Talk Python To Me

Talk Python To Me

By Michael Kennedy

Talk Python to Me is a weekly podcast hosted by developer and entrepreneur Michael Kennedy. We dive deep into the popular packages and software developers, data scientists, and incredible hobbyists doing amazing things with Python. If you're new to Python, you'll quickly learn the ins and outs of the community by hearing from the leaders. And if you've been Pythoning for years, you'll learn about your favorite packages and the hot new ones coming out of open source.

Episodes

#485: Secure coding for Python with SheHacksPurple

What do developers need to know about AppSec and building secure software? We have Tanya Janca (AKA SheHacksPurple) on the show to tell us all about it. We talk about what developers should expect from threat modeling events as well as concrete tips for security your apps and services. Episode sponsors Posit Bluehost Talk Python Courses Links from the show Tanya on X: @shehackspurple She Hacks Purple website: shehackspurple.ca White House recommends memory safe languages: whitehouse.gov Python Developer Survey Results: jetbrains.com Bandit: github.com Semgrep Academy: academy.semgrep.dev Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy
15/11/241h 9m

#484: From React to a Django+HTMX based stack

Have you heard about HTMX? We've discussed it a time or two on this show. We're back with another episode on HTMX, this time with a real-world success story and lessons learned. We have Sheena O'Connell on to tell us how she moved from a React-Django app to pure Django with HTMX. Episode sponsors Posit Bluehost Talk Python Courses Links from the show Sheena O'Connell: sheenaoc.com An HTMX success story essay: sheenaoc.com Sheena's HTMX Workshop: prelude.tech - discount code: talk_python Talk Python's HTMX Courses HTMX + Flask course: training.talkpython.fm HTMX + Django course: training.talkpython.fm Build An Audio AI App course: training.talkpython.fm HTMX: htmx.org Playwright: playwright.dev django-template-partials: github.com Michael's jinja_partials: github.com django-guardian: github.com Talk Python Courses HTMX Example: training.talkpython.fm/courses/all Alpine.js: alpinejs.dev David Guillot SaaS video: youtube.com awesome-htmx: github.com Guild of Educators: guildofeducators.org The big rewrite song: youtube.com Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy
05/11/2457m 44s

#483: Reflex Framework: Frontend, Backend, Pure Python

Let's say you want to create a web app and you know Python really well. Your first thought might be Flask or Django or even FastAPI? All good choices but there is a lot to get a full web app into production. The framework we'll talk about today, Reflex, allows you to just write Python code and it turns it into a full web app running FastAPI, NextJS, React and more plus it handles the deployment for you. It's a cool idea. Let's talk to Elvis Kahoro and Nikhil Rao from Reflex.dev. Episode sponsors Posit Bluehost Talk Python Courses Links from the show Elvis: github.com Nikhil: github.com Reflex Framework: reflex.dev Reflex source: github.com Reflex docs: reflex.dev Reflex Roadmap: github.com AG Grid: ag-grid.com Warp terminal: warp.dev A Stroll Down Startup Lane episode: talkpython.fm PuePy: Reactive frontend framework in Python episode: talkpython.fm Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy
29/10/241h 3m

#482: Pre-commit Hooks for Python Devs

Do you struggle to make sure your code is always correct before you check it in? What about your team members' code? That one person who never wants to run the linter? Tired of dealing with tons of conflicts and spurious git changes? You need git pre-commit hooks. We're lucky to have Stefanie Molin on this episode who has done a bunch of writing and teaching of git hooks. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Bluehost Talk Python Courses Links from the show Stefanie Molin: stefaniemolin.com Talk Python Blog: talkpython.fm/blog How to Set Up Pre-Commit Hooks: stefaniemolin.com Common Pre-Commit Errors and How to Solve Them: stefaniemolin.com A Behind-the-Scenes Look at How Pre-Commit Works: stefaniemolin.com Pre-Commit Hook Creation Guide: stefaniemolin.com (Pre-)Commit to Better Code Workshop: stefaniemolin.com exif-stripper: stefaniemolin.com exif-stripper on GitHub: github.com docstring-validation-using-pre-commit-hook: numpydoc.readthedocs.io Data Morph: Moving Beyond the Datasaurus Dozen: stefaniemolin.com Data Morph on GitHub: github.com Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy
24/10/241h 10m

#481: Python Opinions and Zeitgeist with Hynek

Hynek has been writing and speaking on some of the most significant topics in the Python space and I've enjoyed his takes. So I invited him on the show to share them with all of us. This episode really epitomizes one of the reasons I launched Talk Python 9 years ago. It's as if we run into each other at a bar during a conference and I ask Hynek, "So what are your thoughts on ..." and we dive down the rabbit hole for an hour. I hope you enjoy it. Episode sponsors WorkOS Bluehost Talk Python Courses Links from the show Hynek Schlawack on Mastodon: @hynek Why I Still Use Python Virtual Environments in Docker: hynek.me Production-ready Python Docker Containers with uv: hynek.me Attrs: github.com uv: astral.sh What’s New In Python 4: python.org BusyBox: busybox.net Hynek's YouTube Channel: youtube.com MOPUp for macOS: github.com Homebrew Python Is Not For You: justinmayer.com argon2-cffi: Argon2 for Python: github.com pytest-freethreaded: github.com LM Studio: lmstudio.ai StackOverflow Trends Graph: trends.stackoverflow.co Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy
17/10/241h 3m

#480: Ahoy, Narwhals are bridging the data science APIs

If you work in data science, you definitely know about data frame libraries. Pandas is certainly the most popular, but there are others such as cuDF, Modin, Polars, Dask, and more. They are all similar but definitely not the same APIs and Polars is quite different. But here's the problem. If you want to write a library that is for users of more than one of these data frame frameworks, how do you do that? Or if you want to leave open the possibility of changing yours after the app is built, same problem. That's the problem that Narwhals solves. We have Marco Gorelli on the show to tell us all about it. Episode sponsors WorkOS Talk Python Courses Links from the show Marco Gorelli: @marcogorelli Marco on LinkedIn: linkedin.com Narwhals: github.io Narwhals on Github: github.com DuckDB: duckdb.org Ibis: ibis-project.org modin: readthedocs.io Pandas and Beyond with Wes McKinney: talkpython.fm Polars: A Lightning-fast DataFrame for Python: talkpython.fm Polars: pola.rs Pandas: pandas.pydata.org Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy
09/10/2459m 15s

