Talk Python To Me - Python Conversations For Passionate Developers

Have you heard of Kedro? It's a Python framework for creating reproducible, maintainable and modular data science code. We all know that reproducibility and related topics are important ones in the data science space. The freedom to pop open a notebook and just start exploring is much of the magic. Yet, that free-form style can lead to difficulties in versioning, reproducibility, collaboration, and moving to production. Solving these problems is the goal of Kedro. And we have 3 great guests from the Kedro community here to give us the rundown: Yetunde Dada, Waylon Walker, and Ivan Danov. Links from the show Waylong on Twitter: @_WaylonWalker Yetunda on Twitter: @yetudada Ivan on Twitter: @ivandanov Kedro: kedro.readthedocs.io Kedro on GitHub: github.com Join the Kedro Discord: discord.gg Articles about Kedro by Waylan: waylonwalker.com Kedro spaceflights tutorial: kedro.readthedocs.io “Hello World” on Kedro: kedro.readthedocs.io Kedro Viz: quantumblacklabs.github.io Spaceflights Tutorial video: you

Have you heard of the package Rich? This library allows you to create very, well, rich terminal-based UIs in Python. When you think of what you can typically build with basic print statements, that may seem quite limited. But with Rich, imagine justified tables, progress bars, rendering of markdown, and way more. This is one of the fastest growing projects in the Python space these days. And the creator, Will McGugan is here to give is the whole history and even a peak at the future of Rich and a follow on library called Textual. Links from the show Will on Twitter: @willmcgugan Rich: github.com Textual: github.com Pyfilesystem: pyfilesystem.org A Look At – and Inside – Textual Video: youtube.com ObjExplore: reposhub.com ghtop: ghtop.fast.ai Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm ---------- Stay in touch with us ---------- Subscribe on YouTube (for live streams): youtube.com Follow Talk Python on Twitter: @talkpython Follow Michael on Twitter: @mkennedy Sponsors S

Gene therapy holds the promise to permanently cure diseases that have been considered life-long challenges. But the complexity of rewriting DNA is truly huge and lives in its own special kind of big-data world. On this episode, you'll meet David Born, a computational biologist who uses Python to help automate genetics research and helps move that work to production. Links from the show David on Twitter: @Hypostulate Beam Therapeutics: beamtx.com AWS Cloud Development Kit: aws.amazon.com/cdk Jupyter: jupyter.org $1,279-per-hour, 30,000-core cluster built on Amazon EC2 cloud: arstechnica.com Luigi data pipelines: luigi.readthedocs.io AWS Batch: aws.amazon.com/batch What is CRISPR?: wikipedia.org SUMMIT supercomputer: olcf.ornl.gov/summit Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm ---------- Stay in touch with us ---------- Subscribe on YouTube (for live streams): youtube.com Follow Talk Python on Twitter: @talkpython Follow Michael on Twitter: @mkennedy Sponsors Shortcu

On this episode, Rob Emanuele and Tom Augspurger join us to talk about building and running Microsoft's Planetary Computer project. This project is dedicated to providing the data around climate records and the compute necessary to process it with the mission of help use all understand climate change better. It combines multiple petabytes of data with a powerful hosted Jupyterlab notebook environment to process it. Links from the show Rob Emanuele on Twitter: @lossyrob Tom Augspurger on Twitter: @TomAugspurger Video at example walkthrough by Tom if you want to follow along: youtube.com?t=2360 Planetary computer: planetarycomputer.microsoft.com Applications in public: planetarycomputer.microsoft.com Microsoft's Environmental Commitments Carbon negative: blogs.microsoft.com Report: microsoft.com AI for Earth grants: microsoft.com Python SDK: github.com Planetary computer containers: github.com IPCC Climate Report: ipcc.ch Episode transcripts: talkpython.fm Stay in touch with us Subscribe on YouTube (for

We know that Python and data science are growing in lock-step together. But exactly what's happening in the data science space in 2021? Stan Seibert from Anaconda is here to give us a report on what they found with their latest "State of Data Science in 2021" survey. Links from the show Stan on Twitter: @seibert State of data science survey results: know.anaconda.com A Python Data Scientist’s Guide to the Apple Silicon Transition: anaconda.com Numpy M1 Issue: github.com A Python Developer Explores Apple's M1 (Michael's video): youtube.com Watch YouTube live stream edition: youtube.com Episode transcripts: talkpython.fm Stay in touch with us Subscribe on YouTube (for live streams): youtube.com Follow Talk Python on Twitter: @talkpython Follow Michael on Twitter: @mkennedy Sponsors Shortcut Masterworks.io AssemblyAI Talk Python Training

