microsearch is a minimal Python search engine designed for simplicity and efficiency. The project allows users to perform searches using Python, and it also provides an option to deploy a FastAPI app with an endpoint and a website for a user-friendly experience. It has been designed to provide users with a straightforward way to deploy their own search engine and search documents from their favorite blogs. The project includes a script for asynchronously downloading all the posts from a series of RSS feeds.

• Python Implementation: microsearch is entirely implemented in Python, making it accessible and easy to understand for developers with varying levels of experience.

• FastAPI App Deployment: The project provides an option to deploy a FastAPI app, allowing users to interact with the search engine through a dedicated endpoint and a user-friendly website.

• RSS Feed Crawling Script: To populate the search engine with data, microsearch offers a script for asynchronously downloading posts from a series of RSS feeds. This feature ensures that users can conveniently aggregate content from their chosen blogs.

The first step is to download this repo

git clone https://github.com/alexmolas/microsearch.git

Then, I recommend you install everything in a virtual environment. I usually use virtualenv but any other environment manager should work.

virtualenv -p python3.10 venv

activate the environment

source venv/bin/activate

and install the package and the dependencies

pip install .

Now we need to download the content of the blogs. I'm sharing here a list of feed examples, but please feel free to use your own. To download the content do

python download_content.py --feed-path feeds.txt

Finally, once the content is crawled and stored you can run the app as

python -m app.app --data-path output.parquet

and if you navigate to http://127.0.0.1:8000/ you'll be able to query the engine.