Issue #613

Packaging, Air-Gapped Systems, Logging in Flask, and More

Jan. 23, 2024

Packaging, Air-Gapped Systems, Logging in Flask, and More
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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?”

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.

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 →

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.

Python 3.13.0 Alpha 3 Is Now Available

PSF Announces More Developer in Residence Roles

PSF Announces Foundation Fellow Members for Q3 2023


PEP 736: Shorthand Syntax for Keyword Arguments

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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.

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 →

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.

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.

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.

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.

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

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harlequin: The SQL IDE for Your Terminal

AnyText: Multilingual Visual Text Generation and Editing

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

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