Can I add a prefix and suffix to the source code of functions?
I know about decorators and do not want to use them (the minimal example below doesn't make clear why, but I have my reasons).
def f():
print('world')
g = patched(f,prefix='print("Hello, ");',suffix='print("!");')
g() # Hello, world!
Here is what I have so far:
import inspect
import ast
import copy
def patched(f,prefix,suffix):
source = inspect.getsource(f)
tree = ast.parse(source)
new_body = [
ast.parse(prefix).body[0],
*tree.body[0].body,
ast.parse(suffix).body[0]
]
tree.body[0].body = new_body
g = copy.deepcopy(f)
g.__code__ = compile(tree,g.__code__.co_filename,'exec')
return g
Unfortunately, nothing happens if I use this and then call g() as above; neither world nor Hello, world! are printed.
Here is a rough version of what can be done:
import inspect
import ast
import copy
def patched(f,prefix,suffix):
source = inspect.getsource(f)
tree = ast.parse(source)
new_body = [
ast.parse(prefix).body[0],
*tree.body[0].body,
ast.parse(suffix).body[0]
]
tree.body[0].body = new_body
code = compile(tree,filename=f.__code__.co_filename,mode='exec')
namespace = {}
exec(code,namespace)
g = namespace[f.__name__]
return g
def temp():
pass
def f():
print('world',end='')
g = patched(f,prefix='print("Hello, ",end="")',suffix='print("!",end="")')
g() # Hello, world!
The call of compile compiles an entire module (represented by tree). This module is then executed in an empty namespace from which the desired function is finally extracted. (Warning: the namespace will need to be filled with some globals from where f comes from if f uses those.)
After some more work, here is a real example of what can be done with this. It uses some extended version of the principle above:
import numpy as np
from playground import graphexecute
#graphexecute(verbose=True)
def my_algorithm(x,y,z):
def SumFirstArguments(x,y)->sumxy:
sumxy = x+y
def SinOfThird(z)->sinz:
sinz = np.sin(z)
def FinalProduct(sumxy,sinz)->prod:
prod = sumxy*sinz
def Return(prod):
return prod
print(my_algorithm(x=1,y=2,z=3))
#OUTPUT:
#>>Executing part SumFirstArguments
#>>Executing part SinOfThird
#>>Executing part FinalProduct
#>>Executing part Return
#>>0.4233600241796016
The clou is that I get the exact same output if I reshuffle the parts of my_algorithm, for example like this:
#graphexecute(verbose=True)
def my_algorithm2(x,y,z):
def FinalProduct(sumxy,sinz)->prod:
prod = sumxy*sinz
def SumFirstArguments(x,y)->sumxy:
sumxy = x+y
def SinOfThird(z)->sinz:
sinz = np.sin(z)
def Return(prod):
return prod
print(my_algorithm2(x=1,y=2,z=3))
#OUTPUT:
#>>Executing part SumFirstArguments
#>>Executing part SinOfThird
#>>Executing part FinalProduct
#>>Executing part Return
#>>0.4233600241796016
This works by (1) grabbing the source of my_algorithm and turning it into an ast (2) patching each function defined within my_algorithm (e.g. SumFirstArguments) to return locals (3) deciding based on the inputs and the outputs (as defined by the type hints) in which order the parts of my_algorithm should be executed. Furthermore, a possibility that I do not have implemented yet is to execute independent parts in parallel (such as SumFirstArguments and SinOfThird). Let me know if you want the sourcecode of graphexecute, I haven't included it here because it contains a lot of stuff that is not relevant to this question.
