Python Bytes

Topics covered in this episode:

Web UIs for your reverse proxy

Wagtail 8.0 is hot off the presses

RISC-V is now officially supported by CPython

Django’s annual releases make every version an LTS

Extras

Joke

Watch on YouTube

About the show

Sponsored by Logfire from Pydantic: pythonbytes.fm/logfire
Connect with the hosts

Michael: Mastodon / BlueSky / X / LinkedIn

Calvin: Mastodon / BlueSky / X / LinkedIn

Show: Mastodon / BlueSky / X
Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Tuesday at 7am PT. Older video versions available there too.
Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it.

Michael #1: Web UIs for your reverse proxy

Traefik, nginx, and Caddy all sit in front of a lot of self-hosted infrastructure, and all three are configured by hand-editing files. Three active projects put a control plane on top: Traefik Manager (Python + Flask), Nginx UI (Go + Vue), and caddy/ui (React + Node). All three are additive rather than replacements - none of them take ownership of your config away from you - which is the part that matters when the thing has write access to production routing.

Traefik Manager is the Python one: Flask 3.1 and Gunicorn for the control plane, a lightweight Go agent for remote instances, currently v1.10.0 with an Android companion app.

Nginx UI is a single Go binary at 11.3k stars, with a block-style config editor, an Ace editor doing LLM completion on nginx syntax, and an MCP server so agents can drive it.

caddy/ui runs as two containers next to your existing Caddy, reads and writes your Caddyfile directly, and uses Caddy's /adapt API to validate before reload - no Docker socket required.

Each one edits the config the underlying server already reads, so your files stay the source of truth and you can drop the UI without unwinding anything.

Undo is a first-class feature across all three - timestamped backups with optional Git history, config version compare and restore, Caddyfile snapshots with one-click rollback.

Observability is where they diverge: Traefik Manager does CrowdSec and a visual route map, Nginx UI does server metrics, caddy/ui streams access logs over SSE and pulls p50/p95/p99 off Caddy's Prometheus endpoint.

Maturity spread is wide - Nginx UI has 11.3k stars, caddy/ui has 4 and was built in a single Claude session - and caddy/ui ships with auth off by default, so set CADDY_UI_USER and JWT_SECRET before it goes anywhere near a public interface.

Calvin #2: Wagtail 8.0 is hot off the presses

Link: https://github.com/wagtail/wagtail/releases/tag/v8.0

Custom base page models are now supported, so projects aren't locked into subclassing Wagtail's Page as shipped (Matt Westcott).

New v3 REST API handles both read and write CMS operations, a first for Wagtail's API.

A global registry for permission policies, plus full customizability for the remaining page views via PageViewSet.

AVIF and WebP images are no longer auto-converted to PNG by default, a real behavior change to watch on upgrade.

Five security fixes: page admin API restrictions, document identification by SHA1 hash, descendant collections in the Documents/Images API, snippet copy permissions, and the page translation endpoint.

Formalized Django 6.1 support, and CI now runs on uv with a lockfile.

Sponsor: Logfire from Pydantic

Your AI agent failed at 2am. Was it the model? A tool call? The database? Most observability tools can't tell you, because they only see part of your stack.
Pydantic Logfire sees all of it. One trace across your agents, LLMs, APIs, and database. Down to the infrastructure: services, Kubernetes, and hosts.
It's built on OpenTelemetry, with SDKs for Python, TypeScript, and Rust, and it works with any OTel-compatible language.
Every prompt, token count, and cost, right next to your vector searches and API calls.
You query everything with Postgres-compatible SQL. And so can your coding agent, through the Logfire MCP server.
Stop guessing. Read the trace.
Pydantic Logfire. AI, it's still just engineering.
Visit pythonbytes.fm/logfire today and sign up today. Get 10M records free every month, no card required. You can even click “Onboard with your coding agent” to copy a prompt to have claude or codex integrate Logfire into your app.
Thanks to Pydantic for supporting the show.

Calvin #3: RISC-V is now officially supported by CPython

Link: https://blog.python.org/2026/08/riscv-now-officially-supported/

CPython added RISC-V as a tier 3 platform under PEP 11, specifically the 64-bit Linux target riscv64-unknown-linux-gnu.

RISC-V is an open ISA anyone can implement, unlike x86 and ARM, and its market is projected to quadruple by 2032.

