https://github.com/fuodorov/yacinema
Web application online cinema
https://github.com/fuodorov/yacinema
authentication clickhouse django docker docker-compose elasticsearch etl fastapi flask gunicorn kafka mongo nginx postgresql pytest python uvicorn
Last synced: 3 months ago
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Web application online cinema
- Host: GitHub
- URL: https://github.com/fuodorov/yacinema
- Owner: fuodorov
- License: mit
- Created: 2021-09-12T09:20:23.000Z (almost 5 years ago)
- Default Branch: main
- Last Pushed: 2022-04-22T13:28:52.000Z (about 4 years ago)
- Last Synced: 2025-10-29T22:35:23.562Z (8 months ago)
- Topics: authentication, clickhouse, django, docker, docker-compose, elasticsearch, etl, fastapi, flask, gunicorn, kafka, mongo, nginx, postgresql, pytest, python, uvicorn
- Language: Python
- Homepage:
- Size: 1.57 MB
- Stars: 4
- Watchers: 2
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Online Movies
## Presentation
[Click here](docs/presentation)
## Architecture
## Running
### Development
Uses the default Django development server.
1. Rename *.env.dev.example* and *.env.streaming.dev.example* to *.env.dev* and *.env.streaming.dev* in envs directory.
2. Update the environment variables in the *.env.dev* and *.env.streaming.dev* file.
3. Build the images and run the containers:
```sh
$ docker-compose -f docker-compose.yml -f docker-compose.dev.yml up --build
```
Test it out at [http://localhost:8000](http://localhost:8000). The "movies_admin" and "movies_etl" folder is mounted into the container and your code changes apply automatically.
4. On first run, after initialising the database to fill the database with data:
```sh
$ docker exec movies_admin python utils/sqlite_to_postgres/load_data.py
```
5. On first run, after initialising the minio create a test bucket in the minio.
### Production
Uses gunicorn + nginx.
1. Rename *.env.prod.example* and *.env.streaming.prod.example* to *.env.prod* and *.env.streaming.prod*.
2. Update the environment variables in the *.env.prod* and *.env.streaming.prod* file.
3. Build the images and run the containers:
```sh
$ docker-compose -f docker-compose.yml -f docker-compose.prod.yml up --build
```
Test it out at [http://localhost:1337](http://localhost:1337). No mounted folders. To apply changes, the image must be re-built.
4. On first run, after initialising the database to fill the database with data:
```sh
$ docker exec movies_admin python utils/sqlite_to_postgres/load_data.py
```
## Technologies used
- The application runs as a WSGI/ASGI server.
- To render [static files](https://nginx.org/ru/docs/beginners_guide.html#static), **Nginx is used.
- Virtualization is done with **Docker.**.
## Main system components
1. **Server WSGI/ASGI** - server running the application.
2. **Nginx** - proxy server which is an entry point for web application.
3. **PostgreSQL** - relational data storage.
4. **ETL** - elasticsearch.
5. **FFmpeg** - FFmpeg.
6. **Airflow ETL** - airflow.
## Project requirements
1. The application must be run via WSGI/ASGI.
2. All system components are hosted in Docker.
3. Static files are served by Nginx.
## Recommendations for the project
1. To work with WSGI/ASGI server the database uses a special user.
2. Use docker compose to communicate between containers.