PyCon US 2020
2020-04-15..2020-04-23
-- 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 |
|---|---|---|
| Debugging Stories from an Advanced Python Class | Luis Diego Conejo Alpizar | 18m |
Four concrete Python debugging stories with reproducible code and fixes: a broad except hiding a NameError fixed by catching specific exceptions; redefining… | ||
| Integrations with Asyncio | Eric Nahuel Horvat | 25m |
An asyncio-based dispatcher runs heterogeneous plugin subprocesses and communicates with them over IPC using their stdout/stderr, while server-to-dispatcher… | ||
| If It’s Not Documented, Your Project Doesn’t Exist | Renne Silva Gomes de Oliveira Rocha | 17m |
Argues that lack of documentation hides otherwise great projects and prescribes four concrete docs types: tutorials, how‑to guides, API reference, and… | ||
| Data, Python and Humans | David Mauricio Delgado Ruiz | 27m |
Five concrete challenges for doing data science in Latin America are presented along with five real Quantil case studies showing practical solutions: adopting… | ||
| Detección automatizada de archivos maliciosos en el repositorio PyPI | Cristina Muñoz | 24m |
PyPI gains an automated malware detection pipeline that produces verdicts for Projects, Versions and Files, integrates YARA rules and VirusTotal scans, uses… | ||
| East Meets West When Translating Django Apps | Andrew Knight | 29m |
A Django admin front end for a family sales app is built, deployed to Heroku, and uses Amazon s3 for images; language switching works via flag widgets that… | ||
| Implementing Ethics: Developing Trustworthy AI | Carol J. Smith | 20m |
Claims a reusable UX framework with four concrete checks: accountable to humans, cognizant of speculative risks and benefits, respectful and secure, and honest… | ||
| Ray: A System for High-performance, Distributed Python Applications | Dean Wampler | 26m |
Ray claims to scale Python from a laptop to a cluster by making functions into remote tasks and actors scheduled across nodes with a global control store and… | ||
| Small Big Data: using NumPy and Pandas when your data doesn't fit ... | Itamar Turner Trauring | 26m |
Explains concrete tactics to handle data too big for RAM using NumPy and Pandas: lossless dtype downcasting (64→16-bit cuts memory ~4x), sparse arrays for… | ||
| Yin Yang Ranch: Building a Distributed Computer Vision Pipeline using Python, O... | Jeff Bass | 31m |
A working hub-and-spoke pipeline runs Python on 20 Raspberry Pi computers with PiCameras that do local motion detection and send only key frames to a hub over… | ||
| How I Solved my NYC Parking Problem with Python | Jessica Garson | 20m |
A working Python pipeline watches the @NYCASP feed and checks for "suspended" and "tomorrow" in recent-search results, then sends an SMS via Twilio when… | ||
| Snakes in a case: Packaging Python apps for distribution | Russell Keith-Magee | 28m |
Briefcase converts a pyproject.toml Python project into platform-native installers, producing MSI DMG AppImage and iOS/Android projects by templating… | ||
| Leadership and Identity in the Pan-African Python movement | Marlene Mhangami | 30m |
Chair of Python Africa and a director at the Python Software Foundation recounts running PyCon Africa 2019 in Accra Ghana, noting repeated surprise when… | ||
| What is deployment, anyway? | Katie McLaughlin | 22m |
A clear checklist: deployment means copying code, running a production web server, migrating a real database and serving static assets — not using the… | ||
| Developing With Doctests - Using Xdoctest As A Backend | Jon Crall | 28m |
Doctests get a practical overhaul: Xdoctest replaces regex parsing with an AST-based parser, accepts a single >>> rule for all statements, adds pytest… | ||
| Comprehensible Comprehensions | Trey Hunner | 33m |
Explains when comprehensions are the right tool and when plain loops or builtins like dict() or list() are clearer, shows concrete translations by copy/paste… | ||
| Automate the Boring Stuff with Slackbot | Takanori Suzuki | 29m |
A Slackbot is built to automate PyCon JP chores and it actually performs: calculator with SymPy, emoji reactions and Block Kit messages, a Peewee-backed karma… | ||
