| Under Discussion: The Performance of Python |
Victor Stinner and Julien Danjou sat down (remotely, that is) with Anne-Laure Civeyrac to talk about Python’s performance. They discuss everything from profiling, why Python is slow, and projects aimed at improving Python’s performance. Check it out!
How to Move a Django Model to Another App
In this step-by-step tutorial, you’ll learn how to move a Django model from one app to another using Django migrations. You’ll explore three different techniques and learn some helpful guidelines for choosing the best approach for your situation and needs.
Find Performance Bottlenecks in Python Code
“We should forget about small efficiencies, say about 97% of the time: premature optimization is the root of all evil. Yet we should not pass up our opportunities in that critical 3%.” - Donald Knuth. Blackfire is built to let you find the 3%. Quick install, appealing and user-friendly UI. →
Naomi Ceder to Step Down From PSF Board of Directors
Naomi Ceder will not be running for re-election to the PSF board of directors. In this blog post, she explains her reasons and thanks the community for the chance to serve.
Effortless Concurrency with Python’s
concurrent.futures module is a high-level interface for the
multiprocessing modules. You can use it to effortlessly code asynchronous tasks!
REDOWAN DELOWAR • Shared by Redowan Delowar
Remapping Python Opcodes
Take a deep dive into
.pyc files, opcodes, and disassembling code in this in-depth article about decompiling a
.pyc module with obfuscated opcodes.
Calculating Streaks in Pandas
Identifying streaks can be useful when dealing with sporting statistics, app logins, and more. Learn how to calculate streaks in Python using the pandas library and visualize them using Matplotlib.
JOSH DEVLIN • Shared by Josh Devlin
Which Characters Are Considered Whitespace by
If you’re porting some Python 2 code to Python 3, you might want to check this out.
The Python World Has Shown Increased Preference for Double Quotes
Is this the new tabs vs. spaces? Which do you prefer?
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Articles & Tutorials
Faster Machine Learning on Larger Graphs: How NumPy and Pandas Slashed Memory and Time in StellarGraph
This week, StellarGraph released a new version of its open source library for machine learning on graphs. One of the most exciting features of StellarGraph 1.0 is a new graph data structure — built using NumPy and Pandas — that results in significantly lower memory usage and faster construction times.
HUON WILSON • Shared by Tim Pitman
eval(): Evaluate Expressions Dynamically
Learn how Python’s
eval() built-in works and how to use it effectively in your programs. Additionally, you’ll learn how to minimize the security risks associated with the use of
Python WebDev Environment
Want to get your web application project started quicker? ActiveState’s WebDev build for Python has everything you need in a single, pre-built runtime environment, including Django, Flask and Bottle frameworks, as well as other useful tools and utilities. Get it for Windows, Mac and Linux. →
Systems Programming With
bash and Python 3
Python’s portability, quick development time, and batteries-included philosophy make it an excellent choice for SysAdmins looking to automate command-line tasks.
Here are six ways you can refactor code to be more concise, more Pythonic, and more performant.
RPP – Episode #8: Docker + Python for Data Science and Machine Learning
Docker is a common tool for Python developers creating and deploying applications, but what do you need to know if you want to use Docker for data science and machine learning? What are the best practices if you want to start using containers for your scientific projects? This week Christopher’s guest is Tania Allard, she is a Sr. Developer Advocate at Microsoft focusing on Machine Learning, scientific computing, research and open source.
REAL PYTHON podcast
Learn the Foundational Coding and Statistics Skills Needed to Start Your Career in Data Science
Interested in data science but not sure where to get started? Springboard’s Data Science Prep course was carefully crafted for go-getters ready for a challenge and need to brush up on a few basics before diving in to a data science bootcamp.
The 2020 Python Language Summit
“The Python Language Summit is a small gathering of Python language implementers (both the core developers of CPython and alternative Pythons), as well third-party library authors and other Python community members. The summit features short presentations followed by group discussions. In 2020, the Summit was held over two days by videoconference […]”
PYTHON SOFTWARE FOUNDATION
Improve Your Tests With the Python Mock Object Library
In this course, you’ll learn how to use the Python mock object library, unittest.mock, to create and use mock objects to improve your tests. Obstacles like complex logic and unpredictable dependencies make writing valuable tests difficult, but unittest.mock can help you overcome these obstacles.
REAL PYTHON video
Monitoring Python Flask Microservices With Prometheus
Learn how to set-up Prometheus on a Flask application to serve up metrics like requests-per-second, average response time, memory usage, and CPU usage.
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 →
pyp: Easily Run Python at the Shell! Magical, but Never Mysterious
client_python: Prometheus Instrumentation Library for Python Applications
pywasm: A WebAssembly Interpreter Written in Pure Python
tqdm: A Fast, Extensible Progress Bar for Python and CLI
machine-learning-experiments: Interactive Machine Learning Experiments
Mimesis: Fake Data Generator
GITHUB.COM/LK-GEIMFARI • Shared by Isaak
datagene: Dataset Comparison Toolbox Using Transformations and Similarity Statistics
pytest-datafixtures: Data Fixtures for Pytest Made Simple
GITHUB.COM/IDLESIGN • Shared by pythonz