If within an instance, I have self.foo = 1, what is the difference between these (or other more complicated examples):
# 1
for i in range(10):
print(self.foo)
# 2
foo = self.foo
for i in range(10):
print(foo)
I'm currently looking at a code base where all the self variables are reassigned to something else. Just wondering if there is any reason to do so and would like to hear both from an efficiency standpoint and a code clarity standpoint.
Consider these possibilities:
The local variable self gets rebound in the middle of the loop. (That's not possible with the specific code you've given, but a different loop could conceivably do it.) In that case, #1 will see the new self's foo attribute, while #2 will not. Although, of course, you could just as easily rebind the local variable foo as the local variable self…
self is mutable, and self.foo is rebound to a different value in the middle of the loop. (That could happen more easily with, e.g., another thread operating on the same object.) Again, #1 will see the new value of the foo attribute, but #2 will not.
self.foo is itself mutable, and its value is mutated in the middle of the loop (e.g., it's a list, and some other thread calls append(2) on it). Now both #1 and #2 will see the new value.
Everything is immutable, or there's just no code (including on other threads) to mutate anything. Now both #1 and #2 are going to see the original value, because there is no other value to see.
If any of those semantic differences are relevant, then of course you want to use whichever one gives you the right answer.
Meanwhile, every time you access self.foo, that requires doing an attribute lookup. In the most common case, this means looking up 'foo' in self.__dict__, which is pretty quick, but not free. And you can easily create pathological cases where it goes through 23 base classes in MRO order before calling a __getattr__ that creates the value on the fly and returns a descriptor whose __get__ method does some non-trivial transformation.
Accessing foo, on the other hand, is going to be compiled into just loading a value out of an array on the frame using a compiled-in index. So it will almost always be faster, and in some cases it can be a lot faster.
In most real-life cases, this doesn't matter at all. But occasionally, it does. In which case copying the value to a local outside the loop is a worthwhile micro-optimization. This is a little more common with bound methods than with normal values (because they always have a descriptor call in the way); see the unique_everseen recipe in the itertools docs for an example.
Of course you could contrive a case where this optimization actually made things slower—e.g., make that loop really tiny, but put the whole thing inside an outer loop. Now the extra self.foo copy each time through the outer loop (and the fact that the bytecode involved in the loop is longer and may spill onto another cache line) could cost a lot more than it saves.
If there's no semantic difference that matters, and the performance difference doesn't matter, then it's just a matter of clarify.
If the expression is a lot more complicated than self.foo, it may well be clearer to pull out the value and give it a name.
But for a trivial case like this, it's probably clearer to just use self.foo. By taking the extra step of copying it to a local variable, you're signaling that you had some reason to do so. So a reader will wonder whether maybe self.foo can get rebound in a different thread, or maybe this loop is a major bottleneck in your code and the self.foo access is a performance issue, etc., and waste time dealing with all of those irrelevancies instead of just reading your code as intended.
I want to get all object generated from another module, even the object do not have a name or reference, is it possible? For example:
in module1.py, there's only one line code:
MyClass()
in module2.py:
module1 = __import__("module1")
# print sth of MyClass from module1
What you're trying to do is generally impossible.
An object that has no name or other reference is garbage. That's the technical meaning of the term "garbage". In CPython (the Python implementation you're probably using if you don't know which one you're using), garbage is collected immediately—as soon as that MyClass() statement ends, the instance gets destroyed.
So, you can't access the object, because it doesn't exist.
In some other Python implementations, the object may not be destroyed until the next garbage collection cycle, but that's going to be pretty soon, and it's not deterministic exactly when—and you still have no way to get at it before it's destroyed. So it might as well not exist, even if it hasn't actually been finalized yet.
Now, "generally" means there are some exceptions. They're not common, but they do exist.
For example, imagine a class like this:
class MyClass:
_instances = []
def __init__(self):
MyClass._instances.append(self)
Now, when you do MyClass(), there actually is a reference to that instance, so it's not garbage. And, if you know where it is (which you'd presumably find in the documentation, or in the source code), you can access it as MyClass._instances[-1]. But it's unlikely that an arbitrary class MyClass does anything like this.
OK, I lied. There is sort of a way to do this, but (a) it’s cheating, and (b) it’s almost certainly a terrible idea that has no valid use cases you’ll ever think of. But just for fun, here’s how you could do this.
