# dbdemos-tracker
A Python library for tracking Databricks demo analytics.
## Installation
```bash
pip install dbdemos-tracker
```
## Usage
### Manual App Usage Tracking
```python
from dbdemos_tracker import Tracker
# Create tracker for app - Use your repo name as app name
ws = WorkspaceClient()
tracker = Tracker(org_id=ws.get_workspace_id(), demo_name="app-name")
# Track app views in functions
@app.get("/")
def home():
tracker.track_app_view(user_email="user@databricks.com", app_path="/dashboard")
return {"message": "Welcome to my demo app"}
```
### FastAPI Middleware
We provide a tool to track all app views out of the box.
Try to filter on the main actions so that we don't have too many views using `patterns=["/my/.*/url/to/track", "..."]`
```python
from fastapi import FastAPI
from dbdemos_tracker import Tracker
# Create FastAPI app
app = FastAPI(title="My Demo App")
# Add tracking middleware - this will track ALL requests automatically
Tracker.add_tracker_fastapi(app, "app-name"))
# You can also filter to only track some URL:
Tracker.add_tracker_fastapi(app, "app-name", patterns=['/demos/.*/load']))
# Then all your API endpoints will be tracked out of the box
@app.get("/")
def home():
return {"message": "Welcome to my demo app"}
# Run with: uvicorn main:app --reload
```
### Streamlit Integration
**EXPERIMENTAL - NOT TESTED - REACH OUT FOR HELP ON #field-demos**
**Automatic Interceptor (Recommended):**
```python
import streamlit as st
from dbdemos_tracker import Tracker
# Setup automatic tracking - call this once at the top of your app
Tracker.setup_streamlit_interceptor("app-name")
# Your Streamlit app - all interactions are automatically tracked!
st.title("My Demo App")
# These will be automatically tracked:
if st.button("Process Data"):
st.write("Data processed!")
name = st.text_input("Enter your name")
age = st.slider("Age", 0, 100, 25)
option = st.selectbox("Choose option", ["A", "B", "C"])
enabled = st.checkbox("Enable feature")
# Set user email for tracking (optional)
st.session_state.user_email = "user@databricks.com"
```
**Manual Tracking (if needed):**
```python
# Track specific interactions manually
Tracker.track_streamlit_app("app-name")
```
## Configuration
### Disable Tracking
```python
# Disable tracking globally
Tracker.enable_tracker = False
# Re-enable when needed
Tracker.enable_tracker = True
```
### Email Filtering
The tracker automatically filters emails to only track Databricks email addresses (`@databricks.com`). Non-Databricks emails are ignored for privacy.
### Test Workspace
Tracking is automatically disabled for test workspace ID `1660015457675682`.
## Features
- Track demo usage analytics
- Configurable tracking enable/disable
- Automatic Databricks email filtering
- Error handling with timeout protection
- FastAPI middleware for automatic request tracking
- Streamlit integration for app interaction tracking
- Support for both notebook and app path tracking
- User hash generation for privacy
## License
Databricks License
Raw data
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"description": "# dbdemos-tracker\n\nA Python library for tracking Databricks demo analytics.\n\n## Installation\n\n```bash\npip install dbdemos-tracker\n```\n\n## Usage\n\n### Manual App Usage Tracking\n\n```python\nfrom dbdemos_tracker import Tracker\n\n# Create tracker for app - Use your repo name as app name\nws = WorkspaceClient()\ntracker = Tracker(org_id=ws.get_workspace_id(), demo_name=\"app-name\")\n\n# Track app views in functions\n@app.get(\"/\")\ndef home():\n tracker.track_app_view(user_email=\"user@databricks.com\", app_path=\"/dashboard\")\n return {\"message\": \"Welcome to my demo app\"}\n```\n\n### FastAPI Middleware\nWe provide a tool to track all app views out of the box.\n\nTry to filter on the main actions so that we don't have too many views using `patterns=[\"/my/.*/url/to/track\", \"...\"]`\n\n```python\nfrom fastapi import FastAPI\nfrom dbdemos_tracker import Tracker\n\n# Create FastAPI app\napp = FastAPI(title=\"My Demo App\")\n\n# Add tracking middleware - this will track ALL requests automatically\nTracker.add_tracker_fastapi(app, \"app-name\"))\n# You can also filter to only track some URL:\nTracker.add_tracker_fastapi(app, \"app-name\", patterns=['/demos/.*/load']))\n\n# Then all your API endpoints will be tracked out of the box\n@app.get(\"/\")\ndef home():\n return {\"message\": \"Welcome to my demo app\"}\n\n# Run with: uvicorn main:app --reload\n```\n\n### Streamlit Integration\n\n**EXPERIMENTAL - NOT TESTED - REACH OUT FOR HELP ON #field-demos**\n\n**Automatic Interceptor (Recommended):**\n```python\nimport streamlit as st\nfrom dbdemos_tracker import Tracker\n\n# Setup automatic tracking - call this once at the top of your app\nTracker.setup_streamlit_interceptor(\"app-name\")\n\n# Your Streamlit app - all interactions are automatically tracked!\nst.title(\"My Demo App\")\n\n# These will be automatically tracked:\nif st.button(\"Process Data\"):\n st.write(\"Data processed!\")\n\nname = st.text_input(\"Enter your name\")\nage = st.slider(\"Age\", 0, 100, 25)\noption = st.selectbox(\"Choose option\", [\"A\", \"B\", \"C\"])\nenabled = st.checkbox(\"Enable feature\")\n\n# Set user email for tracking (optional)\nst.session_state.user_email = \"user@databricks.com\"\n```\n\n**Manual Tracking (if needed):**\n```python\n# Track specific interactions manually\nTracker.track_streamlit_app(\"app-name\")\n```\n\n## Configuration\n\n### Disable Tracking\n\n```python\n# Disable tracking globally\nTracker.enable_tracker = False\n\n# Re-enable when needed\nTracker.enable_tracker = True\n```\n\n### Email Filtering\n\nThe tracker automatically filters emails to only track Databricks email addresses (`@databricks.com`). Non-Databricks emails are ignored for privacy.\n\n### Test Workspace\n\nTracking is automatically disabled for test workspace ID `1660015457675682`.\n\n## Features\n\n- Track demo usage analytics\n- Configurable tracking enable/disable\n- Automatic Databricks email filtering\n- Error handling with timeout protection\n- FastAPI middleware for automatic request tracking\n- Streamlit integration for app interaction tracking\n- Support for both notebook and app path tracking\n- User hash generation for privacy\n\n## License\n\nDatabricks License \n",
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