how do you define dotted function?
i try this:
def myfunc.print(value)
print(value);
but it's said "Invalid syntax"
In python, and in many other languages, the "dot" syntax is a product of code organizational structure. So, X.Y tells python to look for Y inside of X. There are actually a few ways to do this. You can define a class which organizes a set of functions and properties within the class or its associated objects (as #Samwise's answer shows). You can also create a new file "myfunc.py", and have one of the functions defined in that file be def print(): pass - then when you import myfunc in another file you can access myfunc.print. In any case, the dot represents a "belonging" relationship, so you need to have your print function "belong" to the myfunc containing structure in some way.
Here's one way:
>>> class myfunc:
... print = print
...
>>> myfunc.print("foo")
foo
In this example, myfunc is actually a class, and print is a class attribute (which is initialized to point to the print function).
Is it possible to forward-declare a function in Python? I want to sort a list using my own cmp function before it is declared.
print "\n".join([str(bla) for bla in sorted(mylist, cmp = cmp_configs)])
I've put the definition of cmp_configs method after the invocation. It fails with this error:
NameError: name 'cmp_configs' is not defined
Is there any way to "declare" cmp_configs method before it's used?
Sometimes, it is difficult to reorganize code to avoid this problem. For instance, when implementing some forms of recursion:
def spam():
if end_condition():
return end_result()
else:
return eggs()
def eggs():
if end_condition():
return end_result()
else:
return spam()
Where end_condition and end_result have been previously defined.
Is the only solution to reorganize the code and always put definitions before invocations?
Wrap the invocation into a function of its own so that
foo()
def foo():
print "Hi!"
will break, but
def bar():
foo()
def foo():
print "Hi!"
bar()
will work properly.
The general rule in Python is that a function should be defined before its usage, which does not necessarily mean it needs to be higher in the code.
If you kick-start your script through the following:
if __name__=="__main__":
main()
then you probably do not have to worry about things like "forward declaration". You see, the interpreter would go loading up all your functions and then start your main() function. Of course, make sure you have all the imports correct too ;-)
Come to think of it, I've never heard such a thing as "forward declaration" in python... but then again, I might be wrong ;-)
If you don't want to define a function before it's used, and defining it afterwards is impossible, what about defining it in some other module?
Technically you still define it first, but it's clean.
You could create a recursion like the following:
def foo():
bar()
def bar():
foo()
Python's functions are anonymous just like values are anonymous, yet they can be bound to a name.
In the above code, foo() does not call a function with the name foo, it calls a function that happens to be bound to the name foo at the point the call is made. It is possible to redefine foo somewhere else, and bar would then call the new function.
Your problem cannot be solved because it's like asking to get a variable which has not been declared.
I apologize for reviving this thread, but there was a strategy not discussed here which may be applicable.
Using reflection it is possible to do something akin to forward declaration. For instance lets say you have a section of code that looks like this:
# We want to call a function called 'foo', but it hasn't been defined yet.
function_name = 'foo'
# Calling at this point would produce an error
# Here is the definition
def foo():
bar()
# Note that at this point the function is defined
# Time for some reflection...
globals()[function_name]()
So in this way we have determined what function we want to call before it is actually defined, effectively a forward declaration. In python the statement globals()[function_name]() is the same as foo() if function_name = 'foo' for the reasons discussed above, since python must lookup each function before calling it. If one were to use the timeit module to see how these two statements compare, they have the exact same computational cost.
Of course the example here is very useless, but if one were to have a complex structure which needed to execute a function, but must be declared before (or structurally it makes little sense to have it afterwards), one can just store a string and try to call the function later.
If the call to cmp_configs is inside its own function definition, you should be fine. I'll give an example.
def a():
b() # b() hasn't been defined yet, but that's fine because at this point, we're not
# actually calling it. We're just defining what should happen when a() is called.
a() # This call fails, because b() hasn't been defined yet,
# and thus trying to run a() fails.
def b():
print "hi"
a() # This call succeeds because everything has been defined.
In general, putting your code inside functions (such as main()) will resolve your problem; just call main() at the end of the file.
There is no such thing in python like forward declaration. You just have to make sure that your function is declared before it is needed.
Note that the body of a function isn't interpreted until the function is executed.
Consider the following example:
def a():
b() # won't be resolved until a is invoked.
def b():
print "hello"
a() # here b is already defined so this line won't fail.
