PyCon US 2023
2023-04-19..2023-04-27
-- online --
PyCon US ·
[PyCon US 2008, PyCon US 2020, PyCon US 2021, PyCon US 2022, PyCon US 2023, PyCon US 2024, PyCon US 2025, PyCon US 2026]
| title | author | length |
|---|---|---|
| Welcome to | Mariatta Wijaya | 29m |
Debut of a 20 years throwback video and concrete logistics: 89 talks across five tracks, live captioning for key rooms, meals in the expo hall and a swag sale… | ||
| Keynote Speaker – Ned Batchelder | Ned Batchelder | 47m |
Keynote claims people behave like high-uncertainty components and gives a concrete model: every message carries information + sentiment, and missing sentiment… | ||
| Keynote Speaker – Python Steering Council | James Powell | 21m |
The Python Steering Council states concrete changes: F-strings moved into parser for measurable speed and proper nesting, an experimental per-subinterpreter… | ||
| Keynote Speaker – Diversity and Inclusion Panel | 24m | |
Panel states the PSF DNI work group has representatives from every continent except Antarctica, shows the board’s diversity growth over 20 years, and gives… | ||
| Keynote Speaker – James Powell | James Powell | 26m |
Argues that replacing a monolithic scipy.optimize.newton API with an explicit generator yields concrete gains: fewer combinatorial keyword arguments, far fewer… | ||
| Keynote Speaker – Margaret Mitchell | Margaret Mitchell | 42m |
Creates early image‑description systems in 2011 that surpass human BLEU scores yet fail blind users because BLEU misses real needs; builds a Seeing AI… | ||
| Keynote Speaker – Carol Willing | Carol Willing | 45m |
Three concrete claims: networks rest on connection communication scale, interactive notebooks scale education and research, and LLMs and agents are tools not… | ||
| Community Service Awards & Python Software Foundation Update | Deb Nicholson | 27m |
The Python Software Foundation reports infrastructure and community milestones: 300 million downloads per day for Python, PyPI growth of 57% in 2022, and 152… | ||
| Keynote Speaker – Guido van Rossum | Guido van Rossum | 31m |
A personal retrospective traces PyCon from the first Python Workshop (1994) with about 30 people through the move to annual conferences, Fortec-run IPCs, and… | ||
| Closing Ceremony | Mariatta Wijaya | 34m |
Closing ceremony summarizes outcomes and next steps with numbers and logistics: 2,000 attendees total, 1672 first‑timers, 270 travel grants distributed (about… | ||
| Lightning Talks | 46m | |
A rapid grab bag of five‑minute community demos: a Python+Rich pipeline that renders tables to SVG then converts them with ImageMagick and Inkscape and uploads… | ||
| Lightning Talks | 59m | |
A rapid-fire mix: a Temporal workflow stack using Pydantic models and YAML deployment, a PyOpenSci review that turned Crozet into a published package, an… | ||
| Lightning Talks | 01h 04m | |
A rapid set of concrete takeaways: PyPI traffic is quantified as 257 million requests per week and AWS funds a PSF security hire; an organizations feature for… | ||
| Intro to Hugging Face: Fine-tuning BERT for NLP tasks | Juhi, Dana | 02h 10m |
Shows step‑by‑step fine‑tuning of a public BERT checkpoint via Hugging Face + PyTorch in Jupyter notebooks: tokenization, masked‑LM and next‑sentence… | ||
| Introduction to Property-Based Testing | Zac Hatfield-Dodds, Ryan Soklaski | 01h 31m |
Introduction covers property-based testing using Hypothesis and pytest with runnable examples that actually find bugs: a NaN case breaking sort, floating-point… | ||
| Intro to Python for Brand New Programmers | Trey Hunner | 02h 17m |
Starts at the basics and shows actual code: live use of the python REPL, building and running scripts (greetings.py, rand.py, die.py), surprising big integers… | ||
| Comprehending comprehensions | Reuven M. Lerner | 02h 18m |
Claims that comprehensions are both essential and often misunderstood get demonstrated with concrete code: live Jupyter notebooks pushed to GitHub show list… | ||
| Build a production ready GraphQL API using Python | Patrick Arminio | 02h 23m |
Hands-on workshop that builds a production GraphQL API with Strawberry on Django, using Gitpod/PDM for setup, async resolvers, cookie auth and mutations that… | ||
