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Track changes inside a class using a dict [duplicate]

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

Can't use "from" property when reading JSON file [duplicate]

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

Can you make classes in a loop in python?

I have a situation where I'm making a bunch of classes, and a bunch of them are really basically the same, so I'd like to make them in a loop. They are being used with a registration system, so there's no problem one the USAGE side, but I'm not sure how to actually define a class with a variable determining the class name...
Simple example:
classList = ['foo', 'bar', 'baz']
for className in classList:
class {{{className}}}_calc(BaseCalc):
def __init__ (self, dataFrame):
self.column = dataFrame[className]
def calc ():
return self.column.sum()
This is a very simplified case, obviously. I can't change the arguments to init because there are a whole bunch of these already existing, that are part of a larger structure.
The rest of the example is using pandas syntax, just to give an idea of how this is being used... but it's actually being used with a SQL DB, and is much more complicated... I just don't want to have to defend "why are you doing this in the first place?" I have good reasons, leave it at that.
classname is in {{{ }}} in the class line to denote that it's a variable, and not actually syntactically correct there. The question is "how do I denote what I have used {{{ }}} for?" I think.
The answer may be metaclasses, but I'm still not sure how to make the NAME of my class variable....
ETA: Trying to use #python_user answer:
classList = ['foooo', 'bar', 'baaz']
class Base ():
def __init__ (self, buq):
self.buq = buq
def getBuq(self):
return 'buq: ' + self.buq
for cls in classList:
class TEMP(Base):
className = cls
def __init__ (self):
self.qux = len(cls)
Base.__init__(self, cls)
def blee(self, inpt):
return inpt+ self.qux
TEMP.__name__ = f'{cls}'
TEMP.__qualname__ = f'{cls}'
globals()[cls] = TEMP
f = foo()
f.getBuq()
>>>> 'buq: baaz'
This is only giving me the baaz class. All three are giving baaz... Am I doing something really dumb?

You can do like so, using globals()
classList = ['foo', 'bar', 'baz']
for className in classList:
class Temp:
def __init__ (self, dataFrame):
self.column = dataFrame[className]
def calc ():
return self.column.sum()
Temp.__name__ = className
globals()[className] = Temp
You can then do foo() to create an object of class foo. You have to call with the args required for the __init__ method for the actual example. This is just to show it works.
print(type(foo()).__name__) # foo
print(type(bar()).__name__) # bar
print(type(baz()).__name__) # baz
If you want to change your class names then you can do
Temp.__name__ = f'{className}_calc'
globals()[f'{className}_calc'] = Temp
As pointed out by wim in the comments you need to also set __qualname__. Temp.__qualname__ = f'{className}_calc'
Edit:
As name lookups in methods of a class are performed at runtime (not at compile time), the code snippet has a bug. className would always refer to the last element in the classList (baz in this case), this name exists outside the scope of the loop and will be the value for className in the methods for ALL classes. (eg : self.column = dataFrame[className]). <--- This is always dataFrame['baz']
To fix this, one has to declare a class level variable called className and assign className (the one from the loop) to that. So at compile time this value will be bound to the class. All reference to className inside the methods of the class needs to be changed to self.className for the code to work as expected.
class Temp:
className = className # note this line
def __init__ (self, dataFrame):
self.column = dataFrame[self.className] # and this line with the original snippet

You can use the type function, however, to create such dynamic classes. names = ['name1', 'name2'] Suppose you have to create 10 class objects in python, and do something with them, like: obj_1 = MyClass() other_object.
Hope I could help you.

Well, there is a a kind of messy way to do this using the "exec()" function which takes any string and executes it; then you can build your classes as a string and run that. Here is an example which builds your classes, you can see that they are declared by looking in the global namespace which is printed at the end.
classList = ['foo', 'bar', 'baz']
class BaseCalc():
def __init__ (self, dataFrame):
self.column = dataFrame[className]
def calc ():
return self.column.sum()
for className in classList:
template = '''class %s_calc(BaseCalc):
def __init__ (self, dataFrame):
self.column = dataFrame[className]
def calc ():
return self.column.sum()''' % className
exec(template)
print(globals())

Share variable between instances of the same class in python

I have a class that I need:
First instance MUST receive a parameter.
All the following instances have this parameter be optional.
If it is not passed then I will use the parameter of the previous object init.
For that, I need to share a variable between the objects (all objects belong to classes with the same parent).
For example:
class MyClass:
shared_variable = None
def __init__(self, paremeter_optional=None):
if paremeter_optional is None: # Parameter optional not given
if self.shared_variable is None:
print("Error! First intance must have the parameter")
sys.exit(-1)
else:
paremeter_optional = self.shared_variable # Use last parameter
self.shared_variable = paremeter_optional # Save it for next object
objA = MyClass(3)
objB = MyClass()
Because the shared_variable is not consistent/shared across inits, when running the above code I get the error:
Error! First intance must have the parameter
(After the second init of objB)
Of course, I could use a global variable but I want to avoid it if possible and use some best practices for this.

