How to solve the problem of Pylance type detection of custom decorators in Python?

Conflict and solution between Pylance and Python custom decorator type prompts

Python decorators are powerful code reuse tools, but when using custom decorators, static type checkers (such as Pylance) may experience type prompt errors, especially when the decorator modifies the return type of the function. This article will demonstrate a common problem and solution.

Problem: Pylance cannot correctly identify the function return type modified by a custom decorator. For example, a decorator modifies the return type of a function, but Pylance still displays the return type of the original function, resulting in a type warning.

Sample code:

 def execute(func):
    def inner_wrapper(*args, **kwargs) -> result[any]: # Pylance problem lies with session.begin() as session:
            result = session.execute(func(*args, **kwargs))
            return result
    return inner_wrapper

@execute
def query_data_source(start_id: int = 1, max_results_amount: int = 10) -> select:
    stmt = select(
        datasource.id,
        datasource.name,
        datasource.source_url,
        datasource.author,
        datasource.description,
        datasource.cover_image_url,
        datasource.start_date,
        datasource.end_date,
    ).where(datasource.id >= start_id).limit(max_results_amount).order_by(datasource.id)
    return stmt

The query_data_source function actually returns result[any] type, but Pylance still recognizes it as select type, raising a type warning.

Solution: Use typing.Callable to declare the return type of the decorator more accurately, thus helping Pylance to correctly understand the behavior of the decorator.

Modified code:

 from typing import Callable, Any

def execute(func: Callable[..., Any]) -> Callable[..., Result[Any]]: # Use typing.Callable
    def inner_wrapper(*args, **kwargs) -> Result[Any]:
        with Session.begin() as session:
            result = session.execute(func(*args, **kwargs))
            return result
    return inner_wrapper

@execute
def query_data_source(start_id: int = 1, max_results_amount: int = 10) -> select:
    stmt = select(
        datasource.id,
        datasource.name,
        datasource.source_url,
        datasource.author,
        datasource.description,
        datasource.cover_image_url,
        datasource.start_date,
        datasource.end_date,
    ).where(datasource.id >= start_id).limit(max_results_amount).order_by(datasource.id)
    return stmt

By using Callable[..., Result[Any]] as the return type prompt in the execute decorator, Pylance can accurately infer the actual return type of the query_data_source function, thereby eliminating the type warning. ... means that the number of parameters is variable, Any means that the parameter type is variable. Make sure that Result and select types are correctly defined.

This approach effectively solves the limitations of Pylance's return type inference when handling custom decorators, thereby improving the readability and maintainability of the code.

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