How to install Python Libraries in Visual Studio Code

Learn how to easily install Python libraries in Visual Studio Code with our step-by-step guide. Boost your coding efficiency today!

Python stands as one of the most popular programming languages today, largely due to its vast ecosystem of libraries that simplify complex tasks. Python libraries are collections of pre-written code providing ready-made functionality for specific tasks, from data analysis and visualization to machine learning and web development. They enhance efficiency by eliminating the need to write repetitive code. This guide will walk you through the process of setting up your Python environment in Visual Studio Code and installing these essential libraries.

Installing Python Libraries in Visual Studio Code

To successfully install Python libraries within Visual Studio Code, follow these detailed steps:

1] Install Python on Your Computer

The foundational step is to install Python itself on your system.

• Crucial Step: During the installation process, it is critical to tick the "Add Python to PATH" option. This ensures that Python's executable is accessible from your command line, which is necessary for subsequent steps.
• After the installation is complete, proceed to the next step.

2] Download and Install Visual Studio Code

Visual Studio Code (VS Code) is a free, powerful Integrated Development Environment (IDE) developed by Microsoft.

• Download and Install: Go to the official Visual Studio Code website and download the installer for your operating system. Follow the on-screen instructions to complete the installation.

3] Configure Python Environment

With both Python and VS Code installed, the next step is to configure your Python environment within the IDE.

• Install Python Extension in VS Code:

• Open Visual Studio Code.
• Click on the Extensions icon in the Activity Bar on the side (it looks like four squares, one detached).
• In the Extensions marketplace search bar, type "Python."
• Look for the official "Python" extension published by Microsoft and click "Install." This extension provides rich support for Python development in VS Code.

• Create a Virtual Environment:

  Creating a virtual environment is an optional but highly recommended practice. It provides an isolated environment for your project, ensuring that dependencies for one project don't conflict with those of another. This makes your projects self-contained and easily manageable.

• Open Your Project Folder: In VS Code, go to File > Open Folder... and select your project directory.
• Open Terminal: Click on Terminal > New Terminal in the VS Code menu.
• Verify Path: In the terminal, run the command pwd (or cd on Windows without arguments to show current directory). Ensure the displayed path is your project folder. If not, use cd followed by the correct path to navigate to your project directory.
• Create Virtual Environment: Once in the correct project location, run the following command in the terminal:

  Bash

  python -m venv env

  This command creates a new folder named env (a common convention) within your project directory. This env folder will contain your isolated virtual environment and all the Python libraries you install specifically for this project.

• Activate the Virtual Environment:

  Before installing libraries, you must activate the virtual environment to ensure they are installed within that isolated space.

  • Windows (PowerShell):

    PowerShell

    .envScriptsActivate.ps1

    If you encounter an error stating that running scripts is disabled on your system, you may need to adjust the execution policy for the current user. Run the following command in PowerShell as Administrator first (this is a one-time setup for your system):

    PowerShell

    Set-ExecutionPolicy RemoteSigned -Scope CurrentUser

    After setting the execution policy, try the activation command again: .envScriptsActivate.ps1.
  • Windows (Command Prompt):

    Bash

    envScriptsactivate.bat

  • macOS/Linux:

    Bash

    source env/bin/activate

  • Verification: Upon successful activation, you will see (env) (or the name you gave your virtual environment) appear in the prompt before the path in your terminal, indicating that the virtual environment is active.

4] Start Installing Libraries

With your Python environment configured and activated, you can now easily install libraries using PIP (Pip Installs Packages), Python's standard package manager. PIP allows you to install, upgrade, and manage Python libraries and packages with simple commands.

• General Installation Command:

  To install a single library, use the following command structure:

  
  

  
  

  Bash
  

  
  

  
  

  pip install <library_name>

• Common and Useful Python Libraries (with installation commands):

  • Numpy: For numeric calculation and efficient array manipulation.
    • Installation Command: pip install numpy
  • Pandas: For powerful data analysis and manipulation, especially with tabular data.
    • Installation Command: pip install pandas
  • Matplotlib: For creating static, interactive, and animated visualizations in Python (plots and graphs).
    • Installation Command: pip install matplotlib
  • Requests: For making HTTP requests and seamlessly working with web APIs.
    • Installation Command: pip install requests
  • TensorFlow: A comprehensive open-source library for machine learning, deep learning, and AI projects.
    • Installation Command: pip install tensorflow

• Verify Installation: After installing libraries, you can run pip list in your active terminal to see a list of all installed packages within your current virtual environment, confirming successful installation.

• Bulk Installation using a Requirements File:

  For larger projects, or when sharing your project with others, it's common practice to list all required libraries in a file for bulk installation.

• Create requirements.txt: In your project's root directory, create a new file named requirements.txt (or libraries.txt as per the example).
• Populate the File: Add the name of each required library and its specific version (highly recommended for reproducibility) on a new line.
  

  
  

  
  

  numpy==1.23.5 pandas==1.5.1 requests==2.28.1 tensorflow==2.11.0 matplotlib==3.6.2

• Install from File: In your activated virtual environment terminal, run the following command:
  

  
  

  Bash
  

  
  

  
  

  pip install -r requirements.txt

  (Replace requirements.txt with libraries.txt if that's what you named it).

By following these steps, you will be able to successfully set up your Python environment in Visual Studio Code and install its libraries, streamlining your development workflow.