| Beautiful Python Refactoring | Conor Hoekstra | 30m |
A concrete refactor pipeline takes scraped HTML rows using requests and lxml into a list comprehension and finally into a pandas DataFrame reducing code from… | ||
| Static Typing in Python | Dustin Ingram | 22m |
Claim: Python is dynamically typed but can be made as statically typed as desired. History and specifics: PEP 3107 adds annotations in 2006, PEP 484 and the… | ||
| The Hitchhiker's Guide to CLIs in Python | Vinayak Mehta | 25m |
Shows how terminal ancestry and live modes cause quirks (canonical vs raw input, echo off, carriage return behavior) and uses stty -a shows modes examples to… | ||
| Saved by In-Memory NoSQL | Deepak K Gupta | 15m |
Claim: use in-memory NoSQL as a real-time TCP logging endpoint to capture encoded debug logs (short numeric codes from a mapping table) so every state, event… | ||
| Transitioning from developing software to developing people | Matthew Knapp Bachmann | 32m |
Transition details: managed six engineers in a newly formed team for six months; developed the team’s process with a scrum-like workflow—ticket breakdown… | ||
| Building Docs like Code: Continuous Integration for Documentation | Mason Egger | 35m |
Move documentation into the repository and wire it to CI so commits build and publish artifacts automatically. Uses MKDocs and Sphinx (doc tests validate… | ||
| AsyncIO + Music | Łukasz Langa | 01h 33m |
Python uses AsyncIO plus uvloop and RTMidi to read MIDI, forward a hardware clock, and schedule generators; the demo builds a sequencer that forwards the… | ||
| 9 Years of PyLadies: Lessons Learned and What Comes Next | Lorena Mesa, Elaine Wong, Mariatta | 34m |
Nine years of growth claims move from seven founders to 100+ chapters worldwide but also surface concrete problems: volunteer burnout, stagnant resources, and… | ||
| Pyambic Pentameter: generating rhyming and metered poems | Kathryn Lingel | 24m |
Claims an automated pipeline that generates rhyming, metered lines by combining a Markov chain generator with the pronunciation lookup in NLTK CMUdict, slicing… | ||
| The Hidden Power of the Python Runtime | Elizaveta Shashkova | 27m |
Explains how to read the actual runtime facts: use sys._getframe and code objects to get names and file/line, read values from frame.f_locals and traceback… | ||
| Organizing To Improve Your Workplace: Know Your Rights | Shauna Gordon-McKeon | 53m |
Overview of legal rights and concrete organizing steps with examples and outcomes: details on NDAs and forced arbitration, contractor misclassification with… | ||
| Introduction to Writing Network Tests with pyATS | Hank Preston | 34m |
pyATS is a Python test framework that lets teams describe a network with a testbed YAML, write Python test scripts with explicit setup/test/cleanup phases, and… | ||
| C++ ♥ Python: from modules to hybrid applications | Cristián Maureira-Fredes | 29m |
Shows how to write real CPython extensions in modern C++ with concrete code, benchmarks, and a working hybrid app: uses the CPython C API and std::transform to… | ||
| 1 + 1 = 1 or Record Deduplication with Python | Flávio Juvenal da Silva Junior | 29m |
Record deduplication uses concrete signals: Python code that applies fingerprinting and blocking (unidecode for accents, token ordering, geocoding via Google… | ||
| Let's talk Databases in Python: SQLAlchemy and Alembic | Hannah Stepanek | 34m |
Shows concrete use of SQLAlchemy and Alembic to model tables, run multi-step migrations, and deploy schema and data changes (adds an organization table, adds… | ||
| Mixing a Raspberry Pi with Python into a 5th Grade Science Fair Project | Wendi Dreesen | 33m |
A Raspberry Pi measures marble travel time using two photogates built from a photo transistor and a light source and Python code that polls the GPIO and… | ||
| Privacy-preserving methods: Building secure projects | Rebeca Sarai | 29m |
Conference notes state privacy laws grow from 20 to 100, and the session shows concrete techniques: randomized response gives plausible deniability for… | ||
| Using Python to Detect Vulnerabilities in Binaries | Terri Oda | 24m |
A small open source scanner called CVE Binary Tool detects known vulnerabilities inside binary files by matching simple strings + grep signatures to extract… | ||
