The hottest Programming Substack posts right now

And their main takeaways
Category
Top Technology Topics

Testing a book's code, part 4: Testing Matplotlib data visualizations

Mostly Python • 314 implied HN points • 01 Feb 24
🕹 Technology Programming Data Testing
  1. Testing data visualizations programs involves assessing both terminal and graphical outputs.
  2. Automated testing of Matplotlib programs can be challenging due to the appearance of the Matplotlib plot viewer.
  3. One approach to overcome the challenge of testing Matplotlib programs is to modify the files to generate image files for testing.

Code “Smells”?

Software Design: Tidy First? • 2181 implied HN points • 03 Jul 23
🕹 Technology Programming Software Development
  1. Code that works might still be problematic if it's hard to understand or change later on.
  2. It's important for programmers to focus on writing code that not only works now but is also easy to change in the future.
  3. The analogy of 'code smells' is like food that smells bad: a warning of potential future issues in the code.

A quick introduction to Memory Pools [Math Mondays]

Technology Made Simple • 179 implied HN points • 27 Feb 24
🕹 Technology Memory management Software Engineering Optimization Performance Programming
  1. Memory pools are a way to pre-allocate and reuse memory blocks in software, which can significantly enhance performance.
  2. Benefits of memory pools include reduced fragmentation, quick memory management, and improved performance in programs with frequent memory allocations.
  3. Drawbacks of memory pools include fixed-size blocks, overhead in management, and potential for memory exhaustion if not carefully managed.

Chip Letter Links No. 16 : Gordon Moore's Notebooks, Nvidia on Acquired, Assembly Language, Jeff Hinton, RISC-V on Jupyter

The Chip Letter • 2672 implied HN points • 16 Apr 23
🕹 Technology Tech news Computer History Programming Podcasts Artificial Intelligence
  1. Gordon Moore's notebooks from Fairchild provide a unique insight into his work and research in the early days of computing.
  2. Assembly language, especially 8-bit, was more popular and necessary in the past compared to modern 64-bit architectures.
  3. Nvidia's survival and success were closely tied to their alignment with Moore's Law in the GPU industry.

How to Use AI to Do Stuff: An Opinionated Guide

One Useful Thing • 1801 implied HN points • 15 Jul 23
🕹 Technology AI Machine Learning Programming Data Analysis Education
  1. Increasingly powerful AI systems are being released rapidly without proper user documentation.
  2. The major Large Language Models in use currently are GPT-3.5, GPT-4, Bard, Pi, and Claude 2.
  3. AI can assist with writing, generating images, coming up with ideas, making videos, and working with documents and data, but users must be cautious of biases and ethical concerns.
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Console #189 - Interview with Elia of Opal - a Ruby to JavaScript source-to-source compiler

Console • 413 implied HN points • 24 Dec 23
🕹 Technology Programming Open Source Web Development Software Tools Debugging
  1. Opal is a source-to-source compiler that converts Ruby to JavaScript.
  2. Opal leverages the underlying JavaScript engine for speed, size, and debugging benefits.
  3. The project Opal aims to continue improving by exploring features like dead-code-elimination and better module support.

The Lightness of Unscheduled Calls

Register Spill • 196 implied HN points • 11 Feb 24
🕹 Technology Collaboration Remote work Culture Communication Programming
  1. Collaboration without elaborate scheduling can feel light and spontaneous, leading to a more open and fluid work environment.
  2. Embracing unscheduled calls and spontaneous pairing sessions can foster better knowledge transfer and idea exchange among team members.
  3. Using tools that support easy and on-the-fly collaboration can significantly impact the culture and productivity of a remote team, making workdays feel full of possibilities rather than meetings.

Creativity is Domain Independent

Insight Axis • 671 implied HN points • 22 Oct 23
🎨 Art & Illustration Science Art Writing Programming Creativity
  1. Creativity is not limited to specific fields like art or music; it is a fundamental aspect of being human, manifested across various domains like science, art, writing, and programming.
  2. The creative process involves daring to create something, followed by refining and improving upon it - a cycle present in science, art, and literature.
  3. In programming and software engineering, creativity is not just about writing code but also about the iterative process of refining, debugging, and deleting code - highlighting the importance of continuous improvement and simplification.

