Overriding function signature (in help) when using functools.wraps - python

I'm creating a wrapper for a function with functools.wraps. My wrapper has the effect of overriding a default parameter (and it doesn't do anything else):
def add(*, a=1, b=2):
"Add numbers"
return a + b
#functools.wraps(add)
def my_add(**kwargs):
kwargs.setdefault('b', 3)
return add(**kwargs)
This my_add definition behaves the same as
#functools.wraps(add)
def my_add(*, a=1, b=3):
return add(a=a, b=b)
except that I didn't have to manually type out the parameter list.
However, when I run help(my_add), I see the help string for add, which has the wrong function name and the wrong default argument for the parameter b:
add(*, a=1, b=2)
Add numbers
How can I override the function name and the default argument in this help() output?
(Or, is there a different way to define my_add, using for example some magic function my_add = magic(add, func_name='my_add', kwarg_defaults={'b': 3}) that will do what I want?)

Let me try and explain what happens.
When you call the help functions, this is going to request information about your function using the inspect module. Therefore you have to change the function signature, in order to change the default argument.
Now this is not something that is advised, or often preferred, but who cares about that right? The provided solution is considered hacky and probably won't work for all versions of Python. Therefore you might want to reconsider how important the help function is... Any way let's start with some explanation on how it was done, followed by the code and test case.
Copying functions
Now the first thing we will do is copy the entire function, this is because I only want to change the signature of the new function and not the original function. This decouples the new my_add signature (and default values) from the original add function.
See:
How to create a copy of a python function
How can I make a deepcopy of a function in Python?
For ideas of how to do this (I will show my version in a bit).
Copying / updating signature
The next step is to get a copy of the function signature, for that this post was very useful. Except for the part where we have to adjust the signature parameters to match the new keyword default arguments.
For that we have to change the value of a mappingproxy, which we can see when running the debugger on the return value of inspect.signature(g). Now so far this can only be done by changing the private variables (the values with leading underscores _private). Therefore this solution will be considered hacky and is not guaranteed to withstand possible updates. That said, let's see the solution!
Full code
import inspect
import types
import functools
def update_func(f, func_name='', update_kwargs: dict = None):
"""Based on http://stackoverflow.com/a/6528148/190597 (Glenn Maynard)"""
g = types.FunctionType(
code=f.__code__,
globals=f.__globals__.copy(),
name=f.__name__,
argdefs=f.__defaults__,
closure=f.__closure__
)
g = functools.update_wrapper(g, f)
g.__signature__ = inspect.signature(g)
g.__kwdefaults__ = f.__kwdefaults__.copy()
# Adjust your arguments
for key, value in (update_kwargs or {}).items():
g.__kwdefaults__[key] = value
g.__signature__.parameters[key]._default = value
g.__name__ = func_name or g.__name__
return g
def add(*, a=1, b=2):
"Add numbers"
return a + b
my_add = update_func(add, func_name="my_add", update_kwargs=dict(b=3))
Example
if __name__ == '__main__':
a = 2
print("*" * 50, f"\nMy add\n", )
help(my_add)
print("*" * 50, f"\nOriginal add\n", )
help(add)
print("*" * 50, f"\nResults:"
f"\n\tMy add : a = {a}, return = {my_add(a=a)}"
f"\n\tOriginal add: a = {a}, return = {add(a=a)}")
Output
**************************************************
My add
Help on function my_add in module __main__:
my_add(*, a=1, b=3)
Add numbers
**************************************************
Original add
Help on function add in module __main__:
add(*, a=1, b=2)
Add numbers
**************************************************
Results:
My add : a = 2, return = 5
Original add: a = 2, return = 4
Usages
f: is the function that you want to update
func_name: is optionally the new name of the function (if empty, keeps the old name)
update_kwargs: is a dictionary containing the key and value of the default arguments that you want to update.
Notes
The solution is using copy variables to make full copies of dictionaries, such that there is no impact on the original add function.
The _default value is a private variable, and can be changed in future releases of python.

Related

Trouble naming csv file I'm writing a dataframe to in pandas in Python [duplicate]

I already read How to get a function name as a string?.
How can I do the same for a variable? As opposed to functions, Python variables do not have the __name__ attribute.
In other words, if I have a variable such as:
foo = dict()
foo['bar'] = 2
I am looking for a function/attribute, e.g. retrieve_name() in order to create a DataFrame in Pandas from this list, where the column names are given by the names of the actual dictionaries:
# List of dictionaries for my DataFrame
list_of_dicts = [n_jobs, users, queues, priorities]
columns = [retrieve_name(d) for d in list_of_dicts]
With Python 3.8 one can simply use f-string debugging feature:
>>> foo = dict()
>>> f'{foo=}'.split('=')[0]
'foo'
One drawback of this method is that in order to get 'foo' printed you have to add f'{foo=}' yourself. In other words, you already have to know the name of the variable. In other words, the above code snippet is exactly the same as just
>>> 'foo'
Even if variable values don't point back to the name, you have access to the list of every assigned variable and its value, so I'm astounded that only one person suggested looping through there to look for your var name.
Someone mentioned on that answer that you might have to walk the stack and check everyone's locals and globals to find foo, but if foo is assigned in the scope where you're calling this retrieve_name function, you can use inspect's current frame to get you all of those local variables.
My explanation might be a little bit too wordy (maybe I should've used a "foo" less words), but here's how it would look in code (Note that if there is more than one variable assigned to the same value, you will get both of those variable names):
import inspect
x, y, z = 1, 2, 3
def retrieve_name(var):
callers_local_vars = inspect.currentframe().f_back.f_locals.items()
return [var_name for var_name, var_val in callers_local_vars if var_val is var]
print(retrieve_name(y))
If you're calling this function from another function, something like:
def foo(bar):
return retrieve_name(bar)
foo(baz)
And you want the baz instead of bar, you'll just need to go back a scope further. This can be done by adding an extra .f_back in the caller_local_vars initialization.
See an example here: ideone
The only objects in Python that have canonical names are modules, functions, and classes, and of course there is no guarantee that this canonical name has any meaning in any namespace after the function or class has been defined or the module imported. These names can also be modified after the objects are created so they may not always be particularly trustworthy.
What you want to do is not possible without recursively walking the tree of named objects; a name is a one-way reference to an object. A common or garden-variety Python object contains no references to its names. Imagine if every integer, every dict, every list, every Boolean needed to maintain a list of strings that represented names that referred to it! It would be an implementation nightmare, with little benefit to the programmer.
TL;DR
Use the Wrapper helper from python-varname:
from varname.helpers import Wrapper
foo = Wrapper(dict())
# foo.name == 'foo'
# foo.value == {}
foo.value['bar'] = 2
For list comprehension part, you can do:
n_jobs = Wrapper(<original_value>)
users = Wrapper(<original_value>)
queues = Wrapper(<original_value>)
priorities = Wrapper(<original_value>)
list_of_dicts = [n_jobs, users, queues, priorities]
columns = [d.name for d in list_of_dicts]
# ['n_jobs', 'users', 'queues', 'priorities']
# REMEMBER that you have to access the <original_value> by d.value
I am the author of the python-varname package. Please let me know if you have any questions or you can submit issues on Github.
The long answer
Is it even possible?
Yes and No.
We are retrieving the variable names at runtime, so we need a function to be called to enable us to access the previous frames to retrieve the variable names. That's why we need a Wrapper there. In that function, at runtime, we are parsing the source code/AST nodes in the previous frames to get the exact variable name.
However, the source code/AST nodes in the previous frames are not always available, or they could be modified by other environments (e.g: pytest's assert statement). One simple example is that the codes run via exec(). Even though we are still able to retrieve some information from the bytecode, it needs too much effort and it is also error-prone.
How to do it?
First of all, we need to identify which frame the variable is given. It's not always simply the direct previous frame. For example, we may have another wrapper for the function:
from varname import varname
def func():
return varname()
def wrapped():
return func()
x = wrapped()
In the above example, we have to skip the frame inside wrapped to get to the right frame x = wrapped() so that we are able to locate x. The arguments frame and ignore of varname allow us to skip some of these intermediate frames. See more details in the README file and the API docs of the package.
