Talk Python To Me - Python Conversations For Passionate Developers

For all the amazing powers of Python, deploying packaged apps that leverage native OS-level capabilities isn't one of them. But it can be done and we have a great guest, Rhet Turnbull, here to tell us how he built his distributable macOS app Textinator that uses macOS's native vision recognition framework through Python. Links from the show Rhet Turnbull on Twitter: @RhetTurnbull Textinator app: github.com Homebrew Python Is Not For You: justinmayer.com asdf: asdf-vm.com Space Force: spaceforce.com TextSniper app: textsniper.app Apple's Natural Language ML: developer.apple.com Apple's Vision ML: developer.apple.com py2app: py2app.readthedocs.io py2exe: pypi.org pyinstaller: pyinstaller.org RUMPS: github.com Michael's RUMPS app - URLify: github.com Home Brew: brew.sh pipx: github.com Gooey: github.com PLS CLI: github.com textX: pypi.org Join Space Force: spaceforce.com Beeware: beeware.org Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe t

When you think data exploration using Python, Jupyter notebooks likely come to mind. They are excellent for those of us who gravitate towards Python. But what about your everyday power user? Think of that person who is really good at Excel but has never written a line of code? They can still harness the power of modern Python using a cool application called Superset. This open source Python-based web app is all about connecting to live data and creating charts and dashboards based on it using only UI tools. It's super popular too with almost 50,000 GitHub stars. Its creator, Max Beauchemin is here to introduce it to us all. Links from the show Max on Twitter: @mistercrunch Superset: superset.apache.org 60 notebook environments: talkpython.fm SQL Fluff linter: sqlfluff.com DB API PEP: peps.python.org Preset Company: preset.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 Twitter:

We are on the edge of a major jump in Python performance. With the work done by the Faster CPython team and Python 3.11 due out in around a month, your existing Python code might see an increase of well over 25% in speed with no changes. One of the main reasons is its new specializing, adaptive interpreter. This episode is about that new feature and a great tool called Specialist which lets you visualize how Python is speeding up your code and where it can't unless you make minor changes. Its creator, Brandt Bucher is here to tell us all about. Links from the show Brandt Bucher: github.com Specialist package: github.com Faster CPython: github.com Faster CPython Ideas: github.com pymtl package: pypi.org PeachPy: 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 Twitter: @talkpython Follow Michael on Twitter: @mkennedy Sponsors Microsoft RedHat Talk Python Training

Terminals seem like the very lowest common denominator for software platforms. They have to work over SSH. They only show text. You can't do much with them. Or can you? Will McGugan and team have been building Textual (based on Rich) which looks more like an animated web app than a terminal app. And he has learned a bunch of lessons trying to maximize terminal based apps. He's here to share his 7 lessons he's learned while building a modern TUI (text user interface) framework. Links from the show Will McGugan: @willmcgugan 7 things I've learned building a modern TUI framework post: textualize.io Prior Talk Python Episode: talkpython.fm Textualize: textualize.io Kitty terminal: sw.kovidgoyal.net Pydantic Immutability: pydantic-docs.helpmanual.io Monodraw: monodraw.helftone.com Async's lru cache: github.com Rich CLI: github.com Nerd Fonts: nerdfonts.com Oh My Posh: ohmyposh.dev Python Object Allocator ASCII Art: github.com Balsamiq wireframes: balsamiq.com Watch this episode on YouTube: youtube.com Episode tr

Do you write web apps in Django? The framework has come a long way lately with versions 3 and 4 adopting many of the modern Python capabilities (async, for example). But there are so many other libraries and apps that you can use to do more with less code in plugin new functionality. I'm happy to have Christopher Trudeau here on talk Python to take us through his 17 favorite libraries you should be using in Django. Links from the show Chris on Twitter: @cltrudeau Django: Getting Started Course (by Chris): training.talkpython.fm Foundational libraries: coverage: coverage.readthedocs.io Sphinx: sphinx-doc.org Sphinx-rtd-theme: github.com pudb: documen.tician.de tox: tox.wiki Pillow (sort of Django, needed by ImageField): github.com Django libraries: Django Ninja: django-ninja.rest-framework.com DRF: django-rest-framework.org Grappelli: github.com django-import-export: github.com Django Debug Toolbar: github.com Django local flavor: github.com Django admin-extra-buttons: github.com django-awl: github.com dj