| Function dissection lab -- learn how functions | Reuven M. Lerner | 28m |
Asserts that Python treats functions as objects and demonstrates the mechanics: inspect __code__ and its fields (co_argcount, co_varnames, co_flags… | ||
| The joy of creating art with code | Neeraj Pandey | 32m |
Examples use actual code and specific libraries: Processing, PyCario and Python scripts that draw vectors, use Perlin noise, implement pixel‑sorting and… | ||
| How to build an intelligent “indoor garden” | Maria Jose Molina Contreras | 28m |
A reproducible prototype waters plants when soil moisture crosses calibrated thresholds and plays a voice alert when the reservoir runs low, built with… | ||
| Big O No: Django ORM runtime complexity and how to avoid it using LATERAL JOINS | Chris Seto | 16m |
Claims that Django can avoid N+1 and even O(n^2) query explosions by using LATERAL JOINs and correlated subqueries to run per-row aggregations and embed… | ||
| Practical privacy-preserving machine learning in Python | Catherine Nelson | 19m |
Shows working Python code using TensorFlow Privacy with gradient clipping and noise multiplier so stochastic gradient descent adds Gaussian noise and a… | ||
| Python in High Energy Physics | Pratyush Das | 31m |
High Energy Physics uses concrete tooling and measurable shifts: the Worldwide LHC Computing Grid handles petabytes and experiments like CMS and ATLAS have… | ||
| If Statements are a Code Smell | Aly Sivji | 31m |
Claim: if statements are a code smell when duplicated or deeply nested. The talk refactors an open source Busy Beaver Slack bot that calls the GitHub API with… | ||
| How multilingual is your NLP model? | Shreya Khurana | 45m |
Off-the-shelf language detectors like cld3 and langid frequently misclassify short, transliterated or code-switched text (examples show cld3 returning Maori or… | ||
| The Limitations and Danger of Facial Recognition | Manojit Nandi | 27m |
Commercial systems show 20–35% higher error rate on darker‑skinned women, prompting vendors to publish fixes like IBM’s Diversity in Faces dataset (built… | ||
| Building interactive applications for image data | Emmanuelle Gouillart | 29m |
Live demos show Dash apps with drawing tools that emit JSON geometry, annotations saved to a store and wired to callbacks; the UI integrates with plotly graphs… | ||
| Write Less and Test More with Data Regression Testing | Igor T. Ghisi | 32m |
Shows a concrete workflow: use pytest-regressions and its fixtures — data_regression, file_regression, image_regression, num_regression — to serialize expected… | ||
| A 🐍's guide to Unicode | James Bennett | 44m |
Explains what Unicode actually is (databases, properties, not just an encoding), shows 17 planes of code points and 65,536 per plane, demonstrates code point… | ||
| Goodbye Print, Hello Debugger! | Nina Zakharenko | 28m |
Claim: giving up print statements measurably increases debugging productivity. Demonstration uses a simple Flask app calling the GitHub Search API that returns… | ||
| From 0 to 60 in 2,592,000 seconds | Alexandra Sunderland | 21m |
Claims a repeatable onboarding process scales from one to fifty hires and compresses ramp to about 2,592,000 seconds (30 days). Implements six concrete… | ||
| Multiply your Testing Effectiveness with Parameterized Testing | Brian K Okken | 21m |
Covers how pytest parametrization turns four triangle test cases into dozens with one function and demonstrates three concrete techniques: function… | ||
| Docker and Python: making them play nicely and securely for Data Science and ML | Tania Allard | 40m |
Practical checklist: use an official Python slim-buster base image rather than Alpine for scientific stacks; prefer Jupyter Docker Stacks or repo2docker… | ||
| Decoding bias and narrative in competitive video games | Kim-Adeline Miguel | 35m |
Built a Python pipeline that splices broadcast video with ffmpeg, crops with Pillow, sends frames to Azure Computer Vision OCR, stores results in TinyDB and… | ||
| Why is Python slow? | Anthony Shaw | 33m |
CPython often shows concrete slowdowns on tight numeric loops: the n-body 7s vs 14min benchmark exposes the bytecode evaluation loop overhead. JITs win here —… | ||
