EmbeddingGemma 2: an open, lightweight multimodal embedding model
deepmind.google·6d ago
AI Engineering
Lobsters·Aug 21·5 min read
Better Batteries
TL;DR
The discussion around Python's standard library highlights that the real issue is not its size but the inconsistent quality of its modules. Some modules fail to adhere to established naming conventions, leading to confusion among developers.
✦ Why It Matters
Review your use of Python's standard library modules to ensure they meet naming conventions and quality standards.
Key Takeaways
- Assess the quality of your standard library's APIs regularly.
- Adopt naming conventions to enhance consistency.
- Learn from Go's approach to API design.
- Address organizational challenges to improve library development.
Full Summary
Programming languages often debate whether their standard libraries should be minimal or comprehensive. However, the real concern lies in the quality and consistency of the APIs provided.
Python's standard library is criticized for its uneven quality, with some modules not adhering to naming conventions, yet this flexibility has allowed it to thrive in data science. In contrast, Go's standard library is praised for its well-designed APIs, thanks to the team's institutional capacity.
Rust's 1.0 standard library is noted for its brilliance, particularly in collections and iterators, but it struggles with executing new design decisions due to organizational challenges. This highlights the importance of not just having a comprehensive library but ensuring that it is well-maintained and designed.