For your problem, you don't need to recompile your functions. Just define a list of functions, you inspect for arguments and return variable name:
def FinalProduct(sumxy, sinz) -> "prod":
return sumxy * sinz
def SumFirstArguments(x, y) -> "sumxy":
return x + y
def SinOfThird(z) -> "sinz":
return np.sin(z)
def execute(funcs, **args):
result = None
while funcs:
func = funcs.pop(0)
try:
kw = {a: args[a]
for a in func.__code__.co_varnames[:func.__code__.co_argcount]
}
except KeyError:
# not all arguments found
funcs.append(func)
else:
print(func,kw)
result = func(**kw)
args[func.__annotations__['return']] = result
return result
print(execute([FinalProduct, SumFirstArguments, SinOfThird], x=1,y=2,z=3))
Related
This question already has answers here:
Getting the name of a variable as a string
(32 answers)
Closed 4 months ago.
Is it possible to get the original variable name of a variable passed to a function? E.g.
foobar = "foo"
def func(var):
print var.origname
So that:
func(foobar)
Returns:
>>foobar
EDIT:
All I was trying to do was make a function like:
def log(soup):
f = open(varname+'.html', 'w')
print >>f, soup.prettify()
f.close()
.. and have the function generate the filename from the name of the variable passed to it.
I suppose if it's not possible I'll just have to pass the variable and the variable's name as a string each time.
EDIT: To make it clear, I don't recommend using this AT ALL, it will break, it's a mess, it won't help you in any way, but it's doable for entertainment/education purposes.
You can hack around with the inspect module, I don't recommend that, but you can do it...
import inspect
def foo(a, f, b):
frame = inspect.currentframe()
frame = inspect.getouterframes(frame)[1]
string = inspect.getframeinfo(frame[0]).code_context[0].strip()
args = string[string.find('(') + 1:-1].split(',')
names = []
for i in args:
if i.find('=') != -1:
names.append(i.split('=')[1].strip())
else:
names.append(i)
print names
def main():
e = 1
c = 2
foo(e, 1000, b = c)
main()
Output:
['e', '1000', 'c']
To add to Michael Mrozek's answer, you can extract the exact parameters versus the full code by:
import re
import traceback
def func(var):
stack = traceback.extract_stack()
filename, lineno, function_name, code = stack[-2]
vars_name = re.compile(r'\((.*?)\).*$').search(code).groups()[0]
print vars_name
return
foobar = "foo"
func(foobar)
# PRINTS: foobar
Looks like Ivo beat me to inspect, but here's another implementation:
import inspect
def varName(var):
lcls = inspect.stack()[2][0].f_locals
for name in lcls:
if id(var) == id(lcls[name]):
return name
return None
def foo(x=None):
lcl='not me'
return varName(x)
def bar():
lcl = 'hi'
return foo(lcl)
bar()
# 'lcl'
Of course, it can be fooled:
def baz():
lcl = 'hi'
x='hi'
return foo(lcl)
baz()
# 'x'
Moral: don't do it.
Another way you can try if you know what the calling code will look like is to use traceback:
def func(var):
stack = traceback.extract_stack()
filename, lineno, function_name, code = stack[-2]
code will contain the line of code that was used to call func (in your example, it would be the string func(foobar)). You can parse that to pull out the argument
You can't. It's evaluated before being passed to the function. All you can do is pass it as a string.
#Ivo Wetzel's answer works in the case of function call are made in one line, like
e = 1 + 7
c = 3
foo(e, 100, b=c)
In case that function call is not in one line, like:
e = 1 + 7
c = 3
foo(e,
1000,
b = c)
below code works:
import inspect, ast
def foo(a, f, b):
frame = inspect.currentframe()
frame = inspect.getouterframes(frame)[1]
string = inspect.findsource(frame[0])[0]
nodes = ast.parse(''.join(string))
i_expr = -1
for (i, node) in enumerate(nodes.body):
if hasattr(node, 'value') and isinstance(node.value, ast.Call)
and hasattr(node.value.func, 'id') and node.value.func.id == 'foo' # Here goes name of the function:
i_expr = i
break
i_expr_next = min(i_expr + 1, len(nodes.body)-1)
lineno_start = nodes.body[i_expr].lineno
lineno_end = nodes.body[i_expr_next].lineno if i_expr_next != i_expr else len(string)
str_func_call = ''.join([i.strip() for i in string[lineno_start - 1: lineno_end]])
params = str_func_call[str_func_call.find('(') + 1:-1].split(',')
print(params)
You will get:
[u'e', u'1000', u'b = c']
But still, this might break.