Update: Having misunderstood the original problem, I would still recommend being explicit, rather than having the class track information better tracked outside the class.
class MyClass:
def __init__(self, parameter):
...
objA = MyClass(3)
objB = MyClass(4)
objC = MyClass(5)
objD = MyClass(5) # Be explicit; don't "remember" what was used for objC
If objC and objD are "related" enough that objD can rely on the initialization of objC, and you want to be DRY, use something like
objC, objD = [MyClass(5) for _ in range(2)]
Original answer:
I wouldn't make this something you set from an instance at all; it's a class attribute, and so should be set at the class level only.
class MyClass:
shared_variable = None
def __init__(self):
if self.shared_variable is None:
raise RuntimeError("shared_variable must be set before instantiating")
...
MyClass.shared_variable = 3
objA = MyClass()
objB = MyClass()

Assigning a value to self.shared_variable makes self.shared_variable an instance attribute so that the value is not shared among instances.
You can instead assign the value explicitly to the class attribute by referencing the attribute of the instance's class object instead.
Change:
self.shared_variable = paremeter_optional
to:
self.__class__.shared_variable = paremeter_optional

Python How to create method of class in runtime

I am curious how to create a custom method for a class at runtime...
I mean for example with name of method, name of parameters, body of method read from database and assign this method to a class or to an instance.
I have a found possibility to add method that is already written:
class A:
def __init__(self):
pass
def method(self):
return True
A.method = method
a = A()
print(a.method())
but I am interested in completely assembling a new method from scratch:
name = "method"
params = ["self"] # Params in list should be a strings
body = "return True"
# To create method from pieces
Is it possible using __dict__ ? Or how else this be done?

Methods are another attribute on the object that is the class. They can be added like other attributes:
Code:
class A:
def __init__(self):
pass
def method(self):
return True
def another_method(self):
return False
setattr(A, 'another_method', another_method)
Test Code:
a = A()
print(a.another_method())
Results:
False
Methods from a string:
Add if you really need to get your methods from a database or such you can use exec like:
method_string = """
def yet_another_method(self):
return type(self).__name__
"""
exec(method_string)
setattr(A, 'yet_another_method', yet_another_method)
a = A()
print(a.yet_another_method())
Results:
A

This answer has to be treated with care, using exec or eval can run arbitary code and may compromise your system. So if you rely on user-input to create the function you mustn't use this!!!
The warning aside you can simply create anything using exec:
exec("""
def method():
return True
""")
>>> method()
True
So what you basically need is just a way to get your requirements in there:
functionname = 'funfunc'
parameters = ['a', 'b']
body = 'return a + b'
exec("""
def {functionname}({parameters}):
{body}
""".format(
functionname=functionname,
parameters=', '.join(parameters),
body='\n'.join([' {line}'.format(line=line) for line in body.split('\n')])))
The body will be indented so that it's valid syntax and the parameter list will be joined using ,. And the test:
>>> funfunc(1, 2)
3

One of the best solutions that I have found is the following:
def import_code(code, name, add_to_sys_modules=0):
"""
Import dynamically generated code as a module. code is the
object containing the code (a string, a file handle or an
actual compiled code object, same types as accepted by an
exec statement). The name is the name to give to the module,
and the final argument says wheter to add it to sys.modules
or not. If it is added, a subsequent import statement using
name will return this module. If it is not added to sys.modules
import will try to load it in the normal fashion.
import foo
is equivalent to
foofile = open("/path/to/foo.py")
foo = importCode(foofile,"foo",1)
Returns a newly generated module.
"""
import sys,imp
module = imp.new_module(name)
exec(code,module.__dict__)
if add_to_sys_modules:
sys.modules[name] = module
return module
class A:
def __init__(self):
pass
name = "method"
params = ["self"] # Params in list should be a strings
body = "return True"
scratch = "def {0}({1}):\n\t{2}".format(name, ','.join(params), body)
new_module = import_code(scratch, "test")
A.method = new_module.method
a = A()
print(a.method())
Original function import_code by the following link http://code.activestate.com/recipes/82234-importing-a-dynamically-generated-module/
Using this solution I can dynamically create methods, load them in runtime and link to whatever I want object !!