The python documentation frequently speaks of "containers". E.g. :
If check_circular is False (default: True), then the circular reference check for container types will be skipped and a circular reference will result in an OverflowError (or worse).
But I can't find any official definition of containers, neither a list of them.
For Python 2.7.3:
Checked builtin types which are containers:
(isinstance(object, collections.Container) returns True)
Containers which have a __contains__ method defined:
Containers which do not have a __contains__ method defined:
Checked builtin types which are not containers:
(isinstance(object, collections.Container) returns False):
Tell me which other builtin types you have checked for isinstance(object, collections.Container) and I'll add them to the list.
In computer science, a container is a class or a data structure whose instances are collections of other objects. In other words, they store objects in an organized way that follows specific access rules. The size of the container depends on the number of objects (elements) it contains.
Variables are containers in which data values can be stored within the computer's memory. They have a name, which is also referred to as an address.
A list can hold strings, other lists, numbers. To tell Python that a thing is a list, use square brackets around it and separate items by a comma. This is a full list of stuff you can do to a list.
Containers are any object that holds an arbitrary number of other objects. Generally, containers provide a way to access the contained objects and to iterate over them.
Examples of containers include tuple, list, set, dict; these are the built-in containers. More container types are available in the collections module.
Strictly speaking, the collections.abc.Container abstract base class (collections.Container in Python2) holds for any type that supports the in operator via the __contains__ magic method; so if you can write x in y then y is usually a container, but not always: an important point of difference between containers and general iterables is that when iterated over, containers will return existing objects that they hold a reference to, while generators and e.g. file objects will create a new object each time. This has implications for garbage collection and deep object traversal (e.g. deepcopy and serialisation).
As an example, iter(lambda: random.choice(range(6)), 0) supports the in operator, but it is certainly not a container!
The intent of the Collections.abc.Container abstract base class in only considering the __contains__ magic method and not other ways of supporting the in operator is that a true container should be able to test for containment in a single operation and without observably changing internal state. Since Collections.abc.Container defines __contains__ as an abstract method, you are guaranteed that if isinstance(x, collections.abc.Container) then x supports the in operator.
In practice, then, all containers will have the __contains__ magic method. However, when testing whether an object is a container you should use isinstance(x, collections.abc.Container) for clarity and for forward compatibility should the Container subclass check ever be changed.
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