You need to write an import hook, and make sure it gets installed before the first time you import the module. Then you can do almost anything you want. The simplest idea I can think of is transforming the AST to turn every expression statement (or maybe just every expression statement at the top level) into an assignment statement that assigns to a hidden variable. You can even make the variable name an invalid identifier, so it'll be safe to run on any legal module no matter what's in the global namespace. Then you can access the first object created and abandoned by the module as something like module.globals()['.0'].
In other languages, a general guideline that helps produce better code is always make everything as hidden as possible. If in doubt about whether a variable should be private or protected, it's better to go with private.
Does the same hold true for Python? Should I use two leading underscores on everything at first, and only make them less hidden (only one underscore) as I need them?
If the convention is to use only one underscore, I'd also like to know the rationale.
Here's a comment I left on JBernardo's answer. It explains why I asked this question and also why I'd like to know why Python is different from the other languages:
I come from languages that train you to think everything should be only as public as needed and no more. The reasoning is that this will reduce dependencies and make the code safer to alter. The Python way of doing things in reverse -- starting from public and going towards hidden -- is odd to me.
When in doubt, leave it "public" - I mean, do not add anything to obscure the name of your attribute. If you have a class with some internal value, do not bother about it. Instead of writing:
class Stack(object):
def __init__(self):
self.__storage = [] # Too uptight
def push(self, value):
self.__storage.append(value)
write this by default:
class Stack(object):
def __init__(self):
self.storage = [] # No mangling
def push(self, value):
self.storage.append(value)
This is for sure a controversial way of doing things. Python newbies hate it, and even some old Python guys despise this default - but it is the default anyway, so I recommend you to follow it, even if you feel uncomfortable.
If you really want to send the message "Can't touch this!" to your users, the usual way is to precede the variable with one underscore. This is just a convention, but people understand it and take double care when dealing with such stuff:
class Stack(object):
def __init__(self):
self._storage = [] # This is ok, but Pythonistas use it to be relaxed about it
def push(self, value):
self._storage.append(value)
This can be useful, too, for avoiding conflict between property names and attribute names:
class Person(object):
def __init__(self, name, age):
self.name = name
self._age = age if age >= 0 else 0
#property
def age(self):
return self._age
#age.setter
def age(self, age):
if age >= 0:
self._age = age
else:
self._age = 0
What about the double underscore? Well, we use the double underscore magic mainly to avoid accidental overloading of methods and name conflicts with superclasses' attributes. It can be pretty valuable if you write a class to be extended many times.
If you want to use it for other purposes, you can, but it is neither usual nor recommended.
EDIT: Why is this so? Well, the usual Python style does not emphasize making things private - on the contrary! There are many reasons for that - most of them controversial... Let us see some of them.
Python has properties
Today, most OO languages use the opposite approach: what should not be used should not be visible, so attributes should be private. Theoretically, this would yield more manageable, less coupled classes because no one would change the objects' values recklessly.
However, it is not so simple. For example, Java classes have many getters that only get the values and setters that only set the values. You need, let us say, seven lines of code to declare a single attribute - which a Python programmer would say is needlessly complex. Also, you write a lot of code to get one public field since you can change its value using the getters and setters in practice.
So why follow this private-by-default policy? Just make your attributes public by default. Of course, this is problematic in Java because if you decide to add some validation to your attribute, it would require you to change all:
person.age = age;
in your code to, let us say,
person.setAge(age);
setAge() being:
public void setAge(int age) {
if (age >= 0) {
this.age = age;
} else {
this.age = 0;
}
}
So in Java (and other languages), the default is to use getters and setters anyway because they can be annoying to write but can spare you much time if you find yourself in the situation I've described.
However, you do not need to do it in Python since Python has properties. If you have this class:
class Person(object):
def __init__(self, name, age):
self.name = name
self.age = age
...and then you decide to validate ages, you do not need to change the person.age = age pieces of your code. Just add a property (as shown below)
class Person(object):
def __init__(self, name, age):
self.name = name
self._age = age if age >= 0 else 0
#property
def age(self):
return self._age
#age.setter
def age(self, age):
if age >= 0:
self._age = age
else:
self._age = 0
Suppose you can do it and still use person.age = age, why would you add private fields and getters and setters?
(Also, see Python is not Java and this article about the harms of using getters and setters.).
