python internals

Armin Ronacher, creator of Flask, explains how CPython's internals and C API leak into the language's semantics. Using examples like the complexity of the add operation, he shows why Python is hard to optimize or reimplement.

Brandt Bucher presents his prototype JIT compiler for CPython at the 2023 Core Developer Sprint. He explains the copy-and-patch approach, the implementation and its performance.

Armin Ronacher's EuroPython 2017 keynote examining how the CPython interpreter's leaky abstractions affect language design and how Python could evolve, drawing on JavaScript and Rust experience.

Larry Hastings explains what Python's GIL is, what problems it solves and how it works, and presents his Gilectomy project to remove it, including the performance and C-extension obstacles.

A PyData London 2018 talk on how JPMorgan scaled its Athena Python platform over ten years to about 35 million lines of code and thousands of developers. It covers infrastructure, tooling and culture for analytics and visualization at that scale.

An open Q&A with Python creator Guido van Rossum hosted by Microsoft Reactor, covering his career, PyCon's origins and his opinions on other languages.

An overview of the PTVS 2.0 beta feature for debugging Python and C/C++ together in one session in Visual Studio.

Alex Martelli's Google Developers Day talk on classic design patterns (creational, structural and behavioral) and how they appear in Python. He stresses that patterns must be studied in the context of the implementing language.

David Beazley's workshop screencast builds asynchronous programming in Python from scratch, starting from callbacks and continuations and replacing threads to show how concurrency works underneath.

Raymond Hettinger's PyBay 2018 keynote on preventing, finding and fixing bugs under a time budget. He covers testing practice, type annotation tradeoffs and the limits of coverage metrics.

John Kitchin shows how Emacs org-mode with Python lets researchers combine narrative, math, figures and executable code in one document. It exports to LaTeX, HTML and PDF, and he used it for papers and e-books.

David Beazley's PyData Global 2021 keynote, an oral history of early scientific Python. He tells how Python ended up running on a Connection Machine supercomputer at Los Alamos.

A three-hour PyCon 2016 tutorial by Christophe Pettus that orients Python developers to PostgreSQL. It covers installation, administration, and use, including vacuuming, MVCC, replication and backups.

Ned Batchelder's PyCon 2012 talk gives a quick overview of what Unicode is, then focuses on what a Python programmer needs to handle text correctly. It presents the 'Unicode sandwich' strategy: decode bytes at input, work with Unicode internally, encode at output.

Raymond Hettinger's PyBay 2019 talk on the mental strategies he uses when programming in Python, such as chunking, solving a simpler related problem, and repeating tasks manually until patterns emerge. This version is re-synced with the slides.

Anthony Scopatz presents xonsh at PyCon 2016, a shell that is a superset of Python combining the best features of bash, zsh and fish. It covers rich history, tab completion, and how the language compiles to a Python AST.

A PyCon 2012 talk by early YouTube engineer Mike Solomon on how YouTube scaled its architecture, which is mostly Python.

Developer Voices interviews Chris Lattner about Mojo, a Python-compatible language aimed at CPU/GPU performance built on LLVM and MLIR. It covers performance features, the type system and why Mojo uses Python syntax.

David Beazley's PyCon India closing keynote, in which he live-codes a stack machine and grows it into an interpreter that runs WebAssembly, then uses it to play a Rust-written game. It requires no prior WebAssembly knowledge.

Robert Erdmann, a materials scientist at the Rijksmuseum, gives a PyCon keynote on the ultra-high-resolution imaging of Rembrandt's Night Watch. He covers the automated gantry camera system, the Python software that drives it, and the large volumes of image data involved.

Nathaniel J. Smith's PyCon 2018 talk introducing Trio, a Python concurrency library designed around usability and structured concurrency. He live-codes a problem and analyzes pitfalls in other async libraries.

A one-minute clip from Monty Python's Life of Brian in which revolutionaries grudgingly list everything the Romans have done for them, from roads to clean water. It is a satirical sketch about refusing to credit a disliked group.

David Beazley's PyCon 2019 tutorial derives the lambda calculus from the ground up in Python, using only single-argument functions. He builds booleans, numerals and more with no other language features.

Cory Benfield's PyCon 2016 talk on building protocol libraries that can be reused widely, using the Python Hyper HTTP project as the example. He argues for separating protocol parsing from I/O.

Felienne Hermans presents Hedy, a gradual programming language for teaching kids that moves through levels from almost no syntax toward full Python. The talk covers why error messages and syntax are scary for beginners.

A PyCon 2013 block of Friday evening lightning talks. It includes the debut of Hy, a Lisp dialect that compiles to Python AST, and Solomon Hykes's first public talk on Docker.

A Monty Python sketch in which Oscar Wilde, James Whistler and George Bernard Shaw trade witticisms in a stuffy literary salon with Bertie.

A five-minute lightning demo of VisiData, a terminal tool for exploring and manipulating data. It uses two months of NYC 311 complaint data to drill down, plot points on a virtual map and save selected rows.

Cliff Click of Azul Systems asks what a JVM is supposed to do, in a Google Tech Talk from 2011. He covers the services a JVM provides, such as garbage collection and compilation, and the messy reality beneath the abstractions.

Hillel Wayne's PyCon 2018 talk on testing beyond pytest and mypy. It introduces property-based testing with the Hypothesis library and design-by-contract with dpcontracts, and shows how to combine them with an existing test suite.

Jake Vanderplas's PyCon 2016 talk shows how sampling-based methods such as simulation, shuffling and bootstrapping make statistics intuitive. His pitch is that if you can write a for-loop, you can do statistics.

Brian Warner, author of magic-wormhole, presents the tool at PyCon 2016. He explains how a few secret words let two computers securely transfer files, covering the cryptography (NaCl, SPAKE2) and library use.

K Lars Lohn's PyCon 2016 keynote weaves together music theory, programming, biking road trips and fractals. It is a personal, wide-ranging talk rather than a Python how-to.

Elasticsearch engineer and Lucene committer Adrien Grand explains the design decisions inside a Lucene index and what problems it can and cannot solve. The talk goes into how Lucene stores data for fast search and analytics.

Christopher Domas's DEF CON 26 talk on secret processor registers that vendors reserve for third parties holding trusted keys. He examines how users are locked out of parts of their own CPUs.

Timothy Baldridge presents Pixie, a lightweight Lisp built on RPython, at Strange Loop 2015. It covers C interop, immutable data structures, fast startup and async-by-default IO.

A short Portuguese-language excerpt of Gerald Sussman's 2016 NYC Lisp Meetup talk explaining why MIT replaced the Scheme-based 6.001 (SICP) course with Python courses. The full talk is linked in the description.

An AWS re:Invent 2018 session in which Holly Mesrobian and Marc Brooker explain how AWS Lambda is built, including its sandboxing, isolation and scaling architecture. It covers what happens under the hood when serverless code runs.

Cuong Do of YouTube describes how a handful of engineers scaled the site, covering hardware, software and database scalability challenges during its rapid growth. The talk was given at the 2007 Seattle Conference on Scalability.

Jim Weirich's RubyConf 2012 talk derives the Y combinator step by step, live-coding in Ruby lambdas. It builds up an understanding of functional programming and lambda calculus from first principles.