autoshazam

Autoshazam lets you shazam a long audio file, typically a mix, according to a specified interval in minutes. It can also process a folder of audio files (other types are ignored). Soon it will process urls

Install and run the frontend

First, install the required node packages. We need to use -f since there are some incompatibilities between some packages.

npm install -f

Then, build the frontend website with gastby using the following alias:

npm run build

Finally, run the frontend.

npm run start

Install and run the backend

Using python3.11, install the requirements (note that this includes yt-dlp to be able to use autoshazam with URLs, which will require ffmpeg to be installed in order to function properly):

apt-get install ffmpeg # Optional (note: use brew install ffmpeg if on macOS)
pip install -r requirements.txt

Run the backend via the uvicorn python module:

uvicorn src.app.main:app --reload --host 0.0.0.0 --port 8000

Install and run frontend and backend using docker-compose

If you have docker and docker-compose installed, it might be easier (and much lighter!) for you to simply build and run the containers:

docker-compose up -d --build

You can then make sure everything is running properly by following the logs:

docker-compose logs -f

Just to give you an idea, thanks to multi-stage Docker building and slim packages, we go from a total size of around 2.5Gb (~1Gb for frontend and ~1.5Gb for backend) to a total built size of "only" 500Mb for the two Docker images (~50Mb for frontend and ~450Mb for backend).

Future updates

• Persistent results
• Audio controls on the original file for each result for easier comparison
• Scrap youtube url from shazam info page
• Tests !
• Containerize
• Integrate with a media downloader

Suggestions are welcome !