Episodes HN recommended
#407: pytest tips and tricks for better testing
Mar 18, 2023 • 56 min#406: Reimagining Python's Packaging Workflows
Mar 12, 2023 • 1 h 07 min#400: Ruff - The Fast, Rust-based Python Linter
Jan 25, 2023 • 1 h 04 min#398: Imaging Black Holes with Python
Jan 14, 2023 • 58 min#395: Tools for README.md Creation and Maintenance
Dec 22, 2022 • 1 h 14 min#391: Pyscript powered by MicroPython
Nov 29, 2022 • 1 h 11 min#390: Mastodon for Python Devs
Nov 15, 2022 • 1 h 09 min#378: Flet: Flutter apps in Python
Aug 21, 2022 • 1 h 00 min#357: Python and the James Webb Space Telescope
Mar 21, 2022 • 1 h 03 min#344: SQLAlchemy 2.0
Dec 9, 2021 • 1 h 06 min#336: Terminal magic with Rich and Textual
Oct 5, 2021 • 59 min#328: Piccolo: A fast, async ORM for Python (updated)
Aug 8, 2021 • 59 min#327: Little Automation Tools in Python
Jul 30, 2021 • 1 h 06 min#316: Flask 2.0
May 14, 2021 • 58 min#299: Personal search engine with datasette and dogsheep
Jan 17, 2021 • 1 h 02 min#295: GIS + Python
Dec 18, 2020 • 57 min#294: oso authorizes Python
Dec 7, 2020 • 51 min#281: Python in Car Racing
Sep 9, 2020 • 1 h 00 min#271: Unlock the mysteries of time, Python's datetime that is!
Jul 4, 2020 • 1 h 05 min#260: From basic script to interactive data sci app with Streamlit
Apr 18, 2020 • 59 min#258: Thriving in a remote developer environment
Apr 4, 2020 • 1 h 08 min#248: Climate change and your Python code
Jan 24, 2020 • 1 h 17 min#244: Top 10 Real Python Articles of 2019
Dec 27, 2019 • 1 h 00 min#243: Python on Windows is OK, actually
Dec 17, 2019 • 58 min#240: A guided tour of the CPython source code
Nov 27, 2019 • 1 h 00 min#206: Running Django in Production
Apr 6, 2019 • 51 min#191: Python's journey at Microsoft
Dec 18, 2018 • 1 h 12 min#183: Qt for Python
Oct 24, 2018 • 58 min#173: Coming into Python from another Industry (part 1)
Aug 7, 2018 • 57 min#172: Nuitka: A full Python compiler
Aug 1, 2018 • 1 h 07 min#171: 1M Jupyter notebooks analyzed
Jul 29, 2018 • 59 min#159: Inside the new PyPI launch
Apr 27, 2018 • 1 h 01 min#156: Python History and Perspectives
Mar 24, 2018 • 59 min#155: Practical steps for moving to Python 3
Mar 16, 2018 • 1 h 03 min#153: How Python Evolves
Mar 1, 2018 • 1 h 22 min#150: Technical Lessons Learned from Pythonic Refactoring
Feb 8, 2018 • 1 h 00 min#149: 4 Python Web Frameworks, Compared
Feb 2, 2018 • 57 min#147: Quart: Flask, but 3x faster
Jan 19, 2018 • 51 min#145: 2017 Python Year in Review
Dec 31, 2017 • 59 min#144: Machine Learning at the Large Hadron Collider
Dec 26, 2017 • 58 min#143: Tuning Python Web App Performance
