Urban & Community Forestry Accreditation Dashboard

A lightweight Flask web application for browsing accreditation snapshots for New Jersey municipalities. It surfaces data parsed from annual Urban & Community Forestry (UCF) accreditation reports and links each result directly to the page in the source PDF. The dashboard exposes a searchable web UI as well as JSON APIs that can be reused by other tools.

How it works

• Data extraction: The scripts/extract_reports.py script reads PDF reports in the context/ directory using PyPDF2, pulls out municipality, county, accreditation status, plan year, update date, and the report year inferred from the filename, then writes the consolidated dataset to data/reports.json.
• Application: app/__init__.py loads reports.json, builds common filter lists (counties, years), and exposes both HTML and JSON routes. PDFs in context/ are served via /pdf/<filename> so the UI and API responses can link to the exact report page.
• Frontend: The app/templates/index.html template renders filters for county, municipality, year, and accreditation status. It calls /api/reports to show matching entries and links to municipality detail pages (/municipality/<slug>) and PDF anchors (#page=<n>).

Key routes:

• / – search dashboard UI.
• /municipality/<slug> – all records for a municipality.
• /api/meta – metadata for populating filters (counties, years, municipalities).
• /api/reports – filtered report data with links to PDFs and profiles.
• /api/municipalities/<slug> – records for a specific municipality.
• /pdf/<filename> – serves source PDFs stored in context/.

Getting started locally

1. Create a virtual environment and install dependencies (Python 3.10+ recommended):

   python -m venv .venv
   source .venv/bin/activate
   pip install -r requirements.txt

2. Verify data and PDFs: Ensure data/reports.json exists and that the referenced PDFs live in context/. If you add new PDFs or want to refresh the dataset, run:

   python scripts/extract_reports.py

3. Run the development server:

   flask --app app:build_app --debug run

   The site will be available at http://127.0.0.1:5000/.

Using it as a web application

• Production server: Point a WSGI server like gunicorn at the factory app:build_app, e.g.:

  gunicorn --bind 0.0.0.0:8000 'app:build_app()'

  Serve the context/ directory so /pdf/<filename> can return the source PDFs.
• Static hosting setup: Behind a reverse proxy (nginx/Apache), route application traffic to the WSGI server and allow direct access to context/ for PDF downloads. Ensure the proxy forwards X-Forwarded-Proto headers if you terminate TLS upstream.
• Refreshing data: Place new yearly accreditation PDFs in context/, rerun python scripts/extract_reports.py, and redeploy or reload the WSGI process to pick up the updated reports.json.

Project layout

• app/__init__.py – Flask application factory, routes, and filtering logic.
• app/templates/ – HTML templates for the search page and municipality details.
• app/static/ – Shared styling for the UI.
• data/reports.json – Parsed accreditation metadata.
• context/ – Source accreditation report PDFs and related context files.
• scripts/extract_reports.py – PDF parser that regenerates data/reports.json.

API quick start

Query the JSON API directly, for example:

curl 'http://127.0.0.1:5000/api/reports?county=Monmouth&accredited=true'

Each record includes pdf_url (link to the PDF page) and municipality_url (link to the municipality summary page) to make integrating the data into other tools straightforward.