#479: Designing Effective Load Tests for Your Python App

You're about to launch your new app or API, or even just a big refactor of your current project. Will it stand up and deliver when you put it into production or when that big promotion goes live? Or will it wither and collapse? How would you know? Well you would test that of course. We have Anthony Shaw back on the podcast to dive into a wide range of tools and techniques for performance and loading testing of web apps. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON WorkOS Talk Python Courses Links from the show Anthony on Twitter: @anthonypjshaw Anthony's PyCon Au Talk: youtube.com locust load testing tool: locust.io playwright: playwright.dev mimesis: github.com mimesis providers: mimesis.name vscode pets: marketplace.visualstudio.com vscode power-mode: marketplace.visualstudio.com opentelemetry: opentelemetry.io uptime-kuma: github.com Talk Python uptime / status: talkpython.fm/status when your serverless computing bill goes parabolic...: youtube.com Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy
06/10/2459m 6s

#478: When and how to start coding with kids

Do you have kids? Maybe nieces and nephews? Or maybe you work in a school environment? Maybe it's just friend's who know you're a programmer and ask about how they should go about introducing programming concepts with them. Anna-Lena Popkes is back on the show to share her research on when and how to teach kids programming. We spend the second half of the episode talking about concrete apps and toys you might consider for each age group. Plus, some of these things are fun for adults too. ;) Episode sponsors WorkOS Talk Python Courses Links from the show Anna-Lena: alpopkes.com Magical universe repo: github.com Machine learning basics repo: github.com PyData recording "when and how to start coding with kids": youtube.com Robots and devices Bee Bot: terrapinlogo.com Cubelets: modrobotics.com BBC Microbit: microbit.org RaspberryPi: raspberrypi.com Adafruit Qualia ESP32 for CircuitPython: adafruit.com Zumi: robolink.com Board games Think Fun Robot Turtles Board Game: amazon.com Visual programming: Scratch Jr.: scratchjr.org Scratch: scratch.org Blocky: google.com Microbit's Make Code: microbit.org Code Club: codeclubworld.org Textual programming Code Combat: codecombat.com Hedy: hedycode.com Anvil: anvil.works Coding classes / summer camps (US) Portland Community College Summer Teen Program: pcc.edu Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy
25/09/2454m 25s

#477: Awesome Text Tricks with NLP and spaCy

Do you have text that you want to process automatically? Maybe you want to pull out key products or topics of conversation? Maybe you want to get the sentiment? The possibilities are many with this week's topic: NLP with spaCy and Python. Our guest, Vincent D. Warmerdam, has worked on spaCy and other tools at Explosion AI and he's here to give us his tips and tricks for working with text from Python. Episode sponsors Posit Talk Python Courses Links from the show Course: Getting Started with NLP and spaCy: talkpython.fm Vincent on X: @fishnets88 Vincent on Mastodon: @koaning Programmable Keyboards on CalmCode: youtube.com Sample Space Podcast: youtube.com spaCy: spacy.io Course: Build An Audio AI App: talkpython.fm Lemma example: github.com Code for spaCy course: github.com Python Bytes transcripts: github.com scikit-lego: github.com Projects that import "this": calmcode.io Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy
20/09/241h 3m

#476: Unified Python packaging with uv

A couple of weeks ago, Charlie Marsh and the folks at Astral made another big splash with a major release of uv called "uv: Unified Python packaging" which has many far reaching features. We had to have Charlie on the show to give us the inside look into this development. Let's get to it. Episode sponsors Posit Talk Python Courses Links from the show Charlie Marsh on Twitter: @charliermarsh Charlie Marsh on Mastodon: @charliermarsh Episode follow up: Wrote up how we use uv at Talk Python: mkennedy.codes uv: Unified Python packaging: astral.sh Python executable management: astral.sh Projects: astral.sh Tools: astral.sh Scripts: astral.sh Rye and uv: August is Harvest Season for Python Packaging: lucumr.pocoo.org Python Build Standalone releases: github.com Rules: astral.sh Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy
04/09/241h 12m

#475: Python Language Summit 2024

Every year the core developers meet to discuss and propose the major changes and trends in Python itself. This invite-only conference of about 50 people happens inside PyCon in the US. Because it's private, we rarely get detailed looks inside this event. On this episode, we have Seth Michael Larson here to give us his account of the sessions and proposals. It's a unique look into the zeitgeist of CPython. Episode sponsors Posit Talk Python Courses Links from the show Seth on Mastodon: @sethmlarson@fosstodon.org Seth on Twitter: @sethmlarson Seth on Github: github.com The Python Language Summit 2024: blogspot.com PEP 2026: Calendar versioning for Python: github.com PSF authorized as a CVE Numbering Authority: python.org Recommends Memory-Safe Programming Languages: blogspot.com Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy
24/08/241h 1m

#474: Python Performance for Data Science

Python performance has come a long way in recent times. And it's often the data scientists, with their computational algorithms and large quantities of data, who care the most about this form of performance. It's great to have Stan Seibert back on the show to talk about Python's performance for data scientists. We cover a wide range of tools and techniques that will be valuable for many Python developers and data scientists. Episode sponsors Posit Talk Python Courses Links from the show Stan on Twitter: @seibert Anaconda: anaconda.com High Performance Python with Numba training: learning.anaconda.cloud PEP 0703: peps.python.org Python 3.13 gets a JIT: tonybaloney.github.io Numba: numba.pydata.org LanceDB: lancedb.com Profiling tips: docs.python.org Memray: github.com Fil: a Python memory profiler for data scientists and scientists: pythonspeed.com Rust: rust-lang.org Granian Server: github.com PIXIE at SciPy 2024: github.com Free threading Progress: py-free-threading.github.io Free Threading Compatibility: py-free-threading.github.io caniuse.com: caniuse.com SPy, presented at PyCon 2024: us.pycon.org Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy
19/08/241h 8m

