ruby

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.

Noel Rappin's MountainWest RubyConf talk introduces Smalltalk to Ruby programmers. He compares the two languages' object models, blocks, 1-based arrays, simple syntax and live programming environment, and walks through sample code.

Tom Stuart's Ruby Manor 3 talk builds FizzBuzz using nothing but Ruby lambdas, working through Church encodings of numbers, booleans and data structures. It is a hands-on introduction to lambda calculus.

Glenn Vanderburg argues at Lone Star Ruby Conference 2010 that university-style software engineering does not work, and asks what real software engineering would look like. He revisits the waterfall model and what engineering means in other fields.

Gary Bernhardt's RubyConf 2012 talk on testing in isolation without mocking everything. It goes through behavior versus data, mutation versus immutability, and how a functional core with an imperative shell yields natural isolation and parallelism.

Greg Baugues tells his story of living with bipolar II and ADHD as a developer at a Ruby conference. He urges openness about mental illness and explains how to get help and support colleagues.

Sandi Metz's RailsConf 2013 talk offers practical guidelines for deciding what to test and how, so tests stay cheap and stable. She argues for testing the public interface rather than implementation and using mocks appropriately.

Sandi Metz argues that hidden assumptions in code are missing concepts, and shows how to name and expose them so code is easier to understand and change. It covers null objects and messages in Ruby.

Sandi Metz takes an ugly section of conditional code and refactors it into a few simple objects, bridging object-oriented theory and practice. The talk includes her take on the Gilded Rose refactoring kata and the idea that duplication is cheaper than the wrong abstraction.

Yehuda Katz's Railsberry 2012 talk on why Rails is hard to learn and use. He explains that the framework's many features reflect real complexity in web applications that newcomers do not yet see.

Matt Wynne's GoRuCo 2012 talk on why Rails apps get hard to change as they grow, and how a ports-and-adapters hexagonal architecture separates application logic from the framework.

Aaron Patterson's RailsConf 2011 talk on Rails 3.1 performance, showing why deeper Rack middleware stacks slow Rails and how a shallower pipeline helps. It also touches on Rack API design.

Richard Feldman's GOTO Copenhagen 2022 talk on why dynamic languages like Python, Ruby, PHP and JavaScript rose in the 1990s and why each now has a popular static type checker. It argues that modern static typing recovers the advantages that made dynamic languages attractive.

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.

Philip Roberts explains the JavaScript event loop, call stack, callbacks and asynchronous behavior with live visualizations using a tool he built. It demystifies terms like non-blocking and single-threaded.

Sam Stephenson's RailsConf 2016 talk on Turbolinks 5, showing how small teams can ship fast Rails apps in the browser and hybrid iOS and Android apps sharing one set of web views.

Tavis Rudd describes how RSI forced him to program by voice, and shows the Python and Emacs Lisp system he built with voice recognition. A live demo creates and deploys a small system without touching the keyboard.

Raymond Hettinger's PyCon 2013 talk on transforming code into idiomatic Python through a series of before-and-after refactorings. It shows how to use iterators, dictionaries, named tuples and other language features well.

Jack Diederich's PyCon 2012 talk argues that classes are overused in Python and walks through real code, refactoring away unnecessary classes, exceptions and modules. It popularized the heuristic that a class with two methods, one being __init__, should be a function.

Mirabai Knight's PyCon 2013 talk on Plover, a free cross-platform stenography engine that lets people write at up to 240 WPM on ordinary hardware, including a demo of coding by steno.

Paul Graham's keynote at PyCon 2012, in which he talks about startup ideas and what kinds of companies are likely to matter in the future. He discusses ideas such as a better email client and a search engine for hackers, and argues for looking back at the present from the future.

Miguel de Icaza's GodotCon 2023 talk on Swift bindings for Godot. He argues that garbage-collector pauses in C# are a persistent problem and that Swift's reference counting avoids them.

Joel Grus's JupyterCon talk explaining why he dislikes Jupyter notebooks. He covers hidden state, trouble with reproducibility and testing, and how notebooks frustrate teaching. He shows his preferred workflow and what Jupyter could change.

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.

Brandon Rhodes' PyOhio 2014 talk on applying the Clean Architecture in Python. He shows how this high-level design pattern fits Python's features and addresses maintainability problems in large applications.

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.

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.

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.

David Beazley's PyCon 2010 talk explains how the Python Global Interpreter Lock works and shows experiments where multithreaded code runs slower, even on more cores, due to lock contention and context-switching overhead.

David Guillot describes how his team replaced a two-year-old React UI of their SaaS product with Django templates and htmx in a couple of months. The talk gives concrete indicators on code size, performance and team impact.

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.

First lecture of MIT 6.00, an introductory computer science course taught in Python by Eric Grimson and John Guttag. It covers the goals of the course, what computation is, and data types, operators and variables.

Emily Shea, a Fastly engineer with repetitive strain injury, describes using voice dictation as her main way of programming. She covers homophones, custom vocabulary and building her own voice commands to write Perl.

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.

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.

Ricardo Signes' YAPC::Asia Tokyo 2011 talk on the legends and horrors of email: how messy the SMTP and email standards are in practice. The first few minutes are Perl-specific, but the rest applies to anyone handling email.

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.

Brian Cardarella's RailsConf 2016 talk on why and how teams can move from Rails to Elixir and Phoenix. It covers performance gains without losing productivity and how to introduce Phoenix in an organization.

David Schachter describes how he made a data-collection Python program run 114,000 times faster, drawing on decades of experience. The talk covers pipelining, cache effects and other optimization lessons.

Charlie Marsh of Astral explains how uv, a Rust Python package manager, got so fast. He covers allocators, concurrency, zero-copy tricks and the challenges of Python packaging.