In the following example, the class MyExample read a list of filenames which have underscores in their file names.
class MyExample(object):
def __init__(self, location: str):
self.location = location
def get_file_names(self):
# For simplicity, lets just return an example of the output
return ["my_file_name_01.txt", "my_file_name_02.txt"]
def get_file_name_number(self):
# Idem as before.
return ["file_name_01.txt", "file_name_02.txt"]
def get_file_size(self):
# It does not return a list of strings so the desired
# property or function will not be applied here
return [3800, 4000]
When the code is executed, the results are
my_object = MyExample("./a/random/path")
print(my_object.get_file_names())
print(my_object.get_file_name_number())
print(my_object.get_file_size())
# The results:
['my_file_name_01.txt', 'my_file_name_02.txt']
['file_name_01.txt', 'file_name_02.txt']
[3800, 4000]
Now, I would like to find a way to apply a function or property (let's call it to_dot) that can replace the underscores for dots from the output of get_file_names() and get_file_name_number.
The final code should have to return something like
# Calling this function with .to_dots
my_object.get_file_names().to_dots
["my.file.name.01.txt", "my.file.name.02.txt"] # <-- The desired output
# Calling this function with .to_dots
my_object.get_file_name_number().to_dots
["file.name.01.txt", "file.name.02.txt"] # <-- The desired output
# Calling this function with .to_dots
my_object.get_file_name_number().to_dots
AttributeError # # <-- The desired output ... or something similar
Is there a way to add the to_dots to the class MyExample in order to replace the underscores of some of the methods inside?
I am not very familiar with decorators but I suspect there could be a trick to do that. So far I have unsuccessfully tried with #property but as far as I know, there are many types of decorators.... Or maybe it can be done without decorators and I am very lost.
Thank you.
You could do something like this:
from collections import UserList
class MyList(UserList):
#property
def to_dots(self):
return [s.replace("_", ".") for s in self.data]
class MyExample(object):
def __init__(self, location: str):
self.location = location
def get_file_names(self):
return MyList(["my_file_name_01.txt", "my_file_name_02.txt"])
Result for
my_object = MyExample("./a/random/path")
print(my_object.get_file_names())
print(my_object.get_file_names().to_dots)
is
['my_file_name_01.txt', 'my_file_name_02.txt']
['my.file.name.01.txt', 'my.file.name.02.txt']
You can use a class decorator to apply a function decorator to the specified class methods.
from functools import wraps
import inspect
def dec_methods(decorator, *members):
"""Class decorator to apply specfied decorator to specified members of class."""
def dec_the_class(cls):
for name, m in inspect.getmembers(cls, inspect.isfunction):
if name in members:
setattr(cls, name, decorator(m))
return cls
return dec_the_class
def to_dots(func):
"""Function decorator to replace '_' with dots in list of strings returned."""
#wraps(func)
def wrapped(*args, **kwargs):
results = func(*args, **kwargs)
results = [result.replace('_', '.') for result in results]
return results
return wrapped
#dec_methods(to_dots, 'get_file_names', 'get_file_name_number')
class MyExample(object):
def __init__(self, location: str):
self.location = location
def get_file_names(self):
# For simplicity, lets just return an example of the output
return ["my_file_name_01.txt", "my_file_name_02.txt"]
def get_file_name_number(self):
# Idem as before.
return ["file_name_01.txt", "file_name_02.txt"]
def get_file_size(self):
# It does not return a list of strings so the desired
# property or function will not be applied here
return [3800, 4000]
my_object = MyExample("./a/random/path")
print(my_object.get_file_names()) # -> ['my.file.name.01.txt', 'my.file.name.02.txt']
print(my_object.get_file_name_number()) # -> ['file.name.01.txt', 'file.name.02.txt']
print(my_object.get_file_size()) # -> [3800, 4000]
Why not pass the required output format (dotted or not) as optional argument to those methods?
class MyExample(object):
def __init__(self, location: str):
self.location = location
#staticmethod
def map_list(lst, dotted=False):
return [s.replace("_", ".") for s in lst] if dotted else lst
def get_file_names(self, dotted=False):
return self.map_list(["my_file_name_01.txt", "my_file_name_02.txt"], dotted)
def get_file_name_number(self, dotted=False):
return self.map_list(["file_name_01.txt", "file_name_02.txt"], dotted)
def get_file_size(self):
return [3800, 4000]
my_object = MyExample("./a/random/path")
print(my_object.get_file_names()) # Underscores untouched
print(my_object.get_file_name_number(dotted=True)) # Underscores replaced
print(my_object.get_file_size())
Define your own decorator:
def to_dots(func):
def inner():
original_return = func()
return [item.replace('_','.') for item in original_return ]
return inner
And use it as :
#to_dots
def get_file_names(self):
Related
I have some classes FooA and FooB which are basically a collection of "static" methods. They operate on data - let's say it is an DataItem object:
# Base class with common behavior
class FooBase:
#classmethod
def method1(cls, arg, data: DataItem):
#res = ...
