Featbit Python Sdk

FeatBit Python Server-Side SDK

Expert guidance for integrating the FeatBit Python Server-Side SDK in backend applications. This skill is based on the official SDK README and keeps details in reference files for quick navigation.

Activates When

• The user asks about FeatBit Python SDK setup, usage, or troubleshooting.
• The user mentions fbclient, FBClient, variation, variation_detail, or flag_tracker.
• The user needs server-side feature flag evaluation in Python (Flask, Django, FastAPI, etc.).

Overview

Use this SDK to evaluate feature flags on the server. The SDK syncs flag data via websocket and stores it in memory by default. If you need a custom data source, use offline mode with bootstrap JSON.

Core Knowledge Areas

1. Data Synchronization

• Websocket sync keeps local data updated (average sync < 100 ms).
• The connection can be interrupted but resumes automatically after outages.
• Offline mode disables remote sync; use bootstrap JSON if needed.

2. Installation and Prerequisites

• Install: pip install fb-python-sdk (Python 3.6–3.11).
• Required values: env_secret, event_url, streaming_url.
• Official FAQ: environment secret + SDK URLs.

3. Initialization and Client Lifecycle

• Preferred pattern: call set_config(...), then get() for a singleton client.
• Direct instantiation: FBClient(Config(...), start_wait=15).
• Async readiness: client.update_status_provider.wait_for_OKState().

4. Evaluation and All Flags

• Evaluate: variation() for value, variation_detail() for value + reason.
• All flags: get_all_latest_flag_variations(user).
• Defaults are returned when SDK is not initialized or keys are invalid.

5. User Model

• Use a dict with required key and name.
• Add custom properties (string, number, boolean).

6. Flag Change Tracking

• flag_tracker.add_flag_value_maybe_changed_listener(...).
• flag_tracker.add_flag_value_changed_listener(...).

7. Offline Mode and Bootstrap Data

• Enable: Config(..., offline=True).
• Initialize with JSON: client.initialize_from_external_json(json).
• Use FeatBit to export a bootstrap JSON snapshot.

8. Experiments (A/B/n)

• Track custom events: client.track_metric(user, event_name, numeric_value).
• Ensure the flag is evaluated before tracking the metric.

Quick Start (Concise)

from fbclient import get, set_config
from fbclient.config import Config

set_config(Config(env_secret, event_url, streaming_url))
client = get()

if client.initialize:
    user = {"key": "bot-id", "name": "bot"}
    detail = client.variation_detail("flag-key", user, default=None)
    print(detail.variation, detail.reason)

client.stop()

For a complete walkthrough and full examples, see the reference guides below.

Reference Guides

• references/quick-start.md — installation, prerequisites, and full quick start
• references/data-synchronization.md — websocket sync behavior and recovery
• references/bootstrapping-and-lifecycle.md — singleton pattern, init waits, readiness
• references/evaluation-and-tracking.md — evaluation, all-flags, change tracking, experiments
• references/offline-mode.md — offline setup and bootstrap JSON
• references/support-and-links.md — official docs, GitHub repo, support channels

Best Practices

1. Create one client per environment: keep FBClient instances for the app lifetime.
2. Check readiness only when needed: evaluate with defaults if not ready, and log status for diagnostics.
3. Prefer variation_detail() for debugging: it returns evaluation reasons.
4. Call stop() on shutdown: allow pending events to flush.

Documentation Reference

• Official Docs: https://docs.featbit.co/sdk/overview#python
• Complete Guide (full README and latest updates): https://github.com/featbit/featbit-python-sdk

Related Topics

• FeatBit OpenFeature integration (if using OpenFeature with Python SDK)
• Server-side SDKs for other languages