I have a function that most of the time should return a single value, but sometimes I need a second value returned from the function. Here I found how to return multiple values, but as most of the time I need only one of them I would like to write something like this:
def test_fun():
return 1,2
def test_call():
x = test_fun()
print x
but calling this results in
>>> test_call()
(1,2)
and when trying to return more than two, as in
def test_fun2():
return 1,2,3
def test_call2():
x,y = test_fun2()
print x,y
I get an error
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "my_module.py", line 47, in test_call2
x,y = test_fun2()
ValueError: too many values to unpack
I am thinking about something like in matlab, where x = test_fun() would result in x == 1 (while [x y] = test_fun() would also work as expected). Is something like that possible in python?
You can use star unpacking to gather all additional return values into a list:
x, *y = fun()
x will contain the first return value. y will be a list of the remaining values. y will be empty if there is only one return value. This particular example will only work if the function returns a tuple, even if there is only one value.
When fun always returns 1 or 2 values, you can just do
if y:
print(y[0])
else:
print('only one value')
If, on the other hand, you want to completely ignore the number of return values, do
*x = fun()
Now all the arguments will be gathered into the list. You can then print it with either
print(x)
or
print(*x)
The latter will pass each element as a separate argument, exactly as if you did
x, y, z = fun()
print(x, y, z)
The reason to use *x = fun() instead of just x = fun() is to get an error immediately when a function returns something that isn't a tuple. Think of it as an assertion to remind you to write fun properly.
Since this form of star unpacking only works in Python 3, your only option in Python 2 is to do
x = fun()
and to inspect the result manually.
There are several ways to get multiple return values.
Example 1:
def test_fun():
return 1,2
def test_call():
x, y = test_fun()
print x
print y
you will get correct output:
1
2
When you would like to ignore several return values, you can use * before a variable in python3.
Example 2:
def test_fun2():
return 1,2,3
def test_call2():
x, *y = test_fun2()
print x
print y
you will get the result:
1
(2, 3)
Related
def firstone():
x= 1
print(x)
def firsttwo():
y=1
print(y)
**D={firstone,firsttwo}** ***#Problem is here***
What can be done to run the last line properly? Any ideas?
You should return a value from your functions, if you just print(), their return would be None. If your goal is to create a dict when the output of firstone() is the key and the output of firsttwo() is the value:
Code:
def firstone():
return 1
def firsttwo():
return 1
d = {firstone(): firsttwo()}
Output:
{1: 1}
First you need to make sure your functions actually return a value. Change it from printing to returning. Then call those function in the dictionary (notice the parentheses around the function name?).
def firstone():
x= 1
return x
def firsttwo():
y=1
return y
d = {"firstone":firstone(),"firsttwo":firsttwo()}
I am using the numpy.random.choice module to generate an 'array' of choices based on an array of functions:
def f(x):
return np.sin(x)
def g(x):
return np.cos(x)
base=[f, g]
funcs=np.random.choice(base,size=2)
This code will produce an 'array' of 2 items referencing a function from the base array.
The reason for this post is, I have printed the outcome of funcs and recieved:
[<function f at 0x00000225AC94F0D0> <function f at 0x00000225AC94F0D0>]
Clearly this returns a reference to the functions in some form, not that I understand what that form is or how to manipulate it, this is where the problem comes in. I want to change the choice of function, so that it is no longer random and instead depends on some conditions, so it might be:
for i in range(2):
if testvar=='true':
choice[i] = 0
if testvar== 'false':
choice[i] = 1
This would return an array of indicies to be put in later function
The problem is, the further operations of the code (I think) require this previous form of function reference: [ ] as an input, instead of a simple array of 0,1 Indicies and I don't know how I can get an array of form [ ] by using if statements.
I could be completely wrong about the rest of the code requiring this input, but I don't know how I can amend it, so am hence posting it here. The full code is as follows: (it is a slight variation of code provided by #Attack68 on Evolving functions in python) It aims to store a function that is multiplied by a random function on each iteration and integrates accordingly. (I have put a comment on the code above the function that is causing the problem)
import numpy as np
import scipy.integrate as int
def f(x):
return np.sin(x)
def g(x):
return np.cos(x)
base = [f, g]
funcs = np.random.choice(base, size=2)
print(funcs)
#The below function is where I believe the [<function...>] input to be required
def apply(x, funcs):
y = 1
for func in funcs:
y *= func(x)
return y
print('function value at 1.5 ', apply(1.5, funcs))
answer = int.quad(apply, 1, 2, args=(funcs,))
print('integration over [1,2]: ', answer)
Here is my attempt of implementing a non-random event:
import numpy as np
import scipy.integrate as int
import random
def f(x):
return np.sin(x)
def g(x):
return np.cos(x)
base = [f, g]
funcs = list()
for i in range(2):
testvar=random.randint(0,100) #In my actual code, this would not be random but dependent on some other situation I have not accounted for here
if testvar>50:
func_idx = 0 # choose a np.random operation: 0=f, 1=g
else:
func_idx= 1
funcs.append(func_idx)
#funcs = np.random.choice(base, size=10)
print(funcs)
def apply(x, funcs):
y = 1
for func in funcs:
y *= func(x)
return y
print('function value at 1.5 ', apply(1.5, funcs))
answer = int.quad(apply, 1, 2, args=(funcs,))
print('integration over [1,2]: ', answer)
This returns the following error:
TypeError: 'int' object is not callable
If: You are trying to refactor your original code that operates on a list of randomly chosen functions to a version that operates with random indices which correspond to items in a list of functions. Refactor apply.