Then we need to parse the AST node to locate where the variable is assigned value (function call) to. It's not always just a simple assignment. Sometimes there could be complex AST nodes, for example, x = [wrapped()]. We need to identify the correct assignment by traversing the AST tree.
How reliable is it?
Once we identify the assignment node, it is reliable.
varname is all depending on executing package to look for the node. The node executing detects is ensured to be the correct one (see also this).
It partially works with environments where other AST magics apply, including pytest, ipython, macropy, birdseye, reticulate with R, etc. Neither executing nor varname is 100% working with those environments.
Do we need a package to do it?
Well, yes and no, again.
If your scenario is simple, the code provided by #juan Isaza or #scohe001 probably is enough for you to work with the case where a variable is defined at the direct previous frame and the AST node is a simple assignment. You just need to go one frame back and retrieve the information there.
However, if the scenario becomes complicated, or we need to adopt different application scenarios, you probably need a package like python-varname, to handle them. These scenarios may include to:
present more friendly messages when the source code is not available or AST nodes are not accessible
skip intermediate frames (allows the function to be wrapped or called in other intermediate frames)
automatically ignores calls from built-in functions or libraries. For example: x = str(func())
retrieve multiple variable names on the left-hand side of the assignment
etc.
How about the f-string?
Like the answer provided by #Aivar Paalberg. It's definitely fast and reliable. However, it's not at runtime, meaning that you have to know it's foo before you print the name out. But with varname, you don't have to know that variable is coming:
from varname import varname
def func():
return varname()
# In external uses
x = func() # 'x'
y = func() # 'y'
Finally
python-varname is not only able to detect the variable name from an assignment, but also:
Retrieve variable names directly, using nameof
Detect next immediate attribute name, using will
Fetch argument names/sources passed to a function using argname
Read more from its documentation.
However, the final word I want to say is that, try to avoid using it whenever you can.
Because you can't make sure that the client code will run in an environment where the source node is available or AST node is accessible. And of course, it costs resources to parse the source code, identify the environment, retrieve the AST nodes and evaluate them when needed.
On python3, this function will get the outer most name in the stack:
import inspect
def retrieve_name(var):
"""
Gets the name of var. Does it from the out most frame inner-wards.
:param var: variable to get name from.
:return: string
"""
for fi in reversed(inspect.stack()):
names = [var_name for var_name, var_val in fi.frame.f_locals.items() if var_val is var]
if len(names) > 0:
return names[0]
It is useful anywhere on the code. Traverses the reversed stack looking for the first match.
I don't believe this is possible. Consider the following example:
>>> a = []
>>> b = a
>>> id(a)
140031712435664
>>> id(b)
140031712435664
The a and b point to the same object, but the object can't know what variables point to it.
def name(**variables):
return [x for x in variables]
It's used like this:
name(variable=variable)
>> my_var = 5
>> my_var_name = [ k for k,v in locals().items() if v == my_var][0]
>> my_var_name
'my_var'
In case you get an error if myvar points to another variable, try this (suggested by #mherzog)-
>> my_var = 5
>> my_var_name = [ k for k,v in locals().items() if v is my_var][0]
>> my_var_name
'my_var'
locals() - Return a dictionary containing the current scope's local variables.
by iterating through this dictionary we can check the key which has a value equal to the defined variable, just extracting the key will give us the text of variable in string format.
from (after a bit changes)
https://www.tutorialspoint.com/How-to-get-a-variable-name-as-a-string-in-Python
I wrote the package sorcery to do this kind of magic robustly. You can write:
from sorcery import dict_of
columns = dict_of(n_jobs, users, queues, priorities)
and pass that to the dataframe constructor. It's equivalent to:
columns = dict(n_jobs=n_jobs, users=users, queues=queues, priorities=priorities)
Here's one approach. I wouldn't recommend this for anything important, because it'll be quite brittle. But it can be done.
Create a function that uses the inspect module to find the source code that called it. Then you can parse the source code to identify the variable names that you want to retrieve. For example, here's a function called autodict that takes a list of variables and returns a dictionary mapping variable names to their values. E.g.:
x = 'foo'
y = 'bar'
d = autodict(x, y)
print d
Would give:
{'x': 'foo', 'y': 'bar'}
Inspecting the source code itself is better than searching through the locals() or globals() because the latter approach doesn't tell you which of the variables are the ones you want.
At any rate, here's the code:
def autodict(*args):
get_rid_of = ['autodict(', ',', ')', '\n']
calling_code = inspect.getouterframes(inspect.currentframe())[1][4][0]
calling_code = calling_code[calling_code.index('autodict'):]
for garbage in get_rid_of:
calling_code = calling_code.replace(garbage, '')
var_names, var_values = calling_code.split(), args
dyn_dict = {var_name: var_value for var_name, var_value in
zip(var_names, var_values)}
return dyn_dict
The action happens in the line with inspect.getouterframes, which returns the string within the code that called autodict.
The obvious downside to this sort of magic is that it makes assumptions about how the source code is structured. And of course, it won't work at all if it's run inside the interpreter.
>>> locals()['foo']
{}
>>> globals()['foo']
{}
If you wanted to write your own function, it could be done such that you could check for a variable defined in locals then check globals. If nothing is found you could compare on id() to see if the variable points to the same location in memory.
If your variable is in a class, you could use className.dict.keys() or vars(self) to see if your variable has been defined.
This function will print variable name with its value:
import inspect
def print_this(var):
callers_local_vars = inspect.currentframe().f_back.f_locals.items()
print(str([k for k, v in callers_local_vars if v is var][0])+': '+str(var))
***Input & Function call:***
my_var = 10
print_this(my_var)
***Output**:*
my_var: 10
I have a method, and while not the most efficient...it works! (and it doesn't involve any fancy modules).
Basically it compares your Variable's ID to globals() Variables' IDs, then returns the match's name.
def getVariableName(variable, globalVariables=globals().copy()):
""" Get Variable Name as String by comparing its ID to globals() Variables' IDs
args:
variable(var): Variable to find name for (Obviously this variable has to exist)
kwargs:
globalVariables(dict): Copy of the globals() dict (Adding to Kwargs allows this function to work properly when imported from another .py)
"""
for globalVariable in globalVariables:
if id(variable) == id(globalVariables[globalVariable]): # If our Variable's ID matches this Global Variable's ID...
return globalVariable # Return its name from the Globals() dict
In Python, the def and class keywords will bind a specific name to the object they define (function or class). Similarly, modules are given a name by virtue of being called something specific in the filesystem. In all three cases, there's an obvious way to assign a "canonical" name to the object in question.
However, for other kinds of objects, such a canonical name may simply not exist. For example, consider the elements of a list. The elements in the list are not individually named, and it is entirely possible that the only way to refer to them in a program is by using list indices on the containing list. If such a list of objects was passed into your function, you could not possibly assign meaningful identifiers to the values.
Python doesn't save the name on the left hand side of an assignment into the assigned object because:
It would require figuring out which name was "canonical" among multiple conflicting objects,
It would make no sense for objects which are never assigned to an explicit variable name,
It would be extremely inefficient,
Literally no other language in existence does that.
So, for example, functions defined using lambda will always have the "name" <lambda>, rather than a specific function name.
The best approach would be simply to ask the caller to pass in an (optional) list of names. If typing the '...','...' is too cumbersome, you could accept e.g. a single string containing a comma-separated list of names (like namedtuple does).
