The hottest Python Substack posts right now

And their main takeaways
Category
Top Technology Topics

A small set of special integers

Mostly Python • 524 implied HN points • 25 May 23
🕹 Technology Python
  1. Python uses optimization for smaller integers by pointing multiple variables to the same memory address
  2. For larger integers, Python creates new objects for each variable even if they have the same value
  3. Integer values from -5 through 256 are pre-loaded at startup for efficiency reasons

Testing a book's code, part 3: Testing a game

Mostly Python • 314 implied HN points • 25 Jan 24
🕹 Technology Python
  1. The post discusses testing a game project, Alien Invasion, which may seem challenging to test at first.
  2. Testing the book's code against different versions of Python is important to identify bugs and incompatibilities.
  3. Using tools like pyenv to switch between Python versions can make testing with different versions easier.

Top 10 Events 2024

Bytewax • 39 implied HN points • 18 Jan 24
🕹 Technology Python
  1. Top tech conferences in 2024 focus on AI, data science, ML, and Python.
  2. Events offer opportunities to learn, connect with peers, and expand skills.
  3. Attendees benefit from valuable insights, networking, and community engagement.
Get a weekly roundup of the best Substack posts, by hacker news affinity:

Using The GPT-4 Custom Instructions Tool To Optimize Python Data Visual Code Creation

Data at Depth • 39 implied HN points • 12 Jan 24
🕹 Technology Python
  1. The author, a computer science professor, has incorporated GPT-4 into data visualization creation workflow over the past 8 months.
  2. Significant improvements have been noticed in how GPT-4 manages data visualization requests.
  3. Data at Depth is a reader-supported publication that offers options for subscription to receive new posts and support the author's work.

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

Confessions of a Code Addict • 293 HN points • 06 Dec 23
🕹 Technology 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.

Four Essential Skills to Improve Your Python Data Visualization Workflow

Data at Depth • 19 implied HN points • 06 Apr 24
🕹 Technology Python
  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.

Modular Prompting GPT-4 For Interactive Multi-visual Python Dashboards: A Detailed Guide

Data at Depth • 39 implied HN points • 04 Jan 24
🕹 Technology Python
  1. The article discusses using GPT-4 to generate Python Plotly code for interactive data visuals in Python dashboards.
  2. The author shares their experience of how GPT-4 has significantly improved over 8 months in creating Python Plotly dashboard code.
  3. There's an opportunity to access the full post archives with a 7-day free trial subscription to 'Data at Depth.'

Interactive Maps and Plots With GPT-4 & Plotly Dash: A Story about UN Population Projections

Data at Depth • 39 implied HN points • 31 Dec 23
🕹 Technology Python
  1. Interactive maps and plots can now be created using GPT-4 and Plotly Dash, enhancing data visualization capabilities in Python.
  2. GPT-4's capacity to generate interactive Python Plotly dashboards has significantly improved in recent months, showcasing advancements in AI technology.
  3. Computer science professors have utilized GPT-4 to explore its Python data visualization code creation abilities, pushing the boundaries of AI in this field.

Why is there more than one way to end a while loop?

Mostly Python • 419 implied HN points • 14 Mar 23
🕹 Technology Python
  1. Programming languages may offer multiple ways to accomplish the same task for different use cases.
  2. Python emphasizes having one clear and obvious way to do things to promote readability and maintainability.
  3. Ending a while loop in Python can be done using the while statement, break statement, or a flag - each with its own unique advantages.

Launch of Conformal Prediction Book 🦫

Mindful Modeler • 59 implied HN points • 14 Feb 23
🚌 Education Python
  1. Conformal prediction can be combined with any uncertainty quantification method you already use, making it versatile and not restrictive.
  2. Conformal prediction is model-agnostic, meaning you can implement it without changing your existing models or user interface.
  3. One of the key advantages of conformal prediction is its guarantee of the true outcome coverage, making it a practical and useful addition to predictive modeling.

cppyy

Software Bits Newsletter • 206 implied HN points • 30 Apr 23
🕹 Technology Python
  1. Python is versatile for many tasks like web development and data science.
  2. Using C++ for compute-heavy tasks in Python can boost performance.
  3. Cppyy offers a simple way to integrate C++ code snippets into Python for performance improvements.

High Impact Python Streamlit: Beautiful Interactive Maps and Charts

Data at Depth • 5 HN points • 15 May 24
🕹 Technology Python
  1. Creating an interactive Streamlit dashboard can be done step by step with a modular approach, allowing users to select a year, view a global choropleth map, and see a horizontal bar chart of top 10 countries.
  2. By using Python libraries like Streamlit, Pandas, and Plotly Express, you can efficiently build interactive data visualizations for a dashboard project.
  3. Data preprocessing steps, such as filtering, cleaning, and extracting necessary information, are essential before visualizing data on the dashboard using tools like Plotly Express for map and chart creation.

The Anatomy of the Least Squares Method, Part Three

The Palindrome • 4 implied HN points • 11 Nov 25
🕹 Technology Python
  1. Using real data helps you understand the real-world quirks and problems that simulations can't show. It's like learning to drive in a car instead of a video game.
  2. Real data can reveal hidden patterns and insights about how things work, giving you a better chance to discover new information.
  3. Cleaning and transforming your data is crucial for accurate analysis. You need to tackle issues like outliers and non-normal distributions to get reliable results.

