The hottest Programming Substack posts right now

And their main takeaways
Category
Top Technology Topics

RAG Glossary

The Tech Buffet • 179 implied HN points • 21 Jan 24
🕹 Technology Machine Learning AI Research Software Development Data Management Programming
  1. Retrieval Augmented Generation (RAG) helps AI answer questions and generate content. It combines searching through documents with generating relevant answers.
  2. Using RAG can be tricky, especially in production environments. Adjustments may be needed to improve reliability and performance.
  3. Different indexing methods can optimize how RAG retrieves information. This can make it more efficient and effective in finding the right data.

Amusing logical errors

Mostly Python • 314 implied HN points • 07 Mar 24
🕹 Technology Programming Bug Fixing
  1. There are two main types of bugs - those that cause code to break and those that are logical errors, which are harder to fix as the code runs without generating a traceback.
  2. Current platforms like Substack and Ghost have limitations in displaying code blocks, lacking proper syntax highlighting and tools for pointing out specific lines.
  3. Developing utility functions to isolate and troubleshoot problematic code can make it easier to maintain and use in larger projects, ultimately saving time and effort in the long run.
Get a weekly roundup of the best Substack posts, by hacker news affinity:

A Guide to Optimising your Spark Application Performance (Part 2)

SwirlAI Newsletter • 314 implied HN points • 06 Aug 23
🕹 Technology Programming Big Data Optimization Data Storage
  1. Choose the right file format for your data storage in Spark like Parquet or ORC for OLAP use cases.
  2. Understand and utilize encoding techniques like Run Length Encoding and Dictionary Encoding in Parquet for efficient data storage.
  3. Optimize Spark Executor Memory allocation and maximize the number of executors for improved application performance.

Accelerate by years part IV - The prototype

Opral (lix & inlang) • 19 implied HN points • 23 Jul 24
🕹 Technology Software Development Databases APIs Programming Tech Innovation
  1. Using SQLite can really speed up the development of both inlang and lix. This saves a lot of time on needing to create complex systems.
  2. Lix 1.0 is coming soon, with simple plugins that can manage changes easily. This makes it easy for apps to work with changes directly.
  3. The next steps involve building a user interface for merging data and creating a plugin for inlang. This should help make the system more efficient.

Accelerate by years part III - Lix on SQLite

Opral (lix & inlang) • 19 implied HN points • 23 Jul 24
🕹 Technology Software Development Databases Programming Innovation Tech Tools
  1. Building lix without relying on Git can simplify the process. This means avoiding the complications that come with Git's file-based storage model.
  2. Using SQLite for storing data will solve many problems like concurrency and data integrity. It makes it easier to manage application data compared to handling everything through Git.
  3. The main requirements for lix 1.0 will be a merging function and a plugin for inlang. This will open up opportunities for third-party developers to create new lix applications.

Accelerate by years part I - Inlang directories as lix repositories

Opral (lix & inlang) • 19 implied HN points • 23 Jul 24
🕹 Technology Software Development Networking Systems Programming
  1. Making inlang directories work as independent repositories can speed up the development process significantly. This means less reliance on GitHub and fewer complications.
  2. Smaller, self-contained inlang repositories require less hosting and have lower scalability needs. This makes it easier to manage and use them without needing a lot of resources.
  3. With control over push, pull, and commit actions, developers can streamline their workflows. This helps avoid many frustrating issues related to traditional version control systems.

GroupBy #35: The Netflix Data Engineering Stack, Atlassian - Evolve the data platform with a Deployment Capability

VuTrinh. • 59 implied HN points • 14 May 24
🕹 Technology Data Engineering Software Development Cloud Computing Data architecture Programming
  1. Netflix has a strong data engineering stack that supports both batch and streaming data pipelines. It focuses on building flexible and efficient data architectures.
  2. Atlassian has revamped its data platform to include a new deployment capability inspired by technologies like Kubernetes. This helps streamline their data management processes.
  3. Migrating from dbt Cloud can teach valuable lessons about data development. Companies should explore different options and learn from their migration journeys.

Python Plotly Mapping Magic: Better Results With GPT-4 Prompting

Data at Depth • 59 implied HN points • 13 May 24
🕹 Technology Data Visualization Python AI Programming
  1. GPT-4 can be useful for generating data cleaning and visualization code in Python when combined with libraries like pandas and plotly
  2. Using GPT-4, you can learn how to clean datasets, create choropleth maps, and even animated choropleth maps to visualize data over time
  3. Interactive geospatial data visualizations that tell stories over time can be quickly created with Plotly by using GPT-4 prompts

Workshop on Performance Optimizations in Code: The One Billion Row Challenge

Confessions of a Code Addict • 577 implied HN points • 15 Jan 24
🕹 Technology Programming Workshop Optimization Performance Coding
  1. Code efficiency at scale is crucial - data structures and algorithms matter, but execution cost is also important.
  2. Participating in challenges like the 1 Billion Row Challenge can enhance performance engineering skills.
  3. The workshop covers optimization techniques like flamegraphs, I/O strategies, system calls, SIMD instructions, and more.

