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Setting up a proper Python environment is crucial for writing clean, testable, and maintainable code — whether you’re building a simple script or a full-scale data science pipeline.
In this article, I’ll break down how to manage your Python environments using two tools: venv (Python’s built-in virtual environment tool) and pipenv (a higher-level tool for dependency management). You’ll also learn how to test your code with pytest.
? Why Use a Virtual Environment?
A virtual environment isolates your project’s dependencies from your global Python installation. This prevents conflicts and keeps your project clean and reproducible.
? Option 1: Using venv (Built-in)
? Step-by-Step Setup
Create the environment
`python -m venv env
Activate it`
On Windows:
env\Scripts\activate
On macOS/Linux:
source env/bin/activate
Install packages
pip install requests
Install pytest for testing
pip install pytest
Freeze dependencies
pip freeze > requirements.txt
Deactivate when done
Example Test with pytest
calculator.py
def add(a, b):
return a + b
test_calculator.py
from calculator import add
def test_add():
assert add(2, 3) == 5
Run your tests with:
pytest
? Option 2: Using pipenv (Modern and Streamlined)
pipenv simplifies dependency management and keeps everything tracked in Pipfile.
? Step-by-Step Setup
Install pipenv
pip install pipenv
Create an environment and install a package
pipenv install requests
Install pytest as a dev dependency
pipenv install --dev pytest
Activate the shell
pipenv shell
Run your tests
pytest
Exit the shell
exit
? Why Use pytest?
Clean syntax with simple assert statements
Fast test discovery
Plugins for coverage, mocking, fixtures, etc.
? Suggested Folder Structure
my_project/
├── env/ or .venv/ # virtual environment (excluded from Git)
├── calculator.py
├── test_calculator.py
├── requirements.txt or Pipfile
└── .gitignore
Add this to .gitignore:
env/
.venv/
__pycache__/
.pytest_cache/
In this article, I’ll break down how to manage your Python environments using two tools: venv (Python’s built-in virtual environment tool) and pipenv (a higher-level tool for dependency management). You’ll also learn how to test your code with pytest.
? Why Use a Virtual Environment?
A virtual environment isolates your project’s dependencies from your global Python installation. This prevents conflicts and keeps your project clean and reproducible.
? Option 1: Using venv (Built-in)
? Step-by-Step Setup
Create the environment
`python -m venv env
Activate it`
On Windows:
env\Scripts\activate
On macOS/Linux:
source env/bin/activate
Install packages
pip install requests
Install pytest for testing
pip install pytest
Freeze dependencies
pip freeze > requirements.txt
Deactivate when done
Example Test with pytestcalculator.py
def add(a, b):
return a + b
test_calculator.py
from calculator import add
def test_add():
assert add(2, 3) == 5
Run your tests with:
pytest
? Option 2: Using pipenv (Modern and Streamlined)
pipenv simplifies dependency management and keeps everything tracked in Pipfile.
? Step-by-Step Setup
Install pipenv
pip install pipenv
Create an environment and install a package
pipenv install requests
Install pytest as a dev dependency
pipenv install --dev pytest
Activate the shell
pipenv shell
Run your tests
pytest
Exit the shell
exit
? Why Use pytest?
Clean syntax with simple assert statements
Fast test discovery
Plugins for coverage, mocking, fixtures, etc.
? Suggested Folder Structure
my_project/
├── env/ or .venv/ # virtual environment (excluded from Git)
├── calculator.py
├── test_calculator.py
├── requirements.txt or Pipfile
└── .gitignore
Add this to .gitignore:
env/
.venv/
__pycache__/
.pytest_cache/