How do I get list of methods in a Python class?

There is the dir(theobject) method to list all the fields and methods of your object (as a tuple) and the inspect module (as codeape write) to list the fields and methods with their doc (in """).

Because everything (even fields) might be called in Python, I'm not sure there is a built-in function to list only methods. You might want to try if the object you get through dir is callable or not.

Python 3.x answer without external libraries

method_list = [func for func in dir(Foo) if callable(getattr(Foo, func))]

dunder-excluded result:

method_list = [func for func in dir(Foo) if callable(getattr(Foo, func)) and not func.startswith("__")]

Say you want to know all methods associated with list class Just Type The following

 print (dir(list))

Above will give you all methods of list class

Try the property __dict__.

you can also import the FunctionType from types and test it with the class.__dict__:

from types import FunctionType

class Foo:
    def bar(self): pass
    def baz(self): pass

def methods(cls):
    return [x for x, y in cls.__dict__.items() if type(y) == FunctionType]

methods(Foo)  # ['bar', 'baz']

You can list all methods in a python class by using the following code

dir(className)

This will return a list of all the names of the methods in the class

Note that you need to consider whether you want methods from base classes which are inherited (but not overridden) included in the result. The dir() and inspect.getmembers() operations do include base class methods, but use of the __dict__ attribute does not.

If your method is a "regular" method and not a staticmethod, classmethod etc.
There is a little hack I came up with -

for k, v in your_class.__dict__.items():
    if "function" in str(v):
        print(k)

This can be extended to other type of methods by changing "function" in the if condition correspondingly.
Tested in Python 2.7 and Python 3.5.

Try print(help(ClassName)) It prints out methods of the class

I just keep this there, because top rated answers are not clear.

This is simple test with not usual class based on Enum.

# -*- coding: utf-8 -*-
import sys, inspect
from enum import Enum

class my_enum(Enum):
    """Enum base class my_enum"""
    M_ONE = -1
    ZERO = 0
    ONE = 1
    TWO = 2
    THREE = 3

    def is_natural(self):
            return (self.value > 0)
    def is_negative(self):
            return (self.value < 0)

def is_clean_name(name):
    return not name.startswith('_') and not name.endswith('_')
def clean_names(lst):
    return [ n for n in lst if is_clean_name(n) ]
def get_items(cls,lst):
    try:
            res = [ getattr(cls,n) for n in lst ]
    except Exception as e:
            res = (Exception, type(e), e)
            pass
    return res


print( sys.version )

dir_res = clean_names( dir(my_enum) )
inspect_res = clean_names( [ x[0] for x in inspect.getmembers(my_enum) ] )
dict_res = clean_names( my_enum.__dict__.keys() )

print( '## names ##' )
print( dir_res )
print( inspect_res )
print( dict_res )

print( '## items ##' )
print( get_items(my_enum,dir_res) )
print( get_items(my_enum,inspect_res) )
print( get_items(my_enum,dict_res) )

And this is output results.

3.7.7 (default, Mar 10 2020, 13:18:53) 
[GCC 9.2.1 20200306]
## names ##
['M_ONE', 'ONE', 'THREE', 'TWO', 'ZERO']
['M_ONE', 'ONE', 'THREE', 'TWO', 'ZERO', 'name', 'value']
['is_natural', 'is_negative', 'M_ONE', 'ZERO', 'ONE', 'TWO', 'THREE']
## items ##
[<my_enum.M_ONE: -1>, <my_enum.ONE: 1>, <my_enum.THREE: 3>, <my_enum.TWO: 2>, <my_enum.ZERO: 0>]
(<class 'Exception'>, <class 'AttributeError'>, AttributeError('name'))
[<function my_enum.is_natural at 0xb78a1fa4>, <function my_enum.is_negative at 0xb78ae854>, <my_enum.M_ONE: -1>, <my_enum.ZERO: 0>, <my_enum.ONE: 1>, <my_enum.TWO: 2>, <my_enum.THREE: 3>]

So what we have:

• dir provide not complete data
• inspect.getmembers provide not complete data and provide internal keys that are not accessible with getattr()
• __dict__.keys() provide complete and reliable result

Why are votes so erroneous? And where i'm wrong? And where wrong other people which answers have so low votes?