Faking OpenAI - Unit testing in the age of LLMs (Part Two)

Laszlo’s Newsletter • 27 implied HN points • 02 Mar 25
🕹 Technology Python
  1. Dependency Injection helps organize code better. This makes your testing process simpler and more modular.
  2. Faking and spying in tests allow you to check if your code works without relying on external systems. It gives you more control over your testing!
  3. Using structured testing techniques reduces mental load. It helps you focus on writing clean tests instead of remembering complicated mocking syntax.

Working with your git diffs

CodeFaster • 108 implied HN points • 05 Sep 23
🕹 Technology Python
  1. Ignore whitespace in git diffs using -w flag to reduce size and focus on content
  2. Filter diffs using filterdiff CLI tool to include or ignore specific files in your git diffs
  3. Convert git diff output to JSON for easier parsing using tools like diff-to-json or unidiff in Python

CI / CD for Data Engineering (Python)

The Orchestra Data Leadership Newsletter • 19 implied HN points • 22 Oct 23
🕹 Technology Python
  1. Understanding basic CI / CD for Python code in a Data Engineering context is crucial for Data Engineering Leaders.
  2. For unit tests, use pytest to ensure functions work correctly, and for integration tests, test connections to third-party APIs.
  3. Implementing CI / CD involves writing code, testing and linting locally, and then deploying to a merge environment to ensure code compatibility.

TIL 1: Running coqui-ai/TTS on my M2

Omar’s Newsletter • 19 implied HN points • 18 May 23
🕹 Technology Python
  1. The user successfully ran Coqui-ai's TTS library on their M2 MacBook after debugging some Python code.
  2. The issue was related to the M2 chip on the laptop, causing a memory error and program crash.
  3. By using Python's built-in debugger and modifying a specific line of code, the user was able to fix the error and run the program successfully.

Interactive Mapping Tutorial With Python: Visualizing US Education Trends

Data at Depth • 19 implied HN points • 08 Jun 23
🕹 Technology Python
  1. Data visualization skills are crucial for modern data analysis, and mapping skills are a valuable addition to visualization abilities.
  2. Python libraries like Folium, Plotly, and Dash can be used for effective display of data.
  3. Interactive mapping tutorials using Python can help in visualizing US education trends with tools like Folium, Plotly, and Dash.

#OpenSourceDiscovery 79: PentestGPT

#OpenSourceDiscovery • 19 implied HN points • 18 Jun 23
🕹 Technology Python
  1. PentestGPT is a GPT-powered pen testing tool that guides users through steps in an interactive mode.
  2. PentestGPT is safer than AutoGPT and focuses on user interaction rather than executing commands automatically.
  3. PentestGPT has some bugs and token limit issues but can be a great learning tool for penetration testing with potential improvements in the future.

Getting Responses to Questions from Azure Open AI ChatGPT in a CMD Window

Rod’s Blog • 19 implied HN points • 19 Apr 23
🕹 Technology Python
  1. The author has been exploring Azure Open AI ChatGPT and its security implications, highlighting the importance of understanding security when implementing new technologies.
  2. A simple command-line Chatbot utilizing external files for configuration data and questions was created to demonstrate the possibilities with Azure Open AI ChatGPT.
  3. To use the command-line Chatbot, access to Azure Open AI, Python, and specific Python libraries is required.

Java, when to love it & when to not

Shivam’s Substack • 2 HN points • 24 Jun 24
🕹 Technology Python
  1. Understanding Java's paradigms like OOP principles can make you a more careful, skilled programmer over time.
  2. Java can be great for creating stable, reliable code that handles last-minute changes well.
  3. Choosing between Java and Python depends on the task: Java for reliability and Python for quicker idea realization and fun projects.

Math, Where are the static types?

Ron Friedhaber • 3 HN points • 26 May 24
🔬 Science Python
  1. Math notation focuses on simplification, not optimization, unlike in computer programming where efficiency is crucial.
  2. In math, statements are mostly immutable and remain so until proven true, contrasting with programs that are mutable to accommodate bugs and user requests.
  3. Python initially succeeded with dynamic typing for prototyping but has gradually shifted towards typed Python, reflecting a broader trend in the language's evolution.

The Nerdiest Possible Way to Make Sourdough

Tim's Tech Things • 2 HN points • 09 May 24
🕹 Technology Python
  1. Creating a healthy sourdough starter involves feeding it with flour and water until it's ready to use in baking, which contributes to the delicious taste and texture of the bread.
  2. Monitoring the rise of sourdough starter is crucial to ensure there are enough active yeast cells to create CO2 bubbles, which make the bread light and fluffy.
  3. Using computer vision with Python, ffmpeg, and algorithms like rolling averages and derivatives can help automate the process of determining when sourdough is ready for baking.

Why and How Does Python Use Bloom Filters in String Processing?

Confessions of a Code Addict • 46 HN points • 14 Sep 23
🕹 Technology Python
  1. Python uses Bloom filters in its string data structure to speed up certain string processing functions like strip and splitlines.
  2. The unique Bloom filter implementation in CPython uses an unsigned long type to represent the bit vector, making storing and querying items more efficient.
  3. CPython determines the position in the bit vector for adding and querying characters by using the lower n-bits of the character, avoiding costly hash computations.

Data Science Weekly - Issue 453

Data Science Weekly Newsletter • 19 implied HN points • 28 Jul 22
🕹 Technology Python
  1. Creating a focused GitHub repository can help others in the field, like those working with satellite images and deep learning.
  2. There are unique Python packages available that can enhance your data workflow, making tasks easier and more efficient.
  3. Understanding the technology behind AI and how to use it effectively is crucial for building better models and systems.