Core Python Programming (2nd Edition)

4.5.3. Boolean
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.
Expressions may be linked together or negated using the Boolean logical operators and, or, and not, all
of which are Python keywords. These Boolean operations are in highest-to-lowest order of precedence in
Table 4.3. The not operator has the highest precedence and is immediately one level below all the
comparison operators. The and and or operators follow, respectively.