith
This is straying from the original question but building off of @dangom's answer using TypeVarand @Georgy's comment that there is no way to specify datatypes for DataFrame columns in type hints, you could use a simple work-around like this to specify datatypes in a DataFrame:
这与原始问题背道而驰，但基于@dangom 的回答使用TypeVar和@Georgy 的评论，即无法在类型提示中为 DataFrame 列指定数据类型，您可以使用这样的简单解决方法来指定 DataFrame 中的数据类型：
from typing import TypeVar
DataFrameStr = TypeVar("pandas.core.frame.DataFrame(str)")
def csv_to_df(path: str) -> DataFrameStr:
return pd.read_csv(path, skiprows=1, sep='\t', comment='#')
