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I read an article about the getattr function, but I still can't understand what it's for.
The only thing I understand about getattr() is that getattr(li, "pop") is the same as calling li.pop.
When and how do I use this exactly? The book said something about using it to get a reference to a function whose name isn't known until runtime, but when and why would I use this?
Objects in Python can have attributes -- data attributes and functions to work with those (methods). Actually, every object has built-in attributes (try dir(None), dir(True), dir(...), dir(dir) in Python console).
For example you have an object person, that has several attributes: name, gender, etc.
You access these attributes (be it methods or data objects) usually writing: person.name, person.gender, person.the_method(), etc.
But what if you don't know the attribute's name at the time you write the program? For example you have attribute's name stored in a variable called attr_name.
if
attr_name = 'gender'
then, instead of writing
gender = person.gender
you can write
gender = getattr(person, attr_name)
Some practice:
Python 3.4.0 (default, Apr 11 2014, 13:05:11)
>>> class Person():
... name = 'Victor'
... def say(self, what):
... print(self.name, what)
...
>>> getattr(Person, 'name')
'Victor'
>>> attr_name = 'name'
>>> person = Person()
>>> getattr(person, attr_name)
'Victor'
>>> getattr(person, 'say')('Hello')
Victor Hello
getattr will raise AttributeError if attribute with the given name does not exist in the object:
>>> getattr(person, 'age')
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AttributeError: 'Person' object has no attribute 'age'
But you can pass a default value as the third argument, which will be returned if such attribute does not exist:
>>> getattr(person, 'age', 0)
0
You can use getattr along with dir to iterate over all attribute names and get their values:
>>> dir(1000)
['__abs__', '__add__', ..., '__trunc__', '__xor__', 'bit_length', 'conjugate', 'denominator', 'from_bytes', 'imag', 'numerator', 'real', 'to_bytes']
>>> obj = 1000
>>> for attr_name in dir(obj):
... attr_value = getattr(obj, attr_name)
... print(attr_name, attr_value, callable(attr_value))
...
__abs__ <method-wrapper '__abs__' of int object at 0x7f4e927c2f90> True
...
bit_length <built-in method bit_length of int object at 0x7f4e927c2f90> True
...
>>> getattr(1000, 'bit_length')()
10
A practical use for this would be to find all methods whose names start with test and call them.
Similar to getattr there is setattr which allows you to set an attribute of an object having its name:
>>> setattr(person, 'name', 'Andrew')
>>> person.name # accessing instance attribute
'Andrew'
>>> Person.name # accessing class attribute
'Victor'
>>>
getattr(object, 'x') is completely equivalent to object.x.
There are only two cases where getattr can be useful.
you can't write object.x, because you don't know in advance which attribute you want (it comes from a string). Very useful for meta-programming.
you want to provide a default value. object.y will raise an AttributeError if there's no y. But getattr(object, 'y', 5) will return 5.
For me, getattr is easiest to explain this way:
It allows you to call methods based on the contents of a string instead of typing the method name.
For example, you cannot do this:
obj = MyObject()
for x in ['foo', 'bar']:
obj.x()
because x is not of the type builtin, but str. However, you CAN do this:
obj = MyObject()
for x in ['foo', 'bar']:
getattr(obj, x)()
It allows you to dynamically connect with objects based on your input. I've found it useful when dealing with custom objects and modules.
A pretty common use case for getattr is mapping data to functions.
For instance, in a web framework like Django or Pylons, getattr makes it straightforward to map a web request's URL to the function that's going to handle it. If you look under the hood of Pylons's routing, for instance, you'll see that (by default, at least) it chops up a request's URL, like:
http://www.example.com/customers/list
into "customers" and "list". Then it searches for a controller class named CustomerController. Assuming it finds the class, it creates an instance of the class and then uses getattr to get its list method. It then calls that method, passing it the request as an argument.
Once you grasp this idea, it becomes really easy to extend the functionality of a web application: just add new methods to the controller classes, and then create links in your pages that use the appropriate URLs for those methods. All of this is made possible by getattr.