I think it's so difficult to do this in Python because of the simple fact that you never will not know the name of the variable you're using. So, in his example, you could do:
Instead of:
list_of_dicts = [n_jobs, users, queues, priorities]
dict_of_dicts = {"n_jobs" : n_jobs, "users" : users, "queues" : queues, "priorities" : priorities}
Many of the answers return just one variable name. But that won't work well if more than one variable have the same value. Here's a variation of Amr Sharaki's answer which returns multiple results if more variables have the same value.
def getVariableNames(variable):
results = []
globalVariables=globals().copy()
for globalVariable in globalVariables:
if id(variable) == id(globalVariables[globalVariable]):
results.append(globalVariable)
return results
a = 1
b = 1
getVariableNames(a)
# ['a', 'b']
just another way to do this based on the content of input variable:
(it returns the name of the first variable that matches to the input variable, otherwise None. One can modify it to get all variable names which are having the same content as input variable)
def retrieve_name(x, Vars=vars()):
for k in Vars:
if isinstance(x, type(Vars[k])):
if x is Vars[k]:
return k
return None
If the goal is to help you keep track of your variables, you can write a simple function that labels the variable and returns its value and type. For example, suppose i_f=3.01 and you round it to an integer called i_n to use in a code, and then need a string i_s that will go into a report.
def whatis(string, x):
print(string+' value=',repr(x),type(x))
return string+' value='+repr(x)+repr(type(x))
i_f=3.01
i_n=int(i_f)
i_s=str(i_n)
i_l=[i_f, i_n, i_s]
i_u=(i_f, i_n, i_s)
## make report that identifies all types
report='\n'+20*'#'+'\nThis is the report:\n'
report+= whatis('i_f ',i_f)+'\n'
report+=whatis('i_n ',i_n)+'\n'
report+=whatis('i_s ',i_s)+'\n'
report+=whatis('i_l ',i_l)+'\n'
report+=whatis('i_u ',i_u)+'\n'
print(report)
This prints to the window at each call for debugging purposes and also yields a string for the written report. The only downside is that you have to type the variable twice each time you call the function.
I am a Python newbie and found this very useful way to log my efforts as I program and try to cope with all the objects in Python. One flaw is that whatis() fails if it calls a function described outside the procedure where it is used. For example, int(i_f) was a valid function call only because the int function is known to Python. You could call whatis() using int(i_f**2), but if for some strange reason you choose to define a function called int_squared it must be declared inside the procedure where whatis() is used.
Maybe this could be useful:
def Retriever(bar):
return (list(globals().keys()))[list(map(lambda x: id(x), list(globals().values()))).index(id(bar))]
The function goes through the list of IDs of values from the global scope (the namespace could be edited), finds the index of the wanted/required var or function based on its ID, and then returns the name from the list of global names based on the acquired index.
Whenever I have to do it, mostly while communicating json schema and constants with the frontend I define a class as follows
class Param:
def __init__(self, name, value):
self.name = name
self.value = value
Then define the variable with name and value.
frame_folder_count = Param({'name':'frame_folder_count', 'value':10})
Now you can access the name and value using the object.
>>> frame_folder_count.name
'frame_folder_count'
>>> def varname(v, scope=None):
d = globals() if not scope else vars(scope); return [k for k in d if d[k] == v]
...
>>> d1 = {'a': 'ape'}; d2 = {'b': 'bear'}; d3 = {'c': 'cat'}
>>> ld = [d1, d2, d3]
>>> [varname(d) for d in ld]
[['d1'], ['d2'], ['d3']]
>>> d5 = d3
>>> [varname(d) for d in ld]
[['d1'], ['d2'], ['d3', 'd5']]
>>> def varname(v, scope=None):
d = globals() if not scope else vars(scope); return [k for k in d if d[k] is v]
...
>>> [varname(d) for d in ld]
[['d1'], ['d2'], ['d3', 'd5']]
As you see and is noted here, there can be multiple variables with the same value or even address, so using a wrapper to keep the names with the data is best.
Following method will not return the name of variable but using this method you can create data frame easily if variable is available in global scope.
class CustomDict(dict):
def __add__(self, other):
return CustomDict({**self, **other})
class GlobalBase(type):
def __getattr__(cls, key):
return CustomDict({key: globals()[key]})
def __getitem__(cls, keys):
return CustomDict({key: globals()[key] for key in keys})
class G(metaclass=GlobalBase):
pass
x, y, z = 0, 1, 2
print('method 1:', G['x', 'y', 'z']) # Outcome: method 1: {'x': 0, 'y': 1, 'z': 2}
print('method 2:', G.x + G.y + G.z) # Outcome: method 2: {'x': 0, 'y': 1, 'z': 2}
A = [0, 1]
B = [1, 2]
pd.DataFrame(G.A + G.B) # It will return a data frame with A and B columns
Some of the previous cases would fail if there are two variables with the same value. So it is convenient to alert it:
Defining function:
# Variable to string of variable name
def var_name(variable,i=0):
results = []
for name in globals():
if eval(name) == variable:
results.append(name)
if len(results) > 1:
print('Warning:' )
print(' var_name() has found',len(results), 'possible outcomes.')
print(' Please choose the suitable parameter "i". Where "i" is the index')
print(' that matches your choice from the list below.')
print(' ',results) ; print('')
return results[i]
Use:
var_1 = 10
var_name(var_1) # Output will be "var_1"
If you have 2 variables with the same value like var_1 = 8 and var_2 = 8, then a warning will appear.
var_1 = 8
var_2 = 8
var_name(var_2) # Output will be "var_1" too but Warning will appear
You can get your variable as kwargs and return it as string:
var=2
def getVarName(**kwargs):
return list(kwargs.keys())[0]
print (getVarName(var = var))
Note: variable name must be equal to itself.
I try to get name from inspect locals, but it cann't process var likes a[1], b.val.
After it, I got a new idea --- get var name from the code, and I try it succ!
code like below:
#direct get from called function code
def retrieve_name_ex(var):
stacks = inspect.stack()
try:
func = stacks[0].function
code = stacks[1].code_context[0]
s = code.index(func)
s = code.index("(", s + len(func)) + 1
e = code.index(")", s)
return code[s:e].strip()
except:
return ""
You can try the following to retrieve the name of a function you defined (does not work for built-in functions though):
import re
def retrieve_name(func):
return re.match("<function\s+(\w+)\s+at.*", str(func)).group(1)
def foo(x):
return x**2
print(retrieve_name(foo))
# foo
When finding the name of a variable from its value,
you may have several variables equal to the same value,
for example var1 = 'hello' and var2 = 'hello'.
My solution:
def find_var_name(val):
dict_list = []
global_dict = dict(globals())
for k, v in global_dict.items():
dict_list.append([k, v])
return [item[0] for item in dict_list if item[1] == val]
var1 = 'hello'
var2 = 'hello'
find_var_name('hello')
Outputs
['var1', 'var2']
Compressed version of iDilip's answer:
import inspect
def varname(x):
return [k for k,v in inspect.currentframe().f_back.f_locals.items() if v is x][0]
hi = 123
print(varname(hi))
It's totally possible to get the name of an instance variable, so long as it is the property of a class.
I got this from Effective Python by Brett Slatkin. Hope it helps someone:
The class must implement the get, set, and set_name dunder methods, which are part of the "Descriptor Protocol"
This worked when I ran it:
class FieldThatKnowsItsName():
def __init__(self):
self.name = None
self._value= None
self.owner = None
def __set_name__(self, owner, name):
self.name = name
self.owner = owner
self.owner.fields[self.name] = self
def __get__(self, instance, instance_type):
return self
def __set__(self, instance, value):
self = value
class SuperTable:
fields = {}
field_1=FieldThatKnowsItsName()
field_2=FieldThatKnowsItsName()
table = SuperTable()
print(table.field_1.name)
print(table.field_2.name)
You can then add methods and or extend your datatype as you like.
As a bonus, the set_name(self, owner, name) dunder also passes the parent instance, so the Field class instance can register itself with the parent.
I got this from Effective Python by Brett Slatkin. It took a while to figure out how to implement.
How can I do the same for a variable? As opposed to functions, Python variables do not have the __name__ attribute.
The problem comes up because you are confused about terminology, semantics or both.
"variables" don't belong in the same category as "functions". A "variable" is not a thing that takes up space in memory while the code is running. It is just a name that exists in your source code - so that when you're writing the code, you can explain which thing you're talking about. Python uses names in the source code to refer to (i.e., give a name to) values. (In many languages, a variable is more like a name for a specific location in memory where the value will be stored. But Python's names actually name the thing in question.)
