Open Source Libraries
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Browse free open source Libraries and projects for Mac and Linux below. Use the toggles on the left to filter open source Libraries by OS, license, language, programming language, and project status.
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Build Securely on Azure with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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Dlib is a C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems.
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AlphaZero.jl
A generic, simple and fast implementation of Deepmind's AlphaZero
Beyond its much publicized success in attaining superhuman level at games such as Chess and Go, DeepMind's AlphaZero algorithm illustrates a more general methodology of combining learning and search to explore large combinatorial spaces effectively. We believe that this methodology can have exciting applications in many different research areas. Because AlphaZero is resource-hungry, successful open-source implementations (such as Leela Zero) are written in low-level languages (such as C++) and optimized for highly distributed computing environments. This makes them hardly accessible for students, researchers and hackers. Many simple Python implementations can be found on Github, but none of them is able to beat a reasonable baseline on games such as Othello or Connect Four. As an illustration, the benchmark in the README of the most popular of them only features a random baseline, along with a greedy baseline that does not appear to be significantly stronger. -
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Arduino FOC
Arduino FOC for BLDC and Stepper motors
We live in very exciting times 😃! BLDC motors are entering the hobby community more and more and many great projects have already emerged leveraging their far superior dynamics and power capabilities. BLDC motors have numerous advantages over regular DC motors but they have one big disadvantage, the complexity of control. Even though it has become relatively easy to design and manufacture PCBs and create our own hardware solutions for driving BLDC motors the proper low-cost solutions are yet to come. One of the reasons for this is the apparent complexity of writing the BLDC driving algorithms, Field oriented control (FOC) being an example of one of the most efficient ones. The solutions that can be found online are almost exclusively very specific for certain hardware configurations and the microcontroller architecture used. Additionally, most of the efforts at this moment are still channeled towards the high-power applications of the BLDC motors and proper low-cost FOC. -
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Python Outlier Detection
A Python toolbox for scalable outlier detection
PyOD is a comprehensive and scalable Python toolkit for detecting outlying objects in multivariate data. This exciting yet challenging field is commonly referred as outlier detection or anomaly detection. PyOD includes more than 30 detection algorithms, from classical LOF (SIGMOD 2000) to the latest COPOD (ICDM 2020) and SUOD (MLSys 2021). Since 2017, PyOD [AZNL19] has been successfully used in numerous academic researches and commercial products [AZHC+21, AZNHL19]. PyOD has multiple neural network-based models, e.g., AutoEncoders, which are implemented in both PyTorch and Tensorflow. PyOD contains multiple models that also exist in scikit-learn. It is possible to train and predict with a large number of detection models in PyOD by leveraging SUOD framework. A benchmark is supplied for select algorithms to provide an overview of the implemented models. In total, 17 benchmark datasets are used for comparison, which can be downloaded at ODDS. -
No-Nonsense Code-to-Cloud Security for Devs | AikidoAikido provides a unified security platform for developers, combining 12 powerful scans like SAST, DAST, and CSPM. AI-driven AutoFix and AutoTriage streamline vulnerability management, while runtime protection blocks attacks.
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The fstrcmp project provides a shared library for making fuzzy string comparisons, and also provides an fstrcmp command for use in shell scripts.
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ViennaCL
Linear algebra and solver library using CUDA, OpenCL, and OpenMP
ViennaCL provides high level C++ interfaces for linear algebra routines on CPUs and GPUs using CUDA, OpenCL, and OpenMP. The focus is on generic implementations of iterative solvers often used for large linear systems and simple integration into existing projects. -
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C# Algorithms
Plug-and-play class-library project of standard data structures
A plug-and-play class-library project of standard Data Structures and Algorithms, written in C#. It contains 75+ Data Structures and Algorithms, designed as Object-Oriented isolated components. Even though this project started for educational purposes, the implemented Data Structures and Algorithms are standard, efficient, stable and tested. This is a C#.NET solution-project, and it contains three subprojects. Algorithms, a class library project which contains the Algorithms implementations. Data Structures, a class library project which contains the Data Structures implementations. Also, UnitTest, a unit-testing project for the Algorithms and Data Structures. -
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EASTL
EASTL, Electronic Arts Standard Template Library
EASTL stands for Electronic Arts Standard Template Library. It is a C++ template library of containers, algorithms, and iterators useful for runtime and tool development across multiple platforms. It is a fairly extensive and robust implementation of such a library and has an emphasis on high performance above all other considerations. If you are familiar with the C++ STL or have worked with other templated container/algorithm libraries, you probably don't need to read this. If you have no familiarity with C++ templates at all, then you probably will need more than this document to get you up to speed. In this case, you need to understand that templates, when used properly, are powerful vehicles for the ease of creation of optimized C++ code. A description of C++ templates is outside the scope of this documentation, but there is plenty of such documentation on the Internet. -
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TBOX
A glib-like multi-platform c library
TBOX is a glib-like cross-platform C library that is simple to use yet powerful in nature. The project focuses on making C development easier and provides many modules (.e.g stream, coroutine, regex, container, algorithm ...), so that any developer can quickly pick it up and enjoy the productivity boost when developing in C language. It supports the following platforms: Windows, Macosx, Linux, Android, iOS, BSD and etc. Supports file, data, http and socket source. Supports the stream filter for gzip, charset. etc. Implements stream transfer. Implements the static buffer stream for parsing data. Supports coroutine and implements asynchronous operation. The coroutine library. Provides high-performance coroutine switch. Supports arm, arm64, x86, x86_64. Provides channel interfaces. Provides semaphore and lock interfaces. Supports io socket and stream operation in coroutine. Provides some io servers (http ..) using coroutine. Provides stackfull and stackless coroutines. -
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This library contains generic algorithms from STL and boost.org and other sources, re-implemented using Instigate's GP methodology, based on modern principles of Generic Programming.
