Related
Suppose I have a function like:
def foo():
x = 'hello world'
How do I get the function to return x, in such a way that I can use it as the input for another function or use the variable within the body of a program? I tried using return and then using the x variable in another function, but I get a NameError that way.
For the specific case of communicating information between methods in the same class, it is often best to store the information in self. See Passing variables between methods in Python? for details.
def foo():
x = 'hello world'
return x # return 'hello world' would do, too
foo()
print(x) # NameError - x is not defined outside the function
y = foo()
print(y) # this works
x = foo()
print(x) # this also works, and it's a completely different x than that inside
# foo()
z = bar(x) # of course, now you can use x as you want
z = bar(foo()) # but you don't have to
Effectively, there are two ways: directly and indirectly.
The direct way is to return a value from the function, as you tried, and let the calling code use that value. This is normally what you want. The natural, simple, direct, explicit way to get information back from a function is to return it. Broadly speaking, the purpose of a function is to compute a value, and return signifies "this is the value we computed; we are done here".
Directly using return
The main trick here is that return returns a value, not a variable. So return x does not enable the calling code to use x after calling the function, and does not modify any existing value that x had in the context of the call. (That's presumably why you got a NameError.)
After we use return in the function:
def example():
x = 'hello world'
return x
we need to write the calling code to use the return value:
result = example()
print(result)
The other key point here is that a call to a function is an expression, so we can use it the same way that we use, say, the result of an addition. Just as we may say result = 'hello ' + 'world', we may say result = foo(). After that, result is our own, local name for that string, and we can do whatever we want with it.
We can use the same name, x, if we want. Or we can use a different name. The calling code doesn't have to know anything about how the function is written, or what names it uses for things.1
We can use the value directly to call another function: for example, print(foo()).2 We can return the value directly: simply return 'hello world', without assigning to x. (Again: we are returning a value, not a variable.)
The function can only return once each time it is called. return terminates the function - again, we just determined the result of the calculation, so there is no reason to calculate any further. If we want to return multiple pieces of information, therefore, we will need to come up with a single object (in Python, "value" and "object" are effectively synonyms; this doesn't work out so well for some other languages.)
We can make a tuple right on the return line; or we can use a dictionary, a namedtuple (Python 2.6+), a types.simpleNamespace (Python 3.3+), a dataclass (Python 3.7+), or some other class (perhaps even one we write ourselves) to associate names with the values that are being returned; or we can accumulate values from a loop in a list; etc. etc. The possibilities are endless..
On the other hand, the function returns whether you like it or not (unless an exception is raised). If it reaches the end, it will implicitly return the special value None. You may or may not want to do it explicitly instead.
Indirect methods
Other than returning the result back to the caller directly, we can communicate it by modifying some existing object that the caller knows about. There are many ways to do that, but they're all variations on that same theme.
If you want the code to communicate information back this way, please just let it return None - don't also use the return value for something meaningful. That's how the built-in functionality works.
In order to modify that object, the called function also has to know about it, of course. That means, having a name for the object that can be looked up in a current scope. So, let's go through those in order:
Local scope: Modifying a passed-in argument
If one of our parameters is mutable, we can just mutate it, and rely on the caller to examine the change. This is usually not a great idea, because it can be hard to reason about the code. It looks like:
def called(mutable):
mutable.append('world')
def caller():
my_value = ['hello'] # a list with just that string
called(my_value)
# now it contains both strings
If the value is an instance of our own class, we could also assign to an attribute:
class Test:
def __init__(self, value):
self.value = value
def called(mutable):
mutable.value = 'world'
def caller():
test = Test('hello')
called(test)
# now test.value has changed
Assigning to an attribute does not work for built-in types, including object; and it might not work for some classes that explicitly prevent you from doing it.
Local scope: Modifying self, in a method
We already have an example of this above: setting self.value in the Test.__init__ code. This is a special case of modifying a passed-in argument; but it's part of how classes work in Python, and something we're expected to do. Normally, when we do this, the calling won't actually check for changes to self - it will just use the modified object in the next step of the logic. That's what makes it appropriate to write code this way: we're still presenting an interface, so the caller doesn't have to worry about the details.
class Example:
def __init__(self):
self._words = ['hello']
def add_word(self):
self._words.append('world')
def display(self):
print(*self.words)
x = Example()
x.add_word()
x.display()
In the example, calling add_word gave information back to the top-level code - but instead of looking for it, we just go ahead and call display.3
See also: Passing variables between methods in Python?
Enclosing scope
This is a rare special case when using nested functions. There isn't a lot to say here - it works the same way as with the global scope, just using the nonlocal keyword rather than global.4
Global scope: Modifying a global
Generally speaking, it is a bad idea to change anything in the global scope after setting it up in the first place. It makes code harder to reason about, because anything that uses that global (aside from whatever was responsible for the change) now has a "hidden" source of input.