In Python, a function is a value. (In some languages, this is not the case; although there are bytes of memory used to represent the actual executable code, it isn't a discrete chunk of memory that your program logic gets to interact with directly.) In Python, every value is an object, meaning that you can assign names to it freely, pass it as an argument, return it from a function, etc. (In many languages, this is not the case.) Objects in Python have attributes, which are the things you access using the . syntax. Functions in Python have a __name__ attribute, which is assigned when the function is created. Specifically, when a def statement is executed (in most languages, creation of a function works quite differently), the name that appears after def is used as a value for the __name__ attribute, and also, independently, as a variable name that will get the function object assigned to it.
But most objects don't have an attribute like that.
In other words, if I have a variable such as:
That's the thing: you don't "have" the variable in the sense that you're thinking of. You have the object that is named by that variable. Anything else depends on the information incidentally being stored in some other object - such as the locals() of the enclosing function. But it would be better to store the information yourself. Instead of relying on a variable name to carry information for you, explicitly build the mapping between the string name you want to use for the object, and the object itself.

Can I implement a function or better a decorator that makes func(a1)(a2)(a3)...(an) == func(a1, a2, a3,...,an)? [duplicate]

On Codewars.com I encountered the following task:
Create a function add that adds numbers together when called in succession. So add(1) should return 1, add(1)(2) should return 1+2, ...
While I'm familiar with the basics of Python, I've never encountered a function that is able to be called in such succession, i.e. a function f(x) that can be called as f(x)(y)(z).... Thus far, I'm not even sure how to interpret this notation.
As a mathematician, I'd suspect that f(x)(y) is a function that assigns to every x a function g_{x} and then returns g_{x}(y) and likewise for f(x)(y)(z).
Should this interpretation be correct, Python would allow me to dynamically create functions which seems very interesting to me. I've searched the web for the past hour, but wasn't able to find a lead in the right direction. Since I don't know how this programming concept is called, however, this may not be too surprising.
How do you call this concept and where can I read more about it?
I don't know whether this is function chaining as much as it's callable chaining, but, since functions are callables I guess there's no harm done. Either way, there's two ways I can think of doing this:
Sub-classing int and defining __call__:
The first way would be with a custom int subclass that defines __call__ which returns a new instance of itself with the updated value:
class CustomInt(int):
def __call__(self, v):
return CustomInt(self + v)
Function add can now be defined to return a CustomInt instance, which, as a callable that returns an updated value of itself, can be called in succession:
>>> def add(v):
... return CustomInt(v)
>>> add(1)
1
>>> add(1)(2)
3
>>> add(1)(2)(3)(44) # and so on..
50
In addition, as an int subclass, the returned value retains the __repr__ and __str__ behavior of ints. For more complex operations though, you should define other dunders appropriately.
As #Caridorc noted in a comment, add could also be simply written as:
add = CustomInt
Renaming the class to add instead of CustomInt also works similarly.
Define a closure, requires extra call to yield value:
The only other way I can think of involves a nested function that requires an extra empty argument call in order to return the result. I'm not using nonlocal and opt for attaching attributes to the function objects to make it portable between Pythons:
def add(v):
def _inner_adder(val=None):
"""
if val is None we return _inner_adder.v
else we increment and return ourselves
"""
if val is None:
return _inner_adder.v
_inner_adder.v += val
return _inner_adder
_inner_adder.v = v # save value
return _inner_adder
This continuously returns itself (_inner_adder) which, if a val is supplied, increments it (_inner_adder += val) and if not, returns the value as it is. Like I mentioned, it requires an extra () call in order to return the incremented value:
>>> add(1)(2)()
3
>>> add(1)(2)(3)() # and so on..
6
You can hate me, but here is a one-liner :)
add = lambda v: type("", (int,), {"__call__": lambda self, v: self.__class__(self + v)})(v)
Edit: Ok, how this works? The code is identical to answer of #Jim, but everything happens on a single line.
type can be used to construct new types: type(name, bases, dict) -> a new type. For name we provide empty string, as name is not really needed in this case. For bases (tuple) we provide an (int,), which is identical to inheriting int. dict are the class attributes, where we attach the __call__ lambda.
self.__class__(self + v) is identical to return CustomInt(self + v)
The new type is constructed and returned within the outer lambda.
If you want to define a function to be called multiple times, first you need to return a callable object each time (for example a function) otherwise you have to create your own object by defining a __call__ attribute, in order for it to be callable.
The next point is that you need to preserve all the arguments, which in this case means you might want to use Coroutines or a recursive function. But note that Coroutines are much more optimized/flexible than recursive functions, specially for such tasks.
Here is a sample function using Coroutines, that preserves the latest state of itself. Note that it can't be called multiple times since the return value is an integer which is not callable, but you might think about turning this into your expected object ;-).
def add():
current = yield
while True:
value = yield current
current = value + current
it = add()
next(it)
print(it.send(10))
print(it.send(2))
print(it.send(4))
10
12
16
Simply:
class add(int):
def __call__(self, n):
return add(self + n)
If you are willing to accept an additional () in order to retrieve the result you can use functools.partial:
from functools import partial
def add(*args, result=0):
return partial(add, result=sum(args)+result) if args else result
For example:
>>> add(1)
functools.partial(<function add at 0x7ffbcf3ff430>, result=1)
>>> add(1)(2)
functools.partial(<function add at 0x7ffbcf3ff430>, result=3)
>>> add(1)(2)()
3
This also allows specifying multiple numbers at once:
>>> add(1, 2, 3)(4, 5)(6)()
21
If you want to restrict it to a single number you can do the following:
def add(x=None, *, result=0):
return partial(add, result=x+result) if x is not None else result
If you want add(x)(y)(z) to readily return the result and be further callable then sub-classing int is the way to go.
The pythonic way to do this would be to use dynamic arguments:
def add(*args):
return sum(args)
This is not the answer you're looking for, and you may know this, but I thought I would give it anyway because if someone was wondering about doing this not out of curiosity but for work. They should probably have the "right thing to do" answer.

Getting the name of a variable as a string

I already read How to get a function name as a string?.
How can I do the same for a variable? As opposed to functions, Python variables do not have the __name__ attribute.
In other words, if I have a variable such as:
foo = dict()
foo['bar'] = 2
I am looking for a function/attribute, e.g. retrieve_name() in order to create a DataFrame in Pandas from this list, where the column names are given by the names of the actual dictionaries:
# List of dictionaries for my DataFrame
list_of_dicts = [n_jobs, users, queues, priorities]
columns = [retrieve_name(d) for d in list_of_dicts]
With Python 3.8 one can simply use f-string debugging feature:
>>> foo = dict()
>>> f'{foo=}'.split('=')[0]
'foo'
One drawback of this method is that in order to get 'foo' printed you have to add f'{foo=}' yourself. In other words, you already have to know the name of the variable. In other words, the above code snippet is exactly the same as just
>>> 'foo'
Even if variable values don't point back to the name, you have access to the list of every assigned variable and its value, so I'm astounded that only one person suggested looping through there to look for your var name.
Someone mentioned on that answer that you might have to walk the stack and check everyone's locals and globals to find foo, but if foo is assigned in the scope where you're calling this retrieve_name function, you can use inspect's current frame to get you all of those local variables.
My explanation might be a little bit too wordy (maybe I should've used a "foo" less words), but here's how it would look in code (Note that if there is more than one variable assigned to the same value, you will get both of those variable names):
import inspect
x, y, z = 1, 2, 3
def retrieve_name(var):
callers_local_vars = inspect.currentframe().f_back.f_locals.items()
return [var_name for var_name, var_val in callers_local_vars if var_val is var]
print(retrieve_name(y))
If you're calling this function from another function, something like:
def foo(bar):
return retrieve_name(bar)
foo(baz)
And you want the baz instead of bar, you'll just need to go back a scope further. This can be done by adding an extra .f_back in the caller_local_vars initialization.
