This was originally published on rollgate.io/blog/feature-flags-python . Why Feature Flags in Python? Python powers everything from web applications and REST APIs to data pipelines and machine learning systems. Across all of these, you face the same challenge: how do you ship new features safely without risky deployments? Feature flags solve this by decoupling deployment from release. You deploy code with the feature wrapped in a conditional, then control who sees it — without touching your codebase. Here is where feature flags shine in Python projects: Web applications — Roll out new UI components or API endpoints to a subset of users in Django, FastAPI, or Flask. REST APIs — Version API behavior dynamically without maintaining separate endpoints. Data pipelines — Toggle new ETL logic or processing steps without redeploying Airflow DAGs. ML model rollouts — A/B test model versions in production, compare accuracy, and roll back instantly if metrics degrade.…