You can use python-varname package
from varname import nameof
s = 'Hey!'
print (nameof(s))
Output:
s
Package below:
https://github.com/pwwang/python-varname
For posterity, here's some code I wrote for this task, in general I think there is a missing module in Python to give everyone nice and robust inspection of the caller environment. Similar to what rlang eval framework provides for R.
import re, inspect, ast
#Convoluted frame stack walk and source scrape to get what the calling statement to a function looked like.
#Specifically return the name of the variable passed as parameter found at position pos in the parameter list.
def _caller_param_name(pos):
#The parameter name to return
param = None
#Get the frame object for this function call
thisframe = inspect.currentframe()
try:
#Get the parent calling frames details
frames = inspect.getouterframes(thisframe)
#Function this function was just called from that we wish to find the calling parameter name for
function = frames[1][3]
#Get all the details of where the calling statement was
frame,filename,line_number,function_name,source,source_index = frames[2]
#Read in the source file in the parent calling frame upto where the call was made
with open(filename) as source_file:
head=[source_file.next() for x in xrange(line_number)]
source_file.close()
#Build all lines of the calling statement, this deals with when a function is called with parameters listed on each line
lines = []
#Compile a regex for matching the start of the function being called
regex = re.compile(r'\.?\s*%s\s*\(' % (function))
#Work backwards from the parent calling frame line number until we see the start of the calling statement (usually the same line!!!)
for line in reversed(head):
lines.append(line.strip())
if re.search(regex, line):
break
#Put the lines we have groked back into sourcefile order rather than reverse order
lines.reverse()
#Join all the lines that were part of the calling statement
call = "".join(lines)
#Grab the parameter list from the calling statement for the function we were called from
match = re.search('\.?\s*%s\s*\((.*)\)' % (function), call)
paramlist = match.group(1)
#If the function was called with no parameters raise an exception
if paramlist == "":
raise LookupError("Function called with no parameters.")
#Use the Python abstract syntax tree parser to create a parsed form of the function parameter list 'Name' nodes are variable names
parameter = ast.parse(paramlist).body[0].value
#If there were multiple parameters get the positional requested
if type(parameter).__name__ == 'Tuple':
#If we asked for a parameter outside of what was passed complain
if pos >= len(parameter.elts):
raise LookupError("The function call did not have a parameter at postion %s" % pos)
parameter = parameter.elts[pos]
#If there was only a single parameter and another was requested raise an exception
elif pos != 0:
raise LookupError("There was only a single calling parameter found. Parameter indices start at 0.")
#If the parameter was the name of a variable we can use it otherwise pass back None
if type(parameter).__name__ == 'Name':
param = parameter.id
finally:
#Remove the frame reference to prevent cyclic references screwing the garbage collector
del thisframe
#Return the parameter name we found
return param
If you want a Key Value Pair relationship, maybe using a Dictionary would be better?
...or if you're trying to create some auto-documentation from your code, perhaps something like Doxygen (http://www.doxygen.nl/) could do the job for you?
I wondered how IceCream solves this problem. So I looked into the source code and came up with the following (slightly simplified) solution. It might not be 100% bullet-proof (e.g. I dropped get_text_with_indentation and I assume exactly one function argument), but it works well for different test cases. It does not need to parse source code itself, so it should be more robust and simpler than previous solutions.
