Issue 359
原文: PyCoder’s Weekly - Issue #359 用 PEP 8 撰写真正 Pythonic 代码 REAL PYTHON video Learn how to write high-quality, readable code by using the Python style guidelines laid out in PEP 8. Following these guidelines helps you make a great impression when sharing your work with potential employers and team mates. Learn how to make your code PEP 8 compliant with these bite-sized lessons. (是也乎: 没那么简单, 团队习惯兼容的配置又能有用, 太难 ) 在Python中实施单一责任原则(SRP) NIKITA SOBOLEV The Single Responsibility Principle (or SRP) is an important concept in software development. The main idea of this concept is: all pieces of software must have only a single responsibility. Nikita’s article guides you through the complex process of writing simple code with some hands-on refactoring examples. You’ll use callable classes, SRP, dependency injection, and composition to write simple Python code. Nice read! (是也乎: Python 是个橡皮泥, 嘦愿意, 总是能嗯哼成喜欢的样子… ) 如何使用测试 CI 和代码覆盖率设置 Python 项目以取得成功 JEFF HALE How to add tests, CI, code coverage, and more. Very detailed writeup. (是也乎: 非常详细…以致难以简单的向团队交付… Install Black Create .pycache Install pytest Create Tests Sign up for Travis CI and Configure Create .travis.yaml Test Travis CI Add Code Coverage Add Coveralls Add PyUp 看起来步骤不多…但是,,,, ) 用 Python 和 OpenCV 检测真/假面孔 ADRIAN ROSEBROCK Learn how to detect liveness with OpenCV, Deep Learning, and Keras. You’ll learn how to detect fake faces and perform anti-face spoofing in face recognition systems with OpenCV. 用 pyenv 管理多个 Python 版本 REAL PYTHON In this step-by-step tutorial, you’ll learn how to install multiple Python versions and switch between them with ease, including project-specific virtual environments, even if you don’t have sudo access with pyenv. (是也乎: 其实 PyEnv 比 pipenv 灵活就在, 不仅仅是将运行时版本进行了管理, 而且可以简便的将 Python 版本环境, 工程模块依赖环境, 在本地自由结合到任意工程目录上. 就是缺少一个一键将当前环境所有依赖模块冻结为压缩文件, 并能简洁的传送到远方主机, 一键完成再安装配置的工具… 毕竟, 总是有些模块是依赖外部 GCC 之类工具现场编译的. ) 2005 年以来 Python 包的增长 PYDIST.COM “The Python ecosystem has been steadily growing [since 2005]. After the first few years of hyper growth as PyPI gained near-full adoption in the Python community, the number of packages actively developed each year—meaning they had at least one release or new distribution uploaded—has increased 28% to 48% every year.” (是也乎: 每年 28%~48% 的增长, 比中国 GDP 高, 但是远远小于 node.js 的. ) 讨论 Discussions ...