gensim

Why we included this project

Gensim has long been the Python library people reach for when they need topic models or word embeddings without standing up a deep-learning stack. Its algorithms stream over the corpus, so collections far larger than RAM are workable, and the multicore implementations of LDA, LSA, and HDP make it a practical tool for clustering and similarity search on large text sets. It is also a common fixture in NLP coursework and research pipelines, backed by extensive documentation and notebook tutorials. One thing to know: the project is in stable maintenance mode, so bugs and documentation fixes still land, but new features are not being added. Treat it as a proven, well-documented library rather than an evolving one.