If you still want to do it, the syntax is straightforward:
words = ['hello']
def add_global_word():
words.append('world')
add_global_word() # `words` is changed
Global scope: Assigning to a new or existing global
This is actually a special case of modifying a global. I don't mean that assignment is a kind of modification (it isn't). I mean that when you assign a global name, Python automatically updates a dict that represents the global namespace. You can get that dict with globals(), and you can modify that dict and it will actually impact what global variables exist. (I.e., the return from globals() is the dictionary itself, not a copy.)5
But please don't. That's even worse of an idea than the previous one. If you really need to get the result from your function by assigning to a global variable, use the global keyword to tell Python that the name should be looked up in the global scope:
words = ['hello']
def replace_global_words():
global words
words = ['hello', 'world']
replace_global_words() # `words` is a new list with both words
Global scope: Assigning to or modifying an attribute of the function itself
This is a rare special case, but now that you've seen the other examples, the theory should be clear. In Python, functions are mutable (i.e. you can set attributes on them); and if we define a function at top level, it's in the global namespace. So this is really just modifying a global:
def set_own_words():
set_own_words.words = ['hello', 'world']
set_own_words()
print(*set_own_words.words)
We shouldn't really use this to send information to the caller. It has all the usual problems with globals, and it's even harder to understand. But it can be useful to set a function's attributes from within the function, in order for the function to remember something in between calls. (It's similar to how methods remember things in between calls by modifying self.) The functools standard library does this, for example in the cache implementation.
Builtin scope
This doesn't work. The builtin namespace doesn't contain any mutable objects, and you can't assign new builtin names (they'll go into the global namespace instead).
Some approaches that don't work in Python
Just calculating something before the function ends
In some other programming languages, there is some kind of hidden variable that automatically picks up the result of the last calculation, every time something is calculated; and if you reach the end of a function without returning anything, it gets returned. That doesn't work in Python. If you reach the end without returning anything, your function returns None.
Assigning to the function's name
In some other programming languages, you are allowed (or expected) to assign to a variable with the same name as the function; and at the end of the function, that value is returned. That still doesn't work in Python. If you reach the end without returning anything, your function still returns None.
def broken():
broken = 1
broken()
print(broken + 1) # causes a `TypeError`
It might seem like you can at least use the value that way, if you use the global keyword:
def subtly_broken():
global subtly_broken
subtly_broken = 1
subtly_broken()
print(subtly_broken + 1) # 2
But this, of course, is just a special case of assigning to a global. And there's a big problem with it - the same name can't refer to two things at once. By doing this, the function replaced its own name. So it will fail next time:
def subtly_broken():
global subtly_broken
subtly_broken = 1
subtly_broken()
subtly_broken() # causes a `TypeError`
Assigning to a parameter
Sometimes people expect to be able to assign to one of the function's parameters, and have it affect a variable that was used for the corresponding argument. However, this does not work:
def broken(words):
words = ['hello', 'world']
data = ['hello']
broken(data) # `data` does not change
Just like how Python returns values, not variables, it also passes values, not variables. words is a local name; by definition the calling code doesn't know anything about that namespace.
One of the working methods that we saw is to modify the passed-in list. That works because if the list itself changes, then it changes - it doesn't matter what name is used for it, or what part of the code uses that name. However, assigning a new list to words does not cause the existing list to change. It just makes words start being a name for a different list.
For more information, see How do I pass a variable by reference?.
1 At least, not for getting the value back. If you want to use keyword arguments, you need to know what the keyword names are. But generally, the point of functions is that they're an abstraction; you only need to know about their interface, and you don't need to think about what they're doing internally.
2 In 2.x, print is a statement rather than a function, so this doesn't make an example of calling another function directly. However, print foo() still works with 2.x's print statement, and so does print(foo()) (in this case, the extra parentheses are just ordinary grouping parentheses). Aside from that, 2.7 (the last 2.x version) has been unsupported since the beginning of 2020 - which was nearly a 5 year extension of the normal schedule. But then, this question was originally asked in 2010.
3Again: if the purpose of a method is to update the object, don't also return a value. Some people like to return self so that you can "chain" method calls; but in Python this is considered poor style. If you want that kind of "fluent" interface, then instead of writing methods that update self, write methods that create a new, modified instance of the class.
4 Except, of course, that if we're modifying a value rather than assigning, we don't need either keyword.
5 There's also a locals() that gives you a dict of local variables. However, this cannot be used to make new local variables - the behaviour is undefined in 2.x, and in 3.x the dict is created on the fly and assigning to it has no effect. Some of Python's optimizations depend on the local variables for a function being known ahead of time.
>>> def foo():
return 'hello world'
>>> x = foo()
>>> x
'hello world'
You can use global statement and then achieve what you want without returning value from
the function. For example you can do something like below:
def foo():
global x
x = "hello world"
foo()
print x
The above code will print "hello world".
But please be warned that usage of "global" is not a good idea at all and it is better to avoid usage that is shown in my example.
Also check this related discussion on about usage of global statement in Python.
Suppose I have a function like:
def foo():
x = 'hello world'
How do I get the function to return x, in such a way that I can use it as the input for another function or use the variable within the body of a program? I tried using return and then using the x variable in another function, but I get a NameError that way.
For the specific case of communicating information between methods in the same class, it is often best to store the information in self. See Passing variables between methods in Python? for details.
def foo():
x = 'hello world'
return x # return 'hello world' would do, too
foo()
print(x) # NameError - x is not defined outside the function
y = foo()
print(y) # this works
x = foo()
print(x) # this also works, and it's a completely different x than that inside
# foo()
z = bar(x) # of course, now you can use x as you want
z = bar(foo()) # but you don't have to
Effectively, there are two ways: directly and indirectly.
