Addressing instance name string in __init__(self) in Python - python

I am doing something like this:
class Class(object):
def __init__(self):
self.var=#new instance name string#
How do I make the __ init __ method of my instance to use the instance name string for 'c'? Say in case:
c=Class()
I want c.var equal to 'c'.
Thanks for your replies, I am implementing persistence and Class is persistent object's class. I want __ init __ to add an entry to the database when:
c=Class()
Then, suppose:
del c
Later on:
c=Class()
sholuld create an instance using data from database if there already is an entry 'c', otherwise create new entry.
Thanks for your replies, I am implementing persistence and Class is persistent object's class. I want __ init __ to add an entry to the database when:
c=Class()
Then, suppose:
del c
Later on:
c=Class()
sholuld create an instance using data from database if there already is an entry 'c', otherwise create new entry.

Python doesn't have variables, it has objects and names. When you do
c = Class()
you're doing two things:
Creating a new object of type Class
Binding the object to the name c in the current scope.
The object you created doesn't have any concept of a "variable name" -- If later you do
a = c
then the same object is accessible in exactly the same way using the names a and c. You can delete the name a, and the object would still exist.
If the objects you create need to have a name, the best way is to pass it to them explicitly,
class Class(object):
def __init__(self, name):
self.name = name
var = Class('var')

You can't do this. The reason for this is that the object of the class is created first, and only afterwards is this object bound to the name of the instance.

You can't (short of incredible hacks like examining the stack frame and inspecting the bytecode). There may not even be a name, or there could be multiple such names. What should be given for the following code fragments for instance:
l = [Class(), Class()]
a=b=c=d=Class()

I don't think this would be possible because the assignment to the variable of your new instance occours after the object is fully constructed and initialized and so you don't know the variable name it will be assigned to within init method

To persist data objects you need to use the database record's unique ID.
pesudo code because I don't know what database module you're using
import db # assume this is your db module
class Class(object):
def __init__(self):
self.id = None
self.name = None
def get_by_id(self, id):
records = db.execute('select * from table where id=%s' % str(id))
if records:
self.id = records[0]['id']
self.name = records[0]['name']
def save(self):
db.execute('update table set name=%s where id=%s' % (self.name, str(self.id)))
Again, this is pseudo code, the string injection technique I'm using is NOT advised as its fairly insecure, its just there to illustrate how to persist using classes with a db.

I am unaware of a way to access a variable's name programmatically without using deep reflection and a debugger. I do not think the information is available at runtime.
If you want to give instances a (unique?) name, you should probably make the initializer accept an extra argument.
def __init__(self, name):
self.name = name
And the caller should pass in the appropriate name:
c = Class("c")

This is a scope issue, you can't do what you're asking. Because c would be declared outside your class' scope, your instance is unaware of what its been named in code.
Perhaps if you can provide a broader explanation of what you're trying to accomplish a better solution can be suggested.

That isn't possible. You seem to be confusing variables and objects.
In any case there may well not be a variable:
e.g.
foo(Class())
Class().arbitraryMethod()
Or multiple:
a = b = Class()

I have the same thought several years ago. This is somekind of neat feature, but the language creator doesn't provide it. And I thought they are all fool to not discover this great feature.
But then come to think about that. I think the logic is impossible. say:
class Class(object):
def __init__(self):
self.instance_name.move() # self.instance_name refer to var
def move(self):
print "move"
var = Class()
now if the var is an array is that possible too ?
var[0] = Class() # i think it will get confused a bit
that's what i think of, i don't think that assigning the instance into itself is possible. and in some language I just sent the instance string into the object then using eval to execute the function

Related

What is the difference between assign and declare a variable in python? [duplicate]

