Standard type operators in python

In the above examples with the foo1 and foo2 objects, you will notice that we use floating point values rather than integers. The reason for this is although integers and strings are immutable objects, Python sometimes caches them to be more efficient. This would have caused the examples to appear that Python is not creating a new object when it should have. For example:

>>> a = 1 >>> id[a] 8402824 >>> b = 1 >>> id[b] 8402824 >>> >>> c = 1.0 >>> id[c] 8651220 >>> d = 1.0 >>> id[d] 8651204

In the above example, a and b reference the same integer object, but c and d do not reference the same float object. If we were purists, we would want a and b to work just like c and d because we really did ask to create a new integer object rather than an alias, as in b = a.

Python caches or interns only simple integers that it believes will be used frequently in any Python application. At the time of this writing, Python interns integers in the range[-1, 100] but this is subject to change, so do not code your application to expect this.

In Python 2.3, the decision was made to no longer intern strings that do not have at least one reference outside of the "interned strings table." This means that without that reference, interned strings are no longer immortal and subject to garbage collection like everything else. A BIF introduced in 1.5 to request interning of strings, intern[], has now been deprecated as a result.

not expr

Logical NOT of expr [negation]

expr1 and expr2

Logical AND of expr1 and expr2 [conjunction]

expr1 orexpr2

Logical OR of expr1 and expr2 [disjunction]