Here's a quick and dirty example of how a class could fire different versions of a save method depending on which operating system it's being executed on using getattr().
import os
class Log(object):
def __init__(self):
self.os = os.name
def __getattr__(self, name):
""" look for a 'save' attribute, or just
return whatever attribute was specified """
if name == 'save':
try:
# try to dynamically return a save
# method appropriate for the user's system
return getattr(self, self.os)
except:
# bail and try to return
# a default save method
return getattr(self, '_save')
else:
return getattr(self, name)
# each of these methods could have save logic specific to
# the system on which the script is executed
def posix(self): print 'saving on a posix machine'
def nt(self): print 'saving on an nt machine'
def os2(self): print 'saving on an os2 machine'
def ce(self): print 'saving on a ce machine'
def java(self): print 'saving on a java machine'
def riscos(self): print 'saving on a riscos machine'
def _save(self): print 'saving on an unknown operating system'
def which_os(self): print os.name
Now let's use this class in an example:
logger = Log()
# Now you can do one of two things:
save_func = logger.save
# and execute it, or pass it along
# somewhere else as 1st class:
save_func()
# or you can just call it directly:
logger.save()
# other attributes will hit the else
# statement and still work as expected
logger.which_os()
Other than all the amazing answers here, there is a way to use getattr to save copious lines of code and keeping it snug. This thought came following the dreadful representation of code that sometimes might be a necessity.
Scenario
Suppose your directory structure is as follows:
- superheroes.py
- properties.py
And, you have functions for getting information about Thor, Iron Man, Doctor Strange in superheroes.py. You very smartly write down the properties of all of them in properties.py in a compact dict and then access them.
properties.py
thor = {
'about': 'Asgardian god of thunder',
'weapon': 'Mjolnir',
'powers': ['invulnerability', 'keen senses', 'vortex breath'], # and many more
}
iron_man = {
'about': 'A wealthy American business magnate, playboy, and ingenious scientist',
'weapon': 'Armor',
'powers': ['intellect', 'armor suit', 'interface with wireless connections', 'money'],
}
doctor_strange = {
'about': ' primary protector of Earth against magical and mystical threats',
'weapon': 'Magic',
'powers': ['magic', 'intellect', 'martial arts'],
}
Now, let's say you want to return capabilities of each of them on demand in superheroes.py. So, there are functions like
from .properties import thor, iron_man, doctor_strange
def get_thor_weapon():
return thor['weapon']
def get_iron_man_bio():
return iron_man['about']
def get_thor_powers():
return thor['powers']
...and more functions returning different values based on the keys and superhero.
With the help of getattr, you could do something like:
from . import properties
def get_superhero_weapon(hero):
superhero = getattr(properties, hero)
return superhero['weapon']
def get_superhero_powers(hero):
superhero = getattr(properties, hero)
return superhero['powers']
You considerably reduced the number of lines of code, functions and repetition!
Oh and of course, if you have bad names like properties_of_thor for variables , they can be made and accessed by simply doing
def get_superhero_weapon(hero):
superhero = 'properties_of_{}'.format(hero)
all_properties = getattr(properties, superhero)
return all_properties['weapon']
NOTE: For this particular problem, there can be smarter ways to deal with the situation, but the idea is to give an insight about using getattr in right places to write cleaner code.
# getattr
class hithere():
def french(self):
print 'bonjour'
def english(self):
print 'hello'
def german(self):
print 'hallo'
def czech(self):
print 'ahoj'
def noidea(self):
print 'unknown language'
def dispatch(language):
try:
getattr(hithere(),language)()
except:
getattr(hithere(),'noidea')()
# note, do better error handling than this
dispatch('french')
dispatch('english')
dispatch('german')
dispatch('czech')
dispatch('spanish')
I sometimes use getattr(..) to lazily initialise attributes of secondary importance just before they are used in the code.
Compare the following:
class Graph(object):
def __init__(self):
self.n_calls_to_plot = 0
#...
