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    Data Types
    import sys
    import cmath
    import math

    Numeric Data Types

    Integers

    a=10
    b=20
    c=30
    print(“a=%d address=%d type=%s” %(a,id(a),type(a)))
    print(“b=%d address=%d type=%s” %(b,id(b),type(b)))
    print(“c=%d address=%d type=%s” %(c,id(c),type(c)))

    Output:

    a=10 address=10914784 type=
    b=20 address=10915104 type=
    c=30 address=10915424 type=

    integer size can be dynamic

    a = 12345678
    b = 1234567898726512
    c = 9283787182749827498
    print(“a = %d address=%d type=%s size=%d”%(a,id(a),type(a),sys.getsizeof(a)))
    print(“b = %d address=%d type=%s size=%d”%(b,id(b),type(b),sys.getsizeof(b)))
    print(“c = %d address=%d type=%s size=%d”%(c,id(c),type(c),sys.getsizeof(c)))

    a = 12345678 address=140126022940752 type= size=28
    b = 1234567898726512 address=140126022940112 type= size=32
    c = 9283787182749827498 address=140126022314704 type= size=36

    Integer Pooling

    To fasten allocation and de-allocation of memory to ingeters, python uses dedicated memorypool for integers between -5 to +256.

    when integer values are diff the memory allocation is also diff


    a=10
    b=12
    c=14
    print(“a=%d address=%d type=%s”%(a,id(a),type(a)))
    print(“b=%d address=%d type=%s”%(b,id(b),type(b)))
    print(“c=%d address=%d type=%s”%(c,id(c),type(c)))

    When we have same data, with in (-5 to -256) then we do get same address

    d=100
    e=100
    f=1020
    g=1020
    print(“d=%d address=%d type=%s”%(d,id(d),type(d)))
    print(“e=%d address=%d type=%s”%(e,id(e),type(e)))
    print(“f=%d address=%d type=%s”%(f,id(f),type(f)))
    print(“g=%d address=%d type=%s”%(g,id(g),type(g)))

    a=10 address=10914784 type=
    b=12 address=10914848 type=
    c=14 address=10914912 type=
    d=100 address=10917664 type=
    e=100 address=10917664 type=
    f=1020 address=140126022940560 type=
    g=1020 address=140126022939504 type=