Programming Digest - Text Editor Data Structures
#527 – June 19, 2023 | View in browser |
Programming Digest
Text editors can be an interesting challenge to program. The types of problems that text editors need to solve can range from trivial to mind-bogglingly difficult. Recently, I have been on something of a spiritual journey to rework some internal data structures in an editor I have been building, specifically the most fundamental data structure to any text editor.
Modern Guide to OAuth 2.0 (sponsor)
Most OAuth guides lack modern, practical examples. So that's why we put together this guide that covers the real-world use cases and it even includes a sample application repo so you can see working code. It’s based on client conversations and our experience building FusionAuth, a ten million+ downloaded OAuth server. Start reading now.
Real-time experience makes the platform feel like a place of activity for the clients. Live commenting is a feature that allows clients to publish real-time comments on live videos. The live comments are usually a mixture of feedback from the clients on the live video or casual conversations between clients.
The modern way of serving images
All-in-one guide for responsive & performant images and the introduction of the 'boolean' image tag in HTML.
Rank is a fundamental operation for Succinct Data Structures. It counts the number of set bits up to a given index in a bit array. How can this be done in constant time and sub-linear space?
Understanding DeepMind's Sorting Algorithm
Working code examples meant to clarify AlphaDev's deep learning assembly optimizations.
Boost your productivity as a developer! Join Adam Fortuna, Founder of Hardcover, in an exclusive talk on Rails, Next.js, and Hasura architecture. Discover how they saved countless hours and unlocked the power of a public API. Register now!
Improving Performance with HTTP Streaming
How HTTP Streaming can improve page performance and how Airbnb enabled it on an existing codebase.
Large language models such as GPT-3/4, LLaMA and PaLM work in terms of tokens. They take text, convert it into tokens (integers), then predict which tokens should come next.
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