Python生成器对象和.join [英] Python generator objects and .join

问题描述

关于python和.join()方法的一个基本问题:

Just a fundamental question regarding python and .join() method:

file1 = open(f1,"r")
file2 = open(f2,"r")
file3 = open("results","w")

diff = difflib.Differ()
result = diff.compare(file1.read(),file2.read())
file3.write("".join(result)),

上面的代码片段产生了一个不错的输出，该输出以字符串格式存储在名为"results"的文件中，逐行显示了两个文件之间的差异.但是，我注意到，如果仅使用.join()打印结果" ，编译器将返回一条包含内存地址的消息.尝试使用.join()将结果写入文件 后，编译器通知我，.join()中只能使用字符串和字符缓冲区. )方法，而不是生成器对象.因此，根据我引用的所有证据，如果我错了，请纠正我:

The above snippet of code yields a nice output stored in a file called "results", in string format, showing the differences between the two files line-by-line. However I notice that if I just print "result" without using .join(), the compiler returns a message that includes a memory address. After trying to write the result to the file without using .join(), I was informed by the compiler that only strings and character buffers may be used in the .join() method, and not generator objects. So based off of all the evidence that I have adduced, please correct me if I am wrong:

1. result = diff.compare(file1.read(),file2.read())< ----结果是生成器对象吗?

1. result = diff.compare(file1.read(),file2.read()) <---- result is a generator object?

result是一个字符串列表，而result本身是对第一个字符串的引用?

result is a list of strings, with result itself being the reference to the first string?

.join()获取一个内存地址并指向第一个，然后迭代该结构中字符串的其余地址?

.join() takes a memory address and points to the first, and then iterates over the rest of the addresses of strings in that structure?

生成器对象是返回指针的对象吗?

A generator object is an object that returns a pointer?

如果我的问题不清楚，我深表歉意，但我基本上想问一下python的退伍军人，我的推论是否正确.我的问题不是关于可观察到的结果，而是关于python的内部工作原理.感谢您的帮助.

I apologize if my questions are unclear, but I basically wanted to ask the python veterans if my deductions were correct. My question is less about the observable results, and more so about the inner workings of python. I appreciate all of your help.

推荐答案

join是字符串的方法.该方法采用任何可迭代的方法并对其进行迭代，然后将内容连接在一起. (内容必须为字符串，否则将引发异常.)

join is a method of strings. That method takes any iterable and iterates over it and joins the contents together. (The contents have to be strings, or it will raise an exception.)

如果尝试将生成器对象直接写入文件，则只会获取生成器对象本身，而不是其内容. join展开"生成器的内容.

If you attempt to write the generator object directly to the file, you will just get the generator object itself, not its contents. join "unrolls" the contents of the generator.

您可以看到一个简单的显式生成器的工作原理:

You can see what is going with a simple, explicit generator:

def gen():
    yield 'A'
    yield 'B'
    yield 'C'

>>> g = gen()
>>> print g
<generator object gen at 0x0000000004BB9090>
>>> print ''.join(g)
ABC

生成器一次分发一次其内容.如果您尝试查看生成器本身，则它不会破坏任何内容，而只是将其视为生成器对象".要了解其内容，您需要对其进行迭代.您可以使用for循环，next函数或迭代事物的其他各种函数/方法(其中的str.join)来完成此操作.

The generator doles out its contents one at a time. If you try to look at the generator itself, it doesn't dole anything out and you just see it as "generator object". To get at its contents, you need to iterate over them. You can do this with a for loop, with the next function, or with any of various other functions/methods that iterate over things (str.join among them).

当您说结果是一个字符串列表"时，您已经接近这个主意了.生成器(或可迭代的)有点像潜在列表".与其一次真正地成为所有内容的列表，不如让您一次剥离每个项目.

When you say that result "is a list of string" you are getting close to the idea. A generator (or iterable) is sort of like a "potential list". Instead of actually being a list of all its contents all at once, it lets you peel off each item one at a time.

所有对象都不是内存地址".生成器对象(与许多其他对象一样)的字符串表示形式包含一个内存地址，因此，如果您将其打印(如上)或将其写入文件，则会看到该地址.但这并不意味着对象就是"那个内存地址，并且地址本身本身并不是真正可用的.这只是一个方便的识别标签，因此，如果您有多个对象，可以将它们分开.

None of the objects is a "memory address". The string representation of a generator object (like that of many other objects) includes a memory address, so if you print it (as above) or write it to a file, you'll see that address. But that doesn't mean that object "is" that memory address, and the address itself isn't really usable as such. It's just a handy identifying tag so that if you have multiple objects you can tell them apart.

这篇关于Python生成器对象和.join的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！