#473: Being a developer with ADHD

Do you feel like ADHD is holding you back? Maybe you don't personally have ADHD but you work with folks who do and you'd like to support them better. Either way, how ADHD interplays with programming and programmers is pretty fascinating. On this episode we have Chris Ferdinandi who himself has ADHD and has written a lot about it to share his journey and his advice for thriving with ADHD as a programmer or data scientist. Episode sponsors Posit Talk Python Courses Links from the show Chris on Mastodon: @cferdinandi ADHD FTW Talk Python Page: adhdftw.com Building a Second Brain: buildingasecondbrain.com Building a Second Brain Book: buildingasecondbrain.com White Collar Jobs are Just Meetings: theatlantic.com Article with Fighting Duck-Sized Horses Agile: mensurdurakovic.com Nothing Phone: nothing.tech Apple Watch: apple.com Todoist: todoist.com Anytype (open source Notion): anytype.io Obsidian: obsidian.md Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy
02/08/241h

#472: State of Flask and Pallets in 2024

Flask is one of the most important Python web frameworks and powers a bunch of the internet. David Lord, Flask's lead maintainer is here to give us an update on the state of Flask and Pallets in 2024. If you care about where Flask is and where it's going, you'll definitely want to listen in. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Talk Python Courses Links from the show David on Mastodon: @davidism David on X: @davidism State of Pallets 2024 FlaskCon Talk: youtube.com FlaskCon: flaskcon.com FlaskCon 2024 Talks: youtube.com Pallets Discord: discord.com Pallets Eco: github.com JazzBand: jazzband.co Pallets Github Org: github.com Jinja: github.com Click: github.com Werkzeug: github.com MarkupSafe: github.com ItsDangerous: github.com Quart: github.com pypistats: pypistats.org Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy
26/07/241h 1m

#471: Learning and teaching Pandas

If you want to get better at something, often times the path is pretty clear. If you get better at swimming, you go to the pool and practice your strokes and put in time doing the laps. If you want to get better at mountain biking, hit the trails and work on drills focusing on different aspects of riding. You can do the same for programming. Reuven Lerner is back on the podcast to talk about his book Pandas Workout. We dive into strategies for learning Pandas and Python as well as some of his workout exercises. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Scalable Path Talk Python Courses Links from the show Reuven Lerner on Twitter: @reuvenmlerner Pandas Workout Book: manning.com Bamboo Weekly: Solar eclipse: bambooweekly.com Bamboo Weekly: Avocado hand: bambooweekly.com Scaling data science across Python and R: talkpython.fm Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy
22/07/241h 4m

#470: Python in Medicine and Patient Care

Python is special. It's used by the big tech companies but also by those you would rarely classify as developers. On this episode, we get a look inside how Python is being used at a Children's Hospital to speed and improve patient care. We have Dr. Somak Roy here to share how he's using Python in his day to day job to help kids get well a little bit faster. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Posit Talk Python Courses Links from the show Somak Roy: linkedin.com Cincinnati Children's Hospital: cincinnatichildrens.org CNVkit: Genome-wide copy number: readthedocs.io cnaplotr: github.com hgvs: readthedocs.io openpyxl: readthedocs.io Hera is an Argo Python SDK: github.com insiM: in silico Mutator software for bioinformatics: github.com Bamsurgeon: github.com pysam - An interface for reading and writing SAM files: readthedocs.io Scientists rename human genes to stop Microsoft Excel from misreading them as dates: theverge.com BioPython: biopython.org Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy
12/07/241h 19m

#469: PuePy: Reactive frontend framework in Python

Python is one of the most popular languages of the current era. It dominates data science, it an incredible choice for web development, and its many people's first language. But it's not super great on front-end programing, is it? Frameworks like React, Vue and other JavaScript frameworks rule the browser and few other languages even get a chance to play there. But with pyscript, which I've covered several times on this show, we have the possibility of Python on the front end. Yet it's not really a front end framework, just a runtime in the browser. That's why I'm excited to have Ken Kinder on the podcast to talk about his project PuePy, a reactive frontend framework in Python. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Code Comments Talk Python Courses Links from the show Michael's Code in a Castle Course: talkpython.fm/castle Ken Kinder: @bouncing@twit.social PuePy: puepy.dev PuePy Docs: docs.puepy.dev PuePy on Github: github.com pyscript: pyscript.net VueJS: vuejs.org Hello World example: docs.puepy.dev Tutorial: docs.puepy.dev Tutorial running at pyscript.com: pyscript.com Micropython: micropython.org Pyodide: pyodide.org PgQueuer: github.com Writerside: jetbrains.com Michael's PWA pyscript app: github.com Michael's demo of a PWA pyscript app: youtube.com Python iOS Web App with pyscript and offline PWAs video: youtube.com Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy
08/07/2458m 46s

#468: Python Trends Episode 2024

I've gathered a group of Python experts who have been thinking deeply about where Python is going and who have lived through where it has been. This episode is all about near-term Python trends and things we each believe will be important to focus on as Python continues to grow. Our panelists are Jodie Burchell, Carol Willing, and Paul Everett. Episode sponsors Code Comments Posit Talk Python Courses Links from the show Shiny course at Talk Python: talkpython.fm/shiny Jodie Burchell: @t_redactyl Carol on Mastodon: @willingc@hachyderm.io Paul Everitt: @paulweveritt Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy
01/07/241h 5m