Edge 376: The Creators of Vicuna and Chatbot Arena Built SGLang for Super Fast LLM Inference

TheSequence • 98 implied HN points • 07 Mar 24
🕹 Technology Artificial Intelligence Programming Open Source Machine Learning
  1. SGLang is a new open source project from Berkeley University designed to enhance interactions with Large Language Models (LLMs), making them faster and more manageable.
  2. SGLang integrates backend runtime systems with frontend languages to provide better control over LLMs, aiming to optimize the processes involved in working with these models.
  3. The framework created by LMSys offers significant optimizations that can boost the inference times in LLMs by up to 5 times, showcasing advancements in processing vast amounts of data at incredible speeds.

Write Cleaner, More Maintainable Rust Code with PhantomData

Aayushya’s Substack • 99 implied HN points • 06 Mar 24
🕹 Technology Coding Software Development Rust Programming
  1. Using PhantomData in Rust can help reduce code duplication by creating a generic struct with common fields and methods.
  2. Marker types like FreeLineQuantityTag and BilledLineQuantityTag can help differentiate between types when refactoring code.
  3. Leveraging advanced Rust features like PhantomData can lead to more maintainable and expressive code in real-world projects.

GPT-4 Plugs In

thezvi • 1740 implied HN points • 27 Mar 23
🕹 Technology AI Internet Privacy Security Programming
  1. GPT-4 is getting an upgrade with plug-ins for browsing the internet and using various websites.
  2. Concerns about safety and risks involved in using these new plug-ins have been raised.
  3. The introduction of plug-ins makes it easier to interact with GPT-4, but also raises questions about trust and potential misuse.

OOP in Python: Why is object-oriented programming so important?

Mostly Python • 1257 implied HN points • 06 Jul 23
🕹 Technology Programming
  1. Object-oriented programming (OOP) is important because it stores information and actions in one place.
  2. OOP is powerful for getting work done efficiently, as shown by the ease of creating and working with objects in Python.
  3. Even if you don't write classes often, understanding OOP in Python can make you a better programmer since everything in Python is an object.

This will be easy

Bite code! • 1223 implied HN points • 08 Jul 23
🕹 Technology Programming Networking Error Handling Logging
  1. Making HTTP POST requests can have unexpected challenges, like dealing with network issues and corporate setups.
  2. Using ThreadExecutor and ThreadPoolExecutor in Python can help manage tasks efficiently, especially in scenarios like log aggregation.
  3. Error handling is crucial in programming, and sometimes unconventional solutions are needed to manage exceptions effectively.

The devil is old

Wednesday Wisdom • 113 implied HN points • 21 Feb 24
🕹 Technology Programming Mathematics Physics Concurrency Software Development
  1. Experience and age often bring wisdom, knowledge, and a unique perspective.
  2. In technology, while tools and capabilities have evolved, fundamental principles like people dynamics, math, and physics remain constant.
  3. Despite advancements, people still struggle with basic math, concurrent programming, and effective communication in group settings.

All the bullshit I did as a kid (part 1?)

Basta’s Notes • 204 implied HN points • 17 Jan 24
🕹 Technology Programming Web Development Operating Systems Software Development Tech industry
  1. The author reflects on the interesting and ambitious projects they worked on as a kid, showcasing a strong interest in technology and programming.
  2. Despite lacking mentorship, the author taught themselves valuable programming skills, such as building their own web browser and writing complex code like a CSS parser.
  3. The journey from tinkering with personal computers to winning a programming contest and earning internship opportunities highlights the author's growth and passion for technology.

A World without C

Deus In Machina • 72 implied HN points • 07 Mar 24
🕹 Technology Programming Software Languages Innovation Legacy
  1. The push towards memory-safe languages like C++ over C is gaining attention due to concerns about software security, especially in critical systems like government infrastructure and services.
  2. C's simplicity and widespread usage make it a common choice for interlanguage bindings, but its simplicity can also lead to challenges in areas like memory management and handling large projects.
  3. While C has a rich history and legacy, there is growing discussion about the potential for newer languages like Zig to eventually replace C in its core functionalities, driven by advancements in the programming landscape.

