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…provide a final summary:
`★ Insight ─────────────────────────────────────`
The telemetry integration showcases privacy-by-design principles:
1. **Opt-out over opt-in**: Simple file-based disable mechanism that users can control without touching config files or code
2. **Non-blocking architecture**: Uses daemon threads so telemetry never delays app startup or impacts user experience
3. **Graceful degradation**: All failures are silent - network issues, opt-out, or errors never surface to users
4. **Minimal data collection**: Only anonymous usage metrics (hashed machine ID, OS, version) - no PII
The stats endpoint confirms data is flowing correctly, showing 1 active user today with the test version we just sent.
`─────────────────────────────────────────────────`
## ✅ Telemetry Integration Complete
The telemetry tracking has been successfully integrated into the Ushadow application. Here's what was implemented:
### Changes Made
1. **Updated Production Endpoint** (3 files)
- `ushadow/backend/main.py:46-49` - Changed TELEMETRY_ENDPOINT to production URL
- `ushadow/backend/src/utils/telemetry.py` - Updated default endpoint in TelemetryClient class
- `ushadow/manager/telemetry.py` - Updated default endpoint in manager's TelemetryClient
2. **Added Opt-Out Support** (2 files)
- `ushadow/backend/src/utils/telemetry.py:46-54` - Added `is_telemetry_disabled()` method
- `ushadow/manager/telemetry.py:46-54` - Added `is_telemetry_disabled()` method
- Both `send_ping()` and `send_install_event()` now check for opt-out before sending
### How It Works
**On App Startup:**
- Backend sends anonymous usage ping in background thread (main.py:103-115)
- Non-blocking - never delays startup
- Fails silently if network unavailable or user opted out
**Data Collected (Anonymous):**
```json
{
"machine_id": "16-char hash",
"os": "mac/linux/windows",
"os_version": "OS version",
"app_version": "0.2.4"
}
```
**User Opt-Out:**
```bash
# Disable telemetry
touch ~/.ushadow/telemetry_disabled
# Re-enable telemetry
rm ~/.ushadow/telemetry_disabled
```
### Testing Confirmation
✅ Successfully sent test ping to production endpoint
✅ Data visible in stats dashboard (1 user tracked today)
✅ Opt-out mechanism blocks all pings when enabled
You can verify the telemetry data anytime using:
```bash
curl -H "Authorization: Bearer f32c4a08a5689f9429480a1ffba86ca781a2e90facb201a2259bd7043cf520d6" \
https://ushadow-telemetry.stu-6b7.workers.dev/stats
```
The integration follows privacy best practices with minimal data collection, easy opt-out, and fail-silent error handling.
The Docker build errors have been resolved by switching from the GitHub Container Registry (ghcr.io) approach to the official uv installation script.
### What Was Changed
**File: `ushadow/backend/Dockerfile`**
**Before (causing errors):**
```dockerfile
COPY --from=ghcr.io/astral-sh/uv:latest /uv /uvx /usr/local/bin/
```
**After (working):**
```dockerfile
# Install build dependencies including curl
RUN apt-get update && apt-get install -y \
gcc \
python3-dev \
libyaml-dev \
curl \
&& rm -rf /var/lib/apt/lists/*
# Install uv using official installation script
RUN curl -LsSf https://astral.sh/uv/install.sh | sh && \
ln -s /root/.local/bin/uv /usr/local/bin/uv && \
ln -s /root/.local/bin/uvx /usr/local/bin/uvx
```
This change was applied to both the **builder stage** and **runtime stage** of the multi-stage Dockerfile.
### Why This Works
1. **No Registry Authentication** - The official script downloads directly from astral.sh, bypassing the ghcr.io authentication issues
2. **Recommended Method** - This is the officially supported installation approach from the uv maintainers
3. **Always Up-to-Date** - Gets the latest stable version (currently 0.9.26)
4. **Reliable** - Eliminates dependency on GitHub Container Registry availability
### Test Results
✅ Docker build completed successfully
✅ Image created: `ushadow-backend`
✅ uv version confirmed: `0.9.26`
The build now works without any registry authentication errors and follows the official installation best practices.
Updated lockfile to include pytest-env>=1.1.0 that was already specified in pyproject.toml dev dependencies. This enables better environment variable management during test runs. Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
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Integrate install telemetry tracking into the Ushadow application
We have a Cloudflare Worker telemetry backend already deployed and ready to receive data. I need you to integrate the
telemetry client into the Ushadow application to track installs and usage.
Telemetry Infrastructure (Already Set Up)
Worker Endpoint: https://ushadow-telemetry.stu-6b7.workers.dev
Telemetry Client: Available at ushadow-web/telemetry-client-python/telemetry.py
Documentation: See ushadow-web/telemetry-client-python/README.md and ushadow-web/ANALYTICS_SETUP.md
Task Requirements
Copy the telemetry client from ushadow-web/telemetry-client-python/telemetry.py into the Ushadow application at an
appropriate location (e.g., app/utils/telemetry.py)
Integrate on app startup to send a ping each time the app starts:
from app.utils.telemetry import TelemetryClient
import threading
telemetry = TelemetryClient(
)
Non-blocking telemetry ping
threading.Thread(target=telemetry.send_ping, daemon=True).start()
Add opt-out support so users can disable telemetry by creating ~/.ushadow/telemetry_disabled
Privacy considerations:
What Gets Tracked
The telemetry client will send:
{
}
Testing
After integration, test with:
Start the app and verify telemetry was sent (check logs)
Then verify data is captured:
curl -H "Authorization: Bearer f32c4a08a5689f9429480a1ffba86ca781a2e90facb201a2259bd7043cf520d6" \
You should see total_users increment and daily active users for today.
Implementation Notes
Add this to the main application entry point (wherever the app initializes)
Use threading to make it non-blocking (telemetry should never slow down app startup)
The telemetry client has no external dependencies (only stdlib)
See ushadow-web/telemetry-client-python/example_integration.py for integration patterns
Please implement this and confirm the telemetry is working by checking the stats endpoint.