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 typing.NamedTuple
name: str
id: int = 3 # default value
employee = Employee(‘Guido’)
assert employee.id == 3
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 get_image_data(filename):
[snip]
return size, (format, version, compression), (width,height)
size, type, dimensions = get_image_data(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).