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Python Testing Cookbook

Год: 2011
Автор: Greg L. Turnquist
Жанр: Программирование
Издательство: Packt Publishing
ISBN: 978-1-849514-66-8
Язык: Английский
Формат: PDF
Качество: Изначально компьютерное (eBook)
Количество страниц: 362

Описание: Are you looking at new ways to write better, more efficient tests? Are you struggling to add automated testing to your existing system? The Python unit testing framework, originally referred to as “PyUnit” and now known as unittest, is a framework that makes it easier for you to write automated test suites efficiently in Python. This book will show you exactly how to squeeze every ounce of value out of automated testing.
The Python Testing Cookbook will empower you to write tests using lots of Python test tools, code samples, screenshots, and detailed explanations. By learning how and when to write tests at every level, you can vastly improve the quality of your code and your personal skill set. Packed with lots of test examples, this will become your go-to book for writing good tests.
This practical cookbook covers lots of test styles including unit-level, test discovery, doctest, BDD, acceptance, smoke, and load testing. It will guide you to use popular Python tools effectively and discover how to write custom extensions. You will learn how to use popular continuous integration systems like Jenkins (formerly known as Hudson) and TeamCity to automatically test your code upon check in. This book explores Python’s built-in ability to run code found embedded in doc strings and also plugging in to popular web testing tools like Selenium. By the end of this book, you will be proficient in many test tactics and be ready to apply them to new applications as well as legacy ones.

You will learn from this book :
* Get started with the basics of writing automated unit tests and asserting results
* Use Nose to discover tests and build suites automatically
* Write Nose plugins that control what tests are discovered and how to produce test reports
* Add testable documentation to your code
* Filter out test noise, customize test reports, and tweak doctest’s to meet your needs
* Write testable stories using lots of tools including doctest, mocks, Lettuce, and Should DSL
* Get started with the basics of customer-oriented acceptance testing
* Test the web security of your application
* Configure Jenkins and TeamCity to run your test suite upon check-in
* Capture test coverage reports in lots of formats, and integrate with Jenkins and Nose
* Take the pulse of your system with a quick smoke test and overload your system to find its breaking points
* Add automated testing to an existing legacy system that isn’t test oriented
•Chapter 1: Using Unittest To Develop Basic Tests
◦Introduction
◦Asserting the basics
◦Setting up and tearing down a test harness
◦Running test cases from the command line with increased verbosity
◦Running a subset of test case methods
◦Chaining together a suite of tests
◦Defining test suites inside the test module
◦Retooling old test code to run inside unittest
◦Breaking down obscure tests into simple ones
◦Testing the edges
◦Testing corner cases by iteration

•Chapter 2: Running Automated Test Suites with Nose
◦Introduction
◦Getting nosy with testing
◦Embedding nose inside Python
◦Writing a nose extension to pick tests based on regular expressions
◦Writing a nose extension to generate a CSV report
◦Writing a project-level script that lets you run different test suites

•Chapter 3: Creating Testable Documentation with doctest
◦Introduction
◦Documenting the basics
◦Catching stack traces
◦Running doctests from the command line
◦Coding a test harness for doctest
◦Filtering out test noise
◦Printing out all your documentation including a status report
◦Testing the edges
◦Testing corner cases by iteration
◦Getting nosy with doctest
◦Updating the project-level script to run this chapter's doctests

•Chapter 4: Testing Customer Stories with Behavior Driven Development
◦Introduction
◦Naming tests that sound like sentences and stories
◦Testing separate doctest documents
◦Writing a testable story with doctest
◦Writing a testable novel with doctest
◦Writing a testable story with Voidspace
◦Mock and nose
◦Writing a testable story with mockito and nose
◦Writing a testable story with Lettuce
◦Using Should DSL to write succinct assertions with Lettuce
◦Updating the project-level script to run this chapter's BDD tests

•Chapter 5: High Level Customer Scenarios with Acceptance Testing
◦Introduction
◦Installing Pyccuracy
◦Testing the basics with Pyccuracy
◦Using Pyccuracy to verify web app security
◦Installing the Robot Framework
◦Creating a data-driven test suite with Robot
◦Writing a testable story with Robot
◦Tagging Robot tests and running a subset
◦Testing web basics with Robot
◦Using Robot to verify web app security
◦Creating a project-level script to verify this chapter's acceptance tests

•Chapter 6: Integrating Automated Tests with Continuous Integration
◦Introduction
◦Generating a continuous integration report for Jenkins using NoseXUnit
◦Configuring Jenkins to run Python tests upon commit
◦Configuring Jenkins to run Python tests when scheduled
◦Generating a CI report for TeamCity using teamcity-nose
◦Configuring TeamCity to run Python tests upon commit
◦Configuring TeamCity to run Python tests when scheduled

•Chapter 7: Measuring your Success with Test Coverage
◦Introduction
◦Building a network management application
◦Installing and running coverage on your test suite
◦Generating an HTML report using coverage
◦Generating an XML report using coverage
◦Getting nosy with coverage
◦Filtering out test noise from coverage
◦Letting Jenkins get nosy with coverage
◦Updating the project-level script to provide coverage reports

•Chapter 8: Smoke/Load Testing—Testing Major Parts
◦Introduction
◦Defining a subset of test cases using import statements
◦Leaving out integration tests
◦Targeting end-to-end scenarios
◦Targeting the test server
◦Coding a data simulator
◦Recording and playing back live data in real time
◦Recording and playing back live data as fast as possible
◦Automating your management demo

•Chapter 9: Good Test Habits for New and Legacy Systems
◦Introduction
◦Something is better than nothing
◦Coverage isn't everything
◦Be willing to invest in test fixtures
◦If you aren't convinced on the value of testing, your team won't be either
◦Harvesting metrics
◦Capturing a bug in an automated test
◦Separating algorithms from concurrency
◦Pause to refactor when test suite takes too long to run
◦Cash in on your confidence
◦Be willing to throw away an entire day of changes
◦Instead of shooting for 100 percent coverage, try to have a steady growth
◦Randomly breaking your app can lead to better code

•Index
Доп. информация: Python developers and programmers with a basic understanding of Python and Python testing will find this cookbook beneficial. It will build on that basic knowledge equipping you with the intermediate and advanced skills required to fully utilize the Python testing tools. Broken up into lots of small code recipes, you can read this book at your own pace, whatever your experience. No prior experience of automated testing is required.

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