#!/usr/bin/env python3
import inspect
from executing import Source
def func(var):
callFrame = inspect.currentframe().f_back
callNode = Source.executing(callFrame).node
source = Source.for_frame(callFrame)
expression = source.asttokens().get_text(callNode.args[0])
print(expression, '=', var)
i = 1
f = 2.0
dct = {'key': 'value'}
obj = type('', (), {'value': 42})
func(i)
func(f)
func(s)
func(dct['key'])
func(obj.value)
Output:
i = 1
f = 2.0
s = string
dct['key'] = value
obj.value = 42
Update: If you want to move the "magic" into a separate function, you simply have to go one frame further back with an additional f_back.
def get_name_of_argument():
callFrame = inspect.currentframe().f_back.f_back
callNode = Source.executing(callFrame).node
source = Source.for_frame(callFrame)
return source.asttokens().get_text(callNode.args[0])
def func(var):
print(get_name_of_argument(), '=', var)
If you want to get the caller params as in #Matt Oates answer answer without using the source file (ie from Jupyter Notebook), this code (combined from #Aeon answer) will do the trick (at least in some simple cases):
def get_caller_params():
# get the frame object for this function call
thisframe = inspect.currentframe()
# get the parent calling frames details
frames = inspect.getouterframes(thisframe)
# frame 0 is the frame of this function
# frame 1 is the frame of the caller function (the one we want to inspect)
# frame 2 is the frame of the code that calls the caller
caller_function_name = frames[1][3]
code_that_calls_caller = inspect.findsource(frames[2][0])[0]
# parse code to get nodes of abstract syntact tree of the call
nodes = ast.parse(''.join(code_that_calls_caller))
# find the node that calls the function
i_expr = -1
for (i, node) in enumerate(nodes.body):
if _node_is_our_function_call(node, caller_function_name):
i_expr = i
break
# line with the call start
idx_start = nodes.body[i_expr].lineno - 1
# line with the end of the call
if i_expr < len(nodes.body) - 1:
# next expression marks the end of the call
idx_end = nodes.body[i_expr + 1].lineno - 1
else:
# end of the source marks the end of the call
idx_end = len(code_that_calls_caller)
call_lines = code_that_calls_caller[idx_start:idx_end]
str_func_call = ''.join([line.strip() for line in call_lines])
str_call_params = str_func_call[str_func_call.find('(') + 1:-1]
params = [p.strip() for p in str_call_params.split(',')]
return params
def _node_is_our_function_call(node, our_function_name):
node_is_call = hasattr(node, 'value') and isinstance(node.value, ast.Call)
if not node_is_call:
return False
function_name_correct = hasattr(node.value.func, 'id') and node.value.func.id == our_function_name
return function_name_correct
You can then run it as this:
def test(*par_values):
par_names = get_caller_params()
for name, val in zip(par_names, par_values):
print(name, val)
a = 1
b = 2
string = 'text'
test(a, b,
string
)
to get the desired output:
a 1
b 2
string text
Since you can have multiple variables with the same content, instead of passing the variable (content), it might be safer (and will be simpler) to pass it's name in a string and get the variable content from the locals dictionary in the callers stack frame. :
def displayvar(name):
import sys
return name+" = "+repr(sys._getframe(1).f_locals[name])
If it just so happens that the variable is a callable (function), it will have a __name__ property.
E.g. a wrapper to log the execution time of a function:
def time_it(func, *args, **kwargs):
start = perf_counter()
result = func(*args, **kwargs)
duration = perf_counter() - start
print(f'{func.__name__} ran in {duration * 1000}ms')
return result
Starting from a script foo.py find all functions that are in use in local source code (i.e not built-in or third party packages), recursively.