| Data analysis with SQLite and Python | Simon Willison | 02h 46m |
Shows concrete workflows: use Python's sqlite3 and sqlite-utils to import CSVs (14,341 manatee records), normalize columns into foreign keys, and add ISO… | ||
| Web Development With A Python-backed Frontend: Featuring HTMX and Tailwind | Mario Munoz | 02h 26m |
Claims a Python-backed frontend replaces JSON-over-HTTP complexity with hypermedia using htmx and Tailwind CSS, implemented with FastAPI, Jinja templates… | ||
| Feature Engineering is for Everyone! | Leah Berg, Ray McLendon | 02h 17m |
Claims that non‑scientists can create features get tested with runnable Colab notebooks using pandas, ydata‑profiling, scikit‑learn, CountVectorizer… | ||
| Data of Unusual Size: Interactive Visualization | Pavithra Eswaramoorthy, Dharhas Pothina | 03h 07m |
Loads a 70 GB CSV airline set from cloud storage, converts to columnar Parquet, and shows why data types, partitioning and pre-sorting matter for performance… | ||
| How to create beautiful interactive GUIs and web apps | Lisa Carpenter | 01h 58m |
3.5 hour hands‑on tutorial uses the streamlit library to build interactive Python GUIs, showing actual code: st.cache_data for expensive loads, session… | ||
| Writing Serverless Python Web Apps with PyScript | Ted Patrick | 02h 55m |
Claims: Python web apps run entirely in the browser (no server) by fetching runtimes and wheels over URLs. Tools actually used: PyScript with pyodide vs… | ||
| Write your first package using literate programming | Ítalo Epifânio | 01h 51m |
Shows exactly what gets built and what tools actually wire it up: export notebook code to a package with Nbdev, build sdist and wheel with twine, push a… | ||
| The How and Why of Object-oriented Programming in Python | Mike Müller | 02h 46m |
Starts from a working procedural script that reads CSVs and produces the same travel‑time chart, then refactors that code into classes and small, testable… | ||
| Introduction to Decorators: Power Up Your Python Code | Geir Arne Hjelle | 02h 21m |
Covers how decorators actually work and how to write them: uses IPython, time.sleep, pathlib and random and standard tools like functools.cache and… | ||
| Power up your work with compiling and profiling | Cheuk Ting Ho | 01h 33m |
Workshop demonstrates using Numba to speed numeric Python: profiling with cProfile identifies backprop and element‑wise loops as hotspots, then applying Numba… | ||
| Automate Documentation with Sphinx & GitHub Actions | Olga Matoula, Aya Elsayed | 46m |
Shows how to generate HTML docs from real docstrings using Sphinx autodoc + Napoleon, builds per-module rst with sphinx-apidoc, applies the furo theme, and… | ||
| Exploring Eco topics with Python | Mx Chiin-Rui Tan | 02h 59m |
Shows exact datasets and code: numpy pandas matplotlib geopandas networkx xarray rioxarray inside prepared Jupyter notebooks, not high-level promises. Filters… | ||
| How To Troubleshoot and Monitor Applications using OpenTelemetry | Ron Nathaniel | 02h 02m |
Shows exactly what gets built and what it actually produces: a local demo (Docker Compose) that runs Jaeger, Zipkin, Prometheus and an OpenTelemetry Collector… | ||
| Building human-first and machine-friendly CLI applications | Reka Horvath | 02h 28m |
Builds a CLI catalogue of PyCon talks using clig.dev guidelines and scaffolds the project with Cookiecutter plus poetry, implements commands with typer and… | ||
| Building a Model Prediction Server | Ethan Swan | 01h 45m |
Starts from a trained scikit-learn model (an Iris classifier the uploader notes as 100% accuracy), loads the pickle via importlib.resources, and embeds it in a… | ||
| Getting Started with Polars | Matt Harrison | 02h 14m |
Workshop uses Polars 0.17.5 on a real Twitter CSV (~5700 rows × 40 cols) and shows concrete moves: parse messy datetimes with strptime and timezone convert… | ||
| Eroding Coastlines: A Geospatial & Computer Vision Analysis | Kevin Lacaille, Mansi Shah | 01h 34m |
Uses Planet satellite imagery and runnable Colab notebooks to show a reproducible pipeline: reading multispectral data with rasterio and numpy, computing NDWI… | ||