See an example here: ideone
The only objects in Python that have canonical names are modules, functions, and classes, and of course there is no guarantee that this canonical name has any meaning in any namespace after the function or class has been defined or the module imported. These names can also be modified after the objects are created so they may not always be particularly trustworthy.
What you want to do is not possible without recursively walking the tree of named objects; a name is a one-way reference to an object. A common or garden-variety Python object contains no references to its names. Imagine if every integer, every dict, every list, every Boolean needed to maintain a list of strings that represented names that referred to it! It would be an implementation nightmare, with little benefit to the programmer.
TL;DR
Use the Wrapper helper from python-varname:
from varname.helpers import Wrapper
foo = Wrapper(dict())
# foo.name == 'foo'
# foo.value == {}
foo.value['bar'] = 2
For list comprehension part, you can do:
n_jobs = Wrapper(<original_value>)
users = Wrapper(<original_value>)
queues = Wrapper(<original_value>)
priorities = Wrapper(<original_value>)
list_of_dicts = [n_jobs, users, queues, priorities]
columns = [d.name for d in list_of_dicts]
# ['n_jobs', 'users', 'queues', 'priorities']
# REMEMBER that you have to access the <original_value> by d.value
I am the author of the python-varname package. Please let me know if you have any questions or you can submit issues on Github.
The long answer
Is it even possible?
Yes and No.
We are retrieving the variable names at runtime, so we need a function to be called to enable us to access the previous frames to retrieve the variable names. That's why we need a Wrapper there. In that function, at runtime, we are parsing the source code/AST nodes in the previous frames to get the exact variable name.
However, the source code/AST nodes in the previous frames are not always available, or they could be modified by other environments (e.g: pytest's assert statement). One simple example is that the codes run via exec(). Even though we are still able to retrieve some information from the bytecode, it needs too much effort and it is also error-prone.
How to do it?
First of all, we need to identify which frame the variable is given. It's not always simply the direct previous frame. For example, we may have another wrapper for the function:
from varname import varname
def func():
return varname()
def wrapped():
return func()
x = wrapped()
In the above example, we have to skip the frame inside wrapped to get to the right frame x = wrapped() so that we are able to locate x. The arguments frame and ignore of varname allow us to skip some of these intermediate frames. See more details in the README file and the API docs of the package.
Then we need to parse the AST node to locate where the variable is assigned value (function call) to. It's not always just a simple assignment. Sometimes there could be complex AST nodes, for example, x = [wrapped()]. We need to identify the correct assignment by traversing the AST tree.
How reliable is it?
Once we identify the assignment node, it is reliable.
varname is all depending on executing package to look for the node. The node executing detects is ensured to be the correct one (see also this).
It partially works with environments where other AST magics apply, including pytest, ipython, macropy, birdseye, reticulate with R, etc. Neither executing nor varname is 100% working with those environments.
Do we need a package to do it?
Well, yes and no, again.
If your scenario is simple, the code provided by #juan Isaza or #scohe001 probably is enough for you to work with the case where a variable is defined at the direct previous frame and the AST node is a simple assignment. You just need to go one frame back and retrieve the information there.
However, if the scenario becomes complicated, or we need to adopt different application scenarios, you probably need a package like python-varname, to handle them. These scenarios may include to:
present more friendly messages when the source code is not available or AST nodes are not accessible
skip intermediate frames (allows the function to be wrapped or called in other intermediate frames)
automatically ignores calls from built-in functions or libraries. For example: x = str(func())
retrieve multiple variable names on the left-hand side of the assignment
etc.
How about the f-string?
Like the answer provided by #Aivar Paalberg. It's definitely fast and reliable. However, it's not at runtime, meaning that you have to know it's foo before you print the name out. But with varname, you don't have to know that variable is coming:
from varname import varname
def func():
return varname()
# In external uses
x = func() # 'x'
y = func() # 'y'
Finally
python-varname is not only able to detect the variable name from an assignment, but also:
Retrieve variable names directly, using nameof
Detect next immediate attribute name, using will
Fetch argument names/sources passed to a function using argname
Read more from its documentation.
However, the final word I want to say is that, try to avoid using it whenever you can.
Because you can't make sure that the client code will run in an environment where the source node is available or AST node is accessible. And of course, it costs resources to parse the source code, identify the environment, retrieve the AST nodes and evaluate them when needed.
On python3, this function will get the outer most name in the stack:
import inspect
def retrieve_name(var):
"""
Gets the name of var. Does it from the out most frame inner-wards.
:param var: variable to get name from.
:return: string
"""
for fi in reversed(inspect.stack()):
names = [var_name for var_name, var_val in fi.frame.f_locals.items() if var_val is var]
if len(names) > 0:
return names[0]
It is useful anywhere on the code. Traverses the reversed stack looking for the first match.
I don't believe this is possible. Consider the following example:
>>> a = []
>>> b = a
>>> id(a)
140031712435664
>>> id(b)
140031712435664
The a and b point to the same object, but the object can't know what variables point to it.
def name(**variables):
return [x for x in variables]
It's used like this:
name(variable=variable)
>> my_var = 5
>> my_var_name = [ k for k,v in locals().items() if v == my_var][0]
>> my_var_name
'my_var'
In case you get an error if myvar points to another variable, try this (suggested by #mherzog)-
>> my_var = 5
>> my_var_name = [ k for k,v in locals().items() if v is my_var][0]
>> my_var_name
'my_var'
locals() - Return a dictionary containing the current scope's local variables.
by iterating through this dictionary we can check the key which has a value equal to the defined variable, just extracting the key will give us the text of variable in string format.
from (after a bit changes)
https://www.tutorialspoint.com/How-to-get-a-variable-name-as-a-string-in-Python
I wrote the package sorcery to do this kind of magic robustly. You can write:
from sorcery import dict_of
columns = dict_of(n_jobs, users, queues, priorities)
and pass that to the dataframe constructor. It's equivalent to:
columns = dict(n_jobs=n_jobs, users=users, queues=queues, priorities=priorities)
Here's one approach. I wouldn't recommend this for anything important, because it'll be quite brittle. But it can be done.
Create a function that uses the inspect module to find the source code that called it. Then you can parse the source code to identify the variable names that you want to retrieve. For example, here's a function called autodict that takes a list of variables and returns a dictionary mapping variable names to their values. E.g.:
x = 'foo'
y = 'bar'
d = autodict(x, y)
print d
Would give:
{'x': 'foo', 'y': 'bar'}
Inspecting the source code itself is better than searching through the locals() or globals() because the latter approach doesn't tell you which of the variables are the ones you want.
At any rate, here's the code:
def autodict(*args):
get_rid_of = ['autodict(', ',', ')', '\n']
calling_code = inspect.getouterframes(inspect.currentframe())[1][4][0]
calling_code = calling_code[calling_code.index('autodict'):]
for garbage in get_rid_of:
calling_code = calling_code.replace(garbage, '')
var_names, var_values = calling_code.split(), args
dyn_dict = {var_name: var_value for var_name, var_value in
zip(var_names, var_values)}
return dyn_dict
The action happens in the line with inspect.getouterframes, which returns the string within the code that called autodict.
The obvious downside to this sort of magic is that it makes assumptions about how the source code is structured. And of course, it won't work at all if it's run inside the interpreter.
This function will print variable name with its value:
import inspect
def print_this(var):
callers_local_vars = inspect.currentframe().f_back.f_locals.items()
print(str([k for k, v in callers_local_vars if v is var][0])+': '+str(var))
***Input & Function call:***
my_var = 10
print_this(my_var)
***Output**:*
my_var: 10
>>> locals()['foo']
{}
>>> globals()['foo']
{}
If you wanted to write your own function, it could be done such that you could check for a variable defined in locals then check globals. If nothing is found you could compare on id() to see if the variable points to the same location in memory.
If your variable is in a class, you could use className.dict.keys() or vars(self) to see if your variable has been defined.
I have a method, and while not the most efficient...it works! (and it doesn't involve any fancy modules).