EDIT: I do not want to find recursive functions. I want to find all functions that are in use!
e.g. foo.py
import bar
def not_used():
pass
bar.do_stuff(x,y)
bar.py
import math
def more_stuff(x,y):
result = math.abs(-x+-y)
return result
def do_stuff(x,y):
more_stuff(x,y)
Should return do_stuff & more_stuff
Should ignore not_used & abs
Many thanks
EDIT: Code so far
import dis
py_file = 'foo.py'
with open(py_file) as file:
source_code = file.read()
compiled = compile(source_code, py_file, "exec")
funcs = []
byte_code = dis.Bytecode(compiled)
instructions = list(reversed([x for x in byte_code]))
for (ix, instruction) in enumerate(instructions):
if instruction.opname == "CALL_FUNCTION":
load_func_instr = instructions[ix + instruction.arg + 1]
funcs.append(load_func_instr.argval)
results = [f'{ix}: {funcname}'for (ix, funcname) in enumerate(reversed(funcs), 1)]
You can use Python's ast (abstract syntax tree) module
A short example:
import ast
code = """
import math
def more_stuff(x,y):
result = math.abs(-x+-y)
return result
def do_stuff(x,y):
more_stuff(x,y)
"""
tree = ast.parse(code)
funcs = [x for x in ast.walk(tree) if isinstance(x, ast.FunctionDef)]
print(', '.join(f.name for f in funcs))
prints:
more_stuff, do_stuff
now you can add the tests, you like. For example the SO question
How to find/detect if a build-in function is used in Python AST?
discusses how to detect if a function is being used.
I'm trying to build a decorator-based dispatcher, such as you find used by Flask or Pyramid. I got something that works, but ran into a bit of a catch-22. The following code works, but only because foo() gets executed and sets the .mq_path-attribute. When starting the application and building a list of the dispatchable functions no attributes are thus set yet. I want to execute foo() driven by events.
I could "manually" prepare a list of functions ahead and updated as I add functions, but I enjoy the way Flask works, by just adding a decorator to a function that handles an URL (or in this case a MQ path).
list_of_paths = []
path_dispatcher = {}
def handle_mq(path):
def decorator(fn):
def decorated(*args,**kwargs):
decorated.mq_path = path
print "Hello from the handle_mq() decorator, your path is: {0}".format(path)
return fn(*args,**kwargs)
return decorated
return decorator
#handle_mq('/some/path')
def foo():
print "foo!"
foo() # <- this code only works if I first call the decorated function
for k, v in globals().items():
if hasattr(v, 'mq_path'):
list_of_paths.append(v.mq_path)
path_dispatcher[v.mq_path] = v
print list_of_paths
print path_dispatcher
path_dispatcher['/some/path']()
So basically the question is, how to gather a list of the decorated functions before they are first executed?
I'm on Python 2.7.
I found the answer!
list_of_paths = []
path_dispatcher = {}
def handle_mq(path):
def decorator(fn):
list_of_paths.append(path)
path_dispatcher[path] = fn
def decorated(*args,**kwargs):
print "Hello from handl_mq decorator, your path is: {0}".format(path)
return fn(*args,**kwargs)
return decorated
return decorator
#handle_mq('/some/path')
def foo():
print "foo!"
print list_of_paths
print path_dispatcher
path_dispatcher['/some/path']()
E.g. I've got the following python function:
def func(x):
"""Function docstring."""
result = x + 1
if result > 0:
# comment 2
return result
else:
# comment 3
return -1 * result
And I want to have some function that would print all function docstrings and comments that are met along the execution path, e.g.
> trace(func(2))
Function docstring.
Comment 2
3
In fact what I try to achieve is to provide some comments how the result has been calculated.
What could be used? AST as far as I understand does not keep comment in the tree.
I thought this was an interesting challenge, so I decided to give it a try. Here is what I came up with:
import ast
import inspect
import re
import sys
import __future__
if sys.version_info >= (3,5):
ast_Call = ast.Call
else:
def ast_Call(func, args, keywords):
"""Compatibility wrapper for ast.Call on Python 3.4 and below.
