Document Type
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BL
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Record Number
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855819
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Main Entry
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Arbuckle, Daniel
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Title & Author
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Learning Python testing : : a straightforward and easy approach to testing your Python projects /\ Daniel Arbuckle.
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Edition Statement
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Second edition.
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Publication Statement
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Birmingham, UK :: Packt Publishing,, 2014.
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Series Statement
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Community experience distilled
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Page. NO
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1 online resource (1 volume) :: illustrations
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ISBN
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1783553219
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: 1783553227
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: 9781783553211
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: 9781783553228
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9781783553211
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Notes
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Includes index.
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Contents
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Cover; Copyright; Credits; About the Author; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Python and Testing; Testing for fun and profit; Levels of testing; Unit testing; Integration testing; System testing; Acceptance testing; Regression testing; Test-driven development; You'll need Python; Summary; Chapter 2: Working with doctest; Where doctest performs best; The doctest language; Example -- creating and running a simple doctest; Result -- three times three does not equal ten; The syntax of doctests; Example -- a more complex test; Result -- five tests run?
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Example -- a doctest in a docstringResult -- the code is now self-documenting and self-testable; Putting it into practice -- an AVL tree; English specification; Node data; Testing the constructor; Recalculating height; Making a node deletable; Rotation; Locating a node; The rest of the specification; Summary; Chapter 3: Unit Testing with doctest; What is unit testing?; The limitations of unit testing; Example -- identifying units; Choosing units; Check your understanding; Unit testing during the development process; Design; Development; Feedback; Development, again; Later stages of the process.
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Expecting exceptionsExample -- checking for an exception; Result -- success at failing; Expecting blank lines; Controlling doctest behavior with directives; Ignoring part of the result; Example -- ellipsis test drive; Result -- ellipsis elides; Ignoring white space; Example -- invoking normality; Result -- white space matches any other white space; Skipping an example; Example -- humans only; Result -- it looks like a test, but it's not; The other directives; The execution scope of doctest tests; Check your understanding; Exercise -- English to doctest; Embedding doctests into docstrings.
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The basicsAssertions; The assertTrue method; The assertFalse method; The assertEqual method; The assertNotEqual method; The assertAlmostEqual method; The assertNotAlmostEqual method; The assertIs and assertIsNot methods; The assertIsNone and assertIsNotNone methods; The assertIn and assertNotIn methods; The assertIsInstance and assertNotIsInstance methods; The assertRaises method; The fail method; Make sure you get it; Test fixtures; Example -- testing database-backed units; Summary; Chapter 6: Running Your Tests with Nose; Installing Nose; Organizing tests; An example of organizing tests.
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Abstract
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Chapter 4: Decoupling Units with unittest.mock; Mock objects in general; Mock objects according to unittest.mock; Standard mock objects; Non-mock attributes; Non-mock return values and raising exceptions; Mocking class or function details; Mocking function or method side effects; Mocking containers and objects with a special behavior; Mock objects for properties and descriptors; Mocking file objects; Replacing real code with mock objects; Mock objects in action; Better PID tests; Patching time.time; Decoupling from the constructor; Summary; Chapter 5: Structured Testing with unittest.
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This book is ideal if you want to learn about the testing disciplines and automated testing tools from a hands-on, conversational guide. You should already know Python and be comfortable with Python 3.
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Subject
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Object-oriented programming (Computer science)
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Subject
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Python (Computer program language)
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Subject
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COMPUTERS-- Computer Literacy.
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Subject
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COMPUTERS-- Computer Science.
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Subject
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COMPUTERS-- Data Processing.
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Subject
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COMPUTERS-- Hardware-- General.
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Subject
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COMPUTERS-- Information Technology.
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Subject
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COMPUTERS-- Machine Theory.
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Subject
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COMPUTERS-- Reference.
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Subject
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Object-oriented programming (Computer science)
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Subject
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Python (Computer program language)
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Dewey Classification
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004.6186
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LC Classification
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QA76.73.P98
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