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.ci | ||
doc | ||
flatisfy | ||
hooks | ||
.babelrc | ||
.eslintrc | ||
.gitignore | ||
CONTRIBUTING.md | ||
LICENSE.md | ||
package.json | ||
README.md | ||
requirements.txt | ||
webpack.config.js | ||
wsgi.py |
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
- Clone the repository.
- Install required Python modules:
pip install -r requirements.txt
. - Init a configuration file:
python -m flatisfy init-config > config.json
. Edit it according to your needs (see doc). - Build the required data files:
python -m flatisfy build-data --config config.json
. - Use it to
fetch
(and output a filtered JSON list of flats) orimport
(into an SQLite database, for the web visualization) a list of flats matching your criteria. - Install JS libraries and build the webapp:
npm install && npm run build:dev
(usebuild:prod
in production). - 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 :)
- Current favicon is from Wikipedia