The direct way is to return a value from the function, as you tried, and let the calling code use that value. This is normally what you want. The natural, simple, direct, explicit way to get information back from a function is to return it. Broadly speaking, the purpose of a function is to compute a value, and return signifies "this is the value we computed; we are done here".
Directly using return
The main trick here is that return returns a value, not a variable. So return x does not enable the calling code to use x after calling the function, and does not modify any existing value that x had in the context of the call. (That's presumably why you got a NameError.)
After we use return in the function:
def example():
x = 'hello world'
return x
we need to write the calling code to use the return value:
result = example()
print(result)
The other key point here is that a call to a function is an expression, so we can use it the same way that we use, say, the result of an addition. Just as we may say result = 'hello ' + 'world', we may say result = foo(). After that, result is our own, local name for that string, and we can do whatever we want with it.
We can use the same name, x, if we want. Or we can use a different name. The calling code doesn't have to know anything about how the function is written, or what names it uses for things.1
We can use the value directly to call another function: for example, print(foo()).2 We can return the value directly: simply return 'hello world', without assigning to x. (Again: we are returning a value, not a variable.)
The function can only return once each time it is called. return terminates the function - again, we just determined the result of the calculation, so there is no reason to calculate any further. If we want to return multiple pieces of information, therefore, we will need to come up with a single object (in Python, "value" and "object" are effectively synonyms; this doesn't work out so well for some other languages.)
We can make a tuple right on the return line; or we can use a dictionary, a namedtuple (Python 2.6+), a types.simpleNamespace (Python 3.3+), a dataclass (Python 3.7+), or some other class (perhaps even one we write ourselves) to associate names with the values that are being returned; or we can accumulate values from a loop in a list; etc. etc. The possibilities are endless..
On the other hand, the function returns whether you like it or not (unless an exception is raised). If it reaches the end, it will implicitly return the special value None. You may or may not want to do it explicitly instead.
Indirect methods
Other than returning the result back to the caller directly, we can communicate it by modifying some existing object that the caller knows about. There are many ways to do that, but they're all variations on that same theme.
If you want the code to communicate information back this way, please just let it return None - don't also use the return value for something meaningful. That's how the built-in functionality works.
In order to modify that object, the called function also has to know about it, of course. That means, having a name for the object that can be looked up in a current scope. So, let's go through those in order:
Local scope: Modifying a passed-in argument
If one of our parameters is mutable, we can just mutate it, and rely on the caller to examine the change. This is usually not a great idea, because it can be hard to reason about the code. It looks like:
def called(mutable):
mutable.append('world')
def caller():
my_value = ['hello'] # a list with just that string
called(my_value)
# now it contains both strings
If the value is an instance of our own class, we could also assign to an attribute:
class Test:
def __init__(self, value):
self.value = value
def called(mutable):
mutable.value = 'world'
def caller():
test = Test('hello')
called(test)
# now test.value has changed
Assigning to an attribute does not work for built-in types, including object; and it might not work for some classes that explicitly prevent you from doing it.
Local scope: Modifying self, in a method
We already have an example of this above: setting self.value in the Test.__init__ code. This is a special case of modifying a passed-in argument; but it's part of how classes work in Python, and something we're expected to do. Normally, when we do this, the calling won't actually check for changes to self - it will just use the modified object in the next step of the logic. That's what makes it appropriate to write code this way: we're still presenting an interface, so the caller doesn't have to worry about the details.
class Example:
def __init__(self):
self._words = ['hello']
def add_word(self):
self._words.append('world')
def display(self):
print(*self.words)
x = Example()
x.add_word()
x.display()
In the example, calling add_word gave information back to the top-level code - but instead of looking for it, we just go ahead and call display.3
See also: Passing variables between methods in Python?
Enclosing scope
This is a rare special case when using nested functions. There isn't a lot to say here - it works the same way as with the global scope, just using the nonlocal keyword rather than global.4
Global scope: Modifying a global
Generally speaking, it is a bad idea to change anything in the global scope after setting it up in the first place. It makes code harder to reason about, because anything that uses that global (aside from whatever was responsible for the change) now has a "hidden" source of input.
If you still want to do it, the syntax is straightforward:
words = ['hello']
def add_global_word():
words.append('world')
add_global_word() # `words` is changed
Global scope: Assigning to a new or existing global
This is actually a special case of modifying a global. I don't mean that assignment is a kind of modification (it isn't). I mean that when you assign a global name, Python automatically updates a dict that represents the global namespace. You can get that dict with globals(), and you can modify that dict and it will actually impact what global variables exist. (I.e., the return from globals() is the dictionary itself, not a copy.)5
But please don't. That's even worse of an idea than the previous one. If you really need to get the result from your function by assigning to a global variable, use the global keyword to tell Python that the name should be looked up in the global scope:
words = ['hello']
def replace_global_words():
global words
words = ['hello', 'world']
replace_global_words() # `words` is a new list with both words
Global scope: Assigning to or modifying an attribute of the function itself
This is a rare special case, but now that you've seen the other examples, the theory should be clear. In Python, functions are mutable (i.e. you can set attributes on them); and if we define a function at top level, it's in the global namespace. So this is really just modifying a global:
def set_own_words():
set_own_words.words = ['hello', 'world']
set_own_words()
print(*set_own_words.words)
We shouldn't really use this to send information to the caller. It has all the usual problems with globals, and it's even harder to understand. But it can be useful to set a function's attributes from within the function, in order for the function to remember something in between calls. (It's similar to how methods remember things in between calls by modifying self.) The functools standard library does this, for example in the cache implementation.