Does it seem like your Python projects are getting bigger and bigger? Are you feeling the pain as your codebase expands and gets tougher to debug and maintain? Patrick Viafore is here to help us write more maintainable, longer-lived, and more enjoyable Python code. Links from the show Pat on Twitter: @PatViaforever Robust Python Book: oreilly.com Typing in Python: docs.python.org mypy: mypy-lang.org SQLModel: sqlmodel.tiangolo.com CUPID principles @ relevant time: overcast.fm Stevedore package: docs.openstack.org Watch YouTube live stream edition: youtube.com Episode transcripts: talkpython.fm Stay in touch with us Subscribe on YouTube (for live streams): youtube.com Follow Talk Python on Twitter: @talkpython Follow Michael on Twitter: @mkennedy Sponsors Shortcut Masterworks.io AssemblyAI Talk Python Training

Python is a technology and community built upon the goodwill and volunteer time of 1,000s of contributors from the core devs inside CPython to the authors of 100,000s of external packages on PyPI. Until recently, the only full time folks have been at the PSF doing very important work but that work has been largely outside of CPython the technology. In July, 2021, the PSF created the Python Developer in Residence position. The first person in that role is Łukasz Langa and he's here to tell us how it's going and how it will benefit Python at large. Links from the show Łukasz Langa on twitter: @llanga Black: github.com/psf/black CPython PRs: github.com Weekly reports: lukasz.langa.pl Visionary Sponsors: python.org/psf/sponsorship/sponsors What do you get when you sponsor the PSF?: www.python.org/sponsors/application Brett Canon's PyCascades talk: youtube.com Django fellowship program: djangoproject.com Lukasz's prior episodes: Gradual Typing of Production Applications: talkpython.fm/151 Dive into CPython

If you are working with data pipelines, you definitely need to give Apache Airflow a look. This pure-Python workflow framework is one of the most popular and capable out there. You create your workflows by writing Python code using clever language operators and then you can monitor them and even debug them visually once they get started. Stop writing manual code or cron-job based code to create data pipelines check out Airflow. We're joined by three excellent guests from the Airflow community: Jarek Potiuk, Kaxil Naik, and Leah Cole. Links from the show Jarek Potiuk: linkedin.com Kaxil Naik: @kaxil Leah Cole: @leahecole Airflow site: airflow.apache.org Airflow on GitHub: github.com Airflow community: airflow.apache.org UI: github.com Helm Chart for Apache Airflow: airflow.apache.org Airflow Summit: airflowsummit.org Astronomer: astronomer.io Astronomer Registry (Easy to search for official and community Providers): registry.astronomer.io REST API: airflow.apache.org Contributing: github.com Airflow Love

We're back with another GeekOut episode. Richard Campbell, a developer and podcaster who also dives deep into science and tech topics, is back for our third GeekOut episode. This time around, we're diving into renewable energy, energy storage, and just what do we do to keep the lights on with our frying our beloved Earth? Links from the show Richard on Twitter: @richcampbell IEA report 2021: iea.org Flywheel storage: blogspot.com Crane storage: eni.com Pumped hydro storage: eurekalert.org Tesla battery utility-scale: tesla.com The US’s largest solar farm is canceled because Nevada locals don’t want to look at it: electrek.co DEVintersection conference (run by Richard): devintersection.com .NET Rocks Podcast (Richard's a cohost, many geekout episodes): dotnetrocks.com Prior Geekouts on Talk Python #276: Geekout: Life in the solar system and beyond: talkpython.fm #253: Moon base geekout: talkpython.fm Watch YouTube live stream edition: youtube.com Episode transcripts: talkpython.fm Stay in touch with us Su

ORMs are one of the main tools to put first-class data access in the hands on non-SQL-loving developers and even for those who do love SQL, making them way more productive. When you hear about ORMs in Python, we often hear about either SQLAlchemy and Django ORM. And we should, they are great. But there are newer ORMs that take better advantage of modern Python. On this episode, you'll meet Daniel Townsend. He's the creator of Piccilo ORM. A great ORM that is async first, but also has synchronous APIs. It has a super clean query syntax. And, it's easy to learn. Links from the show Dan on Twitter: danieltownsend Piccolo ORM: piccolo-orm.com Piccolo on GitHub: github.com Little Bobby Tables joke: bobby-tables.coml Syntax example: github.com Piccolo Admin: piccolo-orm.readthedocs.io Python's Pathlib: docs.python.org Watch YouTube live stream edition: youtube.com Episode transcripts: talkpython.fm Stay in touch with us Subscribe on YouTube (for live streams): youtube.com Follow Talk Python on Twitter: @tal