#467: Data Science Panel at PyCon 2024

I have a special episode for you this time around. We're coming to you live from PyCon 2024. I had the chance to sit down with some amazing people from the data science side of things: Jodie Burchell, Maria Jose Molina-Contreras, and Jessica Greene. We cover a whole set of recent topics from a data science perspective. Though we did have to cut the conversation a bit short as they were coming from and go to talks they were all giving but it was still a pretty deep conversation. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Code Comments Talk Python Courses Links from the show Jodie Burchell: @t_redactyl Jessica Greene: linkedin.com Maria Jose Molina-Contreras: linkedin.com Talk Python's free Shiny course: talkpython.fm/shiny Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy
20/06/2434m 40s

#466: Pydantic Performance Tips

You're using Pydantic and it seems pretty straightforward, right? But could you adopt some simple changes to your code that would make it a lot faster and more efficient? Chances are, you'll find a couple of the tips from Sydney Runkle that will do just that. Join us to talk about Pydantic performance tips here on Talk Python. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Code Comments Talk Python Courses Links from the show Sydney Runkle: linkedin.com Pydantic: pydantic.dev Performance docs: docs.pydantic.dev Union tips: docs.pydantic.dev Sydney's presentation slides: docs.google.com JSON to Pydantic: jsontopydantic.com Samuel talking FastUI: talkpython.fm CodeFlash: codeflash.ai Codspeed: codspeed.io Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy
14/06/241h

#465: The AI Revolution Won't Be Monopolized

There hasn't been a boom like the AI boom since the .com days. And it may look like a space destined to be controlled by a couple of tech giants. But Ines Montani thinks open source will play an important role in the future of AI. I hope you join us for this excellent conversation about the future of AI and open source. Episode sponsors Sentry Error Monitoring, Code TALKPYTHON Porkbun Talk Python Courses Links from the show Ines Montani on Twitter: @_inesmontani spaCy: spacy.io Prodigy App: prodi.gy Ines' presentation at PyCon Lithuania: youtube.com LM Studio: lmstudio.ai Little Bobby Tables: xkcd.com spaCy and NLP course: talkpython.fm Use my link to get your .app, .dev, or .foo domain for just $1 right now at Porkbun: talkpython.fm/porkbun Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube: youtube.com Follow Talk Python on Mastodon: talkpython Follow Michael on Mastodon: mkennedy
08/06/241h 8m

#464: Seeing code flows and generating tests with Kolo

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29/05/2454m 59s

#463: Running on Rust: Granian Web Server

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25/05/241h 4m

#462: Pandas and Beyond with Wes McKinney

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15/05/2459m 51s

#461: Python in Neuroscience and Academic Labs

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09/05/241h 3m

#460: Dropbase: Build Internal Tools with Python

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02/05/2452m 29s

#459: I Built A Python SaaS with AI

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27/04/2455m 6s

#458: Serverless Python in 2024

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24/04/241h

#457: Software Supply Chain Security with Phylum

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19/04/241h 8m

#456: Building GPT Actions with FastAPI and Pydantic

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16/04/241h 5m

#455: Land Your First Data Job

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04/04/2459m 33s

#454: Data Pipelines with Dagster

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21/03/2458m 25s

#453: uv - The Next Evolution in Python Packages?

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13/03/241h 14m

#452: Top Quart (async Flask) Extensions

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10/03/2455m 42s

#451: Djangonauts, Ready for Blast-Off

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01/03/2458m 33s

#450: Versioning Web APIs in Python

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22/02/241h 2m

#449: Building UIs in Python with FastUI

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13/02/241h 6m

#448: Full-Time Open Source Devs Panel

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08/02/2458m 46s

#447: Parallel Python Apps with Sub Interpreters

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03/02/241h 11m

#446: Python in Excel

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26/01/2448m 9s

#445: Inside Azure Data Centers with Mark Russinovich

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19/01/2442m 25s

#444: The Young Coder's Blueprint to Success

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02/01/2454m 59s

#443: Python Bytes Crossover 2023

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29/12/2335m 15s

#442: Ultra High Speed Message Parsing with msgspec

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14/12/231h

#441: Python = Syntactic Sugar?

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06/12/231h 7m

#440: Talking to Notebooks with Jupyter AI

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30/11/2358m 52s

#439: Pixi, A Fast Package Manager

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22/11/2359m 4s

#438: Celebrating JupyterLab 4 and Jupyter 7 Releases

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16/11/231h 4m

#437: HTMX for Django Developers (And All of Us)

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07/11/231h 4m

#436: An Unbiased Evaluation of Environment and Packaging Tools

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01/11/2358m 32s

#435: PyPI Security

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25/10/231h 3m

#434: Building Mobile Apps Backed with Python

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19/10/2358m 49s

#433: Litestar: Effortlessly Build Performant APIs

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15/10/231h 4m

#432: Migrating to Pydantic 2.0: Beanie for MongoDB

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06/10/2353m 54s

#431: Visualizing CPython Release Process

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29/09/231h 2m

#430: Delightful Machine Learning Apps with Gradio

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19/09/2359m 43s

#429: Taming Flaky Tests

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11/09/231h 9m

#428: Django Trends in 2023

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29/08/231h 9m

#427: 10 Tips and Ideas for the Beginner to Expert Python Journey

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19/08/231h 6m

#426: What's New in PyScript [August 2023]