Builtin scope
This doesn't work. The builtin namespace doesn't contain any mutable objects, and you can't assign new builtin names (they'll go into the global namespace instead).
Some approaches that don't work in Python
Just calculating something before the function ends
In some other programming languages, there is some kind of hidden variable that automatically picks up the result of the last calculation, every time something is calculated; and if you reach the end of a function without returning anything, it gets returned. That doesn't work in Python. If you reach the end without returning anything, your function returns None.
Assigning to the function's name
In some other programming languages, you are allowed (or expected) to assign to a variable with the same name as the function; and at the end of the function, that value is returned. That still doesn't work in Python. If you reach the end without returning anything, your function still returns None.
def broken():
broken = 1
broken()
print(broken + 1) # causes a `TypeError`
It might seem like you can at least use the value that way, if you use the global keyword:
def subtly_broken():
global subtly_broken
subtly_broken = 1
subtly_broken()
print(subtly_broken + 1) # 2
But this, of course, is just a special case of assigning to a global. And there's a big problem with it - the same name can't refer to two things at once. By doing this, the function replaced its own name. So it will fail next time:
def subtly_broken():
global subtly_broken
subtly_broken = 1
subtly_broken()
subtly_broken() # causes a `TypeError`
Assigning to a parameter
Sometimes people expect to be able to assign to one of the function's parameters, and have it affect a variable that was used for the corresponding argument. However, this does not work:
def broken(words):
words = ['hello', 'world']
data = ['hello']
broken(data) # `data` does not change
Just like how Python returns values, not variables, it also passes values, not variables. words is a local name; by definition the calling code doesn't know anything about that namespace.
One of the working methods that we saw is to modify the passed-in list. That works because if the list itself changes, then it changes - it doesn't matter what name is used for it, or what part of the code uses that name. However, assigning a new list to words does not cause the existing list to change. It just makes words start being a name for a different list.
For more information, see How do I pass a variable by reference?.
1 At least, not for getting the value back. If you want to use keyword arguments, you need to know what the keyword names are. But generally, the point of functions is that they're an abstraction; you only need to know about their interface, and you don't need to think about what they're doing internally.
2 In 2.x, print is a statement rather than a function, so this doesn't make an example of calling another function directly. However, print foo() still works with 2.x's print statement, and so does print(foo()) (in this case, the extra parentheses are just ordinary grouping parentheses). Aside from that, 2.7 (the last 2.x version) has been unsupported since the beginning of 2020 - which was nearly a 5 year extension of the normal schedule. But then, this question was originally asked in 2010.
3Again: if the purpose of a method is to update the object, don't also return a value. Some people like to return self so that you can "chain" method calls; but in Python this is considered poor style. If you want that kind of "fluent" interface, then instead of writing methods that update self, write methods that create a new, modified instance of the class.
4 Except, of course, that if we're modifying a value rather than assigning, we don't need either keyword.
5 There's also a locals() that gives you a dict of local variables. However, this cannot be used to make new local variables - the behaviour is undefined in 2.x, and in 3.x the dict is created on the fly and assigning to it has no effect. Some of Python's optimizations depend on the local variables for a function being known ahead of time.
>>> def foo():
return 'hello world'
>>> x = foo()
>>> x
'hello world'
You can use global statement and then achieve what you want without returning value from
the function. For example you can do something like below:
def foo():
global x
x = "hello world"
foo()
print x
The above code will print "hello world".
But please be warned that usage of "global" is not a good idea at all and it is better to avoid usage that is shown in my example.
Also check this related discussion on about usage of global statement in Python.
Suppose I have a function like:
def foo():
x = 'hello world'
How do I get the function to return x, in such a way that I can use it as the input for another function or use the variable within the body of a program? I tried using return and then using the x variable in another function, but I get a NameError that way.
For the specific case of communicating information between methods in the same class, it is often best to store the information in self. See Passing variables between methods in Python? for details.
def foo():
x = 'hello world'
return x # return 'hello world' would do, too
foo()
print(x) # NameError - x is not defined outside the function
y = foo()
print(y) # this works
x = foo()
print(x) # this also works, and it's a completely different x than that inside
# foo()
z = bar(x) # of course, now you can use x as you want
z = bar(foo()) # but you don't have to
Effectively, there are two ways: directly and indirectly.
The direct way is to return a value from the function, as you tried, and let the calling code use that value. This is normally what you want. The natural, simple, direct, explicit way to get information back from a function is to return it. Broadly speaking, the purpose of a function is to compute a value, and return signifies "this is the value we computed; we are done here".
Directly using return
The main trick here is that return returns a value, not a variable. So return x does not enable the calling code to use x after calling the function, and does not modify any existing value that x had in the context of the call. (That's presumably why you got a NameError.)
After we use return in the function:
def example():
x = 'hello world'
return x
we need to write the calling code to use the return value:
result = example()
print(result)
The other key point here is that a call to a function is an expression, so we can use it the same way that we use, say, the result of an addition. Just as we may say result = 'hello ' + 'world', we may say result = foo(). After that, result is our own, local name for that string, and we can do whatever we want with it.
