Is it possible to have a Python docstring calculated? I have a lot of repetitive things in my docstrings, so I'd like to either use f-strings or a %-style format expression.
When I use an f-string at the place of a docstring
importing the module invokes the processing
but when I check the __doc__ of such a function it is empty
sphinx barfs when the docstring is an f-string
I do know how to process the docstrings after the import, but that doesn't work for object 'doc' strings which is recognized by sphinx but is not a real __doc__'s of the object.
Docstrings in Python must be regular string literals.
This is pretty easy to test - the following program does not show the docstring:
BAR = "Hello world!"
def foo():
f"""This is {BAR}"""
pass
assert foo.__doc__ is None
help(foo)
The Python syntax docs say that the docstring must be a "string literal", and the tail end of the f-string reference says they "cannot be used as docstrings".
So unfortunately you must use the __doc__ attribute.
However, you should be able to use a decorator to read the __doc__ attribute and replace it with whatever you want.
I've noticed some functions are called using the var.func() format as in var1.split() while other functions are called using the func(var) format as in sorted(list1).
Here's a very simple program to illustrate the question. I've also noticed the same behavior with open and read functions.
str1 = "This is a string"
list1 = str1.split()
print str1.split(' ')
print sorted(list1)
I'm very new to programming so any help would be greatly appreciated!
Everything in python is an object. Thus when doing something like this:
s = "some string"
s is an str object and you can call all the str methods on it. You can also do things like this:
"some string".split()
and it will give you a list of splitted strings.
This difference has to do with issues of scope. Functions which can be called directly, such as sorted(list1) in your example above, are either builtin functions, or else defined at the top level of one of your imported libraries (for example when using from simpy import *, you can call test() directly to run the built in test suite for the simpy library). Functions which are accessed through the dot operator are functions which are defined for the particular data type that you are applying them to. Remember that each data type in python is an object, and therefore an instance of a class. Those functions, such as split() are defined in that data type's class definition. Additionally, to use the example of test() from the simpy library again, if you were to import a library with only import simpy, you would have to use simpy.test() to call that method.
from simpy import *
test()
vs
import simpy
simpy.test()
The first works because you've imported all methods and classes from the top level of the simpy library, whereas the second works because you've explicitly dived into the scope of the simpy library.
var.func() just means that the function belongs to the object.
For instance, x.sort(). lists (like x) have a function sort.
When you call func(var), func is not a function of lists.
For instance, sorted(x).
This isn't Python specific. You will see the same idea in other languages (e.g. Java).
In var.func() the func() is meant to be used with the var object.
e.g. split() on a string object but cannot use on a list
But func(var) is not confined to a single var object type. you can use it with any appropriate var object.
e.g. sorted() can be used with any iterable like lists, tuples, dicts...
Following TraxusIV's line of thought, I tried the following and it worked!
from string import split
str1 = "This is a string"
list1 = str1.split()
print split(str1)
print sorted(list1)
If one does dir() on some builtin callables (class constructors, methods, etc) on CPython 3.4, one finds out that many of them often have a special attribute called __text_signature__, for example:
>>> object.__text_signature__
'()'
>>> int.__text_signature__
>>> # was None
However the documentation for this is nonexistent. Furthermore, googling for the attribute name suggests that there is also another possible special attribute __signature__, though I did not find any built-in functions that would have it.
I do know they are related to the function argument signature, but nothing beyond that, what do their values signify and what is the use of them?
These attributes are there to enable introspection for Python objects defined in C code. The C-API Argument Clinic provides the data, to assist the inspect module when building Signature objects. Introspection of C-API functions was not supported before.
See the internal inspect._signature_fromstr() function on how the __text_signature__ value is used.
Currently, the __text_signature__ attribute is filled from the internal docstring set on objects in the C-API; a simple text search is done for objectname(...)\n--\n\n, where the \n--\n\n is typical of Attribute Clinic-generated documentation strings. Take a look at the type object slots if you wanted to find some examples. Or you could look at the audioop module source to see how the Argument Clinic is being used to define signatures; the Argument Clinic script is run on those when building to generate the docstrings (in the accompanying audioop.c.h file).
The __signature__ attribute, if present, would be a inspect.Signature() object; instead of providing a text version a C-API can provide a fully parsed Signature instance instead.
Quick Summary
Those two attributes are used by the inspect.signature() function to retrieve metadata about a function or method's call signature.
Real-world Application
One use case for manually specifying one of these attributes is to provide useful tooltips for a function that uses *args.
