# django-silky 1.7.0: a rebuilt django-silk UI that shows which line causes your N+1 **URL:** \ **Category:** Packages\ **Created:** [October 29, 2026, 12:57pm UTC](https://forum.djangoproject.com/t/django-silky-1-7-0-a-rebuilt-django-silk-ui-that-shows-which-line-causes-your-n-1/46336 "2026-10-29T12:57:01Z")\ **Posts on this page:** 1\ **Page:** 1
**Author:** ![vaishnavghenge](https://sea2.discourse-cdn.com/flex026/user_avatar/forum.djangoproject.com/vaishnavghenge/32/29035_2.png) [@vaishnavghenge](https://forum.djangoproject.com/u/vaishnavghenge)\ **Post date:** [October 29, 2026, 12:57pm UTC](https://forum.djangoproject.com/t/django-silky-1-7-0-a-rebuilt-django-silk-ui-that-shows-which-line-causes-your-n-1/46336/1 "2026-10-29T12:57:01Z")
![demo](https://us1.discourse-cdn.com/flex026/uploads/djangoproject/original/3X/c/7/c7d881857d55d69fe8595993e13de9c423163f59.gif) django-silky is my fork of django-silk. It keeps the same app label, middleware and settings, and carries upstream’s migrations unchanged, so switching is a package swap plus `manage.py migrate silk`. 1.7.0 rebuilds the whole interface, and it’s the first release I’d recommend trying even if plain silk works fine for you. The part I use most: open a request and, if it has an N+1, the panel names the line in your code that runs the repeated query and suggests the `select_related()` or `prefetch_related()` call that would batch it. It also shows the endpoint’s usual time and query count, so you can tell a slow request from a slow endpoint. Three pages are new: - **SQL** groups every recorded query by shape, with calls, total and p95 time, and DB time per table. - **Hotspots** ranks lines of your app code by the database time they cause, and flags the ones running inside a loop. - **Compare** puts two requests or two time ranges side by side, down to which query patterns appeared or disappeared. It’s also faster. On 5,000 recorded requests (76,000 queries) the Summary page renders in 59 ms instead of 465 ms, and the requests list runs 13 queries for its rows instead of 59. JavaScript per page dropped from 0.7 to 2.4 MB to 20 to 78 KB, jQuery and Bootstrap are gone, and filtering updates the list in place instead of reloading. A few pages render a little slower on a cold cache because they now show more (sidebar counts, the endpoint baseline). Every figure is in `benchmarks/README.md` with the scripts to reproduce it. Two things to know before upgrading. Migration 0010 adds two indexed columns to `silk_sqlquery` and backfills them, which took about 10 s for 76,000 queries on SQLite. If you override silk templates, check them against the new ones: the old base templates are gone. URL names and `SILKY_*` settings didn’t change. ```bash pip uninstall django-silk pip install django-silky python manage.py migrate silk ``` Repo, screenshots and migration guide: [GitHub - VaishnavGhenge/django-silky: Silky smooth profiling for Django · GitHub](https://github.com/VaishnavGhenge/django-silky) I’d like to hear what’s missing, especially from anyone running silk against Postgres or MySQL with a lot of recorded data.