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Rouwel Ngacha
Rouwel Ngacha

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How the python package installer works

#tutorial #beginners #python

My first encounter with pip was trying to run a Python script that imported the requests library, only to be met with an import error. The fix turned out to be straightforward: using pip, Python's package installer.

To use pip, you need to have Python installed on your system. The basic command to install any library is:

pip install <package-name>
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Best Practice: Using a Virtual Environment (venv)

Before installing packages everywhere, it’s best to create an isolated workspace for your project called a virtual environment. This keeps package dependencies for different projects separate so they don't clash with each other or your system's main Python installation.

1. Create the environment

Open your terminal in your project directory and run:

python -m venv venv
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(This creates a folder named venv containing a standalone copy of Python and pip.)

2. Activate the environment

Before installing anything, activate it:

  • Windows: 
  venv\Scripts\activate
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  • macOS / Linux: 
  source venv/bin/activate
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Once activated, your terminal prompt will show (venv) at the beginning. Any pip install commands you run now will stay inside this isolated environment.

Bulk Installing Dependencies with requirements.txt

When you're running a Python script with multiple required packages, installing them one by one gets tedious. You can streamline this process by bulk installing everything at once using a requirements file.

Step 1: Create a requirements.txt file

Create a standard text file named requirements.txt in your project folder and list all your dependencies, one per line:

requests
pandas
numpy
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Step 2: Run the bulk install command

With your virtual environment active, run:

pip install -r requirements.txt
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Specifying Package Versions

Sometimes, the newest version of a library breaks compatibility with other packages in your project. To prevent this, you can specify exact version numbers directly inside your requirements.txt:

requests==2.31.0
pandas>=2.0.0
numpy<=1.24.0
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  • == installs an exact version.
  • >= or <= sets a minimum or maximum allowed version.

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