Basically it compares your Variable's ID to globals() Variables' IDs, then returns the match's name.
def getVariableName(variable, globalVariables=globals().copy()):
""" Get Variable Name as String by comparing its ID to globals() Variables' IDs
args:
variable(var): Variable to find name for (Obviously this variable has to exist)
kwargs:
globalVariables(dict): Copy of the globals() dict (Adding to Kwargs allows this function to work properly when imported from another .py)
"""
for globalVariable in globalVariables:
if id(variable) == id(globalVariables[globalVariable]): # If our Variable's ID matches this Global Variable's ID...
return globalVariable # Return its name from the Globals() dict
In Python, the def and class keywords will bind a specific name to the object they define (function or class). Similarly, modules are given a name by virtue of being called something specific in the filesystem. In all three cases, there's an obvious way to assign a "canonical" name to the object in question.
However, for other kinds of objects, such a canonical name may simply not exist. For example, consider the elements of a list. The elements in the list are not individually named, and it is entirely possible that the only way to refer to them in a program is by using list indices on the containing list. If such a list of objects was passed into your function, you could not possibly assign meaningful identifiers to the values.
Python doesn't save the name on the left hand side of an assignment into the assigned object because:
It would require figuring out which name was "canonical" among multiple conflicting objects,
It would make no sense for objects which are never assigned to an explicit variable name,
It would be extremely inefficient,
Literally no other language in existence does that.
So, for example, functions defined using lambda will always have the "name" <lambda>, rather than a specific function name.
The best approach would be simply to ask the caller to pass in an (optional) list of names. If typing the '...','...' is too cumbersome, you could accept e.g. a single string containing a comma-separated list of names (like namedtuple does).
I think it's so difficult to do this in Python because of the simple fact that you never will not know the name of the variable you're using. So, in his example, you could do:
Instead of:
list_of_dicts = [n_jobs, users, queues, priorities]
dict_of_dicts = {"n_jobs" : n_jobs, "users" : users, "queues" : queues, "priorities" : priorities}
Many of the answers return just one variable name. But that won't work well if more than one variable have the same value. Here's a variation of Amr Sharaki's answer which returns multiple results if more variables have the same value.
def getVariableNames(variable):
results = []
globalVariables=globals().copy()
for globalVariable in globalVariables:
if id(variable) == id(globalVariables[globalVariable]):
results.append(globalVariable)
return results
a = 1
b = 1
getVariableNames(a)
# ['a', 'b']
just another way to do this based on the content of input variable:
(it returns the name of the first variable that matches to the input variable, otherwise None. One can modify it to get all variable names which are having the same content as input variable)
def retrieve_name(x, Vars=vars()):
for k in Vars:
if isinstance(x, type(Vars[k])):
if x is Vars[k]:
return k
return None
If the goal is to help you keep track of your variables, you can write a simple function that labels the variable and returns its value and type. For example, suppose i_f=3.01 and you round it to an integer called i_n to use in a code, and then need a string i_s that will go into a report.
def whatis(string, x):
print(string+' value=',repr(x),type(x))
return string+' value='+repr(x)+repr(type(x))
i_f=3.01
i_n=int(i_f)
i_s=str(i_n)
i_l=[i_f, i_n, i_s]
i_u=(i_f, i_n, i_s)
## make report that identifies all types
report='\n'+20*'#'+'\nThis is the report:\n'
report+= whatis('i_f ',i_f)+'\n'
report+=whatis('i_n ',i_n)+'\n'
report+=whatis('i_s ',i_s)+'\n'
report+=whatis('i_l ',i_l)+'\n'
report+=whatis('i_u ',i_u)+'\n'
print(report)
This prints to the window at each call for debugging purposes and also yields a string for the written report. The only downside is that you have to type the variable twice each time you call the function.
I am a Python newbie and found this very useful way to log my efforts as I program and try to cope with all the objects in Python. One flaw is that whatis() fails if it calls a function described outside the procedure where it is used. For example, int(i_f) was a valid function call only because the int function is known to Python. You could call whatis() using int(i_f**2), but if for some strange reason you choose to define a function called int_squared it must be declared inside the procedure where whatis() is used.
Maybe this could be useful:
def Retriever(bar):
return (list(globals().keys()))[list(map(lambda x: id(x), list(globals().values()))).index(id(bar))]
The function goes through the list of IDs of values from the global scope (the namespace could be edited), finds the index of the wanted/required var or function based on its ID, and then returns the name from the list of global names based on the acquired index.
Whenever I have to do it, mostly while communicating json schema and constants with the frontend I define a class as follows
class Param:
def __init__(self, name, value):
self.name = name
self.value = value
Then define the variable with name and value.
frame_folder_count = Param({'name':'frame_folder_count', 'value':10})
Now you can access the name and value using the object.
>>> frame_folder_count.name
'frame_folder_count'
>>> def varname(v, scope=None):
d = globals() if not scope else vars(scope); return [k for k in d if d[k] == v]
...
>>> d1 = {'a': 'ape'}; d2 = {'b': 'bear'}; d3 = {'c': 'cat'}
>>> ld = [d1, d2, d3]
>>> [varname(d) for d in ld]
[['d1'], ['d2'], ['d3']]
>>> d5 = d3
>>> [varname(d) for d in ld]
[['d1'], ['d2'], ['d3', 'd5']]
>>> def varname(v, scope=None):
d = globals() if not scope else vars(scope); return [k for k in d if d[k] is v]
...
>>> [varname(d) for d in ld]
[['d1'], ['d2'], ['d3', 'd5']]
As you see and is noted here, there can be multiple variables with the same value or even address, so using a wrapper to keep the names with the data is best.
Following method will not return the name of variable but using this method you can create data frame easily if variable is available in global scope.
class CustomDict(dict):
def __add__(self, other):
return CustomDict({**self, **other})
class GlobalBase(type):
def __getattr__(cls, key):
return CustomDict({key: globals()[key]})
def __getitem__(cls, keys):
return CustomDict({key: globals()[key] for key in keys})
class G(metaclass=GlobalBase):
pass
x, y, z = 0, 1, 2
print('method 1:', G['x', 'y', 'z']) # Outcome: method 1: {'x': 0, 'y': 1, 'z': 2}
print('method 2:', G.x + G.y + G.z) # Outcome: method 2: {'x': 0, 'y': 1, 'z': 2}
A = [0, 1]
B = [1, 2]
pd.DataFrame(G.A + G.B) # It will return a data frame with A and B columns
Some of the previous cases would fail if there are two variables with the same value. So it is convenient to alert it:
Defining function:
# Variable to string of variable name
def var_name(variable,i=0):
results = []
for name in globals():
if eval(name) == variable:
results.append(name)
if len(results) > 1:
print('Warning:' )
print(' var_name() has found',len(results), 'possible outcomes.')
print(' Please choose the suitable parameter "i". Where "i" is the index')
print(' that matches your choice from the list below.')
print(' ',results) ; print('')
return results[i]
Use:
var_1 = 10
var_name(var_1) # Output will be "var_1"
If you have 2 variables with the same value like var_1 = 8 and var_2 = 8, then a warning will appear.
var_1 = 8
var_2 = 8
var_name(var_2) # Output will be "var_1" too but Warning will appear
You can get your variable as kwargs and return it as string:
var=2
def getVarName(**kwargs):
return list(kwargs.keys())[0]
print (getVarName(var = var))
Note: variable name must be equal to itself.
I try to get name from inspect locals, but it cann't process var likes a[1], b.val.
After it, I got a new idea --- get var name from the code, and I try it succ!
code like below:
#direct get from called function code
def retrieve_name_ex(var):
stacks = inspect.stack()
try:
func = stacks[0].function
code = stacks[1].code_context[0]
s = code.index(func)
s = code.index("(", s + len(func)) + 1
e = code.index(")", s)
return code[s:e].strip()
except:
return ""
You can try the following to retrieve the name of a function you defined (does not work for built-in functions though):
import re
def retrieve_name(func):
return re.match("<function\s+(\w+)\s+at.*", str(func)).group(1)
def foo(x):
return x**2
print(retrieve_name(foo))
# foo
When finding the name of a variable from its value,
you may have several variables equal to the same value,
for example var1 = 'hello' and var2 = 'hello'.