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09/08/231h 5m

#425: Memray: The endgame Python memory profiler

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04/08/231h 10m

#424: Shiny for Python

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27/07/231h 4m

#423: Solving 10 different simulation problems with Python

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24/07/231h 6m

#422: How data scientists use Python

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07/07/231h 2m

#421: Python at Netflix

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02/07/231h 4m

#420: Database Consistency & Isolation for Python Devs

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26/06/2356m 2s

#419: Debugging Python in Production with PyStack

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14/06/231h 12m

#418: How To Keep A Secret in Python Apps

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02/06/231h 7m

#417: Test-Driven Prompt Engineering for LLMs with Promptimize

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30/05/231h 13m

#416: Open Source Sports Analytics with PySport

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22/05/2357m 29s

#415: Future of Pydantic and FastAPI

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15/05/2350m 5s

#414: A Stroll Down Startup Lane

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07/05/2352m 47s

#413: Live from PyCon 2023

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26/04/2347m 20s

#412: PEP 711 - Distributing Python Binaries

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19/04/231h 18m

#411: Things I Wish Someone Had Explained To Me Sooner About Python

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14/04/231h 3m

#410: The Intersection of Tabular Data and Generative AI

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06/04/231h 5m

#409: Privacy as Code with Fides

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01/04/231h 8m

#408: Hatch: A Modern Python Workflow

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24/03/231h 2m

#407: pytest tips and tricks for better testing

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18/03/2356m 22s

#406: Reimagining Python's Packaging Workflows

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12/03/231h 6m

#405: Testing in Radio Astronomy with Python and pytest

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03/03/2359m 21s

#404: Clean Code in Python

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20/02/231h 4m

#403: Fusion Ignition Breakthrough and Python

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13/02/231h 4m

#402: Polars: A Lightning-fast DataFrame for Python [updated audio]

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08/02/2358m 48s

#401: Migrating 3.8 Million Lines of Python

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02/02/231h

#400: Ruff - The Fast, Rust-based Python Linter

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25/01/231h 3m

#399: Monorepos in Python

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18/01/231h 10m

#398: Imaging Black Holes with Python

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14/01/2358m 13s

#397: Evaluating New Open Source Tech Panel

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05/01/231h 3m

#396: AI Goes on Trial For Writing Code (crossover)

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30/12/2237m 32s

#395: Tools for README.md Creation and Maintenance

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22/12/221h 13m

#394: Awesome Jupyter Libraries and Extensions in 2022

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15/12/221h 2m

#393: Space Science with Python

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08/12/221h 3m

#392: Data Science from the Command Line

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02/12/221h 11m

#391: Pyscript powered by MicroPython

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29/11/221h 11m

#390: Mastodon for Python Devs

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15/11/221h 8m

#389: 18 awesome asyncio packages in Python

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09/11/2257m 28s

#388: Python 3.11 is here and it's fast

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02/11/221h 6m

#387: Build All the Things with Pants Build System

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27/10/221h 7m

#386: Realtime Web Apps and Dashboards with H2O Wave

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19/10/221h 5m

#385: Higher level Python asyncio with AnyIO

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15/10/2259m 55s

#384: Python Data Visualization - Where To Start?

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04/10/221h 13m

#383: Textinator and Building macOS Apps with Python

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28/09/221h 6m

#382: Apache Superset: Modern Data Exploration Platform

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22/09/221h 8m

#381: Python Perf: Specializing, Adaptive Interpreter

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16/09/221h 8m

#380: 7 lessons from building a modern TUI framework

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05/09/221h 7m

#379: 17 Libraries You Should Be Using in Django

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26/08/221h 20m

#378: Flet: Flutter apps in Python

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21/08/221h

#377: Python Packaging and PyPI in 2022

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13/08/221h 8m

#376: Pydantic v2 - The Plan

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04/08/221h 18m

#375: Python Language Summit 2022

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30/07/2258m 31s

#374: PSF Survey in Review

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20/07/221h 2m

#373: Reinventing Azure's Python CLI

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12/07/221h 6m

#372: Applied mathematics with Python

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08/07/221h 15m

#371: pipx - Installable, Isolated Python Applications

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30/06/2258m 43s

#370: OpenBB: Python's Open-source Investment Platform

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22/06/2254m 28s

#369: Getting Lazy with Python Imports and PEP 690

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16/06/2256m 26s

#368: End-to-End Web Testing with Playwright

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03/06/221h 13m

#367: Say Hello to PyScript (WebAssembly Python)

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25/05/221h 13m

#366: Optimizing PostgreSQL DB Queries with pgMustard

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20/05/221h 14m

#365: Solving Negative Engineering Problems with Prefect

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12/05/221h 4m

#364: Symbolic Math with Python using SymPy

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07/05/221h 7m

#363: Python for .NET and C# developers

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28/04/221h 6m

#362: Hypermodern Python Projects

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20/04/221h 6m

#361: Pangeo Data Ecosystem

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16/04/2254m 16s

#360: Removing Python's Dead Batteries (in just 5 years)

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08/04/221h 20m

#359: Lifecycle of a machine learning project

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03/04/221h 7m

#358: Understanding Pandas visually with PandasTutor

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25/03/2246m 48s

#357: Python and the James Webb Space Telescope

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21/03/221h 2m

#356: Tips for ML / AI startups

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14/03/221h 6m

#355: EdgeDB - Building a database in Python

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06/03/221h 18m

#354: Sphinx, MyST, and Python Docs in 2022

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24/02/221h 11m

#353: SQLModel: The New ORM for FastAPI and Beyond

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18/02/221h 18m

#352: Running Python in Production

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08/02/221h

#351: Machine Learning Ethics and Laws Panel

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03/02/221h 10m

#350: Python Steering Council 2021 Retrospective

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26/01/221h 10m

#349: Meet Beanie: A MongoDB ODM + Pydantic

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22/01/221h 20m

#348: Dear PyGui: Simple yet Fast Python GUI Apps

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17/01/221h 1m

#347: Cinder - Specialized Python that Flies

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08/01/221h 11m

#346: 20 Recommended Packages in Review

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21/12/211h 13m

#345: 10 Tips and Tools for Developer Productivity

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15/12/211h 16m

#344: SQLAlchemy 2.0

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09/12/211h 6m

#343: Do Excel things, get notebook Python code with Mito

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30/11/211h 6m

#342: Python in Architecture (as in actual buildings)

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23/11/211h 1m

#341: 25 Pandas Functions You Didn’t Know Existed

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17/11/2159m 16s

#340: Time to JIT your Python with Pyjion?

