I read on another Stack Overflow question that Python was just like Ruby, as it relates to "everything's an object," and everything in Python was an object, just like Ruby.
Is this true? Is everything an object in Python like Ruby?
How are the two different in this respect or are they really the same? For example, can you take a number and do the Ruby stuff I've seen like:
y = 5.plus 6
Can that be done the same way in Python?
DiveIntoPython - Everything Is an Object
Everything in Python is an object, and almost everything has attributes and methods. All functions have a built-in attribute
__doc__, which returns thedoc stringdefined in the function's source code. Thesysmodule is an object which has (among other things) an attribute calledpath. And so forth.Still, this begs the question. What is an object? Different programming languages define “object” in different ways. In some, it means that all objects must have attributes and methods; in others, it means that all objects are subclassable. In Python, the definition is looser; some objects have neither attributes nor methods (more on this in Chapter 3), and not all objects are subclassable (more on this in Chapter 5). But everything is an object in the sense that it can be assigned to a variable or passed as an argument to a function (more in this in Chapter 4).
Ruby Docs - To Ruby From Python
As with Python, in Ruby,... Everything is an object
So there you have it from Ruby's own website: in Python everything is an object.
One of my goals for Python was to make it so that all objects were "first class." By this, I meant that I wanted all objects that could be named in the language (e.g., integers, strings, functions, classes, modules, methods, etc.) to have equal status. That is, they can be assigned to variables, placed in lists, stored in dictionaries, passed as arguments, and so forth. –
Charlinecharlock x is not an object, it is a name (possibly one of many) of an object. –
Furcate While everything is an object in Python, it differs from Ruby in its approach to resolving names and interacting with objects.
For example, while Ruby provides you with a 'to_s' method on the Object base class, in order to expose that functionality, Python integrates it into the string type itself - you convert a type to a string by constructing a string from it. Instead of 5.to_s, you have str(5).
Don't be fooled, though. There's still a method behind the scenes - which is why this code works:
(5).__str__()
So in practice, the two are fundamentally similar, but you use them differently. Length for sequences like lists and tuples in Python is another example of this principle at work - the actual feature is built upon methods with special names, but exposed through a simpler, easier-to-use interface (the len function).
The Python equivalent to what you wrote in your question would thus be:
(5).__add__(6)
The other difference that's important is how global functions are implemented. In Python, globals are represented by a dictionary (as are locals). This means that the following:
foo(5)
Is equivalent to this in Python:
globals()["foo"].__call__(5)
While Ruby effectively does this:
Object.foo(5)
This has a large impact on the approach used when writing code in both languages. Ruby libraries tend to grow through the addition of methods to existing types like Object, while Python libraries tend to grow through the addition of global functions to a given module.
"everything" is a tad of an overbid, for both Python and Ruby -- for example, if is not "an object", rather it's a keyword used to start a conditional statement or (in Python) inside list comprehensions and generator expressions. The enthusiasm of finding out that functions, classes, methods, and all sort of such things that aren't really objects in (say) C++, are objects in Ruby or Python, causes such enthusiasm. Other things may be objects in Ruby but not Python or viceversa (code blocks, regular expressions, ...).
proc, &, &: and define_method. –
Exercise In answer to your second question, yes:
>>> (1).__add__(2)
3
1. __add__(2) (note the space). Will even work for floats: 1..__add__(2). –
Disavow 1 .__add__(2) –
Rosyrot Yep, as far as I know everything is an object in Python. Certainly the primitive and builtin types (int, long, str, float, etc.) can be subclassed - and in fact the types themselves are objects. Functions are objects, classes are objects, even code blocks are objects in a sense... I can't think of anything in Python that can't be treated as an object.
# comment an object? This isn't a criticism; I'm honestly curious. –
Tolly if is an object. –
Hardened Hello and answer is out of the bat not everything, reference is more complete than that and offers many more avenues, within Python 3.8.5 for example Delimiters, Operators and Keywords are not objects. https://mcmap.net/q/37458/-everything-in-python-is-an-object-why-operators-are-not
Have explained it with some detail in that link feel free to check it along.
Anyway, next one says that statement you can correct it by saying (something more correct, although if still can be more completed feel free): "Everything in a logical line that is not NEWLINE, INDENT, DEDENT, Space bar Character, Operator, Keyword or Delimiter is an object in Python."
Cheers.
To add a comment to other people's excellent answers: everything is an object, but some – notably strings and numeric types – are immutable. This means that these types behave the way they do in languages like C or Java (where integers, etc. are not objects) with respect to assignment, parameter passing, etc, and you never have to worry about traps caused by pass-by-reference. It's rather a good solution :-)
Yes, everything is object in Python as long as I researched.
The documentation says below:
Objects are Python’s abstraction for data. All data in a Python program is represented by objects or by relations between objects.
Every object has an identity, a type and a value.
And, I also checked the type of each value and if each of them is the instance of a particular class as shown below:
from types import FunctionType
class Person:
pass
def test():
pass
print(type("Hello"), isinstance("Hello", str))
print(type(100), isinstance(100, int))
print(type(100.23), isinstance(100.23, float))
print(type(100 + 2j), isinstance(100 + 2j, complex))
print(type(True), isinstance(True, bool))
print(type(None), isinstance(None, type(None)))
print(type([]), isinstance([], list))
print(type(()), isinstance((), tuple))
print(type({}), isinstance({}, dict))
print(type({""}), isinstance({""}, set))
print(type(Person), isinstance(Person, type))
print(type(test), isinstance(test, FunctionType))
Output:
<class 'str'> True
<class 'int'> True
<class 'float'> True
<class 'complex'> True
<class 'bool'> True
<class 'NoneType'> True
<class 'list'> True
<class 'tuple'> True
<class 'dict'> True
<class 'set'> True
<class 'type'> True
<class 'function'> True
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nilis an object), but beyond that it gets more tricky. Classes are objects, methods are not. Procs are objects, blocks are not. (but both a method and a block can be converted into and from a Proc). Bindings are objects, local variables are not. Etc... – Exercise