| | Python Packaging, One Year Later: A Look Back at 2023 This is a follow-on post to Chris’s article from last year called Fourteen tools at least twelve too many. “Are there still fourteen tools, or are there even more? Has Python packaging improved in a year?” CHRIS WARRICK
Running Python on Air-Gapped Systems This post describes running Python code on a “soft” air-gapped system, one without direct internet access. Installing packages in a clean environment and moving them to the air-gapped machine has challenges. Read Ibrahim’s take on how he solved the problem. IBRAHIM AHMED
Elevate Your Web Development with MongoDB’s Full Stack FastAPI App Generator Get ready to elevate your web development process with the newly released Full Stack FastAPI App Generator by MongoDB, offering a simplified setup process for building modern full-stack web applications with FastAPI and MongoDB → MONGODBsponsor
Add Logging and Notification Messages to Flask Web Projects After you implement the main functionality of a web project, it’s good to understand how your users interact with your app and where they may run into errors. In this tutorial, you’ll enhance your Flask project by creating error pages and logging messages. REAL PYTHON
Python 3.13.0 Alpha 3 Is Now Available CPYTHON DEV BLOG
PSF Announces More Developer in Residence Roles PYTHON SOFTWARE FOUNDATION
PSF Announces Foundation Fellow Members for Q3 2023 PYTHON SOFTWARE FOUNDATION
Discussions PEP 736: Shorthand Syntax for Keyword Arguments PYTHON.ORG
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Articles & Tutorials Bias, Toxicity, and Truthfulness in LLMs With Python How can you measure the quality of a large language model? What tools can measure bias, toxicity, and truthfulness levels in a model using Python? This week on the show, Jodie Burchell, developer advocate for data science at JetBrains, returns to discuss techniques and tools for evaluating LLMs With Python. REAL PYTHON podcast
Postgres vs. DynamoDB: Which Database to Choose This article presents various aspects you need to consider when choosing a database for your project - querying, performance, ORMs, migrations, etc. It shows how things are approached differently for Postgres vs. DynamoDB and includes examples in Python. JAN GIACOMELLI • Shared by Jan Giacomelli
Building with Temporal Cloud Webinar Series Hear from our technical team on how we’ve built Temporal Cloud to deliver world-class latency, performance, and availability for the smallest and largest workloads. Whether you’re using Temporal Cloud or self-host, this series will be full of insights into how to optimize your Temporal Service → TEMPORALsponsor
Python App Development: In-Depth Guide for Product Owners “As with every technology stack, Python has its advantages and limitations. The key to success is to use Python at the right time and in the right place.” This guide talks about what a product owner needs to know to take on a Python project. PAVLO PYLYPENKO • Shared by Alina
HTTP Requests With Python’s urllib.request In this video course, you’ll explore how to make HTTP requests using Python’s handy built-in module, urllib.request . You’ll try out examples and go over common errors, all while learning more about HTTP requests and Python in general. REAL PYTHON course
Beware of Misleading GPU vs CPU Benchmarks Nvidia has created GPU-based replacements for NumPy and other tools and promises significant speed-ups, but the comparison may not be accurate. Read on to learn if GPU replacements for CPU-based libraries are really that much faster. ITAMAR TURNER-TRAURING
Django Migration Files: Automatic Clean-Up Your Django migrations are piling up in your repo? You want to clean them up without a hassle? Check out this new package django-migration-zero that helps make migration management a piece of cake! RONNY VEDRILLA • Shared by Sarah Boyce
Understanding NumPy’s ndarray To understand NumPy, you need to understand the ndarray type. This article starts with Python’s native lists and shows you when you need to move to NumPy’s ndarray data type. STEPHEN GRUPPETTA • Shared by Stephen Gruppetta
Type Information for Faster Python C Extensions PyPy is an alternative implementation of Python, and its C API compatibility layer has some performance issues. This article describes on-going work to improve its performance. MAX BERNSTEIN
Fastest Way to Read Excel in Python It’s not uncommon to find yourself reading Excel in Python. This article compares several ways to read Excel from Python and how they perform. HAKI BENITA
How Are Requests Processed in Flask? This article provides an in-depth walkthrough of how requests are processed in a Flask application. TESTDRIVEN.IO • Shared by Michael Herman
Projects & Code Brought to you by Real Python for Teamssponsor Online Python training created by a community of experts. Give your team the real-world Python skills they need to succeed → harlequin: The SQL IDE for Your Terminal GITHUB.COM/TCONBEER
AnyText: Multilingual Visual Text Generation and Editing GITHUB.COM/TYXSSPA
Websocket CLI Testing Interface GITHUB.COM/LEWOUDAR • Shared by Kevin Tewouda
Autometrics-py: Metrics to Debug in Production GITHUB.COM/AUTOMETRICS-DEV • Shared by Adelaide Telezhnikova
django-cte: Common Table Expressions (CTE) for Django GITHUB.COM/DIMAGI
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