#A lot of code here
#...
def plot(self):
self.n_calls_to_plot += 1
To this:
class Graph(object):
def plot(self):
self.n_calls_to_plot = 1 + getattr(self, "n_calls_to_plot", 0)
The advantage of the second way is that n_calls_to_plot only appears around the place in the code where it is used. This is good for readability, because (1) you can immediately see what value it starts with when reading how it's used, (2) it doesn't introduce a distraction into the __init__(..) method, which ideally should be about the conceptual state of the class, rather than some utility counter that is only used by one of the function's methods for technical reasons, such as optimisation, and has nothing to do with the meaning of the object.
Quite frequently when I am creating an XML file from data stored in a class I would frequently receive errors if the attribute didn't exist or was of type None. In this case, my issue wasn't not knowing what the attribute name was, as stated in your question, but rather was data ever stored in that attribute.
class Pet:
def __init__(self):
self.hair = None
self.color = None
If I used hasattr to do this, it would return True even if the attribute value was of type None and this would cause my ElementTree set command to fail.
hasattr(temp, 'hair')
>>True
If the attribute value was of type None, getattr would also return it which would cause my ElementTree set command to fail.
c = getattr(temp, 'hair')
type(c)
>> NoneType
I use the following method to take care of these cases now:
def getRealAttr(class_obj, class_attr, default = ''):
temp = getattr(class_obj, class_attr, default)
if temp is None:
temp = default
elif type(temp) != str:
temp = str(temp)
return temp
This is when and how I use getattr.
Another use of getattr() in implementing a switch statement in Python. It uses both reflection to get the case type.
import sys
class SwitchStatement(object):
""" a class to implement switch statement and a way to show how to use gettattr in Pythion"""
def case_1(self):
return "value for case_1"
def case_2(self):
return "value for case_2"
def case_3(self):
return "value for case_3"
def case_4(self):
return "value for case_4"
def case_value(self, case_type=1):
"""This is the main dispatchmethod, that uses gettattr"""
case_method = 'case_' + str(case_type)
# fetch the relevant method name
# Get the method from 'self'. Default to a lambda.
method = getattr(self, case_method, lambda: "Invalid case type")
# Call the method as we return it
return method()
def main(_):
switch = SwitchStatement()
print swtich.case_value(_)
if __name__ == '__main__':
main(int(sys.argv[1]))
setattr()
We use setattr to add an attribute to our class instance. We pass the class instance, the attribute name, and the value.
getattr()
With getattr we retrive these values
For example
Employee = type("Employee", (object,), dict())
employee = Employee()
# Set salary to 1000
setattr(employee,"salary", 1000 )
# Get the Salary
value = getattr(employee, "salary")
print(value)
I think this example is self explanatory. It runs the method of first parameter, whose name is given in the second parameter.
class MyClass:
def __init__(self):
pass
def MyMethod(self):
print("Method ran")
# Create an object
object = MyClass()
# Get all the methods of a class
method_list = [func for func in dir(MyClass) if callable(getattr(MyClass, func))]
# You can use any of the methods in method_list
# "MyMethod" is the one we want to use right now
# This is the same as running "object.MyMethod()"
getattr(object,'MyMethod')()
It is also clarifying from https://www.programiz.com/python-programming/methods/built-in/getattr
class Person:
age = 23
name = "Adam"
person = Person()
print('The age is:', getattr(person, "age"))
print('The age is:', person.age)
The age is: 23
The age is: 23
class Person:
age = 23
name = "Adam"
person = Person()
# when default value is provided
print('The sex is:', getattr(person, 'sex', 'Male'))
# when no default value is provided
print('The sex is:', getattr(person, 'sex'))
The sex is: Male
AttributeError: 'Person' object has no attribute 'sex'
I have tried in Python2.7.17
Some of the fellow folks already answered. However I have tried to call
getattr(obj, 'set_value') and this didn't execute the set_value method, So i changed to getattr(obj, 'set_value')() --> This helps to invoke the same.