| Publishing your Python project, the conda way | Dave, Bianca, Valerio, Mahe | 02h 45m |
Step‑by‑step demo shows creating a conda environment, writing a small Python package (dnd_roller) with tests, adding dependencies (nomoji, tabulate), and… | ||
| Developing on Google Cloud with Python and DataFrames | Jason Davenport | 40m |
BigQuery is presented as a serverless analytics engine with a 250 petabyte single-query scale, result caching (~24 hours), and SQL plus Python execution paths… | ||
| Accelerate your workflow from local Python prototype to the cloud | S. Ostrowski | 51m |
Shows a working end-to-end workflow that actually scaffolds, provisions and deploys a Python React app using the Azure developer CLI so local code becomes live… | ||
| Using Python to Power Serverless Applications | Brian McNamara, Dan Furman | 01h 02m |
Capital One shows Python powering API, streaming and ML-inference workflows with concrete artifacts: a GitHub sample project (pycon2023), local testing via AWS… | ||
| Modern, typed Python for (multimodal) ML | Johannes Messner | 57m |
Argues that Python type hints are now practical in ML and shows concrete tooling: mypy and beartype for checks, Pydantic+FastAPI for APIs, jaxtyping for tensor… | ||
| How to build stunning Data Science Web applications in Python | Vincent Gosselin, Florian Jacta | 54m |
Taipy presents a low‑code Python stack — Taipy Core, Taipy GUI, and Taipy Studio — that claims to build full data‑science apps with scenario management… | ||
| Building LLM-based Agents | Tuana Celik | 35m |
Claims a reproducible pattern: an LLM (GPT‑4) acting as a decision loop that picks real tools, runs them, and composes answers. Implements Haystack pipelines… | ||
| Joyful Django DX with PyCharm | Paul Everitt | 01h 02m |
PyCharm demos real, concrete DX: IDE-created virtualenvs and Django run configs, template and template-debugger breakpoints that show template context, SQL… | ||
| Fixing legacy code, one pull request at a time | Guillaume Dequenne | 54m |
Modernize a tiny Flask Pokedex by onboarding SonarCloud, running SonarCloud automatic analysis then switching to CI-based Sonar scan with GitHub Actions to… | ||
| Python & Bloomberg: An Open Source Duo | Pradyun Gedam, Bernát Gábor, Laszlo Kiss Kollar, Mario Corchero, Matt Wozniski, Pablo Galindo Salgado | 57m |
Bloomberg describes concrete work: Python 3.11 gains frozen modules that cut startup syscalls from ~85 to ~14 and make cold starts roughly ten times faster in… | ||
| Advancements in High-Performance AI/ML through PyTorch's Python Compiler | Sam Gross, Justin Jeffress, Suraj Subramanian | 24m |
PyTorch 2.0 adds a Python-based compiler that captures program graphs with Dynamo, lowers them via FX and the frame-evaluation API (PEP 523), and emits GPU… | ||
| Python Profiling State of the World | Shana Matthews, Indragie Karunaratne | 56m |
Survey of concrete tools and results rather than theory: cProfile and profile are shown with measured overheads — 15% overhead for cProfile and ~106% for the… | ||
| Python Meets Heterogeneous Computing | Sponsor | 59m |
Claims a working Python SDK plus server called Covalent that orchestration-izes heterogeneous distributed runs, with AWS Batch and Azure Batch plugins, a desk… | ||
| Flagging in the Backend: Shipping API's with Flask and LaunchDarkly | Cody De Arkland | 51m |
A React front end talks to a Flask backend that uses the LaunchDarkly server SDK to toggle behavior at runtime; feature flags carry JSON configs (one contains… | ||
| Breaking Away from the Empire: Avoiding the Evil Clutches of If-Then Statements | Jason Koo, Alison Cossette | 53m |
A concrete claim: replace nested if‑then routing code with a graph model and query it. The demo loads 2000+ planets via CSV into neo4j + Cypher, uses a… | ||
| The ChatGPT Privacy Tango: Dancing with Data Security and Large Language Models | Jason Mancuso, Mike Gardner | 50m |
A working proxy system uses AWS Nitro enclaves and mutual attestation to encrypt uploads, run a de‑identification model inside enclaves, build embeddings into… | ||
