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是否有静态分析/验证工具?
原标题:Are there Python statical analysis/validation tools?

我永远不会是一场巨大的狂热。 我学习了这门课程,教师们确实进入了这个课程,但是他的热情从来不会给我们这个班子的其余部分带来很大的影响:我们一有机会,就马上跳到C#/Java。

任何途径。 这是一次总结经验,而我最不喜欢的是,如果发现甲型六氯环己烷法会奏效,你实际上必须加以执行,并且由于像一个不同名称的打字体(浏览NameError)一样,有可能半途衰落。 只靠编集语言的编集者在一线上播下,但这种编篡者赢得双手抱怨,直到时间太晚。 (我知道你可以always)。 半途经经编辑的方案测试后死亡,但至少从打字中赢得。

我不真正给它第二次机会,但为了下学生,那里是否有静态分析或鉴定工具可以消除大多数错误(我理解你可以赶上所有错误),汇编者将在汇编时赶上吗?

最佳回答

探讨以下方案:

问题回答

“然而,在 Python太晚之前,沙尔赢得双手抱怨”

这并不是说信息太晚了。 你们再等待太久才使用沙捞越。 Don t 型山脉代码,然后抱怨一小块土地不好。

  1. 使用单位测试。 在进行测试之前,写作的代码较少。

  2. 以互动方式开展试验。 您可以迅速从<代码>、>、>、进行大部分统计处理。

  3. Don 写长、重订字。 书写短篇——小篇——并测试小篇。

除司机提到的内容外。

Try Pydev,它有静态的代码分析。 Or ,Pida ,有两种不同的固定分析工具。

或者,如果你正在寻找一个独立的图书馆,则尝试





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