The RISE Project donated real RISC-V machines for buildbots; the author's work was funded by a Sovereign Tech Agency fellowship.

What changes: the port is now a maintained compatibility target, so CPython changes are less likely to quietly break it. What doesn't: no python.org installers, no binary wheel parity for native extensions.

Next up: RISC-V runners in CPython CI for pre-merge feedback, then a push toward tier 2, plus architecture-specific optimizations.

The ask is testing. If you have RISC-V hardware, build CPython, run your test suite, file what breaks.
Tier 3 is the weakest support tier. PEP 11 tier 3 requires a core developer contact and a buildbot, but failures on tier 3 platforms explicitly do not block a release. Saying "ongoing CI/testing expectations" oversells it. The honest bit is "someone is now on the hook for it, and breakage gets noticed," not "it's guaranteed working."
Worth the caveat that this is Linux SBCs, not microcontrollers. A VisionFive 2 counts, an ESP32-C6 or Pico 2 does not. Those are 32-bit non-Linux parts where MicroPython is still the answer.

Michael #4: Django’s annual releases make every version an LTS

Starting with Django 2028, Django will move to one January feature release per year, adopt calendar-based version numbers, and support every release for three years. The old distinction between standard and LTS releases disappears, giving teams a predictable annual upgrade path that aligns more closely with Python’s own release and support cadence.

Every Django release becomes the safe, long-supported choice, so teams no longer need to wait for a specially designated LTS version or absorb two years of changes at once.

Each release gets one year of mainstream bug fixes followed by two years of security and data-loss fixes.

New releases support the three latest Python versions and add the next Python release during their first year.

Calendar versioning begins with Django 2028, followed by Django 2029 and so on.

Three Django versions will be supported at any time, giving third-party packages a clearer rolling target.

Nothing changes before 2028, and existing commitments for Django 5.2 LTS and 6.2 LTS remain in place.

Extras

Calvin:

The Python docs now document the time complexity of built-in types
https://docs.python.org/3.16/library/time-complexity.html

Thinking in Python - Bruce Eckel's free book
https://thinkinginpython.com/
Michael:

prune_uv_pythons.py - Prune uv-managed Python installs, keeping only the newest patch per minor version

Runs automatically in my system “upgrade” script: upgrade-output-2026.png

Started using Ollama cloud models for my Hermes assistant. Thanks to Jeff Triplett I learned they are not just local models.

Joke: The Tao of Programming - Book Seven: Corporate Wisdom

Topics covered in this episode:

Python 3.12.14, 3.11.16, 3.10.21 - security releases

Codeberg’s AI-code ban tests its role as a GitHub alternative

Brett Cannon: what's missing for reproducible builds on PyPI

nothing records the source code a distribution came from. direct_url.json captures it when you install from a repo or archive, so the fix is putting the same info in sdist/wheel metadata.

recording the build tools. Wheels can already do this via PEP 770 SBOMs in .dist-info/sboms/ - sdists can't, since they're a tarball plus a precalculated PKG-INFO with nowhere to hang extra metadata. Either "don't use sdists" or an sdist v2.

Extra extra extra, hear all about it

Extras

Joke

Watch on YouTube

Sponsored by Logfire from Pydantic pythonbytes.fm/logfire

This episode is brought to you by Pydantic Logfire. It's observability for AI apps from the team behind Pydantic - agents, LLMs, APIs, database, and infrastructure in a single trace, queried with Postgres-compatible SQL. Your coding agent can query it too, through their MCP server. I'll tell you more later.

Connect with the hosts

Michael: Mastodon / BlueSky / X / LinkedIn

Calvin: Mastodon / BlueSky / X / LinkedIn

Show: Mastodon / BlueSky / X

Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Tuesday at 7am PT. Older video versions available there too.

Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it.

Calvin #1: Python 3.12.14, 3.11.16, 3.10.21 - security releases

https://blog.python.org/2026/08/python-31214-31116-31021/

Source-only security releases for the three branches now in security-fix-only mode; release team blamed the European solar eclipse for the timing.

tarfile hardening. Multiple path-traversal bypasses of the data filter closed, including a symlink escape that bypassed the CVE-2025-4330 fix; extract() now applies the filter to link targets too.

Four fresh CVEs: CVE-2026-2297 (SourcelessFileLoader not using io.open_code() for .pyc), CVE-2026-4224 (expat crash on deeply nested content models), CVE-2026-3644 (control chars in http.cookies.Morsel), plus the completed CVE-2021-4189 fix in ftplib.ftpcp.