Everything is visible anyway - and trying to hide complicates your work
Even in languages with private attributes, you can access them through some reflection/introspection library. And people do it a lot, in frameworks and for solving urgent needs. The problem is that introspection libraries are just a complicated way of doing what you could do with public attributes.
Since Python is a very dynamic language, adding this burden to your classes is counterproductive.
The problem is not being possible to see - it is being required to see
For a Pythonista, encapsulation is not the inability to see the internals of classes but the possibility of avoiding looking at it. Encapsulation is the property of a component that the user can use without concerning about the internal details. If you can use a component without bothering yourself about its implementation, then it is encapsulated (in the opinion of a Python programmer).
Now, if you wrote a class you can use it without thinking about implementation details, there is no problem if you want to look inside the class for some reason. The point is: your API should be good, and the rest is details.
Guido said so
Well, this is not controversial: he said so, actually. (Look for "open kimono.")
This is culture
Yes, there are some reasons, but no critical reason. This is primarily a cultural aspect of programming in Python. Frankly, it could be the other way, too - but it is not. Also, you could just as easily ask the other way around: why do some languages use private attributes by default? For the same main reason as for the Python practice: because it is the culture of these languages, and each choice has advantages and disadvantages.
Since there already is this culture, you are well-advised to follow it. Otherwise, you will get annoyed by Python programmers telling you to remove the __ from your code when you ask a question in Stack Overflow :)
First - What is name mangling?
Name mangling is invoked when you are in a class definition and use __any_name or __any_name_, that is, two (or more) leading underscores and at most one trailing underscore.
class Demo:
__any_name = "__any_name"
__any_other_name_ = "__any_other_name_"
And now:
>>> [n for n in dir(Demo) if 'any' in n]
['_Demo__any_name', '_Demo__any_other_name_']
>>> Demo._Demo__any_name
'__any_name'
>>> Demo._Demo__any_other_name_
'__any_other_name_'
When in doubt, do what?
The ostensible use is to prevent subclassers from using an attribute that the class uses.
A potential value is in avoiding name collisions with subclassers who want to override behavior, so that the parent class functionality keeps working as expected. However, the example in the Python documentation is not Liskov substitutable, and no examples come to mind where I have found this useful.
The downsides are that it increases cognitive load for reading and understanding a code base, and especially so when debugging where you see the double underscore name in the source and a mangled name in the debugger.
My personal approach is to intentionally avoid it. I work on a very large code base. The rare uses of it stick out like a sore thumb and do not seem justified.
You do need to be aware of it so you know it when you see it.
PEP 8
PEP 8, the Python standard library style guide, currently says (abridged):
There is some controversy about the use of __names.
If your class is intended to be subclassed, and you have attributes that you do not want subclasses to use, consider naming them with double leading underscores and no trailing underscores.
Note that only the simple class name is used in the mangled name, so if a subclass chooses both the same class name and attribute name,
you can still get name collisions.
Name mangling can make certain uses, such as debugging and __getattr__() , less convenient. However the name mangling algorithm is well documented and easy to perform manually.
Not everyone likes name mangling. Try to balance the need to avoid accidental name clashes with potential use by advanced callers.
How does it work?
If you prepend two underscores (without ending double-underscores) in a class definition, the name will be mangled, and an underscore followed by the class name will be prepended on the object:
>>> class Foo(object):
... __foobar = None
... _foobaz = None
... __fooquux__ = None
...
>>> [name for name in dir(Foo) if 'foo' in name]
['_Foo__foobar', '__fooquux__', '_foobaz']
Note that names will only get mangled when the class definition is parsed:
>>> Foo.__test = None
>>> Foo.__test
>>> Foo._Foo__test
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AttributeError: type object 'Foo' has no attribute '_Foo__test'
Also, those new to Python sometimes have trouble understanding what's going on when they can't manually access a name they see defined in a class definition. This is not a strong reason against it, but it's something to consider if you have a learning audience.
One Underscore?
If the convention is to use only one underscore, I'd also like to know the rationale.
When my intention is for users to keep their hands off an attribute, I tend to only use the one underscore, but that's because in my mental model, subclassers would have access to the name (which they always have, as they can easily spot the mangled name anyways).
If I were reviewing code that uses the __ prefix, I would ask why they're invoking name mangling, and if they couldn't do just as well with a single underscore, keeping in mind that if subclassers choose the same names for the class and class attribute there will be a name collision in spite of this.
