Best of PythonMarch 2024

  1. 1
    Article
    Avatar of lobstersLobsters·2y

    I'm a programmer and I'm stupid

    A programmer shares their experience of feeling limited in their mental capacity and discusses their approach to programming with simple languages and minimal dependencies.

  2. 2
    Article
    Avatar of medium_jsMedium·2y

    Forget `pip install`, Use This Instead

    Install Python packages up to 100x faster with uv, a turbo-fast Python package installer and resolver written in Rust as a substitute for pip. uv is faster due to Rust, global module cache, copy-on-write and hardlinks. You can install uv using curl, pip, or brew.

  3. 3
    Video
    Avatar of beyondfireshipBeyond Fireship·2y

    How I deploy serverless containers for free

    Learn how to remove backgrounds from images using AI-powered tools, dockerize a Python web app, and deploy containers to the cloud for free or on various cloud services.

  4. 4
    Article
    Avatar of freecodecampfreeCodeCamp·2y

    How to Build an Online Banking System – Python Object-Oriented Programming Tutorial

    Learn the basics of Object-Oriented Programming (OOP) in Python by building an online banking system. Understand classes, objects, and inheritance.

  5. 5
    Article
    Avatar of communityCommunity Picks·2y

    Enhance Your Project Quality with These Top Python Libraries

    Learn about the top Python libraries that can enhance the quality of your projects, including tools for code style, linting, type checking, unit tests, and documentation.

  6. 6
    Article
    Avatar of gcgitconnected·2y

    Monte Carlo Simulation in Python: Advanced Investment Risk Analysis

    Monte Carlo Simulation is a computational algorithm that utilizes repeated random sampling to obtain numerical results. It is used in finance to model scenarios that involve uncertainty and predict the impact of risk. The simulation for stocks and cryptocurrencies involves historical data analysis, random sample generation, price simulation, and result analysis. The accuracy of the simulation depends on the assumptions made about return distributions and volatility.

  7. 7
    Article
    Avatar of kdnuggetsKDnuggets·2y

    Build An AI Application with Python in 10 Easy Steps

    Learn the 10 easy steps to build an AI application with Python, including defining objectives, collecting data, data preparation, selecting a model, training the model, evaluating model performance, iterating and optimizing, creating a web application, deploying to the cloud, and sharing the AI model.

  8. 8
    Article
    Avatar of communityCommunity Picks·2y

    microsoft/generative-ai-for-beginners: 18 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/

    Comprehensive course by Microsoft Cloud Advocates covering the fundamentals of building Generative AI applications with 18 lessons. Lessons include both theory and coding examples in Python and TypeScript.

  9. 9
    Article
    Avatar of communityCommunity Picks·2y

    Python String Methods

    This post introduces Python string methods, including basic methods for case adjustment, searching and replacing, trimming, splitting and joining, advanced manipulations, and subtly different methods for decimals, digits, and numerics. It also mentions new additions in Python 3.9 for removing prefixes and suffixes from strings.

  10. 10
    Article
    Avatar of planetpythonPlanet Python·2y

    Setting Your Python Working Environment, the Right Way

    Learn about the importance of Python virtual environments, how they work, and how to create and manage them. Discover how virtual environments help manage package dependencies and avoid conflicts.

  11. 11
    Article
    Avatar of kdnuggetsKDnuggets·2y

    5 Free University Courses to Learn Computer Science

    Learn computer science fundamentals with these free university courses. Topics covered include computer hardware, software, programming, data structures, and essential tools for software engineering.

  12. 12
    Article
    Avatar of kdnuggetsKDnuggets·2y

    Mastering Python for Data Science: Beyond the Basics

    Learn advanced Python techniques for data science, including efficient data manipulation with Pandas, high-performance computing with NumPy, and leveraging niche libraries for elevated data analysis.

  13. 13
    Article
    Avatar of communityCommunity Picks·2y

    Python Shorthand Operators

    Learn about Python shorthand operators, including one-liner if-else statements, one-liner for-loops, dictionary comprehension, lambda functions, and one-liner functions.

