You can use dir(module) to see all available methods/attributes. Also check out PyDocs.

import types
import yourmodule

print([getattr(yourmodule, a) for a in dir(yourmodule)
  if isinstance(getattr(yourmodule, a), types.FunctionType)])

Once you’ve imported the module, you can just do:

help(modulename)

… To get the docs on all the functions at once, interactively. Or you can use:

dir(modulename)

… To simply list the names of all the functions and variables defined in the module.

This will do the trick:

dir(module) 

However, if you find it annoying to read the returned list, just use the following loop to get one name per line.

for i in dir(module): print i

Use inspect.getmembers to get all the variables/classes/functions etc. in a module, and pass in inspect.isfunction as the predicate to get just the functions:

from inspect import getmembers, isfunction
from my_project import my_module
    
functions_list = getmembers(my_module, isfunction)

getmembers returns a list of tuples (object_name, object) sorted alphabetically by name.

You can replace isfunction with any of the other isXXX functions in the inspect module.

dir(module) is the standard way when using a script or the standard interpreter, as mentioned in most answers.

However with an interactive python shell like IPython you can use tab-completion to get an overview of all objects defined in the module.
This is much more convenient, than using a script and print to see what is defined in the module.

• module.<tab> will show you all objects defined in the module (functions, classes and so on)
• module.ClassX.<tab> will show you the methods and attributes of a class
• module.function_xy? or module.ClassX.method_xy? will show you the docstring of that function / method
• module.function_x?? or module.SomeClass.method_xy?? will show you the source code of the function / method.

None of these answers will work if you are unable to import said Python file without import errors. This was the case for me when I was inspecting a file which comes from a large code base with a lot of dependencies. The following will process the file as text and search for all method names that start with “def” and print them and their line numbers.

import re
pattern = re.compile("def (.*)(")
for i, line in enumerate(open('Example.py')):
  for match in re.finditer(pattern, line):
    print '%s: %s' % (i+1, match.groups()[0])

For completeness’ sake, I’d like to point out that sometimes you may want to parse code instead of importing it. An import will execute top-level expressions, and that could be a problem.

For example, I’m letting users select entry point functions for packages being made with zipapp. Using import and inspect risks running astray code, leading to crashes, help messages being printed out, GUI dialogs popping up and so on.

Instead I use the ast module to list all the top-level functions:

import ast
import sys

def top_level_functions(body):
    return (f for f in body if isinstance(f, ast.FunctionDef))

def parse_ast(filename):
    with open(filename, "rt") as file:
        return ast.parse(file.read(), filename=filename)

if __name__ == "__main__":
    for filename in sys.argv[1:]:
        print(filename)
        tree = parse_ast(filename)
        for func in top_level_functions(tree.body):
            print("  %s" % func.name)

Putting this code in list.py and using itself as input, I get:

$ python list.py list.py
list.py
  top_level_functions
  parse_ast

Of course, navigating an AST can be tricky sometimes, even for a relatively simple language like Python, because the AST is quite low-level. But if you have a simple and clear use case, it’s both doable and safe.

Though, a downside is that you can’t detect functions that are generated at runtime, like foo = lambda x,y: x*y.

You can use the following method to get list all the functions in your module from shell:

import module

module.*?

Except dir(module) or help(module) mentioned in previous answers, you can also try:
– Open ipython
– import module_name
– type module_name, press tab. It’ll open a small window with listing all functions in the python module.
It looks very neat.

Here is snippet listing all functions of hashlib module

(C:Program FilesAnaconda2) C:Userslenovo>ipython
Python 2.7.12 |Anaconda 4.2.0 (64-bit)| (default, Jun 29 2016, 11:07:13) [MSC v.1500 64 bit (AMD64)]
Type "copyright", "credits" or "license" for more information.

IPython 5.1.0 -- An enhanced Interactive Python.
?         -> Introduction and overview of IPython's features.
%quickref -> Quick reference.
help      -> Python's own help system.
object?   -> Details about 'object', use 'object??' for extra details.

