akhil-egov/chad-polio-ingest

Elasticsearch extraction pipeline for Chad nOPV2 campaign data # chad-polio-ingest Data extraction pipeline for the WHO AFRO nOPV2 campaign dashboard — N'Djamena, Chad, June 2026. Pulls structured data from Elasticsearch, shapes it with pandas, and writes a timestamped Excel file consumed by `chad-polio-dashboard`. --- ## Pipeline overview ``` Elasticsearch (WHO AFRO) │ ▼ chad-polio-ingest ← you are here (extractors/ + main.py) │ ▼ output/chad_YYYYMMDD_HHMM.xlsx │ ▼ chad-polio-dashboard (fetch_latest.py → data.json → Vercel) ``` --- ## Quick start (local) ```bash git clone github.com cd chad-polio-ingest pip install -r requirements.txt cp .env.example .env # fill in ES_URL + ES_AUTH_HEADER python main.py ``` Output lands in `output/chad_YYYYMMDD_HHMM.xlsx`. --- ## Environment variables (`.env`) ``` ES_URL=elasticsearch-data.es-clust… ES_AUTH_HEADER=Basic OUTPUT_DIR=output JUPYTER_BASE=https:// /jupyter/user/ JUPYTER_TOKEN= JUPYTER_REMOTE_ROOT= ``` --- ## Repository structure ``` extractors/ base.py — ESClient (only file that touches ES) coverage.py — daily vaccinations by facility activity.py — per-user task count + last sync refusals.py — refusal reason codes by facility enumeration.py — households + eligible children + vaccinated stock.py — vial reconciliation (supply-side) stock_daily.py — per-team per-day vial issuance gps.py — household GPS + vaccination count + head-of-household gps_refusals.py — refusal household dots gps_zerodose.py — zero-dose children microplan.py — coverage vs microplan target settlement.py — URBAN/RURAL/SLUMS breakdown demographics.py — age/gender of vaccinated children inactive_users.py — users not synced in 24h config/ chad.json — campaign config (IDs, bounds, facility map) deploy.py — push any local file to remote Jupyter server scheduler.py — hourly background runner for Jupyter server run_hourly.py — wrapper called by s …