Quadratic-complexity DoS cleanup across the stdlib: HTMLParser, configparser regexes, unicodedata.normalize(), csv.Sniffer.sniff(), and ElementTree XPath index predicates.

Header/injection fixes: CR/LF rejected in HTTPConnection.set_tunnel(), control chars blocked in wsgiref.handlers status, and webbrowser now rejects leading dashes (plus a %action prefix bypass).

http.client now caps chunked trailer lines and 1xx interim responses at 100 each - a hostile server could previously hang the client forever despite a socket timeout.

Memory-safety odds and ends: stale pointers in lzma/bz2/zlib decompressors after MemoryError, a bz2 stack overflow on reuse-after-error, and bundled libexpat bumped to 2.8.3.
If you're still on 3.10, 3.11, or 3.12 - and you extract tarballs from anywhere you don't fully control - this one's not optional.

Michael #2: Codeberg’s AI-code ban tests its role as a GitHub alternative

Armin’s article “Codeberg Divides”

Armin Ronacher argues that Codeberg’s new terms, which prohibit projects mostly written with generative AI, create a vague and difficult-to-enforce boundary. His larger concern is that a democratically governed host can still be unpredictable or ideologically narrow, weakening Codeberg’s potential as a broad European alternative to GitHub.

The strongest question for Python developers is whether repository hosting should judge legal open source by how code was produced, or focus on behavior and resource abuse.

“Mostly generated” is hard to measure in modern codebases where developers mix handwritten code, completions, agents, and generated refactors.

Ronacher suggests clearer alternatives: ban all LLM involvement, or target autonomous repository spam, abusive resource use, and low-quality generated contributions directly.

Codeberg is free to choose a values-driven community, but that may conflict with being predictable, neutral infrastructure and a serious GitHub competitor.

Worth discussing: can open-source communities set meaningful AI boundaries without driving maintainers and projects into opposing camps?

Very first search for these terms lands on this page.

Codeberg looked like a viable alternative. … Unfortunately, the latest update to its terms of service seems to mark a first step in changing one part I moved there for, namely the “freedom” part.

Sponsor: Logfire from Pydantic

Your AI agent failed at 2am. Was it the model? A tool call? The database? Most observability tools can't tell you, because they only see part of your stack.
Pydantic Logfire sees all of it. One trace across your agents, LLMs, APIs, and database. Down to the infrastructure: services, Kubernetes, and hosts.
It's built on OpenTelemetry, with SDKs for Python, TypeScript, and Rust, and it works with any OTel-compatible language.
Every prompt, token count, and cost, right next to your vector searches and API calls.
You query everything with Postgres-compatible SQL. And so can your coding agent, through the Logfire MCP server.
Stop guessing. Read the trace.
Pydantic Logfire. AI, it's still just engineering.
Visit pythonbytes.fm/logfire today and sign up today. Get 10M records free every month, no card required. You can even click “Onboard with your coding agent” to copy a prompt to have claude or codex integrate Logfire into your app.
Thanks to Pydantic for supporting the show.

Calvin #3: Brett Cannon: what's missing for reproducible builds on PyPI

Framing came out of his 2026 Python Packaging Council nomination - the secure-supply-chain gap he found is that Python has no defined way to do reproducible builds at all.

Design goal is zero friction: producers uploading to PyPI shouldn't have to do anything. The work lands on build backends and installers.

Gap #1: nothing records the source code a distribution came from. direct_url.json captures it when you install from a repo or archive, so the fix is putting the same info in sdist/wheel metadata.

Gap #2: recording the build tools. Wheels can already do this via PEP 770 SBOMs in .dist-info/sboms/ - sdists can't, since they're a tarball plus a precalculated PKG-INFO with nowhere to hang extra metadata. Either "don't use sdists" or an sdist v2.

The replay mechanism already exists: [build-system] in pyproject.toml is a defined entry point, so if backends recorded their own environment, you could reinstall and re-run the build.

Payoff idea: trusted third parties report successful reproductions back to PyPI, which displays "independently reproduced by X" - surfaced in the index API so installers could prefer reproduced files.

Explicitly framed as a perk, not a requirement - roughly SLSA build level 1, no shaming projects that don't opt in.
Verbal kicker option: "And don't think pure-Python wheels are off the hook. Something built that wheel, and if that something was compromised, so is your wheel. SolarWinds was a build-process attack."