| Build Yourself a PyScript | Nicholas H. Tollervey, Paul Everitt | 39m |
PyScript and Pyodide have gained a lot of attention, as Python in the browser presents interesting opportunities. And architectural questions as well. What… | ||
| Cross-Server Data Joins on Slow Networks with Python | Bert Wagner | 29m |
While working from home has its perks, you've found one thing missing in your remote work life: speed of network data transfer. It doesn't matter if you can… | ||
| Inside CPython 3.11's new specializing, adaptive interpreter | Brandt Bucher | 23m |
Python 3.11 was released on October 24th, bringing with it a new "specializing, adaptive interpreter." As one of the engineers who works on this ambitious… | ||
| Introducing incompatible changes in Python | Victor Stinner | 43m |
In the Python 2 era, it was decided to migrate at a D-Day: convert all your code base to Python 3. It didn't go as well as expected. We learnt lessons from… | ||
| How To Monitor and Troubleshoot Applications using OpenTelemetry | Ron Nathaniel | 24m |
OpenTelemetry is a free, open-source Observability Protocol. OpenTelemetry sits at the application layer, and exports Traces, Metrics, and Logs to a backend… | ||
| How Python is Behind the Science of the James Webb Space Telescope | Erik Tollerud | 31m |
The James Webb Space Telescope (JWST) is one of the largest science projects in history. Its aim is to blow the door open on infrared astronomy: it has already… | ||
| Improving Efficiency in Transportation Networks using Python | Uzoma Nicholas Muoh | 28m |
When we think about what Python is for, we often think of things like analytics, machine learning, and web apps, but python is a workhorse that plays a… | ||
| Building NumPy Arrays from CSV Files, Faster than Pandas | Christopher Ariza | 27m |
Claims a C extension delimited_to_arrays() that reuses Python’s csv.reader tokenizer, collects Unicode code point lines per column, then converts directly to C… | ||
| Instrumentation Nightmares: A review of our toughest cases | Hannah, Lalleh, Timothy, Uma | 40m |
Ever wonder how companies like New Relic, Data Dog, and Sentry instrument your code? In this talk we will briefly review how to hook into the Python import… | ||
| Working with Time Zones: Everything You Wish You Didn't Need to Know | Paul Ganssle | 30m |
Python now ships a concrete time zone implementation called zoneinfo that uses the IANA database and a pip fallback package called tzdata; it handles ambiguous… | ||
| My Personal Journey Teaching Programming to Neurodivergent Students | Marlene Marchena | 31m |
Describes switching from Python to Scratch to boost immediate engagement, running inclusive summer workshops and regular classes for 12–15 children aged 9–11… | ||
| Create interactive games using MicroPython and electronics | Juliana Karoline de Sousa | 30m |
Do you want to have fun and learn Python? Let's learn how to use electronics and programming to create games using MicroPython and a micro:bit board. In this… | ||
| Using Python and PyQgis to make cool maps | Samweli Mwakisambwe | 27m |
QGIS is a freely downloadable open source GIS software suite that contains a desktop option, mobile, and web component. QGIS is free to download and use, it is… | ||
| Three Musketeers: Sherlock Holmes, Mathematics and Python | Gajendra Deshpande | 35m |
Shows concrete forensic computations: shoeprint pressure computed with P = m g / A from measured depth and contact area, fall-distance angle thresholds that… | ||
| Jaguars and Snakes | Nicole Franco Leon | 31m |
Describes a workflow that processes VHF PTT and GPS telemetry CSVs into spatial points, converts points to lines, and computes kernel density and movement… | ||
| Solving Crimes with Python Using Natural Language Processing (NLP) | Carolina Passarello | 34m |
A Python-based workflow that classifies WhatsApp messages for crime-related signals: messages are extracted with the huasteca library into DataFrames… | ||
| Biohacking with Python: How to Become Mr. Burns Fluorescent | Marina Moro López | 32m |
A Python script and FASTA parser are used to design CRISPR reagents: it outputs a mutated target sequence, guide RNA(s), and DNA repair template(s) to delete… | ||
