What exactly are "containers" in python? (And what are all the python container types?)
Question:
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.
Edit
For Python 2.7.3:
Checked builtin types which are containers:
(isinstance(object, collections.Container) returns True)
-
Containers which have a __contains__ method defined:
- All builtin sequence types: Lists, bytearrays, strings, unicode strings and
tuples.
- Dictionaries
- All builtin set types: sets and frozensets
-
Containers which do not have a __contains__ method defined:
- xrange objects
Checked builtin types which are not containers:
(isinstance(object, collections.Container) returns False):
- Int objects
- Float objects
- Long objects
- Boolean objects
- Module objects
- File objects
- Buffer objects
- The None object
Tell me which other builtin types you have checked for isinstance(object, collections.Container) and I’ll add them to the list.
Answers:
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.
According to http://docs.python.org/dev/library/collections.abc.html#module-collections.abc, the most general definition of a container is simply an object that implements __contains__. In general, Python concepts like “container” or “sequence” are not defined abstractly; they are “duck-typed” by their behavior. That is, a container is something that you can use the in operator on.
The Python builtin container types are tuple, list, dict, set, frozenset and str and unicode (or bytes and str in Python 3), as well as a couple other constructs that are technically types but are not commonly used outside of specific contexts (e.g., buffer objects and xrange objects). Additional container types are provided in the collections module.
Container are all python objects that contain other object like list or dict. The Container type is an ABC, it behave like an interface. A Container is a class that implements the __contains__ method.
Here is the doc
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.
Edit
For Python 2.7.3:
Checked builtin types which are containers:
(isinstance(object, collections.Container) returns True)
-
Containers which have a
__contains__method defined:- All builtin sequence types: Lists, bytearrays, strings, unicode strings and
tuples. - Dictionaries
- All builtin set types: sets and frozensets
- All builtin sequence types: Lists, bytearrays, strings, unicode strings and
-
Containers which do not have a
__contains__method defined:- xrange objects
Checked builtin types which are not containers:
(isinstance(object, collections.Container) returns False):
- Int objects
- Float objects
- Long objects
- Boolean objects
- Module objects
- File objects
- Buffer objects
- The None object
Tell me which other builtin types you have checked for isinstance(object, collections.Container) and I’ll add them to the 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.
According to http://docs.python.org/dev/library/collections.abc.html#module-collections.abc, the most general definition of a container is simply an object that implements __contains__. In general, Python concepts like “container” or “sequence” are not defined abstractly; they are “duck-typed” by their behavior. That is, a container is something that you can use the in operator on.
The Python builtin container types are tuple, list, dict, set, frozenset and str and unicode (or bytes and str in Python 3), as well as a couple other constructs that are technically types but are not commonly used outside of specific contexts (e.g., buffer objects and xrange objects). Additional container types are provided in the collections module.
Container are all python objects that contain other object like list or dict. The Container type is an ABC, it behave like an interface. A Container is a class that implements the __contains__ method.
Here is the doc