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Source channel @olddriverGDstudy · Post #40 · Mar 17

秀哥语录: 开水烫鸡把,锻炼起来 123的兄弟,我给你们说个方法 蛮有效的,就是开水烫几把 你每天洗澡的时候,水温稍微调高一点点 比如平时40度,你就45 用淋浴头冲,冲龟头,每天冲个五分钟 正经点,靠,虽然开水烫几把名字不正经 但是真的有用 你快,是因为敏感,每天冲,可以降低敏感度 一边冲,一边两个指头按压捏,每天五分钟 养成习惯,慢慢就好了 到后期,你可以用毛巾,湿水 然后慢慢尝试那毛巾擦龟头,上下撸 什么时候毛巾擦龟头,你不抖了,就好了 慢慢来啊,过犹不及,慢慢锻炼,降低龟头敏感度 可以尝试下,多少有点用 另外就是心里调节了 不要老是想,不要在意长短 学会去享受,要自信,自我暗示,我是来爽的,不是来比赛的 心里 生理 双管齐下,从此告别123 #秀哥语录#语录

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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.