In [1]: import hashlib

In [2]: hashlib.
             hashlib.algorithms            hashlib.new                   hashlib.sha256
             hashlib.algorithms_available  hashlib.pbkdf2_hmac           hashlib.sha384
             hashlib.algorithms_guaranteed hashlib.sha1                  hashlib.sha512
             hashlib.md5                   hashlib.sha224

For code that you do not wish to evaluate, I recommend an AST-based approach (like csl‘s answer), e.g.:

import ast

source = open(<filepath_to_parse>).read()
functions = [f.name for f in ast.parse(source).body
             if isinstance(f, ast.FunctionDef)]

For everything else, the inspect module is correct:

import inspect

import <module_to_inspect> as module

functions = inspect.getmembers(module, inspect.isfunction)

This gives a list of 2-tuples in the form [(<name:str>, <value:function>), ...].

The simple answer above is hinted at in various responses and comments, but not called out explicitly.

For global functions dir() is the command to use (as mentioned in most of these answers), however this lists both public functions and non-public functions together.

For example running:

>>> import re
>>> dir(re)

Returns functions/classes like:

'__all__', '_MAXCACHE', '_alphanum_bytes', '_alphanum_str', '_pattern_type', '_pickle', '_subx'

Some of which are not generally meant for general programming use (but by the module itself, except in the case of DunderAliases like __doc__, __file__ ect). For this reason it may not be useful to list them with the public ones (this is how Python knows what to get when using from module import *).

__all__ could be used to solve this problem, it returns a list of all the public functions and classes in a module (those that do not start with underscores – _). See
Can someone explain __all__ in Python? for the use of __all__.

Here is an example:

>>> import re
>>> re.__all__
['match', 'fullmatch', 'search', 'sub', 'subn', 'split', 'findall', 'finditer', 'compile', 'purge', 'template', 'escape', 'error', 'A', 'I', 'L', 'M', 'S', 'X', 'U', 'ASCII', 'IGNORECASE', 'LOCALE', 'MULTILINE', 'DOTALL', 'VERBOSE', 'UNICODE']
>>>

All the functions and classes with underscores have been removed, leaving only those that are defined as public and can therefore be used via import *.

Note that __all__ is not always defined. If it is not included then an AttributeError is raised.

A case of this is with the ast module:

>>> import ast
>>> ast.__all__
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
AttributeError: module 'ast' has no attribute '__all__'
>>>

This will append all the functions that are defined in your_module in a list.

result=[]
for i in dir(your_module):
    if type(getattr(your_module, i)).__name__ == "function":
        result.append(getattr(your_module, i))

import sys
from inspect import getmembers, isfunction
fcn_list = [o[0] for o in getmembers(sys.modules[__name__], isfunction)]

r = globals()
sep = 'n'+100*'*'+'n' # To make it clean to read.
for k in list(r.keys()):
    try:
        if str(type(r[k])).count('function'):
            print(sep+k + ' : n' + str(r[k].__doc__))
    except Exception as e:
        print(e)

Output :

******************************************************************************************
GetNumberOfWordsInTextFile : 

    Calcule et retourne le nombre de mots d'un fichier texte
    :param path_: le chemin du fichier à analyser
    :return: le nombre de mots du fichier

******************************************************************************************

    write_in : 

        Ecrit les donnees (2nd arg) dans un fichier txt (path en 1st arg) en mode a,
        :param path_: le path du fichier texte
        :param data_: la liste des données à écrire ou un bloc texte directement
        :return: None


 ******************************************************************************************
    write_in_as_w : 

            Ecrit les donnees (2nd arg) dans un fichier txt (path en 1st arg) en mode w,
            :param path_: le path du fichier texte
            :param data_: la liste des données à écrire ou un bloc texte directement
            :return: None

The Python documentation provides the perfect solution for this which uses the built-in function dir.

You can just use dir(module_name) and then it will return a list of the functions within that module.

