Develop Reference

Is it possible to "hack" Python's print function?

Note: This question is for informational purposes only. I am interested to see how deep into Python's internals it is possible to go with this.
Not very long ago, a discussion began inside a certain question regarding whether the strings passed to print statements could be modified after/during the call to print has been made. For example, consider the function:
def print_something():
print('This cat was scared.')
Now, when print is run, then the output to the terminal should display:
This dog was scared.
Notice the word "cat" has been replaced by the word "dog". Something somewhere somehow was able to modify those internal buffers to change what was printed. Assume this is done without the original code author's explicit permission (hence, hacking/hijacking).
This comment from the wise #abarnert, in particular, got me thinking:
There are a couple of ways to do that, but they're all very ugly, and
should never be done. The least ugly way is to probably replace the
code object inside the function with one with a different co_consts
list. Next is probably reaching into the C API to access the str's
internal buffer. [...]
So, it looks like this is actually possible.
Here's my naive way of approaching this problem:
>>> import inspect
>>> exec(inspect.getsource(print_something).replace('cat', 'dog'))
>>> print_something()
This dog was scared.
Of course, exec is bad, but that doesn't really answer the question, because it does not actually modify anything during when/after print is called.
How would it be done as #abarnert has explained it?

First, there's actually a much less hacky way. All we want to do is change what print prints, right?
_print = print
def print(*args, **kw):
args = (arg.replace('cat', 'dog') if isinstance(arg, str) else arg
for arg in args)
_print(*args, **kw)
Or, similarly, you can monkeypatch sys.stdout instead of print.
Also, nothing wrong with the exec … getsource … idea. Well, of course there's plenty wrong with it, but less than what follows here…
But if you do want to modify the function object's code constants, we can do that.
If you really want to play around with code objects for real, you should use a library like bytecode (when it's finished) or byteplay (until then, or for older Python versions) instead of doing it manually. Even for something this trivial, the CodeType initializer is a pain; if you actually need to do stuff like fixing up lnotab, only a lunatic would do that manually.
Also, it goes without saying that not all Python implementations use CPython-style code objects. This code will work in CPython 3.7, and probably all versions back to at least 2.2 with a few minor changes (and not the code-hacking stuff, but things like generator expressions), but it won't work with any version of IronPython.
import types
def print_function():
print ("This cat was scared.")
def main():
# A function object is a wrapper around a code object, with
# a bit of extra stuff like default values and closure cells.
# See inspect module docs for more details.
co = print_function.__code__
# A code object is a wrapper around a string of bytecode, with a
# whole bunch of extra stuff, including a list of constants used
# by that bytecode. Again see inspect module docs. Anyway, inside
# the bytecode for string (which you can read by typing
# dis.dis(string) in your REPL), there's going to be an
# instruction like LOAD_CONST 1 to load the string literal onto
# the stack to pass to the print function, and that works by just
# reading co.co_consts[1]. So, that's what we want to change.
consts = tuple(c.replace("cat", "dog") if isinstance(c, str) else c
for c in co.co_consts)
# Unfortunately, code objects are immutable, so we have to create
# a new one, copying over everything except for co_consts, which
# we'll replace. And the initializer has a zillion parameters.
# Try help(types.CodeType) at the REPL to see the whole list.
co = types.CodeType(
co.co_argcount, co.co_kwonlyargcount, co.co_nlocals,
co.co_stacksize, co.co_flags, co.co_code,
consts, co.co_names, co.co_varnames, co.co_filename,
co.co_name, co.co_firstlineno, co.co_lnotab,
co.co_freevars, co.co_cellvars)
print_function.__code__ = co