Have you heard of Flutter? It's a modern and polished UI framework to write mobile apps, desktop apps, and even web apps. While interesting, you may have kept your distance because Flutter is a Dart language-based framework. But with the project we're covering today, Flet, many Flutter UIs can now be written in pure Python. Flet is a very exciting development in the GUI space for Python devs. And we have the creator, Feodor Fitsner, here to take us through it. Links from the show Feodor on GitHub: github.com Flet: flet.dev Flutter: flutter.dev Dart: dart.dev Flet Tutorials: flet.dev It's All Widgets Showcase: itsallwidgets.com Roadmap: flet.dev pglet: pglet.io Flutter Flow Designer: flutterflow.io Fluent UI for Flutter Showcase App: bdlukaa.github.io macOS UI: pub.dev Flet Mobile Strategy: flet.dev Michael's flutter doctor output: flutter-doctor.png Pyscript: pyscript.net Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subscribe to us on YouTube:

PyPI has been in the news for a bunch of reasons lately. Many of them good. But also, some with a bit of drama or mixed reactions. On this episode, we have Dustin Ingram, one of the PyPI maintainers and one of the directors of the PSF, here to discuss the whole 2FA story, securing the supply chain, and plenty more related topics. This is another important episode that people deeply committed to the Python space will want to hear. Links from the show Dustin on Twitter: @di_codes Hardware key giveaway: pypi.org OpenSSF funds PyPI: openssf.org James Bennet's take: b-list.org Atomicwrites (left-pad on PyPI): reddit.com 2FA PyPI Dashboard: datadoghq.com github 2FA - all users that contribute code by end of 2023: github.blog GPG - not the holy grail: caremad.io Sigstore for Python: pypi.org pip-audit: pypi.org PEP 691: peps.python.org PEP 694: peps.python.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

Pydantic has become a core building block for many Python projects. After 5 years, it's time for a remake. With version 2, the plan is to rebuild the internals (with benchmarks already showing a 17x performance improvement) and clean up the API. Sounds great, but what does that mean for us? Samuel Colvin, the creator of Pydantic, is here to share his plan for Pydantic v2. Links from the show Samuel on Twitter: @samuel_colvin Pydantic v2 plan: pydantic-docs.helpmanual.io Py03: pyo3.rs FastAPI: fastapi.tiangolo.com Beanie: github.com SQLModel: sqlmodel.tiangolo.com Speedate: docs.rs Pytests running on Pydantic in browser: githubproxy.samuelcolvin.workers.dev JSON to Pydantic tool: jsontopydantic.com Pyscript: pyscript.net Michael's Pyscript + WebAssembly: Python Web Apps 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 Twitter: @talkpython Follow Michael on Twitter: @mke

Every year, the Python core developers and a few other key players in the Python ecosystem meet to discuss the pressing issues and important advancements at an event called the Python Language Summit. While Python is a community known for openness, this meeting is typically held behind closed doors mostly for efficiency's sake. On this episode, we'll give you a look behind that door. We have Alex Waygood here on this episode to break it down for us and give a look inside the summit. Links from the show Alex on Twitter: @alexwaygood 2022 Python Language Summit: pyfound.blogspot.com Individual Talks Python without the GIL: pyfound.blogspot.com Reaching a per-interpreter GIL: pyfound.blogspot.com The "Faster CPython" project: 3.12 and beyond: pyfound.blogspot.com WebAssembly: Python in the browser and beyond: pyfound.blogspot.com F-strings in the grammar: pyfound.blogspot.com Cinder Async Optimizations: pyfound.blogspot.com The issue and PR backlog: pyfound.blogspot.com The path forward for immortal objects:

Every year, the PSF and JetBrains team up to do a Python community survey. The most recent one was Fall of 2021. For this episode, I've gathered a great group of Python enthusiasts to discuss the results. I think you'll really enjoy the group discussion on this episode. Links from the show Guests Gina Häußge: @foosel Emily Morehouse-Valcarcel: @emilyemorehouse Tonya Sims: @TonyaSims Brett Cannon: @brettsky Jay Miller: @kjaymiller Paul Everitt: @paulweveritt 2021 Survey Results: jetbrains.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 Twitter: @talkpython Follow Michael on Twitter: @mkennedy Sponsors Sentry Error Monitoring, Code TALKPYTHON RedHat AssemblyAI Talk Python Training