Dec 20, 2017 • 1 h 03 min#141: Python tricks
Dec 7, 2017 • 1 h 12 min#140: Level up your Python with #100DaysOfCode challenge
Nov 29, 2017 • 58 min#137: Design concepts and tips for developers
Nov 8, 2017 • 58 min#134: Python in Climate Science
Oct 19, 2017 • 53 min#132: Contributing to open source
Oct 4, 2017 • 1 h 05 min#131: Top 10 machine learning libraries
Sep 26, 2017 • 54 min#127: Shipping software to users
Aug 31, 2017 • 1 h 15 min#126: Kubernetes for Pythonistas
Aug 22, 2017 • 1 h 00 min#124: Python for AI research
Aug 7, 2017 • 55 min#123: Lessons from 100 straight dev job interviews
Jul 31, 2017 • 46 min#122: Home Assistant: Pythonic Home Automation
Jul 26, 2017 • 58 min#121: Microservices in Python
Jul 19, 2017 • 1 h 06 min#119: Python in Engineering
Jul 6, 2017 • 52 min#118: Serverless software
Jun 27, 2017 • 55 min#117: Functional Python with Coconut
Jun 21, 2017 • 1 h 04 min#116: 10 top talks of PyCon 2017 reviewed
Jun 12, 2017 • 1 h 00 min#115: Python for Humans projects
Jun 8, 2017 • 54 min#114: Empowering developers at the Hidden Genius project
May 30, 2017 • 38 min#113: Dedicated AI chips and running old Python faster at Intel
May 27, 2017 • 53 min#112: Geeking out in the golden years
May 18, 2017 • 1 h 07 min#110: Data Democratization with Redash
May 2, 2017 • 56 min#109: MongoDB Applied Design Patterns
Apr 29, 2017 • 1 h 00 min#107: Python concurrency with Curio
Apr 15, 2017 • 1 h 01 min#103: Compiling Python through PyLLVM and MongoDB for Data Scientists
Mar 16, 2017 • 53 min#102: Effective Code Reviews
Mar 8, 2017 • 51 min#101: Adding a full featured Python environment to Visual Studio Code
Mar 3, 2017 • 55 min#100: Python past, present, and future with Guido van Rossum
Feb 22, 2017 • 1 h 03 min#99: Morepath: Super Powered Python Web Framework
Feb 15, 2017 • 1 h 05 min#98: Adding concurrency to Django with Django Channels
Feb 8, 2017 • 1 h 05 min#97: Flask, Django style with Flask-Diamond
Feb 2, 2017 • 1 h 05 min#96: Exploring Awesome Python
Jan 25, 2017 • 52 min#95: Grumpy: Running Python on Go
Jan 18, 2017 • 52 min#94: Guarenteed packages via Conda and Conda-Forge
Jan 11, 2017 • 47 min#93: Spreading Python through the sciences with Software Carpentry
Jan 3, 2017 • 1 h 02 min#91: Top 10 Data Science Stories of 2016
Dec 27, 2016 • 1 h 08 min#89: A conversation with the Chief Data Scientist of the United States
Dec 15, 2016 • 53 min#88: Lightweight Django
Dec 6, 2016 • 1 h 00 min#87: PonyORM: The most Pythonic ORM yet?
Nov 29, 2016 • 56 min#86: Python at StackOverflow
Nov 24, 2016 • 1 h 10 min#84: Are we failing to fund Python's core infrastructure?
