Skip to main content

dependent testing framework

Project description

# 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

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.

2. 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'

def test_b():
print 'b'
return 'b'

def test_c():
print 'c'
return 'c'

def test_d():
print 'd'
return 'd'

The dependent graph of the four functions will be:

| \
b c
| /

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.test_d... OK
→ simple_test.test_b... OK
→ 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/`](examples) folder,
It's worth mentioning that [``](examples/
simulates an HTTP API testing case, which is mostly the reason why I develop this tool.

> Note: to run ``, 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
--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`:

![Normal Mode](_images/normal.png)

With `--nologcapture` argument:

![With -s Stdout](_images/withstdout.png)


- [ ] support generator test function

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for deptest, version 0.2.1
Filename, size File type Python version Upload date Hashes
Filename, size deptest-0.2.1-py2-none-any.whl (17.9 kB) File type Wheel Python version 2.7 Upload date Hashes View
Filename, size deptest-0.2.1.tar.gz (11.4 kB) File type Source Python version None Upload date Hashes View

Supported by

Pingdom Pingdom Monitoring Google Google Object Storage and Download Analytics Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page