| Modernizing Your Python Package with pyproject and hatch | Oscar Cortez | 30m |
Shows migrating a legacy setup.py to pyproject.toml using Hatch’s new --init command, then creating isolated Hatch environments with per-environment… | ||
| Let’s Save the Penguins with Green Computing | Elena Guidi | 36m |
Presents concrete energy-impact figures for tech (7% of electricity use in 2019; ~70% projected demand increase by 2030; up to 222% rise for data-center… | ||
| Introduction to FastAPI | Sebastián Ramírez | 29m |
Introduces FastAPI, a Python web framework that builds production-ready JSON APIs from standard type annotations. Covers its use of Pydantic for validation and… | ||
| Unit Testing with Pytest | Sofía Denner | 33m |
Unit testing with pytest: shows how unit tests provide confidence for refactors and document behavior, demonstrates pytest’s precise failure diffs, and… | ||
| Improving debuggability of complex asyncio applications | Joongi Kim | 30m |
The key of debugging is observability and reproducibility. Despite a series of the asyncio stdlib improvements for the last few years, it is still challenging… | ||
| Why You Should Care About Open Source Supply Chain Security | Nina Zakharenko | 32m |
Over the past several years, large-scale hacks triggered by compromised software supply chains have dominated the news. The aftermath has inspired the creation… | ||
| Ergonomic codesigning for the Python ecosystem with Sigstore | William Woodruff | 29m |
Code signing is coming to the Python packaging ecosystem, in the form of Sigstore: individual package maintainers and users will be able to sign for and verify… | ||
| Async: scaling structured concurrency with static and dynamic analysis | Zac Hatfield-Dodds | 22m |
Async python is a relatively recent addition to Python’s longstanding concurrency options of processes and threads - and offers a very different programming… | ||
| Generators, coroutines and nanoservices | Reuven M. Lerner | 26m |
Generator functions have been a part of Python for many years already, and are a well known technique for creating iterators. But generators have a few… | ||
| Pythonic `functional` (`iter`)tools for your data challenges | Valerio Maggio | 33m |
Nowadays Python is very likely to be the first choice for developing machine learning or data science applications. Reasons for this are manifold, but very… | ||
| Working Around the GIL with asyncio | Łukasz Langa | 44m |
Concrete claim: using asyncio plus OS shared memory avoids pickle serialization overhead and yields a ~25× speedup on a 45 GB synthetic dataset (about 2… | ||
| Next level Machine Learning with TinyML and Python | Maria Jose Molina Contreras | 32m |
We usually associate the future of computing as large clusters being able to perform tasks in a fraction of a second, but is it really the only scenario on how… | ||
| Kill All Mutants! (Intro to Mutation Testing) | Dave Aronson | 30m |
How good is your test suite? Would it all still pass if the tested code was changed? If so, there may be problems with your code, your tests, or… | ||
| Consistency and isolation for Python programmers | A. Jesse Jiryu Davis | 24m |
Builds a toy Python telnet server demo that actually runs concurrency tests and shows which anomalies occur and why; implements read uncommitted, read… | ||
| Transforming a Jupyter Notebook into a reproducible pipeline for ML experiments | Rob de Wit | 26m |
Jupyter Notebooks are part of every data scientist's arsenal and for good reason. But while they're great for prototyping in data science projects, they are… | ||
| Testing Spacecraft with Pytest | Dan Craig | 30m |
Much of the industry discussion around software testing over the last couple of decades has been focused on web services, but there are lots of different types… | ||
| Trying No GIL on Scientific Programming | Cheuk Ting Ho | 29m |
Last year, Sam Gross, the author of nogil fork on Python 3.9, demonstrated the GIL can be removed. For scientific programs which use heavy CPU-bound processes… | ||
| Reproducible molecular simulations with Python | Iván Pulido | 31m |
