📦 Pip & Dependencies — Managing Python Packages

Pip is Python's package manager. It lets you download and install packages from PyPI (Python Package Index) and manage your project dependencies.

🎯 Installing Packages with Pip

Pip is the standard tool for installing Python packages.

# Basic install
pip install requests

# Install specific version
pip install numpy==1.21.0

# Install multiple packages
pip install flask django pytest

# Install with version constraints
pip install "pandas>=1.0,<2.0"

# Upgrade installed package
pip install --upgrade requests
pip install -U requests  # Shorthand

💡 Common Pip Commands

Finding packages:

# Search for a package
pip search flask  # (deprecated, use PyPI website instead)

# Show package information
pip show numpy
# Output:
# Name: numpy
# Version: 1.21.0
# Location: /usr/local/lib/python3.9/site-packages

Viewing installed packages:

# List all installed packages
pip list

# List with specific format
pip list --format=json

# Check if a package is installed
pip show pandas

Uninstalling packages:

# Remove a package
pip uninstall requests

# Remove multiple packages
pip uninstall flask django pytest

# Uninstall without confirmation
pip uninstall -y requests

📋 Requirements Files

Manage dependencies with `requirements.txt`.

Creating requirements.txt:

# Generate from current environment
pip freeze > requirements.txt

# Manual format
flask==2.0.1
requests>=2.26.0
pytest>=6.2.0
numpy>=1.20.0
pandas>=1.2.0

Using requirements.txt:

# Install all dependencies
pip install -r requirements.txt

# Install dev dependencies
pip install -r requirements-dev.txt

# Install with constraints
pip install -r requirements.txt --upgrade

Different requirements files:

project/
├── requirements.txt           # Core dependencies
├── requirements-dev.txt       # Development tools
├── requirements-test.txt      # Testing tools
└── requirements-prod.txt      # Production settings

requirements.txt:

flask==2.0.1
sqlalchemy==1.4.0
requests>=2.26.0

requirements-dev.txt:

-r requirements.txt    # Include core requirements
pytest==6.2.0
black==21.7b0
flake8==3.9.0
pytest-cov>=2.12.0

# Install production dependencies
pip install -r requirements.txt

# Install development dependencies
pip install -r requirements-dev.txt

🏗️ Virtual Environments

Use virtual environments to isolate project dependencies.

# Create virtual environment
python -m venv venv

# Activate (macOS/Linux)
source venv/bin/activate

# Activate (Windows)
venv\Scripts\activate

# Install packages in virtual environment
pip install flask requests

# Deactivate virtual environment
deactivate

Why virtual environments?

# Without venv: packages conflict
# Project A needs: flask==1.0
# Project B needs: flask==2.0
# Can't have both installed globally!

# With venv: each project isolated
project_a/venv/  # has flask==1.0
project_b/venv/  # has flask==2.0
# Both work simultaneously!

📊 Project Setup Example

myproject/
├── venv/                    # Virtual environment (don't commit!)
├── src/
│   └── myapp/
│       ├── __init__.py
│       └── main.py
├── tests/
│   └── test_main.py
├── requirements.txt
└── README.md

setup.sh:

#!/bin/bash

# Create and activate virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Run application
python src/myapp/main.py

💻 Using Installed Packages

# After pip install requests
import requests

response = requests.get("https://api.example.com")
data = response.json()

# After pip install numpy
import numpy as np

array = np.array([1, 2, 3, 4, 5])
mean = np.mean(array)

# After pip install flask
from flask import Flask, jsonify

app = Flask(__name__)

@app.route("/api/data")
def get_data():
    return jsonify({"message": "Hello, World!"})

if __name__ == "__main__":
    app.run(debug=True)

🔄 Version Specifiers

Control which versions of packages are installed.

# Exact version
pip install numpy==1.21.0

# Greater than or equal
pip install "pandas>=1.2.0"

# Less than
pip install "flask<3.0"

# Range
pip install "requests>=2.26.0,<3.0"

# Compatible release
pip install "django~=3.2"  # >= 3.2, < 4.0

# Any version
pip install numpy

🎨 Practical Dependency Examples

Data Science Project:

# requirements.txt
numpy==1.21.0
pandas==1.3.0
matplotlib==3.4.2
scikit-learn==0.24.2
jupyter==1.0.0

Web Application:

# requirements.txt
flask==2.0.1
sqlalchemy==1.4.0
flask-sqlalchemy==2.5.1
flask-cors==3.0.10
python-dotenv==0.19.0
gunicorn==20.1.0

# requirements-dev.txt
-r requirements.txt
pytest==6.2.0
black==21.7b0
flake8==3.9.0

Testing Setup:

# requirements-test.txt
pytest==6.2.0
pytest-cov==2.12.0
pytest-xdist==2.3.0
hypothesis==6.13.1

⚠️ Common Issues

Issue 1: "No module named 'x'"

# ❌ Package not installed
python my_script.py  # Error: ModuleNotFoundError

# ✅ Install the package
pip install requests

# Verify in virtual environment
which python  # Should show venv/bin/python

Issue 2: Version Conflicts

# ❌ Package requires different version
pip install "numpy>=1.20" "numpy<1.21"

# ✅ Use compatible versions
pip install "numpy>=1.20,<2.0"

# Or check compatibility
pip check

Issue 3: Frozen Dependencies

# ❌ requirements.txt with no versions
flask
requests

# ✅ Pin versions for reproducibility
pip freeze > requirements.txt
# Creates exact versions:
# flask==2.0.1
# requests==2.26.0

🔑 Key Takeaways

• ✅ Use `pip install package_name` to install packages

• ✅ Use `requirements.txt` to manage dependencies

• ✅ Use virtual environments to isolate projects

• ✅ Pin versions in requirements.txt for reproducibility

• ✅ Use `pip freeze` to capture current environment

• ✅ Check compatibility with `pip check`

• ✅ Always activate virtual environment before installing

Ready to practice? Challenges | Quiz