return res
#classmethod
def method2(cls, arg1, arg2, data: DataItem):
# res = ... # using method1
return res
# specialized classes
class FooA(FooBase):
# define extra methods
pass
class FooB(FooBase):
# define extra methods
pass
# usage 1: as "static methods"
res = FooA.method1(arg, data)
res2 = FooB.method2(args, data)
Now, I'd like to use these classes as attributes of a "managing" class (MyApp) which also has access to a datasource and should implicitly supply DataItems to the static methods of FooA and FooB. Moreover, the datasource supplies a list of DataItem objects.
# usage 2: as part of an "App" class
# here, the "data" argument should be supplied implicitly by MyApp
# also: MyApp contains a list of "data" objects
class MyApp:
def __init__(self, datasrc):
self.datasrc = datasrc
# this could be a generator
def get_data(self, key) -> List[DataItem]:
return self.datasrc.get_data(key)
# FooA, FooB as class / instance level attributes, descriptors, ???
# usage
my_app = MyApp("datasrc")
res_list = my_app.foo_a.method1(arg) # foo_a is a FooA obj, "data" arg is supplied automatically
# optionally, but not necessarily call as a static attribute:
res = MyApp.foo_a.method1(arg, data: DataItem) # same as FooA.method1(arg, data)
I have tried different things but found not satisfactory solution.
So... I am not sure can it be done in nice way, I thought about that and all approaches has serious drawbacks. One of the problem is we actually want to have a method that returns list or single item, depending on input parameters, which is bad.
One of way could be store datasrc in FooBase, but it violates SRP
class FooBase:
def __init__(self, datasrc):
FooBase.datasrc = datasrc
#classmethod
def method1(cls, arg, data=None):
if data is None:
return [cls.method1(arg, d) for d in cls.datasrc]
return data
Or use isinstance
#classmethod
def method1(cls, arg, data):
if isinstance(data, list):
return [cls.method1(arg, d) for d in data]
return data
But it forces us to adjust every method (which could be done with decorator or metaclass).
Another way could be use some intermediate layer:
def decorator(datasrc):
def wrapper(foo):
def f(*args, **kwargs):
# We could catch TypeError here to serve case when data is passed
return [foo(*args, **kwargs, data=data) for data in datasrc]
return f
return wrapper
class FooAdapter:
def __init__(self, datasrc, foo_cls):
self.datasrc = datasrc
methods = [
getattr(foo_cls, m)
for m in dir(foo_cls)
if callable(getattr(foo_cls, m)) and not m.startswith("__")
] # all methods of our Foo class
for method in methods:
setattr(self, method.__name__, decorator(datasrc)(method))
class MyApp:
def __init__(self, datasrc):
self.datasrc = datasrc
self.foo_a = FooAdapter(datasrc, FooA)
self.foo_b = FooAdapter(datasrc, FooB)
But solution with dynamically added functions breaks IDE support.
The cleanest solution imo could be to have Enum for Foo methods and Enum for Foo classes, then you could write code in MyApp
def get_bulk(m: MethodEnum, f: FooEnum, *args):
return [getattr(enum_to_cls_mapping[f], m)(*args, data=d) for d in self.datasrc]
Is there a way to have completion/intellisense on (*args ,**kwargs) functions?
For instance:
class GetVar(GetVarInterface):
#classmethod
def fromcustom(cls,locorvar,offset=0,varType="int", name=None,deref=False,member=None):
return GetVarCustom(locorvar,offset,varType, name,deref,member)
class GetVarCustom(GetVar):
def __init__(self,locorvar,offset=0,varType="int", name=None,deref=False,member=None):
I wanted to implement this without specifying every argument of the constructor (For example using *vars, **kwargs) but didn't want to lose completion/intellisense abilities. Is there a way?
The disadvantage in the current implementation is that you would have to replicate the signature twice for every change...
The only option is to add a comment under the function to hint the arguments, otherwise you can't; if the ide is reading that a function has undefined arguments, it will show you that it's undefined.
