📘 Day 21: Virtual Environments - Professional Project Management

As you work on more complex projects, you'll find they have different requirements. Project A might need an older version of a library, while Project B needs the latest version. Installing everything globally on your computer leads to conflicts.

The professional solution is to use virtual environments.

What is a Virtual Environment?

A virtual environment is an isolated, self-contained directory that holds a specific version of Python plus all the specific packages and libraries required for a particular project. Think of it as a clean, separate workspace for each project.

This is a critical best practice for any serious Python development because it makes your projects:

• Isolated: Prevents package versions from clashing between projects.
• Reproducible: Allows anyone to recreate the exact same environment your project needs to run correctly.

How it Works: venv and requirements.txt

The main README.md file for this entire repository now contains the standard setup instructions for this project, which includes creating a virtual environment and installing the project's dependencies.

The key commands, which you should run from your terminal, are:

1. Create Environment: python3 -m venv venv

2. This creates a venv folder in your project directory.

3. Activate Environment:

4. macOS/Linux: source venv/bin/activate

5. Windows: venv\\Scripts\\activate

6. Your terminal prompt will change to show (venv), indicating it's active.

7. Install Packages: pip install -r requirements.txt

8. This command reads the requirements.txt file and installs the exact versions of all necessary packages into your active venv.

9. Deactivate Environment: deactivate

10. When you're done, this command returns you to your normal shell.

💻 Exercises: Day 21

This lesson is about terminal commands, not Python scripts. The best way to learn is by doing.

1. Create a New Project:

2. On your computer, create a new folder called my_test_project.

3. Navigate into it using cd my_test_project.

4. Initialize and Activate:

5. Create a new virtual environment inside it: python3 -m venv my_env.

6. Activate the new environment.

7. Install and Freeze:

8. Install a package that is not in our main project, for example: pip install "cowsay==5.0".

9. Generate a requirements.txt file for this new project using the pip freeze command. Open the file and see that cowsay is listed.

10. Deactivate and Clean Up:

11. Deactivate the environment. You can now delete the my_test_project folder.

🎉 Congratulations! You've practiced one of the most important skills for professional Python development. Using virtual environments will save you from countless headaches and make your projects more robust and shareable.

Previous: Day 20 – Day 20: Python Package Manager (pip) & Third-Party Libraries • Next: Day 22 – Day 22: NumPy - The Foundation of Numerical Computing

You are on lesson 21 of 108.

Additional Materials

• solutions.ipynb 📁 View on GitHub 🚀 Run in Google Colab ☁️ Run in Binder
• virtual_environments.ipynb 📁 View on GitHub 🚀 Run in Google Colab ☁️ Run in Binder

"""
Day 21: Solutions to Exercises (Command-Line Steps)

These exercises are performed in your terminal. This file describes
the steps you would take to complete them.
"""

# --- Exercise 1: Create a Project and Environment ---
solution_1 = """
--- Solution to Exercise 1 ---
1. Open your terminal (Command Prompt, PowerShell, Terminal, etc.).
2. Navigate to a place where you want to create your project (e.g., Desktop or Documents).
   cd Desktop
3. Create the project folder:
   mkdir my_analytics_project
4. Navigate into the new folder:
   cd my_analytics_project
5. Create the virtual environment (named 'venv'):
   # On macOS/Linux:
   python3 -m venv venv
   # On Windows:
   python -m venv venv
"""
print(solution_1)


# --- Exercise 2: Activate and Install ---
solution_2 = """
--- Solution to Exercise 2 ---
1. Make sure you are inside the 'my_analytics_project' directory.
2. Activate the environment:
   # On macOS/Linux:
   source venv/bin/activate
   # On Windows Command Prompt:
   venv\\Scripts\\activate.bat
   # Your terminal prompt should now start with '(venv)'.

3. Install the packages using pip:
   pip install pandas scipy

4. Verify the installation by listing the packages:
   pip list
   # You should see pandas, scipy, and their dependencies in the output.
"""
print(solution_2)


# --- Exercise 3: Create a Requirements File ---
solution_3 = """
--- Solution to Exercise 3 ---
1. Ensure your virtual environment is still active.
2. Run the 'pip freeze' command and redirect the output to a file:
   pip freeze > requirements.txt

3. You can now see a 'requirements.txt' file in your project folder.
   If you open it, it will contain lines like:
   numpy==...
   pandas==...
   scipy==...
   ...and other dependencies with their exact versions.
"""
print(solution_3)


# --- Exercise 4: Deactivate ---
solution_4 = """
--- Solution to Exercise 4 ---
1. To exit the virtual environment, simply type:
   deactivate
2. Your terminal prompt will return to normal.
"""
print(solution_4)

"""
Day 21: Virtual Environments

This lesson is primarily focused on commands you run in your terminal,
not in a Python script.

Please see the README.md file for the full lesson and exercises.

The key commands are:
1. Create environment: python -m venv venv
2. Activate (macOS/Linux): source venv/bin/activate
3. Activate (Windows): venv\\Scripts\\activate.bat
4. Install packages: pip install <package_name>
5. Save packages: pip freeze > requirements.txt
6. Deactivate: deactivate
"""

print("This Python script is a placeholder.")
print(
    "Please follow the instructions in README.md to practice using virtual environments in your terminal."
)