name: Issue Manager

on:
  schedule:
    - cron: "10 3 * * *"
  issue_comment:
    types:
      - created
  issues:
    types:
      - labeled
  pull_request_target:
    types:
      - labeled
  workflow_dispatch:

jobs:
  issue-manager:
    if: github.repository_owner == 'tiangolo'
    runs-on: ubuntu-latest
    steps:
      - name: Dump GitHub context
        env:

```Python
with open("file.txt") as file:
    file.read()
```

In recent versions of Python, there's also an **async context manager**. You would use it with `async with`:

```Python
async with lifespan(app):
    await do_stuff()
```

### Multiple Processes - An Example

In this example, there's a **Manager Process** that starts and controls two **Worker Processes**.

This Manager Process would probably be the one listening on the **port** in the IP. And it would transmit all the communication to the worker processes.

manager = ConnectionManager()


@app.get("/")
async def get():
    return HTMLResponse(html)


@app.websocket("/ws/{client_id}")
async def websocket_endpoint(websocket: WebSocket, client_id: int):
    await manager.connect(websocket)
    try:
        while True:
            data = await websocket.receive_text()

Underneath, the `open("./somefile.txt")` creates an object that is called a "Context Manager".

When the `with` block finishes, it makes sure to close the file, even if there were exceptions.

When you create a dependency with `yield`, **FastAPI** will internally create a context manager for it, and combine it with some other related tools.

### Using context managers in dependencies with `yield`

!!! warning

### Mehrere Prozesse – Ein Beispiel

Im folgenden Beispiel gibt es einen **Manager-Prozess**, welcher zwei **Workerprozesse** startet und steuert.

Dieser Manager-Prozess wäre wahrscheinlich derjenige, welcher der IP am **Port** lauscht. Und er würde die gesamte Kommunikation an die Workerprozesse weiterleiten.

Sie erfordern in der Regel komplexere Konfigurationen und einen Nachrichten-/Job-Queue-Manager wie RabbitMQ oder Redis, ermöglichen Ihnen jedoch die Ausführung von Hintergrundtasks in mehreren Prozessen und insbesondere auf mehreren Servern.

But Gunicorn supports working as a **process manager** and allowing users to tell it which specific **worker process class** to use. Then Gunicorn would start one or more **worker processes** using that class.

And **Uvicorn** has a **Gunicorn-compatible worker class**.

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So, in this case, you **would not** want to have a process manager like Gunicorn with Uvicorn workers, or Uvicorn using its own Uvicorn workers. You would want to have just a **single Uvicorn process** per container (but probably multiple containers).