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PlanetPython
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Mike Driscoll: Creating TUI Applications with Textual and Python Kickstarter Launched
- Text-based user interfaces (TUIs) are making a BIG comeback with the help of Textual.
- The Kickstarter campaign for the book 'Creating TUI Applications with Textual and Python' has been launched.
- The book covers various topics including application development basics, styling, DOM queries, and more.
- The book will be available in multiple formats, such as paperback, PDF, and epub.
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RealPython
1M
36
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Managing Python Projects With uv: An All-in-One Solution
- The uv tool is a high-speed package and project manager for Python, written in Rust, offering fast dependency installation and multiple functionalities.
- uv enables managing multiple Python versions, creating virtual environments, handling project dependencies, reproducing working environments, and building and publishing projects.
- It serves as an all-in-one tool for Python project management, enhancing productivity and efficiency.
- uv supports building and publishing Python packages to repositories like PyPI, streamlining the process from development to distribution.
- Automatically managing virtual environments, uv ensures clean and isolated project dependencies.
- Key features of uv include fast dependency installation, virtual environment management, Python version management, project initialization, dependency management, and package builds and publication management.
- uv integrates various functionalities and tools into a single solution, boosting project management actions.
- It is a standalone binary allowing smooth installation and quick upgrades, independent of having Python installed.
- Installation options for uv include using a standalone installer, installing from PyPI with tools like pipx or pip, and other methods specified in the official installation guide.
- Standalone installer commands for Windows, Linux, and macOS are provided, facilitating the download and installation of the latest binary version of uv.
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Medium
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197
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10 Essential Skills and Practices Every Beginner Must Master to Excel in Python or JavaScript
- Master the Fundamentals of Programming, including variables and data types, conditional statements, loops, functions, and error handling.
- Learn and Practice Problem-Solving Techniques by solving coding problems daily, focusing on algorithm design and optimization.
- Understand Data Structures and Algorithms (DSA) like arrays, strings, linked lists, and sorting and searching algorithms.
- Develop the Habit of Writing Clean and Readable Code by using meaningful variable names, small modular functions, comments, and following coding style guides.
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Dev
1M
398
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Building a RESTful To-Do API with Clean Architecture in Python
- APIs power modern apps, but without good structure they become tangled.
- A minimal To-Do API with endpoints to create, list, update, and delete tasks.
- Clean architecture separates concerns into layers: Entities, Use Cases, Interface Adapters, and Framework & Drivers.
- The tutorial also includes steps on how to create entities, implement business logic, define interface adapters, set up the Flask framework, and perform testing.
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23 Likes
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Kitploit
1M
73
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Scrapling - An Undetectable, Powerful, Flexible, High-Performance Python Library That Makes Web Scraping Simple And Easy Again!
- Scrapling is a high-performance, intelligent web scraping library for Python that adapts to website changes and outperforms popular alternatives.
- It provides features like dynamic loading, automation, anti-bot protection bypass, smart element tracking, and flexible selection methods.
- Scrapling offers lightning-fast HTTP requests, memory efficiency, and fast JSON serialization.
- Developer-friendly features include a powerful navigation API, rich text processing, auto selectors generation, and familiar API.
- Installation is simple using pip and browsers' dependencies can be installed by running a command.
- The library allows fetching websites with interfaces like Fetcher, StealthyFetcher, and PlayWrightFetcher.
- Scrapling's advanced parsing features include smart navigation, content-based selection, finding similar elements, and handling structural changes.
- The article also compares Scrapling's performance with popular Python libraries like Scrapy and Lxml in text extraction and extraction by text speed tests.
- The library addresses common questions in FAQs and emphasizes educational and research purposes only with a BSD-3 license.
- Contributions are welcome, with known issues highlighted, acknowledgments given, and references to related projects.
- Scrapling is designed and crafted by Karim Shoair, emphasizing its high functionality, ease of use, and performance benefits.
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PlanetPython
1M
151
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Talk Python to Me: #503: The PyArrow Revolution
- Pandas is at the core of virtually all data science done in Python, that is virtually all data science.
- Changes are afoot to update the internals of Pandas by using PyArrow.
- PyArrow offers benefits such as a columnar format for faster analytical queries, support for high performance file formats, and faster file IO.
- Reuven Lerner explains the PyArrow revolution in this episode of Talk Python to Me podcast.
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PlanetPython
1M
73
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Python GUIs: Kivy's Complex Widgets ��� Learn How to Use Kivy's Complex UX Widgets in Your Apps
- Kivy is a framework for developing multi-touch GUI apps in Python with rich built-in widgets.
- This tutorial covers complex widgets in Kivy like Bubble, DropDown, FileChooser, Popup, Spinner, RecycleView, TabbedPanel, VideoPlayer, and VKeyboard.
- You can enhance your Kivy apps with advanced features using these widgets.
- The tutorial starts with building an outline Kivy app and progresses to Spinner for option selections.
- DropDown is introduced for providing a menu component with multiple options.
- File access is facilitated using FileChooser for describing and browsing file systems.
- Quick dialogs can be created with the Popup widget for modal dialogs.
- Bubble is discussed for contextual popups, tooltips, or chat applications.
- RecycleView efficiently displays data by recycling views, avoiding a widget for every item.
- TabbedPanel organizes content into tabs, improving navigation and space utilization.
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4 Likes
Medium
1M
398
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10 AI-Powered Python Libraries That Will Supercharge Your Next Project
- 10 AI-powered Python libraries that will supercharge your next project.
