Difference between __str__ and __repr__ in Python

First, let me reiterate the main points in Alex’s post:
• The default implementation is useless (it’s hard to think of one which wouldn’t be, but yeah)
repr goal is to be unambiguous
str goal is to be readable
• Container’s str uses contained objects’ repr
Default implementation is useless
This is mostly a surprise because Python’s defaults tend to be fairly useful. However, in this case, having a default for repr which would act like:
return “%s(%r)” % (self.class, self.dict)
would have been too dangerous (for example, too easy to get into infinite recursion if objects reference each other). So Python cops out. Note that there is one default which is true: if __repr__is defined, and str is not, the object will behave as though str=repr.
This means, in simple terms: almost every object you implement should have a functional __repr__that’s usable for understanding the object. Implementing str is optional: do that if you need a “pretty print” functionality (for example, used by a report generator).
The goal of repr is to be unambiguous
Let me come right out and say it — I do not believe in debuggers. I don’t really know how to use any debugger, and have never used one seriously. Furthermore, I believe that the big fault in debuggers is their basic nature — most failures I debug happened a long long time ago, in a galaxy far far away. This means that I do believe, with religious fervor, in logging. Logging is the lifeblood of any decent fire-and-forget server system. Python makes it easy to log: with maybe some project specific wrappers, all you need is a
log(INFO, “I am in the weird function and a is”, a, “and b is”, b, “but I got a null C — using default”, default_c)
But you have to do the last step — make sure every object you implement has a useful repr, so code like that can just work. This is why the “eval” thing comes up: if you have enough information so eval(repr©)==c, that means you know everything there is to know about c. If that’s easy enough, at least in a fuzzy way, do it. If not, make sure you have enough information about canyway. I usually use an eval-like format: “MyClass(this=%r,that=%r)” % (self.this,self.that). It does not mean that you can actually construct MyClass, or that those are the right constructor arguments — but it is a useful form to express “this is everything you need to know about this instance”.
Note: I used %r above, not %s. You always want to use repr() [or %r formatting character, equivalently] inside repr implementation, or you’re defeating the goal of repr. You want to be able to differentiate MyClass(3) and MyClass(“3”).
The goal of str is to be readable
Specifically, it is not intended to be unambiguous — notice that str(3)==str(“3”). Likewise, if you implement an IP abstraction, having the str of it look like 192.168.1.1 is just fine. When implementing a date/time abstraction, the str can be “2010/4/12 15:35:22”, etc. The goal is to represent it in a way that a user, not a programmer, would want to read it. Chop off useless digits, pretend to be some other class — as long is it supports readability, it is an improvement.
Container’s str uses contained objects’ repr
This seems surprising, doesn’t it? It is a little, but how readable would
[moshe is, 3, hello
world, this is a list, oh I don’t know, containing just 4 elements]
be? Not very. Specifically, the strings in a container would find it way too easy to disturb its string representation. In the face of ambiguity, remember, Python resists the temptation to guess. If you want the above behavior when you’re printing a list, just
print “[” + ", ".join(l) + “]”
(you can probably also figure out what to do about dictionaries.
Summary
Implement repr for any class you implement. This should be second nature. Implement str if you think it would be useful to have a string version which errs on the side of more readability in favor of more ambiguity.

先展示下效果 https://pan.quark.cn/s/a4b39357ea24 遗传算法 - 简书 遗传算法的理论是根据达尔文进化论而设计出来的算法: 人类是朝着好的方向(最优解)进化,进化过程中,会自动选择优良基因,淘汰劣等基因。 遗传算法(英语:genetic algorithm (GA) )是计算数学中用于解决最佳化的搜索算法,是进化算法的一种。 进化算法最初是借鉴了进化生物学中的一些现象而发展起来的,这些现象包括遗传、突变、自然选择、杂交等。 搜索算法的共同特征为: 首先组成一组候选解 依据某些适应性条件测算这些候选解的适应度 根据适应度保留某些候选解,放弃其他候选解 对保留的候选解进行某些操作,生成新的候选解 遗传算法流程 遗传算法的一般步骤 my_fitness函数 评估每条染色体所对应个体的适应度 升序排列适应度评估值,选出 前 parent_number 个 个体作为 待选 parent 种群(适应度函数的值越小越好) 从 待选 parent 种群 中随机选择 2 个个体作为父方和母方。 抽取父母双方的染色体,进行交叉,产生 2 个子代。 (交叉概率) 对子代(parent + 生成的 child)的染色体进行变异。 (变异概率) 重复3,4,5步骤,直到新种群(parentnumber + childnumber)的产生。 循环以上步骤直至找到满意的解。 名词解释 交叉概率:两个个体进行交配的概率。 例如,交配概率为0.8,则80%的“夫妻”会生育后代。 变异概率:所有的基因中发生变异的占总体的比例。 GA函数 适应度函数 适应度函数由解决的问题决定。 举一个平方和的例子。 简单的平方和问题 求函数的最小值,其中每个变量的取值区间都是 [-1, ...
### 作用 在 Python 中,`__str__` 和 `__repr__` 都是用于定义对象的字符串表示的魔法方法,它们的目的和使用场景不同,但都用于将对象转换为字符串形式展示[^2]。 - **`__str__`**:用于生成用户友好的字符串表示,它应该返回一个易于理解的字符串,通常是在打印或显示对象时使用。当使用 `print()` 或 `str()` 函数时,Python 会调用 `__str__` 方法。如果没有定义 `__str__`,Python 会回退到 `__repr__` 方法[^2]。 - **`__repr__`**:用于生成开发者友好的字符串表示,它返回的字符串通常包含足够的信息,以便能够准确地重建对象。当在交互式环境中直接输入对象名,或者使用 `repr()` 函数时,Python 会调用 `__repr__` 方法。 ### 区别 - **面向对象不同**:`__str__` 旨在面向最终用户,返回的字符串应该简洁且易于理解;而 `__repr__` 主要面向开发者,提供对象的详细信息,方便调试和开发[^2]。 - **调用场景不同**:`__str__` 会在使用 `print()` 或 `str()` 函数时被调用;`__repr__` 会在交互式环境中直接输入对象名或使用 `repr()` 函数时被调用。 ### 使用方法 以下是一个示例,展示了 `__str__` 和 `__repr__` 的使用方法: ```python class Person: def __init__(self, name, age): self.name = name self.age = age def __str__(self): return f"Person(Name: {self.name}, Age: {self.age})" def __repr__(self): return f"Person(name='{self.name}', age={self.age})" p = Person("Alice", 30) # 调用 __str__ print(str(p)) # 调用 __repr__ print(repr(p)) ``` 在这个示例中,`__str__` 方法返回了一个简洁的、用户友好的字符串,而 `__repr__` 方法返回了一个更详细的、可以用于重建对象的字符串。
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