AlgoNest

AlgoNest is a Python toolkit for reusable algorithms, data structures, and small utility helpers. It gives developers a consistent, iterable-first API for common problems without rebuilding the same primitives each time.

Problem Statement

Many algorithm libraries are either classroom examples or narrow problem-specific snippets. AlgoNest is built as a practical toolkit instead: a collection of reusable building blocks for search, sorting, trees, graphs, dynamic programming, strings, math, and supporting utilities. It is useful when you want clean, typed implementations that are easy to import, compose, and reuse in exercises, interview prep, and real code.

Target Audience

AlgoNest is for:

• Students learning core data structures and algorithm patterns
• Developers preparing for interviews
• Engineers who want reliable reference implementations
• Maintainers who need compact reusable helpers instead of one-off snippets

Key Features

• arrays/: interval helpers, prefix sums, two pointers, Kadane, rotations, and matrix utilities
• search/: linear, binary, rotated, exponential, interpolation, jump, ternary, and 2D matrix search
• sort/: classic and advanced sorting implementations
• linked_list/: singly, doubly, and circular list structures plus linked-list algorithms
• stack_queue/: stacks, queues, deques, monotonic stack utilities, and expression helpers
• heap/: min/max heaps, priority queue, top-k helpers, merge helpers, and median tracking
• trees/: binary trees, BSTs, AVL trees, segment trees, Fenwick trees, traversals, views, and path helpers
• graphs/: traversal, shortest path, MST, SCC, bipartite, DSU, and representation helpers
• dynamic_programming/: Fibonacci, knapsack, coin change, LCS, LIS, edit distance, subset DP, and grid DP
• strings/: trie, anagram helpers, KMP, Rabin-Karp, Z algorithm, rolling hash, and palindrome helpers
• math/: number theory, modular arithmetic, combinatorics, matrix math, statistics, and bit manipulation
• backtracking/: combinations, permutations, subsets, and combination sum helpers
• greedy/: activity selection, fractional knapsack, jump-game helpers, and reachability logic
• nodes/ and utils/: shared node types, validation, testing helpers, I/O helpers, and debug utilities

Installation

pip install algonest

For local development:

pip install -e .

Quick Usage Examples

Search

from algonest import binary_search, search_2d_matrix

index = binary_search([1, 3, 5, 7, 9], 7)
location = search_2d_matrix([[1, 4, 7], [10, 13, 16]], 13)

Arrays

from algonest import max_subarray_sum, prefix_sum, range_sum

best = max_subarray_sum([-2, 1, -3, 4, -1, 2, 1, -5, 4])
prefix_values = prefix_sum([1, 2, 3, 4])
window_total = range_sum(prefix_values, 1, 3)

Trees

from algonest import BinaryTree

tree = BinaryTree()
for value in [5, 3, 8, 1, 4]:
	tree.insert(value)

height = tree.height()
balanced = tree.is_balanced()

Strings

from algonest import Trie, kmp_search

trie = Trie()
trie.insert("algo")
matches = kmp_search("ababcabcab", "abc")

Project Structure

AlgoNest/
|-- algonest/
|   |-- arrays/
|   |-- backtracking/
|   |-- dynamic_programming/
|   |-- graphs/
|   |-- greedy/
|   |-- heap/
|   |-- linked_list/
|   |-- math/
|   |-- nodes/
|   |-- search/
|   |-- sort/
|   |-- stack_queue/
|   |-- strings/
|   |-- trees/
|   `-- utils/
|-- benchmarks/
|-- docs/
|   `-- Project Structure.md
|-- tests/
|-- ALGONEST_API.md
|-- CONTRIBUTING.md
|-- CODE_OF_CONDUCT.md
|-- README.md
`-- pyproject.toml

Design Philosophy

AlgoNest is a toolkit, not a problem bank. The goal is to provide small, reusable implementations with consistent naming, clear signatures, and predictable behavior so the package is useful as a reference and as a foundation for real code.

Development Notes

• Tests are organized with pytest under tests/.
• Public API signatures are documented in ALGONEST_API.md.
• Contribution guidance is in CONTRIBUTING.md.

License

AlgoNest is released under the MIT License. See LICENSE for details.