spacy

name	spacy
description	spaCy NLP library with pipelines. Use for text processing.

spaCy

spaCy is "Industrial Strength" NLP. Unlike NLTK (academic), spaCy focuses on providing the best single algorithm for a task. v3.8 supports Python 3.13.

When to Use

• NER (Named Entity Recognition): Extracting person names, dates, orgs.
• Parsing: Dependency parsing to understand sentence structure.
• Speed: Cython-optimized pipelines.

Core Concepts

Pipeline

Tokenizer -> Tagger -> Parser -> NER.

Doc / Token / Span

The core data structures. Efficient memory usage.

Prodigy

The annotation tool (paid) from the same creators, tightly integrated.

Best Practices (2025)

Do:

• Use Transformer pipelines: en_core_web_trf (Roberta-based) for high accuracy.
• Use nlp.pipe(): For batch processing huge texts.

Don't:

• Don't use for GenAI: spaCy is for structure extraction, not text generation (LLMs).

References

• spaCy Documentation