We can use the same name, x, if we want. Or we can use a different name. The calling code doesn't have to know anything about how the function is written, or what names it uses for things.1
We can use the value directly to call another function: for example, print(foo()).2 We can return the value directly: simply return 'hello world', without assigning to x. (Again: we are returning a value, not a variable.)
The function can only return once each time it is called. return terminates the function - again, we just determined the result of the calculation, so there is no reason to calculate any further. If we want to return multiple pieces of information, therefore, we will need to come up with a single object (in Python, "value" and "object" are effectively synonyms; this doesn't work out so well for some other languages.)
We can make a tuple right on the return line; or we can use a dictionary, a namedtuple (Python 2.6+), a types.simpleNamespace (Python 3.3+), a dataclass (Python 3.7+), or some other class (perhaps even one we write ourselves) to associate names with the values that are being returned; or we can accumulate values from a loop in a list; etc. etc. The possibilities are endless..
On the other hand, the function returns whether you like it or not (unless an exception is raised). If it reaches the end, it will implicitly return the special value None. You may or may not want to do it explicitly instead.
Indirect methods
Other than returning the result back to the caller directly, we can communicate it by modifying some existing object that the caller knows about. There are many ways to do that, but they're all variations on that same theme.
If you want the code to communicate information back this way, please just let it return None - don't also use the return value for something meaningful. That's how the built-in functionality works.
In order to modify that object, the called function also has to know about it, of course. That means, having a name for the object that can be looked up in a current scope. So, let's go through those in order:
Local scope: Modifying a passed-in argument
If one of our parameters is mutable, we can just mutate it, and rely on the caller to examine the change. This is usually not a great idea, because it can be hard to reason about the code. It looks like:
def called(mutable):
mutable.append('world')
def caller():
my_value = ['hello'] # a list with just that string
called(my_value)
# now it contains both strings
If the value is an instance of our own class, we could also assign to an attribute:
class Test:
def __init__(self, value):
self.value = value
def called(mutable):
mutable.value = 'world'
def caller():
test = Test('hello')
called(test)
# now test.value has changed
Assigning to an attribute does not work for built-in types, including object; and it might not work for some classes that explicitly prevent you from doing it.
Local scope: Modifying self, in a method
We already have an example of this above: setting self.value in the Test.__init__ code. This is a special case of modifying a passed-in argument; but it's part of how classes work in Python, and something we're expected to do. Normally, when we do this, the calling won't actually check for changes to self - it will just use the modified object in the next step of the logic. That's what makes it appropriate to write code this way: we're still presenting an interface, so the caller doesn't have to worry about the details.
class Example:
def __init__(self):
self._words = ['hello']
def add_word(self):
self._words.append('world')
def display(self):
print(*self.words)
x = Example()
x.add_word()
x.display()
In the example, calling add_word gave information back to the top-level code - but instead of looking for it, we just go ahead and call display.3
See also: Passing variables between methods in Python?
Enclosing scope
This is a rare special case when using nested functions. There isn't a lot to say here - it works the same way as with the global scope, just using the nonlocal keyword rather than global.4
Global scope: Modifying a global
Generally speaking, it is a bad idea to change anything in the global scope after setting it up in the first place. It makes code harder to reason about, because anything that uses that global (aside from whatever was responsible for the change) now has a "hidden" source of input.
If you still want to do it, the syntax is straightforward:
words = ['hello']
def add_global_word():
words.append('world')
add_global_word() # `words` is changed
Global scope: Assigning to a new or existing global
This is actually a special case of modifying a global. I don't mean that assignment is a kind of modification (it isn't). I mean that when you assign a global name, Python automatically updates a dict that represents the global namespace. You can get that dict with globals(), and you can modify that dict and it will actually impact what global variables exist. (I.e., the return from globals() is the dictionary itself, not a copy.)5
But please don't. That's even worse of an idea than the previous one. If you really need to get the result from your function by assigning to a global variable, use the global keyword to tell Python that the name should be looked up in the global scope:
words = ['hello']
def replace_global_words():
global words
words = ['hello', 'world']
replace_global_words() # `words` is a new list with both words
Global scope: Assigning to or modifying an attribute of the function itself
This is a rare special case, but now that you've seen the other examples, the theory should be clear. In Python, functions are mutable (i.e. you can set attributes on them); and if we define a function at top level, it's in the global namespace. So this is really just modifying a global:
def set_own_words():
set_own_words.words = ['hello', 'world']
set_own_words()
print(*set_own_words.words)
We shouldn't really use this to send information to the caller. It has all the usual problems with globals, and it's even harder to understand. But it can be useful to set a function's attributes from within the function, in order for the function to remember something in between calls. (It's similar to how methods remember things in between calls by modifying self.) The functools standard library does this, for example in the cache implementation.
Builtin scope
This doesn't work. The builtin namespace doesn't contain any mutable objects, and you can't assign new builtin names (they'll go into the global namespace instead).
Some approaches that don't work in Python
Just calculating something before the function ends
In some other programming languages, there is some kind of hidden variable that automatically picks up the result of the last calculation, every time something is calculated; and if you reach the end of a function without returning anything, it gets returned. That doesn't work in Python. If you reach the end without returning anything, your function returns None.