In this example, the randrange() method uses *args to accept a variable number of inputs. However, we want the signature provided to help() and tooltips to show the meaning of each argument so that it matches the corresponding range() function.
import random
class Random(random.Random):
def randrange(self, /, *args):
'Choose a random value from range(start[, stop[, step]]).'
return self.choice(range(*args))
randrange.__text_signature__ = '($self, start, stop=None, step=1, /)'
The __text_signature__ attribute informs the creation of the Signature object:
>>> inspect.signature(Random.randrange)
<Signature (self, start, stop=None, step=1, /)>
This makes the help() output more useful:
>>> help(Random.randrange)
Help on function randrange in module __main__:
randrange(self, start, stop=None, step=1, /)
Choose a random value from range(start[, stop[, step]]).
How can I find the number of arguments of a Python function? I need to know how many normal arguments it has and how many named arguments.
Example:
def someMethod(self, arg1, kwarg1=None):
pass
This method has 2 arguments and 1 named argument.
The previously accepted answer has been deprecated as of Python 3.0. Instead of using inspect.getargspec you should now opt for the Signature class which superseded it.
Creating a Signature for the function is easy via the signature function:
from inspect import signature
def someMethod(self, arg1, kwarg1=None):
pass
sig = signature(someMethod)
Now, you can either view its parameters quickly by string it:
str(sig) # returns: '(self, arg1, kwarg1=None)'
or you can also get a mapping of attribute names to parameter objects via sig.parameters.
params = sig.parameters
print(params['kwarg1']) # prints: kwarg1=20
Additionally, you can call len on sig.parameters to also see the number of arguments this function requires:
print(len(params)) # 3
Each entry in the params mapping is actually a Parameter object that has further attributes making your life easier. For example, grabbing a parameter and viewing its default value is now easily performed with:
kwarg1 = params['kwarg1']
kwarg1.default # returns: None
similarly for the rest of the objects contained in parameters.
As for Python 2.x users, while inspect.getargspec isn't deprecated, the language will soon be :-). The Signature class isn't available in the 2.x series and won't be. So you still need to work with inspect.getargspec.
As for transitioning between Python 2 and 3, if you have code that relies on the interface of getargspec in Python 2 and switching to signature in 3 is too difficult, you do have the valuable option of using inspect.getfullargspec. It offers a similar interface to getargspec (a single callable argument) in order to grab the arguments of a function while also handling some additional cases that getargspec doesn't:
from inspect import getfullargspec
def someMethod(self, arg1, kwarg1=None):
pass
args = getfullargspec(someMethod)
As with getargspec, getfullargspec returns a NamedTuple which contains the arguments.
print(args)
FullArgSpec(args=['self', 'arg1', 'kwarg1'], varargs=None, varkw=None, defaults=(None,), kwonlyargs=[], kwonlydefaults=None, annotations={})
import inspect
inspect.getargspec(someMethod)
see the inspect module
func.__code__.co_argcount gives you the number of any arguments BEFORE *args
func.__kwdefaults__ gives you a dict of the keyword arguments AFTER *args
func.__code__.co_kwonlyargcount is equal to len(func.__kwdefaults__)
func.__defaults__ gives you the values of optional arguments that appears before *args
Here is a simple illustration:
>>> def a(b, c, d, e, f=1, g=3, h=None, *i, j=2, k=3, **L):
pass
>>> a.__code__.co_argcount
7
>>> a.__defaults__
(1, 3, None)
>>> len(a.__defaults__)
3
>>>
>>>
>>> a.__kwdefaults__
{'j': 2, 'k': 3}
>>> len(a.__kwdefaults__)
2
>>> a.__code__.co_kwonlyargcount
2
someMethod.func_code.co_argcount
or, if the current function name is undetermined:
import sys
sys._getframe().func_code.co_argcount
inspect.getargspec()
Get the names and default values of a function’s arguments. A tuple of four things is returned: (args, varargs, varkw, defaults). args is a list of the argument names (it may contain nested lists). varargs and varkw are the names of the * and ** arguments or None. defaults is a tuple of default argument values or None if there are no default arguments; if this tuple has n elements, they correspond to the last n elements listed in args.
Changed in version 2.6: Returns a named tuple ArgSpec(args, varargs, keywords, defaults).
See can-you-list-the-keyword-arguments-a-python-function-receives.
Adding to the above, I've also seen that the most of the times help() function really helps
For eg, it gives all the details about the arguments it takes.
help(<method>)
gives the below
method(self, **kwargs) method of apiclient.discovery.Resource instance
Retrieves a report which is a collection of properties / statistics for a specific customer.
