Category: software-engineering
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Layered Architecture for Building Readable, Robust, and Extensible Apps
Layered Architecture for Building Readable, Robust, and Extensible Apps If adding a feature feels like open-heart surgery on your codebase, the problem isn’t bugs, it’s structure. This article shows how better architecture reduces risk, speeds up change, and keeps teams moving. The post Layered Architecture for Building Readable, Robust, and Extensible Apps appeared first on…
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Ray: Distributed Computing For All, Part 2
Ray: Distributed Computing For All, Part 2 Deploying and running Python code on cloud-based clusters The post Ray: Distributed Computing For All, Part 2 appeared first on Towards Data Science. Thomas Reid Go to original source
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Ray: Distributed Computing for All, Part 1
Ray: Distributed Computing for All, Part 1 From single to multi-core on your local PC and beyond The post Ray: Distributed Computing for All, Part 1 appeared first on Towards Data Science. Thomas Reid Go to original source
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Personal, Agentic Assistants: A Practical Blueprint for a Secure, Multi-User, Self-Hosted Chatbot
Personal, Agentic Assistants: A Practical Blueprint for a Secure, Multi-User, Self-Hosted Chatbot Build a self-hosted, end-to-end platform that gives each user a personal, agentic chatbot that can autonomously vector-search through files that the user explicitly allows it to access. The post Personal, Agentic Assistants: A Practical Blueprint for a Secure, Multi-User, Self-Hosted Chatbot appeared first…
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AI Engineering and Evals as New Layers of Software Work
AI Engineering and Evals as New Layers of Software Work How to maintain reliability in inherently stochastic systems The post AI Engineering and Evals as New Layers of Software Work appeared first on Towards Data Science. Clara Chong Go to original source
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Reducing Time to Value for Data Science Projects: Part 4
Reducing Time to Value for Data Science Projects: Part 4 Embrace your inner software developer The post Reducing Time to Value for Data Science Projects: Part 4 appeared first on Towards Data Science. Kristopher McGlinchey Go to original source
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Automated Testing: A Software Engineering Concept Data Scientists Must Know To Succeed
Automated Testing: A Software Engineering Concept Data Scientists Must Know To Succeed Why you should read this article Most data scientists whip up a Jupyter Notebook, play around in some cells, and then maintain entire data processing and model training pipelines in the same notebook. The code is tested once when the notebook was first…
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Software Engineering in the LLM Era
Software Engineering in the LLM Era On growing new software engineers, even when it’s inefficient The post Software Engineering in the LLM Era appeared first on Towards Data Science. Stephanie Kirmer Go to original source
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Mobile App Development with Python
Mobile App Development with Python Build iOS & Android Apps with Kivy The post Mobile App Development with Python appeared first on Towards Data Science. Mauro Di Pietro Go to original source
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Get Started with Rust: Installation and Your First CLI Tool – A Beginner’s Guide
Get Started with Rust: Installation and Your First CLI Tool – A Beginner’s Guide Rust has become a popular programming language in recent years as it combines security and high performance and can be used in many applications. It combines the positive characteristics of C and C++ with the modern syntax and simplicity of other…
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The Shape‑First Tune‑Up Provides Organizations with a Means to Reduce MongoDB Expenses by 79%
The Shape‑First Tune‑Up Provides Organizations with a Means to Reduce MongoDB Expenses by 79% TL;DR A fast‑growing SaaS woke up to a silent auto‑scale from M20 → M60, adding 20 % to their cloud bill overnight. In a frantic 48‑hour sprint we: flattened N + 1 waterfalls with $lookup , tamed unbounded cursors with projection,…
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How to Optimize your Python Program for Slowness
How to Optimize your Python Program for Slowness Also available: A Rust version of this article. Everyone talks about making Python programs faster [1, 2, 3], but what if we pursue the opposite goal? Let’s explore how to make them slower — absurdly slower. Along the way, we’ll examine the nature of computation, the role of memory,…
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Nine Pico PIO Wats with Rust (Part 2)
Nine Pico PIO Wats with Rust (Part 2) This is Part 2 of an exploration into the unexpected quirks of programming the Raspberry Pi Pico PIO with Micropython. If you missed Part 1, we uncovered four Wats that challenge assumptions about register count, instruction slots, the behavior of pull noblock, and smart yet cheap hardware.…
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Forget About Cloud Computing. On-Premises Is All the Rage Again
Forget About Cloud Computing. On-Premises Is All the Rage Again Ten years ago, everybody was fascinated by the cloud. It was the new thing, and companies that adopted it rapidly saw tremendous growth. Salesforce, for example, positioned itself as a pioneer of this technology and saw great wins. The tides are turning though. As much…
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Manage Environment Variables with Pydantic
Manage Environment Variables with Pydantic Introduction Developers work on applications that are supposed to be deployed on some server in order to allow anyone to use those. Typically in the machine where these apps live, developers set up environment variables that allow the app to run. These variables can be API keys of external services,…
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How to Pick Between Data Science, Data Analytics, Data Engineering, ML Engineering, and SW…
How to Pick Between Data Science, Data Analytics, Data Engineering, ML Engineering, and SW… Make the right choice for YOU Continue reading on Towards Data Science » Marina Wyss – Gratitude Driven Go to original source
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Machine Learning: From 0 to Something
Machine Learning: From 0 to Something How I learned ML foundations to tackle a complex problem Continue reading on Towards Data Science » Ricardo Ribas Go to original source
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Measuring the Cost of Production Issues on Development Teams
Measuring the Cost of Production Issues on Development Teams Deprioritizing quality sacrifices both software stability and velocity, leading to costly issues. Investing in quality boosts speed and outcomes. Image by the author. (AI generated Midjourney) Investing in software quality is often easier said than done. Although many engineering managers express a commitment to high-quality software,…
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How to Solve a Simple Problem With Machine Learning
How to Solve a Simple Problem With Machine Learning A technical walkthrough of lesson one Continue reading on Towards Data Science » Oscar Leo Go to original source