I want to clarify how variables are declared in Python.
I have seen variable declaration as
class writer:
path = ""
sometimes, there is no explicit declaration but just initialization using __init__:
def __init__(self, name):
self.name = name
I understand the purpose of __init__, but is it advisable to declare variable in any other functions?
How can I create a variable to hold a custom type?
class writer:
path = "" # string value
customObj = ??
Okay, first things first.
There is no such thing as "variable declaration" or "variable initialization" in Python.
There is simply what we call "assignment", but should probably just call "naming".
Assignment means "this name on the left-hand side now refers to the result of evaluating the right-hand side, regardless of what it referred to before (if anything)".
foo = 'bar' # the name 'foo' is now a name for the string 'bar'
foo = 2 * 3 # the name 'foo' stops being a name for the string 'bar',
# and starts being a name for the integer 6, resulting from the multiplication
As such, Python's names (a better term than "variables", arguably) don't have associated types; the values do. You can re-apply the same name to anything regardless of its type, but the thing still has behaviour that's dependent upon its type. The name is simply a way to refer to the value (object). This answers your second question: You don't create variables to hold a custom type. You don't create variables to hold any particular type. You don't "create" variables at all. You give names to objects.
Second point: Python follows a very simple rule when it comes to classes, that is actually much more consistent than what languages like Java, C++ and C# do: everything declared inside the class block is part of the class. So, functions (def) written here are methods, i.e. part of the class object (not stored on a per-instance basis), just like in Java, C++ and C#; but other names here are also part of the class. Again, the names are just names, and they don't have associated types, and functions are objects too in Python. Thus:
class Example:
data = 42
def method(self): pass
Classes are objects too, in Python.
So now we have created an object named Example, which represents the class of all things that are Examples. This object has two user-supplied attributes (In C++, "members"; in C#, "fields or properties or methods"; in Java, "fields or methods"). One of them is named data, and it stores the integer value 42. The other is named method, and it stores a function object. (There are several more attributes that Python adds automatically.)
These attributes still aren't really part of the object, though. Fundamentally, an object is just a bundle of more names (the attribute names), until you get down to things that can't be divided up any more. Thus, values can be shared between different instances of a class, or even between objects of different classes, if you deliberately set that up.
Let's create an instance:
x = Example()
Now we have a separate object named x, which is an instance of Example. The data and method are not actually part of the object, but we can still look them up via x because of some magic that Python does behind the scenes. When we look up method, in particular, we will instead get a "bound method" (when we call it, x gets passed automatically as the self parameter, which cannot happen if we look up Example.method directly).
What happens when we try to use x.data?
When we examine it, it's looked up in the object first. If it's not found in the object, Python looks in the class.
However, when we assign to x.data, Python will create an attribute on the object. It will not replace the class' attribute.
This allows us to do object initialization. Python will automatically call the class' __init__ method on new instances when they are created, if present. In this method, we can simply assign to attributes to set initial values for that attribute on each object:
class Example:
name = "Ignored"
def __init__(self, name):
self.name = name
# rest as before
Now we must specify a name when we create an Example, and each instance has its own name. Python will ignore the class attribute Example.name whenever we look up the .name of an instance, because the instance's attribute will be found first.
One last caveat: modification (mutation) and assignment are different things!
In Python, strings are immutable. They cannot be modified. When you do:
a = 'hi '
b = a
a += 'mom'
You do not change the original 'hi ' string. That is impossible in Python. Instead, you create a new string 'hi mom', and cause a to stop being a name for 'hi ', and start being a name for 'hi mom' instead. We made b a name for 'hi ' as well, and after re-applying the a name, b is still a name for 'hi ', because 'hi ' still exists and has not been changed.
But lists can be changed:
a = [1, 2, 3]
b = a
a += [4]
Now b is [1, 2, 3, 4] as well, because we made b a name for the same thing that a named, and then we changed that thing. We did not create a new list for a to name, because Python simply treats += differently for lists.
This matters for objects because if you had a list as a class attribute, and used an instance to modify the list, then the change would be "seen" in all other instances. This is because (a) the data is actually part of the class object, and not any instance object; (b) because you were modifying the list and not doing a simple assignment, you did not create a new instance attribute hiding the class attribute.
This might be 6 years late, but in Python 3.5 and above, you can give a hint about a variable type like this:
variable_name: type_name
or this:
variable_name # type: shinyType
This hint has no effect in the core Python interpreter, but many tools will use it to aid the programmer in writing correct code.
So in your case(if you have a CustomObject class defined), you can do:
customObj: CustomObject
See this or that for more info.
There's no need to declare new variables in Python. If we're talking about variables in functions or modules, no declaration is needed. Just assign a value to a name where you need it: mymagic = "Magic". Variables in Python can hold values of any type, and you can't restrict that.
Your question specifically asks about classes, objects and instance variables though. The idiomatic way to create instance variables is in the __init__ method and nowhere else — while you could create new instance variables in other methods, or even in unrelated code, it's just a bad idea. It'll make your code hard to reason about or to maintain.
So for example:
class Thing(object):
def __init__(self, magic):
self.magic = magic
Easy. Now instances of this class have a magic attribute:
thingo = Thing("More magic")
# thingo.magic is now "More magic"
Creating variables in the namespace of the class itself leads to different behaviour altogether. It is functionally different, and you should only do it if you have a specific reason to. For example:
class Thing(object):
magic = "Magic"
def __init__(self):
pass
Now try:
thingo = Thing()
Thing.magic = 1
# thingo.magic is now 1
Or:
class Thing(object):
magic = ["More", "magic"]
def __init__(self):
pass
thing1 = Thing()
thing2 = Thing()
thing1.magic.append("here")
# thing1.magic AND thing2.magic is now ["More", "magic", "here"]
This is because the namespace of the class itself is different to the namespace of the objects created from it. I'll leave it to you to research that a bit more.
The take-home message is that idiomatic Python is to (a) initialise object attributes in your __init__ method, and (b) document the behaviour of your class as needed. You don't need to go to the trouble of full-blown Sphinx-level documentation for everything you ever write, but at least some comments about whatever details you or someone else might need to pick it up.
For scoping purpose, I use:
custom_object = None
Variables have scope, so yes it is appropriate to have variables that are specific to your function. You don't always have to be explicit about their definition; usually you can just use them. Only if you want to do something specific to the type of the variable, like append for a list, do you need to define them before you start using them. Typical example of this.
list = []
for i in stuff:
list.append(i)
By the way, this is not really a good way to setup the list. It would be better to say:
list = [i for i in stuff] # list comprehension
...but I digress.
Your other question.
The custom object should be a class itself.
class CustomObject(): # always capitalize the class name...this is not syntax, just style.
pass
customObj = CustomObject()
As of Python 3, you can explicitly declare variables by type.
For instance, to declare an integer one can do it as follows:
x: int = 3
or:
def f(x: int):
return x
see this question for more detailed info about it:
Explicitly declaring a variable type in Python

