Book Image

pytest Quick Start Guide

By : Bruno Oliveira
Book Image

pytest Quick Start Guide

By: Bruno Oliveira

Overview of this book

Python's standard unittest module is based on the xUnit family of frameworks, which has its origins in Smalltalk and Java, and tends to be verbose to use and not easily extensible.The pytest framework on the other hand is very simple to get started, but powerful enough to cover complex testing integration scenarios, being considered by many the true Pythonic approach to testing in Python. In this book, you will learn how to get started right away and get the most out of pytest in your daily work?ow, exploring powerful mechanisms and plugins to facilitate many common testing tasks. You will also see how to use pytest in existing unittest-based test suites and will learn some tricks to make the jump to a pytest-style test suite quickly and easily.
Table of Contents (9 chapters)

Introducing fixtures

Most tests need some kind of data or resource to operate on:

def test_highest_rated():
series = [
("The Office", 2005, 8.8),
("Scrubs", 2001, 8.4),
("IT Crowd", 2006, 8.5),
("Parks and Recreation", 2009, 8.6),
("Seinfeld", 1989, 8.9),
]
assert highest_rated(series) == "Seinfeld"

Here, we have a list of (series name, year, rating) tuples that we use to test the highest_rated function. Inlining data into the test code as we do here works well for isolated tests, but often you have a dataset that can be used by multiple tests. One solution would be to copy over the dataset to each test:

def test_highest_rated():
series = [
("The Office", 2005, 8.8),
...,
]
assert highest_rated(series) == "Seinfeld"

def test_oldest(...