Data Science Weekly - Issue 512

Data Science Weekly Newsletter • 299 implied HN points • 14 Sep 23
🕹 Technology Data science Artificial Intelligence Machine Learning Data Engineering Programming
  1. Nvidia has been a leader in AI technology, but its dominance might not last. Changes in the market and technology could shift the competitive landscape soon.
  2. For those who know R and want to learn Python, there are resources available to help make the transition easier. These resources provide advice and tips catered to R users.
  3. Reinforcement Learning with Human Feedback (RLHF) is an important part of training large language models. It's essential for improving how these models understand and respond to human preferences.

Testing a book's code, part 6: Testing a Django project

Mostly Python • 314 implied HN points • 15 Feb 24
🕹 Technology Programming Software Testing Web Development
  1. Testing a Django project in a book involves creating a copy of the project, setting up a separate virtual environment, and ensuring it functions correctly on new Django versions.
  2. When testing a Django project, focus is usually on internal code, but the priority here is verifying functionality on new Django versions due to its frequent updates.
  3. The post discusses developing a single test function for a Django project named Learning Log, emphasizing the importance of testing project functionality as intended.

"Organic Markdown" Intro

Rethinking Software • 199 implied HN points • 21 Aug 24
🕹 Technology Programming Software Development Documentation Open Source
  1. Organic Markdown helps keep your code and documentation in sync. This means you won't have to edit your code separately from your notes, making everything easier to manage.
  2. It improves how your code is presented. By arranging your code better for people to understand, you can still adjust it later for the computer to run.
  3. You can run commands and build applications right from your Markdown file. This makes the workflow smoother and lets you focus more on coding.

Console #193 -- An Interview with Alain of Planify - Task manager for GNU/Linux

Console • 531 implied HN points • 21 Jan 24
🕹 Technology Open Source Development Programming Linux
  1. Planify is a task manager designed for GNU/Linux, inspired by popular task managers like Things 3 and Todoist.
  2. Planify's developer, Alain, started the project as a way to create a task manager with a nice design and good functionality for Linux users.
  3. Planify is free to download and is maintained through donations, with a focus on design, detail, and user-friendly elements.

Once a Maintainer: André Luis Cardoso Jr.

Once a Maintainer • 49 implied HN points • 18 Oct 24
🕹 Technology Software Development Open Source Programming Mentoring Community Engagement
  1. Getting into programming can start with just curiosity and having a computer. Self-study can lead you to discover what you really want to do.
  2. Contributing to open source is about giving back to the community and helps you grow as a developer. Even small contributions can make a big difference.
  3. It's important to teach younger developers about understanding the code under the hood, not just using tools. Encouraging contribution can keep projects alive and thriving.

Software Developer Influencers: The Modern Snake Oil Salesmen

Based Meditations • 278 implied HN points • 19 Aug 23
🕹 Technology Programming Influencer Career Market Culture
  1. Becoming a software developer is highly appealing due to the potential for high salaries and the option to work from home
  2. Influencers in the software development space often oversimplify the requirements and challenges of breaking into the industry
  3. Having a degree, building a strong portfolio, and understanding the nuanced demands of the software industry are crucial for success

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.

Seven things I know after 25 years of development

zverok on lucid code • 57 implied HN points • 27 Jan 25
🕹 Technology Software Development Programming Conferences Technical Writing
  1. After many years of working in development, it's clear that balancing technical skills with human connection is crucial. Building good relationships can make a big difference in your career.
  2. Learning is a lifelong journey, and it's important to be open to new ideas and changes in the industry. Staying curious helps you adapt and grow.
  3. Reflecting on personal and professional lessons can lead to meaningful growth. Taking time to think about your experiences is valuable for future decisions.

For Pete's sake, learn what a machine is.

Top Carbon Chauvinist • 19 implied HN points • 17 Jul 24
🕹 Technology Machine Learning Artificial Intelligence Robotics Programming Computer Science
  1. A machine is made up of parts that do work by handling loads, like electricity or mechanics. It does not actually understand or think about what it does.
  2. When programming a machine, like a catapult, you're just adjusting physical elements, not teaching it to know or understand concepts like 'rock' or 'lever'.
  3. Living things are not machines because they aren't made of manufactured parts. They grow and evolve in ways that machines cannot.

Sometimes complicated is clearer

CodeFaster • 36 implied HN points • 19 Feb 25
🕹 Technology Software Programming Development Automation Open Source
  1. Complicated things can sometimes be clearer than simple ones. It can help to look at details closely. It's okay to dive deeper to understand better.
  2. Taking screenshots at different intervals can help document changes over time. This can be useful for tracking progress or capturing important moments.
  3. Support from readers can help content creators keep producing work. Subscribing, whether free or paid, can make a difference.

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.