You've heard me talk to wide cast of people building amazing things with Python. Some of them are building bio-reactors to remove carbon from the air with AI and Python. Others are optimizing aerodynamics and race strategy at the highest levels of automobile racing. This episode is different. Rather than seeing how far we can push Python to the edges of technology, we are diving in to the tiny Python applications that might never be released publicly and yet can transform our day to day lives with simple automation on an individual level. We have 4 great guests with us here today: Rivers Cuomo, Jay Miller, Kim van Wyk, and Rusti Gregory. They will each share a couple of apps and the underlying packages they used to build them. I know this will be a super motivational episode for many of you. I hope that after listening, you'll transform something tedious and error-prone in your live to an instantaneous button click solution with Python. Links from the show Panelists Rivers Cuomo: @RiversCuomo Jay Mi

Did you know I'm a fan of GUIs. You know, they are kind of like web pages, but they run on your computer, they have their own windows, and you can even use them offline! On this episode, we'll dive into wxPython with Mike Driscoll. He's back on the podcast to share his hard-won experience on building and distributing Python Window-based applications. Links from the show Mike on Twitter: @driscollis Creating GUI Applications with wxPython book: amazon.com PySimpleGUI: pysimplegui.readthedocs.io DearPyGui: github.com wxPython: wxpython.org wxPython Phoenix: github.com wxWidgets: wxwidgets.org wxFormBuilder: github.com wxGlade: sourceforge.net Balsamiq: balsamiq.com RoboMongo: robomongo.org Toga: beeware.org api.nasa.gov: api.nasa.gov PyInstaller: pyinstaller.org URLify app: pyinstaller.org wingware: wingware.com openpyxl: openpyxl.readthedocs.io Watch YouTube live stream edition: youtube.com Episode transcripts: talkpython.fm Stay in touch with us Subscribe on YouTube (for live streams): youtube.com Follow T

When you think about embedded programming, does it bring low-level languages and tools to mind? Maybe Embedded C or even Assembly language? Thanks to the groundbreaking work by Damien George back in 2014 to create MicroPython, Python is one of the very solid choices for building tiny programmable devices. On this episode, we welcome back Damien George from MicroPython along with Scott Shawcroft from CircuitPython and Adafruit. We'll talk about how these two frameworks are solving similar problems with slightly different philosophies. More importantly, they are working closely to bring MicroPython and CircuitPython more in sync. Links from the show Scott on Twitter: @tannewt Damien's Site: dpgeorge.net CircuitPython: circuitpython.org MicroPython: micropython.org Upstream MicroPython Versions Merged Into CircuitPython: adafruitdaily.com Boards (MicroPython): store.micropython.org Boards (CircuitPython): adafruit.com MicroPython Forums: forum.micropython.org Become a sponsor to MicroPython: github.com

Python is used to solve a large and varied set of problems. One of its core pillars is web APIs. Another one is ML and data science. Those two important pieces were brought together in an unexpected yet magically-futuristic way by Rod Senra's team working with the Gatorade Sports Science Institute. They created a patch that you wear while working out once or twice. It analyzes your perspiration. Combines with it other factors like running distance, sleep quality, and more. Then provides recommendations, using Python, about how to get more effective fitness. Links from the show Rod on Twitter: @rodsenra GX Sweat Patch: gatorade.com Work & Co.: work.co Pint package: pint.readthedocs.io unyt package: pypi.org/project/unyt Pendulum: pendulum.eustace.io MongoDB: mongodb.com python-constraint package: github.com/python-constraint PSF Developer Survey 2020: jetbrains.com Rich: github.com Textual: github.com YouTube Live Stream: youtube.com Episode transcripts: talkpython.fm Sponsors Sentry Error Monitoring

You've got your Python API or app running in a Docker container. Great! Are you ready to ship it to that hosted cluster service and head off to production? Not so fast. Have you considered how you'll manage evolving dependencies and addressing security updates over time? Not just for the base OS but for installed packages? How about your pip installed dependencies? Are you running as root? If you don't know, the answer is yes. We'll discuss these issues and many more with Itamar Turner-Trauring on this episode. Links from the show PyCon Talk: youtube.com Docker packaging articles (code TALKPYTHON to get 15% off): pythonspeed.com PSF+JetBrains 2020 Survey: jetbrains.com Give me back my monolith article: craigkerstiens.com TestContainers: github.com SpaceMacs: spacemacs.org Rust bindings for Python: github.com PyOxidizer: pyoxidizer.readthedocs.io ahocorasick_rs: Quickly search for multiple substrings at once: github.com FIL Profiler: pythonspeed.com Free ebook covering this process: pythonspeed.com Tal

