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Some of the type descriptions below contain a paragraph listing ‘special attributes.’ These are attributes that provide access to the implementation and are not intended for general use. (The interpreter will then try the reflected operation, or some other fallback, depending on the operator.) Its truth value is true.
See These are created by numeric literals and returned as results by arithmetic operators and arithmetic built-in functions.
All data in a Python program is represented by objects or by relations between objects.
(In a sense, and in conformance to Von Neumann’s model of a “stored program computer,” code is also represented by objects.) .
The only types of values not acceptable as keys are values containing lists or dictionaries or other mutable types that are compared by value rather than by object identity, the reason being that the efficient implementation of dictionaries requires a key’s hash value to remain constant.
Types affect almost all aspects of object behavior.
(If the object contains references to other objects, these other objects may be mutable and may be changed; however, the collection of objects directly referenced by an immutable object cannot change.) The following types are immutable sequences: The items of a tuple are arbitrary Python objects.
Tuples of two or more items are formed by comma-separated lists of expressions.
You are at the mercy of the underlying machine architecture (and C or Java implementation) for the accepted range and handling of overflow.
Python does not support single-precision floating point numbers; the savings in processor and memory usage that are usually the reason for using these are dwarfed by the overhead of using objects in Python, so there is no reason to complicate the language with two kinds of floating point numbers.
It is understood that these resources are freed when the object is garbage-collected, but since garbage collection is not guaranteed to happen, such objects also provide an explicit way to release the external resource, usually a .