pylsl is a Python binding for the Lab Streaming Layer (LSL), a real-time network protocol for exchanging time-series data, primarily used in neuroscience and biomedical research. The library provides a clean, ctypes-based interface to the native liblsl C library, exposing classes for stream declaration (StreamInfo), data output (StreamOutlet), data input (StreamInlet), and network discovery (resolve_streams, ContinuousResolver). The codebase is well-structured with thorough error handling, graceful degradation for older liblsl versions, and comprehensive test coverage. It includes a micro-benchmarking suite for measuring ctypes call overhead and data conversion costs. The library is actively maintained, with CI/CD pipelines, platform-specific wheels bundling liblsl, and support for Python 3.10–3.13.
CATMAID (Collaborative Annotation Toolkit for Massive Amounts of Image Data) is a full-stack web application for collaborative connectomics research. It enables neuroscientists to trace neuron skeletons, annotate synapses, and analyze neural circuits across massive image stacks. The backend is a Django monolith with a REST API, PostgreSQL/PostGIS database, Celery for async tasks, and WebSockets for real-time collaboration. The frontend is a large JavaScript codebase using jQuery, Three.js, Pixi.js, D3, and custom widget system. Key features include skeleton tracing tools, 3D visualization, NBLAST neuron similarity, connectivity matrices, and review workflows. The codebase is well-structured with many reusable client-side utilities (event system, command pattern, caching, settings manager) and demonstrates strong engineering practices with CI/CD, tests, and Docker deployment. However, it carries some technical debt from vendored libraries and complex database migrations.