Learn SPACY with Real Code Examples

Install Python 3.8+

Install spaCy via pip: pip install spacy

Download a model: python -m spacy download en_core_web_sm

Verify installation: import spacy; nlp = spacy.load('en_core_web_sm')

Set up IDE or Jupyter Notebook for experimentation

Install Python 3.8+

Install spaCy via pip or conda

Set up Jupyter Notebook or IDE

Download required pre-trained models

Verify by processing sample text

main.py / notebook.ipynb

data/ - raw text corpora

utils/ - preprocessing helpers

models/ - trained pipelines and components

notebooks/ - experimentation and prototyping

python main.py - run script

pip install spacy - install library

python -m spacy download en_core_web_sm - download model

python -m spacy validate - check model compatibility

jupyter notebook - interactive experiments

Supports Unicode text

Handles multiple languages and models

Integrates with global NLP datasets

Supports locale-specific preprocessing

Compatible with multilingual ML pipelines

Cross-platform: Windows, macOS, Linux

Open-source and free

Documentation and community widely available

Beginner-friendly tutorials and examples

Supports multiple languages and scripts

DisplaCy for visualizing entities and dependencies

Integrate with Jupyter Notebook for rich display

Highlight entities and tokens

Visualize syntactic trees and relations

Render text with annotations in dashboards

Track processed Doc objects

Store custom pipeline components

Manage model weights and vectors

Log preprocessing and analysis steps

Version control for pipelines and models

Organize raw and cleaned text corpora

Annotate text for NER or classification

Store processed Doc objects efficiently

Manage custom training datasets

Export processed data for downstream tasks