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10/11/211h 13m

#339: Making Python Faster with Guido and Mark

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04/11/211h 1m

#338: Using cibuildwheel to manage the scikit-HEP packages

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17/10/211h 17m

#337: Kedro for Maintainable Data Science

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09/10/211h 3m

#336: Terminal magic with Rich and Textual

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05/10/2159m 12s

#335: Gene Editing with Python

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24/09/2158m 20s

#334: Microsoft Planetary Computer

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18/09/2159m 46s

#333: State of Data Science in 2021

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10/09/211h 3m

#332: Robust Python

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31/08/211h 11m

#331: Meet the Python Developer in Residence: Lukasz Langa

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27/08/211h 6m

#330: Apache Airflow Open-Source Workflow with Python

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20/08/211h 7m

#329: Geekout: Renewable Energy

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13/08/2148m 18s

#328: Piccolo: A fast, async ORM for Python (updated)

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08/08/2158m 51s

#327: Little Automation Tools in Python

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30/07/211h 5m

#326: Building Desktop Apps with wxPython

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23/07/2153m 32s

#325: MicroPython + CircuitPython

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15/07/211h 8m

#324: Gatorade-powered Python APIs

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09/07/211h 12m

#323: Best practices for Docker in production

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03/07/211h 10m

#322: A path into data science

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25/06/2159m 56s

#321: HTMX - Clean, Dynamic HTML Pages

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19/06/211h 12m

#320: Python in the Electrical Energy Sector

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12/06/211h 8m

#319: Typosquatting and Supply Chains Vulnerabilities

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06/06/2159m 43s

#318: Measuring your ML impact with CodeCarbon

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28/05/211h 7m

#317: Python at the US Federal Election Commission

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21/05/2152m 39s

#316: Flask 2.0

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14/05/2157m 38s

#315: Awesome FastAPI extensions and add ons

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07/05/211h 7m

#314: Ask us about modern Python projects and tools

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30/04/211h 4m

#313: Automate your data exchange with PyDantic

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22/04/211h

#312: Python Apps that Scale to Billions of Users

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18/04/211h 17m

#311: Get inside the .git folder

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08/04/211h 12m

#310: AMA (Ask Me Anything) with Michael

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02/04/211h 2m

#309: What ML Can Teach Us About Life: 7 Lessons

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26/03/2155m 44s

#308: Docker for Python Developers (2021 Edition)

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20/03/211h 8m

#307: Python from 1994 to 2021, my how you've grown!

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11/03/211h 11m

#306: Scaling Python and Jupyter with ZeroMQ

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05/03/211h 5m

#305: Python community at Python Discord

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01/03/211h 1m

#304: asyncio all the things with Omnilib

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21/02/211h

#303: Python for Astronomy with Dr. Becky

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12/02/211h 3m

#302: The Data Engineering Landscape in 2021

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04/02/211h 4m

#301: Deploying and running Django web apps in 2021

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28/01/211h 8m

#300: Building a data science startup (panel)

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22/01/211h 6m

#299: Personal search engine with datasette and dogsheep

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17/01/211h 1m

#298: Building ML teams and finding ML jobs

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11/01/2156m 10s

#297: Python year in review (2020 edition)

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28/12/201h 10m

#296: Python in F1 racing

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23/12/201h 5m

#295: GIS + Python

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18/12/2057m 0s

#294: oso authorizes Python

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07/12/2051m 27s

#293: Learning how to learn as a developer

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01/12/201h

#292: Pythonic identity (auth in Python ecosystem)

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26/11/201h 5m

#291: Operational Resilience with Pyomo

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22/11/2059m 36s

#290: Side Hustles for Data Scientists

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13/11/201h 8m

#289: Discovering exoplanets with Python

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09/11/2047m 26s

#288: 10 tips to move from Excel to Python

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31/10/201h 3m

#287: Testing without dependencies, mocking in Python

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21/10/201h 3m

#286: Python and ML at NASA Jet Propulsion Laboratory (JPL)

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16/10/201h 7m

#285: Dask as a Platform Service with Coiled

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09/10/201h 11m

#284: Modern and fast APIs with FastAPI

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04/10/201h 6m

#283: Web scraping, the 2020 edition

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23/09/2048m 34s

#282: pre-commit framework

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17/09/2059m 33s

#281: Python in Car Racing

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09/09/201h

#280: Python and AI in Journalism

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05/09/2055m 51s

#279: Modern Python Developer's Toolkit

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29/08/201h 1m

#278: Teach kids Python with real programming and fun games at Code Combat

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21/08/201h 5m

#277: 10 tips every Django developer should know

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10/08/201h 11m

#276: Geekout: Life in the solar system and beyond

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06/08/201h 14m

#275: Beautiful Pythonic Refactorings

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01/08/2055m 4s

#274: Profiling data science code with FIL

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24/07/2058m 12s

#273: CoCalc: A fully colloborative notebook development environment

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18/07/2055m 6s

#272: No IoT things in hand? Simulate them with Device Simulator Express

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12/07/2051m 47s

#271: Unlock the mysteries of time, Python's datetime that is!

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04/07/201h 4m

#270: Python in supply chains: oil rigs, rockets, and lettuce

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25/06/2059m 20s

#269: HoloViz - a suite of tools for Python visualization

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19/06/2055m 57s

#268: Analyzing dozens of notebook environments

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13/06/2054m 24s

#267: 15 amazing pytest plugins

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06/06/2053m 34s

#266: Refactoring your code, like magic with Sourcery

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29/05/2057m 5s

#265: Why is Python slow?