Nov 8, 2016 • 1 h 05 min#82: Grokking Algorithms in Python
Oct 27, 2016 • 59 min#81: Python and Machine Learning in Astronomy
Oct 21, 2016 • 1 h 02 min#80: TinyDB: A tiny document db written in Python
Oct 16, 2016 • 47 min#79: Beeware Python Tools
Oct 7, 2016 • 1 h 22 min#74: Past, Present, and Future of IronPython
Sep 2, 2016 • 51 min#73: Machine learning at the new Microsoft
Aug 26, 2016 • 1 h 05 min#72: Fashion-driven open source software at Zalando
Aug 19, 2016 • 1 h 01 min#66: Faster Python Programs: Measure, Don't Guess
Jul 7, 2016 • 1 h 05 min#65: Jump on the real-time web with RethinkDB
Jun 29, 2016 • 59 min#61: Free software, free people
May 30, 2016 • 54 min#60: Scaling Python to 1000's of cores with Ufora
May 24, 2016 • 1 h 07 min#58: Create better Python programs with concurrency, libraries, and patterns
May 10, 2016 • 55 min#57: Python performance from the inside-out at Intel
May 5, 2016 • 57 min#56: Data Science from Scratch
Apr 27, 2016 • 51 min#55: How our engineering environments are killing diversity (and how we can fix it)
Apr 21, 2016 • 1 h 02 min#54: Enterprise Software with Python
Apr 14, 2016 • 1 h 08 min#53: Python in Visual Studio
Apr 6, 2016 • 51 min#52: EVE Online: MMO game powered by Python
Mar 27, 2016 • 55 min#50: Web scraping at scale with Scrapy and ScrapingHub
Mar 15, 2016 • 58 min
Recent episodes
#568: Cloudflare Python Workers
Nov 3, 2026 • 1 h 02 min#567: Personal AI Agents for Pythonistas
Oct 27, 2026 • 1 h 07 min#566: State of the art in Python 2026
Oct 17, 2026 • 1 h 05 min#565: Tachyon, Python 3.15's Built-in Sampling Profiler
Oct 2, 2026 • 1 h 28 min#564: EVE Online Departs for Python 3
Sep 22, 2026 • 1 h 08 min#563: Getting Started with Rust as Python Devs
Sep 16, 2026 • 1 h 11 min#562: DuckLake: The Lakehouse That's Just SQL and Parquet
Sep 10, 2026 • 1 h 11 min#561: TonIO, a Multi-threaded Async Runtime for Python
Sep 4, 2026 • 1 h 16 min#560: Building a Research OS: From Django to 30,000 Samples
Aug 26, 2026 • 1 h 03 min#559: 12 Things You Should (and Shouldn't) Do in AWS
Aug 19, 2026 • 1 h 08 min#558: Hyper-Personal Software with Python
Aug 10, 2026 • 1 h 02 min#557: Security of everything at PyCon 2026
Aug 2, 2026 • 1 h 08 min#556: Updates on Django's Async Story
Jul 26, 2026 • 1 h 05 min#555: Marimo Pair - A Canvas for Agent + Developers Collaboration
Jul 13, 2026 • 1 h 05 min#554: Trustworthy AI in Healthcare and Longevity
Jul 10, 2026 • 1 h 01 min#553: All of our tools
Jun 26, 2026 • 55 min#552: Astral joins OpenAI
Jun 17, 2026 • 1 h 05 min#551: Stroll Down Startup Lane - 2026
Jun 11, 2026 • 1 h 49 min#550: AI Contributions and Maintainer Load in Open Source
May 30, 2026 • 1 h 03 min#549: Great Docs
May 25, 2026 • 1 h 07 min#548: Event Sourcing Design Pattern
May 11, 2026 • 1 h 09 min#547: Parallel Python at Anyscale with Ray
May 6, 2026 • 59 min#546: Self hosting apps for Python people
Apr 27, 2026 • 1 h 03 min#545: OWASP Top 10 (2025 List) for Python Devs
Apr 16, 2026 • 1 h 06 min#544: Wheel Next + Packaging PEPs
Apr 10, 2026 • 1 h 11 min#543: Deep Agents: LangChain's SDK for Agents That Plan and Delegate
Apr 1, 2026 • 1 h 04 min#542: Zensical - a modern static site generator
Mar 25, 2026 • 1 h 04 min#541: Monty - Python in Rust for AI
Mar 19, 2026 • 1 h 06 min#540: Modern Python monorepo with uv and prek
Mar 13, 2026 • 1 h 02 min#539: Catching up with the Python Typing Council
Mar 6, 2026 • 1 h 02 min
What HN said
- rgreasonsSep 2016Not all of these are "software engineering," but many of them often tie to the soft skills side of things or general development rigor.