def apply(x,indices,base=base):
y = 1
for i in indices:
f = base[i]
y *= f(x)
return y
...this returns a reference to the functions in some form, not that I understand what that form is or how to manipulate it...
Functions are objects, the list contains a reference to the objects themselves. They can be used by either assigning them to a name then calling them or indexing the list and calling the object:
>>> def f():
... return 'f'
>>> def g():
... return 'g'
>>> a = [f,g]
>>> q = a[0]
>>> q()
'f'
>>> a[1]()
'g'
>>> for thing in a:
print(thing())
f
g
Or you can pass them around:
>>> def h(thing):
... return thing()
>>> h(a[1])
'g'
>>>
If you still want to use your function apply as-is, you need to keep your input a list of functions. Instead of providing a list of indices, you can use those indices to create your list of functions.
Instead of apply(1.5, funcs), try:
apply(1.5, [base(n) for n in funcs])
I want to write a python function like this:
def foo():
if x:
return y
else:
return y, z
Is it possible? If it is possible then how can I detect the number of return values?
It may be easier to modify the function to always return a 2-tuple:
def foo():
if x:
return y, None
else:
return y, z
or what I'd do absent compelling reasons why not:
def foo( z_default = None):
# plug in whatever default makes sense in place of None
# and the caller can override the default if he wants to
if x:
return y, z_default
else:
return y, z
Yes, it is possible. But when your if condition is false your function will return a tuple with y at index 0 and z at index 1. You can catch the return values in a tuple variable and check the number of returned values using len() function for the tuple.
Yes, it is highly possible:
def foo():
if x:
return y
else:
return y, z
result = foo()
the_number_of_return_values_of_foo_function = \
1 if type(result) is not tuple else len(result)
Good nights.
I am new to python. This might be a simple question, but if I have many functions that are dependent on each other how would I access lists from one function to use in another.
So...
def function_1():
list_1=[]
def function_2():
list_2= [2*x for x in list_1]
def function_3():
list_3= [x * y for x, y in zip(list_1, list_2)]
That is not the exact code but that is the idea of my problem. I would just put them all together in one function but I need them to be separate.
The correct way to do this would be to use a class. A class is an object that has internal variables (in your case, the three lists), and methods (functions that can access the internal methods). So, this would be:
class Foo(object):
def __init__(self, data=None):
self.list_1 = data if not data is None else []
def function_2():
self.list_2 = [2 * x for x in self.list_1]
And so on. For calling it:
foo = Foo() # list_1 is empty
foo2 = Foo([1,2,3]) # list_1 is not empty
foo2.function_2()
print foo2.list_2
# prints [2, 4, 6]
Make them arguments and return values:
def function_1():
return []
def function_2(list_1):
return [2*x for x in list_1]
def function_3(list_1, list_2):
return [x * y for x, y in zip(list_1, list_2)]
(this suggests that function_1 isn't much worth having...)
The exact way will depend on exactly how you want things to work, but here is a simple example:
def function_1():
return []
def function_2():
return [2*x for x in function_1()]
def function_3():
return [x * y for x, y in zip(function_1(), function_2())]
The key point is that functions do not generally just "do" things, they return things. If you have a value in one function that you want to use in another function, the first function should return that value. The second function should call the first function, and use its return value.
Functions are basically black boxes -- the outside world doesn't really know what goes on inside or what variables exist there. From the outside, other code only sees what goes in (the function's arguments) and what goes out (its return value).
So if your function computes some value that is to be used elsewhere, it should be returned as the result of the function.
E.g.,
def square(x):
return x * x
Takes a number, computes its square, and returns it.
Then you could do:
print(square(5))
and it will print 25.
So in your case you can return the lists and use them in the other functions, as the other answers showed:
def function_1():
return []
def function_2():
return [2*x for x in function_1()]
def function_3():
return [x * y for x, y in zip(function_1(), function_2())]
Imagine I've got a Python module with some function in it:
def sumvars(x, y, z):
s = x
s += y
s += z
return s
But sometimes I want to get results of some intermediate calculations (for example, I could have a function which reverses a matrix and would like to know the determinant which has been calculated as an intermediate step as well). Obviously, I wouldn't want to redo those calculations again if they were already done within that function.
