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Re:Exposing Python 3.6's Private Dict Version by ericfrederich on Tuesday May 30, 2017 @04:03PM (#14448109)
I watched an earlier version of Raymond's talk and I skimmed through the other one. One thing that I think they both mention is that to take advantage of some of these improvements you need to set every attribute any instance of your class will ever set on the __init__ method.

This is probably a good practice anyway. I'm curious now how I can test and see if I'm taking advantage of this or not. I wonder if using the attrs module will also make use of this new feature.

Re:Exposing Python 3.6's Private Dict Version by m_mueller on Wednesday May 31, 2017 @01:53AM (#14450651)
I'm starting to wonder whether it wouldn't be a better design to forget about classes for most use cases, instead only use namedtuples and have a bunch of functions defined that take one type of namedtuple in their first argument. You can easily bind this by doing my_applied_func = functools.partial(my_func, my_named_tuple). This design IMO has a few advantages compared to classes:

* __repr__ comes for free.

* converting all members to a list or dict comes for free.

* converting a list or dict TO a namedtuple comes for free.

* more restrictive in what you can do with data structures inside the namedtuple - may lead to a cleaner design where you think about pulling apart the data into multiple tuples at an earlier point in the prototype phase.

* You by design won't make functions into instance methods that depend on multiple data tuples.

* Need to extend a function to deal with different types of tuples? You now don't need to refactor an instance method into a first class function, instead just dispatch and be done.

* Inheritance can be solved with the above method as well. This may actually be more maintainable than class based inheritance, since you see all the logic for a specific function explicitely (or explicitely dispatched) in one place.

The only reason I can think of to still use a class: If you can heavily profit from inheritance or if you need to program against an "interface" like dict- or listlike behavior or comparison operators.

Re:Exposing Python 3.6's Private Dict Version by ericfrederich on Wednesday May 31, 2017 @07:56AM (#14451761)
A lot of your points are solved with attrs. I suggest reading up on it if you haven't already. http://www.attrs.org/en/stable/

I think organizing / refactoring a bunch of named tuples would be a mess. In one code base I maintain I switched a bunch of namedtuples to attrs classes and the code instantly became more readable / maintainable.

The downside to the namedtuple is that it's a tuple and can be unpacked as one.

for x, y in points: print x, y

# vs.

for p in points: print p.x, p.y

# ... now go and add a z to the point class and see what happens to your code.

Re:Exposing Python 3.6's Private Dict Version by m_mueller on Wednesday May 31, 2017 @09:38PM (#14457336)
I don't get your point about unpacking yet to be honest. Both your code examples work fine with namedtuples I think. Adding additional attributes is better in the second example, which is why it is to be preferred, but that works with namedtuples as far as I understand.
Re:Exposing Python 3.6's Private Dict Version by maxerickson on Wednesday May 31, 2017 @09:47PM (#14457367)
Adding a member to the tuple requires updating all code that unpacks it.

Adding an attribute doesn't impact any code that doesn't use the attribute.

Re:Exposing Python 3.6's Private Dict Version by m_mueller on Wednesday May 31, 2017 @10:10PM (#14457439)
Yes, that's why you usually don't use unpacking for a namedtuple. This works just fine without me adding additional 3rd party packages:

> from collections import namedtuple

> Point = namedtuple('Point', ['x', 'y'])

> points = [Point(3,4), Point(5,2)]

> for p in points:

> print(p.x, p.y)