winzig 0.1.1

A tiny search engine for personal use.

winzig

winzig is a tiny search engine designed for personal use that enables users to download and search for posts from their favourite feeds.

This project is heavily inspired by the microsearch project and the article about it.

Motivation

For quite some time, I've been contemplating the idea of creating my own personal search engine. I wanted a tool that could facilitate searching through my personal notes, books, articles, podcast transcripts, and anything else I wished to include. However, I was unsure of how or where to begin until I discovered the microsearch project, which reignited the momentum for the idea in my mind.

This project started as a "manual" clone of the microsearch project to be able to better understand how some things worked. Later, I decided to start implementing some changes like using httpx instead of aiohttp or keeping all the data in a SQLite database.

Features

• Fetch only what you need: winzig optimizes data retrieval by exclusing content that is already in the database, making sure that only new content is fetched after the intial crawl.
• Async, Async, Async: crawling as well as the posterior data processing operate asynchronously, resulting in lightning-fast performance.
• Efficient data management with SQLite: everything is kept in a SQLite database in your home directory.
• Easy to use: searching is just one command; the setup is handled after the initial data fetching.

Installation

You'll need Python >= 3.12 to be able to run winzig.

pip

pip install winzig

pipx

pipx install winzig

Cloning this repository

Clone this repo with git clone:

git clone https://github.com/dnlzrgz/winzig winzig

Or use gh if you prefer it instead:

gh repo clone dnlzrgz/winzig

Then, create a virtualvenv inside the winzig directory:

python -m venv venv

Activate the virtualvenv:

activate venv/bin/activate

And run:

pip install .

Instead of using pip you can also use poetry:

poetry install

And now you should be able to run:

winzig --help

Usage

The first time you initiate a crawl, you'll need a file containing a list of feeds to fetch. These feeds will be stored in the SQLite database. Therefore, there is no need to provide this file again unless you're adding new feeds. This repository contains a urls file that you can use.

Currently, there is no way to manage the feeds or posts added to the database. So if you want to remove some of them you will need to do it manually. However, it may be more efficient to delete the database and crawl again.

Crawling

The following command starts the crawler. Initially, it extracts the URLs from the specified file and saves them to the database. Then, it proceeds to fetch all the posts listed on each of these feeds. The --verbose flag signals that the command will provide detailed output, including HTTP errors.
Once all the posts have been crawled, it proceeds to calculate the Inverse Document Frequency (IDF) for all the terms in the database. IDF is a statistical measure used in information retrieval to determine the importance of a term within a collection of documents. Basically, doing this now makes the search faster.

winzig crawl --file="./urls" --verbose

Searching

The following command starts a search for content matching the provided query and after a few seconds will return a list of relevant links.

winzig search --query="async databases with sqlalchemy"

By default the number of results is 5 but you can change this by using the -n flag.

winzig search --query="async databases with sqlalchemy" -n 10

Roadmap

• Add tests.
• Add a TUI using textual.
• Add documents like markdown or plain text files.
• Add support for PDFs and other formats.
• Make the CLI nicer.
• Add commands to manage the SQLite database.

Contributing

If you are interested in contributing, please open an issue first. I will try to answer as soon as possible.