Assigning to the function's name
In some other programming languages, you are allowed (or expected) to assign to a variable with the same name as the function; and at the end of the function, that value is returned. That still doesn't work in Python. If you reach the end without returning anything, your function still returns None.
def broken():
broken = 1
broken()
print(broken + 1) # causes a `TypeError`
It might seem like you can at least use the value that way, if you use the global keyword:
def subtly_broken():
global subtly_broken
subtly_broken = 1
subtly_broken()
print(subtly_broken + 1) # 2
But this, of course, is just a special case of assigning to a global. And there's a big problem with it - the same name can't refer to two things at once. By doing this, the function replaced its own name. So it will fail next time:
def subtly_broken():
global subtly_broken
subtly_broken = 1
subtly_broken()
subtly_broken() # causes a `TypeError`
Assigning to a parameter
Sometimes people expect to be able to assign to one of the function's parameters, and have it affect a variable that was used for the corresponding argument. However, this does not work:
def broken(words):
words = ['hello', 'world']
data = ['hello']
broken(data) # `data` does not change
Just like how Python returns values, not variables, it also passes values, not variables. words is a local name; by definition the calling code doesn't know anything about that namespace.
One of the working methods that we saw is to modify the passed-in list. That works because if the list itself changes, then it changes - it doesn't matter what name is used for it, or what part of the code uses that name. However, assigning a new list to words does not cause the existing list to change. It just makes words start being a name for a different list.
For more information, see How do I pass a variable by reference?.
1 At least, not for getting the value back. If you want to use keyword arguments, you need to know what the keyword names are. But generally, the point of functions is that they're an abstraction; you only need to know about their interface, and you don't need to think about what they're doing internally.
2 In 2.x, print is a statement rather than a function, so this doesn't make an example of calling another function directly. However, print foo() still works with 2.x's print statement, and so does print(foo()) (in this case, the extra parentheses are just ordinary grouping parentheses). Aside from that, 2.7 (the last 2.x version) has been unsupported since the beginning of 2020 - which was nearly a 5 year extension of the normal schedule. But then, this question was originally asked in 2010.
3Again: if the purpose of a method is to update the object, don't also return a value. Some people like to return self so that you can "chain" method calls; but in Python this is considered poor style. If you want that kind of "fluent" interface, then instead of writing methods that update self, write methods that create a new, modified instance of the class.
4 Except, of course, that if we're modifying a value rather than assigning, we don't need either keyword.
5 There's also a locals() that gives you a dict of local variables. However, this cannot be used to make new local variables - the behaviour is undefined in 2.x, and in 3.x the dict is created on the fly and assigning to it has no effect. Some of Python's optimizations depend on the local variables for a function being known ahead of time.
>>> def foo():
return 'hello world'
>>> x = foo()
>>> x
'hello world'
You can use global statement and then achieve what you want without returning value from
the function. For example you can do something like below:
def foo():
global x
x = "hello world"
foo()
print x
The above code will print "hello world".
But please be warned that usage of "global" is not a good idea at all and it is better to avoid usage that is shown in my example.
Also check this related discussion on about usage of global statement in Python.
What is the reason of having globals() function in Python? It only returns dictionary of global variables, which are already global, so they can be used anywhere... I'm asking only out of curiosity, trying to learn python.
def F():
global x
x = 1
def G():
print(globals()["x"]) #will return value of global 'x', which is 1
def H():
print(x) #will also return value of global 'x', which, also, is 1
F()
G()
H()
I can't really see the point here? Only time I would need it, was if I had local and global variables, with same name for both of them
def F():
global x
x = 1
def G():
x = 5
print(x) #5
print(globals()["x"]) #1
F()
G()
But you should never run into a problem of having two variables with same name, and needing to use them both within same scope.
Python gives the programmer a large number of tools for introspecting the running environment. globals() is just one of those, and it can be very useful in a debugging session to see what objects the global scope actually contains.
The rationale behind it, I'm sure, is the same as that of using locals() to see the variables defined in a function, or using dir to see the contents of a module, or the attributes of an object.
Coming from a C++ background, I can understand that these things seem unnecessary. In a statically linked, statically typed environment, they absolutely would be. In that case, it is known at compile time exactly what variables are global, and what members an object will have, and even what names are exported by another compilation unit.
In a dynamic language, however, these things are not fixed; they can change depending on how code is imported, or even during run time. For that reason at least, having access to this sort of information in a debugger can be invaluable.
It's also useful when you need to call a function using function's string name. For example:
def foo():
pass
function_name_as_string = 'foo'
globals()[function_name_as_string]() # foo().
You can pass the result of globals() and locals() to the eval, execfile and __import__ commands. Doing so creates a restricted environment for those commands to work in.
Thus, these functions exist to support other functions that benefit from being given an environment potentially different from the current context. You could, for example, call globals() then remove or add some variables before calling one of those functions.
globals() is useful for eval() -- if you want to evaluate some code that refers to variables in scope, those variables will either be in globals or locals.
To expand a bit, the eval() builtin function will interpret a string of Python code given to it. The signature is: eval(codeString, globals, locals), and you would use it like so:
def foo():
x = 2
y = eval("x + 1", globals(), locals())
print("y=" + y) # should be 3
This works, because the interpreter gets the value of x from the locals() dict of variables. You can of course supply your own dict of variables to eval.