Can I declare a variable firmly typed as an integer in Python, like I do in Java? [duplicate]

I want to clarify how variables are declared in Python.
I have seen variable declaration as
class writer:
path = ""
sometimes, there is no explicit declaration but just initialization using __init__:
def __init__(self, name):
self.name = name
I understand the purpose of __init__, but is it advisable to declare variable in any other functions?
How can I create a variable to hold a custom type?
class writer:
path = "" # string value
customObj = ??
Okay, first things first.
There is no such thing as "variable declaration" or "variable initialization" in Python.
There is simply what we call "assignment", but should probably just call "naming".
Assignment means "this name on the left-hand side now refers to the result of evaluating the right-hand side, regardless of what it referred to before (if anything)".
foo = 'bar' # the name 'foo' is now a name for the string 'bar'
foo = 2 * 3 # the name 'foo' stops being a name for the string 'bar',
# and starts being a name for the integer 6, resulting from the multiplication
As such, Python's names (a better term than "variables", arguably) don't have associated types; the values do. You can re-apply the same name to anything regardless of its type, but the thing still has behaviour that's dependent upon its type. The name is simply a way to refer to the value (object). This answers your second question: You don't create variables to hold a custom type. You don't create variables to hold any particular type. You don't "create" variables at all. You give names to objects.
Second point: Python follows a very simple rule when it comes to classes, that is actually much more consistent than what languages like Java, C++ and C# do: everything declared inside the class block is part of the class. So, functions (def) written here are methods, i.e. part of the class object (not stored on a per-instance basis), just like in Java, C++ and C#; but other names here are also part of the class. Again, the names are just names, and they don't have associated types, and functions are objects too in Python. Thus:
class Example:
data = 42
def method(self): pass
Classes are objects too, in Python.
So now we have created an object named Example, which represents the class of all things that are Examples. This object has two user-supplied attributes (In C++, "members"; in C#, "fields or properties or methods"; in Java, "fields or methods"). One of them is named data, and it stores the integer value 42. The other is named method, and it stores a function object. (There are several more attributes that Python adds automatically.)
These attributes still aren't really part of the object, though. Fundamentally, an object is just a bundle of more names (the attribute names), until you get down to things that can't be divided up any more. Thus, values can be shared between different instances of a class, or even between objects of different classes, if you deliberately set that up.
Let's create an instance:
x = Example()
Now we have a separate object named x, which is an instance of Example. The data and method are not actually part of the object, but we can still look them up via x because of some magic that Python does behind the scenes. When we look up method, in particular, we will instead get a "bound method" (when we call it, x gets passed automatically as the self parameter, which cannot happen if we look up Example.method directly).
What happens when we try to use x.data?
When we examine it, it's looked up in the object first. If it's not found in the object, Python looks in the class.
However, when we assign to x.data, Python will create an attribute on the object. It will not replace the class' attribute.
This allows us to do object initialization. Python will automatically call the class' __init__ method on new instances when they are created, if present. In this method, we can simply assign to attributes to set initial values for that attribute on each object:
class Example:
name = "Ignored"
def __init__(self, name):
self.name = name
# rest as before
Now we must specify a name when we create an Example, and each instance has its own name. Python will ignore the class attribute Example.name whenever we look up the .name of an instance, because the instance's attribute will be found first.
One last caveat: modification (mutation) and assignment are different things!
In Python, strings are immutable. They cannot be modified. When you do:
