https://github.com/zackees/template-docker-fastapi-site

Fastapi for the backend, npm based front end, runs in docker and can be fired up immediately in Render.com or DigitalOcean
https://github.com/zackees/template-docker-fastapi-site

Last synced: about 1 month ago
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Fastapi for the backend, npm based front end, runs in docker and can be fired up immediately in Render.com or DigitalOcean

• Host: GitHub
• URL: https://github.com/zackees/template-docker-fastapi-site
• Owner: zackees
• License: mit
• Created: 2023-12-16T02:19:50.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2024-04-10T05:22:02.000Z (9 months ago)
• Last Synced: 2024-04-10T06:28:17.102Z (9 months ago)
• Language: Python
• Size: 151 KB
• Stars: 0
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# template-docker-fastapi-site

![image](https://github.com/TechWatchProject/media-bias-scorer/assets/6856673/25e239e8-1600-4805-870c-877abe8c7be3)

# Design

This is to be a fastapi app. Use this template: https://github.com/zackees/template-docker-fastapi-site

### The app will have the following endpoints:

  * POST `/api/youtube/channel`

    * Header: Auth token (just make up a sufficiently large random token)

    * body: the channel id

    * returns: a json response

      * ok: { ok: True, rank: float, err: None }

      * not found: { ok: Fale, rank: None, err: "Not Found" }

  * POST `/api/youtube/video`

    * Header: Autho token

    * body: the video id (for example ?watch=XXXX where XXXX is the video id)

    * returns: a json response

      * ok: `{ ok: True, rank: float, channel_id: str, err: None }`

      * not found: `{ ok: False, rank: None, channel_id: None, err: "Not Found" }`

## Endpoint management:

  * All endpoints will input pydantic objects, and return pydantic objects.

    * Pydantic models convert to json for input and outputs, and are type checked

    * They will also become part of the openapi that's automatically generated for the fastapi site

## Database

  * Use the `postgres` database in render.com

  * Use the `sqlaclchemy` ORM to model and access the `postgres`

  * Models.py will model the `postgres` database

  * db.py will use models.py to query, and return data as a pydantic object that will be returned

  * It's important to note that the api endpoints should be as simple as possible, with db.py doing most of the work.

## Background worker

  * A background worker will periodically scrape youtube and collect data on all videos to target channels. We will use yt-dlp for this task.

  * But don't worry too much about how this is scheduled.

# First deliverables

  * Generate all the boilerplate listed in this document and then contact me for next steps.