It can be useful in 'declarative python'. For instance, in the below FooDef and BarDef are classes used to define a series of data structures which are then used by some package as its input, or its configuration. This allows you a lot of flexibility in what your input is, and you don't need to write a parser.
# FooDef, BarDef are classes
Foo_one = FooDef("This one", opt1 = False, valence = 3 )
Foo_two = FooDef("The other one", valence = 6, parent = Foo_one )
namelist = []
for i in range(6):
namelist.append("nm%03d"%i)
Foo_other = FooDef("a third one", string_list = namelist )
Bar_thing = BarDef( (Foo_one, Foo_two), method = 'depth-first')
Note that this configuration file uses a loop to build up a list of names which are part of the configuration of Foo_other. So, this configuration language comes with a very powerful 'preprocessor', with an available run-time library. In case you want to, say, find a complex log, or extract things from a zip file and base64 decode them, as part of generating your configuration (this approach is not recommended, of course, for cases where the input may be from an untrusted source...)
The package reads the configuration using something like the following:
conf_globals = {} # make a namespace
# Give the config file the classes it needs
conf_globals['FooDef']= mypkgconfig.FooDef # both of these are based ...
conf_globals['BarDef']= mypkgconfig.BarDef # ... on .DefBase
fname = "user.conf"
try:
exec open(fname) in conf_globals
except Exception:
...as needed...
# now find all the definitions in there
# (I'm assuming the names they are defined with are
# significant to interpreting the data; so they
# are stored under those keys here).
defs = {}
for nm,val in conf_globals.items():
if isinstance(val,mypkgconfig.DefBase):
defs[nm] = val
So, finally getting to the point, globals() is useful, when using such a package, if you want to mint a series of definitions procedurally:
for idx in range(20):
varname = "Foo_%02d" % i
globals()[varname]= FooDef("one of several", id_code = i+1, scale_ratio = 2**i)
This is equivalent to writing out
Foo_00 = FooDef("one of several", id_code = 1, scale_ratio=1)
Foo_01 = FooDef("one of several", id_code = 2, scale_ratio=2)
Foo_02 = FooDef("one of several", id_code = 3, scale_ratio=4)
... 17 more ...
An example of a package which obtains its input by gathering a bunch of definitions from a python module is PLY (Python-lex-yacc) http://www.dabeaz.com/ply/ -- in that case the objects are mostly function objects, but metadata from the function objects (their names, docstrings, and order of definition) also form part of the input. It's not such a good example for use of globals() . Also, it is imported by the 'configuration' - the latter being a normal python script -- rather than the other way around.
I've used 'declarative python' on a few projects I've worked on, and have had occasion to use globals() when writing configurations for those. You could certainly argue that this was due to a weakness in the way the configuration 'language' was designed. Use of globals() in this way doesn't produce very clear results; just results which might be easier to maintain than writing out a dozen nearly-identical statements.
You can also use it to give variables significance within the configuration file, according to their names:
# All variables above here starting with Foo_k_ are collected
# in Bar_klist
#
foo_k = [ v for k,v in globals().items() if k.startswith('Foo_k_')]
Bar_klist = BarDef( foo_k , method = "kset")
This method could be useful for any python module that defines a lot of tables and structures, to make it easier to add items to the data, without having to maintain the references as well.
It can also be used to get an instance of the class 'classname' from a
string:
class C:
def __init__(self, x):
self.x = x
print('Added new instance, x:', self.x)
def call(str):
obj = globals()[str](4)
return obj
c = call('C')
print(c.x)
It might be useful if you like to import module you just have built:
a.py
[...]
def buildModule():
[...code to build module...]
return __import__("somemodule")
[...]
b.py
from a import buildModule
def setup():
globals()["somemodule"] = buildModule()
Not really. Global variables Python really has are module-scoped variables.
# a.py
print(globals())
import b
b.tt()
# b.py
def tt():
print(globals())
run python a.py, at least two output of globals()['__name__'] is different.
Code here in cpython on Github shows it.
I did not notice in answers anything about using globals() to check if you have value set. Maybe you only set value if debugging or have forgotten to set one and want to avoid getting exception. Though locals() might be better solution in some of the cases to avoid accessing global scope and to access local scope only.
# DEBUG = True
if 'DEBUG' in globals():
print(f'We found debug flag and it has value {DEBUG}.')
else:
print(f'Debug flag was not found.')
Also you can use it with combination with get() to set the default value in case variable was not found
# VARIABLE = "Value of var"
my_var = globals().get("VARIABLE", "Value was not found")
print(my_var) # Prints: "Value was not found"
print(VARIABLE) # Raises NameError
VARIABLE = "Value of var"
my_var = globals().get("VARIABLE", "Value was not found")
print(my_var) # prints: "Value of var"
print(VARIABLE) # prints: "Value of var"
In many languages (and places) there is a nice practice of creating local scopes by creating a block like this.
void foo()
{
... Do some stuff ...
if(TRUE)
{
char a;
int b;
... Do some more stuff ...
}
... Do even more stuff ...
}
How can I implement this in python without getting the unexpected indent error and without using some sort of if True: tricks
Why do you want to create new scopes in python anyway?