a = 'hi '
b = a
a += 'mom'
You do not change the original 'hi ' string. That is impossible in Python. Instead, you create a new string 'hi mom', and cause a to stop being a name for 'hi ', and start being a name for 'hi mom' instead. We made b a name for 'hi ' as well, and after re-applying the a name, b is still a name for 'hi ', because 'hi ' still exists and has not been changed.
But lists can be changed:
a = [1, 2, 3]
b = a
a += [4]
Now b is [1, 2, 3, 4] as well, because we made b a name for the same thing that a named, and then we changed that thing. We did not create a new list for a to name, because Python simply treats += differently for lists.
This matters for objects because if you had a list as a class attribute, and used an instance to modify the list, then the change would be "seen" in all other instances. This is because (a) the data is actually part of the class object, and not any instance object; (b) because you were modifying the list and not doing a simple assignment, you did not create a new instance attribute hiding the class attribute.
This might be 6 years late, but in Python 3.5 and above, you can give a hint about a variable type like this:
variable_name: type_name
or this:
variable_name # type: shinyType
This hint has no effect in the core Python interpreter, but many tools will use it to aid the programmer in writing correct code.
So in your case(if you have a CustomObject class defined), you can do:
customObj: CustomObject
See this or that for more info.
There's no need to declare new variables in Python. If we're talking about variables in functions or modules, no declaration is needed. Just assign a value to a name where you need it: mymagic = "Magic". Variables in Python can hold values of any type, and you can't restrict that.
Your question specifically asks about classes, objects and instance variables though. The idiomatic way to create instance variables is in the __init__ method and nowhere else — while you could create new instance variables in other methods, or even in unrelated code, it's just a bad idea. It'll make your code hard to reason about or to maintain.
So for example:
class Thing(object):
def __init__(self, magic):
self.magic = magic
Easy. Now instances of this class have a magic attribute:
thingo = Thing("More magic")
# thingo.magic is now "More magic"
Creating variables in the namespace of the class itself leads to different behaviour altogether. It is functionally different, and you should only do it if you have a specific reason to. For example:
class Thing(object):
magic = "Magic"
def __init__(self):
pass
Now try:
thingo = Thing()
Thing.magic = 1
# thingo.magic is now 1
Or:
class Thing(object):
magic = ["More", "magic"]
def __init__(self):
pass
thing1 = Thing()
thing2 = Thing()
thing1.magic.append("here")
# thing1.magic AND thing2.magic is now ["More", "magic", "here"]
This is because the namespace of the class itself is different to the namespace of the objects created from it. I'll leave it to you to research that a bit more.
The take-home message is that idiomatic Python is to (a) initialise object attributes in your __init__ method, and (b) document the behaviour of your class as needed. You don't need to go to the trouble of full-blown Sphinx-level documentation for everything you ever write, but at least some comments about whatever details you or someone else might need to pick it up.
For scoping purpose, I use:
custom_object = None
Variables have scope, so yes it is appropriate to have variables that are specific to your function. You don't always have to be explicit about their definition; usually you can just use them. Only if you want to do something specific to the type of the variable, like append for a list, do you need to define them before you start using them. Typical example of this.
list = []
for i in stuff:
list.append(i)
By the way, this is not really a good way to setup the list. It would be better to say:
list = [i for i in stuff] # list comprehension
...but I digress.
Your other question.
The custom object should be a class itself.
class CustomObject(): # always capitalize the class name...this is not syntax, just style.
pass
customObj = CustomObject()
As of Python 3, you can explicitly declare variables by type.
For instance, to declare an integer one can do it as follows:
x: int = 3
or:
def f(x: int):
return x
see this question for more detailed info about it:
Explicitly declaring a variable type in Python

