Coroutines (practical)

https://tacaswell.github.io/coroutines-i.html

What is closure in Python
We will learn about nested function, closure and nonlocal

https://medium.com/@SergiAlfonso/what-is-closure-in-python-7eec3e663b4b

Hey, there 👋
I've started Telegram channel about POSIX, Git, Ci, Ansible, Terraform and everything related to the administrative tasks. And if this channel is more personal bookmarks on a topic, then Tux will be a real small channel. With regular updates and descriptions.

Subscribe 😊!
https://t.me/tuxua
#DevOps #linux #ci_cd

Never Use Print() To Debug Your Python Code
Why I stopped using print() statements for debugging and why you should too

https://towardsdatascience.com/introducing-icecream-never-use-print-to-debug-your-python-code-again-d8f2e5719f8a

How to Structure a Data Science Project for Readability and Transparency
And How to Create One in One Line of Code
Motivation
It is important to structure your data science project based on a certain standard so that your teammates can easily maintain and modify your project.

https://towardsdatascience.com/how-to-structure-a-data-science-project-for-readability-and-transparency-360c6716800

Apache Kafka в цепочке поставок в пищепроме и ритейле

Цепочка поставок в пищевой промышленности и ритейле — это сложная, медленная и ненадёжная система. В этой статье мы рассмотрим развёртывание Apache Kafka для обработки данных в реальном времени в таких сферах, как производство, логистика, розничная торговля, доставка, рестораны и другие части бизнеса. Это будут примеры из настоящих компаний: Walmart, Albertsons, Instacart, Domino’s Pizza, Migros и т. д.
Читать дальше

Читать: https://habr.com/ru/post/689460/?utm_campaign=689460

Awesome Software and Architectural Design Patterns

A curated list of software and architecture related design patterns.

https://github.com/DovAmir/awesome-design-patterns

My favorite Github project template for data science projects

TLDR:
In this story, I am sharing a git project structure that I often use as a starting point for data science projects and talk about few packages that could help organize code. I also implement a basic version of a CI pipeline that allows to automatize code quality analysis.

https://medium.com/@kaislar17/mlops-my-favorite-github-project-template-for-data-science-projects-2edda25099cd

Learning Python and SQL is one of the best ways to land a job in Data Science.
🧵

https://twitter.com/chrisstaud/status/1584430472876040192?

A Gentle Introduction to Graph Neural Networks

Neural networks have been adapted to leverage the structure and properties of graphs. We explore the components needed for building a graph neural network - and motivate the design choices behind them.

https://distill.pub/2021/gnn-intro/

10 MLOps Projects Ideas for Beginners to Practice in 2022

Collection of interesting MLOps projects ideas for practice to kickstart your journey towards becoming an MLOps engineer in 2021.

https://www.projectpro.io/article/mlops-projects-ideas/486

Data Classes
This module provides a decorator and functions for automatically adding generated special methods such as init() and repr() to user-defined classes. It was originally described in PEP 557.
- https://docs.python.org/3/library/dataclasses.html

Support for enumerations

- is a set of symbolic names (members) bound to unique values
- can be iterated over to return its members in definition order
- uses call syntax to return members by value
- uses index syntax to return members by name
- https://docs.python.org/3/library/enum.html

Efficient Python Tricks and Tools for Data Scientists

The goal of this book is to spread the awareness of efficient ways to do Python. They include:

- efficient methods and libraries to work with iterator, dictionary, function, and class
- efficient methods to work with popular data science libraries such as pandas and NumPy
- efficient tools to incorporate in a data science project
- efficient tools to incorporate in any project
- efficient tools to work with Jupyter Notebook.

#book #python #datascience
https://khuyentran1401.github.io/Efficient_Python_tricks_and_tools_for_data_scientists/README.html

Humanities Data Analysis: Case Studies with Python is a practical guide to data-intensive humanities research using the Python programming language.

The book, written by Folgert Karsdorp, Mike Kestemont and Allen Riddell, was originally published with Princeton University Press in 2021 (for a printed version of the book, see the publisher’s website), and is now available as an Open Access interactive Juptyer Book.

#book #python #datascience
https://www.humanitiesdataanalysis.org/index.html

Create a Maintainable Data Pipeline with Prefect and DVC

Make Your Pipelines Easier to Support and Maintain

#python #pipelline
https://towardsdatascience.com/create-a-maintainable-data-pipeline-with-prefect-and-dvc-1d691ea5bcea

Goodbye os.path
15 Pathlib Tricks to Quickly Master The File System in Python

Pathlib came out in Python 3.4 as a replacement for the nightmare that was os.path. It also marked an important milestone for Python language on the whole: they finally turned every single thing into an object (even nothing).

#python #tricks
https://towardsdatascience.com/goodbye-os-path-15-pathlib-tricks-to-quickly-master-the-file-system-in-python-881213ca7c21

Wolverine Gives Your Python Scripts The Ability To Self-Heal | Hackaday

Wolverine is a wrapper that runs the buggy script, captures any error messages, then sends those errors to GPT-4 to ask it what it thinks went wrong with the code.

#python #ai #gpt
https://hackaday.com/2023/04/09/wolverine-gives-your-python-scripts-the-ability-to-self-heal/

A Python implementation of Larry's famous PageRank algorithm.

From late 90-s.
#python
https://github.com/ashkonf/PageRank

A Gentle Introduction To Rust

The aim of this tutorial is to take you to a place where you can read and write enough Rust to fully appreciate the excellent learning resources available online, in particular The Book. It's an opportunity to try before you buy, and get enough feeling for the power of the language to want to go deeper.

#rust #book
https://stevedonovan.github.io/rust-gentle-intro/readme.html