I'm new in Python and I'm trying to get my head around how are managed attributes between methods of a class.
In the following example, I'm trying to modify a list in the method "regex" and use it afterwards in another method "printsc".
The "regex" part works without issues, but the attribute "self.mylist" is not updated so when I call "printsc" the result is "None".
class MyClass():
def __init__(self):
self.mylist = None
def regex(self, items):
self.mylist = []
for item in items:
if re.match(r"^\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3}$", item):
self.mylist.append("IP:" + item)
else:
self.mylist.append("DNS:" + item)
return self.mylist
def printsc(self):
print(self.mylist)
items = ['192.168.0.1', 'hostname1', '10.0.1.15', 'server.local.fr']
MyClass().regex(items)
MyClass().printsc()
What am I missing ? What is the best way to achieve this goal ?
Thank you for your answers!
When you do MyClass(), it returns you an object.. And you are calling your methods on the object. Since you are doing it twice, each time a new object is created and regex and printsc are called on different objects.
what you should do is
myObj = MyClass()
myObj.regex(items)
myObj.printsc()
The problem is that when you do:
MyClass().regex(items)
MyClass().printsc()
You are creating 2 separate instances of MyClass, each of which will have a different .mylist attribute.
Either mylist is an instance attribute, and then this will work:
instance = MyClass()
instance.regex(items)
instance.printsc()
Or, if you want to share .mylist across instances, it should be
a class attribute:
class MyClass():
class_list = None
def __init__(self):
pass
def regex(self, items):
cls = self.__class__
if cls.class_list is None:
cls.class_list = []
for item in items:
if re.match(r"^\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3}$", item):
cls.class_list.append("IP:" + item)
else:
cls.class_list.append("DNS:" + item)
return cls.class_list
def printsc(self):
# Going throuhgh `.__class__.` is actually optional for
# reading an attribute - if it is not in the instance
# Python will fetch it from the class instead.
# i.e. , the line bellow would work with `self.class_list`
print(self.__class__.class_list)
This way, the list persists across different instances of the class, as you try to do in your example.
You should create an object of the class:
a = MyClass()
a.regex(items)
a.printsc()
>>> ['IP:192.168.0.1', 'DNS:hostname1', 'IP:10.0.1.15', 'DNS:server.local.fr']
Related
I'm trying to define two clases, A and B, with B being the child, as in the following code
class A:
def __init__(self, att_A=False):
self.att_A = att_A
def call_B(self):
b = B()
class B(A):
def __init__(self):
super().__init__()
print(f'{self.att_A=}')
a = A()
a.att_A = True
a.call_B()
B does properly inherit the methods and attributes at the time of definition but I want it to also access the values of self.att_A even when they were updated after being initiated.
Is it possible to do that or is there any workaround, like forwarding the attribute as a method parameter?
I have tried deffining att_A as a class attribute but still B cannot access the updated value
I have two classes MyLib(object) and MyHash(MyLib).
class MyLib(object):
def __init__(self):
pass
def inp (self):
self.liblist = str(input()).split()
def librar(self):
self.libdict = {item: self.liblist[index + 1] for index,
item in enumerate(self.liblist) if index % 2 == 0}
class MyHash(MyLib):
def Hashing(self):
self.hashkeys = list(MyLib.libdict.keys())
I'd like MyHash to get libdict from MyLib, and make some manipulations with it. How should I do it?
Because class MyHash extends MyLib, it also inherits all of MyLib's fields. Thus, it will also have self.libdict. Of course, it has to be assigned first.
(Side note: Python makes no checks if the field is actually inherited, which means it even simpler: the field exists iff it has been assigned.)
I would like to define a decorator that will register classes by a name given as an argument of my decorator. I could read from stackoverflow and other sources many examples that show how to derive such (tricky) code but when adapted to my needs my code fails to produce the expected result. Here is the code:
import functools
READERS = {}
def register(typ):
def decorator_register(kls):
#functools.wraps(kls)
def wrapper_register(*args, **kwargs):
READERS[typ] = kls
return wrapper_register
return decorator_register
#register(".pdb")
class PDBReader:
pass
#register(".gro")
class GromacsReader:
pass
print(READERS)
This code produces an empty dictionary while I would expect a dictionary with two entries. Would you have any idea about what is wrong with my code ?
Taking arguments (via (...)) and decoration (via #) both result in calls of functions. Each "stage" of taking arguments or decoration maps to one call and thus one nested functions in the decorator definition. register is a three-stage decorator and takes as many calls to trigger its innermost code. Of these,
the first is the argument ((".pdb")),
the second is the class definition (#... class), and
the third is the class call/instantiation (PDBReader(...))