A "solution" is to just use the common arguments and pass the rest as kwargs, or you can keep the original init.
class Single_Init:
def __init__(self, val_a, val_b, name=None):
self.val_a = val_a
self.val_b = val_b
self.name = name
class Single_Init_B(Single_Init):
# The previous contructor is calld
def get_result(self):
return self.val_a + self.val_b
class Split_Const:
def op_offset(self, offset):
self.offset = offset
def __init__(self, name, member=None, **kwargs):
""" You olso can hint in a func coment """
self.name = name
self.member = member
if 'offset' in kwargs:
self.offset = kwargs['offset']
else:
self.offset = None
if __name__ == '__main__':
single = Single_Init_B(2, 3)
print('Single:', single.get_result())
split = Split_Const('Name')
split.op_offset(0.5)
print('Split:', split.offset)
Got the solution outside this site..
#functools.wraps(functools.partial(GetVarCustom.__init__,1))
def f(*args,**kwargs):
return GetVarCustom(*args,**kwargs)
Of course, it would have been easier in case of a standard function. However, you need to update the assigned attribute of wraps. Otherwise it will change the function name.
#functools.wraps(GetVarCustom.value,assigned=['__doc__'])
def getvalue(*args,**kwargs):
return self_custom.value(*args,**kwargs)
Say I have 2 different implementations of a class
class ParentA:
def initialize(self):
pass
def some_event(self):
pass
def order(self, value):
# handle order in some way for Parent A
class ParentB:
def initialize(self):
pass
def some_event(self):
pass
def order(self, value):
# handle order in another for Parent B
How can I dynamically let some 3rd class inherit from either ParentA or ParentB based on something like this?
class MyCode:
def initialize(self):
self.initial_value = 1
def some_event(self):
# handle event
order(self.initial_value)
# let MyCode inherit from ParentA and run
run(my_code, ParentA)
Simply store the class-object in a variable (in the example below, it is named base), and use the variable in the base-class-spec of your class statement.
def get_my_code(base):
class MyCode(base):
def initialize(self):
...
return MyCode
my_code = get_my_code(ParentA)
Also, you can use type builtin. As callable, it takes arguments: name, bases, dct (in its simplest form).
def initialize(self):
self.initial_value = 1
def some_event(self):
# handle event
order(self.initial_value)
subclass_body_dict = {
"initialize": initialize,
"some_event": some_event
}
base_class = ParentA # or ParentB, as you wish
MyCode = type("MyCode", (base_class, ), subclass_body_dict)
This is more explicit than snx2 solution, but still - I like his way better.
PS. of course, you dont have to store base_class, nor subclass_body_dict, you can build those values in type() call like:
MyCode = type("MyCode", (ParentA, ), {
"initialize": initialize,
"some_event": some_event
})
Just as a quick copy-and-paste-ready snippet, I've added the comments from shx2's answer to create this (memoized with a created_classes dict attribute, so that the classes created by successive identical calls with the same class will give identical classes):
class ParentA:
val = "ParentA"
class ParentB:
val = "ParentB"
class DynamicClassCreator():
def __init__(self):
self.created_classes = {}
def __call__(self, *bases):
rep = ",".join([i.__name__ for i in bases])
if rep in self.created_classes:
return self.created_classes[rep]
class MyCode(*bases):
pass
self.created_classes[rep] = MyCode
return MyCode
creator = DynamicClassCreator()
instance1 = creator(ParentA, ParentB)()
print(instance1.val) #prints "ParentA"
instance2 = creator(ParentB, ParentA)()
print(instance2.val) #prints "ParentB"
If you wanted to get fancy you could even make DynamicClassCreator a Singleton: https://stackoverflow.com/a/7346105/5122790
As an alternative to Chris's answer implementing the memoisation suggestion for shx2's answer, I'd prefer to use a memoize decorator (the end result is still a class but it's clearer to me that the function is the interface), and also use setdefault to simplify adding to the memo dict, and do not convert the names to string but use the tuple bases itself as the key, simplifying the code to:
class Memoize:
def __init__(self, f):
self.f = f
self.memo = {}
def __call__(self, *args):
return self.memo.setdefault(args, self.f(*args))
class ParentA:
def initialize(self):
pass
class ParentB:
def initialize(self):
pass
#Memoize
def get_my_code(base):
class MyCode(base):
def initialize(self):
pass
return MyCode
a1 = get_my_code(ParentA)
a2 = get_my_code(ParentA)
b1 = get_my_code(ParentB)
print(a1 is a2) # True
print(a1 is b1) # False
(Not a good example as the code provided doesn't actually do anything other than overwrite the parent class's initialize method...)
