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Python Bytes

Python Bytes
Author: Michael Kennedy and Brian Okken
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© Copyright 2016-2023
Description
Python Bytes is a weekly podcast hosted by Michael Kennedy and Brian Okken. The show is a short discussion on the headlines and noteworthy news in the Python, developer, and data science space.
355 Episodes
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Topics include 3.12 is out, Trouble with virtualenv caching, a tale of 3.12 update, Python Developers Survey 2022 Results, and Scientific Python Library Development Guide.
Topics include logmerger, The third and final Python 3.12 RC is out now, The Python dictionary dispatch pattern, and Visualizing the CPython Release Process.
Topics include OverflowAI, Switching to Hatch, Alpha release of the Ruff formatter, and What is wrong with TOML?
Topics include Heliclockter, Wagtail 5, Git log customization, and MiniJinja template engine.
Topics include mpire, mopup, Immortal Objects for Python, and Common Docstring Formats in Python.
Topics include Make Each Line Count, Keeping Things Simple in Python, Parsel, A Comprehensive Guide to Python Logging with Structlog, and Stamina.
Topics include Omnivore app, Djangonaut.space, Server-side hot reload, and Python in Excel.
Topics include Differentiating between writing down dependencies to use packages and for packages themselves, PythonMonkey, Quirks of Python package versioning, and bear-type.
Topics include async-timeout, PyPI Project URLs Cheatsheet, httpx-sse, and Creating a context manager in Python.
Topics include A Steering Council notice about PEP 703 (Making the Global Interpreter Lock Optional in CPython), Google's post-cookie world could turn into DRM for the internet, How ruff changed my Python programming habits, and pathlib api extended to use fsspec backends.
Topics include Cython 3.0, Reading code: An important but seldom-discussed skill, Major new version of MicroPython: v1.20.0, and Advanced Python Tips for Development.
Topics include Pydantic v2 released, Two Ways to Turbo-Charge tox, Awesome Pydantic, and CLI tools hidden in the Python standard library.
Topics include Plumbum: Shell Combinators and More, Our plan for Python 3.13, Some blogging myths, and Jupyter AI.
Topics include Pydantic roadmap, The Right Way to Run Shell Commands From Python, US: Yep, We're Buying Your Data, Including Your Embarrassing Secrets, and Pro-Tip – pytest fixtures are magic!
Topics include PythonGUIS, JupyterLab 4.0 is Here, Proposing a struct syntax for Python, and Python 3.13 Removes 20 Stdlib Modules.
Topics include pystack, Securing PyPI accounts via Two-Factor Authentication, Propan - a declarative Python MQ framework, and Makefile tricks for Python projects.
Topics include The Basics of Python Packaging in Early 2023, vecs, Introducing Grasshopper - An Open Source Python Library for Load Testing, and memocast.
Topics include Ruff PyCharm plugin, Writing Python like it's Rust, Pip 23.1 Released - Massive improvement to backtracking, and Markdown Code Runner.
Topics include Python's Missing Batteries: Essential Libraries You're Missing Out On, awesome-polars, Running Headless Selenium in Python (2023), and Gracy.
Very good podcast!
sorry, but I can't with so many yawning 😂
I get that str.strip() needs some work. However, for the time being (and to ensure backwards compatibility) surely re.sub() is a solid choice for some of the use cases you guys are discussed no?
can't believe it
Author: Jukka Lehtosalo Sponsor: Guido van Rossum Status: Accepted Version: 3.8 PEP 484 defines the type Dict[K, V] for uniform dictionaries, where each value has the same type, and arbitrary key values are supported. It doesn't properly support the common pattern where the type of a dictionary value depends on the string value of the key. Core idea: Consider creating a type to validate an arbitrary JSON document with a fixed schema Proposed syntax: https://icetutor.com
I think the methodology for the calculation of language popularity is specifically under representative of both R and python. if you check out trends for dplyr (R) or pandas (python) packages for data manipulation, both dwarf the overall language specific searches. I wonder if that bias also partially led to the declining interest in Ruby on Rails.
fgr Dr rhh
Thanks for the kubernetes example, and overall good episode
ypf
As usual, perfect!
I think you missed to highlight all the nice work of realphlython and your podcasts, these are key stuffs for Python in 2018!
The jokes are good but let brian do it. 😂
Congrats Python Bytes. This episode was really great 😎
Joel Grus talk can be found here: https://youtu.be/7jiPeIFXb6U
víbora means in Spanish: snake. umm, just thinking about Phyton
It's intetesting the title is flask but you guys spoke more about Django? kidding? hahaha please dont mess with us《Mico framework fans Thanks
nice, another super good Python postcast