fix: allow gunicorn auto-reload locally

.env

@@ -44,7 +44,8 @@ POSTGRES_HOST=postgres
 POSTGRES_DB=postgres
 POSTGRES_USER=postgres
 POSTGRES_PASSWORD=postgres
-POSTGRES_EXPOSE=127.0.0.1:5432
+# Expose postgres on localhost for dev
+# POSTGRES_EXPOSE=127.0.0.1:5432
 
 # Triton ML inference server
 TRITON_HOST=triton
@@ -84,4 +85,8 @@ FASTTEXT_MODEL_DIR=./models
 # Enable/disable MongoDB access. All insights/predictions are checked
 # against MongoDB, we disable by default locally to be able to easily test
 # image import
-ENABLE_MONGODB_ACCESS=0
+ENABLE_MONGODB_ACCESS=0
+
+# gunicorn --auto-reload is not compatible with preload_app
+# so it has to be disabled when developing, to allow hot reload
+GUNICORN_PRELOAD_APP=0

Dockerfile

@@ -88,3 +88,5 @@ RUN \
     mkdir -p /opt/robotoff/gh_pages /opt/robotoff/doc /opt/robotoff/.cov && \
     chown -R off:off /opt/robotoff/gh_pages /opt/robotoff/doc /opt/robotoff/.cov
 USER off
+CMD [ "gunicorn", "--reload", "--config /opt/robotoff/gunicorn.py", "--log-file=-", "robotoff.app.api:api"]
+

docker-compose.yml

@@ -22,6 +22,7 @@ x-robotoff-base-env:
   ROBOTOFF_TLD:
   ROBOTOFF_SCHEME:
   STATIC_DOMAIN:
+  GUNICORN_PRELOAD_APP:
   GUNICORN_NUM_WORKERS:
   ROBOTOFF_UPDATED_PRODUCT_WAIT:
   REDIS_HOST:

gunicorn.py

@@ -4,5 +4,8 @@
 # we have a trade-off with memory vs cpu numbers
 workers = int(os.environ.get("GUNICORN_NUM_WORKERS", 4))
 worker_connections = 1000
-preload_app = True
+# gunicorn --auto-reload is not compatible with preload_app
+# so it has to be disabled when developing
+# Default to True (production) if not specified
+preload_app = bool(os.environ.get("GUNICORN_PRELOAD_APP", True))
 timeout = 60