| Finite State Machine (FSM) in Django | Calvin Hendryx-Parker | 32m |
Shows how to model real workflows in Django and actually ship them using django-fsm, with concrete examples (university program-change form and case-report… | ||
| A careful walk through probability distributions, using Python | Eric J. Ma | 19m |
Python code and SciPy.stats power an interactive Streamlit app at python-prob.ericmjl.com that constructs a Gaussian class with mu=1.7 and sigma=2.4… | ||
| “Sorry, Could you repeat that again?” - Speech Recognition with Python | Javier Jorge Cano | 31m |
A working Python pipeline converts audio to MFCC features, trains a hidden Markov model + neural hybrid acoustic model and an n‑gram or neural language model… | ||
| Polyglot data with python: Introducing Pandas and Apache Arrow | Robson Luis Monteiro Junior | 24m |
Claims that Apache Arrow + pandas let Python exchange data with other ecosystems without expensive serialization, demonstrates reading a Spark-created Parquet… | ||
| Bridging Data Science and Data Infrastructure with Apache Airflow | Daniel Imberman | 16m |
Shows how Apache Airflow moves a prototype from a single-machine Jupyter Notebook to a distributed pipeline running Spark + TensorFlow, using custom Airflow… | ||
| Deploying Python at Scale with Dask | Matthew Rocklin | 25m |
Dask claims to make NumPy/Pandas/Scikit-Learn scale to 100+TB datasets and runs on Kubernetes, Yarn and cloud VMs; deployments actually use containers, TLS… | ||
| Getting started with automatic differentiation | Colin Carroll | 19m |
Explains how automatic differentiation computes exact derivatives and scales to millions of parameters, demonstrates gradient computation and repeated grad… | ||
| Serverless Python Applications with Google Cloud | Charles Engelke | 02h 05m |
Builds a working distributed serverless contest: a deployed Python player that answers HTTP JSON moves, pub/sub‑triggered questioner functions that run games… | ||
| Easy Data Processing With Azure Fun | Tania Allard | 57m |
Uses Python on Azure Functions to build a concrete, working pipeline: a cron timer-trigger + blob-trigger pipeline calls the Stack Exchange API (demo shows it… | ||
| Optimize Python & Django apps with Postgres superpowers | Louise Grandjonc | 43m |
Shows exact fixes and measurements: use pg_stat_statements and Postgres logs to find offenders, cut 101 queries down to 6 with prefetch_related and limiting… | ||
| Machine Learning on Encrypted Data with CrypTen | Mark Ibrahim | 26m |
A framework called CrypTen runs on PyTorch and uses secure multiparty computation to train real models on encrypted inputs and labels, with encrypted tensors… | ||
| Type Hints: Putting more Buzz in your Fizz | Steven Lott | 37m |
Shows concrete results: runs mypy and tox, annotates an over‑engineered fizzbuzz implementation, and fixes a real mismatch where returns mix strings and ints… | ||
| From Project to Productionized on Heroku | Casey Faist | 36m |
Step-by-step workshop that actually takes a Django project to a live Heroku app: modularizes settings into base and Heroku files, adds django-environ… | ||
| Extending the Python Ecosystem to Xilinx | Patrick Lysaght | 37m |
PYNQ extends Python to Xilinx SoCs by shipping a browser IDE and JupyterLab running on PYNQ that loads FPGA overlays as Python-accessible modules. The workflow… | ||
| GPU-Accelerated Data Analytics in Python | Keith Kraus, Bartley Richardson | 01h 12m |
The RAPIDS stack demonstrates concrete speedups: GPU dataframes via cuDF read a 1.9 GB NYC taxi CSV in ~2s versus ~29s with pandas; a 200 GB end‑to‑end… | ||
| How Python Powers Salesforce.org's Unique Open Source... | Jason Lantz | 01h 55m |
Claims concrete: Salesforce.org runs open source products for 44,000 nonprofit and education orgs and uses a Python-based DevOps stack to package, test and… | ||
| We need to talk about Windows | Shaun Lowry | 17m |
Builds Python from source across Linux Mac and Windows and shows why Windows forces a different approach: Visual Studio project files + msbuild, hard-coded… | ||
| Demystifying Deep Learning for Data Scientists | Eric J. Ma | 01h 10m |