In this talk the audience will be briefly introduced to the field of molecular dynamics simulations and its challenges. Special attention will be given to how… | ||
| A Per-Interpreter GIL: Concurrency and Parallelism with Subinterpreters | Eric Snow | 30m |
We live in a world of concurrent code and multi-core computing, so come learn about a new solution for both in Python 3.12. We'll quickly explain the new… | ||
| You *can* take it with you: Packaging your Python code with Briefcase | Russell Keith-Magee | 31m |
Once you're written your amazing new application using Python, the next problem you'll face is how to get that application into the hands of users. If your… | ||
| Inside web framework: intro to the ASGI spec, middleware and apps | Adrian Garcia Badaracco | 26m |
What do FastAPI and Django have in common? They both use ASGI under the hood. ASGI, which stands for Asynchronous Server Gateway Interface, is a specification… | ||
| Catching Tensor Shape Errors without Running Your Code | Pradeep Kumar Srinivasan | 27m |
ML developers are often slowed down by errors because of long iteration times and difficulty in debugging ML code. Tensor shape mismatches are some of the most… | ||
| How memory profilers work | Pablo Galindo Salgado | 31m |
These days, it is very easy for applications to run out of memory due to the vast amounts of data they need to process. While Python makes it very easy to get… | ||
| Rethinking Objects | Bruce Eckel | 32m |
This presentation revisits two core concepts of Object-Oriented programming: encapsulation and code reuse. Using a series of examples, we'll ask whether these… | ||
| Algorithmic ideas, engineering tricks, and trivia behind CPython's new sorting algorithm | Sebastian Wild | 30m |
Writing a sorting function is easy - coding a fast and reliable reference implementation less so. In this talk, I tell the story behind CPython's latest… | ||
| XGBoost for Classification: Building Accurate and Efficient Models | Laura Gutiérrez Funderburk | 35m |
Shows using XGBoost for binary classification on the UCI wine dataset: splitting data, fitting and predicting with model.fit, and searching hyperparameters via… | ||
| Low-code Interfaces with Qt and Their Integration with Python | Daniel Hernández Méndez | 22m |
Shows how to build low-code GUIs with Qt Designer, convert .ui files to .py using PySide6 commands, and integrate the results into pure Python code. Presents a… | ||
| Reproducible Molecular Simulations with the Help of Python | Iván Pulido | 33m |
Shows how Python plus OpenMM ecosystem tools (OpenMM, openmmtools, perses) can reduce the effort to parametrize and run molecular dynamics: example scripts… | ||
| Manage your SCM security using Python Open Policy Agent (OPA) Client | Natalie Serebryakova | 26m |
The talk will explain using an Open Policy Agent (OPA) to ensure that governance, compliance, and security controls are implemented in the development process… | ||
| Plug life into your codebase: Making established Python codebase pluggable | Bianca Henderson | 26m |
You will learn about the pluggy Python framework and how it can be used to make your codebase plugin-friendly. As a real-life example, you will also learn… | ||
| The CPU in your browser: WebAssembly demystified | Antonio Cuni | 31m |
Shows concrete artifacts and outcomes: a factorial C→WASM demo is compiled, disassembled and invoked from JavaScript in the browser and from a standalone… | ||
| Iteration Toward Transformation of the Python Documentation | C.A.M. Gerlach, Erlend Aasland | 37m |
With the tremendous growth of the Python ecosystem, attracting an ever-wider audience of users with a variety of backgrounds and experience levels, it is more… | ||
| pyproject.toml, packaging, and you | Moshe Zadka | 30m |
What is pyproject.toml? What is it good for?
The talk will cover the basic format and extensibility of pyproject.toml. It will show how it is extensible by… | ||
| 10 Ways To Shoot Yourself In The Foot With Tests | Shai Geva | 28m |
Tests are great.
Except when they’re not.
Almost every developer who’s worked with tests has encountered a test suite that caused a lot of pain.
