I want to find the caller callable from within the called object, without explcitely forwarding the caller to the called as an object.
My current code looks something like this:
class Boo:
#classmethod
def foo(cls, aa, b2=2):
_ret = aa + b2
autolog(fn=Boo.foo, values={"input": locals(), "output": _ret}, message="This is what it should look like")
autolog_nameless(values={"input": locals(), "output": _ret}, message="This would be convenient")
return _ret
and yields
DEBUG | Boo.foo with aa=3.14159, b2=2 yields 5.14159. Message: This is what it should look like
DEBUG | cls=<class '__main__.Boo'>, aa=3.14159, b2=2, _ret=5.14159 yields 5.14159. Message: This would be convenient
The method autolog gets the locals() and the caller method fn, and parses them using the signature of the caller. This works nice and provides the desired output, but requires passing the caller as an object - something I'd like to avoid as I'm refractoring to include this feature and have about 1000 places to modify.
What I'd like to achieve is: pass locals() only; get the name of the caller within autolog_nameless, using inspect.stack()[1][3] or rather inspect.currentframe().f_back.f_code.co_name (latter has much less overhead), and using this - an possibly the information in locals() - find the caller object to inspect it for its signature.
The method autolog_nameless gets cls, actually the class as part of locals() (or would get self if the caller was a simple method), but I can't really do anything with it.
I'd think all the information required is given, but I just can't find a solution. Any help is greatly appreciated.
As it turns out it's quite simple: listing the methods of the class object found in locals() and searching by name should do the trick.
Code, without error checking:
# getting all methods of the class
methods = inspect.getmembers(locals()['cls'], predicate=inspect.ismethod)
# finding the callers name; won't work within the list comprehension for scope issues
_name = inspect.currentframe().f_back.f_code.co_name
# methods is a list of tuples, each tuple holds the name and the method object
fn = [x for x in methods if x[0] == _name][0][1]
and fn is the caller object to check the signature.
Note, locals()['cls'] works here as in the example we have a classmethod, but this is just the object that the called method belongs to.
Related
I want to get the type hints for an object's attributes. I can only get the hints for the class and not an instance of it.
I have tried using foo_instance.__class__ from here but that only shows the class variables.
So in the example how do I get the type hint of bar?
class foo:
var: int = 42
def __init__(self):
self.bar: int = 2
print(get_type_hints(foo)) # returns {'var': <class 'int'>}
I just had the same problem. The python doc isn't that clear since the example is made with what is now officially called dataclass.
Student(NamedTuple):
name: Annotated[str, 'some marker']
get_type_hints(Student) == {'name': str}
get_type_hints(Student, include_extras=False) == {'name': str}
get_type_hints(Student, include_extras=True) == {
'name': Annotated[str, 'some marker']
}
It give the impression that get_type_hints() works on class directly. Turns out get_type_hints() returns hints based on functions, not on class. That way it can be use with both if we know that. A normal class obviously not being instantiated at it's declaration, it does not have any of the variables set within the __init__() method who hasn't yet been called. It couldn't be that way either if we want the possibility to get the type hints from class-wide variables.
So you could either call it on __init__(), that is if variables are passed in arguments though (yes i seen it's not in your example but might help others since i didn't seen this anywhere in hours of search);
class foo:
var: int = 42
def __init__(self, bar: int = 2):
self.bar = int
print(get_type_hints(foo.__init__))
At last for your exact example i believe you have two choices. You could instantiate a temporary object and use del to clean it right after if your logic allows it. Or declare your variables as class ones with or without default values so you can get them with get_type_hints() and assign them later in instantiations.
Maybe this is a hack, and you have to be the creator of your instances, but there are a subset of cases in which using a data class will get you what you want;
Python 3.7+
#dataclass
class Foo:
bar: str = 2
if __name__ == '__main__':
f = Foo()
print(f.bar)
print(get_type_hints(f))
2
{'bar': <class 'str'>}
Hints only exist at the class level — by the time an instance is created the type of its attributes will be that of whatever value has been assigned to them. You can get the type of any instance attribute by using the first form of the built-in type() function — e.g. type(foo_instance.var).
