oosei25/africa-momentum-index-demo

A small, production-friendly pipeline + Streamlit dashboard capturing African startup momentum via RSS/Google News and optional X/Twitter (Snscrape). With PostgreSQL (Neon-ready) storage and daily momentum/maturity indices, the app highlights KPIs, trend lines, sentiment, and recent headlines. # Africa Momentum Index — MVP A lightweight data pipeline + Streamlit dashboard that tracks startup momentum across African countries from news (RSS/Google News) and optional social signals (X/Twitter via `snscrape`). Data lands in PostgreSQL (Neon-ready), daily indices are computed (momentum, maturity), and the app visualizes KPIs, trends, sentiment, and headlines. > Countries in scope (MVP): Ghana (GH), Kenya (KE), Nigeria (NG) ## 🚀 Live Demo --- ## What you get - **Sources**: RSS/Google News (primary); optional X/Twitter via `snscrape` (off by default). - **Processing**: ingestion → VADER sentiment → daily per-country indices (momentum, maturity). - **Storage**: PostgreSQL schema (Docker locally, Neon in the cloud). - **App**: Streamlit KPIs, 7-day rolling trend, colored sentiment bars, latest headlines with links. - **Ops**: Nightly refresh via GitHub Actions; optional in-app **Run demo** button to seed data. ## Quickstart (local via Docker) ```bash make bootstrap ``` > Opens (Adminer at if enabled) --- ## Run steps individually ```bash python -m scripts.ingest python -m scripts.run_sentiment python -m scripts.compute_indices ``` ## Or all at once ```bash make demo-local # host → localhost:6543 # or inside the container make demo-docker # container → db:5432 ``` ## Data Model (MVP) - `countries` (id, iso2, name) - `articles` (id, country_id, source_name, sub_indicator, title, url, published_at, sentiment_label, sentiment_score, …) - `social_posts` (optional tweets) - `indices_daily` (country_id, date, momentum, maturity, drivers, computed_at) - There’s a unique constraint on `(country_id, date)` in `indices_daily`. --- ## How the pipeline works ```mermaid flowchart LR A[Sources] B[scripts/ingest.py] C[(PostgreSQL)] D[scripts/run_sentiment.py] E[scripts/compute_indices.py] F[indices_daily] G["dashboard/app.py (Streamlit)"] A -->|RSS/Google News| B A -->|optional X/Twitter via snscrape| B B -->|dedup + upsert| C C -.->|updates art …