Flexibility of plang programming language

Ingig • 3 HN points • 05 May 24
🕹 Technology Programming Apps Syntax Algebra
  1. The Plang programming language offers great flexibility, allowing for simplified and personalized app development without the need for extensive programming.
  2. FoodDiaryApp in Plang demonstrates how job-related tasks can be efficiently accomplished with minimal user input.
  3. Plang allows for the creation of variables within user input, showcasing a unique approach to designing personalized applications with user-defined logic.

jDeploy vs jpackage

jDeploy Newsletter • 84 implied HN points • 27 Feb 24
🕹 Technology Programming Software Development Tools Deployment
  1. jpackage is an official tool for bundling Java apps, dependent on platform tools, and useful for creating app bundles for Mac, Windows, or Linux with embedded Java runtime.
  2. jDeploy is an open source tool that can build and deploy app bundles for all platforms from any platform, offering a smaller app bundle size, auto updates, and deployment through GitHub or npm.
  3. Use jpackage for app store distributions, while jDeploy is great for easy deployment, auto-updates, and quick distribution of internal utilities or PoC apps.

SDL Tutorial Part 1: Opening A Window

Deus In Machina • 108 implied HN points • 15 Feb 24
🕹 Technology Programming Software Tutorial
  1. The tutorial provides a cheat sheet for essential SDL functions like initializing, creating a window, rendering, and cleaning up.
  2. The tutorial gives practical code examples for opening a window in SDL2, emphasizing error handling for function calls.
  3. It emphasizes the importance of clearing the screen with a color to prevent interference between frames and discusses the choice between SDL and Raylib for game development.

Creating Individualised Chess Engines

Chess Engine Lab • 39 implied HN points • 26 Mar 24
🕹 Technology Artificial Intelligence Data Analysis Programming Chess Machine Learning
  1. An engine called Maia focused on predicting human moves accurately instead of just being the strongest in chess, resulting in a more meaningful impact, especially for club-level players.
  2. By individualizing chess engines to predict moves of specific players, accuracy can be increased by 4-5% and players can be identified with 98% accuracy from a pool of 400, based on their game patterns.
  3. Identifying players through their mistakes is a crucial aspect - as mistakes are unique to individual players, understanding and fixing them can greatly aid in chess improvement.

Using Matplotlib To Create The 50th Article Cover Mosaic Animation (#50 Part 2)

The Python Coding Stack • by Stephen Gruppetta • 117 implied HN points • 10 Feb 24
🕹 Technology Programming Animation Visualization
  1. You can use Matplotlib to create animations, like a mosaic of previous article cover images, by following a step-by-step tutorial.
  2. Before starting the animation, ensure you have images ready and the necessary libraries installed like Matplotlib, NumPy, and Pillow.
  3. You can control how images are plotted, resize images in the animation frames, and save the animation as a movie file like an mp4 or an animated GIF using libraries like Matplotlib or PillowWriter.

CPython Dynamic Dispatch Internals: What Happens When You do a + b?

Confessions of a Code Addict • 293 HN points • 06 Dec 23
🕹 Technology Programming Python
  1. Each type in Python implements functions for the operators it supports and populates a function pointer table in its header.
  2. The CPython Virtual Machine calls a function in the abstract object interface based on the operator being executed.
  3. The abstract object interface performs function pointer table lookup in the object headers to call the right function for dynamic dispatch.

What Every Developer Should Know About GPU Computing

Confessions of a Code Addict • 465 HN points • 18 Oct 23
🕹 Technology Programming Architecture
  1. GPUs are designed for high throughput and massive parallelism, while CPUs focus on executing sequential instructions quickly.
  2. GPU architecture includes streaming multiprocessors with cores, various memory layers, and dynamic resource partitioning for efficient execution.
  3. Executing code on GPUs involves launching grids of thread blocks, with each block consisting of threads that work in parallel to optimize performance.

