Factorial counts permutations of n distinct objects.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 | from bisect import bisect_left # Iterative Factorial in Python # # PURPOSE # Factorial counts permutations of n distinct objects. Iterative multiplication avoids # recursion and its call-stack overhead. # # METHOD # Start with the empty product one. Multiply successively by every integer from two through # n. After each multiplication the accumulator is the factorial of the current index. # # COMPLEXITY # O(n) multiplications and O(1) auxiliary space; arbitrary-precision arithmetic costs are # excluded. # # CONTRACT # n >= 0. For a portable signed 32-bit result use n <= 12. Factorial grows quickly. # Public APIs infer array lengths except in C, which accepts pointer/length pairs. Vertex # counts and matrix dimensions remain explicit. Arrays must contain signed 32-bit integers. # Sorted order, correct tree topology, and caller-owned data-structure invariants are # preconditions; checking them on every query would change query complexity. # Scalar and shape checks are included. Value-range checks are included where needed to # prevent invalid indexing or nontermination. Allocation sizes are capped at 4,000,000 # workspace entries. Arithmetic outside Python raises an error on 32-bit overflow; Python # uses arbitrary precision. Native allocation failures propagate. In-place outputs may be # partly updated after arithmetic failure. These are single-threaded, in-memory # implementations. # # LANGUAGE DETAILS # Python 3.9+: automatic lengths, native lists, arbitrary-precision arithmetic, and # bisect_left for LIS. Invalid scalar/shape inputs raise ValueError. Integer element types # and sorted/tree invariants remain caller preconditions. # # EXAMPLE # Expected return: 1. # Run: python example.py # Tests for this exact source artifact run before publication. The accompanying source # archive includes unit cases, runtime results, and source hashes. def alg_require(condition): if not condition: raise ValueError("invalid algorithm input; see contract") def alg_size(n): alg_require(0 <= n <= 4000000) return n def factorial(n: int) -> int: alg_require(type(n) is int and -2147483648 <= n <= 2147483647) alg_require(n >= 0 and n <= 1000000) alg_require(n >= 0 and n <= 12) result: int = 1 i: int = 2 while i <= n: result *= i i += 1 return result n = 0 result = factorial(n) print(result) |