You can think that a body of a function is just another script that will be interpreted once you call the function.
Sometimes an algorithm is easiest to understand top-down, starting with the overall structure and drilling down into the details.
You can do so without forward declarations:
def main():
make_omelet()
eat()
def make_omelet():
break_eggs()
whisk()
fry()
def break_eggs():
for egg in carton:
break(egg)
# ...
main()
# declare a fake function (prototype) with no body
def foo(): pass
def bar():
# use the prototype however you see fit
print(foo(), "world!")
# define the actual function (overwriting the prototype)
def foo():
return "Hello,"
bar()
Output:
Hello, world!
No, I don't believe there is any way to forward-declare a function in Python.
Imagine you are the Python interpreter. When you get to the line
print "\n".join([str(bla) for bla in sorted(mylist, cmp = cmp_configs)])
either you know what cmp_configs is or you don't. In order to proceed, you have to
know cmp_configs. It doesn't matter if there is recursion.
You can't forward-declare a function in Python. If you have logic executing before you've defined functions, you've probably got a problem anyways. Put your action in an if __name__ == '__main__' at the end of your script (by executing a function you name "main" if it's non-trivial) and your code will be more modular and you'll be able to use it as a module if you ever need to.
Also, replace that list comprehension with a generator express (i.e., print "\n".join(str(bla) for bla in sorted(mylist, cmp=cmp_configs)))
Also, don't use cmp, which is deprecated. Use key and provide a less-than function.
Import the file itself. Assuming the file is called test.py:
import test
if __name__=='__main__':
test.func()
else:
def func():
print('Func worked')
TL;DR: Python does not need forward declarations. Simply put your function calls inside function def definitions, and you'll be fine.
def foo(count):
print("foo "+str(count))
if(count>0):
bar(count-1)
def bar(count):
print("bar "+str(count))
if(count>0):
foo(count-1)
foo(3)
print("Finished.")
recursive function definitions, perfectly successfully gives:
foo 3
bar 2
foo 1
bar 0
Finished.
However,
bug(13)
def bug(count):
print("bug never runs "+str(count))
print("Does not print this.")
breaks at the top-level invocation of a function that hasn't been defined yet, and gives:
Traceback (most recent call last):
File "./test1.py", line 1, in <module>
bug(13)
NameError: name 'bug' is not defined
Python is an interpreted language, like Lisp. It has no type checking, only run-time function invocations, which succeed if the function name has been bound and fail if it's unbound.
Critically, a function def definition does not execute any of the funcalls inside its lines, it simply declares what the function body is going to consist of. Again, it doesn't even do type checking. So we can do this:
def uncalled():
wild_eyed_undefined_function()
print("I'm not invoked!")
print("Only run this one line.")
and it runs perfectly fine (!), with output
Only run this one line.
The key is the difference between definitions and invocations.
The interpreter executes everything that comes in at the top level, which means it tries to invoke it. If it's not inside a definition.
Your code is running into trouble because you attempted to invoke a function, at the top level in this case, before it was bound.
The solution is to put your non-top-level function invocations inside a function definition, then call that function sometime much later.
The business about "if __ main __" is an idiom based on this principle, but you have to understand why, instead of simply blindly following it.
There are certainly much more advanced topics concerning lambda functions and rebinding function names dynamically, but these are not what the OP was asking for. In addition, they can be solved using these same principles: (1) defs define a function, they do not invoke their lines; (2) you get in trouble when you invoke a function symbol that's unbound.
Python does not support forward declarations, but common workaround for this is use of the the following condition at the end of your script/code:
if __name__ == '__main__': main()
With this it will read entire file first and then evaluate condition and call main() function which will be able to call any forward declared function as it already read the entire file first. This condition leverages special variable __name__ which returns __main__ value whenever we run Python code from current file (when code was imported as a module, then __name__ returns module name).
"just reorganize my code so that I don't have this problem." Correct. Easy to do. Always works.
You can always provide the function prior to it's reference.
"However, there are cases when this is probably unavoidable, for instance when implementing some forms of recursion"
Can't see how that's even remotely possible. Please provide an example of a place where you cannot define the function prior to it's use.
Now wait a minute. When your module reaches the print statement in your example, before cmp_configs has been defined, what exactly is it that you expect it to do?
If your posting of a question using print is really trying to represent something like this:
fn = lambda mylist:"\n".join([str(bla)
for bla in sorted(mylist, cmp = cmp_configs)])
then there is no requirement to define cmp_configs before executing this statement, just define it later in the code and all will be well.