Some of… | ||
| Python Linters at Scale | Jimmy Lai | 27m |
Black, Flake8, isort, and Mypy are useful Python linters but it’s challenging to use them effectively at scale in the case of multiple codebases, in a large… | ||
| Python's syntactic sugar | Brett Cannon | 31m |
Did you know that it only takes 11 pieces of syntax and some special functions to implement all the rest of the syntax of Python 3.8? It turns out you can take… | ||
| Subclassing, Composition, Python, and You | Hynek Schlawack | 46m |
Ever seen a code base where understanding a simple method meant jumping through tangled class hierarchies? We all have! And while "Favor composition over… | ||
| International Cooperation in the Python Community | Débora Azevedo | 29m |
Practical ways to support international Python communities are described, including moderating forums, organizing local meetups and workshops (e.g. Django… | ||
| Orcha 🐳: Massive Parallel Processing (MPP) and API design | Javier, Miguel | 31m |
Orcha is a Python-based Massively Parallel Processing orchestrator that parallelizes CI by using only Python multiprocessing plus a plugin model (docker… | ||
| Argument Clinic: What Healthy Professional Conflict Looks Like | Sumana, Jacob | 30m |
What does healthy disagreement look like? Many of us have never experienced healthy conflict at work, and so assume our only options are to either avoid… | ||
| Pyscript for Education | Blake Rayfield | 29m |
Claim: PyScript runs Python in the browser so demos run locally with no server, load from a single file and open from a USB drive, and work on tablets and… | ||
| Python Meets UX: Enhancing User Experience with Code | Neeraj Pandey, Aashka Dhebar | 29m |
The intersection of UX and Python programming is a powerful combination for building great products and enhancing user experience. Python is a versatile and… | ||
| Reconciling Everything | Andrew Godwin | 30m |
Queues. The backbone of distributed systems, our old friends that we can rely on, and the cause of a lot of grief and on-call worries as they inevitably back… | ||
| PyScript and the magic of Python in the browser | Fabio Pliger | 43m |
This presentation revisits two core concepts of Object-Oriented programming: encapsulation and code reuse. Using a series of examples, we'll ask whether these… | ||
| Software Security and Slippery Slopes: How to elevate an entire ecosystem at scale | Dustin Ingram | 27m |
Laid‑out claims and concrete results: trusted Publishers for Pi Pi ships and replaces long‑lived API tokens with a GitHub Actions flow that needs three small… | ||
| Creating USB gadgets with Python | Michał Gałka | 27m |
USB is with us for 26 years. Connecting USB devices to our computers, TVs, phones and many other devices became as natural as breathing. Throughout these years… | ||
| How we are making CPython faster. Past, present and future. | Mark Shannon | 29m |
Sums the concrete claim that CPython 3.11 is noticeably faster than 3.10 with measured benchmarks (pyperformance style) and shows the actual changes applied… | ||
| What framework should I use for web testing? | Andrew Knight | 32m |
Web apps these days are bigger than ever! With added complexity comes higher risk for bugs and poor user experience. One of the best ways to improve quality… | ||
| Oh no! My regex is causing a Denial of Service! What can I do about it? | Guillaume, Quazi | 31m |
Every modern programming language supports regular expressions. Python uses a backtracking engine to match developer-defined expressions against a wide range… | ||
| Approaches to Fairness and Bias Mitigation in Natural Language Processing | Angana Borah | 31m |
With the advent of large pre-trained language models like GPT, BERT, etc., and their usage in almost all natural language understanding and generation… | ||
| so much depends upon... your python app's dependencies | Mario Munoz | 31m |
How do you keep track of your project's building blocks? Is it enough just pinning your dependencies in a requirements.txt file? Or is there any reason to… | ||
| It might look normal but this distribution will ruin your stats | Allan Campopiano | 29m |
Claim: a deceptively bell-shaped contaminated normal appears normal yet breaks standard tests and produces many false negatives. A simulation shows two groups… | ||
| The creative art of algorithmic embroidery | Marie Roald, Yngve Mardal Moe | 23m |
Claims that Python code turns turtle drawings into machine-ready embroidery files using Python's built-in turtle plus TurtleThread to export machine files… | ||
| The Lost Art of Diagrams: Making Complex Ideas Easy to See with Python | Tadeh Hakopian | 27m |