Michael #4: Extra extra extra, hear all about it

Python 3.14.7

Upgraded the MCP servers to 2026-07-28 v2 protocols (talk python, python bytes)

Got agentsview running synced via postgres

Talk Python courses, teams trial offering

Talk Python courses, government procurement offering

Lean TDD audio book is out

Extras

Calvin:

uv now prefers post-quantum key exchange - https://github.com/astral-sh/uv/releases/tag/0.12.4

Joke: Beware of dog

Topics covered in this episode:

Claude Code /insights

Post-quantum crypto lands in Python

MCP goes stateless — and FastMCP gets renamed

inshellisense - IDE style command line auto complete

Extras

Joke

Watch on YouTube

About the show

Sponsored by Xweather
Xweather combines enterprise-grade weather intelligence with agent-ready APIs, natural language capabilities, and an MCP server so your agents can adapt workflows, automate responses, and make better decisions based on real-world conditions.
Michael will tell you more about them later in the show. Get started for free at pythonbytes.fm/xweather
Connect with the hosts

Michael: Mastodon / BlueSky / X / LinkedIn

Calvin: Mastodon / BlueSky / X / LinkedIn

Show: Mastodon / BlueSky / X
Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Tuesday at 7am PT. Older video versions available there too.
Finally, if you want an artisanal digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it.

Michael #1: Claude Code /insights

Michael’s Insights: michael-kennedy-claude-code-insights-2026-08-09.html

Be careful sharing these outputs, they include details references to your projects, errors, security findings, etc. ;)

/insights reads your last 30 days of local session transcripts and hands back an interactive HTML report on how you actually work.

One command, zero setup: type /insights in a session, or run claude -p "/insights" from the shell for a non-interactive version that just prints the path

Reads what's already on disk: pulls session logs from ~/.claude/projects/, skipping agent sub-sessions and anything under 2 messages or 1 minute

Project areas: clusters your sessions into themes like "CLI Tooling" or "Documentation" with session counts

Friction analysis: categorizes where things went wrong by root cause - and quotes your own prompts back at you

Interaction style: tells you whether you're a delegator or a micromanager, plus which workflows are worth doubling down on

Actually actionable: suggests concrete CLAUDE.md additions and Claude Code features you're not using

The catch: Haiku does the per-session classification, so the first run takes several minutes; results cache to ~/.claude/usage-data/facets/ and the report lands at ~/.claude/usage-data/report.html

Calvin #2: Post-quantum crypto lands in Python

pyca/cryptography 48 ships ML-KEM (key establishment) and ML-DSA (signatures) — NIST's post-quantum standards, now one pip install away.

Big deal because it's the 11th most-downloaded package on PyPI (~1.2B downloads/month) and sits under Ansible, Certbot, Airflow, and paramiko. No PQ there, no PQ anywhere in Python.

Trail of Bits did the work (Rust bindings, cross-backend API, tests, AWS-LC backend support), funded by the Sovereign Tech Agency.

Timing tracks a June 22 White House order setting federal deadlines: PQ key establishment by end of 2030, PQ signatures by end of 2031.

Not a drop-in swap — the wire sizes explode. ML-DSA-65 signatures are 3,309 bytes vs Ed25519's 64; ML-KEM-768 public keys are 1,184 bytes vs X25519's 32. Hardcoded field sizes and length prefixes will bite.

API looks like the existing asymmetric primitives, except ML-KEM is encapsulate/decapsulate rather than a Diffie-Hellman exchange. SLH-DSA (the hash-based conservative backstop) is still in progress.
The primitives are here, but protocols haven't caught up — so you won't be running post-quantum Certbot this week.

Sponsor: Xweather

You're using agents that can write code, summarize documents, and automate workflows. But they're missing one thing: awareness of the world around them. This is where today's sponsor, Xweather comes in.
Xweather combines enterprise-grade weather intelligence with agent-ready APIs, natural language capabilities, and an MCP server built for tools like Claude, Codex, Copilot, and modern IDEs – so your agents can adapt workflows, automate responses, and make better decisions based on real-world conditions.
Backed by Vaisala, whose instruments fly on NASA missions to Mars, Xweather delivers trusted data and unique insights that go beyond conditions to actual impact – from real-time lightning strikes to road surface forecasts.
Start with 15,000 free API calls each month and pay only for what you use as you grow.
Xweather is your full weather stack, for developers by developers. Start building for free today at pythonbytes.fm/xweather. The link is in your podcast player's show notes and on the episode page.
Thanks so much to Xweather for supporting Python Bytes.

