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A style guide for writing Python tests (and Django tests)
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README.md

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python-testing-style-guide

This document is a draft style guide for writing Python tests (and Django tests). It is meant to be expanded and refined over time.

Many of the recommendations stand in stark contrast to conventions for good code. This is deliberate: tests are not regular code and have a much different set of risks and rewards.

If you're curious why a particular practice is recommended, get someone to defend or explain it (there's a chance it's wrong and needs to be updated). That said, a lot of these recommendations come from specific mistakes and scars earned over many years of work, so don't be surprised if they're passionately defended.

Prerequisites

PEP8 first

Start with PEP8 and strive to understand why it makes the recommendations it does. We like nearly all of it except for the Maximum Line Length recommendation.

Lint in your editor

Configure the Python linting plugin for your editor and use it every time without exception.

Prefer imperfect tests to no tests

Tests should (almost) always accompany code we write professionally. We're fortunate to work in an environment where testing is actively encouraged, so don't waste that priveledge. We get away with all sorts of other efficiencies and laziness because of our sincere dedication to pragmatic and practical testing.

The practice of testing

Tox

Every package should have setup instructions for a developer in the README and should be testable using tox after setup. Use 100% test success to confirm your setup is complete.

Master should be 100%

Strive to never push a failing test to master. If you want to push failing tests to another branch, that's fine (in fact often encouraged).

Run tests often

We run our tests continuously with Jenkins (every morning and after every commit), but you still need to run them locally before pushing code.

Use TDD if it makes sense

Some people do TDD often, sometimes, or rarely. Figure out when it's an effective habit for you.

Pay attention to coverage

Remember the QA team

We are fortunate in that we have a smart and effective QA team. Some functionality simply cannot be effectively tested, which can feel frustrating to a developer. Before spending too much time on a set of tests of limited benefit, consider whether the issue should be

Delete dead or misleading tests aggressively

Do not be shy about removing tests as soon as they start to become false or unhelpful.

Focus on tests during code reviews

Reproduce before testing

For regressions, you should always make sure you can reproduce the issue in a browser as a typical user before writing a single line of code (test or otherwise). After you can reproduce it, try to get a failing test to reliably reproduce it (if possible). Only then is it a good time to start writing the fix.

Always "Click the thing"

No developer should ever rely on tests alone. Before resolving an issue, make sure you have walked through it at least once in a browser as a typical user.

Write regression tests whenever possible

Fail tests first

How do you know if it is actually testing anything if the assert never failed?

Write descriptive failure messages

When tests fail they should tell you exactly why.

Yes:

response = self.client.post('/api/v1/data/', data=SAMPLE)
assert response.status_code == status.HTTP_201_CREATED, "expected HTTP_201, got HTTP_{} data: {}".format(response.status_code, response.data)

This results in a message which explains exactly what was expected and why the test failed:

>           assert response.status_code == status.HTTP_201_CREATED, "expected HTTP_201, got HTTP_{} data: {}".format(response.status_code, response.data)
E           AssertionError: expected HTTP_201, got HTTP_400 data: {'name': [u'This field is required.']}
E           assert 400 == 201
E            +  where 400 = <rest_framework.response.Response object at 0x1070bbb10>.status_code
E            +  and   201 = status.HTTP_201_CREATED

No:

response = self.client.post('/api/v1/data/', data=SAMPLE)
assert response.status_code == status.HTTP_201_CREATED

This results in a message which isn't very helpful in diagnosing the test failure:

>           assert response.status_code == status.HTTP_201_CREATED
E           AssertionError: assert 201 == 400
E            +  where 400 = <rest_framework.response.Response object at 0x1070bbb10>.status_code
E            +  and   201 = status.HTTP_201_CREATED

Prefer fewer asserts per test

Read through the "One Assert per Test" section of Robert Martin's Clean Code. In fact, read the entire chapter 😉

Structure

Prefer small tests

Separate tests into different files

Tests are generally structured to mirror the file layout of the modules they are testing. It is OK to group tests for small modules or to separate targeted tests for a single module across many files.

Follow import conventions

Imports should be grouped in the following order (extends PEP8 rules):

  1. Python standard library imports
  2. Public library imports
  3. Django imports
  4. Testing library imports
  5. Internal libary imports
  6. Local application imports

Each import line must be in alphabetical order inside its group.

import datetime
import inspect
import logging
import uuid
import os


from lxml import etree
from lxml.html import document_fromstring, html5parser


from django.contrib.auth import get_user_model
from django.core.urlresolvers import reverse
from django.test import TestCase
from django.test.client import Client
from django.views.defaults import server_error


import mock

from nose import SkipTest
from nose.tools import assert_equals, assert_in


import nest.models 

from nest.tests.test_helper import create_document


from entice.models import UserSubject
from heron.decorators import anyone_allowed
from heron.models import Trial
from heron.urls import urlpatterns
from tools.urls import traverse_urls

Write to be read

Our tests are often the first thing other developers read to try to understand our code. They'll also often be the first thing we read when something is on fire and we need to fix a bug. Strive for readability in tests.

