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Why does Python code use len() function instead of a length method?

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Why does Python use Len?

The function len() is one of Python's built-in functions. It returns the length of an object. For example, it can return the number of items in a list. You can use the function with many different data types.

Why do we use LEN function?

LEN returns the number of characters in a text string. LENB returns the number of bytes used to represent the characters in a text string. Important: These functions may not be available in all languages.

What does Len () return in Python?

The len() Python method returns the length of a list, string, dictionary, or any other iterable data format in Python. The len() method takes one argument: an iterable object. len() is a built-in method in Python.

What does Python LEN function do what types can it be used with?

len() is a built-in function in python. You can use the len() to get the length of the given string, array, list, tuple, dictionary, etc. You can use len function to optimize the performance of the program. The number of elements stored in the object is never calculated, so len helps provide the number of elements.


Strings do have a length method: __len__()

The protocol in Python is to implement this method on objects which have a length and use the built-in len() function, which calls it for you, similar to the way you would implement __iter__() and use the built-in iter() function (or have the method called behind the scenes for you) on objects which are iterable.

See Emulating container types for more information.

Here's a good read on the subject of protocols in Python: Python and the Principle of Least Astonishment


Jim's answer to this question may help; I copy it here. Quoting Guido van Rossum:

First of all, I chose len(x) over x.len() for HCI reasons (def __len__() came much later). There are two intertwined reasons actually, both HCI:

(a) For some operations, prefix notation just reads better than postfix — prefix (and infix!) operations have a long tradition in mathematics which likes notations where the visuals help the mathematician thinking about a problem. Compare the easy with which we rewrite a formula like x*(a+b) into x*a + x*b to the clumsiness of doing the same thing using a raw OO notation.

(b) When I read code that says len(x) I know that it is asking for the length of something. This tells me two things: the result is an integer, and the argument is some kind of container. To the contrary, when I read x.len(), I have to already know that x is some kind of container implementing an interface or inheriting from a class that has a standard len(). Witness the confusion we occasionally have when a class that is not implementing a mapping has a get() or keys() method, or something that isn’t a file has a write() method.

Saying the same thing in another way, I see ‘len‘ as a built-in operation. I’d hate to lose that. /…/


There is a len method:

>>> a = 'a string of some length'
>>> a.__len__()
23
>>> a.__len__
<method-wrapper '__len__' of str object at 0x02005650>

Python is a pragmatic programming language, and the reasons for len() being a function and not a method of str, list, dict etc. are pragmatic.

The len() built-in function deals directly with built-in types: the CPython implementation of len() actually returns the value of the ob_size field in the PyVarObject C struct that represents any variable-sized built-in object in memory. This is much faster than calling a method -- no attribute lookup needs to happen. Getting the number of items in a collection is a common operation and must work efficiently for such basic and diverse types as str, list, array.array etc.

However, to promote consistency, when applying len(o) to a user-defined type, Python calls o.__len__() as a fallback. __len__, __abs__ and all the other special methods documented in the Python Data Model make it easy to create objects that behave like the built-ins, enabling the expressive and highly consistent APIs we call "Pythonic".

By implementing special methods your objects can support iteration, overload infix operators, manage contexts in with blocks etc. You can think of the Data Model as a way of using the Python language itself as a framework where the objects you create can be integrated seamlessly.

A second reason, supported by quotes from Guido van Rossum like this one, is that it is easier to read and write len(s) than s.len().

The notation len(s) is consistent with unary operators with prefix notation, like abs(n). len() is used way more often than abs(), and it deserves to be as easy to write.

There may also be a historical reason: in the ABC language which preceded Python (and was very influential in its design), there was a unary operator written as #s which meant len(s).