This also works:

In mymodule.py:

def foo(x):
   return 'foo'
def bar():
   return 'bar'

In another file:

import inspect
import mymodule
method_list = [ func[0] for func in inspect.getmembers(mymodule, predicate=inspect.isroutine) if callable(getattr(mymodule, func[0])) ]

Output:

['foo', 'bar']

From the Python docs:

inspect.isroutine(object)

Return true if the object is a user-defined or built-in function or method.

There's this approach:

[getattr(obj, m) for m in dir(obj) if not m.startswith('__')]

When dealing with a class instance, perhaps it'd be better to return a list with the method references instead of just names¹. If that's your goal, as well as

1. Using no import
2. Excluding private methods (e.g. __init__) from the list

It may be of use. You might also want to assure it's callable(getattr(obj, m)), since dir returns all attributes within obj, not just methods.

In a nutshell, for a class like

class Ghost:
    def boo(self, who):
        return f'Who you gonna call? {who}'

We could check instance retrieval with

>>> g = Ghost()
>>> methods = [getattr(g, m) for m in dir(g) if not m.startswith('__')]
>>> print(methods)
[<bound method Ghost.boo of <__main__.Ghost object at ...>>]

So you can call it right away:

>>> for method in methods:
...     print(method('GHOSTBUSTERS'))
...
Who you gonna call? GHOSTBUSTERS

¹ An use case:

I used this for unit testing. Had a class where all methods performed variations of the same process - which led to lengthy tests, each only a tweak away from the others. DRY was a far away dream.

Thought I should have a single test for all methods, so I made the above iteration.

Although I realized I should instead refactor the code itself to be DRY-compliant anyway... this may still serve a random nitpicky soul in the future.

methods = [(func, getattr(o, func)) for func in dir(o) if callable(getattr(o, func))]

gives an identical list as

methods = inspect.getmembers(o, predicate=inspect.ismethod)

does.

def find_defining_class(obj, meth_name):
    for ty in type(obj).mro():
        if meth_name in ty.__dict__:
            return ty

So

print find_defining_class(car, 'speedometer') 

Think Python page 210

You can use a function which I have created.

def method_finder(classname):

    non_magic_class = []

    class_methods = dir(classname)

    for m in class_methods:

        if m.startswith('__'):

            continue

        else:

            non_magic_class.append(m)

    return non_magic_class




method_finder(list)

Output:

['append',
 'clear',
 'copy',
 'count',
 'extend',
 'index',
 'insert',
 'pop',
 'remove',
 'reverse',
 'sort']

I know this is an old post, but just wrote this function and will leave it here is case someone stumbles looking for an answer:

def classMethods(the_class,class_only=False,instance_only=False,exclude_internal=True):

    def acceptMethod(tup):
        #internal function that analyzes the tuples returned by getmembers tup[1] is the 
        #actual member object
        is_method = inspect.ismethod(tup[1])
        if is_method:
            bound_to = tup[1].im_self
            internal = tup[1].im_func.func_name[:2] == '__' and tup[1].im_func.func_name[-2:] == '__'
            if internal and exclude_internal:
                include = False
            else:
                include = (bound_to == the_class and not instance_only) or (bound_to == None and not class_only)
        else:
            include = False
        return include
    #uses filter to return results according to internal function and arguments
    return filter(acceptMethod,inspect.getmembers(the_class))

use inspect.ismethod and dir and getattr

 import inspect
 class ClassWithMethods:
    
    def method1(self):
        print('method1')
    def method2(self):
        print('method2')

obj=ClassWithMethods()

method_names = [attr for attr in dir(obj) if inspect.ismethod(getattr(obj,attr))

print(method_names)

output:

[[('method1', <bound method ClassWithMethods.method1 of <__main__.ClassWithMethods object at 0x00000266779AF388>>), ('method2', <bound method ClassWithMethods.method2 of <__main__.ClassWithMethods object at 0x00000266779AF388>>)]]

None of the above worked for me.

