标签：#hack

Building StudySift Without Third-Party Dependencies Introduction What if a useful study tool could be built without installing a single third-party package? For the Zero Dependency Hackathon, I built StudySift , a command-line tool that converts lecture transcripts into structured, revision-friendly study notes. The idea is simple: give StudySift a transcript and automatically extract useful information such as keywords, definitions, examples, and important points. The interesting part was the constraint. The project had to run using Python's standard library only , with no third-party runtime dependencies. The Problem Lecture transcripts can be long and difficult to revise. Important definitions, examples, keywords, and important statements can be spread throughout the transcript. Students often have to manually read the entire transcript, identify important sentences, and create their own notes. I wanted to reduce this manual work. StudySift takes a text transcript as input and processes it into organized notes. The basic workflow is: Lecture Transcript ↓ StudySift ↓ ┌─────────────────┐ │ Definitions │ │ Important Points│ │ Examples │ │ Keywords │ └─────────────────┘ **What I Built** StudySift is a Python command-line tool. The user provides a transcript file: python src/main.py examples/lecture.txt StudySift processes the transcript through several stages: 1. Read the input file 2. Split the text into sentences 3. Extract words 4. Remove common words 5. Count word frequencies 6. Detect definitions 7. Detect examples 8. Identify important sentences 9. Score sentences 10. Sort sentences by importance 11. Generate structured notes The goal is not to pretend that a collection of simple rules is a complete natural-language understanding system. Instead, StudySift is a lightweight and transparent approach to turning transcripts into useful revision material. **The Zero-Dependency Challenge** The biggest constraint was that StudySift could not depend on third-party runt

I created a converter that turns HyperCard 2.x stacks into standalone HTML so they can run in a modern browser. I built it to share my own stacks from the early '90s, which have been sitting on old floppy images for 30 years. It's MIT-licensed and I'd welcome contributions - especially stacks that break the converter, since I've only tested it against my own. If you have old HyperCard files lying around, I'd love to hear how they fare.

I have a self playing piano, using a system called PianoDisc Protigy. They have an online store which sells music for their system, from various modern artists along with classics such as Bach and Beethoven. Last night I saw they had released some music from Eric Satre, a 19th century French composer, which I bought. Curious if I could have just used AI to create these files, I began experimenting with Astra and Fable. Feeding the output of one into the other to critique. After an hour of LLM di