This information isn't evaluated and only exists in the source code.
if you must get this information, you can use the ast module and extract the information from the source code yourself, if you have access to the source code.
You should also ask yourself if you need this information because in most cases reevaluating the source code will be to much effort.
Is there a better way of doing this?
def __init__(self,**kwargs):
self.ServiceNo = kwargs["ServiceNo"]
self.Operator = kwargs["Operator"]
self.NextBus = kwargs["NextBus"]
self.NextBus2 = kwargs["NextBus2"]
self.NextBus3 = kwargs["NextBus3"]
The attributes (ServiceNo,Operator,...) always exist
That depends on what you mean by "simpler".
For example, is what you wrote simpler than what I would write, namely
def __init__(self,ServiceNo, Operator, NextBus, NextBus2, NextBus3):
self.ServiceNo = ServiceNo
self.Operator = Operator
self.NextBus = NextBus
self.NextBus2 = NextBus2
self.NextBus3 = NextBus3
True, I've repeated each attribute name an additional time, but I've made it much clearer which arguments are legal for __init__. The caller is not free to add any additional keyword argument they like, only to see it silently ignored.
Of course, there's a lot of boilerplate here; that's something a dataclass can address:
from dataclasses import dataclass
#dataclass
class Foo:
ServiceNo: int
Operator: str
NextBus: Bus
NextBus2: Bus
NextBus3: Bus
(Adjust the types as necessary.)
Now each attribute is mentioned once, and you get the __init__ method shown above for free.
Better how? You don’t really describe what problem you’re trying to solve.
If it’s error handling, you can use the dictionary .get() method in the event that key doesn’t exist.
If you just want a more succinct way of initializing variables, you could remove the ** and have the dictionary as a variable itself, then use it elsewhere in your code, but that depends on what your other methods are doing.
A hacky solution available since the attributes and the argument names match exactly is to directly copy from the kwargs dict to the instance's dict, then check that you got all the keys you expected, e.g.:
def __init__(self,**kwargs):
vars(self).update(kwargs)
if vars(self).keys() != {"ServiceNo", "Operator", "NextBus", "NextBus2", "NextBus3"}:
raise TypeError(f"{type(self).__name__} missing required arguments")
I don't recommend this; chepner's options are all superior to this sort of hackery, and they're more reliable (for example, this solution fails if you use __slots__ to prevent autovivication of attributes, as the instance won't having a backing dict you can pull with vars).
Imagine I have a dict.
d = ['a': 1 , 'b':3]
I'm having a hard time to understand the difference between d.get and d.get().
I know that d.get() get the value from the key, like this:
print(d.get('a') )
output: 1
But when I write d.get, it shows this:
print(d.get)
output: <built-in method get of dict object at .........>
What is 'd.get' doing in my code?
I'm using python 3X
A method is literally just an attribute of an object that happens to be of type <class function>. The output you see is essentially what happens when you try to call print() on any function object, and is essentially a concise string representation that python creates for the function.
Actually calling a function is done with parentheses: d.get('a'), which means to execute the behavior the function refers to. It doesn't especially matter where the function is, though: I could do the following, and it would still work:
d = {'a': 1 , 'b':3}
freefunc = d.get
freefunc('a')
This is what the term "first class functions" refers to, when people compare python to something like Java. An entire function can be encapsulated in a variable and treated no differently than any other variable or attribute.
The short answer? There is no difference between the two methods. They are the same exact method.
The difference in your code is at when you write .get() you call the method, but when you write .get you just get a pointer (or location in the memory, to be exact) for that method, to call it later on if needed.
In the first scenario, you are calling print on the result of executing get('a'), which in this case is 1.