My solution:
def find_var_name(val):
dict_list = []
global_dict = dict(globals())
for k, v in global_dict.items():
dict_list.append([k, v])
return [item[0] for item in dict_list if item[1] == val]
var1 = 'hello'
var2 = 'hello'
find_var_name('hello')
Outputs
['var1', 'var2']
Compressed version of iDilip's answer:
import inspect
def varname(x):
return [k for k,v in inspect.currentframe().f_back.f_locals.items() if v is x][0]
hi = 123
print(varname(hi))
It's totally possible to get the name of an instance variable, so long as it is the property of a class.
I got this from Effective Python by Brett Slatkin. Hope it helps someone:
The class must implement the get, set, and set_name dunder methods, which are part of the "Descriptor Protocol"
This worked when I ran it:
class FieldThatKnowsItsName():
def __init__(self):
self.name = None
self._value= None
self.owner = None
def __set_name__(self, owner, name):
self.name = name
self.owner = owner
self.owner.fields[self.name] = self
def __get__(self, instance, instance_type):
return self
def __set__(self, instance, value):
self = value
class SuperTable:
fields = {}
field_1=FieldThatKnowsItsName()
field_2=FieldThatKnowsItsName()
table = SuperTable()
print(table.field_1.name)
print(table.field_2.name)
You can then add methods and or extend your datatype as you like.
As a bonus, the set_name(self, owner, name) dunder also passes the parent instance, so the Field class instance can register itself with the parent.
I got this from Effective Python by Brett Slatkin. It took a while to figure out how to implement.
How can I do the same for a variable? As opposed to functions, Python variables do not have the __name__ attribute.
The problem comes up because you are confused about terminology, semantics or both.
"variables" don't belong in the same category as "functions". A "variable" is not a thing that takes up space in memory while the code is running. It is just a name that exists in your source code - so that when you're writing the code, you can explain which thing you're talking about. Python uses names in the source code to refer to (i.e., give a name to) values. (In many languages, a variable is more like a name for a specific location in memory where the value will be stored. But Python's names actually name the thing in question.)
In Python, a function is a value. (In some languages, this is not the case; although there are bytes of memory used to represent the actual executable code, it isn't a discrete chunk of memory that your program logic gets to interact with directly.) In Python, every value is an object, meaning that you can assign names to it freely, pass it as an argument, return it from a function, etc. (In many languages, this is not the case.) Objects in Python have attributes, which are the things you access using the . syntax. Functions in Python have a __name__ attribute, which is assigned when the function is created. Specifically, when a def statement is executed (in most languages, creation of a function works quite differently), the name that appears after def is used as a value for the __name__ attribute, and also, independently, as a variable name that will get the function object assigned to it.
But most objects don't have an attribute like that.
In other words, if I have a variable such as:
That's the thing: you don't "have" the variable in the sense that you're thinking of. You have the object that is named by that variable. Anything else depends on the information incidentally being stored in some other object - such as the locals() of the enclosing function. But it would be better to store the information yourself. Instead of relying on a variable name to carry information for you, explicitly build the mapping between the string name you want to use for the object, and the object itself.

Python: Best way to deal with functions with long list of arguments?

I've found various detailed explanations on how to pass long lists of arguments into a function, but I still kinda doubt if that's proper way to do it.
In other words, I suspect that I'm doing it wrong, but I can't see how to do it right.
The problem: I have (not very long) recurrent function, which uses quite a number of variables and needs to modify some content in at least some of them.
What I end up with is sth like this:
def myFunction(alpha, beta, gamma, zeta, alphaList, betaList, gammaList, zetaList):
<some operations>
myFunction(alpha, beta, modGamma, zeta, modAlphaList, betaList, gammaList, modZetaList)
...and I want to see the changes I did on original variables (in C I would just pass a reference, but I hear that in Python it's always a copy?).
Sorry if noob, I don't know how to phrase this question so I can find relevant answers.
You could wrap up all your parameters in a class, like this:
class FooParameters:
alpha = 1.0
beta = 1.0
gamma = 1.0
zeta = 1.0
alphaList = []
betaList = []
gammaList = []
zetaList = []
and then your function takes a single parameter instance:
def myFunction(params):
omega = params.alpha * params.beta + exp(params.gamma)
# more magic...
calling like:
testParams = FooParameters()
testParams.gamma = 2.3
myFunction(testParams)
print params.zetaList
Because the params instance is passed by reference, changes in the function are preserved.
This is commonly used in matplotlib, for example. They pass the long list of arguments using * or **, like:
def function(*args, **kwargs):
do something
Calling function:
function(1,2,3,4,5, a=1, b=2, b=3)
Here 1,2,3,4,5 will go to args and a=1, b=2, c=3 will go to kwargs, as a dictionary. So that they arrive at your function like:
args = [1,2,3,4,5]
kwargs = {a:1, b:2, c:3}
And you can treat them in the way you want.
I don't know where you got the idea that Python copies values when passing into a function. That is not at all true.
On the contrary: each parameter in a function is an additional name referring to the original object. If you change the value of that object in some way - for example, if it's a list and you change one of its members - then the original will also see that change. But if you rebind the name to something else - say by doing alpha = my_completely_new_value - then the original remains unchanged.
You may be tempted to something akin to this:
def myFunction(*args):
var_names = ['alpha','beta','gamma','zeta']
locals().update(zip(var_names,args))
myFunction(alpha,beta,gamma,zeta)
However, this 'often' won't work. I suggest introducing another namespace:
from collections import OrderedDict
def myFunction(*args):
var_names = ['alpha','beta','gamma','zeta']
vars = OrderedDict(zip(var_names,args))
#get them all via vars[var_name]
myFunction(*vars.values()) #since we used an orderedDict we can simply do *.values()
you can capture the non-modfied values in a closure:
def myFunction(alpha, beta, gamma, zeta, alphaList, betaList, gammaList, zetaList):
def myInner(g=gamma, al, zl):
<some operations>
myInner(modGamma, modAlphaList, modZetaList)
myInner(al=alphaList, zl=zetaList)
(BTW, this is about the only way to write a truly recursive function in Python.)
You could pass in a dictionary and return a new dictionary. Or put your method in a class and have alpha, beta etc. be attributes.
You should put myFunction in a class. Set up the class with the appropriate attributes and call the appropriate functions. The state is then well contained in the class.

Set function signature in Python

Suppose I have a generic function f. I want to programmatically create a function f2 that behaves the same as f, but has a customized signature.
More detail
Given a list l and and dictionary d I want to be able to:
Set the non-keyword arguments of f2 to the strings in l
Set the keyword arguments of f2 to the keys in d and the default values to the values of d
ie. Suppose we have
l = ["x", "y"]
d = {"opt": None}
def f(*args, **kwargs):
# My code
Then I would want a function with signature:
def f2(x, y, opt=None):
# My code
A specific use case
This is just a simplified version of my specific use case. I am giving this as an example only.
My actual use case (simplified) is as follows. We have a generic initiation function:
def generic_init(self, *args, **kwargs):
"""Function to initiate a generic object"""
for name, arg in zip(self.__init_args__, args):
setattr(self, name, arg)
for name, default in self.__init_kw_args__.items():
if name in kwargs:
setattr(self, name, kwargs[name])
else:
setattr(self, name, default)
We want to use this function in a number of classes. In particular, we want to create a function __init__ that behaves like generic_init, but has the signature defined by some class variables at creation time:
class my_class:
__init_args__ = ["x", "y"]
__kw_init_args__ = {"my_opt": None}
__init__ = create_initiation_function(my_class, generic_init)
setattr(myclass, "__init__", __init__)
We want create_initiation_function to create a new function with the signature defined using __init_args__ and __kw_init_args__. Is it possible to write create_initiation_function?
Please note:
If I just wanted to improve the help, I could set __doc__.
We want to set the function signature on creation. After that, it doesn't need to be changed.