Always write a docstring

Every single test should have a human-readable docstring. The docstring should follow the pattern of the rest of the module.

See the PEP guidelines for more info on docstring conventions.

Use "should" in every docstring

Tests are often best when they focus on what behavior "should" happen in terms of important actors in the system. A good mental trick to keep tests in this style is to use "should" in every docstring.

In addition, try to use a known actor or object as the subject of the docstring.

Keep the number of words before should (or "should not") to a minimum to improve clarity.

    '''The Manage Users page should show a button to revoke access to the site for each User'''

    '''The Manage Users page should show Users with obscured emails if they are associated with a demo Account'''

    '''A Tutorial should be able to exist in multiple Groups'''

    '''A European User should not be required to enter a state or province'''

Prefer descriptive variables

A reader may have no idea what is happening inside your test. Help them by binding to descriptive variables.

Yes:

reset_url = reverse('django.contrib.auth.views.password_reset_confirm', kwargs={'uidb36': self.user.id, 'token': token})
absolute_reset_url = "http://{}.{}{}'.format(self.account.subdomain, settings.BASE_SITE, reset_url)
expected = "Set your personal password: {}".format(absolute_reset_url)
self.assertOutboxContainsBody(expected)

No:

self.assertOutboxContainsBody(
    'Set your personal password: http://{subdomain}.{base_site}{url}'.format(
        subdomain=self.account.subdomain, base_site=settings.BASE_SITE,
        url=reverse('django.contrib.auth.views.password_reset_confirm',
                    kwargs={'uidb36': self.user.id, 'token': expected})))

Expectations

Always bind an expected value

We always bind an expected value because then the reader has no doubt of what is happening inside our asserts. Conventions like this allow us to focus on what's different about the code instead of being distracted by eccentricities of each implementation.

Yes:

expected = [12, 19]
self.assertEquals(expected, results)

No:

self.assertEquals(40, num_lessons)

Assert the expected value then the returned value

Yes:

self.assertEquals(expected, topic_toc_links)

self.assertEquals(expected, output)

No:

self.assertEquals(results, expected)

Prefer explicit expected values

Unlike regular code, tests are often stronger when they have explicit expected values despite the cost. This can improve readability ("What does this JSON response actually look like in practice?") and ensure that tests don't accidentally test nothing.

Yes:

expected = ["2001-09-01",
            "2002-12-30",
            "2003-08-20",
            "2003-08-29",
            ]
self.assertEquals(expected, dates)

No:

expected = [lesson.started for lesson in self.lessons] # Oops, self.lessons was empty and I just tested nothing
self.assertEquals(expected, dates)

Things that people will yell about

Never print

Use logging instead of print in your code. Learn how to make the logger work for you rather than against you. This should appear in every one of your files:

import logging

log = logging.getLogger(__name__)

Unusual testing conventions

Repeat yourself

Django

Avoid fixtures

Use CSS selectors

More people can read and write CSS selectors than XPath or alternatives.

Prefer extremely targeted functional tests

Use t- CSS classes

Every single test that relies on specific HTML markup must use/add a CSS class starting with t- to the required HTML elements.

This declarative style allows the HTML and CSS to be refactored without impacting tests (even extremely specific ones).

num_revoke_buttons = len(nodes.cssselect(".t-user-table .t-revoke"))

Consider templatetags

Templatetags are often much easier to test (especially in isolation) than the equivalent functional test.

Testing tools and techniques

Use mocks with care

Enjoy assertRaises

How to avoid traps

Really think about boundary values

Test the obvious positive and negative cases separately

Introduce some randomness

We introduce randomness to our tests to make sure we're handling a range of inputs sanely.

The two most common patterns for introducing randomness are using uuid.uuid4() for string values and random.randint().

self.epub = nest.models.EpubArchive.objects.create(identifier=str(uuid.uuid4()))

bit = self.epub.htmlfile_set.create(filename="first.html", virtual_pages=random.randint(1, 100))

how_many = random.randint(10, 100)
for i in range(how_many):
    ...

Warning: Randomness means that some test failures will become hard to reproduce. This is usually an acceptable cost.

Introduce some Unicode

When setting up expected values or string inputs, try to remember to include strange Unicode characters.

expected = [u"R", 
            u"å", 
            u"n",
            u"d", 
            u"☃", 
            u"ɯ"]

Resources

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