Example Code:
Example 1:
class GETATT_VERIFY():
name = "siva"
def __init__(self):
print "Ok"
def set_value(self):
self.value = "myself"
print "oooh"
obj = GETATT_VERIFY()
print getattr(GETATT_VERIFY, 'name')
getattr(obj, 'set_value')()
print obj.value
I am trying to find a way for getting all attributes to evaluate after one attribute change within the class, without calling a function outside the class.
class Students:
def __init__(self, name, mylist):
self.name = name
self.subjects = mylist
self.credits = len(self.subjects) * 2
def credits_calc(self):
self.credits = len(self.subjects) * 2
return self.credits
john = Students("John", ["Maths", "English"])
print(john.subjects)
print(john.credits)
john.subjects.append("History")
print(john.subjects) # --> subjects attribute updated.
print(john.credits) # --> obviously not updated. Still returns initial value.
I have to call the function outside the class to to have the other attributes updated
john.credits_calc() # I know I can take the returned value.
print(john.credits) # --> updated after calling the function.
So my question is how to get the other attributes to evaluate if one attribute is changed without the need to manually call the function later.
What you are looking for is the property decorator. There are additional methods you can add on to this, particularly the fset and fdel logic of this attribute, the code below simply defines the fget behavior.
class Students:
def __init__(self, name, mylist):
self.name = name
self.subjects = mylist
#property
def credits(self):
return len(self.subjects) * 2
john = Students("John", ["Maths", "English"])
print(john.credits) # 4
john.subjects.append("History")
print(john.credits) # 6
I read an article about the getattr function, but I still can't understand what it's for.
The only thing I understand about getattr() is that getattr(li, "pop") is the same as calling li.pop.
When and how do I use this exactly? The book said something about using it to get a reference to a function whose name isn't known until runtime, but when and why would I use this?
Objects in Python can have attributes -- data attributes and functions to work with those (methods). Actually, every object has built-in attributes (try dir(None), dir(True), dir(...), dir(dir) in Python console).
For example you have an object person, that has several attributes: name, gender, etc.
You access these attributes (be it methods or data objects) usually writing: person.name, person.gender, person.the_method(), etc.
But what if you don't know the attribute's name at the time you write the program? For example you have attribute's name stored in a variable called attr_name.
if
attr_name = 'gender'
then, instead of writing
gender = person.gender
you can write
gender = getattr(person, attr_name)
Some practice:
Python 3.4.0 (default, Apr 11 2014, 13:05:11)
>>> class Person():
... name = 'Victor'
... def say(self, what):
... print(self.name, what)
...
>>> getattr(Person, 'name')
'Victor'
>>> attr_name = 'name'
>>> person = Person()
>>> getattr(person, attr_name)
'Victor'
>>> getattr(person, 'say')('Hello')
Victor Hello
getattr will raise AttributeError if attribute with the given name does not exist in the object:
>>> getattr(person, 'age')
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AttributeError: 'Person' object has no attribute 'age'
But you can pass a default value as the third argument, which will be returned if such attribute does not exist:
>>> getattr(person, 'age', 0)
0
You can use getattr along with dir to iterate over all attribute names and get their values:
>>> dir(1000)
['__abs__', '__add__', ..., '__trunc__', '__xor__', 'bit_length', 'conjugate', 'denominator', 'from_bytes', 'imag', 'numerator', 'real', 'to_bytes']
>>> obj = 1000
>>> for attr_name in dir(obj):
... attr_value = getattr(obj, attr_name)
... print(attr_name, attr_value, callable(attr_value))
...
__abs__ <method-wrapper '__abs__' of int object at 0x7f4e927c2f90> True
...
bit_length <built-in method bit_length of int object at 0x7f4e927c2f90> True
...
>>> getattr(1000, 'bit_length')()
10
A practical use for this would be to find all methods whose names start with test and call them.
Similar to getattr there is setattr which allows you to set an attribute of an object having its name:
>>> setattr(person, 'name', 'Andrew')
>>> person.name # accessing instance attribute
'Andrew'
>>> Person.name # accessing class attribute
'Victor'
>>>
getattr(object, 'x') is completely equivalent to object.x.