Prompt Engineering with GPT-4: Charting and Mapping European Tourism Trends

Data at Depth • 19 implied HN points • 11 Apr 24
🕹 Technology Data Analysis Data Visualization Artificial Intelligence Programming Web Development
  1. Efficiency is highly sought after state of being for coders and data analysts. GPT-4's Code Interpreter functionality significantly streamlines the process of transforming CSV data into data visualizations.
  2. GPT-4 can generate Python code for various types of data visualizations like line charts, bar charts, and area charts. Simply prompting GPT-4 with specific information can quickly produce comprehensive visualizations.
  3. GPT-4 can be utilized to filter datasets, analyze trends, and create innovative visual representations like choropleth maps. Incorporating GPT-4 into data analysis workflows can lead to faster and efficient results.

THINK's Lightspeed C

Computer Ads from the Past • 512 implied HN points • 27 Sep 23
🕹 Technology Computers Programming Software Tech Companies Computer History
  1. Lightspeed C was a C programming language software developed in the mid-1980s for Atari systems and Macintosh computers.
  2. Clearstar Softechnologies created Lightspeed C for Atari systems in 1985, and the company was later purchased by Omega Soft in 1988.
  3. THINK Technologies released Lightspeed C for Mac and later renamed it to THINK C in the mid-1980s, receiving positive reviews for its speed and user-friendliness.

The Best Skillsets to Learn in 2024 for Generative AI

Rod’s Blog • 238 implied HN points • 15 Dec 23
🕹 Technology AI Programming Machine Learning Data science Resources
  1. Generative AI is a rapidly evolving field creating novel content like images, text, music, etc., with real-world applications from enhancing creativity to helping solve problems.
  2. To succeed in generative AI, you need skills like mathematics and statistics, programming, data science, knowledge of generative AI methods, and creativity in your specific domain.
  3. To learn generative AI in 2024, leverage online courses, books, blogs, tools, and engage in communities and events dedicated to this field.

Get the most out of Python dicts

Bite code! • 978 implied HN points • 13 Jun 23
🕹 Technology Programming
  1. Merge dictionaries with methods like dict.updates(), **, |, and collections.ChainMap
  2. Deal with missing values in dictionaries using methods like dict.get(), dict.setdefault(), and collections.defaultdict
  3. Extract multiple values at once using tools like operator.itemgetter and match/case

Fast Computation of Fibonacci Numbers: Part II

Confessions of a Code Addict • 288 implied HN points • 12 Nov 23
🕹 Technology Mathematics Programming Algorithms Education
  1. A new method to compute Fibonacci numbers using a closed-form expression without having to resort to floating point arithmetic.
  2. Representation of irrational numbers using two parts can be done in code allowing for precise computation of Fibonacci numbers.
  3. Understanding rings and implementing arithmetic operations within it can help in computing Fibonacci numbers without any loss of precision.

You can't handle Errors

Burning the Midnight Coffee • 83 HN points • 13 Feb 24
🕹 Technology Programming Error Handling
  1. Faults in code lead to errors, which then cause failures in a program's behavior. Understanding this process is crucial for effective error handling.
  2. Handling an error means returning the program to a known, correct state, which usually involves restarting it in some way. Proper failure handling is key.
  3. Exceptions as both error handling and additional return values can lead to more faults and failures. It's important to define and address failures distinctly from errors.

Four Essential Skills to Improve Your Python Data Visualization Workflow

Data at Depth • 19 implied HN points • 06 Apr 24
🕹 Technology Data Visualization Python AI Programming Coding
  1. Understanding Python data visualization libraries like Matplotlib, Seaborn, and Plotly can help you create different types of visualizations.
  2. Learning data cleaning and preprocessing techniques with Pandas is crucial to ensure accurate and meaningful visualizations.
  3. Mastering Modular Prompting with tools like ChatGPT can speed up coding tasks by generating code snippets based on specific instructions.

How To Identify A Good Programmer

Morad’s Substack • 7 HN points • 24 Apr 24
🕹 Technology Programming Learning Intelligence Experience
  1. Passion is a key indicator of a good programmer - they should be enthusiastic about programming, even outside of work.
  2. Good programmers love learning and are self-teaching, constantly exploring new technologies without needing formal training.
  3. Intelligence is crucial for a good programmer - they are smart, have various interests, and usually start programming before university or formal education.