This stage is broken as it does not instantiate the class.
In order to store the class itself in the dictionary, store it at the second stage. As the instances are not to be stored, remove the third stage.
def register(typ): # first stage: file extension
"""Create a decorator to register its target for the given `typ`"""
def decorator_register(kls): # second stage: Reader class
"""Decorator to register its target `kls` for the previously given `typ`"""
READERS[typ] = kls
return kls # <<< return class to preserve it
return decorator_register
Take note that the result of a decorator replaces its target. Thus, you should generally return the target itself or an equivalent object. Since in this case the class is returned immediately, there is no need to use functools.wraps.
READERS = {}
def register(typ): # first stage: file extension
"""Create a decorator to register its target for the given `typ`"""
def decorator_register(kls): # second stage: Reader class
"""Decorator to register its target `kls` for the previously given `typ`"""
READERS[typ] = kls
return kls # <<< return class to preserve it
return decorator_register
#register(".pdb")
class PDBReader:
pass
#register(".gro")
class GromacsReader:
pass
print(READERS) # {'.pdb': <class '__main__.PDBReader'>, '.gro': <class '__main__.GromacsReader'>}
If you don't actually call the code that the decorator is "wrapping" then the "inner" function will not fire, and you will not create an entry inside of READER. However, even if you create instances of PDBReader or GromacsReader, the value inside of READER will be of the classes themselves, not an instance of them.
If you want to do the latter, you have to change wrapper_register to something like this:
def register(typ):
def decorator_register(kls):
#functools.wraps(kls)
def wrapper_register(*args, **kwargs):
READERS[typ] = kls(*args, **kwargs)
return READERS[typ]
return wrapper_register
return decorator_register
I added simple init/repr inside of the classes to visualize it better:
#register(".pdb")
class PDBReader:
def __init__(self, var):
self.var = var
def __repr__(self):
return f"PDBReader({self.var})"
#register(".gro")
class GromacsReader:
def __init__(self, var):
self.var = var
def __repr__(self):
return f"GromacsReader({self.var})"
And then we initialize some objects:
x = PDBReader("Inside of PDB")
z = GromacsReader("Inside of Gromacs")
print(x) # Output: PDBReader(Inside of PDB)
print(z) # Output: GromacsReader(Inside of Gromacs)
print(READERS) # Output: {'.pdb': PDBReader(Inside of PDB), '.gro': GromacsReader(Inside of Gromacs)}
If you don't want to store the initialized object in READER however, you will still need to return an initialized object, otherwise when you try to initialize the object, it will return None.
You can then simply change wrapper_register to:
def wrapper_register(*args, **kwargs):
READERS[typ] = kls
return kls(*args, **kwargs)
I'm writing decorators, and part of what I need to do is discern whether a function is a function or a method. Is there a way I can find what class a given method is a part of?
e.g. If I was to run this code, what could I write in getOwner to make exampleFunc print something like <class '__main__'.Example>?
class Example:
def method(self):
print("I'm a method")
def exampleFunc(func):
owner = getOwner(func)
print(owner)
test = Example()
exampleFunc(test.method)
If all you need to do is figure out of the thing behaving like a function is a method or a function, that is one purpose of the types module.
import types
def is_method(f):
return type(f) == types.MethodType
In the event that the function-like object is a method, you can find its parent class as follows.
Update Patched for Python3 compatibility.
def method_parent(f):
return f.__self__
If you have a reference to the classes defined in your scope, you'd need to check for each one:
def exampleFunc(f):
class_list = [...]
return any(f in vars(c).values() for c in class_List)
This will return True if function f is an instance method. However, if you wish to return the actual class name:
def exampleFunc(f):
class_list = [...]
for c in class_list:
if f in vars(c).values():
return c.__name__
return 'global function' if 'lambda' not in f.__name__ else 'lambda'
Note that this does not work for __dunder__ methods, and methods that your class inherits. For example,
class A:
def f1(self): pass
class B(A):
def f2(self): pass
print(vars(B))
mappingproxy({'__doc__': None,
'__module__': '__main__',
'f2': <function __main__.B.f2>})
Note that f1 is not a part of B's mappingproxy.
I'm trying to write a Database Abstraction Layer in Python which lets you construct SQL statments using chained function calls such as:
results = db.search("book")
.author("J. K. Rowling")
.price("<40.00")
.title("Harry")
.execute()
but I am running into problems when I try to dynamically add the required methods to the db class.