Calvin #3: MCP goes stateless — and FastMCP gets renamed

From Philipp Acsany over at Real Python

The 2026-07-28 spec landed July 28 and the Python SDK shipped 2.0.0 the same day. Biggest rewrite since MCP launched, and it's breaking on purpose. Context for scale: the Tier 1 SDKs are pulling close to half a billion downloads a month, with TypeScript and Python each past a billion total.

The headline is the stateless core. The initialize/initialized handshake and the Mcp-Session-Id header are both retired — protocol version, client identity, and capabilities now ride in _meta on every request, with an optional server/discover RPC if a client wants capabilities up front. Any request can land on any instance behind plain round-robin, no shared storage.

Server-initiated calls are the hard part of the migration. Sampling, elicitation, and roots/list no longer call back to the client; instead the server returns resultType: "input_required" and the client retries with inputResponses attached. Multi Round-Trip Requests, MRTR. Also: Mcp-Method and Mcp-Name are now required headers so gateways route on headers instead of cracking JSON bodies, and missing-resource errors move to standard 32602.

Deprecation sweep with an actual policy behind it — Roots, Sampling, Logging, and the legacy HTTP+SSE transport all deprecated with a twelve-month minimum offramp. Tasks graduated out of the experimental core into a real extension, which is what the formalized extensions framework was for. MCP Apps is now an official extension too, so a tool call can return sandboxed interactive HTML. Auth picked up RFC 9207 issuer validation, issuer-bound credentials, and a shift from DCR toward CIMD.

Python SDK 2.0 is where it gets personal: FastMCP is now MCPServer, no alias, no shim. McpError → MCPError. Wire types went snake_case (is_error, input_schema) and moved to a standalone mcp_types package, with mcp.types kept as a permanent alias. One Client object replaces the old transport + ClientSession + initialize() stack. httpx became httpx2. Sync handlers run on worker threads now, so asyncio.get_running_loop() raises inside them.

The good news: one MCPServer serves both protocol eras, so 2025-era clients keep working with nothing to configure, and a Resolve(fn) parameter lets one tool body cover MRTR and the old path. 1.x is maintenance-and-security-fixes only — pin mcp>=1.28,<2 if this week is already full. The Tasks extension isn't in 2.0.0 yet, so Tasks has left the core spec but hasn't landed in the SDK.
If you only call MCP servers, you mostly just get the benefits for free. If you ship one, you already know what your week looks like. And if you use the standalone fastmcp package instead of the official SDK — different project, 3.x line, none of this touches you. The rename is partly to stop the two from being confused.

Michael #4: inshellisense - IDE style command line auto complete

via Doug Nichols

inshellisense provides IDE style autocomplete for shells.

It's a terminal native runtime for autocomplete which has support for 600+ command line tools.

inshellisense supports Windows, Linux, & macOS.

If you are using a NerdFont patched font, you can enable the NerdFonts support in your config file

Extras

Calvin:

Django 6.1 Released — https://www.djangoproject.com/weblog/2026/aug/05/django-61-released/

DjangoCon US is quickly arriving, grab your tickets now! — https://2026.djangocon.us/
Michael:

AI integration: Python Bytes for AI

Up and Running with Rust Course is out!

Joke: But they already know

Topics covered in this episode:

Some more things about Django I've been enjoying

Who cleans up after the vibe-coding party?

Where Did All Your AI Tokens Go? AgentsView to the rescue!

Careful with phishing all

Extras

Joke

Watch on YouTube

About the show

Sponsored by us! Support our work through:

Our courses at Talk Python

Consulting from Six Feet Up

Connect with the hosts

Michael: Mastodon / BlueSky / X / LinkedIn

Calvin: Mastodon / BlueSky / X / LinkedIn

Show: Mastodon / BlueSky / X

Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Tuesday at 7am PT. Older video versions available there too.

Finally, if you want an artisanal, hand-crafted digest of every week of the show notes in email form? Add your name and email to our friends of the show list, we'll never share it.

