Depth First Search Reachability in Python

Algorithms: Graph Algorithms November 15, 2026 python

DFS follows a branch deeply before returning to pending branches.

python
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from bisect import bisect_left

# Depth First Search Reachability in Python
#
# PURPOSE
# DFS follows a branch deeply before returning to pending branches. An explicit stack avoids
# language recursion limits for reachability exploration.
#
# METHOD
# Push the source and mark it. Pop a vertex, count it, then mark and push each unseen
# neighbor. Marking when pushed bounds stack entries to at most n.
#
# COMPLEXITY
# O(n squared) time with a matrix and O(n) auxiliary space. Adjacency lists reduce traversal
# to O(V+E).
#
# CONTRACT
# Flattened n by n 0/1 matrix, n >= 1, valid source. Returns the number of reachable
# vertices INCLUDING source. Directed edges supported.
# 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: 3.
# 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 dfs_reachable(graph: list[int], n: int, source: int) -> int:
    alg_require(isinstance(graph, (list, tuple)) and len(graph) <= 1000000)
    alg_require(type(n) is int and -2147483648 <= n <= 2147483647)
    alg_require(type(source) is int and -2147483648 <= source <= 2147483647)
    alg_require(n >= 0 and n <= 1000000)
    alg_require(len(graph) == n * n)
    alg_require(n >= 1 and source >= 0 and (source < n))
    seen: list[int] = [0] * alg_size(n)
    stack: list[int] = [0] * alg_size(n)
    top: int = 1
    count: int = 0
    u: int = 0
    v: int = 0
    stack[0] = source
    seen[source] = 1
    while top > 0:
        top -= 1
        u = stack[top]
        count += 1
        v = 0
        while v < n:
            if graph[u * n + v] != 0 and seen[v] == 0:
                seen[v] = 1
                stack[top] = v
                top += 1
            v += 1
    return count

graph = [0, 1, 0, 0, 0, 1, 0, 0, 0]
n = 3
source = 0
result = dfs_reachable(graph, n, source)
print(result)