README.md

Deptest

Deptest is a testing framework to handle situation when your need to control the execution order of the test units. Seriously, deptest does not follow the rules of unit testing, in other words, using this tool means you are thinking againest the philosophy of unit testing: “to isolate each part of the program and show that the individual parts are correct”.

But so what? Programming needs diversity, so does testing methodology. If the situation really exists, we should do something with it, that's why deptest is created, it could be considered as a different approach to organize your tests. Try it if you are stuck with unit testing, maybe it'll be helpful :)

Installation

pip install deptest

Usage

The core part of using deptest is to use depend_on decorator on your test functions. depend_on describes that a test function should be run if and only if its dependency function is OK. If dependency is FAILED, then the test function will not be executed and the status will be set to UNMET.

1. Case 1, simple dependency

   from deptest import depend_on
   
   @depend_on('test_b')
   def test_a():
       print 'a, depend on a'
   
   def test_b():
       print 'b'

   This will ensure test_a run after test_b even though test_a is defined before test_b.

2. Case 2, passing return value

   from deptest import depend_on
   
   @depend_on('test_b', with_return=True)
   def test_a(name):
       print 'a, depend on', name
   
   def test_b():
       print 'b'
       return 'b'

   With with_return argument set to True, the return value of test_b will be passed into test_a. By default return values of dependencies won't be passed.

3. Case 3, complicated dependencies

   from deptest import depend_on
   
   @depend_on('test_c', with_return=True)
   @depend_on('test_b', with_return=True)
   def test_a(name1, name2):
       print 'a, depend on', name1, name2
       return 'a'
   
   @depend_on('test_d')
   def test_b():
       print 'b'
       return 'b'
   
   @depend_on('test_d')
   def test_c():
       print 'c'
       return 'c'
   
   def test_d():
       print 'd'
       return 'd'

   The dependent graph of the four functions will be:

   d
   | \
   b  c
   | /
   a
   

   Thus the execute sequence will be d, b, c, a or d, c, b, a, the results are fairly the same.

   $ deptest -s test/simple_test.py
   d
   → simple_test.test_d... OK
   b
   → simple_test.test_b... OK
   c
   → simple_test.test_c... OK
   a, depend on b c
   → simple_test.test_a... OK
   ______________________________________________________________________
   Ran 4 tests, OK 4, FAILED 0, UNMET 0
   

You can see some practical examples in examples/ folder, It's worth mentioning that http_api_test.py simulates an HTTP API testing case, which is mostly the reason why I develop this tool.

Note: to run http_api_test.py, you need HTTPretty installed.

Deptest provides a cli command also called deptest, it supports some common arguments of nosetests, like -s and --nocapture, see detail usage by deptest -h:

usage: deptest [-h] [-s] [--nologcapture] [--dry] [--debug] [PATH [PATH ...]]

positional arguments:
  PATH             files or dirs to scan

optional arguments:
  -h, --help       show this help message and exit
  -s, --nocapture  Don't capture stdout (any stdout output will be printed
                   immediately)
  --nologcapture   Don't capture logging
  --dry            Dry run, only show matched files
  --debug          Set logging level to debug for deptest logger

Screenshots

See it in action, run deptest examples:

With --nologcapture argument:

TODO

• support generator test function