print_function()
main()
What could go wrong with hacking up code objects? Mostly just segfaults, RuntimeErrors that eat up the whole stack, more normal RuntimeErrors that can be handled, or garbage values that will probably just raise a TypeError or AttributeError when you try to use them. For examples, try creating a code object with just a RETURN_VALUE with nothing on the stack (bytecode b'S\0' for 3.6+, b'S' before), or with an empty tuple for co_consts when there's a LOAD_CONST 0 in the bytecode, or with varnames decremented by 1 so the highest LOAD_FAST actually loads a freevar/cellvar cell. For some real fun, if you get the lnotab wrong enough, your code will only segfault when run in the debugger.
Using bytecode or byteplay won't protect you from all of those problems, but they do have some basic sanity checks, and nice helpers that let you do things like insert a chunk of code and let it worry about updating all offsets and labels so you can't get it wrong, and so on. (Plus, they keep you from having to type in that ridiculous 6-line constructor, and having to debug the silly typos that come from doing so.)
Now on to #2.
I mentioned that code objects are immutable. And of course the consts are a tuple, so we can't change that directly. And the thing in the const tuple is a string, which we also can't change directly. That's why I had to build a new string to build a new tuple to build a new code object.
But what if you could change a string directly?
Well, deep enough under the covers, everything is just a pointer to some C data, right? If you're using CPython, there's a C API to access the objects, and you can use ctypes to access that API from within Python itself, which is such a terrible idea that they put a pythonapi right there in the stdlib's ctypes module. :) The most important trick you need to know is that id(x) is the actual pointer to x in memory (as an int).
Unfortunately, the C API for strings won't let us safely get at the internal storage of an already-frozen string. So screw safely, let's just read the header files and find that storage ourselves.
If you're using CPython 3.4 - 3.7 (it's different for older versions, and who knows for the future), a string literal from a module that's made of pure ASCII is going to be stored using the compact ASCII format, which means the struct ends early and the buffer of ASCII bytes follows immediately in memory. This will break (as in probably segfault) if you put a non-ASCII character in the string, or certain kinds of non-literal strings, but you can read up on the other 4 ways to access the buffer for different kinds of strings.
To make things slightly easier, I'm using the superhackyinternals project off my GitHub. (It's intentionally not pip-installable because you really shouldn't be using this except to experiment with your local build of the interpreter and the like.)
import ctypes
import internals # https://github.com/abarnert/superhackyinternals/blob/master/internals.py
def print_function():
print ("This cat was scared.")
def main():
for c in print_function.__code__.co_consts:
if isinstance(c, str):
idx = c.find('cat')
if idx != -1:
# Too much to explain here; just guess and learn to
# love the segfaults...
p = internals.PyUnicodeObject.from_address(id(c))
assert p.compact and p.ascii
addr = id(c) + internals.PyUnicodeObject.utf8_length.offset
buf = (ctypes.c_int8 * 3).from_address(addr + idx)
buf[:3] = b'dog'
print_function()
main()
If you want to play with this stuff, int is a whole lot simpler under the covers than str. And it's a lot easier to guess what you can break by changing the value of 2 to 1, right? Actually, forget imagining, let's just do it (using the types from superhackyinternals again):
>>> n = 2
>>> pn = PyLongObject.from_address(id(n))
>>> pn.ob_digit[0]
2
>>> pn.ob_digit[0] = 1
>>> 2
1
>>> n * 3
3
>>> i = 10
>>> while i < 40:
... i *= 2
... print(i)
10
10
10
… pretend that code box has an infinite-length scrollbar.
I tried the same thing in IPython, and the first time I tried to evaluate 2 at the prompt, it went into some kind of uninterruptable infinite loop. Presumably it's using the number 2 for something in its REPL loop, while the stock interpreter isn't?