Calvin #1: Some more things about Django I've been enjoying

Julia Evans is learning "2010-style" web dev (Django + SQL + server-rendered HTML) after years of Go backends and JS-heavy frontends

Query builders: likes defining custom QuerySet classes with chainable filter methods (.approved().future().with_tags()) — more readable than raw SQL

Template filters: highlights urlize, linebreaksbr, json_script, and especially querystring for building/modifying query-string links in templates

Migrations: still loves Django's auto-generated migrations — 19 and counting on her project

Skips inheritance for class-based views; prefers function-based views for sharing code, though fine using Django's own mixins/interfaces

Performance surprise: CPU profiling (via py-spy) — not slow DB queries — revealed the culprit; she'd accidentally disabled the cached template loader, and re-enabling it took throughput from ~2-3 req/s to ~12 req/s on a $10/mo VM

Michael #2: Who cleans up after the vibe-coding party?

FT Magazine piece by Sam Learner (July 11) on AI coding tools overwhelming open source maintainers - sent in by listener Dylan McConnell, whose main point was that this ran in the Financial Times, not a dev blog.

cURL as the case study - Daniel Stenberg has been the only full-time person on it for years; libcurl has been installed an estimated 20+ billion times with 3,000+ listed contributors.

Bug bounty killed - cURL ended its paid security bounty program in January, citing an "explosion of AI slop reports" that take real time to debunk and drain morale.

Extractive contributions - authoring a PR is now nearly free, reviewing one still costs a human; tldraw's Steve Ruiz closed outside contributions entirely, asking why he'd want someone else writing the easy part.

Guido weighs in - van Rossum says projects are holding emergency meetings over the slop flow, and notes LLM patches tend to touch unrelated parts of a file, making review more tedious.

"Vibe Coding Kills Open Source" - paper from Miklós Koren's group: packages frequently recommended by coding models saw big download jumps with no matching engagement, breaking the reputation loop that sustains maintainers.

Stack Overflow flatlined - over 100,000 questions a month before ChatGPT, under 1,500 last month, with the response rate cut roughly in half; the public archive is now stale training data.

The course-creator angle - Josh Comeau's newest web dev course launched at about a third of prior enrollment, and he worries about devs who never learn which questions to ask.

But the most interesting portion is what was omitted.

Focused on: The end of the curl bug-bounty

Omitted: High-Quality Chaos

Why the omission is interesting

It fits a narrative. The FT piece is a maintenance-and-decline story, and January-Stenberg is a perfect witness for it. April-Stenberg complicates it - same person, same project, better data, opposite direction on the specific claim being used.

The tell is already in the article. Learner quotes Stenberg saying AI tools are much better at finding problems than fixing them. That's the April thesis in one line, and it goes undeveloped.

Reason for the shift is process, not vibes. Killing the bounty removed the cash incentive and the venue change filtered the rest. Worth saying out loud, because "AI reports got better" isn't quite it - "no bounty plus a real triage platform" is closer.

Joke too: Sarah O’Connor wrote a related piece (is this just before skynet launches?)

Calvin #3: Where Did All Your AI Tokens Go? AgentsView to the rescue!

Local-first desktop/web app for browsing, searching, and analyzing your past AI coding agent sessions (Claude Code, Codex, Copilot, Cursor, Gemini, Aider, and dozens more)

Auto-discovers session files on your machine — no config needed; everything stored locally in SQLite, no cloud/accounts

agentsview usage is a drop-in ccusage alternative — reads from pre-indexed SQLite, reports run 80–220× faster on large histories

New Activity dashboard shows peak concurrency, active vs. idle time, agent-minutes, and cost — filterable by project/agent/machine, with a -json CLI report too

Full-text + optional semantic search across every session; also imports Claude.ai/ChatGPT chat exports

Install via pip install agentsview, uvx agentsview, brew install --cask agentsview, or download desktop binaries from GitHub Releases

Michael #4: Careful with phishing all

The situation

I pass this along because it was a pretty sneaky bit of targeted phishing, and happened to play off an old interaction in bandit's repo. As usual with phishing scams there are a bunch of tells that this isn't legitimate, but just enough plausibility that I could see falling for it in a weak moment. Relative nobodies like me haven't historically been worth the effort to hit with scams this specific. Agents change the game though :-/. Be careful out there folks!

