Example for Setting Up Pytest and Pipenv

This repository is an example project designed to demonstrate how to set up and use pipenv for dependency management and pytest for testing in Python. It includes configuration for code coverage, linting, and formatting, making it an ideal starting point for Python projects with best practices.

Table of Contents

1. Introduction
2. Project Structure
3. Requirements
4. Setup and Installation
5. Running Tests
6. Code Coverage
7. Linting and Formatting
8. Example Usage
9. Troubleshooting

---

Introduction

This repository is intended as a tutorial and starting point for those looking to implement pytest and pipenv in Python projects. By following this guide, you'll learn:

• How to use pipenv to manage dependencies and virtual environments.
• How to set up and configure pytest for running tests.
• How to configure code coverage using pytest-cov.
• How to use flake8 and black for linting and formatting, ensuring code quality.

This project includes an example weather service API function (weather_service.py) and corresponding unit tests with mocked responses, showing how to handle external API dependencies in tests.

---

Project Structure

The project is organized as follows:

python-test/
├── src/
│   └── weather_service.py          # Main module for fetching weather data
├── tests/
│   └── test_weather_service.py      # Unit tests for the weather service
├── Pipfile                          # Pipenv configuration for dependencies
└── README.md                        # Project documentation

• src/: Contains the main module (weather_service.py) that simulates fetching weather data from an API.
• tests/: Contains unit tests with mocked API responses for testing weather_service.py.
• Pipfile: Defines project dependencies, dev dependencies, and script commands for pipenv.

---

Requirements

• Python 3.10 or higher
• Pipenv for dependency management

Setup and Installation

1. Install Pipenv If Pipenv is not installed, install it globally using:

   pip install pipenv

2. Clone the Repository Clone this project repository to your local machine:

   git clone [email protected]:jonmatum/pipenv-pytest-example.git
   cd pipenv-pytest-example

3. Install Dependencies Use Pipenv to install all necessary packages:

   pipenv install --dev

   This installs both regular and development dependencies (such as pytest, flake8, and black).

4. Activate the Virtual Environment Activate the virtual environment created by Pipenv:

   pipenv shell

---

Running Tests

The project uses pytest for testing and pytest-cov for code coverage. Tests are written with mocks to simulate API responses and handle exceptions.

1. Run All Tests Run the tests using the following command:

   pipenv run test

2. Test Command Explanation The test command in the Pipfile is configured as follows:

   [scripts]
   test = "env PYTHONPATH=src pytest --cov=src --cov-report=term-missing --cov-report=html"

   • --cov=src: Specifies the src directory for measuring test coverage.
   • --cov-report=term-missing: Displays a report in the terminal, showing lines that are not covered.
   • --cov-report=html: Generates an HTML report that can be found in the htmlcov directory after running the command.

---

Code Coverage

1. Run Coverage Report Run the tests with coverage by executing:

   pipenv run test

2. View HTML Coverage Report After running the test command, open the coverage report by navigating to htmlcov/index.html in your browser to view a detailed, line-by-line report.

---

Linting and Formatting

This project uses flake8 for linting and black for formatting to maintain code quality and consistency.

1. Run Linting (flake8) Check the code for PEP 8 compliance and common issues:

   pipenv run lint

   The lint command in the Pipfile is configured as:

   lint = "flake8 ."

2. Run Formatting (black) Format the code automatically using black:

   pipenv run format

   The format command in the Pipfile is configured as:

   format = "black ."

---

Example Usage

To fetch weather data from the API in weather_service.py, you can call the get_weather function with a city name:

from src.weather_service import get_weather

temperature = get_weather("New York", api_key="your_api_key")
print(f"The temperature in New York is {temperature}°C")

This example demonstrates handling external API dependencies by using mock data in the tests, allowing you to understand how to structure tests for functions with external dependencies.

---

Troubleshooting

• Module Not Found Error: Ensure PYTHONPATH=src is correctly set in the Pipfile test script.
• Request Timeout: The API call in weather_service.py has a timeout set; adjust this as necessary depending on network conditions.