Named tuples were added in 2.6 for this purpose. Also see os.stat for a similar builtin example.

>>> import collections
>>> Point = collections.namedtuple('Point', ['x', 'y'])
>>> p = Point(1, y=2)
>>> p.x, p.y
1 2
>>> p[0], p[1]
1 2

In recent versions of Python 3 (3.6+, I think), the new typing library got the NamedTuple class to make named tuples easier to create and more powerful. Inheriting from typing.NamedTuple lets you use docstrings, default values, and type annotations.

Example (From the docs):

class Employee(NamedTuple):  # inherit from collections.NamedTuple
    name: str
    id: int = 3  # default value

employee = Employee('Guido')
assert employee.id == 3

• This is only correct answer because it is the only canonical structure that the OP did not consider and because it addresses his problem of managing long tuples. Should be marked as accepted. - Andy Terra
• Well, the design rationale for namedtuple is having a smaller memory footprint for mass results (long lists of tuples, such as results of DB queries). For individual items (if the function in question is not called often) dictionaries and classes are just fine as well. But namedtuples are a nice/nicer solution in this case as well. - Lutz Prechelt
• @wom you can do it on one line: p=collections.namedtuple('point','x,y')(1,2) - Dave X
• @wom: Don't do this. Python makes no effort to uniquify namedtuple definitions (each call creates a new one), creating the namedtuple class is relatively expensive in both CPU and memory, and all class definitions intrinsically involve cyclic references (so on CPython, you're waiting for a cyclic GC run for them to be released). It also makes it impossible to pickle the class (and therefore, impossible to use instances with multiprocessing in most cases). Each creation of the class on my 3.6.4 x64 consumes ~0.337 ms, and occupies just under 1 KB of memory, killing any instance savings. - ShadowRanger
• @SergeStroobandt - This is part of the standard library, just not a builtin. You don't need to worry that it might not be installed on another system with Python >= 2.6. Or do you just object to the extra line of code? - Justin

For small projects I find it easiest to work with tuples. When that gets too hard to manage (and not before) I start grouping things into logical structures, however I think your suggested use of dictionaries and ReturnValue objects is wrong (or too simplistic).

Returning a dictionary with keys y0, y1, y2 etc doesn't offer any advantage over tuples. Returning a ReturnValue instance with properties .y0 .y1 .y2 etc doesn't offer any advantage over tuples either. You need to start naming things if you want to get anywhere, and you can do that using tuples anyway:

def getImageData(filename):
  [snip]
  return size, (format, version, compression), (width,height)
size, type, dimensions = getImageData(x)

IMHO, the only good technique beyond tuples is to return real objects with proper methods and properties, like you get from re.match() or open(file).

• Question - is there any difference between size, type, dimensions = getImageData(x) and (size, type, dimensions) = getImageData(x)? I.e., does wrapping left-hand-side of a tupled assignment make any difference? - Reb.Cabin
• @Reb.Cabin There is no difference. Tuple is identified by comma and the use of parentheses is just to group things together. For example(1) is a int while (1,) or 1, is a tuple. - phil
• Re "returning a dictionary with keys y0, y1, y2 etc doesn't offer any advantage over tuples": dictionary has the advantage in that you can add fields to the returned dictionary without breaking existing code. - ostrokach

A lot of the answers suggest you need to return a collection of some sort, like a dictionary or a list. You could leave off the extra syntax and just write out the return values, comma-separated. Note: this technically returns a tuple.

def f():
    return True, False
x, y = f()
print(x)
print(y)

gives:

True
False

• You are still returning a collection. It is a tuple. I prefer parenthesis to make it more explicit. Try this:type(f()) returns <class 'tuple'>. - Igor
• @Igor: There is no reason to make the tuple aspect explicit; it's not really important that you're returning a tuple, this is the idiom for returning multiple values period. Same reason you omit the parens with the swap idiom, x, y = y, x, multiple initialization x, y = 0, 1, etc.; sure, it makes tuples under the hood, but there is no reason to make that explicit, since the tuples aren't the point at all. The Python tutorial introduces multiple assignment long before it even touches on tuples. - ShadowRanger

I vote for the dictionary.

I find that if I make a function that returns anything more than 2-3 variables I'll fold them up in a dictionary. Otherwise I tend to forget the order and content of what I'm returning.

Also, introducing a 'special' structure makes your code more difficult to follow. (Someone else will have to search through the code to find out what it is)

If your concerned about type look up, use descriptive dictionary keys, for example, 'x-values list'.

def g(x):
  y0 = x + 1
  y1 = x * 3
  y2 = y0 ** y3
  return {'y0':y0, 'y1':y1 ,'y2':y2 }

• after many years of programming, I tend toward what ever the structure of the data and function is required. Function first, you can always refactor as is necessary. - monkut
• How would we get the values within the dictionary without calling the function multiple times? For example, if I want to use y1 and y3 in a different function? - Matt
• assign the results to a separate variable. result = g(x); other_function(result) - monkut
• @monkut yes. This way also allows to pass result to several functions, which take different args from result, without having to specifically reference particular parts of the result every time. - Gnudiff

Another option would be using generators:

>>> def f(x):
        y0 = x + 1
        yield y0
        yield x * 3
        yield y0 ** 4


>>> a, b, c = f(5)
>>> a
6
>>> b
15
>>> c
1296

Although IMHO tuples are usually best, except in cases where the values being returned are candidates for encapsulation in a class.