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19/05/201h 3m

#264: 10 tips every Flask developer should know

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12/05/201h 8m

#263: SEO for developers

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06/05/201h 2m

#262: Build a career in data science

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01/05/201h 11m

#261: Monitoring and auditing machine learning

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25/04/201h

#260: From basic script to interactive data sci app with Streamlit

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18/04/2059m 25s

#259: From Academia to Tech Industry and Python

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09/04/201h

#258: Thriving in a remote developer environment

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04/04/201h 7m

#257: Exploring the galaxy with the fastest supercomputer, Python, and radio astronomy

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28/03/2052m 23s

#256: Click to run your notebook with Binder

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20/03/2057m 26s

#255: Talking to cars with Python

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14/03/2051m 51s

#254: A Python mentorship story

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06/03/201h 7m

#253: Moon base geekout

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25/02/201h 22m

#252: What scientific computing can learn from CS

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21/02/201h 10m

#251: Building and UX Testing Azure's Python SDK

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13/02/2052m 44s

#250: Capture over 400x C02 as trees with AI and Python

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08/02/201h 3m

#249: Capture the Staff of Pythonic Knowledge in TwilioQuest

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30/01/2059m 1s

#248: Climate change and your Python code

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24/01/201h 16m

#247: Solo maintainer of open-source in academia

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16/01/201h 5m

#246: Practices of the Python Pro

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09/01/201h 4m

#245: Python packaging landscape in 2020

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03/01/201h 1m

#244: Top 10 Real Python Articles of 2019

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27/12/1959m 49s

#243: Python on Windows is OK, actually

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17/12/1957m 38s

#242: Your education will be live-streamed

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11/12/1954m 23s

#241: Opal: Full stack health care apps

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07/12/1953m 23s

#240: A guided tour of the CPython source code

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27/11/191h

#239: Bayesian foundations

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23/11/1957m 18s

#237: A gut feeling about Python

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06/11/1949m 40s

#236: Scaling data science across Python and R

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29/10/191h

#235: Python in your Browser with Skulpt

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23/10/191h

#234: Awesome Python Applications

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15/10/191h 4m

#233: The Masonite Python Web Framework

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10/10/191h 8m

#232: Become a robot developer with Python

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04/10/191h 1m

#231: Advice for freelancing with Python

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25/09/191h 9m

#230: Python in digital humanities research

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18/09/1957m 42s

#229: Building advanced Pythonic interviews with docassemble

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12/09/191h

#228: Hunting bugs and tech startups with Python

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04/09/1959m 41s

#227: Maintainable data science: Tips for non-developers

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28/08/191h 10m

#226: Building Flask APIs for data scientists

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23/08/191h 9m

#225: Can subinterpreters free us from Python's GIL?

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12/08/191h 10m

#224: 12 lessons from 100 days of web

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05/08/191h 8m

#223: Fun and Easy 2D Games with Python

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30/07/191h 3m

#222: Interactive graphs with Bokeh and Python

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26/07/1959m 19s

#221: Empowering developers by embedding Python

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18/07/191h 7m

#220: Machine Learning in the cloud with Azure ML

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12/07/1954m 44s

#219: Take a Python tour of duty at the United States Digital Service

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05/07/191h 1m

#218: Serverless Python functions in Azure

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25/06/1947m 57s

#217: Notebooks vs data science-enabled scripts

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21/06/1954m 25s

#216: Digging into Visual Studio Code

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14/06/1953m 5s

#215: The software powering Talk Python courses and podcast

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06/06/191h 7m

#214: Dive into CPython 3.8 and beyond

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31/05/191h

#213: WebAssembly and CPython

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25/05/1949m 8s

#212: Python in Web Assembly with Pyodide

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17/05/1957m 21s

#211: Classic CS problems in Python

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11/05/191h 8m

#210: Making the most out of in-person training

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02/05/191h 7m

#209: Inside Python's new governance model

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28/04/191h 7m

#208: Packaging, Making the most of PyCon, and more

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21/04/191h 10m

#207: Parallelizing computation with Dask

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14/04/1957m 53s

#206: Running Django in Production

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06/04/1951m 25s

#205: Beginners and Experts Panel

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02/04/1957m 53s

#204: StaticFrame, like Pandas but safer

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21/03/191h 1m

#203: Beginners and Experts in Software Development

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13/03/1957m 35s

#202: Building a software business

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09/03/1959m 1s

#201: Choosing JupyterHub and Python over MATLAB

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27/02/191h 3m

#200: Escaping Excel Hell with Python and Pandas

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21/02/191h 6m

#199: Automate all the things with Python at Zapier

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14/02/191h 5m

#198: Catching up with the Anaconda distribution

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09/02/191h 5m

#197: Modern Python Standard Library Cookbook

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02/02/191h 1m

#196: Datalore: Hosted smart notebooks

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23/01/1949m 50s

#195: Teaching Python at Apple

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20/01/191h

#194: Learning (and teaching) Python in a vacuum

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11/01/191h 6m

#193: Data Science Year in Review 2018 Edition

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31/12/181h 20m

#192: Python Year in Review 2018 Edition

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26/12/1859m 3s

#191: Python's journey at Microsoft

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18/12/181h 12m

#190: Teaching Django

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11/12/181h 1m

#189: War Stories of the Developer Evangelists

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07/12/1859m 11s

#188: Async for the Pythonic web with Sanic

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01/12/1856m 22s

#187: Secure all the things with HubbleStack

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20/11/1859m 53s

#186: 100 Days of Python in a Magical Universe

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16/11/181h 2m

#185: Creating a Python 3 Culture at Facebook

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09/11/181h 7m

#184: Teaching Python with BBC micro:bit

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02/11/181h 7m

#183: Qt for Python

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24/10/1858m 3s

#182: Picture Python at Shutterfly

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17/10/1858m 15s

#181: 30 amazing Python projects

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12/10/1852m 10s

#180: What's new in Python 3.7 and beyond

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02/10/1857m 26s

#179: Python Language Summit 2018

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26/09/1850m 36s

#178: Coverage.py

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21/09/181h 3m

#177: Flask goes 1.0

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15/09/181h 2m

#176: The Python Community by the Numbers

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10/09/1853m 29s

#175: Teaching Python to network engineers

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31/08/1855m 27s

#174: Coming into Python from another Industry (part 2)

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16/08/1851m 6s

#173: Coming into Python from another Industry (part 1)