Monkey-patch print
print is a builtin function so it will use the print function defined in the builtins module (or __builtin__ in Python 2). So whenever you want to modify or change the behavior of a builtin function you can simply reassign the name in that module.
This process is called monkey-patching.
# Store the real print function in another variable otherwise
# it will be inaccessible after being modified.
_print = print
# Actual implementation of the new print
def custom_print(*args, **options):
_print('custom print called')
_print(*args, **options)
# Change the print function globally
import builtins
builtins.print = custom_print
After that every print call will go through custom_print, even if the print is in an external module.
However you don't really want to print additional text, you want to change the text that is printed. One way to go about that is to replace it in the string that would be printed:
_print = print
def custom_print(*args, **options):
# Get the desired seperator or the default whitspace
sep = options.pop('sep', ' ')
# Create the final string
printed_string = sep.join(args)
# Modify the final string
printed_string = printed_string.replace('cat', 'dog')
# Call the default print function
_print(printed_string, **options)
import builtins
builtins.print = custom_print
And indeed if you run:
>>> def print_something():
... print('This cat was scared.')
>>> print_something()
This dog was scared.
Or if you write that to a file:
test_file.py
def print_something():
print('This cat was scared.')
print_something()
and import it:
>>> import test_file
This dog was scared.
>>> test_file.print_something()
This dog was scared.
So it really works as intended.
However, in case you only temporarily want to monkey-patch print you could wrap this in a context-manager:
import builtins
class ChangePrint(object):
def __init__(self):
self.old_print = print
def __enter__(self):
def custom_print(*args, **options):
# Get the desired seperator or the default whitspace
sep = options.pop('sep', ' ')
# Create the final string
printed_string = sep.join(args)
# Modify the final string
printed_string = printed_string.replace('cat', 'dog')
# Call the default print function
self.old_print(printed_string, **options)
builtins.print = custom_print
def __exit__(self, *args, **kwargs):
builtins.print = self.old_print
So when you run that it depends on the context what is printed:
>>> with ChangePrint() as x:
... test_file.print_something()
...
This dog was scared.
>>> test_file.print_something()
This cat was scared.
So that's how you could "hack" print by monkey-patching.
Modify the target instead of the print
If you look at the signature of print you'll notice a file argument which is sys.stdout by default. Note that this is a dynamic default argument (it really looks up sys.stdout every time you call print) and not like normal default arguments in Python. So if you change sys.stdout print will actually print to the different target even more convenient that Python also provides a redirect_stdout function (from Python 3.4 on, but it's easy to create an equivalent function for earlier Python versions).
The downside is that it won't work for print statements that don't print to sys.stdout and that creating your own stdout isn't really straightforward.
import io
import sys
class CustomStdout(object):
def __init__(self, *args, **kwargs):
self.current_stdout = sys.stdout
def write(self, string):
self.current_stdout.write(string.replace('cat', 'dog'))
However this also works:
>>> import contextlib
>>> with contextlib.redirect_stdout(CustomStdout()):
... test_file.print_something()
...
This dog was scared.
>>> test_file.print_something()
This cat was scared.
Summary
Some of these points have already be mentioned by #abarnet but I wanted to explore these options in more detail. Especially how to modify it across modules (using builtins/__builtin__) and how to make that change only temporary (using contextmanagers).

A simple way to capture all output from a print function and then process it, is to change the output stream to something else, e.g. a file.
I'll use a PHP naming conventions (ob_start, ob_get_contents,...)
from functools import partial
output_buffer = None
print_orig = print
def ob_start(fname="print.txt"):
global print
global output_buffer
print = partial(print_orig, file=output_buffer)
output_buffer = open(fname, 'w')
def ob_end():
global output_buffer
close(output_buffer)
print = print_orig
def ob_get_contents(fname="print.txt"):
return open(fname, 'r').read()
Usage:
print ("Hi John")
ob_start()
print ("Hi John")
ob_end()
print (ob_get_contents().replace("Hi", "Bye"))
Would print
Hi John
Bye John

Let's combine this with frame introspection!
import sys
_print = print
def print(*args, **kw):
frame = sys._getframe(1)
_print(frame.f_code.co_name)
_print(*args, **kw)
def greetly(name, greeting = "Hi")
print(f"{greeting}, {name}!")
class Greeter:
def __init__(self, greeting = "Hi"):
self.greeting = greeting
def greet(self, name):
print(f"{self.greeting}, {name}!")
You'll find this trick prefaces every greeting with the calling function or method. This might be very useful for logging or debugging; especially as it lets you "hijack" print statements in third party code.

