Data Structures in Python¶
by Alex Gaynor
Python is awesome because it implements basic data structures as described by Knuth.
Paraphrase: The Python core has read Knuth so we don’t have to!
- Use types idiomatically
- Sometimes you don’t get a choice
- Be efficient, when it doesn’t cost you anything
- sometimes you habe more than one concern to deal with. The standard lib can help!
- Don’t do more than you have to: collections.abc are there to help.
- list vs tuple
- list vs set
- set vs frozenset
list vs tuple¶
“I only use tuples if using a namedtuple would be equally appropriate”
Not a performance or mutability issue, but use them idiomatically
sets vs lists¶
- lists have an order, sets don’t
- sets must be hashable
- sets let you check for uniqueness super-fast
sets vs frozenset¶
new in 2.7
For when you have a dict that needs an order
OrderedDict([ ("name":Field), ("type":Field), ("state": Field), ])
- Fact: list.pop(0) and list.insert(0) are slow
- Good for in memory logs and such
- Array: Good for a bunch of types of the same sort
- heapq: Look into it.
Do It Yourself¶
When you have to do it yourself use collections.abc!
abstract base classes for extending collections
Because you don’t subclass dict ever!!!!
- Subclassing Python’s builtin containers tends not to behave as we want
- Subclassing the ABCs does
OrderedSet example: http://code.activestate.com/recipes/576694/