Original message

From: "Patrick (Blacktrace)" [HTML_REMOVED]
To: LISTENER EMAIL
Subject: Your Bandit #1350 (B105 NextToken false positive) -- just fixed that exact case

Date: Wednesday, July 15, 2026 12:02 AM

Hi AJ,

Saw your Bandit issue #1350 -- the B105 hardcoded-password false positive on the string NextToken. I build a deterministic gate that filters that class of Bandit noise, and #1350 was literally the case I just fixed: NextToken / next_token / page_token / nextPageToken now stay quiet, while a genuine hardcoded token like api_token="sk-live-..." still fires. Verified against your exact case.

30-second paste: https://blacktrace.co/noise-eraser

Where it still trips, published: https://blacktrace.co/kruc

Curious whether it clears what you hit -- and if it trips on something of yours, that's the more useful reply.

Patrick, Blacktrace

I asked Claude for some analysis too. It was pretty good at finding them.

The message name-drops enough real detail to feel legit, but the structure is pure phishing - everything in it exists to get AJ onto blacktrace.co. The strongest ones:

Freemail sender, corporate signoff. Signs as "Patrick, Blacktrace" but sends from emailpjv@gmail.com. Real company outreach comes from the company domain, not a personal Gmail - and there's no last name.

Over-specific targeting. It mirrors AJ's exact public activity - issue #1350, the B105 rule, the NextToken false positive, even the token variants. That's the "just enough plausibility" AJ flagged, and it's exactly what agents make cheap: scrape a GitHub issue, auto-generate tailored bait. Legit cold outreach rarely reads your history back to you this precisely.

The entire payload is two links. Strip the technical flattery and the message is just "paste here" plus "see results here." When the whole point of an email is the click, that's the tell.

"30-second paste." Low-friction urgency, and "paste" most likely means paste your source into their tool - handing your code to a stranger's site. Exfiltration dressed as convenience.

Brand-new, no-reputation domain. blacktrace.co has no track record, and the name is doing some ominous work. The /kruc slug is random noise, not how real product pages get named.

Precise-sounding jargon that's actually vague. "Deterministic gate," "noise-eraser" - impressive, empty. Bolted onto correct real details (B105 is the Bandit hardcoded-password test, sk-live- is a Stripe live-key prefix) to borrow credibility.

The disarming close. "if it trips on something of yours, that's the more useful reply" - engineered humility that flatters your expertise and baits a response. Makes engaging feel like you're doing them a favor, which drops your guard.

Extras

Calvin:

DjangoCon US 2026 is rapidly approaching, August 24-28, Chicago

Ruff v0.16.0 massively expands its default rule set

Ruff now enables 413 rules by default, up from 59

https://astral.sh/blog/ruff-v0.16.0

Michael:

Completely redesigned the home page.

Try /insights in Claude Code (terminal)

Joke: We’re Safe

Topics covered in this episode:

django-orjson

Best Django Redis configuration for speed and size

Linus Torvalds puts the foot down against Anti-AI Kernel Maintainers

Django Steering Council backs the Triptych Project

Extras

Joke

Watch on YouTube

About the show

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Consulting from Six Feet Up

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Michael: Mastodon / BlueSky / X / LinkedIn

Calvin: Mastodon / BlueSky / X / LinkedIn

Show: Mastodon / BlueSky / X

Join us on YouTube at pythonbytes.fm/live to be part of the audience. Usually Tuesday at 7am PT. Older video versions available there too.

Michael #1: django-orjson

Adam Johnson dropped django-orjson - drop-in replacements for the Django and DRF pieces that touch JSON, swapping stdlib json for orjson, the Rust-based library. Headline numbers: 10x faster serialization, 2x faster deserialization.

The interesting question is why this needs to be a package at all. pip install orjson is the easy part. Adam's actual pitch: adopting it "isn't easy, especially when your framework uses json in many different parts." Django scatters JSON across JsonResponse, the test client and test case classes, the json_script template tag, and more. There's no single hook to grab, so you get a library that catches them all.

Adam is refreshingly honest about the scale of the win. His words: "While database queries tend to dominate the typical Django application's runtime, the time spent in serialization and deserialization can still be significant." He calls it "a nearly free performance win" - not "this will 10x your app." That's a claim about cost, not magnitude, and it's worth keeping those straight.

Worth flagging what the post doesn't cover: caveats. There are none in the article, but orjson has real ones. Django and Flask both render datetimes as RFC 822 HTTP-date (Wed, 15 Jul 2026 12:00:00 GMT); orjson does ISO 8601. It can't do ensure_ascii, it rejects NaN and Infinity (which stdlib happily emits), and it raises on Decimal. If you've got a JS client parsing dates, that's a wire-format change.