Pass Undefined Argument To Python Function [UX Driven]

I would like to have a plotting interface (I do Allllooottt of plotting) where a user can put in an undefined variable.
Desired Interface
plot(ax,time,n1) # Returns Name Error
Current Interface
plot(ax,'time','n1')
I understand that this is likely a tall order, but I'm curious if the geniuses of Stack Overflow can find a way to do this. So far I've tried a decorator, but thats not working because the error isn't happening in the function, its happening in the calling of the function. Nevertheless I'm still interested in a solution... Even if its cumbersome.
Current Code
def handleUndefined(function):
try:
return function
except NameError as ne:
print ne
except Exception as e:
print e
#handleUndefined
def plot(self,**args):
axesList = filter(lambda arg: isinstance(arg,p.Axes),args.keys())
parmList = filter(lambda arg: arg in self.parms, args.keys())
print axesList
print parmList
fig,ax = p.subplots()
plot(ax,time,n1)
I'm designing a plotting interface, where people might make 20 plots / minute, so its important to give them less syntax here.

It's considered evil (or at least a bad practice) to use exec but that's the only way I could come up with setting up a variable dynamically from the value of a string which is unknown before runtime:
strg = 'time' # suppose this value is received from the user via standard input
exec(strg + " = '" + strg + "'")
print time # now we have a variable called 'time' that holds the value of the string "time"
Using this technique, you can define variables that will hold "their own name" dynamically.

So I had given up on finding the solution to this but low and behold I found a solution. It wasn't obvious but we can rely on pythons magic methods to actually link these variables into a global list all which is python's first stop in finding a variable.
I found a solution in which you can append something to all by using an #public decorator:
http://code.activestate.com/recipes/576993-public-decorator-adds-an-item-to-all/
From there the solution was something like this
#public
class globalVariable(str):
_name = None
def __init__(self,stringInput):
self._name = stringInput
self.__name__ = self._name
def repr(self):
return self._name
# Hopefully There's a strong correlation
xaxis = globalVariable('trees')
yaxis = globalVariable('forest')
#Booya lunchtime
plot(trees,forest)

Python string interpolation implementation

[EDIT 00]: I've edited several times the post and now even the title, please read below.
I just learned about the format string method, and its use with dictionaries, like the ones provided by vars(), locals() and globals(), example:
name = 'Ismael'
print 'My name is {name}.'.format(**vars())
But I want to do:
name = 'Ismael'
print 'My name is {name}.' # Similar to ruby
So I came up with this:
def mprint(string='', dictionary=globals()):
print string.format(**dictionary)
You can interact with the code here:
http://labs.codecademy.com/BA0B/3#:workspace
Finally, what I would love to do is to have the function in another file, named my_print.py, so I could do:
from my_print import mprint
name= 'Ismael'
mprint('Hello! My name is {name}.')
But as it is right now, there is a problem with the scopes, how could I get the the main module namespace as a dictionary from inside the imported mprint function. (not the one from my_print.py)
I hope I made myself uderstood, if not, try importing the function from another module. (the traceback is in the link)
It's accessing the globals() dict from my_print.py, but of course the variable name is not defined in that scope, any ideas of how to accomplish this?
The function works if it's defined in the same module, but notice how I must use globals() because if not I would only get a dictionary with the values within mprint() scope.
I have tried using nonlocal and dot notation to access the main module variables, but I still can't figure it out.
[EDIT 01]: I think I've figured out a solution:
In my_print.py:
def mprint(string='',dictionary=None):
if dictionary is None:
import sys
caller = sys._getframe(1)
dictionary = caller.f_locals
print string.format(**dictionary)
In test.py:
from my_print import mprint
name = 'Ismael'
country = 'Mexico'
languages = ['English', 'Spanish']
mprint("Hello! My name is {name}, I'm from {country}\n"
"and I can speak {languages[1]} and {languages[0]}.")
It prints:
Hello! My name is Ismael, I'm from Mexico
and I can speak Spanish and English.
What do you think guys? That was a difficult one for me!
I like it, much more readable for me.
[EDIT 02]: I've made a module with an interpolate function, an Interpolate class and an attempt for a interpolate class method analogous to the function.
It has a small test suite and its documented!
I'm stuck with the method implementation, I don't get it.
Here's the code: http://pastebin.com/N2WubRSB
What do you think guys?
[EDIT 03]: Ok I have settled with just the interpolate() function for now.
In string_interpolation.py:
import sys
def get_scope(scope):
scope = scope.lower()
caller = sys._getframe(2)
options = ['l', 'local', 'g', 'global']
if scope not in options[:2]:
if scope in options[2:]:
return caller.f_globals
else:
raise ValueError('invalid mode: {0}'.format(scope))
return caller.f_locals
def interpolate(format_string=str(),sequence=None,scope='local',returns=False):
if type(sequence) is str:
scope = sequence
sequence = get_scope(scope)
else:
if not sequence:
sequence = get_scope(scope)
format = 'format_string.format(**sequence)'
if returns is False:
print eval(format)
elif returns is True:
return eval(format)
Thanks again guys! Any opinions?
[EDIT 04]:
This is my last version, it has a test, docstrings and describes some limitations I've found:
http://pastebin.com/ssqbbs57
You can quickly test the code here:
http://labs.codecademy.com/BBMF#:workspace
And clone grom git repo here:
https://github.com/Ismael-VC/python_string_interpolation.git

