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Source channel @GithubDaily · Post #39 · Oct 28

#Github 今天分享一个写得很用心的算法笔记(教程) 该仓库总共 60 多篇原创文章,都是基于LeetCode 的题目,涵盖了所有题型和技巧。作者总结了很多算法上的套路,对于想要学习算法的朋友来说,绝对是值得一看的仓库。 觉得有用的话,给Git主一颗star鼓励。 https://github.com/labuladong/fucking-algorithm

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djangoproject

@djangoproject · Post #335 · 05/09/2017, 05:22 AM

https://code.tutsplus.com/tutorials/behavior-driven-development-in-python--net-26547 Behavior-Driven Development (which we will now refer to as "#BDD") follows on from the ideas and principles introduced in #Test-Driven Development. The key points of writing tests before code really apply to BDD as well. The idea is to not only test your code at the granular level with unit tests, but also test your application end to end, using acceptance tests. We will introduce this style of testing with the use of the Lettuce testing framework.

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djangoproject

@djangoproject · Post #199 · 11/29/2016, 04:13 PM

http://pythonhosted.org/behave/ behave is behaviour-driven development, Python style. Behavior-driven development (or #BDD) is an agile software development technique that encourages collaboration between developers, #QA and non-technical or business participants in a software project. We have a page further describing this philosophy. behave uses tests written in a natural language style, backed up by Python code. Once you’ve installed behave, we recommend reading the tutorial first and then feature test setup, behave API and related software (things that you can combine with behave) finally: how to use and configure the behave tool.

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djangoproject

@djangoproject · Post #552 · 01/23/2018, 04:33 PM

https://pypi.python.org/pypi/pytest-bdd #BDD library for the py.test runner #pytest-bdd implements a subset of Gherkin language for the automation of the project requirements testing and easier behavioral driven development. Unlike many other BDD tools it doesn’t require a separate runner and benefits from the power and flexibility of the #pytest. It allows to unify your unit and functional #tests, easier continuous integration server configuration and maximal reuse of the tests setup. Pytest fixtures written for the #unit_test s can be reused for the setup and actions mentioned in the feature steps with dependency injection, which allows a true BDD just-enough specification of the requirements without maintaining any context object containing the side effects of the Gherkin. imperative declarations.