Deploying and managing your application after you create it can be a big challenge. Cloud platforms such as Azure have literally hundreds of services. Which ones should you choose? How do you link them together? In this episode, Anthony Shaw and Shayne Boyer share a new CLI tool and template they've created for jump starting you use of modern Python apps and deploying them to Azure. We're talking FastAPI, Beanie and MongoDB, async and await, Bicep DevOps, automated CI/CD pipelines and more. Plus we catch up on other Python work happening that Anthony is involved with. If you're interested in deploying or structuring modern Python apps, you'll find some interesting take aways from our conversation. Links from the show Anthony on Twitter: @anthonypjshaw Shayne Boyer: @spboyer Azure azd CLI tools: aka.ms Beanie ODM: github.io Pydantic: helpmanual.io Give me back my monolith article: craigkerstiens.com Python creator Guido van Rossum joins Microsoft: techcrunch.com Making Python Faster with Guido and Mark epis

Often when we learn about or work with Math, it's done so in a very detached style. You might learn the rules and techniques for differentiation, for example. But how often do you get to apply them to meaningful and interesting problems? In this episode, we have Vince Knight and Geraint Palmer on to discuss solving a wide variety of applied and approachable math problems using Python. Whether you're deeply into math or not so much, I think there is a lot to enjoy from this episode. Links from the show Applied Mathematics with Open-Source Software: taylorfrancis.com Book source files: ithub.com Vince on Twitter: @drvinceknight Geraint on Twitter: @geraintpalmer Traces Package: traces.readthedocs.io A Beautiful Mind: wikipedia.org Nashpy: github.com e: The Story of a Number: amazon.com SymPy episode: talkpython.fm 8451: 8451.com Stack Overflow Trends: stackoverflow.com PYCON UK 2017: Python for conducting operational research in healthcare: youtube.com Ciw package: github.com Python ternary: github.com Micha

I'm sure you're familiar with package managers for your OS even if you don't use them. On macOS we have Homebrew, Chocolatey on Windows, and apt, yum, and others on Linux. But if you want to install Python applications, you typically have to fallback to managing them with pip. Maybe you install them for your account with the --user flag. But with pipx you get a clean, isolated install for every Python application that you use. And if you distribute Python apps, pipx is a definitely worth considering as a channel. Links from the show Chad Smith: @cs01_software Pipx: github.com Entry Points: dev.to Python Packaging Dashboard: chadsmith.dev MKDocStrings: mkdocstrings.github.io gdbgui: github.com termpair: github.com httpie: httpie.io pls (ls-replacement): dhruvkb.github.io Glances: nicolargo.github.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 Twitter: @talkpython Follow Michael on T

You may have heard of the Bloomberg terminal. It's expensive software that can monitor and analyze real-time financial market data and place trades on the electronic trading platform. But have you heard of OpenBB? It's similar software for real-time and long term analysis for finance and investing. The difference is it's open source and built entirely with Python and gives you access to analyze a massive amount of real-time and historical data using the full Python data science stack. On this episode, we have one of the cofounders, James Maslek here to give us a look inside this cool piece of Python-based software. Links from the show James Maslek: linkedin.com OpenBB: openbb.co OpenBB Feature Gallery: openbb.co $8.5M seed funding announcement: openbb.co/blog How to get rich talk by Naval (less money-focused than the title implies): 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 Pyth

Python is undergoing a performance renaissance. We already have Python 3.11 20-40% faster than even Python 3.10. On this episode, we'll dive into a new proposal to make Python even more efficient using lazy imports laid out in PEP 690. We have all three folks involved on the episode: Carl Meyer, Germán Méndez Bravo, and Barry Warsaw. Are you ready to get into making Python faster still? Let's dive in. Links from the show Guests Barry Warsaw: @pumpichank Germán Méndez Bravo: @germbravo Carl Meyer: @carljm PEP 690: peps.python.org PEP 690 Discussion: discuss.python.org Cinder project: github.com Python Lazy Imports With Cinder on the Meta blog: developers.facebook.com Python performance renaissance: #339: Making Python Faster: talkpython.fm Performance benchmarks for Python 3.11 are amazing: phoronix.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 Twitter: @talkpython Follow Michael