Modules don't share namespaces in python, so globals() for my_print is always going to be the globals() of my_print.py file ; i.e the location where the function was actually defined.
def mprint(string='', dic = None):
dictionary = dic if dic is not None else globals()
print string.format(**dictionary)
You should pass the current module's globals() explicitly to make it work.
Ans don't use mutable objects as default values in python functions, it can result in unexpected results. Use None as default value instead.
A simple example for understanding scopes in modules:
file : my_print.py
x = 10
def func():
global x
x += 1
print x
file : main.py
from my_print import *
x = 50
func() #prints 11 because for func() global scope is still
#the global scope of my_print file
print x #prints 50

Part of your problem - well, the reason its not working - is highlighted in this question.
You can have your function work by passing in globals() as your second argument, mprint('Hello my name is {name}',globals()).
Although it may be convenient in Ruby, I would encourage you not to write Ruby in Python if you want to make the most out of the language.

Language Design Is Not Just Solving Puzzles: ;)
http://www.artima.com/forums/flat.jsp?forum=106&thread=147358
Edit: PEP-0498 solves this issue!
The Template class from the string module, also does what I need (but more similar to the string format method), in the end it also has the readability I seek, it also has the recommended explicitness, it's in the Standard Library and it can also be easily customized and extended.
http://docs.python.org/2/library/string.html?highlight=template#string.Template
from string import Template
name = 'Renata'
place = 'hospital'
job = 'Dr.'
how = 'glad'
header = '\nTo Ms. {name}:'
letter = Template("""
Hello Ms. $name.
I'm glad to inform, you've been
accepted in our $place, and $job Red
will ${how}ly recieve you tomorrow morning.
""")
print header.format(**vars())
print letter.substitute(vars())
The funny thing is that now I'm getting more fond of using {} instead of $ and I still like the string_interpolation module I came up with, because it's less typing than either one in the long run. LOL!
Run the code here:
http://labs.codecademy.com/BE3n/3#:workspace

Way in Python to make vars visible in calling method scope?

I find myself doing something like this constantly to pull GET args into vars:
some_var = self.request.get('some_var', None)
other_var = self.request.get('other_var', None)
if None in [some_var, other_var]:
logging.error("some arg was missing in " + self.request.path)
exit()
What I would really want to do is:
pull_args('some_var', 'other_var')
And that would somehow pull these variables to be available in current scope, or log an error and exit if not (or return to calling method if possible). Is this possible in Python?

