Verify DataSag analytics on Flask with Jinja

Start with the Flask with Jinja installation

Put the deferred external script once in the shared Jinja base template under your application templates directory. Preserve existing blocks, imports and asset links. Confirm that render_template calls for your public routes select children of that base. The tracker remains an external browser script rather than Python application code.

Blueprint-specific template directories and independent render_template_string responses can bypass the base template. A child head block can replace inherited content unless it retains it. Inspect the generated response from the affected endpoint.

Use the public project key from the DataSag project you are inspecting. A test on a preview domain does not confirm that the production domain has the same code or settings.

Verify DataSag analytics in Flask with Jinja

1. Trace the Flask endpoint render_template call to its Jinja child and base. Confirm the shared head contains one tracker and that a head block override retains it where intended.
2. Publish the application release and open a nested route in a clean browser. Inspect the generated HTML and accepted pageview request. Python template source or a local test response alone does not prove the deployed release is active.
3. Test a route from another blueprint if it has its own template directory or base. Check its public key and path separately. Keep API endpoints and render_template_string responses outside the shared-template assumption.

The sampled Flask endpoints and blueprint template paths render and deliver the intended browser tracking.

Complete the collection checks

1. Open the published website in a normal browser window with the Network panel recording. Use a browser profile where you can control extensions and your consent choice.
2. Filter network requests for tracker.js. Confirm it returns JavaScript successfully and that the rendered script has the project's data-datasag-key attribute. The example YOUR_PUBLIC_KEY must be replaced.
3. Filter for /api/track and reload once. Inspect a request with eventName null or absent. Its projectKey and path should match the chosen project and the page you opened.
4. Open that DataSag project, choose a date range containing today and inspect the matching path. Use the configured report timezone when checking dates.
5. Navigate to a second path, then use Back. Compare pageview requests with the route changes rather than counting every request as a pageview.

document.querySelectorAll('script[data-datasag-key]').length
// Expected: 1

document.querySelector('script[data-datasag-key]')?.getAttribute('data-datasag-key')
// Expected: your project's public key

typeof window.datasag?.track
// Expected after the script runs: 'function'

What a successful check looks like

One rendered tracker installation, a successful request for the intended page and a corresponding entry in the intended project. Scroll and engagement requests are separate event types.

Record the public path you tested, the browser state, the approximate time and the observed request. Check one direct page load and one later navigation so the result covers more than the homepage.

Common mistake

A successful tracker.js download only proves that a file loaded. It does not validate the project key, consent state or tracking endpoint. Test a real published path before declaring setup complete.

Installation snippet for Flask with Jinja

The shared installation belongs in the head of the Jinja base template used by your routes. Use this as the installation reference while checking the procedure above.

<script defer src="https://www.datasag.com/tracker.js" data-datasag-key="YOUR_PUBLIC_KEY"></script>

Related Flask with Jinja guides

• Fix DataSag analytics not working
• Fix duplicate analytics pageviews
• Track custom events
• Track UTM campaigns
• Measure AI referral traffic
• Configure CSP for DataSag analytics
• Exclude your own analytics visits
• Load analytics without blocking rendering

Full Flask with Jinja setup guide · Search and AI visibility

References

Official Flask with Jinja documentation covers the integration point. For DataSag data handling, read the privacy policy. Use support if a request fails after these checks.