There are only two cases where getattr can be useful.
you can't write object.x, because you don't know in advance which attribute you want (it comes from a string). Very useful for meta-programming.
you want to provide a default value. object.y will raise an AttributeError if there's no y. But getattr(object, 'y', 5) will return 5.
For me, getattr is easiest to explain this way:
It allows you to call methods based on the contents of a string instead of typing the method name.
For example, you cannot do this:
obj = MyObject()
for x in ['foo', 'bar']:
obj.x()
because x is not of the type builtin, but str. However, you CAN do this:
obj = MyObject()
for x in ['foo', 'bar']:
getattr(obj, x)()
It allows you to dynamically connect with objects based on your input. I've found it useful when dealing with custom objects and modules.
A pretty common use case for getattr is mapping data to functions.
For instance, in a web framework like Django or Pylons, getattr makes it straightforward to map a web request's URL to the function that's going to handle it. If you look under the hood of Pylons's routing, for instance, you'll see that (by default, at least) it chops up a request's URL, like:
http://www.example.com/customers/list
into "customers" and "list". Then it searches for a controller class named CustomerController. Assuming it finds the class, it creates an instance of the class and then uses getattr to get its list method. It then calls that method, passing it the request as an argument.
Once you grasp this idea, it becomes really easy to extend the functionality of a web application: just add new methods to the controller classes, and then create links in your pages that use the appropriate URLs for those methods. All of this is made possible by getattr.
Here's a quick and dirty example of how a class could fire different versions of a save method depending on which operating system it's being executed on using getattr().
import os
class Log(object):
def __init__(self):
self.os = os.name
def __getattr__(self, name):
""" look for a 'save' attribute, or just
return whatever attribute was specified """
if name == 'save':
try:
# try to dynamically return a save
# method appropriate for the user's system
return getattr(self, self.os)
except:
# bail and try to return
# a default save method
return getattr(self, '_save')
else:
return getattr(self, name)
# each of these methods could have save logic specific to
# the system on which the script is executed
def posix(self): print 'saving on a posix machine'
def nt(self): print 'saving on an nt machine'
def os2(self): print 'saving on an os2 machine'
def ce(self): print 'saving on a ce machine'
def java(self): print 'saving on a java machine'
def riscos(self): print 'saving on a riscos machine'
def _save(self): print 'saving on an unknown operating system'
def which_os(self): print os.name
Now let's use this class in an example:
logger = Log()
# Now you can do one of two things:
save_func = logger.save
# and execute it, or pass it along
# somewhere else as 1st class:
save_func()
# or you can just call it directly:
logger.save()
# other attributes will hit the else
# statement and still work as expected
logger.which_os()
Other than all the amazing answers here, there is a way to use getattr to save copious lines of code and keeping it snug. This thought came following the dreadful representation of code that sometimes might be a necessity.
Scenario
Suppose your directory structure is as follows:
- superheroes.py
- properties.py
And, you have functions for getting information about Thor, Iron Man, Doctor Strange in superheroes.py. You very smartly write down the properties of all of them in properties.py in a compact dict and then access them.
properties.py
thor = {
'about': 'Asgardian god of thunder',
'weapon': 'Mjolnir',
'powers': ['invulnerability', 'keen senses', 'vortex breath'], # and many more
}
iron_man = {
'about': 'A wealthy American business magnate, playboy, and ingenious scientist',
'weapon': 'Armor',
'powers': ['intellect', 'armor suit', 'interface with wireless connections', 'money'],
}
doctor_strange = {
'about': ' primary protector of Earth against magical and mystical threats',
'weapon': 'Magic',
'powers': ['magic', 'intellect', 'martial arts'],
}
Now, let's say you want to return capabilities of each of them on demand in superheroes.py. So, there are functions like
from .properties import thor, iron_man, doctor_strange
def get_thor_weapon():
return thor['weapon']
def get_iron_man_bio():
return iron_man['about']
def get_thor_powers():
return thor['powers']
...and more functions returning different values based on the keys and superhero.
