Flatisfy

Flatisfy is your new companion to ease your search of a new housing :)

Note: This software is under heavy development at the moment, and the database schema could change at any time. Do not consider it as being production ready. However, I am currently using it for my own housing search and it is working fine :)

It uses Weboob to get all the housing posts on most of the websites offering housings posts, and then offers a bunch of pipelines to filter and deduplicate the fetched housings.

It can be used as a command-line utility, but also exposes a web API and visualisation, to browse through the results.

Note: It is targeted at French users (due to the currently supported websites), and in particular at people living close to Paris, as I developped it for my personal use, and am currently living in Paris :) Any feedback and merge requests to better support other countries / cities are more than welcome!

Note: In this repository and across the code, I am using the name "flat". I use it as a placeholder for "housing" and consider both are interchangeable. This code is not restricted to handling flats only!

Getting started

1. Clone the repository.
2. Install required Python modules: pip install -r requirements.txt.
3. Init a configuration file: python -m flatisfy init-config > config.json. Edit it according to your needs (see doc).
4. Build the required data files: python -m flatisfy build-data --config config.json.
5. Use it to fetch (and output a filtered JSON list of flats) or import (into an SQLite database, for the web visualization) a list of flats matching your criteria.
6. Install JS libraries and build the webapp: npm install && npm run build:dev (use build:prod in production).
7. Use python -m flatisfy serve --config config.json to serve the web app.

Documentation

See the dedicated folder.

OpenData

I am using the following datasets, available under flatisfy/data_files, which covers Paris. If you want to run the script using some other location, you might have to change these files by matching datasets.

• LaPoste Hexasmal for the list of cities and postal codes in France.
• RATP stations for the list of subway stations with their positions in Paris and nearby areas.

Both datasets are licensed under the Open Data Commons Open Database License (ODbL): https://opendatacommons.org/licenses/odbl/.

License

The content of this repository is licensed under an MIT license, unless explicitly mentionned otherwise.

Contributing

See the CONTRIBUTING.md file for more infos.

Thanks

• Weboob
• The OpenData providers listed above!
• Navitia for their really cool public transportation API.
• A lots of Python modules, required for this script (see requirements.txt).
• Kresus which gave me part of the original idea (at least proved me such software based on scraping can achieve a high quality level :)