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07/08/1857m 25s

#172: Nuitka: A full Python compiler

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01/08/181h 6m

#171: 1M Jupyter notebooks analyzed

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29/07/1858m 32s

#170: Guido van Rossum steps down

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20/07/1837m 55s

#169: Becoming a Python content creator

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13/07/181h 6m

#168: 10 Python security holes and how to plug them

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06/07/181h

#167: Simplifying Python's Async with Trio

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29/06/1855m 41s

#166: Continuous delivery with Python

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14/06/181h 9m

#165: Python and the blockchain

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08/06/181h 5m

#164: Python in Brain Research at the Allen Institute

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01/06/1857m 54s

#163: Python in Geoscience

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25/05/1852m 17s

#162: Python in Building and Architecture

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21/05/1854m 35s

#161: Django 2.0

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12/05/181h 7m

#160: Lektor: Beautiful websites out of flat files

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04/05/1855m 41s

#159: Inside the new PyPI launch

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27/04/181h

#158: Quantum Computing and Python

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20/04/1847m 54s

#157: The Journal of Open Source Software

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06/04/181h 4m

#156: Python History and Perspectives

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24/03/1859m 7s

#155: Practical steps for moving to Python 3

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16/03/181h 3m

#154: Python in Biology and Genomics

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07/03/1858m 16s

#153: How Python Evolves

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01/03/181h 22m

#152: Understanding and using Python's AST

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23/02/1851m 55s

#151: Gradual Typing of Production Applications

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16/02/181h 9m

#150: Technical Lessons Learned from Pythonic Refactoring

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08/02/1859m 57s

#149: 4 Python Web Frameworks, Compared

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02/02/1857m 25s

#148: Python Book Authors' Panel Discussion

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28/01/181h 2m

#147: Quart: Flask, but 3x faster

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19/01/1851m 2s

#146: Building Alexa Skills with Python and Flask

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11/01/181h 1m

#145: 2017 Python Year in Review

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31/12/1759m 23s

#144: Machine Learning at the Large Hadron Collider

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26/12/1758m 22s

#143: Tuning Python Web App Performance

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20/12/171h 3m

#141: Python tricks

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07/12/171h 11m

#140: Level up your Python with #100DaysOfCode challenge

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29/11/1758m 18s

#139: Paths into a data science career

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22/11/171h 2m

#138: Anvil: All web, all Python

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15/11/171h

#137: Design concepts and tips for developers

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08/11/1758m 3s

#136: Secure code lessons from Have I Been Pwned

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02/11/171h

#135: Capturing human moments with AI and Python

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27/10/1754m 9s

#134: Python in Climate Science

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19/10/1752m 50s

#133: Productivity for developers

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11/10/171h 4m

#132: Contributing to open source

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04/10/171h 4m

#131: Top 10 machine learning libraries

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26/09/1754m 8s

#130: 10 books Python developers should be reading

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19/09/1752m 28s

#129: Falcon: The bare-metal Python web framework

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14/09/1759m 53s

#128: Pythonic Networks with NAPALM

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07/09/1756m 22s

#127: Shipping software to users

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31/08/171h 15m

#126: Kubernetes for Pythonistas

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22/08/1759m 39s

#125: Django REST framework and a new API star is born

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15/08/171h 7m

#124: Python for AI research

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07/08/1755m 20s

#123: Lessons from 100 straight dev job interviews

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31/07/1746m 23s

#122: Home Assistant: Pythonic Home Automation

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26/07/1758m 8s

#121: Microservices in Python

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19/07/171h 5m

#120: Python in Finance

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12/07/171h 7m

#119: Python in Engineering

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06/07/1752m 23s

#118: Serverless software

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27/06/1754m 50s

#117: Functional Python with Coconut

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21/06/171h 3m

#116: 10 top talks of PyCon 2017 reviewed

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12/06/171h

#115: Python for Humans projects

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08/06/1753m 45s

#114: Empowering developers at the Hidden Genius project

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30/05/1738m 2s

#113: Dedicated AI chips and running old Python faster at Intel

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27/05/1753m 2s

#112: Geeking out in the golden years

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18/05/171h 7m

#111: Pythonic Career Advice and More

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13/05/1757m 35s

#110: Data Democratization with Redash

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02/05/1756m 2s

#109: MongoDB Applied Design Patterns

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29/04/171h

#108: MicroPython and Open Source Hardware at Adafruit

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21/04/171h 4m

#107: Python concurrency with Curio

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15/04/171h 1m

#106: Invent your own computer games with Python

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07/04/1758m 12s

#105: A Pythonic Database Tour

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27/03/1757m 56s

#104: Game Theory in Python

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23/03/1757m 50s

#103: Compiling Python through PyLLVM and MongoDB for Data Scientists

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16/03/1752m 36s

#102: Effective Code Reviews

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08/03/1750m 52s

#101: Adding a full featured Python environment to Visual Studio Code

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03/03/1755m 11s

#100: Python past, present, and future with Guido van Rossum

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22/02/171h 2m

#99: Morepath: Super Powered Python Web Framework

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15/02/171h 4m

#98: Adding concurrency to Django with Django Channels

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08/02/171h 5m

#97: Flask, Django style with Flask-Diamond

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02/02/171h 5m

#96: Exploring Awesome Python

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25/01/1752m 20s

#95: Grumpy: Running Python on Go

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18/01/1752m 9s

#94: Guarenteed packages via Conda and Conda-Forge

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11/01/1746m 31s

#93: Spreading Python through the sciences with Software Carpentry

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03/01/171h 1m

#92: Bonus: Python Bytes Crossover: Python 3.6 is going to be awesome, Kite: your friendly co-developing AI

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29/12/1621m 0s

#91: Top 10 Data Science Stories of 2016

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27/12/161h 7m

#90: Data Wrangling with Python

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21/12/161h 1m

#89: A conversation with the Chief Data Scientist of the United States

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15/12/1652m 39s

#88: Lightweight Django

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06/12/1659m 58s

#87: PonyORM: The most Pythonic ORM yet?

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29/11/1656m 29s

#86: Python at StackOverflow

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24/11/161h 10m

#85: Parsing horrible things with Python

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17/11/1659m 46s

#84: Are we failing to fund Python's core infrastructure?

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08/11/161h 5m
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