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_']
I have a hierarchy of data that i would like to build using classes instead of hard coding it in. The structure is like so:
Unit (has name, abbreviation, subsystems[5 different types of subsystems])
Subsystem ( has type, block diagram(photo), ParameterModel[20 different sets of parameterModels])
ParameterModel (30 or so parameters that will have [parameter name, value, units, and model index])
I'm not sure how to do this using classes but what i have made kindof work so far is creating nested dictionaries.
{'Unit':{'Unit1':{'Subsystem':{'Generator':{Parameter:{'Name': param1, 'Value':1, 'Units': 'seconds'}
like this but with 10-15 units and 5-6 subsystems and 30 or so parameters per subsystem. I know using dictionaries is not the best way to go about it but i cannot figure out the class sharing structure or where to start on building the class structure.
I want to be able to create, read, update and delete, parameters in a tkinter gui that i have built as well as export/import these system parameters and do calculations on them. I can handle the calculations and the import export but i need to create classes that will build out this structure and be able to reference each individual unit/subsystem/parameter/value/etc
I know thats alot but any advice? ive been looking into the factory and abstract factory patterns in hope to try and figure out how to create the code structure but to no avail. I have experience with matlab, visual basic, c++, and various arduio projects so i know most basic programming but this inheritance class structure is something i cannot figure out how to do in an abstract way without hardcoding each parameter with giant names like Unit1_Generator_parameterName_parameter = ____ and i really dont want to do that.
Thanks,
-A
EDIT: Here is one way I've done the implementation using a dictionary but i would like to do this using a class that can take a list and make a bunch of empty attributes and have those be editable/callable generally like setParamValue(unit, susystem, param) where i can pass the unit the subsystem and then the parameter such as 'Td' and then be able to change the value of the key,value pair within this hierarchy.
def create_keys(list):
dict = {key: None for key in list}
return dict
unit_list = ['FL','ES','NN','SF','CC','HD','ND','TH'] #unit abbreviation
sub_list = ['Gen','Gov','Exc','PSS','Rel','BlkD']
params_GENROU = ["T'do","T''do","T'qo","T''qo",'H','D','Xd','Xq',"Xd'","Xq'","X''d=X''q",'Xl','S(1.0)','S(1.2)','Ra'] #parameter names
dict = create_keys(unit_list)
for key in dict:
dict[key] = create_keys(sub_list)
dict[key]['Gen'] = create_keys(params_GENROU)
and inside each dict[unit][Gen][ParamNames] there should be a dict containing Value, units(seconds,degrees,etc), description and CON(#basically in index for another program we use)
MyClass is derived from "list": MyClass(list)
I would like to document MyClass nicely.
Unfortunately, when trying help(MyClass),
I get my own documentation, but I also get a lot of stuff about "list".
Would there be a simple way to control that?
I read something about metaclasses, but I was unable to do something.
Thanks for your suggestions,
Michel
Well, that is what help does. It introspects into your class and show the name and the associated __doc__ for each callable attribute in the class, and that is not customizable.
Attributes of the superclass are considered attributes of the class, and are reached in the introspection Python's help do.
Metaclasses could even be used to customize the output one gets when he does "dir" on your class - but they do not change the output of the help text. To change "dir" output, create a metaclass implementing a __dir__ method, and return a list of what you want visible as dir's output.
class M(type):
def __dir__(self):
return [] # blank dir contents
class MyList(list, metaclass=M):
...
On the other hand, the help contents displayed for list attributes are not that verbose, and can actually be helpful - if you override any methods to do something different than described, the incorrect text won't show anyway. So you might just live with it.
Another tip is that instead of subclassing list you might prefer to subclass collections.abc.MutableSequence instead, and use an inner agregated (normal) list to keep your data: that will require you to implement a lot less methods to have your class working properly as a sequence and is preferable in most cases to subclass list. That won't change help's verbosity though.
I am trying to programmatically access all fields of some Python3 object using a combination of dir and getattr. Pseudocode below:
x = some_object()
for i in dir(x):
print(str(getattr(x, i)))
However, the Python docs (https://docs.python.org/2/library/functions.html#dir) on dir is VERY vague:
Note Because dir() is supplied primarily as a convenience for use at an interactive prompt, it tries to supply an interesting set of names more than it tries to supply a rigorously or consistently defined set of names, and its detailed behavior may change across releases.
My questions:
1) Is there a way to achieve the above more rigorously than using dir?
2) What does "interesting set of names" mean and how is it computed?
Kind of?
With custom __getattr__ and __getattribute__ implementations, an object can dynamically respond to requests for any attribute. You could have an object that has every attribute, or an object that randomly has or doesn't have the foo attribute with 50% probability every time you look at it. If you know how an object's __getattr__ and __getattribute__ work, and you know that they respond to a finite list of attribute names, then you can write your own version of dir that lists everything, but even handling the basic built-in types requires an uncomfortable number of cases. You can see the dir implementation in Objects/object.c.
The documentation gives an explanation of which attributes are considered interesting:
If the object is a module object, the list contains the names of the module’s attributes.
If the object is a type or class object, the list contains the names of its attributes, and recursively of the attributes of its bases.
Otherwise, the list contains the object’s attributes’ names, the names of its class’s attributes, and recursively of the attributes of its class’s base classes.
By "attributes", this documentation is mostly referring to the keys of its __dict__. There's also some handling for __members__ and __methods__; those are deprecated, and I don't remember what they do.