I wouldn't say that practice produces better code. Visibility modifiers only distract you from the task at hand, and as a side effect force your interface to be used as you intended. Generally speaking, enforcing visibility prevents programmers from messing things up if they haven't read the documentation properly.
A far better solution is the route that Python encourages: Your classes and variables should be well documented, and their behaviour clear. The source should be available. This is far more extensible and reliable way to write code.
My strategy in Python is this:
Just write the damn thing, make no assumptions about how your data should be protected. This assumes that you write to create the ideal interfaces for your problems.
Use a leading underscore for stuff that probably won't be used externally, and isn't part of the normal "client code" interface.
Use double underscore only for things that are purely convenience inside the class, or will cause considerable damage if accidentally exposed.
Above all, it should be clear what everything does. Document it if someone else will be using it. Document it if you want it to be useful in a year's time.
As a side note, you should actually be going with protected in those other languages: You never know your class might be inherited later and for what it might be used. Best to only protect those variables that you are certain cannot or should not be used by foreign code.
You shouldn't start with private data and make it public as necessary. Rather, you should start by figuring out the interface of your object. I.e. you should start by figuring out what the world sees (the public stuff) and then figure out what private stuff is necessary for that to happen.
Other language make difficult to make private that which once was public. I.e. I'll break lots of code if I make my variable private or protected. But with properties in python this isn't the case. Rather, I can maintain the same interface even with rearranging the internal data.
The difference between _ and __ is that python actually makes an attempt to enforce the latter. Of course, it doesn't try really hard but it does make it difficult. Having _ merely tells other programmers what the intention is, they are free to ignore at their peril. But ignoring that rule is sometimes helpful. Examples include debugging, temporary hacks, and working with third party code that wasn't intended to be used the way you use it.
There are already a lot of good answers to this, but I'm going to offer another one. This is also partially a response to people who keep saying that double underscore isn't private (it really is).
If you look at Java/C#, both of them have private/protected/public. All of these are compile-time constructs. They are only enforced at the time of compilation. If you were to use reflection in Java/C#, you could easily access private method.
Now every time you call a function in Python, you are inherently using reflection. These pieces of code are the same in Python.
lst = []
lst.append(1)
getattr(lst, 'append')(1)
The "dot" syntax is only syntactic sugar for the latter piece of code. Mostly because using getattr is already ugly with only one function call. It just gets worse from there.
So with that, there can't be a Java/C# version of private, as Python doesn't compile the code. Java and C# can't check if a function is private or public at runtime, as that information is gone (and it has no knowledge of where the function is being called from).
Now with that information, the name mangling of the double underscore makes the most sense for achieving "private-ness". Now when a function is called from the 'self' instance and it notices that it starts with '__', it just performs the name mangling right there. It's just more syntactic sugar. That syntactic sugar allows the equivalent of 'private' in a language that only uses reflection for data member access.
Disclaimer: I have never heard anybody from the Python development say anything like this. The real reason for the lack of "private" is cultural, but you'll also notice that most scripting/interpreted languages have no private. A strictly enforceable private is not practical at anything except for compile time.
First: Why do you want to hide your data? Why is that so important?
Most of the time you don't really want to do it but you do because others are doing.
If you really really really don't want people using something, add one underscore in front of it. That's it... Pythonistas know that things with one underscore is not guaranteed to work every time and may change without you knowing.
That's the way we live and we're okay with that.
Using two underscores will make your class so bad to subclass that even you will not want to work that way.
The chosen answer does a good job of explaining how properties remove the need for private attributes, but I would also add that functions at the module level remove the need for private methods.
If you turn a method into a function at the module level, you remove the opportunity for subclasses to override it. Moving some functionality to the module level is more Pythonic than trying to hide methods with name mangling.
Following code snippet will explain all different cases :
two leading underscores (__a)
single leading underscore (_a)
no underscore (a)
class Test:
def __init__(self):
self.__a = 'test1'
self._a = 'test2'
self.a = 'test3'
def change_value(self,value):
self.__a = value
return self.__a
printing all valid attributes of Test Object
testObj1 = Test()
valid_attributes = dir(testObj1)
print valid_attributes
['_Test__a', '__doc__', '__init__', '__module__', '_a', 'a',
'change_value']
Here, you can see that name of __a has been changed to _Test__a to prevent this variable to be overridden by any of the subclass. This concept is known as "Name Mangling" in python.
