Greenhttps://github.com/CleanCut/green |
stestrhttps://pypi.org/project/stestr/ |
|
|---|---|---|
| Programming language | Python | Python |
| Category |
Unit Testing
|
Unit Testing
|
| General info |
Green is a clean, colorful, fast Python test runner This is a test runner that has pretty printing on output that makes results easy to read and understand. Some of its features include: Tests running in independent processes (fast), low redundancy in output (clean), supports pretty printing that is the terminal output, makes good use of color when the terminal supports it (colorful) |
stestr is a Python test runner designed to execute unittest test suites stestr executes unittest test suites by using multiple processes to split up execution of a test suite then stores a history of all test runs to help in debugging failures and optimizing the scheduler to improve speed. |
|
xUnit
Set of frameworks originating from SUnit (Smalltalk's testing framework). They share similar structure and functionality. |
No
|
No
|
|
Client-side
Allows testing code execution on the client, such as a web browser |
Yes It can test front-end components of the django framework |
Yes Stestr being a test runner that runs unittest tests, it can test fron-tend functionality and behaviour. |
|
Server-side
Allows testing the bahovior of a server-side code |
Yes It can test server-side behaviours of web applications written with Python |
Yes Stestr being a test runner that runs unittest tests, it can run back-end tests for functionality and behaviour. |
|
Fixtures
Allows defining a fixed, specific states of data (fixtures) that are test-local. This ensures specific environment for a single test |
N/A
|
Yes By use of a third party library like Fixture |
|
Group fixtures
Allows defining a fixed, specific states of data for a group of tests (group-fixtures). This ensures specific environment for a given group of tests. |
N/A
|
By use of a third party library like Fixture |
|
Generators
Supports data generators for tests. Data generators generate input data for test. The test is then run for each input data produced in this way. |
N/A
|
Yes By using a library like test-generator |
|
Licence
Licence type governing the use and redistribution of the software |
MIT License
|
Apache License 2.0
|
|
Mocks
Mocks are objects that simulate the behavior of real objects. Using mocks allows testing some part of the code in isolation (with other parts mocked when needed) |
Yes Through the use of Python's mock library |
N/A
|
|
Grouping
Allows organizing tests in groups |
N/A
|
N/A
|
|
Other
Other useful information about the testing framework |
|
|
Knapsack Pro