I've encountered this problem while writing pytests.

The only work-around I found was to:

1- create another directory and place all my .py files there

2- create a separate directory for my pytests and then importing the classes I'm interested in

This allowed me to get up-to-dated methods within the class - you can change the method names and then use print(dir(class)) to confirm it.

For my use case, I needed to distinguish between class methods, static methods, properties, and instance methods. The inspect module confuses the issue a bit (particularly with class methods and instance methods), so I used vars based on a comment on this SO question. The basic gist is to use vars to get the __dict__ attribute of the class, then filter based on various isinstance checks. For instance methods, I check that it is callable and not a class method. One caveat: this approach of using vars (or __dict__ for that matter) won't work with __slots__. Using Python 3.6.9 (because it's what the Docker image I'm using as my interpreter has):

class MethodAnalyzer:

    class_under_test = None

    @classmethod
    def get_static_methods(cls):
        if cls.class_under_test:
            return {
                k for k, v in vars(cls.class_under_test).items()
                if isinstance(v, staticmethod)
            }
        return {}

    @classmethod
    def get_class_methods(cls):
        if cls.class_under_test:
            return {
                k for k, v in vars(cls.class_under_test).items()
                if isinstance(v, classmethod)
            }
        return {}

    @classmethod
    def get_instance_methods(cls):
        if cls.class_under_test:
            return {
                k for k, v in vars(cls.class_under_test).items()
                if callable(v) and not isinstance(v, classmethod)
            }
        return {}

    @classmethod
    def get_properties(cls):
        if cls.class_under_test:
            return {
                k for k, v in vars(cls.class_under_test).items()
                if isinstance(v, property)
            }
        return {}

To see it in action, I created this little test class:

class Foo:

    @staticmethod
    def bar(baz):
        print(baz)

    @property
    def bleep(self):
        return 'bloop'

    @classmethod
    def bork(cls):
        return cls.__name__

    def flank(self):
        return 'on your six'

then did:

MethodAnalyzer.class_under_test = Foo
print(MethodAnalyzer.get_instance_methods())
print(MethodAnalyzer.get_class_methods())
print(MethodAnalyzer.get_static_methods())
print(MethodAnalyzer.get_properties())

which output

{'flank'}
{'bork'}
{'bar'}
{'bleep'}

In this example I'm discarding the actual methods, but if you needed to keep them you could just use a dict comprehension instead of a set comprehension:

{
    k, v for k, v in vars(cls.class_under_test).items()
    if callable(v) and not isinstance(v, classmethod)
}

This is just an observation. "encode" seems to be a method for string objects

str_1 = 'a'
str_1.encode('utf-8')
>>> b'a'

However, if str1 is inspected for methods, an empty list is returned

inspect.getmember(str_1, predicate=inspect.ismethod)
>>> []

So, maybe I am wrong, but the issue seems to be not simple.

To produce a list of methods put the name of the method in a list without the usual parenthesis. Remove the name and attach the parenthesis and that calls the method.

    def methodA():
        print("@ MethodA")

    def methodB():
        print("@ methodB")

    a = []
    a.append(methodA)
    a.append(methodB)
    for item in a:
        item()

class CPerson:
    def __init__(self, age):
        self._age = age

    def run(self):
        pass

    @property
    def age(self): return self._age

    @staticmethod
    def my_static_method(): print("Life is short, you need Python")

    @classmethod
    def say(cls, msg): return msg


test_class = CPerson
# print(dir(test_class))  # list all the fields and methods of your object
print([(name, t) for name, t in test_class.__dict__.items() if type(t).__name__ == 'function' and not name.startswith('__')])
print([(name, t) for name, t in test_class.__dict__.items() if type(t).__name__ != 'function' and not name.startswith('__')])

output

[('run', <function CPerson.run at 0x0000000002AD3268>)]
[('age', <property object at 0x0000000002368688>), ('my_static_method', <staticmethod object at 0x0000000002ACBD68>), ('say', <classmethod object at 0x0000000002ACF0B8>)]

Just like this

pprint.pprint([x for x in dir(list) if not x.startswith("_")])