- These libraries can make you rethink what's possible in a weekend project.
- One of the recommended libraries is sentence-transformers for working with text.
- It allows you to load pre-trained models and convert paragraphs into dense vectors.
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23 Likes
Dev
1M
320
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Mastering Python: A Comprehensive Guide
- Python is one of the most versatile and widely-used programming languages.
- Mastering Python allows you to work in web development, data science, automation, and more.
- Python's simplicity, versatility, strong community, and high demand make it a must-learn language.
- The guide covers setup, basics (variables, control structures, functions), data types, OOP, web development, data science, automation, and best practices.
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Hackernoon
1M
123
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Tired of Slow Python ML Pipelines? Try Purem
- Purem is a high-performance AI/ML computation engine that aims to provide native speed to Python code, offering 100–500x acceleration for real-world ML operations.
- Unlike traditional Python accelerators, Purem focuses on optimizing core operations at a pure binary level, eliminating overhead and serialization issues.
- It bridges the Python-hardware performance gap by precompiling core operations for x86-64 and enabling zero Python overhead data flow.
- Purem ensures easy deployment with pip installation, compatibility with Python 3.7+, and production-ready features such as test coverage and logging.
- Benchmark comparisons show significant speedups of Purem over NumPy, JAX, and PyTorch, ranging from 100x to 500x on core operations.
- Current ML libraries like JAX and PyTorch face limitations on CPUs, while NumPy and Pandas struggle with scalability and single-threaded performance.
- Purem unlocks use cases in fintech, edge AI, big data, and ML research by providing rapid computation without infra rewrites or performance compromises.
- Example-driven and performance-focused, Purem sets a new standard for Python-native performance in AI/ML applications.
- It is positioned as SLA-grade and production-ready, aiming to enhance the productivity and performance of teams working at real scale.
- Purem encourages the next generation of AI engineering by offering accelerated computation without sacrificing Python’s elegance and productivity.
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7 Likes
Medium
1M
270
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Mastering Functions in Python: A Complete Beginner’s Chapter (with Examples)
- Functions in Python allow breaking big problems into smaller pieces, avoid repetition, and make code easier to read and maintain.
- Defining a function in Python is done using the def keyword followed by the function name and code block.
- Functions can be called by simply writing the function name followed by parentheses.
- Parameters can be passed to functions, allowing for flexibility and reusability.
- Functions can return values using the return statement, enabling them to provide results for later use.
- Python functions can accept default values, keyword arguments, and handle any number of inputs using *args and **kwargs.
- Local variables are created inside functions, while global variables are accessible throughout the program.
- Functions can take other functions as inputs and even return functions as outputs, known as Higher-Order Functions.
- Lambda functions in Python are small anonymous functions that can simplify tasks and work well with higher-order functions.
- Recursion in Python involves functions calling themselves to solve problems by breaking them down into smaller parts.
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16 Likes
Medium
1M
100
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Pandas in Python
- Pandas is a powerful Python library for working with structured data (like tables, spreadsheets, CSVs).
- Pandas provides the ability to load, clean, manipulate, analyze, and visualize data easily.
- Pandas consists of one-dimensional arrays called Series and two-dimensional data structures called DataFrames.
- CSV files are commonly used in Pandas for storing tabular data in a lightweight and easy-to-read format.
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6 Likes
Medium
1M
160
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Control Flow in Python for Beginners: If-Else, Loops, Break, Continue Explained Simply
- Control flow in Python allows programs to make decisions based on conditions, repeat actions, and choose different paths.
- Python uses conditional statements like if, else, and elif for decision-making based on certain conditions.
- The if statement checks a condition and runs the code inside the block if it's true.
- If-else statements are used to do one thing if a condition is true and another if it's false.
- Python uses elif to check multiple conditions one after another.
- Nested conditional statements are used to handle complex situations by putting if blocks inside each other.
- Loops like while and for allow repeating actions a certain number of times or until a condition is met.
- Python provides loop control statements like break to exit a loop, continue to skip an iteration, and pass as a placeholder.
- Nested loops involve putting one loop inside another for more complex iterations.
- Python loops can iterate over lists, dictionaries, and strings to work with collections of data efficiently.
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9 Likes
Medium
1M
178
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Java Remains a Backend Powerhouse in 2025 (Even vs Go, Python or TypeScript)
- Java remains a heavyweight in the backend world, with a massive community and a vast ecosystem of frameworks and libraries, making it popular in enterprises.
- Frameworks like Spring Boot and Jakarta EE dominate for microservices and APIs, while newer alternatives like Quarkus and Micronaut offer faster startup times for cloud-native services.
- Java's static typing and tooling catch errors at compile time, and modern Java versions add features to reduce boilerplate.
- Go, designed for simplicity and concurrency, appeals to building performant APIs and microservices with an easy deployment process via static binaries.
- Python's extensive ecosystem offers frameworks like Django and Flask for backend development, but its dynamism may lead to runtime bugs and lower performance.
- TypeScript's optional static types and huge ecosystem on Node.js make it a mainstream choice for backend development, providing flexibility and safety.
- Norm4j simplifies mapping entities to DTOs in Java, reducing boilerplate and enabling efficient data transfer in backend development.
- Java continues to evolve, offering a blend of agility, robustness, and cloud-friendly speed, making it a future-proof choice for backend development.
- While Go, Python, and TypeScript are rising stars, Java's maturity and continuous evolution keep it relevant and modern in backend development.
- Investing in Java as a beginner means learning a proven technology that remains highly relevant for building modern applications and services.
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