I have a class that has multiple methods and I want to store all of the available methods that would be easily accessible in example would be something like this
class Methods:
def foo(self, a):
return f'hello {a}'
def bar(self, b):
return f'hello {b}'
def methods_dict(self, var, **kwargs):
dic = {
'me' : self.foo(var),
'be': self.bar(var)
}
return dic
But on runtime my methods_dict() method will execute both of the methods inside of it's dictionary.
One one hand I'm planing to store only strings in there and it's really easily accessible, on the other hand i probably would not need to access all of the available methods at once.
Any suggestions ?
I am planning to use those methods as follows
class InheritMethods(Methods):
def __init__(self, method_name):
self.method_name = method_name
def add_to_list(self, input):
arr = []
arr.append(self.method_dicts(input)[self.method_name]
return arr
To clear things up, I am gonna call specific method based on input name, so basically input == method_name
I could do conditional statements like if input == 'foo': do somethings.., but if i end up having a lot of methods, my code is going to be a mess, so i assume(!) that would not be a great idea
I think you can get what you want with the following. Your exact usecase is still not clear. Please respond if I am heading in the wrong direction.
Using self.__getattribute__() you can get a function by name. Of course you would have to catch exceptions etc.
class Methods:
def foo(self, a):
return f'hello {a}'
def bar(self, b):
return f'hello {b}'
class InheritMethods(Methods):
def __init__(self, method_name):
self.method_name = method_name
def add_to_list(self, method_name, input):
method = getattr(self, method_name)
result = method(input)
return [result]
class InheritSingleMethod(Methods):
def __init__(self, method_name):
self.add_to_list = self.getattr(self, method_name)
Output
# Any method version
inherit_methods = InheritMethods('a') # < no use for that argument right?
inherit_methods.add_to_list('foo', 'laurens')
> ['hello laurens']
# Single method version
inherit_single_method = InheritSingleMethod('foo')
inherit_single_method.add_to_list('laurens')
> 'hello laurens'
If all you want to do is access a method of Methods given the name in a str, use getattr:
name = input()
m = Methods()
getattr(m, name)("bob")
I have a dict of different types for which I want to add a simple getter based on the name of the actual parameter.
For example, for three storage parameters, let's say:
self.storage = {'total':100,'used':88,'free':1}
I am looking now for a way (if possible?) to generate a function on the fly with some meta-programming magic.
Instead of
class spaceObj(object):
def getSize(what='total'):
return storage[what]
or hard coding
#property
def getSizeTotal():
return storage['total']
but
class spaceObj(object):
# manipulting the object's index and magic
#property
def getSize:
return ???
so that calling mySpaceObj.getSizeFree would be derived - with getSize only defined once in the object and related functions derived from it by manipulating the objects function list.
Is something like that possible?
While certainly possible to get an unknown attribute from a class as a property, this is not a pythonic approach (__getattr__ magic methods are rather rubyist)
class spaceObj(object):
storage = None
def __init__(self): # this is for testing only
self.storage = {'total':100,'used':88,'free':1}
def __getattr__(self, item):
if item[:7] == 'getSize': # check if an undefined attribute starts with this
return self.getSize(item[7:])
def getSize(self, what='total'):
return self.storage[what.lower()]
print (spaceObj().getSizeTotal) # 100
You can put the values into the object as properties:
class SpaceObj(object):
def __init__(self, **kwargs):
self.__dict__.update(kwargs)
storage = {'total':100,'used':88,'free':1}
o = SpaceObj(**storage)
print o.total
or
o = SpaceObj(total=100, used=88, free=1)
print o.total
or using __getattr__:
class SpaceObj(object):
def __init__(self, **kwargs):
self.storage = kwargs
def __getattr__(self,name):
return self.storage[name]
o = SpaceObj(total=100, used=88, free=1)
print o.total
The latter approach takes a bit more code but it's more safe; if you have a method foo and someone create the instance with SpaceObj(foo=1), then the method will be overwritten with the first approach.
>>> import new
>>> funcstr = "def wat(): print \"wat\";return;"
>>> funcbin = compile(funcstr,'','exec')
>>> ns = {}
>>> exec funcbin in ns
>>> watfunction = new.function(ns["wat"].func_code,globals(),"wat")
>>> globals()["wat"]=watfunction
>>> wat()
wat