Who should actually take this? If you're a DRF shop shoveling JSON all day, yes - it's cheap and it's real. If your app mostly renders HTML templates, you're optimizing a slice of runtime that's already near zero.

The problem Adam's package solves doesn't exist in Flask or Quart. They already centralize every JSON operation - jsonify, request.get_json(), the test client, the |tojson filter - behind one provider object at app.json. So there's no library to install. It's about ten lines:

import orjson
from quart.json.provider import JSONProvider # or flask.json.provider
class OrjsonProvider(JSONProvider):
def dumps(self, obj, **kwargs) -> str:
return orjson.dumps(obj).decode() # provider must return str
def loads(self, s, **kwargs):
return orjson.loads(s)
app.json = OrjsonProvider(app)

The numbers on talkpython.fm

Evaluated it, measured it, and skipped it. The biggest JSON payload we serve is our MCP server returning a cached episode transcript, about 139 KB. Swapping the provider saves 0.119 milliseconds per request. That total response takes 1.1 ms

We got 4.1x, not 10x - and the reason is the good lesson. Payload shape decides your speedup. The 10x is for structure-heavy data, lots of small keys where stdlib burns time in Python-level dispatch per item. Our hot payload is one giant transcript string, so the work is escaping and memcpy

Calvin #2: Best Django Redis configuration for speed and size

Peter Bengtsson revisits a classic: his 2017 "Fastest Redis configuration for Django" benchmark now has a 2026 update posted this week.

The 2017 post pitted django-redis serializers (json, ujson, msgpack, pickle) and compressors (zlib, lzma) against each other; conclusion was msgpack + zlib as the sweet spot - avoid the json serializer, it's fat and slow.

The 2026 update narrows focus to just compressors: default (no compression), zlib, lzma, and newcomer zstd.

New results: lzma compresses best but is slowest; zstd is the fastest compressor on Ubuntu; differences between them are very small.

Big takeaway across both: compression buys you a lot of space (2–3.5x smaller) for very little speed cost - worth it for Redis where memory is the constraint.

Caveat from the author: results depend heavily on your data - his test stores short strings of numbers, so benchmark your own workload.

Michael #3: Linus Torvalds puts the foot down against Anti-AI Kernel Maintainers

Write up on Ars.

Really good coverage by Maximillian: Time to wake up (for some)

Torvalds said that “Linux is not one of those anti-AI projects, and if somebody has issues with that, they can do the open-source thing and fork it. Or just walk away.”

I agree with Max, putting your head in the sand and waiting for AI to go away will likely mean you won’t be working professionally in software development in the coming years.

The statement came amid a lengthy thread arguing about the use of Sashiko, an “agentic Linux kernel code review system” that its creators claim can, in tests, independently find 53.6 percent of the bugs that would end up being fixed by human coders in later commits.

“We’re not forcing anybody to use [LLM tools], but I will very loudly ignore people who try to argue against other people from using it,” Torvalds said.

“Anybody who points to the problems at AI had better be looking in the mirror and pointing at themselves at the same time,” Torvalds wrote.

Calvin #4: Django Steering Council backs the Triptych Project

Django Steering Council issued a Letter of Collaboration backing Carson Gross & Alex Petros's funding bid for the Triptych Project - three proposals to make HTML more expressive natively, in every browser.

The three additions: PUT/PATCH/DELETE methods for forms, button actions (buttons that fire HTTP requests without a wrapping form), and partial page replacement.

Distills the core ideas from HTMX/Unpoly/Turbo into the HTML standard itself - no JS, no library, nothing to ship or maintain.

Current focus is button actions (WHATWG #12330): <button action=/logout method=POST>Logout</button> instead of wrapping a button in a form.

Relevant to Django directly - think the admin submit row and disguised delete links; Django 6.0's template partials were already inspired by these patterns.

How to help: companies can send non-binding letters of support on letterhead; individuals can read the proposals and weigh in on the WHATWG issues.

Extras

Calvin:

DOOMQL - A playable first-person shooter whose framebuffer is a SQL query.

Michael:

Granian 2.7.9 fixes WSGI threadpool scheduler starvation/underscaling

Welcome Calvin post

Joke: Solving all bugs