Regular listens - shows to which I subscribe, in rough order of how excited I am to see them show up in my podcast app:
Not So Standard Deviations [0]
Immutable [1]
ShopTalk [2]
Talk Python to Me [3]
The Versioning Show [4]
Data Skeptic [5]
Occasional listens - not subscribed but regularly check for interesting guests:
Data Stories [6]
Partially Derivative [7]
I tried Software Engineering Daily last year and wasn't a big fan - based on the following here I'll have to give it another shot.
0 - https://soundcloud.com/nssd-podcast
1 - https://spec.fm/podcasts/immutable
- bredrenAug 2022Mike, thanks for this reply and your work on SQLAlchemy. My employer uses your framework, but not yet the newest versions featuring async.
Previously, and still in my personal projects, I have been a Django and Django ORM person.
I got away with by and large avoiding SQL statements in building web apps and have sometimes struggled to understand why SQL statements seemed much more forward-facing in SQLAlchemy in comparison.
Then I listened to your recent Talk Python podcast episode with M. Kennedy [1] and it helped me understand where the framework is coming from with regards to expectations for SQL capability from a developer that wants to use SQLAlchemy.
I believe the focus was much more so on the dark secrets you mention above, though and colored in how you discovered those.
If anyone wants to learn more about async or SQLAlchemy, I highly recommend listening.
As an aside, it was also cool to hear you talking about your project because for me, it humanized you as the maintainer. You sounded pretty chill, which was for some reason not what I was expecting.
I hope you can make it back on to that podcast with less of a gap between appearances next time.
- sumukh1Feb 2016Here are some related links:
Demo of Python Tutor being used in a computer science textbook: http://www.composingprograms.com/pages/17-recursive-function...
The textbook above is from the introductory computer science course at UC Berkeley (http://cs61a.org)
Previous Discussion (~3 years ago): https://news.ycombinator.com/item?id=4601478
If you are interested in the technical details of CPython, the author posted a mini course on technical details about CPython here: http://pgbovine.net/cpython-internals.htm
1 hour podcast that describes the course: https://talkpython.fm/episodes/show/22/cpython-internals-and...
- guiambrosDec 2016+1. Love This Developer's Life; too bad it stopped being updated a couple of years ago (with only 1-2 episodes since then).
My other picks:
Data Skeptic - http://dataskeptic.com/ (about data, statistics, ML)
Embedded.fm - http://embedded.fm (about embedded development, hardware and electronics)
The Amp Hour - http://theamphour.com/ (about hardware making and electronics)
Talk Python to Me - https://talkpython.fm/ (Python, programming languages, tech interviews)
Floss Weekly - https://twit.tv/shows/floss-weekly (FLOSS, open source, hosted by Randal 'the camel book' Schwartz)
- a-salehDec 2016I listened to a podcast about jupyter [1] some time ago, and remebered them talking about the separation between the kernel and the presentation in jupyter, and that in theory, it should be relatively easy to write your own frontend, that just sends to correct messages to the zmq :-)
Afaik, hydrogen plugin for atom does this [2] And there is another plugin that just wraps the notebook to live inside of atom [3]
[1] https://talkpython.fm/episodes/show/44/project-jupyter-and-i... [2] https://atom.io/packages/hydrogen [3] https://github.com/jupyter/atom-notebook
- 616cJul 2016So I heard the course designer, who is this no-name author generally in Infosec for his work on this no-name Gray Hay Python book (yes, that's absurdist sarcasm).
https://talkpython.fm/episodes/transcript/37/python-cybersec...
He was talking up ISIS analysis using his OSINT methods for someone who does not speak Arabic by analyzing the black Jihadist flags (I find that kind of shoddy, as someone who knows that is painting with broad, but deservedly ugly brush for such people) with Python and OpenCV if I recall.
Has anyone taken the course and willing to say it was worth the money? He is no fool, and the price tag was steep, so I was curious if any in the community saw it is as a worthwhile investment opportunity.