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Implementation of various data structures and algorithms in Go.Containers are either ordered or unordered. All ordered containers provide stateful iterators and some of them allow enumerable functions.

data-structure map tree set list stack iterator enumerable sort avl-tree red-black-tree b-tree binary-heap collections go-collectionGo-datastructures is a collection of useful, performant, and threadsafe Go datastructures.Interval tree for collision in n-dimensional ranges. Implemented via a red-black augmented tree. Extra dimensions are handled in simultaneous inserts/queries to save space although this may result in suboptimal time complexity. Intersection determined using bit arrays. In a single dimension, inserts, deletes, and queries should be in O(log n) time.

data-structure collections go-collectionBoom Filters are probabilistic data structures for processing continuous, unbounded streams. This includes Stable Bloom Filters, Scalable Bloom Filters, Counting Bloom Filters, Inverse Bloom Filters, Cuckoo Filters, several variants of traditional Bloom filters, HyperLogLog, Count-Min Sketch, and MinHash.Classic Bloom filters generally require a priori knowledge of the data set in order to allocate an appropriately sized bit array. This works well for offline processing, but online processing typically involves unbounded data streams. With enough data, a traditional Bloom filter "fills up", after which it has a false-positive probability of 1.

bloom-filter stable-bloom-filters cuckoo-filter probabilistic-programming counting-bloom-filters scalable-bloom-filters count-min-sketch data-stream filter data-structure collections go-collectionOverhauled to now include 120 challenges and solutions and added Anki flashcards.Also included are unit tested reference implementations of various data structures and algorithms.

algorithm data-structure development programming coding interview interview-questions interview-practice competitive-programmingRedis is an advanced key-value store. It is similar to memcached but the dataset is not volatile, and values can be strings, exactly like in memcached, but also lists, sets, and ordered sets. All this data types can be manipulated with atomic operations to push/pop elements, add/remove elements, perform server side union, intersection, difference between sets, and so forth. Redis supports different kind of sorting abilities.

database key-value key-value-store data-structure hyperloglogMinimal and clean example implementations of data structures and algorithms in Python 3.

algorithm competitive-programming data-structure interview algorithms sort search tree graph:pencil: Python / C++ 11 Solutions of All LeetCode Questions

leetcode cpp algorithm data-structure cpp11If you are a newbie of Git, please check this tutorial we have made. Please note, this repository is inspired from KrisYu, and here is the approve letter. However, it has been modified, added and improved to reflect our knowledge, wisdom and efforts.

leetcode algorithm leetcode-solutions data-structure interview coding hacker geeker offerBinarytree is a Python library which provides a simple API to generate, visualize, inspect and manipulate binary trees. It allows you to skip the tedious work of setting up test data, and dive straight into practising your algorithms. Heaps and BSTs (binary search trees) are also supported. You may need to use sudo depending on your environment.

python3 python2 python-3 python-2 python-library binary-trees binary-tree interview-practice interview learning practise python-3-5 algorithm data-structures data-structure heap heaps bst binary-search-treeAn improved version of HyperLogLog for the count-distinct problem, approximating the number of distinct elements in a multiset using 20-50% less space than other usual HyperLogLog implementations.This work is based on "Better with fewer bits: Improving the performance of cardinality estimation of large data streams - Qingjun Xiao, You Zhou, Shigang Chen".

data-structure collections go-collectionThe missing set collection for the Go language. Until Go has sets built-in...use this.I have to give some credit for helping seed the idea with this post on stackoverflow.

set threadsafe datastructures data-structure collections go-collectionPlease note, this repository is inspired from KrisYu, and here is the approve letter. However, it has been modified, added and improved to reflect our knowledge, wisdom and effort.

leetcode algorithm leetcode-solutions data-structure interview coding hacker geeker offerGoque provides embedded, disk-based implementations of stack and queue data structures. Motivation for creating this project was the need for a persistent priority queue that remained performant while growing well beyond the available memory of a given machine. While there are many packages for Go offering queues, they all seem to be memory based and/or standalone solutions that are not embeddable within an application.

stack queue data-structure collections leveldbA Bloom filter is a representation of a set of n items, where the main requirement is to make membership queries; i.e., whether an item is a member of a set.A Bloom filter has two parameters: m, a maximum size (typically a reasonably large multiple of the cardinality of the set to represent) and k, the number of hashing functions on elements of the set. (The actual hashing functions are important, too, but this is not a parameter for this implementation). A Bloom filter is backed by a BitSet; a key is represented in the filter by setting the bits at each value of the hashing functions (modulo m). Set membership is done by testing whether the bits at each value of the hashing functions (again, modulo m) are set. If so, the item is in the set. If the item is actually in the set, a Bloom filter will never fail (the true positive rate is 1.0); but it is susceptible to false positives. The art is to choose k and m correctly.

bloom bloom-filters bloom-filter data-structure collections go-collectionJudy is a general purpose dynamic array implemented as a C callable library. Judy's speed and memory usage are typically better than other data storage models and improves with very large data sets. Judy's key benefits are scalability, high performance, and memory efficiency. A Judy array is extensible and can scale up to a very large number of elements, bounded only by machine memory. Since Judy is designed as an unbounded array, the size of a Judy array is not pre-allocated but grows and shrinks dynamically with the array population.

arrays dynamic-arrays data-structure collectionsPlease note, this repository is inspired from KrisYu, and here is the approve letter. However, it has been modified, added and improved to reflect our knowledge, wisdom and effort.

leetcode algorithm leetcode-solutions data-structure interview codingData structure and relevant algorithms for extremely fast prefix/fuzzy string searching.

data-structure trie fuzzy-search string-searchThis is a go port of the Roaring bitmap data structure.Roaring bitmaps are used by several major systems such as Apache Lucene and derivative systems such as Solr and Elasticsearch, Metamarkets' Druid, LinkedIn Pinot, Netflix Atlas, Apache Spark, OpenSearchServer, Cloud Torrent, Whoosh, Pilosa, Microsoft Visual Studio Team Services (VSTS), and eBay's Apache Kylin.

roaring-bitmaps bitset compressed-bitset data-structureThis is an implementation of DataFrames, Series and data wrangling methods for the Go programming language. The API is still in flux so use at your own risk.The term DataFrame typically refers to a tabular dataset that can be viewed as a two dimensional table. Often the columns of this dataset refers to a list of features, while the rows represent a number of measurements. As the data on the real world is not perfect, DataFrame supports non measurements or NaN elements.

data-structure collections go-collectionPackage bitset implements bitsets, a mapping between non-negative integers and boolean values. It should be more efficient than map[uint] bool.It provides methods for setting, clearing, flipping, and testing individual integers.

bitset data-structure collections go-collection
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