  14. 14
    Article
    Avatar of medium_jsMedium·2y

    Custom pre-commit hooks for safer code changes

    This post provides a step-by-step guide on using custom pre-commit hooks to ensure code quality. It covers how to start using pre-commit hooks, creating a custom pre-commit hook, and testing the hook locally.

  15. 15
    Article
    Avatar of kdnuggetsKDnuggets·2y

    5 Free Books to Master Statistics for Data Science

    A list of 5 free books to master statistics for data science, covering topics such as sampling, probability, regression, and Bayesian methods.

  16. 16
    Article
    Avatar of kdnuggetsKDnuggets·2y

    A Free Data Science Learning Roadmap: For All Levels with IBM

    Learn data science according to your expertise with 4 different learning roadmaps. Start from the introduction level and progress to advanced data science courses.

  17. 17
    Article
    Avatar of devtoDEV·2y

    The programming languages I learned in my Quantum Computing job

    Learn about the popular coding languages used in quantum computing, such as Python, Julia, and C++. Discover resources for learning these languages and their applications in quantum computing.

  18. 18
    Article
    Avatar of medium_jsMedium·2y

    Step by Step Basics: Code Autodocumentation

    Learn how to generate flawless documentation of Python code using Sphinx.

  19. 19
    Article
    Avatar of hnHacker News·2y

    Designing a Pure Python Web Framework · Reflex Blog

    Reflex is a Python web framework that allows developers to build web apps without needing to learn a new language. It combines a React frontend and a FastAPI backend, using WebSockets to handle communication between the two. Reflex simplifies the process of building web apps, eliminates the need for boilerplate code, and provides a unified look and feel. Event triggers and state updates are handled automatically by Reflex.

  20. 20
    Article
    Avatar of kdnuggetsKDnuggets·2y

    Pydantic Tutorial: Data Validation in Python Made Simple

    Learn how to use Pydantic, a popular data validation library, to model and validate your data in Python. This tutorial covers the installation process, creating a basic Pydantic model, and loading and parsing JSON data using Pydantic models.

  21. 21
    Article
    Avatar of communityCommunity Picks·2y

    My favourite data structure: The trie

    The trie is a deeply nested tree data structure commonly used for predictive text engines. It allows efficient search and recommendation of words based on word probabilities.

  22. 22
    Video
    Avatar of TechWithTimTech With Tim·2y

    10 Python Comprehensions You SHOULD Be Using

    Learn about Python list comprehensions, their syntax, and how to use them to perform tasks such as filtering even numbers and flattening a matrix. Discover the advantages of using list comprehensions to write clean and concise code.

  23. 23
    Video
    Avatar of communityCommunity Picks·2y

    Turn Python BLAZING FAST with these 6 secrets

    Learn six secrets to make Python faster, including using building functions from the standard library, utilizing generators, implementing concurrency, compiling code with Cython, using compiled libraries and frameworks such as NumPy, Pandas, and Pillow, and considering alternative interpreters like PyPy.

  24. 24
    Article
    Avatar of tigerdataTigerData (Creators of TimescaleDB)·2y

    Guide to Time-Series Analysis in Python

    Learn how Python can be used for time-series analysis, including loading and analyzing time-series data, plotting with Pyplot, and handling challenges of working with large datasets. Explore the advantages of Python, such as its simplicity, extensive library support, and code reusability. Discover specialized libraries like pandas, Matplotlib, tsfresh, and more for advanced time-series tasks. Gain insights into data cleaning, trend analysis, seasonality detection, forecasting models, and feature extraction for machine learning or deep learning algorithms.

  25. 25
    Article
    Avatar of hnHacker News·2y

    bananaml/fructose

    Fructose is a lightweight python package that allows you to create a dependable, strongly-typed interface around an LLM call. It supports various types, compound types, complex datatypes, and the ability to call local Python functions.