Hey everyone! I've been experimenting with a builder pattern in Python, focusing on achieving proper type hinting. I'm trying to create a pipeline that accommodates a variable number of steps. The pipeline should have input type `TIn` and output type `TOut`, inferred from the inner steps, with `TIn` being the input for the first step and `TOut` for the last one. Here's the code I've come up with:
```python
TIn = TypeVar("TIn")
TOut = TypeVar("TOut")
TNext = TypeVar("TNext")
class Step(ABC, Generic[TIn, TOut]):
def execute(self, data: TIn) -> TOut:
...
def create_process(step: Step[TIn, TOut]) -> "Process[TIn, TOut]":
return Process.start_static(step)
class Process(Generic[TIn, TOut]):
def __init__(self, steps: list[Step] | None = None):
self.steps: list[Step] = steps or []
@classmethod
def start_class(cls, step: Step[TIn, TOut]) -> "Process[TIn, TOut]":
return cls([step])
@staticmethod
def start_static(step: Step[TIn, TOut]) -> "Process[TIn, TOut]":
return Process([step])
def add_step(self, step: Step[TOut, TNext]) -> "Process[TIn, TNext]":
return Process(self.steps + [step])
def execute(self, data: TIn) -> TOut:
current = data
for step in self.steps:
print(type(step))
current = step.execute(current)
return cast(TOut, current)
class IntToStr(Step[int, str]):
def execute(self, data: int) -> str:
return str(data)
class StrToBool(Step[str, bool]):
def execute(self, data: str) -> bool:
return data != ""
process = create_process(IntToStr()).add_step(StrToBool())
process = Process().add_step(IntToStr()).add_step(StrToBool())
process = Process.start_static(IntToStr()).add_step(StrToBool())
process = Process.start_class(IntToStr()).add_step(StrToBool())
process.execute(1)
```
From my experiments, the only way to correctly infer the input type is by using a method outside of my class. I'm curious if there's a workaround for this issue, or if I'm stuck with a factory method approach. It seems like `TIn` is not defined for the first step, leading to an unknown type being returned. Any insights would be greatly appreciated!
6 Answers
There are no strict guarantees on how generic arguments in classes are inferred, which can lead to discrepancies between type checkers. When you use a static method like `Process.start_static(...)`, it might not have the correct data to deduce the `Process[A, B]`. It's better to pass explicit generic parameters, or consider using instance-level method calls. You could also think about redefining your approach to treat steps and pipelines similarly, which may lead to cleaner type handling.
The success of type inference can really depend on the type checker you're using. If you run `reveal_type` on your processes, you might get varied results. For example, using PyCharm returns some different outputs compared to tools like mypy. Just keep in mind that PEP 484 gives a general framework but doesn't dictate exact behaviors for inference across different tools.
It would be wise to avoid class-scoped variables in your `start_class`, `start_static`, and `add_step` methods—switching to method-scoped variables could greatly improve your type hinting accuracy. Also, consider using type annotations from Python 3.12 to streamline your code. Here are some playgrounds to help you test the changes: [mypy playground](https://mypy-play.net)
Don’t forget about `typing.Self`! It might make some of your type hinting easier and more clear in such contexts.
You might want to try using `Self` for your class/static methods instead of quoting `Process`. Also, don't forget to include `from __future__ import annotations` at the top of your file. It could simplify some of the type hinting.
You might want to check out a GitHub repository on Python patterns, particularly the Chain of Responsibility example. It could provide further clarity on structuring your code effectively with generics.

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