With the core language library now written I could go about building the desired (delivery) runtimes. In this article within the series I will delve into my experience integrating the core language library with these chosen runtimes, documenting some of the challenges that I faced along the way.
After implementing santa-lang in TypeScript (Node) I wanted to explore rewriting the tree-walking interpreter in a lower-level systems language for efficiency and performance gains. My goal was to be able to run the entire Advent of Code 2022 calendar *quicker* than the Node variant. I settled on using Rust due to its blend of high and low level constructs, its vibrant package registry (Cargo), memory management model and previous enjoyable experience using the language. In this first article within the series, I will document how I went about organising the project and rewriting the core language within Rust.
The Parkrun Alphabet is an unofficial challenge that sees runners complete a Parkrun at locations starting with each letter of the English alphabet. I am a big fan of the Parkrun and wanted to work out how feasible it would be for me to complete the challenge based on the closest tourist locations to my local weekly run. I also thought this would be a great opportunity to explore pandas and work with DataFrames.
Large-language models (OpenAI/ChatGPT in particular) are all the rage at the moment, and like many developers I am interested at exploring what is possible with this new technology. This article documents the use of LangChain Agents/Tools to help aid in answering questions based on recent NBA events.
Large-language models (OpenAI/ChatGPT in particular) are all the rage at the moment, and like many developers I am interested at exploring what is possible with this new technology. This article documents my experience exploring how to implement Q&A Retrieval Augmented Generation (RAG) using LangChain and Postgres (using the pgvector extension).