Behave
pytest
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Behave | pytest | |
---|---|---|
5 | 30 | |
3,048 | 11,239 | |
1.0% | 1.9% | |
7.1 | 9.9 | |
7 days ago | 7 days ago | |
Python | Python | |
GNU General Public License v3.0 or later | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Behave
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Behave VS vedro - a user suggested alternative
2 projects | 16 Jul 2023
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Behave Driven Development Python library
There are Python BDD frameworks out there, most notably `behave` (https://github.com/behave/behave).
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Top 7 Python Frameworks for Automation Testing
Behave on GitHub — https://github.com/behave/behave
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Automated Testing in Python with pytest, tox, and GitHub Actions
Don't forget behaviour testing too! Something like Behave! to test that high-level behaviour :3
pytest
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The Uncreative Software Engineer's Compendium to Testing
Pytest: is a third-party testing framework that supports fixtures, parameterized testing, and easy test discovery while having room to add plugins to extend its functionality.
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pytest VS vedro - a user suggested alternative
2 projects | 16 Jul 2023
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TDD vs BDD - A Detailed Guide
Next, you need to install a testing framework that will be used for performing unit testing in your project. Several testing frameworks are available depending on the programming language used to create an application. For example, JUnit is commonly used for Java apps, pytest for Python apps, NUnit for .NET apps, Jest for JavaScript apps, and so on. We’ll use the Jest framework for this tutorial since we are using JavaScript.
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Is there a way to automate testing in python? In my case :
Yea, read through the pytest docs.
- Testing an automation framework
- 2023 Development Tool Map
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How to raise the quality of scientific Jupyter notebooks
Since ITK's inception in 1999, there has been a focus on engineering practices that result in high-quality software. High-quality scientific software is driven by regression testing. The ITK project supported the development of CTest and CDash unit testing and software quality dashboard tools for use with the CMake build system. In the Python programming language, the pytest test driver helps developers write small, readable scripts that ensure their software will continue to work as expected. However, pytest can only test Python scripts by default, and errors in untested computational notebooks are more common than well-tested Python code.
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Getting Started with a Web Scraping Project
Inorder to have this project be as well-rounded as possible we'll code a series of tests to test the code using pytest. Create a new directory called tests and create a new file called test_db.py in the tests directory. Inside create a test_players.py file.
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Python Malware Starting to Employ Anti-Debug Techniques
that doesn't make much sense and there are necessary uses for eval() /exec(), mostly for dynamic creation of code:
For example here's Python dataclasses in the standard library using exec() to create the `__init__` and other methods that go on your dataclass:
https://github.com/python/cpython/blob/main/Lib/dataclasses....
Here's Pydantic using it for a jupyter notebook check:
https://github.com/pydantic/pydantic/blob/594effa279668bd955...
here's Pytest using it to rewrite modules so that functions like assert etc. are instrumented by pytest:
https://github.com/pytest-dev/pytest/blob/eca93db05b6c5ec101...
Here's the decorator module using it (as is the only way to do this in Python) to create a signature matching decorator for an arbitrary function:
https://github.com/micheles/decorator/blob/ad013a2c1ad796996...
All of these libraries are completely secure as eval/exec are used with code fragments that are generated by the libraries, not based on untrusted input.
eval() /exec() are not running executable files, just Python code, the same way all the rest of the package is already doing.
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Willans' Formula
For brevity we will test the numbers from 0 through 10, below are a collection of pytest tests covering these cases. Thus, in test_willans.py we have the following:
What are some alternatives?
nose2 - The successor to nose, based on unittest2
Robot Framework - Generic automation framework for acceptance testing and RPA
Slash - The Slash testing infrastructure
hypothesis - Hypothesis is a powerful, flexible, and easy to use library for property-based testing.
nose - nose is nicer testing for python
mamba - The definitive testing tool for Python. Born under the banner of Behavior Driven Development (BDD).
PyRestTest - Python Rest Testing
tox
Schemathesis - Automate your API Testing: catch crashes, validate specs, and save time
Scrapy - Scrapy, a fast high-level web crawling & scraping framework for Python.