The hottest Python Substack posts right now

And their main takeaways
Category
Top Technology Topics

Data Science Weekly - Issue 453

Data Science Weekly Newsletter • 19 implied HN points • 28 Jul 22
🕹 Technology Data science Machine Learning Python AI Deep Learning
  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.

Bloom Filters and Beyond: An Illustrated Introduction and Implementation

Confessions of a Code Addict • 5 HN points • 05 Sep 23
🕹 Technology Data Structures Programming Algorithms Python Applications
  1. Bloom filters are efficient data structures for quick searches in large datasets and minimize memory usage, with a probabilistic approach to determining membership
  2. Bloom filters use hash functions and bit vectors to store data item membership information while conserving memory by not storing actual items
  3. Counting Bloom Filters are an extension that allow item deletion but come with weaknesses such as handling hash collisions and counter overflow, providing an advanced data handling tool
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Week #6 - Python #2

Judson’s Substack • 5 implied HN points • 03 Jul 23
🕹 Technology Programming Python
  1. Object-Oriented Programming (OOP) is like creating blueprints and instances that can be reused.
  2. In Python, you can create classes with attributes like shape and flavor, and then create instances like my_cookie or your_cookie.
  3. The concept is similar to the Aristotelian distinction between universal (class/blueprint) and particulars (instances).

Once a Maintainer: David Wobrock

Once a Maintainer • 2 HN points • 20 Feb 24
🕹 Technology Open Source Programming Software Development Python Community
  1. David Wobrock got into programming due to his parents being involved in meteorology and him tinkering with terminal commands from an early age.
  2. Wobrock's journey into open source started during his studies, with his first major contribution being a Python plugin for Visual Studio.
  3. In the Django community, the maintenance work involves a core team, the Django Software Foundation, technical boards, and security boards, showcasing a structured and collaborative approach.

Building the machine learning interface

The Palindrome • 2 implied HN points • 22 Jan 24
🕹 Technology Machine Learning Programming Python Object Oriented Programming Frameworks
  1. Building a modular interface is crucial as machine learning models complexity increases.
  2. Transitioning from procedural to object-oriented programming can greatly enhance understanding and performance in machine learning.
  3. Good design is essential in setting the framework for machine learning models, drawing inspiration from PyTorch and scikit-learn.

Python Plotly Data Visuals: Dropdowns and Range Sliders For User Interaction

Data at Depth • 0 implied HN points • 23 Jul 23
🕹 Technology Data Visualization Python User Interaction
  1. Interactive data visualization can greatly improve data analysis and understanding of complex datasets.
  2. The Plotly library in Python provides tools like Range Sliders and Dropdown Menus for creating interactive graphs.
  3. Using features like Range Sliders and Dropdown Menus in Plotly can enhance the user experience and make graphs more engaging.

Ready-to-Use GPT-4 Prompts for Python Data Visualization

Data at Depth • 0 implied HN points • 14 Jul 23
🕹 Technology Data Visualization Python GPT-4
  1. Python is widely preferred by data professionals due to its powerful libraries for data visualization like matplotlib, seaborn, and plotly.
  2. GPT-4 can offer valuable benefits in Python data visualization as highlighted in 4 case study examples in the post.
  3. Readers can access more detailed information and a 7-day free trial by subscribing to Data at Depth.

The Atlantis (Old 9:30 Club) Spotify Playlist Automation

Expand Mapping with Mike Morrow • 0 implied HN points • 05 Apr 23
🕹 Technology Automation Python Spotify Data Analysis
  1. The author automated the process of creating a Spotify playlist featuring artists from a new music venue lineup in DC.
  2. They used Spotipy, a Python wrapper for the Spotify Web API, to compile songs from each artist's featured playlist.
  3. The biggest challenge faced during the process was getting the proper access code to work with the Spotify Web API.

Hello! Welcome to Overflow!

Overflow • 0 implied HN points • 28 Apr 23
🕹 Technology Software Engineering Python Docker Kubernetes Programming
  1. Rupesh Mishra is a software engineer with 8 years of experience working with Python, Django, PostgreSQL, MongoDB, AWS, Docker, and Kubernetes.
  2. Rupesh writes articles explaining complex technical concepts like memory management and object instantiation in Python in a simple and easy-to-understand manner.
  3. Rupesh's newsletter covers topics like Python, Docker, Kubernetes, MongoDB, PostgreSQL, Architecture Design, and Microservices, offering a course on Microservices, Docker, and Kubernetes.