This talk is about communicating with visuals to make complex ideas simple to understand. Over the years I have produced diagrams, charts, illustrations and… | ||
| How To Keep A Secret | Glyph | 26m |
Practical rules and concrete failures: docs that paste API keys into code lead to immediate compromise — automated scrapers grab leaked keys minutes after… | ||
| Vectorize using linear algebra and NumPy to make your Python code fast | Jodie Burchell | 29m |
Have you found that your code works beautifully on a few dozen examples, but leaves you wondering how to spend the next couple of hours after you start looping… | ||
| Too Big for DAG Factories? | Calvin Hendryx-Parker | 30m |
You’re working on a project that needs to aggregate petabytes of data, and it doesn’t make sense to manually hard-code thousands of tables, DAGs (Directed… | ||
| Using Python's import machinery to handle API deprecations | Ludovico Bianchi | 31m |
For any software project with an established user base, introducing breaking changes in its API can be daunting. To minimize disruptions for users, projects… | ||
| Robyn: An async Python web framework with a Rust runtime | Sanskar Jethi | 25m |
With the rise of Rust bindings being used in the Python ecosystem, we know that throughput efficiency is one of the top priority items in the Python… | ||
| Getting Around the GIL: Parallelizing Python for Better Performance | Alireza Farhidzadeh | 31m |
One of the ever-present banes of a data scientist’s life is the constant wait for the data processing code to finish executing. Slow code affects almost every… | ||
| Using Python to Help the Unhoused | Josh Weissbock, Sheila Flood | 21m |
How a group of volunteers from around the globe use Python to help an NGO in Victoria, BC, Canada to help the unhoused. By building a tool to find social media… | ||
| Skynet 101 How to Keep Your Machine Learning Code From Getting Away From You | E. Johnson | 26m |
Machine learning can feel pretty mysterious at times, but as python developers you have so many of the tools you need to be a part of it! With basic python… | ||
| A pythonic full-text search | Paolo Melchiorre | 26m |
A full-text search on a website is the best way to make its contents easily accessible to users because it returns better results and is in fact used in online… | ||
| Python on Android | Malcolm Smith | 26m |
By many measures, Android is the most widely-used operating system in the world. But Python development on the platform remains quite rare.
Fortunately there… | ||
| Supercharging Pipeline Efficiency with ML Performance Prediction | Boaz Wiesner, Keren Meron | 25m |
A productionized pipeline-classifier predicts task duration and memory per job (serialized per-customer SVR models stored in Redis and retrained daily)… | ||
| The wheelhouse of horrors | Laszlo Kiss Kollar | 24m |
You might be surprised to learn that, besides naming and cache invalidation problems, building a binary wheel for a Python extension is one of the hardest… | ||
| OCR, Recognition and Information Extraction from Images | Alison Orellana-Rios | 22m |
Uses OpenCV, Tesseract and Python to extract readable text from photos and PDFs, demonstrating three demos: full-image OCR, region-of-interest extraction, and… | ||
| An Overview of the Python Code Tool Landscape 2023 | Al Sweigart | 27m |
Linters, type checkers, style formatters, package linters, security analysis, dead code removers, docstring formatters, code complexity analyzers: There is a… | ||
| How Python can help monitor governments | Judite Cypreste | 25m |
Shows how Python is used in Brazil to build monitoring tools and analyze government agency data to preserve transparency amid threats to democracy and attacks… | ||
| How Pydantic V2 leverages Rust's Superpowers | Samuel Colvin | 46m |
Pydantic is a data validation library for Python that has seen massive adoption over the last few years - it is estimated that Pydantic is now used by about… | ||
| Supercharge your Python Development Environment with VS Code + Dev Container | Dawn Michelle Wages | 31m |
Supercharge your Python Development Environment with VS Code + Dev Container by Dawn Wages | ||
| MQTT: A Pythonic introduction to the protocol for connected devices | Jonas Neubert | 34m |
MQTT is to connected devices what HTTP is to web applications. It is a publish-subscribe protocol specifically designed for devices with limited bandwidth and… | ||
| PyCon 20 Years Throwback | 07m | |
A montage compiles submissions to mark 20 years of PyCon US and stitches crowd clips and short onstage moments into a continuous favorite memories recap voiced… | ||
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