With the help of getattr, you could do something like:
from . import properties
def get_superhero_weapon(hero):
superhero = getattr(properties, hero)
return superhero['weapon']
def get_superhero_powers(hero):
superhero = getattr(properties, hero)
return superhero['powers']
You considerably reduced the number of lines of code, functions and repetition!
Oh and of course, if you have bad names like properties_of_thor for variables , they can be made and accessed by simply doing
def get_superhero_weapon(hero):
superhero = 'properties_of_{}'.format(hero)
all_properties = getattr(properties, superhero)
return all_properties['weapon']
NOTE: For this particular problem, there can be smarter ways to deal with the situation, but the idea is to give an insight about using getattr in right places to write cleaner code.
# getattr
class hithere():
def french(self):
print 'bonjour'
def english(self):
print 'hello'
def german(self):
print 'hallo'
def czech(self):
print 'ahoj'
def noidea(self):
print 'unknown language'
def dispatch(language):
try:
getattr(hithere(),language)()
except:
getattr(hithere(),'noidea')()
# note, do better error handling than this
dispatch('french')
dispatch('english')
dispatch('german')
dispatch('czech')
dispatch('spanish')
I sometimes use getattr(..) to lazily initialise attributes of secondary importance just before they are used in the code.
Compare the following:
class Graph(object):
def __init__(self):
self.n_calls_to_plot = 0
#...
#A lot of code here
#...
def plot(self):
self.n_calls_to_plot += 1
To this:
class Graph(object):
def plot(self):
self.n_calls_to_plot = 1 + getattr(self, "n_calls_to_plot", 0)
The advantage of the second way is that n_calls_to_plot only appears around the place in the code where it is used. This is good for readability, because (1) you can immediately see what value it starts with when reading how it's used, (2) it doesn't introduce a distraction into the __init__(..) method, which ideally should be about the conceptual state of the class, rather than some utility counter that is only used by one of the function's methods for technical reasons, such as optimisation, and has nothing to do with the meaning of the object.
Quite frequently when I am creating an XML file from data stored in a class I would frequently receive errors if the attribute didn't exist or was of type None. In this case, my issue wasn't not knowing what the attribute name was, as stated in your question, but rather was data ever stored in that attribute.
class Pet:
def __init__(self):
self.hair = None
self.color = None
If I used hasattr to do this, it would return True even if the attribute value was of type None and this would cause my ElementTree set command to fail.
hasattr(temp, 'hair')
>>True
If the attribute value was of type None, getattr would also return it which would cause my ElementTree set command to fail.
c = getattr(temp, 'hair')
type(c)
>> NoneType
I use the following method to take care of these cases now:
def getRealAttr(class_obj, class_attr, default = ''):
temp = getattr(class_obj, class_attr, default)
if temp is None:
temp = default
elif type(temp) != str:
temp = str(temp)
return temp
This is when and how I use getattr.
Another use of getattr() in implementing a switch statement in Python. It uses both reflection to get the case type.
import sys
class SwitchStatement(object):
""" a class to implement switch statement and a way to show how to use gettattr in Pythion"""
def case_1(self):
return "value for case_1"
def case_2(self):
return "value for case_2"
def case_3(self):
return "value for case_3"
def case_4(self):
return "value for case_4"
def case_value(self, case_type=1):
"""This is the main dispatchmethod, that uses gettattr"""
case_method = 'case_' + str(case_type)
# fetch the relevant method name
# Get the method from 'self'. Default to a lambda.
method = getattr(self, case_method, lambda: "Invalid case type")
# Call the method as we return it
return method()
def main(_):
switch = SwitchStatement()
print swtich.case_value(_)
if __name__ == '__main__':
main(int(sys.argv[1]))
setattr()
We use setattr to add an attribute to our class instance. We pass the class instance, the attribute name, and the value.
getattr()
With getattr we retrive these values
For example
Employee = type("Employee", (object,), dict())
employee = Employee()
# Set salary to 1000
setattr(employee,"salary", 1000 )
# Get the Salary
value = getattr(employee, "salary")
print(value)
I think this example is self explanatory. It runs the method of first parameter, whose name is given in the second parameter.