How do you test whether your web sites are working well? Unit tests are great. But for web apps, the number of pieces that have to click together "just so" are many. You have databases, server code (such as a Flask app), server templates (Jinja for example), CSS, Javascript, and even deployment topologies (think nginx + uvicorn). Unit tests won't cover all of that integration. But Playwright does. Playwright is a modern, Pythonic take on testing webs apps using code driving a browser core to interact with web apps the way real users and API clients do. I think you'll find a lot to like there. And we have Pandy Knight from Automation Panda here to break it down for us. Links from the show Pandy's Twitter: @AutomationPanda Pandy's blog: automationpanda.com Playwright: playwright.dev Pandy's Playwright tutorial: github.com pytest: pytest.org applitools: applitools.com Screenplay package: pypi.org/project/screenplay Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch

Despite Python being overwhelmingly popular and positive, there are major areas of computing where Python is not present. Most notably on mobile and on the frontend side of the web. PyScript, a new project launched by Fabio Pliger from Anaconda, just might change that. It was made public and announced at PyCon just two weeks ago by Peter Wang and now has over 10,000 GitHub stars. But what is hype vs. reality vs. projected hopes and dreams? We're going to find out on this episode. Fabio is here to tell us all about his new project. Links from the show Fabio on Twitter: @b_smoke PyScript: pyscript.net Birth and Death of Javascript: destroyallsoftware.com Power On: The Story of Xbox: xbox.com PyScript source: github.com JupyterLite: jupyterlite.readthedocs.io Compiling CPython for WebAssembly: python.org Space WebGL Demo: pyscript.net/examples Antigravity Demo: pyscript.net/examples D3 Demo: pyscript.net/examples Most examples: pyscript.net/examples Michael's pyscript PWA YouTube video: youtube.com Watch thi

Does your app have a database? Does that database play an important role in how the app operations and users perceive its quality? Most of you probably said yes to the first, and definitely to the second. But what if your DB isn't doing as well as it should? How would you know? And once you know, what do you do about it? On this episode, we're joined by Michael Christofides, co-creator of pgMustard, to discuss and explore the EXPLAIN command for Postgres and other databases as well as all the recommendations you might dig into as a result of understanding exactly what's happening with you queries. Links from the show Michael Christofides: @michristofides Datagrip: jetbrains.com pgMustard: pgmustard.com pgMustard example 1: app.pgmustard.com pgMustard example 2: app.pgmustard.com pgMustard example 3: app.pgmustard.com Arctype: arctype.com Postico: eggerapps.at/postico Laetitia Avrot Secrets of 'psql'— Video: youtube.com Beekeeper Studio: beekeeperstudio.io DBeaver: dbeaver.io SQLite Browser: sqlitebrowser

How much time do you spend solving negative engineering problems? And can a framework solve them for you? Think of negative engineering as things you do to avoid bad outcomes in software. At the lowest level, this can be writing good error handling with try / except. But it's broader than that: logging, observability (like Sentry tools), retries, failover (as in what you might get from Kubernetes), and so on. We have a great chat with Chris White about Prefect, a tool for data engineers and data scientists meaning to solve many of these problems automatically. But it's a conversation applicable to a broader software development community as well. Links from the show Chris White: @markov_gainz Prefect: prefect.io Fermat's Enigma Book (mentioned by Michael): amazon.com Prefect Docs (2.0): orion-docs.prefect.io Prefect source code: github.com A Brief History of Dataflow Automation: prefect.io/blog Watch this episode on YouTube: youtube.com Episode transcripts: talkpython.fm --- Stay in touch with us --- Subsc

We're all familiar with the data science tools like numpy, pandas, and others. These are numerical tools working with floating point numbers, often to represent real-world systems. But what if you exactly specify the equations, symbolically like many of us did back in Calculus and Differential Equations courses? With SymPy, you can do exactly that. Create equations, integrate, differentiate, and solve them. Then you can convert those solutions into Python (or even C++ and Fortran code). We're here with two of the core maintainer: Ondřej Čertík and Aaron Meurer to learn all about SymPy. Links from the show Ondrej Certik: @OndrejCertik Aaron Meurer: @asmeurer SymPy: sympy.org SymPy Docs: docs.sympy.org/dev Tutorials: docs.sympy.org The SymPy/HackerRank DMCA Incident: asmeurer.com SymEngine: github.com SymPy Gamma: gamma.sympy.org Sovled derivative problem - wait for derivative steps to appear: gamma.sympy.org Github Takedown Repo: github.com e: The Story of a Number book: amazon.com Watch this episode on YouT