My first idea is to return a dict:
def sumvars(x, y, z):
d = {}
s = x
d['first_step'] = s
s += y
d['second_step'] = s
s += z
d['final'] = s
return d
But I don't recall any functions in numpy or scipy which return dicts and so it seems like this might be not a good idea. (Why?) Also routinely I'll always have to type sumvars(x,y,z)['final'] for a default return value...
Another option I see is creating global variables but seems wrong having a bunch of them in my module, I would need to remember their names and in addition not being attached to the function itself looks like a bad design choice.
What would be the proper function design for such situation?
Generally when you have two different ways you want to return data, go ahead and make two different functions. "Flat is better than nested", after all. Just have one call the other so that you Don't Repeat Yourself.
For example, in the standard library, urllib.parse has parse_qs (which returns a dict) and parse_qsl (which returns a list). parse_qs just then calls the other:
def parse_qs(...):
parsed_result = {}
pairs = parse_qsl(qs, keep_blank_values, strict_parsing,
encoding=encoding, errors=errors)
for name, value in pairs:
if name in parsed_result:
parsed_result[name].append(value)
else:
parsed_result[name] = [value]
return parsed_result
Pretty straightforward. So in your example it seems fine to have
def sumvars(x, y, z):
return sumvars_with_intermediates(x, y, z).final
def sumvars_with_intermediates(x, y, z):
...
return my_namedtuple(final, first_step, second_step)
(I favor returning namedtuples instead of dicts from my APIs, it's just prettier)
Another obvious example is in re: re.findall is its own function, not some configuration flag to search.
Now, the standard library is a sprawling thing made by many authors, so you'll find counterexamples to every example. You'll far more often see the above pattern rather than one omnibus function that accepts some configuration flags, though, and I find it far more readable.
Put the common calculation into its own function as Jayanth Koushik recommended if that calculation can be named appropriately. If you want to return many values (an intermediate result and a final result) from a single function then a dict may be an overkill depending on what is your goal but in python it is much more natural to simply return a tuple if your function has many values to return:
def myfunc():
intermediate = 5
result = 6
return intermediate, result
# using the function:
intermediate, result = myfunc()
Not sure if function attributes is a good idea:
In [569]: def sumvars(x, y, z):
...: s = x
...: sumvars.first_step = s
...: s += y
...: sumvars.second_step = s
...: s += z
...: return s
In [570]: res=sumvars(1,2,3)
...: print res, sumvars.first_step, sumvars.second_step
...:
6 1 3
Note: as #BrenBarn mentioned, this idea is just like global variables, your previously calculated "intermediate results" could not be stored when you want to reuse them.
Just came up with this idea which could be a better solution:
def sumvars(x, y, z, mode = 'default'):
d = {}
s = x
d['first_step'] = s
s += y
d['second_step'] = s
s += z
d['final'] = s
if mode == 'default':
return s
else:
return d
I belive the proper solution is to use a class, to have a better grasp of what you are modeling. For example in the case of the Matrix, you could simply store the determinant in the "determinant" attribute.
Here is an example using your matrix example.
class Matrix:
determinant = 0
def calculate_determinant(self):
#calculations
return determinant
def some_method(self, args):
# some calculations here
self.determinant = self.calculate_determinant()
# other calculations
matrix = Matrix()
matrix.some_method(x, y, z)
print matrix.determinant
This also allows you to separate your method into simpler methods, like one for calculating the determinant of your matrix.
Another variation:
def sumvars(x, y, z, d=None):
s = x
if not d is None:
d['first_step'] = s
s += y
if not d is None:
d['second_step'] = s
s += z
return s
The function always returns the desired value without packing it into a tuple or dictionary. The intermediate results are still available, but only if requested. The call
sumvars(1, 2, 3)
just returns 6 without storing intermediate values. But the call
d = {}
sumvars(1, 2, 3, d)
returns the same answer 6 and inserts the intermediate calculations into the supplied dictionary.
Option 1. Make two separate functions.
Option 2. Use a generator:
>>> def my_func():
... yield 1
... yield 2
...
>>> result_gen = my_func()
>>> result_gen
<generator object my_func at 0x7f62a8449370>
>>> next(result_gen)
1
>>> next(result_gen)
2
>>> next(result_gen)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
StopIteration
>>>
Inspired by #zhangxaochen solution, here's my take on your problem using class attributes:
class MyClass():
def __init__(self):
self.i = 4
def f(self):
s = self.i
MyClass.first_step = s
print(MyClass.first_step)
s += self.i
MyClass.second_step = s
print(MyClass.second_step)
s += self.i
return s
def main():
x = MyClass()
print(x.f()) # print final s
print(x.first_step)
print(x.second_step)
print(MyClass.second_step)
Note: I included several prints to make it more explicit how attribute values can be retrieved.
Result:
4
8
12
4
8
8