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A set of hands-on JupyterLab workshops for Tachyon, the sampling profiler in Python 3.15, and the story of why I wrote them to learn it myself.

Seventy free hands-on workshops, from writing decorators with just the standard library through wrapt to testing and tracing with wrapture. Nothing to install.

Writing a small guided workshop for JupyterLab from nothing with jupyterlab-workshop: the manifest, pages, actions, checks, linting, self-testing and author mode.

A JupyterLab extension for guided interactive workshops, with instructions in a side panel whose actions drive the session and check the learner's work as they go.

A summary of my PyCon AU 2026 talk on whether developer workshops still matter when anyone can ask an AI, and why I released 24 wrapture workshops anyway.

wrapture and its instrumentation packages are now at 1.0.0b1 with the API settled. A summary of the posts so far, the packages, the docs, and 24 workshops you can run in your browser on mybinder...

The same events that print a tree or fill a file can feed an OpenTelemetry backend while the application runs, with one trace id shared across files, headers and spans.

One endpoint is slow and there are three layers it could be. Self time for the handful of methods you chose answers the question without a profiler and without a stopwatch in every layer.

One HTTP request as one tree, from a single config entry, with the failing request saying both that it answered 500 and why.

Tracing an application you cannot or should not edit: the bindings and sink move into a TOML file next to the project, and the program runs untouched.

The bindings used to test a piece of code are the same objects that trace it. Take away the timeline, register a sink, and a running program narrates itself.

What a wrapture binding can name that is not a call: attribute reads and writes, values held in place for a test, the content of a settings dict, callables in a registry, and generators consumed...

Testing retry logic, circuit breakers and polling loops with wrapture's phases, where a binding's behaviour changes on a count, a condition, an exhausted sequence, or a signal from elsewhere.

How wrapture's timeline and tape record what real code did, and how to filter, assert on and walk that record. Worked through on a resource leak that no return value reveals.

The same unit tests written with unittest.mock and with wrapture, focusing on the cases where wrapping the real code rather than replacing it changes what a test can say.

wrapture is a new Python package for monkey patching, testing and tracing built on wrapt, written by an AI under my direction. What it does, why I built it, and what happens next.

Free-threading in mod_wsgi 6.0.0 lets a single process spread Python work across multiple cores. A metrics comparison against the GIL-enabled benchmarks from before.

mod_wsgi 6.0.0 adds WSGISwitchInterval, a tuning lever for Python's GIL switch interval. With proper telemetry it can deliver large gains on CPU-bound workloads.

mod_wsgi 6.0.0 adds WSGIFreeThreading, an opt-in directive for PEP 703 free-threaded Python. GIL-enabled mode remains the default even on free-threaded builds.

mod_wsgi 6.0.0 adds WSGIPerInterpreterGIL, an opt-in directive for running sub-interpreters with their own GIL (PEP 684) for parallel Python in one process.

How wrapt 2.2.0 extends the synchronized decorator and context manager to async functions, and why reentrancy is not supported on the async side.

How wrapt 2.2.0 lets a decorator change what runtime introspection sees of a wrapped function's signature or calling convention.

Deferred monkey patching has been in wrapt for years. Python 3.15's lazy imports make it the right default for instrumentation libraries.

How wrapt 2.2.0's lru_cache helper builds on top of functools.lru_cache to fix the issues with using it on instance methods.

A walkthrough of the new bind_state_to_wrapper helper in wrapt 2.2.0 and how it makes stateful decorators in Python easier to write.

Free interactive workshops on Python decorators hosted on the Educates training platform.

Having the Claude browser extension review an Educates workshop as a real user would.

Educates is open source, not a SaaS. Deploy it yourself, wherever you want.

Using an AI agent skill to generate interactive Educates workshops.

From copy and paste to fully guided workshop experiences with clickable actions.

The backlash against AI slop is justified, but risks dismissing purposeful content along with the noise.

What are the major forces that have reshaped developer advocacy.

How to detect if an object has already been wrapped.

How to test out Python lazy module imports right now.

Version 2.0.0 of wrapt is finally available.

Using the wrapt object proxy around immutable objects.

How to implement Python lazy import mechanism using wrapt.

The current status of my Python wrapt package and what to expect next.

After a 6 year hiatus from posting, I'm back.