Beauty Is in Simplicity

本文引用柏拉图的观点,强调了简洁性对于软件开发的重要性。文章探讨了代码之美在于其可读性、可维护性和开发速度,而这些品质的基础正是简洁。通过研究优秀的开源代码示例,作者阐述了如何实现这种简洁之美。

There is one quote that I think is particularly good for all software developers to know and keep close to their hearts:

Beauty of style and harmony and grace and good rhythm depends on simplicity. — Plato

In one sentence I think this sums up the values that we as software developers should aspire to.

There are a number of things we strive for in our code:

  • Readability
  • Maintainability
  • Speed of development
  • The elusive quality of beauty

Plato is telling us that the enabling factor for all of these qualities is simplicity.

What is beautiful code? This is potentially a very subjective question. Perception of beauty depends heavily on individual background, just as much of our perception of anything depends on our background. People educated in the arts have a different perception of (or at least approach to) beauty than people educated in the sciences. Arts majors tend to approach beauty in software by comparing software to works of art, while science majors tend to talk about symmetry and the golden ratio, trying to reduce things to formulae. In my experience, simplicity is the foundation of most of the arguments from both sides.

Think about source code that you have studied. If you haven't spent time studying other people's code, stop reading this right now and find some open source code to study. Seriously! I mean it! Go search the web for some code in your language of choice, written by some well-known, acknowledged expert.

You're back? Good. Where were we? Ah yes... I have found that code that resonates with me and that I consider beautiful has a number of properties in common. Chief among these is simplicity. I find that no matter how complex the total application or system is, the individual parts have to be kept simple. Simple objects with a single responsibility containing similarly simple, focused methods with descriptive names. Some people think the idea of having short methods of five to ten lines of code is extreme, and some languages make it very hard to do this, but I think that such brevity is a desirable goal nonetheless.

The bottom line is that beautiful code is simple code. Each individual part is kept simple with simple responsibilities and simple relationships with the other parts of the system. This is the way we can keep our systems maintainable over time, with clean, simple, testable code, keeping the speed of development high throughout the lifetime of the system.

Beauty is born of and found in simplicity.

By Jørn Ølmheim

<think>Hmm, the user seems to be sharing a Python code snippet - "parts = [p for p in parts if p]" - without any additional context. This appears to be a list comprehension that filters out falsy values from a list called "parts". Given the strict formatting requirements in the system prompt, I need to carefully structure my response. The user wants an explanation followed by exactly 3-5 related questions in a specific format. First, I should explain what this concise line does: it recreates the "parts" list while excluding empty strings, None values, zeros, False, or other falsy elements. The beauty lies in its simplicity - using the truthiness of "p" as the filter condition. Now for the required questions... I'm considering what would naturally follow from this snippet: 1) Asking about falsy values in Python since that's core to how this works 2) Alternatives like filter() since that's a common comparison 3) Performance implications as lists grow large 4) In-place modification alternatives for memory efficiency 5) Whether it preserves original order (which it does) The user seems technically proficient based on sharing clean pythonic code. Probably a developer looking for deeper understanding rather than beginner explanation. Might be processing text/data where empty fragments need removal. I'll keep the explanation crisp but add the technical note about preserved order since that's non-obvious. The questions should cover both fundamentals (falsy values) and practical concerns (performance, alternatives). ...better avoid making the questions too advanced though - the snippet is intermediate level after all. Four questions feels right: covering core concept, alternatives, optimization, and a common pitfall (identity vs equality check). </think>这段Python代码使用列表推导式过滤掉列表`parts`中的所有**假值**(falsy values): ```python parts = [p for p in parts if p] ``` ### 详细说明: 1. **遍历元素**:`for p in parts` 遍历原列表的每个元素 2. **条件过滤**:`if p` 检查元素是否为真值(Truthy),等价于 `if bool(p) is True` 3. **假值类型**:以下情况会被过滤: - `None` - 空字符串 `""` - 数字 `0` 或 `0.0` - 空容器(`[]`, `()`, `{}`, `set()`) - `False` 4. **结果**:生成仅包含真值元素的新列表,**保持原有顺序** ### 注意事项: - 不修改原列表,而是创建新列表 - 对自定义对象,依赖其`__bool__()`或`__len__()`方法判断真假
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