Are you interested in getting ahead in data science? On this episode, you'll meet Sanyam Bhutani who studied computer science but found his education didn't prepare him for getting a data science-focused job. That's where he started his own path of self-education and advancement. Now he's working at an AI startup and ranking high on Kaggle. Links from the show Sanyam on Twitter: @bhutanisanyam1 Chai Time Data Science Podcast: youtube.com Fast AI: fast.ai How not to do Fast.ai (or any ML MOOC): medium.com First Kaggle Competition Experience: towardsdatascience.com Kaggle competitions: kaggle.com Radek Osmulski interview: youtube.com Dima Damen interview: youtube.com Andrada Olteanu interview: youtube.com H2O Wave: wave.h2o.ai Keras: keras.io Tensorflow: tensorflow.org PyTorch: pytorch.org Quick, Draw! Doodle Recognition Challenge: kaggle.com Developers, Developers, Developers song: soundcloud.com YouTube Live Stream: youtube.com Episode transcripts: talkpython.fm Sponsors Sentry Error Monitoring, Code TALKP

Have you wanted to add more interactivity and liveness to your web application? If you built it using Flask, Django, or some other Python web framework, that thought probably didn't fill you with joy. Because it might mean that you need to change a bunch of code and rewrite a significant bit of your app using a full-on front-end framework like Vue.js or React.js. In this episode, we meet Carson from Big Sky Software. He's the creator of HTMX. This front-end JavaScript library let's you leverage the server side aspects of your Python web app and add amazing interactivity but keep the logic on the server, near the database, and implemented in Python. You're going to love it. Links from the show HTMX: htmx.org HTMX on Twitter: @htmx_org Essays: htmx.org/talk Examples: htmx.org/examples Active Search: htmx.org/examples/active-search Click to edit: htmx.org/examples/click-to-edit Infinite scroll: htmx.org/examples/infinite-scroll YouTube Live Stream: youtube.com Episode transcripts: talkpython.fm Spons

In this episode, we cover how Python is being used to understand the electrical markets and grid in Australia. Our guest, Jack Simpson, has used Python to uncover a bunch of interesting developments as the country has adopted more and more solar energy. We round out the episode looking at some best practices for high-performance, large-data processing in Pandas and beyond. In addition to that, we also spend some time on how Jack used Python and Open CV (computer vision) to automate the study of massive bee colonies and behaviors. Spoiler alert: That involved gluing Wing Ding fonts to the backs of bees! Links from the show Jack Simpson: jacksimpson.co Bees, lasers, and machine learning: jacksimpson.co South Australian Gas Generator Interventions: jacksimpson.co PySAM System Advisor Model: sam.nrel.gov Visualizing the impact of Melbourne’s COVID-19 lockdown on Solar Panel Installations: jacksimpson.co Stack Overflow Python graph: insights.stackoverflow.com Episode transcripts: talkpython.fm Sponsors Squ

One of the true superpowers of Python is the libraries over at the Python Package Index. They are all just a "pip install" away. Yet, like all code that you run on your system, it is done with some degree of trust. How do we know that all of those useful packages are trustworthy? That's the topic of this episode. Bentz Tozer and John Speed Meyers are here to share their research into typosquatting on PyPI and other sneaky deeds. But we also discuss some potential solutions and fixes. Links from the show Overview topics SolarWinds: csoonline.com XCodeGhost: macrumors.com Python Package Index nukes 3,653 malicious libraries uploaded: theregister.com Dependency confusion: medium.com Typosquatting Is About More Than Typos: iqt.org Approaches to Protecting the Software Supply Chain: iqt.org A Quant’s View of Software Supply Chain Securityz: usenix.org Organizations Open Source Security Foundation (OpenSSF): openssf.org Python Security Response Team: python.org Proposed solutions and tools pypi-scan: github

Machine learning has made huge advancements in the past couple of years. We now have ML models helping doctors catch disease early. Google is using ML to suggest traffic routes in their maps app that will lesson the amount of gasoline used in the trip. And many more examples. But there is a heavy cost for training machine learning models. In this episode, you'll meet Victor Schmidt, Jonathan Wilson, and Boris Feld. They work on the CodeCarbon project together. This project offers a Python package and dashboarding tool to help you understand and minimize your ML model's environmental impact. Links from the show Guests Victor Schmidt: @vict0rsch Jonathan Wilson: haverford.edu Boris Feld: @Lothiraldan CodeCarbon project: codecarbon.io MIT "5 Cars" Article: technologyreview.com Green Future Choice Renewable Power in Portland: portlandgeneral.com YouTube Live Stream: youtube.com Sponsors Square Talk Python Training