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.

内容概要:文章基于4A架构(业务架构、应用架构、数据架构、技术架构),对SAP的成本中心和利润中心进行了详细对比分析。业务架构上,成本中心是成本控制的责任单元,负责成本归集与控制,而利润中心是利润创造的独立实体,负责收入、成本和利润的核算。应用架构方面,两者都依托于SAP的CO模块,但功能有所区分,如成本中心侧重于成本要素归集和预算管理,利润中心则关注内部交易核算和获利能力分析。数据架构中,成本中心与利润中心存在多对一的关系,交易数据通过成本归集、分摊和利润计算流程联动。技术架构依赖SAP S/4HANA的内存计算和ABAP技术,支持实时核算与跨系统集成。总结来看,成本中心和利润中心在4A架构下相互关联,共同为企业提供精细化管理和决策支持。 适合人群:从事企业财务管理、成本控制或利润核算的专业人员,以及对SAP系统有一定了解的企业信息化管理人员。 使用场景及目标:①帮助企业理解成本中心和利润中心在4A架构下的运作机制;②指导企业在实施SAP系统时合理配置成本中心和利润中心,优化业务流程;③提升企业对成本和利润的精细化管理水平,支持业务决策。 其他说明:文章不仅阐述了理论概念,还提供了具体的应用场景和技术实现方式,有助于读者全面理解并应用于实际工作中。
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