Used to have two additional fields (starargs, kwargs)."""
return ast.Call(func, args, keywords, None, None)
COMMENT_RE = re.compile(r'^(\s*)#\s?(.*)$')
def convert_comment_to_print(line):
"""If `line` contains a comment, it is changed into a print
statement, otherwise nothing happens. Only acts on full-line comments,
not on trailing comments. Returns the (possibly modified) line."""
match = COMMENT_RE.match(line)
if match:
return '{}print({!r})\n'.format(*match.groups())
else:
return line
def convert_docstrings_to_prints(syntax_tree):
"""Walks an AST and changes every docstring (i.e. every expression
statement consisting only of a string) to a print statement.
The AST is modified in-place."""
ast_print = ast.Name('print', ast.Load())
nodes = list(ast.walk(syntax_tree))
for node in nodes:
for bodylike_field in ('body', 'orelse', 'finalbody'):
if hasattr(node, bodylike_field):
for statement in getattr(node, bodylike_field):
if (isinstance(statement, ast.Expr) and
isinstance(statement.value, ast.Str)):
arg = statement.value
statement.value = ast_Call(ast_print, [arg], [])
def get_future_flags(module_or_func):
"""Get the compile flags corresponding to the features imported from
__future__ by the specified module, or by the module containing the
specific function. Returns a single integer containing the bitwise OR
of all the flags that were found."""
result = 0
for feature_name in __future__.all_feature_names:
feature = getattr(__future__, feature_name)
if (hasattr(module_or_func, feature_name) and
getattr(module_or_func, feature_name) is feature and
hasattr(feature, 'compiler_flag')):
result |= feature.compiler_flag
return result
def eval_function(syntax_tree, func_globals, filename, lineno, compile_flags,
*args, **kwargs):
"""Helper function for `trace`. Execute the function defined by
the given syntax tree, and return its return value."""
func = syntax_tree.body[0]
func.decorator_list.insert(0, ast.Name('_trace_exec_decorator', ast.Load()))
ast.increment_lineno(syntax_tree, lineno-1)
ast.fix_missing_locations(syntax_tree)
code = compile(syntax_tree, filename, 'exec', compile_flags, True)
result = [None]
def _trace_exec_decorator(compiled_func):
result[0] = compiled_func(*args, **kwargs)
func_locals = {'_trace_exec_decorator': _trace_exec_decorator}
exec(code, func_globals, func_locals)
return result[0]
def trace(func, *args, **kwargs):
"""Run the given function with the given arguments and keyword arguments,
and whenever a docstring or (whole-line) comment is encountered,
print it to stdout."""
filename = inspect.getsourcefile(func)
lines, lineno = inspect.getsourcelines(func)
lines = map(convert_comment_to_print, lines)
modified_source = ''.join(lines)
compile_flags = get_future_flags(func)
syntax_tree = compile(modified_source, filename, 'exec',
ast.PyCF_ONLY_AST | compile_flags, True)
convert_docstrings_to_prints(syntax_tree)
return eval_function(syntax_tree, func.__globals__,
filename, lineno, compile_flags, *args, **kwargs)
It is a bit long because I tried to cover most important cases, and the code might not be the most readable, but I hope it is nice enough to follow.
How it works:
First, read the function's source code using inspect.getsourcelines. (Warning: inspect does not work for functions that were defined interactively. If you need that, maybe you can use dill instead, see this answer.)
Search for lines that look like comments, and replace them with print statements. (Right now only whole-line comments are replaced, but it shouldn't be difficult to extend that to trailing comments if desired.)
Parse the source code into an AST.
Walk the AST and replace all docstrings with print statements.
Compile the AST.
Execute the AST. This and the previous step contain some trickery to try to reconstruct the context that the function was originally defined in (e.g. globals, __future__ imports, line numbers for exception tracebacks). Also, since just executing the source would only re-define the function and not call it, we fix that with a simple decorator.
It works in Python 2 and 3 (at least with the tests below, which I ran in 2.7 and 3.6).