class MyClass:
def __init__(self):
pass
def MyMethod(self):
print("Method ran")
# Create an object
object = MyClass()
# Get all the methods of a class
method_list = [func for func in dir(MyClass) if callable(getattr(MyClass, func))]
# You can use any of the methods in method_list
# "MyMethod" is the one we want to use right now
# This is the same as running "object.MyMethod()"
getattr(object,'MyMethod')()
It is also clarifying from https://www.programiz.com/python-programming/methods/built-in/getattr
class Person:
age = 23
name = "Adam"
person = Person()
print('The age is:', getattr(person, "age"))
print('The age is:', person.age)
The age is: 23
The age is: 23
class Person:
age = 23
name = "Adam"
person = Person()
# when default value is provided
print('The sex is:', getattr(person, 'sex', 'Male'))
# when no default value is provided
print('The sex is:', getattr(person, 'sex'))
The sex is: Male
AttributeError: 'Person' object has no attribute 'sex'
I have tried in Python2.7.17
Some of the fellow folks already answered. However I have tried to call
getattr(obj, 'set_value') and this didn't execute the set_value method, So i changed to getattr(obj, 'set_value')() --> This helps to invoke the same.
Example Code:
Example 1:
class GETATT_VERIFY():
name = "siva"
def __init__(self):
print "Ok"
def set_value(self):
self.value = "myself"
print "oooh"
obj = GETATT_VERIFY()
print getattr(GETATT_VERIFY, 'name')
getattr(obj, 'set_value')()
print obj.value
I was playing around in Python as I am relatively new to it. Below is a snippet
class Person:
version = "1.0"
def __init__(self, name="john doe",age=25):
self.name = name
self.first_name = name.split()[0]
self.second_name = name.split()[1]
self.age = age
def printi(self):
print(self.name)
new_person = Person()
new_person.printi()
refPerson = Person
print(refPerson.version)
another_one = refPerson()
#another_one.version = "2.0"
print(another_one.version)
another_one.printi()
print(Person.version)
Person.version = "2.0"
print(another_one.version)
print(refPerson.version)
And If you notice, the class name Person is directly assigned to a variable refPerson. I was under the impression that post this assignment new class of name refPerson will be created. But when I modify the Person class attribute, I could see that the value change is reflected in the new class. What am I missing here? I just need a clear picture.
Thanks in advance.
Classes are first-class objects in Python; you can pass references to them around.
Person is a reference to the class defined by the class statement. Person() (calling the class object like a function) returns an instance of that class.
Attribute lookup rules can get complicated, but for this example the following simplification will suffice. Since neither new_person.version nor another_one.version is defined, an attempt to look either one up will result in a class attribute lookup. That is, new_person.version == type(new_person).version.
If you create an instance attribute with the same name, it will shadow the class attribute:
>>> new_person.version = 3
>>> new_person.version
3
>>> type(new_person).version
"1.0"
>>> another_one.version
"1.0"
Going into more detail than you are probably ready for at this stage, Person() breaks down into the following calls:
Person() is equivalent to Person.__call__(Person), where __call__ is an instance method of the class type, of which Person is an instance. (That is, type(Person) returns type.)
Person.__call__ calls Person.__new__, which returns a new instance of Person; call it p.
Person.__call__ then calls Person.__init__ with p as its argument.
Finally, Person.__call__ returns p.
This question already has answers here:
Closed 10 years ago.
Possible Duplicate:
Python: Difference between class and instance attributes
I'm trying to get my head around OOP in Python and I'm a bit confused when it comes to declare variables within a class. Should I declare them inside of the __init__ procedure or outside it? What's the difference?
The following code works just fine:
# Declaring variables within __init__
class MyClass:
def __init__(self):
country = ""
city = ""
def information(self):
print "Hi! I'm from %s, (%s)"%(self.city,self.country)
me = MyClass()
me.country = "Spain"
me.city = "Barcelona"
me.information()
But declaring the variables outside of the __init__ procedure also works:
# Declaring variables outside of __init__
class MyClass:
country = ""
city = ""
def information(self):
print "Hi! I'm from %s, (%s)"%(self.city,self.country)
me = MyClass()
me.country = "Spain"
me.city = "Barcelona"
me.information()
In your first example you are defining instance attributes. In the second, class attributes.
