| Create a Flask Application With Google Login |
In this step-by-step tutorial, you’ll create a Flask application that lets users sign in using their Google login. You’ll learn about OAuth 2 and OpenID Connect and also find out how to implement some code to handle user session management.
Guido on PEG Parsers for Python
“Some years ago someone asked whether it would make sense to switch Python to a PEG parser. […] I looked into it a bit and wasn’t sure what to think, so I dropped the subject. Recently I’ve learned more about PEG (Parsing Expression Grammars), and I now think it’s an interesting alternative to the home-grown parser generator that I developed 30 years ago when I started working on Python.”
GUIDO VAN ROSSUM
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Python 2.x Support in Pip Going Forward
“pip will continue to ensure that it runs on Python 2.7 after the CPython 2.7 EOL date. Support for Python 2.7 will be dropped, if bugs in Python 2.7 itself make this necessary (which is unlikely) or Python 2 usage reduces to a level where pip maintainers feel it is OK to drop support. The same approach is used to determine when to drop support for other Python versions.”
Logging in Python
Python provides a logging system as a part of its standard library, so you can quickly add logging to your application. In this course, you’ll learn why using this module is the best way to add logging to your application as well as how to get started quickly, and you will get an introduction to some of the advanced features available.
REAL PYTHON video
Understand How Celery Works by Building a Clone
“A delayed job processor (also called a background processor, asynchronous task queue, etc.) is a software system that can run code at a later time. Examples of such software includes Celery, Resque, Sidekiq, and others. In this post we will try and understand how these things work by building a clone/replica of such software.”
KOMU WAIRAGU • Shared by Komu Wairagu
Simplify Your Python Developer Environment
Three tools (pyenv, pipx, pipenv) make for smooth, isolated, reproducible Python developer and production environments.
MASON EGGER • Shared by Python Bytes FM
Exploring Best Practices for Upcoming Python 3.8 Features
“As a Python 3.8 learning exercise, I’m using the walrus operator, / notation, and f= at every opportunity and then evaluating the result for clarity.”
Using NumPy With Pandas Without Import NumPy
“Want to use NumPy without importing it? You can access all of its functionality from within pandas…”
Writing the Digits of Pi Backwards…in Python?
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Articles & Tutorials
Making Python Classes More Modular Using Mixins
“In this article I want to discuss mixins: what they are, how they work, and when they’re useful. Hopefully after reading this brief article you will be ready to experiment with this pattern yourself in your own projects.”
ALEKSEY BILOGUR • Shared by Aleksey Bilogur
Keras Learning Rate Schedules and Decay
In this tutorial, you will learn about learning rate schedules and decay using Keras. You’ll learn how to use Keras’ standard learning rate decay along with step-based, linear, and polynomial learning rate schedules.
Safely Roll Out New Features in Python With Optimizely Rollouts
Tired of code rollbacks, hotfixes, or merge conflicts? Instantly turn on or off features in production. Comes with unlimited collaborators and feature flags. Embrace safer CI/CD releases with SDKs for Python and all major platforms →
How to Use
In this step-by-step tutorial, you’ll learn how to use the NumPy arange() function, which is one of the routines for array creation based on numerical ranges. np.arange() returns arrays with evenly spaced values.
Protecting the Future of Python by Hunting Black Swans
An interview with Russell Keith-Magee about identifying potential black swan events for the Python ecosystem and how to address them for the future of the language and its community.
Writing Sustainable Python Scripts
A standalone Python script can come with a discoverable interface a documentation and some tests to keep it useful a year later.
Decoupling Database Migrations From Server Startup: Why and How
Why running migrations on application startup are a bad idea (potential database corruption & downtime) and what to do instead.
Train to a Guaranteed Machine Learning Job
1:1 personalized guidance with your own machine expert. Learn through a curated curriculum designed by hiring managers. Get career support and insider connections to jobs with online self-paced course. Get a machine learning job or your money back.
Let’s Build a Simple Interpreter: Recognizing Procedure Calls
Part 16 in Ruslan’s amazing tutorial series on building a scripting language interpreter using Python, from scratch.
Practical Production Python Scripts
A step-by-step refactoring journey from simple fizzbuzz script to a cleaned up and “production-ready” piece of code.
The Invasion of Giant Pythons Threatening Florida
Python is eating the world! Related discussion on Hacker News.
Extensive Python Testing on Travis CI
Testing open-source Python on several operating systems using Travis for continous integration.
List of Python Anti-Patterns and Worst Practices
Estimating Pi in Python
Multipage PDF to JPEG Image Conversion in Python
M. TARIK YURT
5 Common Beginner Mistakes in Python
Ranking Capitals by the Number of Starbucks Using Python and Google Maps API
Projects & Code
Pdb++: Fancy Pdb (The Python Debugger)
preper: Persian (Farsi) Preprocessing Python Module
GITHUB.COM/ALIIE62 • Shared by Ali Hosseini
pyorbs: Tool for Convenient Python Virtual Environment Management
pyon: The Pythonic Way to Use JSON
snoop: Python Debugging Library Designed for Maximum Convenience
StanfordNLP: Python NLP Library for Many Human Languages
dlint: Robust Static Analysis for Python
pygraphblas: Graph Processing With Python and GraphBLAS