How to Install SpaCy for Python in VS Code | NLP & Text Processing Guide

Want to build powerful Natural Language Processing (NLP) applications? 🚀 SpaCy is one of the fastest and most efficient NLP libraries in Python, used for text analysis, named entity recognition (NER), tokenization, dependency parsing, and machine learning tasks.

In this guide, you'll learn how to install and set up SpaCy in VS Code to process text, extract insights, and power AI-driven applications!

1️⃣ Install Python & VS Code (Skip if already installed)
2️⃣ Install SpaCy Library in VS Code

📌 Open VS Code Terminal (Ctrl + `)
Run the following command:
pip install spacy

3️⃣ Verify installation:
pip show spacy

💡 In this tutorial, you will learn:
✔️ How to install SpaCy in VS Code 📌
✔️ Perform text tokenization & lemmatization 🔡
✔️ Extract Named Entities (NER) 🏷️
✔️ Use dependency parsing & POS tagging 🌐
✔️ Process large-scale text data for AI & ML 📊
✔️ Best practices for NLP in Python ✅

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#SpaCy #Python #NLP #MachineLearning #AI #TextProcessing #NaturalLanguageProcessing #DeepLearning #DataScience #DataAnalysis #NER #TextMining #AIApplications #Automation #PythonTutorial #ArtificialIntelligence #Tokenization #DependencyParsing #VSCode

[irzalamru]

Using cached spacy-3.8.2.tar.gz (1.3 MB)
Installing build dependencies ... error
error: subprocess-exited-with-error

× pip subprocess to install build dependencies did not run successfully.
│ exit code: 1
╰─> [143 lines of output]
Ignoring numpy: markers 'python_version < "3.9"' don't match your environment