Subject
16 entries
Data Structures
Bookmarks
Algotree: Algorithm and Data Structure Reference
Algotree is a reference site for algorithms and data structures with implementations in Python, Java, C++, and Go — covering sorting, graph traversal, dynamic programming, and more. Targeted at students, interview prep, and developers filling knowledge gaps.
Algorithms and Data Structures for Massive Datasets
Manning 2021 textbook covering algorithms and data structures built for massive datasets — Bloom filters, HyperLogLog, Count-Min Sketch, LSH, and streaming algorithms. Practical treatment of how to handle data that won't fit in memory or where exact answers are too expensive.
Advanced Algorithms and Data Structures
Marcello La Rocca's Manning textbook on advanced algorithms and data structures, organized around practical problems like caching, nearest-neighbor search, clustering, and graph planarity. A useful reference for engineers who have outgrown intro-level algorithms and need principled solutions to real design challenges.
CRDTs: Conflict-free Replicated Data Types
crdt.tech is the canonical reference hub for Conflict-free Replicated Data Types — the data structures that enable real-time collaborative editing without central coordination. The math guarantees eventual consistency even when network partitions split collaborators.
Patterns to Ace Coding Interviews
A pattern-based framework for coding interview preparation — reduces hundreds of LeetCode problems to ~20 recognizable patterns. Knowing which pattern applies is usually harder than solving once the pattern is identified.
What's a Linked List, Anyway? (BaseCS)
The first part of Vaidehi Joshi's BaseCS series on linked lists — a beginner-friendly explanation of singly and doubly linked lists with illustrations. Part of a comprehensive CS fundamentals series written for self-taught developers.
The Complete FAANG Preparation Repository
A comprehensive GitHub repository for FAANG interview preparation — DSA problems, technical subject theory (OS, DBMS, networking, OOP), and curated question sets. One of the large open-source interview prep aggregators.
Indexing 1,600,000,000 Keys with Automata and Rust
Andrew Gallant's deep technical post on using finite state transducers to index 1.6 billion keys in a compact data structure — the basis for ripgrep and the fst crate. A masterclass in how the right data structure unlocks orders-of-magnitude improvements.
Sparse Matrices in SciPy
A visual explainer of sparse matrix formats in SciPy (COO, CSR, CSC, LIL, DOK) with animated illustrations showing how data is stored. Essential reading before working with high-dimensional feature matrices in ML or graph algorithms.
Using Python's bisect Module
A practical walkthrough of Python's bisect standard library module — binary search for maintaining sorted lists and efficient data binning. Covers two key use cases with code examples.
Labuladong Algorithm Book (English)
Labuladong's English-translated algorithm patterns book — a framework-first approach to competitive programming and interview preparation that teaches mental models for problem types rather than individual solutions. Popular for its emphasis on patterns over memorization.
Functional Performance with Core Data Structures — PyData SV 2014
Matthew Rocklin's PyData SV 2014 talk on functional performance with core data structures — showing how functional programming patterns and Python's built-in data structures enable high-performance computation without reaching for C extensions.
Advanced Data Structures in Python
Pypix overview of advanced data structures in Python beyond the built-in list/dict/set — covering heaps, tries, segment trees, and other structures that Python's standard library either implements partially or not at all.
Understanding Slices in Go Programming
Going Go Programming's deep explanation of slices in Go — the difference between arrays and slices, the three-field slice header, and the subtle bugs that emerge from sharing underlying arrays. Essential reading for anyone moving from C or Python to Go.
Software Development Final Exam Answers: Part 1
Colin Percival grades a software development final exam and finds most developers can recall what data structures do but not why they're useful in specific contexts — the gap between memorization and understanding. Average score: 15.2/25.
Suffix Trees in Computational Biology
A course page on suffix trees in computational biology from the University of Saskatchewan. Suffix trees are the data structure behind fast substring search in genomic sequences — O(n) construction, O(m) query — making genome-scale string matching tractable.