Web Scraping from 0 to hero: our first scraper with Microsoft Playwright

The Web Scraping Club • 0 implied HN points • 04 Feb 24
🕹 Technology Web scraping Python Web Development Data Extraction
  1. The web scraping course provided by The Web Scraping Club is always free and appreciated if you want to subscribe with a paid plan.
  2. The choice between using Scrapy and Playwright for web scraping depends on factors like anti-bot protection and content loading.
  3. Setting up the environment for building a web scraper with Playwright involves installing Python, Playwright, and browser binaries.

[Zero To Python] Day 4 - Faking The Screens

Brian Knapp’s Newsletter • 0 implied HN points • 08 Mar 23
🕹 Technology Programming Software Development Prototyping Python Coding
  1. Faking screens in software development involves creating realistic-looking interfaces without complex functionality.
  2. Starting ugly in programming means quickly putting together something intentionally messy to learn and iterate faster.
  3. Use print statements and simple design elements to fake screens in your programming projects.

Redis-driven Dataflow for Clickstream Aggregation

Bytewax • 0 implied HN points • 19 Oct 23
🕹 Technology Data processing Python Containers
  1. Bytewax framework strikes a balance between being user-friendly without hiding underlying mechanisms.
  2. When writing custom connectors with Bytewax, focus on transforming messages in the `next_batch` method and delegate other processing to the dataflow.
  3. Consider the partitioned nature of inputs and utilize `list_parts` and `build_part` methods for handling multiple data streams in Bytewax.

Code vs. Cells

Reflective Software Engineering • 0 implied HN points • 08 Jun 23
🕹 Technology Coding Python Data Analytics Automation Problem Solving
  1. Modeling everyday problems using test-driven development with a Python tool instead of spreadsheets can lead to better results and easier adaptability.
  2. Creating simple Python tools with scripting languages can automate mundane tasks, improve problem-solving skills, and potentially lead to open-source contributions.
  3. Writing code can be enjoyable and effective in automating repetitive tasks, enhancing problem-solving abilities, and potentially growing into valuable tools for others.

So you want to code a convolution in Python - a bite-sized image processing with kernel

Curiosity-driven AI/ML Research Engineering • 0 implied HN points • 16 Feb 24
🕹 Technology Programming Image Processing Machine Learning Python AI
  1. Images are represented as pixels, each containing information about red, green, and blue colors (RGB) within the range of 0 to 255.
  2. Implementing a convolution in Python involves using NumPy arrays and Pillow to manipulate images effectively.
  3. Convolution implementation requires traversing the image pixel by pixel, extracting image slices, computing new pixel values using kernels, and ensuring to handle all three color channels in the output.

Switching Gears To AI Agents

Eddie's startup voyage • 0 implied HN points • 15 Apr 24
🕹 Technology AI Software Python Development Learning
  1. Eddie is shifting focus to AI Agents after leaving his previous company, EnVsion, and finding a passion for AI technology.
  2. AI Agents in agentic systems are AI models tasked with specific roles and responsibilities, contributing to the overall goal.
  3. Eddie is excited about building products with AI Agents, currently developing a Python AI Agent library for further learning and exploration.

Data Doc: How GPT-4 Aced My First-Year Python Coding Assignment

Data at Depth • 0 implied HN points • 13 Nov 23
🕹 Technology AI Python Education
  1. GPT-4 has revolutionized the way Computer Science professors deliver and evaluate quality curriculum.
  2. There is a need for a re-design in Computer Science curriculum and evaluation based on advancements like GPT-4.
  3. The integration of advanced technologies like GPT-4 can significantly impact the educational landscape, requiring adaptations in teaching methods.

GPT-4 Code Interpreter: Your Magic Wand for Instant Python Data Visuals

Data at Depth • 0 implied HN points • 24 Jul 23
🕹 Technology Data science Python Data Visualization
  1. GPT-4 Code Interpreter generates data visualization code instantly, allowing users to upload a data file, clean it, load it into a data frame, and display the results.
  2. Users can try GPT-4 Code Interpreter with a 7-day free trial by subscribing to Data at Depth.
  3. John Loewen's post explores a case study example using UN population projection data, showcasing the features and capabilities of the GPT-4 Code Interpreter.

Interactive Python Data Visualization: Adding a Sexy Plotly Range Slider

Data at Depth • 0 implied HN points • 24 Jul 23
🕹 Technology Data Visualization Python Interactive
  1. Data visualization is essential in data analysis, and Python offers strong tools for creating interactive visualizations.
  2. Adding interactive elements to visualizations can greatly improve user engagement and understanding.
  3. Consider incorporating a Plotly range slider to enhance user interactivity in your Python data visualizations.