Python news wrap-up for October 2022
Python news wrap-up for October 2022
Python 3.11, Anaconda Distribution 2022.10, JupyterCon 2023, and more!
Hello Grokking Python readers, and happy Thursday! Without further ado, let's get started.
Python 3.11 is out!
This is one of the most exciting Python releases in recent memory. Python 3.11 introduces some new features that make it even easier to create robust, reliable applications. Here are a few of the improvements you'll find in Python 3.11:
Better performance: Python 3.11 is significantly faster than Python 3.10, by at least 10-60%. On average, it's 25% faster thanks to improved startup times and communication with C.
Improved error handling: Python 3.11's error messages now pinpoint the specific location of the error in tracebacks! This makes it much easier to find and fix bugs in your code.
TOML support: The tomllib module was added to the Python Standard Library in Python 3.11! TOML (Tom's Obvious Minimal Language) is a popular configuration file format that has been growing in popularity and is the format of choice for Python packaging.
You can check out the PEPs for some of the major new features and changes below:
General changes
PEP 657 – Include Fine-Grained Error Locations in Tracebacks
PEP 654 – Exception Groups and except*
PEP 680 – tomllib: Support for Parsing TOML in the Standard Library
Typing and typing language changes
PEP 646 – Variadic Generics
PEP 655 – Marking individual TypedDict items as required or potentially-missing
PEP 673 – Self Type
PEP 675 – Arbitrary Literal String Type
PEP 681 – Data Class Transforms
Anaconda Distribution 2022.10 released
Anaconda is the leading Python distribution and data science platform in Python. It's used by data scientists, engineers, and researchers to power some of the largest Python deployments in the world.
The latest release of Anaconda Distribution, 2022.10, introduces some exciting new features.
Here are some of the highlights:
Conda has been updated to v22.9.0
Anaconda Navigator has been updated to v2.3.1
The 2022.10 installer uses python-3.9
First release to provide a python-3.10 variant for anaconda metapackages
This is the last release that will provide a python-3.7 variant for anaconda metapackages
Qt support for macOS M1 (osx-arm64), enabling full use of GUI applications like Anaconda Navigator and Spyder
If you want to learn more about the new features and performance improvements in Anaconda Distribution 2022.10, head on over to the official release notes.
Jupyter announces dates and location for JupyterCon 2023
JupyterCon 2023 will be held May 10 to 12 (Thursday to Friday) in, Paris, France, at the largest science museum in Europe, the Cité des Sciences et de l’Industrie.
JupyterCon is an annual conference for the Jupyter community, bringing together users and developers of the project's open-source tools from around the world. The conference provides a forum for networking, collaboration, and knowledge sharing on all things Jupyter. JupyterCon celebrates the distributed nature of their community by enhancing year-long remote collaborations with in-person interactions over the span of just a few days. At JupyterCon, attendees will have plenty of chances to learn from each other and gain new professional skills through tutorials, talks, social events, and more.
If you're a fan of Jupyter, now is a good time to sign up for those early email updates on conference planning and news.
New Python course now available on Educative
As the final note for today, here's a short and sweet new course: Applying Hugging Face Machine Learning Pipelines in Python.
You may have heard of Hugging Face before. They're a company (and community) dedicated to democratizing artificial intelligence resources and tools through open source and open science. Hugging Face provides a platform with thousands of machine learning models and is used at companies like Google, Microsoft, Meta, and more!
This course is designed for anyone who wants to use the latest ML models, particularly NLP and computer vision models, for inference. It's perfect for a broad range of users, including industry engineers, software developers, data scientists, and machine learning researchers. You can use it to perform direct inference or as part of another machine learning pipeline.
The goal of this course is to provide you with:
A familiarity with Hugging Face and their library of machine-learning models
A working knowledge of Hugging Face’s pipeline APIs and their applications
The ability to apply Hugging Face models to generate and read text using natural language processing
The ability to apply Hugging Face models to computer vision tasks
Hands-on experience implementing Hugging Face models using Python and PyTorch
So, if you're looking to familiarize yourself with the popular Hugging Face platform, then this course is a great introduction!
That's all for this month! We hope you have a great autumn and stay tuned in for more exciting news in the Python world.
As always, happy learning!