Class attributes are shared between all instances of that class, where as instance attributes are "owned" by that particular instance.
Difference by example
To understand the differences let's use an example.
We'll define a class with instance attributes:
class MyClassOne:
def __init__(self):
self.country = "Spain"
self.city = "Barcelona"
self.things = []
And one with class attributes:
class MyClassTwo:
country = "Spain"
city = "Barcelona"
things = []
And a function that prints out information about one of these objects:
def information(obj):
print "I'm from {0}, ({1}). I own: {2}".format(
obj.city, obj.country, ','.join(obj.things))
Let's create 2 MyClassOne objects and change one to be Milan, and give Milan "something":
foo1 = MyClassOne()
bar1 = MyClassOne()
foo1.city = "Milan"
foo1.country = "Italy"
foo1.things.append("Something")
When we call information() on the foo1 and bar1 we get the values you'd expect:
>>> information(foo1)
I'm from Milan, (Italy). I own: Something
>>> information(bar1)
I'm from Barcelona, (Spain). I own:
However, if we were to do exactly the same thing, but using instances of MyClassTwo you'll see that the class attributes are shared between instances.
foo2 = MyClassTwo()
bar2 = MyClassTwo()
foo2.city = "Milan"
foo2.country = "Italy"
foo2.things.append("Something")
And then call information()...
>>> information(foo2)
I'm from Milan, (Italy). I own: Something
>>> information(bar2)
I'm from Barcelona, (Spain). I own: Something
So as you can see - things is being shared between the instances. things is a reference to a list that each instance has access to. So if you append to things from any instance that same list will be seen by all other instances.
The reason you don't see this behaviour in the string variables is because you are actually assigning a new variable to an instance. In this case that reference is "owned" by the instance and not shared at the class level. To illustrate let's assign a new list to things for bar2:
bar2.things = []
This results in:
>>> information(foo2)
I'm from Milan, (Italy). I own: Something
>>> information(bar2)
I'm from Barcelona, (Spain). I own:
You're two versions of the code are very different. In python, you have 2 distinct entities: classes and class instances. An instance is what is created when you do:
new_instance = my_class()
You can bind attributes to an instance within __init__ via self (self is the new instance).
class MyClass(object):
def __init__(self):
self.country = "" #every instance will have a `country` attribute initialized to ""
There's nothing terribly special about self and __init__. self is the customary name that is used to represent the instance that gets passed to every method (by default).
a.method() #-> Inside the class where `method` is defined, `a` gets passed in as `self`
The only thing special here is that __init__ gets called when the class is constructed:
a = MyClass() #implicitly calls `__init__`
You can also bind attributes to the class (putting it outside __init__):
class MyClass(object):
country = "" #This attribute is a class attribute.
At any point, you can bind a new attribute to an instance simply by:
my_instance = MyClass()
my_instance.attribute = something
Or a new attribute to a class via:
MyClass.attribute = something
Now it gets interesting. If an instance doesn't have a requested attribute, then python looks at the class for the attribute and returns it (if it is there). So, class attributes are a way for all instances of a class to share a piece of data.
Consider:
def MyClass(object):
cls_attr = []
def __init__(self):
self.inst_attr = []
a = MyClass()
a.inst_attr.append('a added this')
a.cls_attr.append('a added this to class')
b = MyClass()
print (b.inst_attr) # [] <- empty list, changes to `a` don't affect this.
print (b.cls_attr) # ['a added this to class'] <- Stuff added by `a`!
print (a.inst_attr) #['a added this']
When you define a variable in class scope (outside any method), it becomes a class attribute. When you define a value in method scope, it becomes a method local variable. If you assign a value to an attribute of self (or any other label referencing an object), it becomes (or modifies) an instance attribute.