To use it, simply do:
result = trace(func, 2) # result = func(2)
Here is a slightly more elaborate test that I used while writing the code:
#!/usr/bin/env python
from trace_comments import trace
from dateutil.easter import easter, EASTER_ORTHODOX
def func(x):
"""Function docstring."""
result = x + 1
if result > 0:
# comment 2
return result
else:
# comment 3
return -1 * result
if __name__ == '__main__':
result1 = trace(func, 2)
print("result1 = {}".format(result1))
result2 = trace(func, -10)
print("result2 = {}".format(result2))
# Test that trace() does not permanently replace the function
result3 = func(42)
print("result3 = {}".format(result3))
print("-----")
print(trace(easter, 2018))
print("-----")
print(trace(easter, 2018, EASTER_ORTHODOX))
I am maintaining a little library of useful functions for interacting with my company's APIs and I have come across (what I think is) a neat question that I can't find the answer to.
I frequently have to request large amounts of data from an API, so I do something like:
class Client(object):
def __init__(self):
self.data = []
def get_data(self, offset = 0):
done = False
while not done:
data = get_more_starting_at(offset)
self.data.extend(data)
offset += 1
if not data:
done = True
This works fine and allows me to restart the retrieval where I left off if something goes horribly wrong. However, since python functions are just regular objects, we can do stuff like:
def yo():
yo.hi = "yo!"
return None
and then we can interrogate yo about its properties later, like:
yo.hi => "yo!"
my question is: Can I rewrite my class-based example to pin the data to the function itself, without referring to the function by name. I know I can do this by:
def get_data(offset=0):
done = False
get_data.data = []
while not done:
data = get_more_starting_from(offset)
get_data.data.extend(data)
offset += 1
if not data:
done = True
return get_data.data
but I would like to do something like:
def get_data(offset=0):
done = False
self.data = [] # <===== this is the bit I can't figure out
while not done:
data = get_more_starting_from(offset)
self.data.extend(data) # <====== also this!
offset += 1
if not data:
done = True
return self.data # <======== want to refer to the "current" object
Is it possible to refer to the "current" object by anything other than its name?
Something like "this", "self", or "memememe!" is what I'm looking for.
I don't understand why you want to do this, but it's what a fixed point combinator allows you to do:
import functools
def Y(f):
#functools.wraps(f)
def Yf(*args):
return inner(*args)
inner = f(Yf)
return Yf
#Y
def get_data(f):
def inner_get_data(*args):
# This is your real get data function
# define it as normal
# but just refer to it as 'f' inside itself
print 'setting get_data.foo to', args
f.foo = args
return inner_get_data
get_data(1, 2, 3)
print get_data.foo
So you call get_data as normal, and it "magically" knows that f means itself.
You could do this, but (a) the data is not per-function-invocation, but per function (b) it's much easier to achieve this sort of thing with a class.
If you had to do it, you might do something like this:
def ybother(a,b,c,yrselflambda = lambda: ybother):
yrself = yrselflambda()
#other stuff
The lambda is necessary, because you need to delay evaluation of the term ybother until something has been bound to it.
Alternatively, and increasingly pointlessly:
from functools import partial
def ybother(a,b,c,yrself=None):
#whatever
yrself.data = [] # this will blow up if the default argument is used
#more stuff
bothered = partial(ybother, yrself=ybother)
Or:
def unbothered(a,b,c):
def inbothered(yrself):
#whatever
yrself.data = []
return inbothered, inbothered(inbothered)
This last version gives you a different function object each time, which you might like.
There are almost certainly introspective tricks to do this, but they are even less worthwhile.
Not sure what doing it like this gains you, but what about using a decorator.
import functools
def add_self(f):
#functools.wraps(f)
def wrapper(*args,**kwargs):
if not getattr(f, 'content', None):
f.content = []
return f(f, *args, **kwargs)
return wrapper
#add_self
def example(self, arg1):
self.content.append(arg1)
print self.content
example(1)
example(2)
example(3)
OUTPUT
[1]
[1, 2]
[1, 2, 3]