Python class: How to check whether an attribute is defined inside __init__ or outside __init__

So if I have an class like this:
class A:
def __init__(self):
self.a = 1
obj = A()
obj.b = 2
Since I need to write a __setattr__ method to modify the attributes (ex. if it was defined inside __init__ then do something; if it was defined outside __init__ do something else. How do I determine if it was declared in init or not?
def __setattr__(self,name,value):
if name not in self.__dict__:
self.__dict__['ABC'+ name] = value # add 'ABC' before attribute's name if it was declared in __init__
else:
self.__dict__[name] = value # if it was declared outside __init__ then the attribute name doesn't change
Most of the instance attributes that you define or the parent class (or object) does are going to behave the same and be for the most part indistinguishable. If you really want to distinguish them for whatever reason, you should yourself create a way to identify them, perhaps by using a dictionary instead.
class A:
def __init__(self):
self.my_variables = {'a': 1}
# Or maintain a list with their names, it seems ugly however
self.my_variables = ['a']
With that said, I am not at all clear about why you want to do this. Maybe you should try looking for a simpler solution to the problem than overriding __setattr__.
Update:
It seems to me that you're trying to restrict updation of variables, perhaps in your attempt to create "real private variables". In my advice, don't. There's a reason that Python allows you to do a lot of things that might seem insane from point of view of Static languages. You should just start your variables with _ to mark them as private similar to what Python recommends. If people are going to access them anyway, then what's stopping them from finding a workaround to circumvent the "restrictions" that you're trying to enforce? Besides, sometimes there is a genuine justification for accessing private variables.