Instead of creating a function like generic_init, but with a different signature we could create a new function with the desired signature that just calls generic_init
We want to define create_initiation_function. We don't want to manually specify the new function!
Related
Preserving signatures of decorated functions: This is how to preserve a signature when decorating a function. We need to be able to set the signature to an arbitrary value
From PEP-0362, there actually does appear to be a way to set the signature in py3.3+, using the fn.__signature__ attribute:
from inspect import signature
from functools import wraps
def shared_vars(*shared_args):
"""Decorator factory that defines shared variables that are
passed to every invocation of the function"""
def decorator(f):
#wraps(f)
def wrapper(*args, **kwargs):
full_args = shared_args + args
return f(*full_args, **kwargs)
# Override signature
sig = signature(f)
sig = sig.replace(parameters=tuple(sig.parameters.values())[1:])
wrapper.__signature__ = sig
return wrapper
return decorator
Then:
>>> #shared_vars({"myvar": "myval"})
>>> def example(_state, a, b, c):
>>> return _state, a, b, c
>>> example(1,2,3)
({'myvar': 'myval'}, 1, 2, 3)
>>> str(signature(example))
'(a, b, c)'
Note: the PEP is not exactly right; Signature.replace moved the params from a positional arg to a kw-only arg.
For your usecase, having a docstring in the class/function should work -- that will show up in help() okay, and can be set programmatically (func.__doc__ = "stuff").
I can't see any way of setting the actual signature. I would have thought the functools module would have done it if it was doable, but it doesn't, at least in py2.5 and py2.6.
You can also raise a TypeError exception if you get bad input.
Hmm, if you don't mind being truly vile, you can use compile()/eval() to do it. If your desired signature is specified by arglist=["foo","bar","baz"], and your actual function is f(*args, **kwargs), you can manage:
argstr = ", ".join(arglist)
fakefunc = "def func(%s):\n return real_func(%s)\n" % (argstr, argstr)
fakefunc_code = compile(fakefunc, "fakesource", "exec")
fakeglobals = {}
eval(fakefunc_code, {"real_func": f}, fakeglobals)
f_with_good_sig = fakeglobals["func"]
help(f) # f(*args, **kwargs)
help(f_with_good_sig) # func(foo, bar, baz)
Changing the docstring and func_name should get you a complete solution. But, uh, eww...
I wrote a package named forge that solves this exact problem for Python 3.5+:
With your current code looking like this:
l=["x", "y"]
d={"opt":None}
def f(*args, **kwargs):
#My code
And your desired code looking like this:
def f2(x, y, opt=None):
#My code
Here is how you would solve that using forge:
f2 = forge.sign(
forge.arg('x'),
forge.arg('y'),
forge.arg('opt', default=None),
)(f)
As forge.sign is a wrapper, you could also use it directly:
#forge.sign(
forge.arg('x'),
forge.arg('y'),
forge.arg('opt', default=None),
)
def func(*args, **kwargs):
# signature becomes: func(x, y, opt=None)
return (args, kwargs)
assert func(1, 2) == ((), {'x': 1, 'y': 2, 'opt': None})
Have a look at makefun, it was made for that (exposing variants of functions with more or less parameters and accurate signature), and works in python 2 and 3.
Your example would be written like this:
try: # python 3.3+
from inspect import signature, Signature, Parameter
except ImportError:
from funcsigs import signature, Signature, Parameter
from makefun import create_function
def create_initiation_function(cls, gen_init):
# (1) check which signature we want to create
params = [Parameter('self', kind=Parameter.POSITIONAL_OR_KEYWORD)]
for mandatory_arg_name in cls.__init_args__:
params.append(Parameter(mandatory_arg_name, kind=Parameter.POSITIONAL_OR_KEYWORD))
for default_arg_name, default_arg_val in cls.__opt_init_args__.items():
params.append(Parameter(default_arg_name, kind=Parameter.POSITIONAL_OR_KEYWORD, default=default_arg_val))
sig = Signature(params)
# (2) create the init function dynamically
return create_function(sig, generic_init)
# ----- let's use it
def generic_init(self, *args, **kwargs):
"""Function to initiate a generic object"""
assert len(args) == 0
for name, val in kwargs.items():
setattr(self, name, val)
class my_class:
__init_args__ = ["x", "y"]
__opt_init_args__ = {"my_opt": None}
my_class.__init__ = create_initiation_function(my_class, generic_init)
and works as expected:
# check
o1 = my_class(1, 2)
assert vars(o1) == {'y': 2, 'x': 1, 'my_opt': None}
o2 = my_class(1, 2, 3)
assert vars(o2) == {'y': 2, 'x': 1, 'my_opt': 3}
o3 = my_class(my_opt='hello', y=3, x=2)
assert vars(o3) == {'y': 3, 'x': 2, 'my_opt': 'hello'}
You can't do this with live code.
That is, you seem to be wanting to take an actual, live function that looks like this:
def f(*args, **kwargs):
print args[0]
and change it to one like this:
def f(a):
print a
The reason this can't be done--at least without modifying actual Python bytecode--is because these compile differently.
The former results in a function that receives two parameters: a list and a dict, and the code you're writing operates on that list and dict. The second results in a function that receives one parameter, and which is accessed as a local variable directly. If you changed the function "signature", so to speak, it'd result in a function like this:
def f(a):
print a[0]
which obviously wouldn't work.
If you want more detail (though it doesn't really help you), a function that takes an *args or *kwargs has one or two bits set in f.func_code.co_flags; you can examine this yourself. The function that takes a regular parameter has f.func_code.co_argcount set to 1; the *args version is 0. This is what Python uses to figure out how to set up the function's stack frame when it's called, to check parameters, etc.
If you want to play around with modifying the function directly--if only to convince yourself that it won't work--see this answer for how to create a code object and live function from an existing one to modify bits of it. (This stuff is documented somewhere, but I can't find it; it's nowhere in the types module docs...)
That said, you can dynamically change the docstring of a function. Just assign to func.__doc__. Be sure to only do this at load time (from the global context or--most likely--a decorator); if you do it later on, tools that load the module to examine docstrings will never see it.
Maybe I didn't understand the problem well, but if it's about keeping the same behavior while changing the function signature, then you can do something like :
# define a function
def my_func(name, age) :
print "I am %s and I am %s" % (name, age)
# label the function with a backup name
save_func = my_func
# rewrite the function with a different signature
def my_func(age, name) :
# use the backup name to use the old function and keep the old behavior
save_func(name, age)
# you can use the new signature
my_func(35, "Bob")
This outputs :
I am Bob and I am 35
We want create_initiation_function to change the signature
Please don't do this.
We want to use this function in a number of classes
Please use ordinary inheritance.
There's no value in having the signature "changed" at run time.
You're creating a maintenance nightmare. No one else will ever bother to figure out what you're doing. They'll simply rip it out and replace it with inheritance.
Do this instead. It's simple and obvious and makes your generic init available in all subclasses in an obvious, simple, Pythonic way.
class Super( object ):
def __init__( self, *args, **kwargs ):
# the generic __init__ that we want every subclass to use
class SomeSubClass( Super ):
def __init__( self, this, that, **kwdefaults ):
super( SomeSubClass, self ).__init__( this, that, **kwdefaults )
class AnotherSubClass( Super ):
def __init__( self, x, y, **kwdefaults ):
super( AnotherSubClass, self ).__init__( x, y, **kwdefaults )
Edit 1: Answering new question:
You ask how you can create a function with this signature:
def fun(a, b, opt=None):
pass
The correct way to do that in Python is thus:
def fun(a, b, opt=None):
pass
Edit 2: Answering explanation:
"Suppose I have a generic function f. I want to programmatically create a function f2 that behaves the same as f, but has a customised signature."
def f(*args, **kw):
pass
OK, then f2 looks like so:
def f2(a, b, opt=None):
f(a, b, opt=opt)
Again, the answer to your question is so trivial, that you obviously want to know something different that what you are asking. You really do need to stop asking abstract questions, and explain your concrete problem.

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