Here is the important parts of my code:
import inspect
def myName():
return inspect.stack()[1][3]
class Search():
def __init__(self, family):
self.family = family
self.options = ['price', 'name', 'author', 'genre']
#self.options is generated based on family, but this is an example
for opt in self.options:
self.__dict__[opt] = self.__Set__
self.conditions = {}
def __Set__(self, value):
self.conditions[myName()] = value
return self
def execute(self):
return self.conditions
However, when I run the example such as:
print(db.search("book").price(">4.00").execute())
outputs:
{'__Set__': 'harry'}
Am I going about this the wrong way? Is there a better way to get the name of the function being called or to somehow make a 'hard copy' of the function?
You can simply add the search functions (methods) after the class is created:
class Search: # The class does not include the search methods, at first
def __init__(self):
self.conditions = {}
def make_set_condition(option): # Factory function that generates a "condition setter" for "option"
def set_cond(self, value):
self.conditions[option] = value
return self
return set_cond
for option in ('price', 'name'): # The class is extended with additional condition setters
setattr(Search, option, make_set_condition(option))
Search().name("Nice name").price('$3').conditions # Example
{'price': '$3', 'name': 'Nice name'}
PS: This class has an __init__() method that does not have the family parameter (the condition setters are dynamically added at runtime, but are added to the class, not to each instance separately). If Search objects with different condition setters need to be created, then the following variation on the above method works (the __init__() method has a family parameter):
import types
class Search: # The class does not include the search methods, at first
def __init__(self, family):
self.conditions = {}
for option in family: # The class is extended with additional condition setters
# The new 'option' attributes must be methods, not regular functions:
setattr(self, option, types.MethodType(make_set_condition(option), self))
def make_set_condition(option): # Factory function that generates a "condition setter" for "option"
def set_cond(self, value):
self.conditions[option] = value
return self
return set_cond
>>> o0 = Search(('price', 'name')) # Example
>>> o0.name("Nice name").price('$3').conditions
{'price': '$3', 'name': 'Nice name'}
>>> dir(o0) # Each Search object has its own condition setters (here: name and price)
['__doc__', '__init__', '__module__', 'conditions', 'name', 'price']
>>> o1 = Search(('director', 'style'))
>>> o1.director("Louis L").conditions # New method name
{'director': 'Louis L'}
>>> dir(o1) # Each Search object has its own condition setters (here: director and style)
['__doc__', '__init__', '__module__', 'conditions', 'director', 'style']
Reference: http://docs.python.org/howto/descriptor.html#functions-and-methods
If you really need search methods that know about the name of the attribute they are stored in, you can simply set it in make_set_condition() with
set_cond.__name__ = option # Sets the function name
(just before the return set_cond). Before doing this, method Search.name has the following name:
>>> Search.price
<function set_cond at 0x107f832f8>
after setting its __name__ attribute, you get a different name:
>>> Search.price
<function price at 0x107f83490>
Setting the method name this way makes possible error messages involving the method easier to understand.
Firstly, you are not adding anything to the class, you are adding it to the instance.
Secondly, you don't need to access dict. The self.__dict__[opt] = self.__Set__ is better done with setattr(self, opt, self.__Set__).
Thirdly, don't use __xxx__ as attribute names. Those are reserved for Python-internal use.
Fourthly, as you noticed, Python is not easily fooled. The internal name of the method you call is still __Set__, even though you access it under a different name. :-) The name is set when you define the method as a part of the def statement.
You probably want to create and set the options methods with a metaclass. You also might want to actually create those methods instead of trying to use one method for all of them. If you really want to use only one __getattr__ is the way, but it can be a bit fiddly, I generally recommend against it. Lambdas or other dynamically generated methods are probably better.
Here is some working code to get you started (not the whole program you were trying to write, but something that shows how the parts can fit together):
class Assign:
def __init__(self, searchobj, key):
self.searchobj = searchobj
self.key = key
def __call__(self, value):
self.searchobj.conditions[self.key] = value
return self.searchobj
class Book():
def __init__(self, family):
self.family = family
self.options = ['price', 'name', 'author', 'genre']
self.conditions = {}
def __getattr__(self, key):
if key in self.options:
return Assign(self, key)
raise RuntimeError('There is no option for: %s' % key)
def execute(self):
# XXX do something with the conditions.
return self.conditions
b = Book('book')
print(b.price(">4.00").author('J. K. Rowling').execute())