Pabulib

Pabulib is an open PArticipatory BUdgeting LIBrary. Project collects the participatory budgeting data from all over the world. In a companion paper we have introduced universal .pb data format in which we store all the files.

http://pabulib.org

NOTE

This repository is still in "work in progress" mode: at the beginnig we wrote the code just for ourselves. Now we need to beautify this to make it understandable and usable for everyone. We will do it, just give us some time :) Till then we think that even in such not-perfect format it could be useful for someone. If something is unclear just contact us! [email protected]

Authors

Usage

Environment

python -m venv venv
pip install -r requirements.txt

Checker

NOTE: The checker is currently in deployment/testing mode. If there are changes in Checker repo (which happens quite often), you must reinstall it to apply the latest updates.

(This ensures you're using the most recent pushed code) To reinstall the latest version from GitHub:

pip uninstall -y pabulib 
pip install git+https://github.com/pabulib/checker.git

Process the data (from csv, excel, pdf):

1. add data to data/<city> directory
2. add all needed scritps to process_data/cities/<city>
    settings.py and budgets.py are obligatory, please check `cities/a_city_template` dir as a reference
3. run the process. Choose year and the city in the script and run it:
    start_process.py

Example processing run

To better understand how the pipeline works, you can use the provided example template. This example processes a fictional city (a_city_template) for the year 2025 and generates .pb files based on example data:

just run

python start_process_template.py

and see the results in output directory!

Check if output .pb files are correct

1. set in params path to .pb files you want to check:
    to check all files in output directory:
        "files_in_output_dir": "*"
    or in provided absolute path:
        "files_in_absolute_dir": "/*" (remember about `*` to match all files)
2. run output checks:
    python run_output_checks.py

Modify .pb files: for example to count votes or to change columns order

modify_pb_files.py

if self.modified is changed to True, new file will be saved in output/cleaned directory.

Visualize, play with data:

src/analytics/test.ipynb