The normal reason for doing it in other languages is variable scoping, but that doesn't happen in python.
if True:
a = 10
print a
In Python, scoping is of three types : global, local and class. You can create specialized 'scope' dictionaries to pass to exec / eval(). In addition you can use nested scopes
(defining a function within another). I found these to be sufficient in all my code.
As Douglas Leeder said already, the main reason to use it in other languages is variable scoping and that doesn't really happen in Python. In addition, Python is the most readable language I have ever used. It would go against the grain of readability to do something like if-true tricks (Which you say you want to avoid). In that case, I think the best bet is to refactor your code into multiple functions, or use a single scope. I think that the available scopes in Python are sufficient to cover every eventuality, so local scoping shouldn't really be necessary.
If you just want to create temp variables and let them be garbage collected right after using them, you can use
del varname
when you don't want them anymore.
If its just for aesthetics, you could use comments or extra newlines, no extra indentation, though.
Python has exactly two scopes, local and global. Variables that are used in a function are in local scope no matter what indentation level they were created at. Calling a nested function will have the effect that you're looking for.
def foo():
a = 1
def bar():
b = 2
print a, b #will print "1 2"
bar()
Still like everyone else, I have to ask you why you want to create a limited scope inside a function.
variables in list comprehension (Python 3+) and generators are local:
>>> i = 0
>>> [i+1 for i in range(10)]
[1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
>>> i
0
but why exactly do you need this?
A scope is a textual region of a
Python program where a namespace is
directly accessible. “Directly
accessible” here means that an
unqualified reference to a name
attempts to find the name in the
namespace...
Please, read the documentation and clarify your question.
btw, you don't need if(TRUE){} in C, a simple {} is sufficient.
As mentioned in the other answers, there is no analogous functionality in Python to creating a new scope with a block, but when writing a script or a Jupyter Notebook, I often (ab)use classes to introduce new namespaces for similar effect. For example, in a notebook where you might have a model "Foo", "Bar" etc. and related variables you might want to create a new scope to avoid having to reuse names like
model = FooModel()
optimizer = FooOptimizer()
...
model = BarModel()
optimizer = BarOptimizer()
or suffix names like
model_foo = ...
optimizer_foo = ...
model_bar = ...
optimizer_bar= ...
Instead you can introduce new namespaces with
class Foo:
model = ...
optimizer = ...
loss = ....
class Bar:
model = ...
optimizer = ...
loss = ...
and then access the variables as
Foo.model
Bar.optimizer
...
I find that using namespaces this way to create new scopes makes code more readable and less error-prone.
While the leaking scope is indeed a feature that is often useful,
I have created a package to simulate block scoping (with selective leaking of your choice, typically to get the results out) anyway.
from scoping import scoping
a = 2
with scoping():
assert(2 == a)
a = 3
b = 4
scoping.keep('b')
assert(3 == a)
assert(2 == a)
assert(4 == b)
https://pypi.org/project/scoping/
I would see this as a clear sign that it's time to create a new function and refactor the code. I can see no reason to create a new scope like that. Any reason in mind?
def a():
def b():
pass
b()
If I just want some extra indentation or am debugging, I'll use if True:
Like so, for arbitrary name t:
### at top of function / script / outer scope (maybe just big jupyter cell)
try: t
except NameError:
class t
pass
else:
raise NameError('please `del t` first')
#### Cut here -- you only need 1x of the above -- example usage below ###
t.tempone = 5 # make new temporary variable that definitely doesn't bother anything else.
# block of calls here...
t.temptwo = 'bar' # another one...
del t.tempone # you can have overlapping scopes this way
# more calls
t.tempthree = t.temptwo; del t.temptwo # done with that now too
print(t.tempthree)
# etc, etc -- any number of variables will fit into t.
### At end of outer scope, to return `t` to being 'unused'
del t
All the above could be in a function def, or just anyplace outside defs along a script.
You can add or del new elements to an arbitrary-named class like that at any point. You really only need one of these -- then manage your 'temporary' namespace as you like.
The del t statement isn't necessary if this is in a function body, but if you include it, then you can copy/paste chunks of code far apart from each other and have them work how you expect (with different uses of 't' being entirely separate, each use starting with the that try: t... block, and ending with del t).
This way if t had been used as a variable already, you'll find out, and it doesn't clobber t so you can find out what it was.
This is less error prone then using a series of random=named functions just to call them once -- since it avoids having to deal with their names, or remembering to call them after their definition, especially if you have to reorder long code.
This basically does exactly what you want: Make a temporary place to put things you know for sure won't collide with anything else, and which you are responsible for cleaning up inside as you go.
Yes, it's ugly, and probably discouraged -- you will be directed to decompose your work into a set of smaller, more reusable functions.
As others have suggested, the python way to execute code without polluting the enclosing namespace is to put it in a class or function. This presents a slight and usually harmless problem: defining the function puts its name in the enclosing namespace. If this causes harm to you, you can name your function using Python's conventional temporary variable "_":
def _():
polluting_variable = foo()
...
_() # Run the code before something overwrites the variable.
This can be done recursively as each local definition masks the definition from the enclosing scope.
This sort of thing should only be needed in very specific circumstances. An example where it is useful is when using Databricks' %run magic, which executes the contents of another notebook in the current notebook's global scope. Wrapping the child notebook's commands in temporary functions prevents them from polluting the global namespace.