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Python Integers Deep Dive, Friendly Tracebacks, Property-Based Testing, and More

#459 – FEBRUARY 9, 2021 VIEW IN BROWSER
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How Python Integers Work
Python’s integer datatype is pretty different from most other languages because they allow arbitrary precision. Learn how integers work under the hood in this in-depth article.
VICTOR

Python’s Tug of War Between Beginner-Friendly Features and Support for Advanced Users
Python has made some big improvements to tracebacks in recent versions. See how tracebacks have evolved over the last couple of major releases and where there’s still some work left to be done. Check out the discussion on Hacker News.
ANDRÉ ROBERGE

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Implementing C++ Virtual Functions in Cython
Learn how one team created Python bindings for a C++ library by implementing virtual functions in Cython. This article is a follow-up to an article we featured last year.
JUAN DIEGO CABALLERO • Shared by JDC

Property-Based Testing With hypothesis, and Associated Use Cases
Testing software is hard. Property-based testing can help you create more effective tests. Learn how to do property-based testing with the hypothesis framework by looking at some real-world use cases.
YING WANG

Python Steering Council Accepts PEP 634
Pattern matching, which adds a kind of switch-case statement to Python, has been accepted.
PYTHON.ORG

Managing Python Dependencies With Pip and Virtualenv
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Discussions


Inline Caching in Python Is a Success
“In 3.9, access to builtins and globals had sped-up considerably. In 3.10, regular attribute access and access to __slots__ are also faster. Most everyday Python programs will benefit. This is a huge win.”
RAYMOND HETTINGER


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Articles & Tutorials


Homebrew Python Is Not For You
Installing Python on macOS with Homebrew is pretty easy, but it comes with some quirks that might not make it the best choice for your development environment. Learn why you might not want to install Python this way and how to fix some common issues you might encounter with Homebrew.
JUSTIN MAYER opinion

C for Python Developers and Data Visualization With Dash
Are you interested in building interactive dashboards with Python? How about a project that takes a flat data file all the way to a web-hosted interactive dashboard? This week on the show, David Amos is back, and he’s brought another batch of PyCoder’s Weekly articles and projects.
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Performance is a Feature, Test it as Such
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All Pythons Are Slow, but Some Are Faster Than Others
Python is not the fastest language around, so any performance boost helps, especially if you’re running at scale. It turns out that depending where you install Python from, its performance can vary quite a bit: choosing the wrong version of Python can cut your speed by 10-20%.
ITAMAR TURNER-TRAURING

How to Speed Up Scikit-Learn Model Training
Sometimes scikit-learn models can take a long time to train. In this article, you’ll explore three approaches to optimizing the model training process.
MICHAEL GALARNYK • Shared by Michael Galarnyk

Python Inner Functions: What Are They Good For?
Learn what inner functions are in Python, how to define them, and what their main use cases are.
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Get Started with Distributed Tracing in Python and Django Using OpenTelemetry
Learn how to get instrumented with OpenTelemetry in under 10 minutes, common distributed tracing use cases, and why tracing is the foundation for observability.
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How to Build a Discord Bot in Python on Ubuntu 20.04
Learn how to build a Discord bot and host it on the DigitalOcean platform.
MASON EGGER • Shared by Mason Egger

Qt Designer and Python: Build Your GUI Applications Faster
Learn how to use Qt Designer to create GUIs from your windows and dialogs and use them in your Python applications.
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Projects & Code


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watchpoints: An Easy to Use Watchpoints Equivalent Library for Python
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PipeLayer: Python Library for Creating Pipelines
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📆🐍 Upcoming Python Events


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Older messages

pandas Memory Explosions, Python Performance, a Case Against OOP, and More

Tuesday, February 2, 2021

Finding and Fixing an Unexpected Memory Explosion in Pandas #458 – FEBRUARY 2, 2021 VIEW IN BROWSER The PyCoder's Weekly Logo Finding and Fixing an Unexpected Memory Explosion in Pandas Storing

Automating Excel, Tracing the Python GIL, Python for Non-Developers, and More

Tuesday, January 19, 2021

Automating Excel File Creation and Distribution With Pandas And Outlook #456 – JANUARY 19, 2021 VIEW IN BROWSER The PyCoder's Weekly Logo Automating Excel File Creation and Distribution With Pandas

Pythonic Exercises, FastAPI App Structure, Data Visualization With Dash, and More

Tuesday, January 12, 2021

Advent of Code 2020 "Pytudes" #455 – JANUARY 12, 2021 VIEW IN BROWSER The PyCoder's Weekly Logo Advent of Code 2020 “Pytudes” Google researcher Peter Norvig goes through a suite of short

Ditching Excel for Python, How Python Attributes Work, IP Addresses in Python, and More

Tuesday, January 5, 2021

Ditching Excel for Python: Lessons Learned From a Legacy Industry #454 – JANUARY 5, 2021 VIEW IN BROWSER The PyCoder's Weekly Logo Ditching Excel for Python: Lessons Learned From a Legacy Industry

10 Million Jupyter Notebooks, Python on GPUs, Unravelling Boolean Operators, and More

Tuesday, December 29, 2020

Accelerating Python on GPUs With `nvc++` and Cython #453 – DECEMBER 29, 2020 VIEW IN BROWSER The PyCoder's Weekly Logo Accelerating Python on GPUs With nvc++ and Cython Python on GPUs has become a

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