Avoiding global variables in fastapi managing a python subprocesses

When working with FastAPI and managing Python subprocesses, it is important to avoid using global variables. Global variables can lead to unexpected behavior and make the code difficult to maintain and debug. In this article, we will explore three different ways to solve the problem of avoiding global variables in FastAPI when managing Python subprocesses.

Option 1: Using Dependency Injection

One way to avoid global variables in FastAPI is by using dependency injection. Dependency injection allows us to pass dependencies into our functions or classes instead of relying on global variables. This promotes better code organization and testability.

from fastapi import Depends, FastAPI
from subprocess import Popen, PIPE

app = FastAPI()

def get_subprocess() -> Popen:
    return Popen(["python", "subprocess_script.py"], stdout=PIPE)

@app.get("/")
def read_root(subprocess: Popen = Depends(get_subprocess)):
    output, _ = subprocess.communicate()
    return {"output": output.decode()}

if __name__ == "__main__":
    uvicorn.run(app, host="0.0.0.0", port=8000)

In this example, we define a function get_subprocess that returns a new instance of the subprocess. We then use the Depends function from FastAPI to inject the subprocess dependency into our route function. This ensures that each request gets its own subprocess instance and avoids the need for global variables.

Option 2: Using a Singleton Class

Another way to avoid global variables is by using a singleton class. A singleton class is a class that can only have one instance. We can use a singleton class to manage the subprocess instance and ensure that only one instance is created and used throughout the application.

from fastapi import FastAPI
from subprocess import Popen, PIPE

class SubprocessManager:
    _instance = None

    def __new__(cls):
        if cls._instance is None:
            cls._instance = super().__new__(cls)
            cls._instance.subprocess = Popen(["python", "subprocess_script.py"], stdout=PIPE)
        return cls._instance

app = FastAPI()
subprocess_manager = SubprocessManager()

@app.get("/")
def read_root():
    output, _ = subprocess_manager.subprocess.communicate()
    return {"output": output.decode()}

if __name__ == "__main__":
    uvicorn.run(app, host="0.0.0.0", port=8000)

In this example, we define a singleton class SubprocessManager that creates and manages the subprocess instance. The __new__ method of the class ensures that only one instance of the class is created. We then use the subprocess_manager instance to access the subprocess in our route function.

Option 3: Using a Context Manager

A third option is to use a context manager to manage the subprocess instance. A context manager allows us to define a setup and teardown behavior for a block of code. We can use a context manager to create and close the subprocess instance when needed.

from fastapi import FastAPI
from subprocess import Popen, PIPE
from contextlib import contextmanager

@contextmanager
def subprocess_manager():
    subprocess = Popen(["python", "subprocess_script.py"], stdout=PIPE)
    try:
        yield subprocess
    finally:
        subprocess.terminate()

app = FastAPI()

@app.get("/")
def read_root():
    with subprocess_manager() as subprocess:
        output, _ = subprocess.communicate()
        return {"output": output.decode()}

if __name__ == "__main__":
    uvicorn.run(app, host="0.0.0.0", port=8000)

In this example, we define a context manager subprocess_manager that creates and terminates the subprocess instance. We use the yield statement to indicate the start and end of the block of code that should be executed with the subprocess instance. The with statement ensures that the subprocess is properly closed even if an exception occurs.

After exploring these three options, it is clear that using dependency injection with FastAPI’s Depends function is the best approach. It promotes better code organization, testability, and avoids the need for global variables. It also allows for easy swapping of dependencies and makes the code more modular and maintainable.

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