# Local-test environment for the modelling_e2e Lambda.
#
#   cp .env.local.example .env.local   then fill in the values below.
#
# .env.local is gitignored. The container hits REAL AWS and a REAL Postgres,
# so every value here points at infrastructure that exists.
#
# Set dry_run=true in invoke_local_lambda.py to run the full pipeline without
# writing anything to the DB — safe for local testing.
#
# Keep comments on their own lines — docker-compose's env_file parser folds a
# trailing "# ..." into the value.

# --- Postgres (infrastructure/postgres/config.py -> PostgresConfig.from_env) ---
# POSTGRES_HOST <- DB_HOST, PORT <- DB_PORT, USERNAME <- DB_USERNAME,
# PASSWORD <- DB_PASSWORD, DATABASE <- DB_NAME.
POSTGRES_HOST=
POSTGRES_PORT=5432
POSTGRES_USERNAME=
POSTGRES_PASSWORD=
POSTGRES_DATABASE=
# POSTGRES_DRIVER=psycopg2   (optional; defaults to psycopg2)

# --- Handler config (applications/modelling_e2e/handler.py) ---
# OPEN_EPC_API_TOKEN: gov.uk EPC API token (root .env: OPEN_EPC_API_TOKEN).
# GOOGLE_SOLAR_API_KEY: Google Solar API key (root .env: GOOGLE_SOLAR_API_KEY).
# DATA_BUCKET: S3 bucket holding geospatial parquet files (root .env: DATA_BUCKET).
OPEN_EPC_API_TOKEN=
GOOGLE_SOLAR_API_KEY=
DATA_BUCKET=

# --- AWS credentials for boto3 (S3 + EPC client) ---
AWS_ACCESS_KEY_ID=
AWS_SECRET_ACCESS_KEY=
AWS_DEFAULT_REGION=eu-west-2
# AWS_SESSION_TOKEN=   (only if using temporary/SSO credentials)