featbit-python-sdk
Guides integration of the FeatBit Python Server-Side SDK for backend services. Use when users ask about FeatBit feature flags in Python, fbclient usage, or server frameworks like Flask, Django, or FastAPI. Not for client-side use.
Best use case
featbit-python-sdk is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Guides integration of the FeatBit Python Server-Side SDK for backend services. Use when users ask about FeatBit feature flags in Python, fbclient usage, or server frameworks like Flask, Django, or FastAPI. Not for client-side use.
Teams using featbit-python-sdk should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/featbit-python-sdk/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How featbit-python-sdk Compares
| Feature / Agent | featbit-python-sdk | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Guides integration of the FeatBit Python Server-Side SDK for backend services. Use when users ask about FeatBit feature flags in Python, fbclient usage, or server frameworks like Flask, Django, or FastAPI. Not for client-side use.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 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)
```python
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](references/quick-start.md) — installation, prerequisites, and full quick start
- [references/data-synchronization.md](references/data-synchronization.md) — websocket sync behavior and recovery
- [references/bootstrapping-and-lifecycle.md](references/bootstrapping-and-lifecycle.md) — singleton pattern, init waits, readiness
- [references/evaluation-and-tracking.md](references/evaluation-and-tracking.md) — evaluation, all-flags, change tracking, experiments
- [references/offline-mode.md](references/offline-mode.md) — offline setup and bootstrap JSON
- [references/support-and-links.md](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)
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