In your second scenario, you are calling print on the get function itself, instead of on an execution of it, which evaluates to its documentation, i.e. <built-in method get of dict object at... etc.
I want to pass a string to a method/class function which resolves the correct attribute to modify. I'm pretty sure i've done this before, but I seem to have forgotten how to.
class A:
def __init__(self):
self.word = B.getWord()
self.phrase = "Some default string"
def set_dynamically(self, attribute, value):
self[attribute] = value
This would let me do something like A.set_dynamically('word', C.getWord())
I've tried searching for a question and answer for this but I'm having a hard time defining what this is called, so I didn't really find anything.
Python objects have a built-in method called __setattr__(self, name, value) that does this. You can invoke this method by calling setattr() with an object as the argument:
A = A()
setattr(A, 'word', C.getWord())
There's no reason to do this when you could just do something like A.word = C.getWord() (which, in fact, resolves down to calling __setattr__() the same way as the built-in setattr() function does), but if the property you're setting is named dynamically, then this is how you get around that limitation.
If you want to customize the behavior of how your class acts when you try to call setattr() on it (or when you try to set an attribute normally), you can override the __setattr__(self, name, value) method in much the same way as you're overriding __init__(). Be careful if you do this, because it's really easy to accidentally produce an infinite recursion error - to avoid this you can use object.__setattr__(self, name_value) inside your overridden __setattr__(self, name, value).
Just wanted to add my own solution as well. I created a mapping object;
def _mapper(self, attr, object):
m = { "funcA" : object.funcA,
"funcB" : object.funcB,
... : ...,
}
return m.get(attr)
def call_specific_func_(self, attr):
--do stuff--
for a in some-list:
attr = a.get_attr()
retvals = self._mapper(attr, a)
-- etc --
I'm still learning and like to build things that I will eventually be doing on a regular basis in the future, to give me a better understanding on how x does this or y does that.
I haven't learned much about how classes work entirely yet, but I set up a call that will go through multiple classes.
getattr(monster, monster_class.str().lower())(1)
Which calls this:
class monster:
def vampire(x):
monster_loot = {'Gold':75, 'Sword':50.3, 'Good Sword':40.5, 'Blood':100.0, 'Ore':.05}
if x == 1:
loot_table.all_loot(monster_loot)
Which in turn calls this...
class loot_table:
def all_loot(monster_loot):
loot = ['Gold', 'Sword', 'Good Sword', 'Ore']
loot_dropped = {}
for i in monster_loot:
if i in loot:
loot_dropped[i] = monster_loot[i]
drop_chance.chance(loot_dropped)
And then, finally, gets to the last class.
class drop_chance:
def chance(loot_list):
loot_gained = []
for i in loot_list:
x = random.uniform(0.0,100.0)
if loot_list[i] >= x:
loot_gained.append(i)
return loot_gained
And it all works, except it's not returning loot_gained. I'm assuming it's just being returned to the loot_table class and I have no idea how to bypass it all the way back down to the first line posted. Could I get some insight?
Keep using return.
def foo():
return bar()
def bar():
return baz()
def baz():
return 42
print foo()
I haven't learned much about how classes work entirely yet...
Rather informally, a class definition is a description of the object of that class (a.k.a. instance of the class) that is to be created in future. The class definition contains the code (definitions of the methods). The object (the class instance) basically contains the data. The method is a kind of function that can take arguments and that is capable to manipulate the object's data.
This way, classes should represent the behaviour of the real-world objects, the class instances simulate existence of the real-world objects. The methods represent actions that the object apply on themselves.
From that point of view, a class identifier should be a noun that describes category of objects of the class. A class instance identifier should also be a noun that names the object. A method identifier is usually a verb that describes the action.
In your case, at least the class drop_chance: is suspicious at least because of naming it this way.
If you want to print something reasonable about the object--say using the print(monster)--then define the __str__() method of the class -- see the doc.