• This seems to be the cleanest solution, and has a clean syntax. Are there any downsides to this? If you don't use all the returns, are there 'unspent' yields waiting to hurt you? - Jiminion
• This may be "clean", but it doesn't seem intuitive at all. How would someone who's never encountered this pattern before know that doing automatic tuple unpacking would trigger each yield? - CoreDumpError

I prefer to use tuples whenever a tuple feels "natural"; coordinates are a typical example, where the separate objects can stand on their own, e.g. in one-axis only scaling calculations, and the order is important. Note: if I can sort or shuffle the items without an adverse effect to the meaning of the group, then I probably shouldn't use a tuple.

I use dictionaries as a return value only when the grouped objects aren't always the same. Think optional email headers.

For the rest of the cases, where the grouped objects have inherent meaning inside the group or a fully-fledged object with its own methods is needed, I use a class.

I prefer

def g(x):
  y0 = x + 1
  y1 = x * 3
  y2 = y0 ** y3
  return {'y0':y0, 'y1':y1 ,'y2':y2 }

it seems everything else is just extra code to do the same thing.

• Tuples are easier to unpack: y0, y1, y2 = g() with a dict you have to do: result = g() y0, y1, y2 = result.get('y0'), result.get('y1'), result.get('y2') which is a little bit ugly. Each solution has its 'pluses' and its 'minuses'. - Oli

>>> def func():
...    return [1,2,3]
...
>>> a,b,c = func()
>>> a
1
>>> b
2
>>> c
3

• @edouard No it doesn't, it returns a tuple not a list. - Simon Hibbs
• destructuring is the argument for returning lists in my opinion - semiomant

Python's tuples, dicts, and objects offer the programmer a smooth tradeoff between formality and convenience for small data structures ("things"). For me, the choice of how to represent a thing is dictated mainly by how I'm going to use the structure. In C++, it's a common convention to use struct for data-only items and class for objects with methods, even though you can legally put methods on a struct; my habit is similar in Python, with dict and tuple in place of struct.

For coordinate sets, I'll use a tuple rather than a point class or a dict (and note that you can use a tuple as a dictionary key, so dicts make great sparse multidimensional arrays).

If I'm going to be iterating over a list of things, I prefer unpacking tuples on the iteration:

for score,id,name in scoreAllTheThings():
    if score > goodScoreThreshold:
        print "%6.3f #%6d %s"%(score,id,name)

...as the object version is more cluttered to read:

for entry in scoreAllTheThings():
    if entry.score > goodScoreThreshold:
        print "%6.3f #%6d %s"%(entry.score,entry.id,entry.name)

...let alone the dict.

for entry in scoreAllTheThings():
    if entry['score'] > goodScoreThreshold:
        print "%6.3f #%6d %s"%(entry['score'],entry['id'],entry['name'])

If the thing is widely used, and you find yourself doing similar non-trivial operations on it in multiple places in the code, then it's usually worthwhile to make it a class object with appropriate methods.

Finally, if I'm going to be exchanging data with non-Python system components, I'll most often keep them in a dict because that's best suited to JSON serialization.

Generally, the "specialized structure" actually IS a sensible current state of an object, with its own methods.

class Some3SpaceThing(object):
  def __init__(self,x):
    self.g(x)
  def g(self,x):
    self.y0 = x + 1
    self.y1 = x * 3
    self.y2 = y0 ** y3

r = Some3SpaceThing( x )
r.y0
r.y1
r.y2

I like to find names for anonymous structures where possible. Meaningful names make things more clear.

+1 on S.Lott's suggestion of a named container class.

For python 2.6 and up, a named tuple provides a useful way of easily creating these container classes, and the results are "lightweight and require no more memory than regular tuples".

In languages like Python, I would usually use a dictionary as it involves less overhead than creating a new class.

However, if I find myself constantly returning the same set of variables, then that probably involves a new class that I'll factor out.

I would use a dict to pass and return values from a function:

Use variable form as defined in form.

form = {
    'level': 0,
    'points': 0,
    'game': {
        'name': ''
    }
}


def test(form):
    form['game']['name'] = 'My game!'
    form['level'] = 2

    return form

>>> print(test(form))
{u'game': {u'name': u'My game!'}, u'points': 0, u'level': 2}

This is the most efficient way for me and for processing unit.

You have to pass just one pointer in and return just one pointer out.

You do not have to change functions' (thousands of them) arguments whenever you make a change in your code.

"Best" is a partially subjective decision. Use tuples for small return sets in the general case where an immutable is acceptable. A tuple is always preferable to a list when mutability is not a requirement.

For more complex return values, or for the case where formality is valuable (i.e. high value code) a named tuple is better. For the most complex case an object is usually best. However, it's really the situation that matters. If it makes sense to return an object because that is what you naturally have at the end of the function (e.g. Factory pattern) then return the object.

As the wise man said:

Premature optimization is the root of all evil (or at least most of it) in programming.