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Brian #1: profiling-explorer
- Adam Johnson
- And intro post Python: introducing profiling-explorer
- “profiling-explorer is a tool for exploring profiling data from Python’s built-in profilers, which are stored in pstats files. ”
- Features
- Dark mode
- Click the calls, internal ms, or cumulative ms column headers to sort by that column.
- Use the search box to filter by filename or function name.
- Hover by a filename + line number pair to reveal the copy button, which copies the location to your clipboard for faster opening.
- Click the callers or callees links on the right of a row (not pictured above) to see the callers or callees of that function.
Michael #2: Reverting the incremental GC in Python 3.14 and 3.15
- Python 3.14 shipped with a new incremental garbage collector, but production reports of severe memory pressure (Neil Schemenauer measured up to 5× peak RSS on pathological cyclic workloads) have pushed the core team and Steering Council to revert it in both 3.14 and 3.15 - returning to the 3.13-era generational GC.
- This is the second time the inc GC has been pulled back: it was also reverted right before 3.13.0 final, and it shipped in 3.14 without going through the PEP process.
- The tradeoff is real: Neil's benchmarks showed max GC pause times of 1.3ms with inc GC versus 26ms with the generational one - great for latency-sensitive apps, terrible for memory-constrained ones.
- Release manager Hugo van Kemenade will ship 3.14.5 early with the revert, and Gregory Smith floated the idea of a 3.14.5rc1 - the first patch-release RC since 3.9.2 back in 2021.
- Tim Peters spent the thread doing live forensics on Windows, running a toy deque program that should cap at 1GB and watching it balloon to 15.6GB on a 16GB machine - and discovered the gen0 collector effectively never fires under the new scheme.
- Tim's bigger meta-point: CPython has a chronic shortage of real-world GC benchmarks, pyperformance has "basically no interesting" cyclic workloads, and users almost never share real data - so core devs keep flying blind on changes like this.
- Django maintainer Adam Johnson published a blog post mid-thread documenting a real memory "leak" in Django's migration system caused by inc GC, with a manual
gc.collect() workaround - the listener-facing receipt that this wasn't just theoretical. - If the inc GC comes back for 3.16, it'll go through a proper PEP, and the discussion is already shifting toward keeping both collectors available via a startup flag - which Neil and Sergey Miryanov have both prototyped.
Brian #3: VSCode AI Co-author defaults to on, then off
Michael #4: django freeze
- Convert your dynamic django site to a static one with one line of code.
- Just run
python manage.py generate_static_site :) - Features
- Generate the static version of your Django site, optionally compressed .zip file
- Generate/download the static site using urls (only superuser and staff)
- Follow sitemap.xml urls
- Follow internal links founded in each page
- Follow redirects
- Report invalid/broken urls
- Selectively include/exclude media and static files
- Custom base url (very useful if the static site will run in a specific folder different by the document-root)
- Convert urls to relative urls (very useful if the static site will run offline or in an unknown folder different by the document-root)
- Prevent local directory index
Extras
Brian:
Michael:
Joke: Friends in tech