Args:
date: string, Represents the date in yyyy-mm-dd format for which the data is to be fetched. (required)
pageToken: string, Token to specify next page.
parameters: string, Represents the application name, parameter name pairs to fetch in csv as app_name1:param_name1, app_name2:param_name2.
Returns:
An object of the form:
{ # JSON template for a collection of usage reports.
"nextPageToken": "A String", # Token for retrieving the next page
"kind": "admin#reports#usageReports", # Th
Good news for folks who want to do this in a portable way between Python 2 and Python 3.6+: use inspect.getfullargspec() method. It works in both Python 2.x and 3.6+
As Jim Fasarakis Hilliard and others have pointed out, it used to be like this:
1. In Python 2.x: use inspect.getargspec()
2. In Python 3.x: use signature, as getargspec() and getfullargspec() were deprecated.
However, starting Python 3.6 (by popular demand?), things have changed towards better:
From the Python 3 documentation page:
inspect.getfullargspec(func)
Changed in version 3.6: This method was previously documented as deprecated in favour of signature() in Python 3.5, but that decision has been reversed in order to restore a clearly supported standard interface for single-source Python 2/3 code migrating away from the legacy getargspec() API.
You get the number of arguments by (replace "function" by the name of your function):
function.__code__.co_argcount ## 2
And the names for the arguments by:
function.__code__.co_varnames ## ('a', 'b')
As other answers suggest, getargspec works well as long as the thing being queried is actually a function. It does not work for built-in functions such as open, len, etc, and will throw an exception in such cases:
TypeError: <built-in function open> is not a Python function
The below function (inspired by this answer) demonstrates a workaround. It returns the number of args expected by f:
from inspect import isfunction, getargspec
def num_args(f):
if isfunction(f):
return len(getargspec(f).args)
else:
spec = f.__doc__.split('\n')[0]
args = spec[spec.find('(')+1:spec.find(')')]
return args.count(',')+1 if args else 0
The idea is to parse the function spec out of the __doc__ string. Obviously this relies on the format of said string so is hardly robust!
inspect.getargspec() to meet your needs
from inspect import getargspec
def func(a, b):
pass
print len(getargspec(func).args)
The accepted answer by Dimitris Fasarakis Hilliard suggests getting parameters in the string format but I think one can make a mistake when parsing this string and thus I created rather a list of the parameters directly using the inspect module
import inspect
def my_function(a,b,c):
#some code
pass
result=list(inspect.signature(my_function).parameters.keys())
print(result)
['a','b','c']
Assuming you may be dealing with class based methods or simply functions, you could do something like the following.
This will automatically subtract one input if the input is a class method (and therefore includes self).
import types
def get_arg_count(fn):
extra_method_input_count=1 if isinstance(fn, types.MethodType) else 0
return fn.__code__.co_argcount-extra_method_input_count
Then you can apply as you need to functions or methods:
def fn1(a, b, c):
return None
class cl1:
def fn2(self, a, b, c):
return None
print(get_arg_count(fn1)) #=> 3
print(get_arg_count(cl1().fn2)) #=> 3
In:
import inspect
class X:
def xyz(self, a, b, c):
return
print(len(inspect.getfullargspec(X.xyz).args))
Out:
4
Note: If xyz wasn't inside class X and had no "self" and just "a, b, c", then it would have printed 3.
For python below 3.5, you may want to replace inspect.getfullargspec by inspect.getargspec in the code above.
This is a solution to getting the number of mandatory arguments of a function (*)
Many of the solutions proposed here do not work for this purpose if some more uncommon parameter specifications are used (positional-only parameters with defaults, keyword-only parameters without defaults, etc.)
from typing import Callable, Any
import inspect
def get_mandatory_argcount(f: Callable[..., Any]) -> int:
"""Get the number of mandatory arguments of a function."""
sig = inspect.signature(f)
def parameter_is_mandatory(p: inspect.Parameter) -> bool:
return p.default is inspect.Parameter.empty and p.kind not in (
inspect.Parameter.VAR_POSITIONAL,
inspect.Parameter.VAR_KEYWORD,
)
return sum(parameter_is_mandatory(p) for p in sig.parameters.values())
# mandatory keyword-only
def f1(b=2, *args, c, d=1, **kwds): pass
print(get_mandatory_argcount(f1))
# positional only with default
def f2(a=1, /, b=3, *args, **kwargs): pass
print(get_mandatory_argcount(f2))
(*) I would have liked to put this as an answer to Programmatically determining amount of parameters a function requires - Python instead, but for some reason this question is marked as duplicate to this one despite it asking specifically about the number of required arguments whereas this question only asks about the general number of arguments.