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C++ Library of Abstract Algebra concepts and arithmetic algorithms defined in terms of these concepts, using Instigate Generic Programming Methodology. Based on this library we plan to develop Linear Algebra and Optimization concepts and algorithms.
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CLAW is a C++ Library providing various tools in different domains, like a Tweener framework, Bézier curves manipulation, a map with multiple value types, a binary search tree container implemented as an AVL and an implementation of the sockets as std::stream. The library also includes a set of classes to easily load and write png, jpeg, gif files and other image formats. Finally, a part of the library is devoted to artificial intelligence in games and includes a generic alpha-beta algorithm. Each module is provided with an example program.
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D-List
An extensive list subsystem, written in C
D-List is an extensive, production quality, and robust list management subsystem written in C that can be used as a shared library or compiled directly into your project. D-List provides access to 3 classes of lists, and allows extensive manipulation and customization of these lists. D-List lists can also be easily incorporated as primitives into larger treed, or nested data management systems. D-List implements a comprehensive set of linked list primitives that provides multiple forms of both sequential and random element access, bi-directional movement within a list, and an extensive set of list and element manipulation and reordering features. It also provides for an expansive set of user functions that can be added to lists and called automatically, to efficiently implement a broad range of services using the list primitives as underlying technology. It was written primarily for accuracy and speed, and provides extensive debugging support for easy code development. -
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This project has moved and is not any longer developed. Please see http://sibirjak.com/blog/index.php/lite-collections/ for more details.
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PWSLIB3
Password Safe encrypted databases, Java library
Java module to create, read and write Password Safe V3 encrypted databases. The package is a mature offspring from project JPasswords and can be used with Java 1.8. There is an API document available. -
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SPLITNEURON is a completely new approach to large-scale, biologically plausible, neural-network simulation library based on data structures and methods directly coded into database and conceived to explicitly share load on multiple machines.
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User AES-128 bit encryption in counter mode of operation. supports interactive mode of operation and command line mode of operation.
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A base set of libraries. Boilerplate type code and algorithms. Currently skuttil (Java util & parsing code) and searKit (generic Java search framework).
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AlgART Java Libraries
Open source library for processing arrays and matrices
AlgART Java libraries for processing arrays and matrices are open-source product, distributed under MIT license. So, anyone can use them for free without any restrictions. Main features: 63-bit addressing of array elements (64-bit long int indexes), memory model concept (allowing storing data in different schemes from RAM to mapped disk files), wide usage of lazy evaluations, built-in multithreading optimization for multi-core processors, wide set of image processing algorithms over matrices, etc. - please see at the site. Almost all classes and methods are thoroughly documented via JavaDoc (you may read full JavaDoc at the site). -
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The goal: to provide implementations of as many algorithms (sorting, searching, ...) and data structures (lists, trees, ...) as possible, accompanied by discussion of big O run time and memory limits and references to sources of further study.
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AlgorithmsDev Library by Arshad Latti
comman and new algorithms and functions development and demo programs.
Provide implemented algorithms and functions with demo programs to test.keeped portable as possible at OS level and programming language(understanding)level.provide third party archives if available for ralvent algorithm.links for YouTube videos on availability by us and third party. -
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Binarytree
Python library for studying Binary Trees
Binarytree is Python library that lets you generate, visualize, inspect and manipulate binary trees. Skip the tedious work of setting up test data, and dive straight into practicing algorithms. Heaps and BSTs (binary search trees) are also supported. Binarytree supports another representation which is more compact but without the indexing properties. Traverse trees using different algorithms. -
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Modules for developing, configuring and running a computation based on function blocks entirely in Python. Function block based computation is a data, event and state driven approach to data processing.
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Implementation of cache conscious STL lists in Frias, L., Petit, J., and Roura, S. 2009. Lists revisited: Cache-conscious STL lists. J. Exp. Algorithmics 14 (Dec. 2009), 3.5-3.27. DOI= http://doi.acm.org/10.1145/1498698.1564505
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A capsule tree is a general purpose, self-balancing tree data structure for large, ordered, data-sets. It is designed to provide the same characteristics as B-trees and B+trees, but built from the ground up for in-memory usage. In other words, there are no provisions for “slow” I/O cases. The original motivation for this tree was a better backend for memory managers. However, the end result was a new sub-category of trees. The implementation giving here is just one implementation of the new tree sub-category, there can be others. In any case, read the PDF: “Capsule Trees - A Primer”, before delving into the code.
