https://github.com/luke100000/immersiveapi

A diverse set of API endpoints
https://github.com/luke100000/immersiveapi

Last synced: about 1 month ago
JSON representation

A diverse set of API endpoints

• Host: GitHub
• URL: https://github.com/luke100000/immersiveapi
• Owner: Luke100000
• Created: 2023-08-10T13:21:58.000Z (over 1 year ago)
• Default Branch: master
• Last Pushed: 2024-09-16T10:41:33.000Z (about 2 months ago)
• Last Synced: 2024-09-16T12:20:21.068Z (about 2 months ago)
• Language: Python
• Size: 3.47 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# ImmersiveAPI

A diverse set of API endpoints for various projects to avoid overhead introduced by creating new repos, deployments,

etc.

## Structure

* `modules` - Each directory represents a module and contains at least a `.py` with the same name, containing the

  initializer.

* `common` - Shared code between modules

* `cache` - Persistent cache for data, each module should have its own subdirectory

* `temp` - Temporary files, each module should clean up after the task is done

* `data` - Static data

* `config.toml` / `default_config.toml` - Used to toggle modules and pass additional config

## Module

Each module is a group of **self-contained, async, thread safe** endpoints.

````py

from main import Configurator

def init(configurator: Configurator):

    configurator.register("Name", "Description")

    @configurator.post("/v1/your_module/your_endpoint")

    async def your_endpoint():

        return {"hello": "world"}

````

## Heavy lifting

For heavy background work, use the worker process pool.

Either use the primary executor, shared among all endpoints:

```py

from common.worker import get_primary_executor

def generate_text():

    return "Hello, world!"

async def your_endpoint():

    # noinspection PyUnusedLocal

    result = await get_primary_executor().submit(

        0,  # priority

        generate_text,

        # args...

        # kwargs...

    )

```

Or create a private executor for your module:

```py

from common.worker import Executor

executor = Executor(1)

```

## Not process-safe

Do not launch with multiple workers, not all operations are process-safe, and especially the ML endpoints would blow up in memory. Use (background) workers instead.