First, a disclaimer: "pulling" variables into the local scope in any way other than var = something is really really really not recommended. It tends to make your code really confusing for someone who isn't intimately familiar with what you're doing (i.e. anyone who isn't you, or who is you 6 months in the future, etc.)
That being said, for educational purposes only, there is a way. Your pull_args function could be implemented like this:
def pull_args(request, *args):
pulled = {}
try:
for a in args:
pulled[a] = request[a]
except AttributeError:
logging.error("some arg was missing in " + self.request.path)
exit()
else:
caller = inspect.stack()[1][0]
caller.f_locals.update(pulled)
At least, something to that effect worked when I came up with it probably about a year ago. I wouldn't necessarily count on it continuing to work in future Python versions. (Yet another reason not to do it) I personally have never found a good reason to use this code snippet.

No it's not and also pointless. Writing to outer namespaces completely destroys the purpose of namespaces, which is having only the things around that you explicitly set. Use lists!
def pull_args(*names):
return [self.request.get(name, None) for name in names]
print None in pull_args('some_var', 'other_var')
Probably this works too, to check if all _var are set:
print all(name in self.request for name in ('some_var', 'other_var'))

Call python function as if it were inline

I want to have a function in a different module, that when called, has access to all variables that its caller has access to, and functions just as if its body had been pasted into the caller rather than having its own context, basically like a C Macro instead of a normal function. I know I can pass locals() into the function and then it can access the local variables as a dict, but I want to be able to access them normally (eg x.y, not x["y"] and I want all names the caller has access to not just the locals, as well as things that were 'imported' into the caller's file but not into the module that contains the function.
Is this possible to pull off?
Edit 2 Here's the simplest possible example I can come up with of what I'm really trying to do:
def getObj(expression)
ofs = expression.rfind(".")
obj = eval(expression[:ofs])
print "The part of the expression Left of the period is of type ", type(obj),
Problem is that 'expression' requires the imports and local variables of the caller in order to eval without error.In reality theres a lot more than just an eval, so I'm trying to avoid the solution of just passing locals() in and through to the eval() since that won't fix my general case problem.

And another, even uglier way to do it -- please don't do this, even if it's possible --
import sys
def insp():
l = sys._getframe(1).f_locals
expression = l["expression"]
ofs = expression.rfind(".")
expofs = expression[:ofs]
obj = eval(expofs, globals(), l)
print "The part of the expression %r Left of the period (%r) is of type %r" % (expression, expofs, type(obj)),
def foo():
derp = 5
expression = "derp.durr"
insp()
foo()
outputs
The part of the expression 'derp.durr' Left of the period ('derp') is of type (type 'int')

I don't presume this is the answer that you wanted to hear, but trying to access local variables from a caller module's scope is not a good idea. If you normally program in PHP or C, you might be used to this sort of thing?
If you still want to do this, you might consider creating a class and passing an instance of that class in place of locals():
#other_module.py
def some_func(lcls):
print(lcls.x)
Then,
>>> import other_module
>>>
>>>
>>> x = 'Hello World'
>>>
>>> class MyLocals(object):
... def __init__(self, lcls):
... self.lcls = lcls
... def __getattr__(self, name):
... return self.lcls[name]
...
>>> # Call your function with an instance of this instead.
>>> other_module.some_func(MyLocals(locals()))
'Hello World'
Give it a whirl.

Is this possible to pull off?
Yes (sort of, in a very roundabout way) which I would strongly advise against it in general (more on that later).
Consider:
myfile.py
def func_in_caller():
print "in caller"
import otherfile
globals()["imported_func"] = otherfile.remote_func
imported_func(123, globals())
otherfile.py
def remote_func(x1, extra):
for k,v in extra.iteritems():
globals()[k] = v
print x1
func_in_caller()
This yields (as expected):
123
in caller
What we're doing here is trickery: we just copy every item into another namespace in order to make this work. This can (and will) break very easily and/or lead to hard to find bugs.
There's almost certainly a better way of solving your problem / structuring your code (we need more information in general on what you're trying to achieve).

From The Zen of Python:
2) Explicit is better than implicit.
In other words, pass in the parameter and don't try to get really fancy just because you think it would be easier for you. Writing code is not just about you.