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The ordered sequential types are lists (dynamic arrays), tuples, and strings. All sequences are indexed positionally (0 through length - 1) and all but strings can contain any type of object, including multiple types in the same sequence. Both strings and tuples are immutable, making them perfect candidates for dictionary keys (see below).
In order to effectively implement variables of such types as array structures (with indexing done by pointer arithmetic), many languages restrict the indices to integer data types [6] [7] (or other types that can be interpreted as integers, such as bytes and enumerated types), and require that all elements have the same data type and storage size.
Some programming languages such as Lisp, Python, Perl, Haskell, Ruby and Raku use, or have an option to use, arbitrary-precision numbers for all integer arithmetic. Although this reduces performance, it eliminates the possibility of incorrect results (or exceptions) due to simple overflow.
If the variable has a signed integer type, a program may make the assumption that a variable always contains a positive value. An integer overflow can cause the value to wrap and become negative, which violates the program's assumption and may lead to unexpected behavior (for example, 8-bit integer addition of 127 + 1 results in −128, a two's ...
There are two types of divisions in Python: floor division (or integer division) // and floating-point / division. [103] Python uses the ** operator for exponentiation. Python uses the + operator for string concatenation. Python uses the * operator for duplicating a string a specified number of times.
In arbitrary-precision arithmetic, it is common to use long multiplication with the base set to 2 w, where w is the number of bits in a word, for multiplying relatively small numbers. To multiply two numbers with n digits using this method, one needs about n 2 operations.
This creational pattern [1] is frequently used for numbers and strings in different programming languages. In many object-oriented languages such as Python, even primitive types such as integer numbers are objects. To avoid the overhead of constructing a large number of integer objects, these objects get reused through interning.
In practice, most floating-point systems use base two, though base ten (decimal floating point) is also common. Floating-point arithmetic operations, such as addition and division, approximate the corresponding real number arithmetic operations by rounding any result that is not a floating-point number itself to a nearby floating-point number.