method to print name of an instance of a class

I am new to classes and writing one to perform a tracking and timing task. Have looked at this but still having trouble getting one aspect of the functionality to work.
Here's the part of what I've got to demonstrate the problem:
class seperate_trackers():
def __init__(self):
print ("class initiated")
def print_instance_name(self):
print (self.__class__.__name__)
Create an instance of it:
track_task1 = separate_trackers()
>> class initiated
Run the method in there:
track_task1.print_instance_name()
>> separate_trackers
That's not what I want!
How can that method be fixed so it returns track_task1 when it is run?
This is not a good idea. If you want your instance to have a name, that should be an attribute of the instance itself (the name of the variabe is just a pointer and it should not represent the object's state).
Try this instead:
# We don't usually use snake case for class names in python (and its 'separate')
class SeparateTrackers():
def __init__(self, name):
self.name = name
instance1 = SeparateTrackers("instance_name")
print(instance1.name) # instance_name
Objects don't know what variables refer to them. There can be any number of references to an object, and none of them is "the real one," they are all equally valid as names for the object. Furthermore, there may be no references that are simple names:
things = [1, "hello", separate_trackers(), 3.14]
There's no useful way to find out what variables refer to an object.
class SeparateTrackers:
def __init__(self, instance_name):
self.instance_name = instance_name
def __str__(self):
return self.instance_name
So you can use something like
a = SeparateTracker("first instance")
print(a) # print instance's name

Calling type(dict) functions within classes on class variables (Python 3.4)

I am creating a class and trying to define class variables that correspond to a function like .keys() or .values() that are called on another class variable.
For example:
class DATA(object):
def __init__(self, id, database = {}):
self.id = id
self.database = database
self.addresses = database.keys()
self.data = database.values()
This does not seem to work, as when I create an instance of the class
foo = DATA(0,{"a":1,"b":2})
and then ask for:
print(foo.addresses)
>>> []
and it gives back an empty list.
Note:
On my actual program I start out with an empty dictionary for any class instance, then later on I use a function to add to the dictionary. In this case calling the ".database" still works but ".addresses" does not.
Can anyone help me with this problem?
I'm not sure that this is the problem, but using a mutable such as {} as a default argument often leads to bugs. See: "Least Astonishment" and the Mutable Default Argument
This is safer:
def __init__(self, id, database=None):
if database is None:
self.database = {}
else:
self.database = database
I don't understand the purpose of DATA.addresses and DATA.data. Could you use functions with the property decorator instead, to avoid redundancy?
#property:
def addresses(self):
return self.database.keys()
#property:
def data(self):
return self.database.values()
The issue is that you're calling keys right in your __init__ method, and saving the result. What you want to do instead is to call keys only when you want to access it.
Now, depending on the requirements of your class, you may be able to do this in a few different ways.
If you don't mind exposing changing the calling code quite a bit, you could make it very simple, just use foo.database.keys() rather than foo.addresses. The latter doesn't need to exist, since all the information it contains is already available via the methods of the databases attribute.
Another approach is to save the bound instance method database.keys to an instance variable of your DATA object (without calling it):
class DATA(object)
def __init__(self, database=None):
if database is None:
database = {}
self.database = database
self.addresses = database.keys # don't call keys here!
In the calling code, instead of foo.addresses you'd use foo.addresses() (a function call, rather than just an attribute lookup). This looks like a method call on the DATA instance, though it isn't really. It's calling the already bound method on the database dictionary. This might break if other code might replace the database dictionary completely (rather than just mutating it in place).
A final approach is to use a property to request the keys from the database dict when a user tries to access the addresses attribute of a DATA instance:
class DATA(object)
def __init__(self, database=None):
if database is None:
database = {}
self.database = database
# don't save anything as "addresses" here
#property
def addresses(self):
return self.database.keys()
This may be best, since it lets the calling code treat addresses just like an attribute. It will also work properly if you completely replace the database object in some other code (e.g. foo.database = {"foo":"bar"}). It may be a bit slower though, since there'll be an extra function call that the other approaches don't need.

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