Intro to PDB, the Python Debugger

Bite code! • 733 implied HN points • 09 May 23
🕹 Technology Programming Debugging Commands Tips Python
  1. PDB is a basic but useful debugger that comes with Python by default, allowing you to pause programs, enter a debugging shell, and analyze program states.
  2. Learning to use PDB is valuable because it helps you understand debugging fundamentals, and knowing PDB can translate to using other debuggers as well.
  3. PDB offers various helpful commands like 'help', 'quit', 'list', 'next', 'continue', 'until line', 'jump line', 'display', 'step', 'return', 'up', and 'down' for effective debugging in Python.

Exploring recent Python repositories, part 2

Mostly Python • 628 implied HN points • 29 Jun 23
🕹 Technology Programming Open Source Software Development Data Analysis Web Development
  1. The post explores new Python repositories that have gained just a small number of stars, filtering out the projects with no attention.
  2. Over 300,000 Python repositories are pushed to GitHub each month, showing the challenge of getting noticed among the vast amount of projects.
  3. Projects with a few stars can still be interesting and worth exploring, like a Pygame project inspired by Factorio.

Faster NTT with RISC-V Vector

Fprox’s Substack • 62 implied HN points • 11 Jan 25
🕹 Technology Software Programming Cryptography Hardware Algorithms
  1. The Number Theoretic Transform (NTT) can speed up polynomial multiplications, which are important for modern cryptography. Optimizing how this process works leads to significant performance improvements.
  2. Using assembly language can help tailor code for specific hardware, allowing more direct control over how instructions are executed, which can greatly enhance speed.
  3. Combining multiple steps of the NTT process into fewer loops and minimizing unnecessary calculations can lead to much lower execution times, achieving targets that seemed difficult at first.

Console #191 -- Interview with Bernhard of ACID Chess - Chess computer for nerds, by nerds

Console • 472 implied HN points • 07 Jan 24
🕹 Technology Open Source Programming AI Software Development Neural Networks
  1. ACID Chess is a chess computer program written in Python that can analyze the movements of pieces on a chessboard through image recognition.
  2. The creator of ACID Chess balanced working on the project with a full-time job by dedicating time in evenings and weekends while finding it to be a good balance.
  3. The creator of ACID Chess believes AI will simplify various aspects of software development, and open-source software will continue to thrive with challenges in monetization for small developers.

How Rust and Python manage memory

VuTrinh. • 119 implied HN points • 27 Jan 24
🕹 Technology Programming Software Data Engineering Memory management System Design
  1. Rust uses ownership to manage memory, meaning each value has a single owner. When that owner goes out of scope, the memory gets freed automatically.
  2. Python uses a garbage collector to handle memory which counts how many references point to an object. Once there are no references left, it cleans up the unused memory.
  3. Rust's approach gives developers more control but requires them to understand ownership rules, while Python's method is easier for beginners but can slow down performance.

Rust: future cannot be sent between threads safely

Art’s Substack • 39 implied HN points • 24 May 24
🕹 Technology Programming Concurrency Error Handling Development Tools
  1. In Rust, sending futures between threads safely can lead to compilation errors. This can happen when sharing mutable data across threads that must be protected with a Mutex.
  2. The issue with sending futures between threads safely is due to the fact that futures in Rust are required to implement the 'Send' trait. Problems arise when trying to hold a MutexGuard across an await, causing the future not to be Send.
  3. To resolve issues related to sending futures between threads safely in Rust, one solution is to explicitly introduce a scope to handle locking and unlocking of the MutexGuard around the await, ensuring that the future is 'Send'.

DataFrame

davidj.substack • 35 implied HN points • 20 Feb 25
🕹 Technology Data science Machine Learning Programming Cloud Computing Open Source
  1. Polars Cloud allows for scaling across multiple machines, making it easier to handle large datasets than using just a single machine. This helps in processing data faster and more efficiently.
  2. Polars is simpler to use compared to Pandas and often performs better, especially when transforming data for machine learning tasks. It supports familiar methods that many users already know.
  3. Unlike SQL, which runs well on cloud services, using Pandas and R for large-scale transformations has been challenging. The new Polars Cloud aims to bridge this gap, providing more scalable solutions.

Settings that change, and settings that don't change

Mostly Python • 628 implied HN points • 18 May 23
🕹 Technology Programming Objects
  1. In Python, mutable objects can change values directly, while immutable objects create new objects when values are changed.
  2. Using dictionaries to group settings allows for changes to be tracked across classes in Python.
  3. Understanding mutable and immutable objects is crucial for managing data changes in Python, ensuring consistency across classes.

The Fastest Way to Run a Typescript Script, with Flags

Jake [Building in NYC] • 59 implied HN points • 15 Apr 24
🕹 Technology Software Programming Development Web Tools Open Source
  1. Bun is a simple tool for running Typescript scripts directly, making the process easy.
  2. You can add runtime flags to your scripts using the 'arg' package, allowing for inputs when the script runs.
  3. The setup involves creating a project directory, installing Bun and 'arg', and then running your code easily with flags.