Now if you are trying to reference cmp_configs as a default value of an argument to the lambda, then this is a different story:
fn = lambda mylist,cmp_configs=cmp_configs : \
"\n".join([str(bla) for bla in sorted(mylist, cmp = cmp_configs)])
Now you need a cmp_configs variable defined before you reach this line.
[EDIT - this next part turns out not to be correct, since the default argument value will get assigned when the function is compiled, and that value will be used even if you change the value of cmp_configs later.]
Fortunately, Python being so type-accommodating as it is, does not care what you define as cmp_configs, so you could just preface with this statement:
cmp_configs = None
And the compiler will be happy. Just be sure to declare the real cmp_configs before you ever invoke fn.
Python technically has support for forward declaration.
if you define a function/class then set the body to pass, it will have an empty entry in the global table.
you can then "redefine" the function/class later on to implement the function/class.
unlike c/c++ forward declaration though, this does not work from outside the scope (i.e. another file) as they have their own "global" namespace
example:
def foo(): pass
foo()
def foo(): print("FOOOOO")
foo()
foo is declared both times
however the first time foo is called it does not do anything as the body is just pass
but the second time foo is called. it executes the new body of print("FOOOOO")
but again. note that this does not fix circular dependancies. this is because files have their own name and have their own definitions of functions
example 2:
class bar: pass
print(bar)
this prints <class '__main__.bar'> but if it was declared in another file it would be <class 'otherfile.foo'>
i know this post is old, but i though that this answer would be useful to anyone who keeps finding this post after the many years it has been posted for
One way is to create a handler function. Define the handler early on, and put the handler below all the methods you need to call.
Then when you invoke the handler method to call your functions, they will always be available.
The handler could take an argument nameOfMethodToCall. Then uses a bunch of if statements to call the right method.
This would solve your issue.
def foo():
print("foo")
#take input
nextAction=input('What would you like to do next?:')
return nextAction
def bar():
print("bar")
nextAction=input('What would you like to do next?:')
return nextAction
def handler(action):
if(action=="foo"):
nextAction = foo()
elif(action=="bar"):
nextAction = bar()
else:
print("You entered invalid input, defaulting to bar")
nextAction = "bar"
return nextAction
nextAction=input('What would you like to do next?:')
while 1:
nextAction = handler(nextAction)
I think that this is a quite basic question, but I wasn't able to find anything. Sorry if this happen to be a duplicate.
I have a file with some functions defined, let's call this file main_functions.py.
In this file I rely on a function, which we can call foo(). For instance, in the file main_functions.py we can have something like this:
def bar():
return foo()
foo() is definend in another file, called secondary_functions.py
def foo():
return 1
Now, in my main script, I would like to import a file where I can define foo(), and then do something like:
from secondary_functions import * # Here I define foo()
from main_functions import *
bar()
If I do so, the function inside main_functions is not able to find the definitions that are present in secondary_functions, and I will get an error like:
NameError: name 'foo' is not defined
It is very important for me to solve this problem.
My aim is to be able to have different files called secondary_functions1.py, secondary_functions2.py, eccetera, definitions of foo().
And, to solve the problem, I don't want to change everytime the file that depend on these definitions, for instance inserting everytime something like import secondary_functionsX.py, which would solve the problem. I would like to change only the main script.
The foo name is imported in main.py. foo is not available in the main_functions.py module, because you have not imported it in that module. See Namespaces with Module Imports for more on why it works this way.
One way to do what you want is to supply foo as an argument to bar(). Example:
main.py:
from secondary_functions import foo
from main_functions import bar
bar(foo)
main_functions.py:
def bar(foo):
return foo()
secondary_functions.py:
def foo():
return 1
After the import statements, variables like pippo have become global variables in the scope of the main program. But global variables are not inherited by modules that get imported. Modules are supposed to be able to stand on their own as self-contained units, that can be imported by any program; imagine what could go wrong if they started using variables from whatever imports them...
Thus, the only way to do this is explicitly ‘giving’ the values to your module, for instance as additional function arguments. You could put everything that’s in main_functions.py in a Class, and then have your main script give it the desired global variables as arguments of its init construction function, so it can store them for usage by bar() and other methods.