For example, dir(time) will return

['_STRUCT_TM_ITEMS', '__doc__', '__loader__', '__name__', '__package__', '__spec__', 'altzone', 'asctime', 'ctime', 'daylight', 'get_clock_info', 'gmtime', 'localtime', 'mktime', 'monotonic', 'monotonic_ns', 'perf_counter', 'perf_counter_ns', 'process_time', 'process_time_ns', 'sleep', 'strftime', 'strptime', 'struct_time', 'time', 'time_ns', 'timezone', 'tzname', 'tzset']

which is the list of functions the ‘time’ module contains.

Use vars(module) then filter out anything that isn’t a function using inspect.isfunction:

import inspect
import my_module

my_module_functions = [f for _, f in vars(my_module).values() if inspect.isfunction(f)]

The advantage of vars over dir or inspect.getmembers is that it returns the functions in the order they were defined instead of sorted alphabetically.

Also, this will include functions that are imported by my_module, if you want to filter those out to get only functions that are defined in my_module, see my question Get all defined functions in Python module.

If you want to get the list of all the functions defined in the current file, you can do it that way:

# Get this script's name.
import os
script_name = os.path.basename(__file__).rstrip(".py")

# Import it from its path so that you can use it as a Python object.
import importlib.util
spec = importlib.util.spec_from_file_location(script_name, __file__)
x = importlib.util.module_from_spec(spec)
spec.loader.exec_module(x)

# List the functions defined in it.
from inspect import getmembers, isfunction
list_of_functions = getmembers(x, isfunction)

As an application example, I use that for calling all the functions defined in my unit testing scripts.

This is a combination of codes adapted from the answers of Thomas Wouters and adrian here, and from Sebastian Rittau on a different question.

Finding the names (and callable objects) in the current script __main__

I was trying to create a standalone python script that used only the standard library to find functions in the current file with the prefix task_ to create a minimal homebrewed version of what npm run provides.

TL;DR

If you are running a standalone script you want to run inspect.getmembers on the module which is defined in sys.modules['__main__']. Eg,

inspect.getmembers(sys.modules['__main__'], inspect.isfunction)

But I wanted to filter the list of methods by prefix and strip the prefix to create a lookup dictionary.

def _inspect_tasks():
    import inspect
    return { f[0].replace('task_', ''): f[1] 
        for f in inspect.getmembers(sys.modules['__main__'], inspect.isfunction)
        if f[0].startswith('task_')
    }

Example Output:

{
 'install': <function task_install at 0x105695940>,
 'dev': <function task_dev at 0x105695b80>,
 'test': <function task_test at 0x105695af0>
}

Longer Version

I wanted the names of the methods to define CLI task names without having to repeat myself.

./tasks.py

#!/usr/bin/env python3
import sys
from subprocess import run

def _inspect_tasks():
    import inspect
    return { f[0].replace('task_', ''): f[1] 
        for f in inspect.getmembers(sys.modules['__main__'], inspect.isfunction)
        if f[0].startswith('task_')
    }

def _cmd(command, args):
    return run(command.split(" ") + args)

def task_install(args):
    return _cmd("python3 -m pip install -r requirements.txt -r requirements-dev.txt --upgrade", args)

def task_test(args):
    return _cmd("python3 -m pytest", args)

def task_dev(args):
    return _cmd("uvicorn api.v1:app", args)

if __name__ == "__main__":
    tasks = _inspect_tasks()

    if len(sys.argv) >= 2 and sys.argv[1] in tasks.keys():
        tasks[sys.argv[1]](sys.argv[2:])
    else:
        print(f"Must provide a task from the following: {list(tasks.keys())}")

Example no arguments:

λ ./tasks.py
Must provide a task from the following: ['install', 'dev', 'test']

Example running test with extra arguments:

λ ./tasks.py test -qq
s.ssss.sF..Fs.sssFsss..ssssFssFs....s.s    

You get the point. As my projects get more and more involved, it’s going to be easier to keep a script up to date than to keep the README up to date and I can abstract it down to just:

./tasks.py install
./tasks.py dev
./tasks.py test
./tasks.py publish
./tasks.py logs