Ship Flask, FastAPI, or Django changes without redeploying to flip them on.
Gate a view, a background task, or an API response behind a flag, and change its state from the dashboard instead of a deploy.
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RubyMCP SupportWhat are feature flags?
A feature flag is a runtime switch in your code that decides whether a piece of functionality is visible or active, without requiring a new deployment.
Instead of shipping a feature straight to every user the moment it merges, you wrap it in a flag. The code reaches production immediately, but stays off until you decide to turn it on — for one user, a percentage of traffic, or everyone at once.
Six problems a feature flag solves
Deploy continuously
Merge and ship to production every day, and keep unfinished work safely behind a flag instead of a long-lived branch.
Release gradually
Turn a feature on for 5% of traffic first, watch for errors, then widen the rollout instead of flipping a switch for everyone at once.
Beta test with real users
Target specific accounts or user IDs so a handful of people can try a feature before it reaches everyone else.
Disable instantly
If a feature misbehaves in production, turn it off from the dashboard in seconds — no rollback, no redeploy.
Reduce deployment risk
Separate "deployed" from "released." Code can sit in production, inactive, until you decide it is ready.
Ship faster as a team
Multiple engineers can merge into main continuously without waiting on each other's features to be release-ready.
One flag, four states
The same flag key, evaluated with a different user context, can return a different result for every visitor — without a second deployment.
Get the SDK
pip install flagpilot
From install to your first evaluation
Install the SDK
Add the package to your project.
pip install flagpilot
Initialize the client
Create one client at app startup and reuse it across requests.
client = FlagPilot(api_key="fk_secret_xxxx", environment="production") client.initialize()
Evaluate a flag
Call evaluate() inside a view or background task.
is_enabled = client.evaluate("new_dashboard_v2", user_id="user_123")Render the response
Use the boolean result to decide what the view returns.
if is_enabled:
render_new_dashboard()
else:
render_old_dashboard()How evaluation works
On startup, the SDK fetches your project's flag configuration once and stores it in an in-memory cache. Every evaluate() call after that reads from the cache, not the network, so checking a flag is effectively free.
The cache refreshes in the background on a polling interval, so a change you make in the dashboard shows up in connected clients within seconds, without blocking any request.
If the API is temporarily unreachable — a network blip, or a cold start before the first fetch completes — evaluation falls back to a safe default instead of throwing, so a flag outage never becomes a feature outage.
Built for Python
Framework-agnostic
The same client works in a Flask view, a FastAPI route handler, or a Django view — no framework-specific plugin needed.
No blocking network calls
Evaluation reads from an in-process cache that refreshes in the background, not a live request on every check.
Thread-safe by design
The client is built to be shared safely across worker threads in a WSGI/ASGI server.
Type hints included
The client ships with inline type hints, so evaluate() signatures work cleanly with mypy and IDE autocomplete.
Fast startup
initialize() completes in under 100ms, so it doesn't noticeably slow down app boot in Flask, FastAPI, or Django.
Works with sync and async apps
The same client works in traditional WSGI apps and in ASGI frameworks like FastAPI.
Common patterns in Python
is_enabled = client.evaluate("new_dashboard_v2", user_id="user_123")
if is_enabled:
render_new_dashboard()Getting flags right from day one
Never expose secret keys
Secret API keys belong on your server only. Client-side code should use a public client key that can't modify flags.
Use stable user identifiers
Percentage rollouts hash the user ID you pass in. A stable ID means the same user always gets the same result.
Keep flags short-lived
A flag that never gets removed becomes a permanent branch in your code. Treat flags as temporary scaffolding, not config.
Remove stale flags regularly
Once a rollout reaches 100% and stays there, delete the flag and the old code path along with it.
Roll out gradually before going global
It's far cheaper to catch a bug at 5% of traffic than to catch it at 100%.
Use meaningful flag names
A key like new-checkout-flow-v2 is easier to audit six months later than test123.
- Create one FlagPilot client at app startup and reuse it — don't construct a new client per request.
- Store the secret key in an environment variable, read via os.getenv, not hardcoded.
- Call initialize() once before your app starts serving requests.
A published Python SDK that works with any WSGI or ASGI framework
Lightweight by default
Every SDK stays under 10KB and evaluates from an in-process cache, so adding flags never becomes a performance conversation.
REST API for everything
Every action available in the dashboard — creating flags, updating rollouts, reading audit history — is also a documented REST endpoint.
A CLI that matches the API
Script flag creation and rollout changes from your terminal or CI pipeline, using the same operations the dashboard performs.
Built for AI-assisted development
A native MCP server lets Cursor, Claude Code, or any MCP-compatible assistant create and toggle flags directly from a prompt.
Dead flag detection included
Flags that haven't been evaluated recently, or have sat at 100%/0% for months, are surfaced automatically instead of silently rotting in your codebase.
Developer experience first
No sales calls, no seat-based pricing negotiations — sign up, get an API key, and evaluate your first flag in the same session.
Fast enough to not think about
Evaluation logic must never slow down your app or disrupt a user flow — here's what that looks like in practice.
Frequently Asked Questions
Ready to ship features safely?
Install FlagPilot in Python in under a minute.