It seems that the problem isn't calling the files correctly it's that you're not calling pippo correctly, if pippo is a global variable then i don't see why it's not working. the only way i can think of solving this is by saying file.pippo
and if you're going to have multiple files with a variable called pippo then it's best not to make them global and call then individually like i just showed you.
another thing that could be the problem is if you are defining pippo inside a function, which then makes it a local variable to that function only.
And the last problem i can think of is if you're using them in main_functions and they haven't been defined in main_functions and you're not importing the files into main_functions i.e
# in main_functions.py
import secondary_functions
then i don't think main_functions will be able to find the function and variable without making them arguments for the function you're using them in. or again you can do something like file.pippo
I was just curious if it was possible to create a module object inside python at runtime, without loading from any python file. The purpose of this would be to create a new empty namespace where other objects can then be stored subsequently. If this is not possible, is there another way to make and pass namespaces in python without saving to disk?
You can use a class with static methods.
class Namespace:
#staticmethod
def greet():
print "hello, world!"
In Python 3 the #staticmethod decorator is not needed.
You can use a simple class:
class Namespace:
pass
Now, to create a new namespace:
n = Namespace()
To store things in the namespace:
n.foo = 1
def square(x):
return x*x
n.squared = square
To refer to things in the namespace:
print n.foo
print n.squared(12)
To pass the namespace:
def func_requiring_a_namesapce(space):
print space.foo
func_requiring_a_namespace(n)
You could use a dictionary?
Modules Are Like Dictionaries
You know how a dictionary is created and used and that it is a way to map one thing to another. That means if you have a dictionary with a key 'apple' and you want to get it then you do this:
mystuff = {'apple': "I AM APPLES!"}
print mystuff['apple']
Imagine if I have a module that I decide to name mystuff.py and I put a function in it called apple. Here's the module mystuff.py:
# this goes in mystuff.py
def apple():
print "I AM APPLES!"
Once I have that, I can use that module with import and then access the apple function:
import mystuff
mystuff.apple()
I could also put a variable in it named tangerine like this:
def apple():
print "I AM APPLES!"
# this is just a variable
tangerine = "Living reflection of a dream"
Then again I can access that the same way:
import mystuff
mystuff.apple()
print mystuff.tangerine
Refer back to the dictionary, and you should start to see how this is similar to using a dictionary, but the syntax is different. Let's compare:
mystuff['apple'] # get apple from dict
mystuff.apple() # get apple from the module
mystuff.tangerine # same thing, it's just a variable
In the case of the dictionary, the key is a string and the syntax is [key]. In the case of the module, the key is an identifier, and the syntax is .key. Other than that they are nearly the same thing.
Editied from here
What I am trying to do, is creating a module, with a class; and a function, which is an interface of that class; and a variable name on-the-fly in this function, which is pointing to an instance of that class. This function and the class itself should be in a separate module, and their usage should be in a different python file.
I think, it's much easier to understand what I am trying to do, when you are looking at my code:
This is the first.py:
class FirstClass:
def setID(self, _id):
self.id = _id
def func(self):
pass
# An 'interface' for FirstClass
def fst(ID):
globals()['%s' % ID] = FirstClass(ID)
return globals()['%s' % ID]
Now, if I'm calling fst('some_text') right in first.py, the result is pretty much what I dreamed of, because later on, any time I write some_text.func(), it will call the func(), because some_text is pointing to an instance of FirstClass.
But, when the second.py is something like this:
from first import fst
fst('sample_name')
sample_name.func()
Then the answer from python is going to be like this:
NameError: name 'sample_name' is not defined.
Which is somewhat reasonable.. So my question is: is there a "prettier" method or a completely different one to do this? Or do I have to change something small in my code to get this done?
Thank you!
Don't set it as a global in the function. Instead, just return the new instance from the function and set the global to that return value:
def fst(ID):
return FirstClass(ID)
then in second.py:
sample_name = fst('sample_name')
where, if inside a function, you declare sample_name a global.
The globals() method only ever returns the globals of the module in which you call it. It'll never return the globals of whatever is calling the function. If you feel you need to have access to those globals, rethink your code, you rarely, if ever, need to alter the globals of whatever is calling your function.
If you are absolutely certain you need access to the caller globals, you need to start hacking with stack frames:
# retrieve caller globals
import sys
caller_globals = sys._getframe(1).f_globals
But, as the documentation of sys._getframe() states:
CPython implementation detail: This function should be used for internal and specialized purposes only. It is not guaranteed to exist in all implementations of Python.