Shows how to implement linear, logistic and feed‑forward networks from first principles using NumPy-style code and Jax automatic differentiation, with working… | ||
| Hands-on Python for Programmers | Matt Harrison | 02h 14m |
Downloads a raw CSV from a GitHub endpoint, parses lines into dictionaries, converts numeric fields, and filters by state; creates a time-series plot with… | ||
| Hands-On Web App Test Automation | Andrew Knight | 01h 45m |
A hands‑on walkthrough builds a real test project from scratch that runs a DuckDuckGo search with pytest and selenium, adds fixtures and page object classes… | ||
| It's Officially Legal so Let's Scrape the Web | Kimberly Fessel | 02h 46m |
Claims recent case law lets scraping publicly available pages (Haikyu Labs v LinkedIn fall 2019) and shows legal risk is reduced; demonstrates concrete tooling… | ||
| Modern Python Developer's Toolkit | Sebastian Witowski | 02h 25m |
Claims to teach the concrete workflow: set up VS Code, manage Python versions with pyenv and isolate tools with pipx/pipenv, enforce style with black and… | ||
| Deploying Django on Serverless Infrastructure | Katie McLaughlin | 39m |
Shows a hands‑on path to take a sample Django app from source and local Docker Compose to a working serverless deployment on Google Cloud: creates Cloud SQL… | ||
| Effective Data Visualization | Husni Almoubayyed | 01h 38m |
Shows concrete recipes and working code: uses seaborn, matplotlib, plotly, sklearn on real datasets like Anscombe, Iris, Diamonds, Flights, Digits, COVID… | ||
| Natural Language Processing (NLP) in Python - From Zero to Hero | Keith Galli | 01h 39m |
Covers concrete recipes: build a classifier with CountVectorizer + linear SVM and see how binary versus counts and n‑grams change results, replace that with… | ||
| Say it with Bots! | Mariatta | 02h 26m |
Builds a real GitHub App bot in Python 3.7 that greets installers and thanks first‑time PR authors, using gidgethub, aiohttp, asyncio and deploying to Heroku… | ||
| Geospatial Public Policy Analysis with GeoPandas | Sergio Sanchez | 03h 59m |
Uses GeoPandas and pandas with geoplot, TIGER shapefiles, NCES IPEDS and ACS via the census-data-downloader to build reproducible JupyterLab/Binder notebooks… | ||
| Python Concurrency: from beginner to pro | Santiago Basulto | 02h 57m |
Covers concrete claims, tools and timings: explains OS/process/thread internals, uses _thread, threading, subprocess, multiprocessing and concurrent.futures… | ||
| Migration from Python 2 to 3 | Mike Müller | 02h 38m |
Shows exact migration steps: create two conda envs with Python 2.7 and 3.8, run JupyterLab, run futurize/pasteurize to apply staged fixes, and commit tests… | ||
| Introduction to Decorators: Power Up Your Python Code | Geir Arne Hjelle | 03h 21m |
Step-by-step tutorial that actually shows working code, exercises, and a repo: implements timer trace register count_calls and a use_unit decorator with live… | ||
| Education Summit 2020 | Elizabeth Wickes, Meenal Pant, Chalmer Lowe, Zoë Wilkinson Saldaña, Jeffrey L. Olson Jr | 02h 52m |
Committee reports list 104 signups 53 submissions 8 mini‑sprints 18 lightning talks 27 talk proposals and two PSF education grants funding Python on Android… | ||
| Python Trainers Summit - Hatchery 2020 | Elizabeth Wickes, Reuven M. Lerner, Trey Hunner, Moshe Zadka, Karen Word | 02h 17m |
A practical summary of what actually happens and what to expect: live coding often uses a terminal mirroring setup (tmux) so students see only one window while… | ||
| Stop Using Mocks (for a while) | Harry Percival | 45m |
The claim is blunt: stop using mocks for a while and instead build an adapter, inject it, and use a small in‑memory fake or integration tests. Concrete tools… | ||
| Nonsense verse with Python and machine learning | Allison Parrish | 03h 22m |
Claims a Python library called Pincelate converts between spelling and sound, using the CMU Pronouncing Dictionary for training and a seq2seq neural model to… | ||
| Interview | Aiko AI | 22m |
Aiko AI describes an email client that converts the inbox into a task workflow and claims concrete results: summarization models that condense long emails… | ||
| nothing matches | ||