colibre/CLAUDE.md

CLAUDE.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

Project Overview

decp.info is a French public procurement data explorer — a Dash (Python) web app for browsing, filtering, and visualizing Données Essentielles de la Commande Publique (DECP). The UI is in French.

Commands

Setup

Setting up the virtual environment:

python -m venv .venv # s'il n'existe pas déjà
source .venv/bin/activate
rtk pip install -U pip > /dev/null 2>&1
rtk pip install -e . --group=dev

Environment variables:

cp .template.env .env   # then customize .env

Development

python run.py         # starts Dash app

Production

gunicorn app:server

Tests

rtk pytest                  # run all tests (some are Selenium-based integration tests)
rtk pytest tests/test_main.py::test_001_logo_and_search   # run a single test

Tests require a running Chrome/Chromium browser. They use DashComposite from dash[testing] with Selenium WebDriver.

Architecture

Multi-page Dash app

• src/app.py — creates the Dash app instance, navbar, SEO endpoints (robots.txt, sitemap.xml), Matomo analytics
• src/pages/*.py — each page registers itself with @register_page() and o.wns its own layout and callbacks
• run.py — dev entry point; exports server (Flask) for gunicorn

Module imports

• always import modules from the app starting with src. (e.g. src.utils., src.pages.recherche, etc.), NOT utils.cache or pages.observatoire.

Key pages

Page	URL	Purpose
recherche.py	/	Search homepage for buyers/contractors
acheteur.py	/acheteur	Buyer detail with stats, charts, maps
titulaire.py	/titulaire	Contractor detail
tableau.py	/tableau	Filterable data table with exports
marche.py	/marche	Individual contract detail
observatoire.py	/observatoire	An interactive analytics dashboard

Data layer

• Data is stored as Parquet at rest, possibly in DuckDB, loaded in DuckDB, served from DuckDB for big queries and manipulated with Polars for the remaining steps
• Path set via DATA_FILE_PARQUET_PATH env var; tests use tests/test.parquet
• src/util/*.py — helpers shared by other modules, search (search_org), link generation, geographic data loading
• src/callbacks.py — shared Dash callbacks (e.g. get_top_org_table)
• src/figures.py — chart and map components (Plotly Express, Dash Leaflet with marker clustering)
• a Parquet file with production data is located at ../decp-processing/decp_prod.parquet (~ 1,5 million records)
• the TableSchema of the dataset with the list of field and their definition is located at ../decp-processing/reference/base_schema.json
• tests/test.parquet is very small and may not contain all possible columns, only those necessary for testing

UI stack

• Dash 3.4 + Dash Bootstrap Components for layout
• Plotly Express for charts
• Dash Leaflet + Dash Extensions for interactive maps with clustering
• Custom CSS in src/assets/css/

Environment

• DEVELOPMENT=true enables debug logging and is set automatically during tests
• .env file is required at runtime (copy from template.env)

Migrations de schéma SQLite

Les migrations sont gérées dans src/migrations.py via une liste _MIGRATIONS de tuples (id, sql). Elles sont appliquées automatiquement au démarrage de l'app (via init_subscriptions).

Pour ajouter une migration :

# src/migrations.py
_MIGRATIONS = [
    ("0001_add_prix_ht_to_subscriptions", "ALTER TABLE subscriptions ADD COLUMN prix_ht REAL"),
    ("0002_ma_nouvelle_migration", "ALTER TABLE ... "),  # ajouter ici
]

• L'ID doit être unique et croissant (convention NNNN_description)
• Les migrations appliquées sont tracées dans la table schema_migrations
• apply_pending() est idempotent : sans effet si la migration est déjà enregistrée, et tolère le cas où la colonne existe déjà dans le schéma (DB fraîche)

Deployment

• main branch → manual deploy to decp.info via GitHub Actions
• dev branch → auto-deploy to test.decp.info via GitHub Actions

Sauvegarde de la base utilisateurs

users.sqlite est sauvegardée toutes les heures sur S3 par un timer systemd (voir deploy/decpinfo-backup.{service,timer}). Installation initiale (une fois, sur le serveur, en root) :

cp deploy/decpinfo-backup.service deploy/decpinfo-backup.timer /etc/systemd/system/
systemctl daemon-reload
systemctl enable --now decpinfo-backup.timer
systemctl list-timers decpinfo-backup.timer # vérifier le prochain déclenchement

Restauration manuelle :

cd /var/www/decpinfo && source .venv/bin/activate
python -m src.backup list
systemctl stop decpinfo
python -m src.backup restore backups/users-YYYYMMDDTHHMMSSZ.sqlite.gz.enc
systemctl start decpinfo