You can access this like this :
testObj2 = Test()
print testObj2._Test__a
test1
Similarly, in case of _a, the variable is just to notify the developer that it should be used as internal variable of that class, the python interpreter won't do anything even if you access it, but it is not a good practise.
testObj3 = Test()
print testObj3._a
test2
a variable can be accesses from anywhere it's like a public class variable.
testObj4 = Test()
print testObj4.a
test3
Hope the answer helped you :)
At first glance it should be the same as for other languages (under "other" I mean Java or C++), but it isn't.
In Java you made private all variables that shouldn't be accessible outside. In the same time in Python you can't achieve this since there is no "privateness" (as one of Python principles says - "We're all adults"). So double underscore means only "Guys, do not use this field directly". The same meaning has singe underscore, which in the same time doesn't cause any headache when you have to inherit from considered class (just an example of possible problem caused by double underscore).
So, I'd recommend you to use single underscore by default for "private" members.
"If in doubt about whether a variable should be private or protected, it's better to go with private." - yes, same holds in Python.
Some answers here say about 'conventions', but don't give the links to those conventions. The authoritative guide for Python, PEP 8 states explicitly:
If in doubt, choose non-public; it's easier to make it public later than to make a public attribute non-public.
The distinction between public and private, and name mangling in Python have been considered in other answers. From the same link,
We don't use the term "private" here, since no attribute is really private in Python (without a generally unnecessary amount of work).
#EXAMPLE PROGRAM FOR Python name mangling
class Demo:
__any_name = "__any_name"
__any_other_name_ = "__any_other_name_"
[n for n in dir(Demo) if 'any' in n] # GIVES OUTPUT AS ['_Demo__any_name',
# '_Demo__any_other_name_']
In python, we could do this,
class TT(object):
def __init__(self):
self.f='ff'
x=TT()
print x.f
If I change the code to:
class TT(object):
def__init__(uu):
uu.f='ff'
x=TT()
print x.f
I will get the same results, both are 'ff'. Is 'uu' here just the alias for 'self'? Or any other difference? When should I use this?
Thanks.
There is no name for the object variable that is set in stone: you can use practically whatever name you want to identify it. However, to easily distinguish between the object variable and other passed variables, it is a commonly-adopted convention to name that variable "self", just to make it more readable for others who are examining your code.
You can technically use whatever name you want, but it is considered bad practice in the programming world.
It's not just __init__, it's all Python's methods: self is merely a convention. The first variable in the method will be the object itself, and it doesn't matter how you name it, self or uu or big_honcho or this; but if you use anything but self, people who read your code will likely be confused for a second or a thousand.
This is in contrast to many other OO languages which have an implicit variable for the current object, usually either self (e.g. Ruby) or this (e.g. JavaScript).
I am new to OOP and hence, am looking for suggestions on good practice for coding something where the following issue arises.
I am defining a Seller(a, b, c, d) class. There are many attributes of this class, two of which are, mostRecentProfit and profitHistory. However, values of these two are not known when the class is initialized. Some other steps in the program have to be executed before these are realized. My questions is:
In the __init__(a, b, c, d) of the seller class, should I write
self.mostRecentProfit = None
self.profitHistory = []
or, should I not define these at all in the __init__ method. The reason former appears attractive to me is that by looking at the __init__() method, I can know all the attributes for the class. However, that may not be a good reason for doing this. Any suggestions would be appreciated.
Thank you.
Defining the attributes in __init__() makes the code better for when someone who has not seen the code has to start working with it. It can be confusing when a class starts accessing an attribute that doesn't seem to exist at first.
Also, since one of your default values is a list instead of None, initializing it means you can always treat the attribute as a list and never have to worry about it's state.
I would define them. In my experience, not doing so when the code dealing with the instances makes frequent references to those properties, means you end up forever typing if object.profitHistory: before looping etc. With an empty list there, you can skip those conditions. And as you say, it makes it much more legible.
I would define them all in the __init() method because that would not only document what they all normally were, but if you define their default values to all be something valid, allow most of the rest of your code to easily process instances of the class even if these attributes never get updated.
So, in your example, that would mean initializing self.mostRecentProfit to 0 or perhaps 0.0 rather than None. Doing this would allow it to be used as a number without checking for it's existence with a value not equal to None before each reference to it or wrapping each of them in a try/except block to handle the cases where they were never explicitly set to another value.