Open Source Libraries - Page 28
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CoolplaySpark
Spark Cool Play: Spark source code analysis, Spark class library, etc.
CoolplaySpark is a learning and practice repository designed to help users understand and work with Apache Spark. It serves as a companion resource for the book 深入理解Spark核心思想与源码分析 (In-Depth Understanding of Spark’s Core Concepts and Source Code Analysis). The project contains annotated examples, explanations, and exercises that guide learners through Spark’s architecture, execution model, and source code internals. It is particularly valuable for developers who want to strengthen their understanding of Spark by not only using it as a data processing engine but also exploring how its internals function. Through code analysis and commentary, CoolplaySpark helps readers connect theoretical concepts with practical implementation details. By combining book study with this repository, learners can develop both conceptual clarity and hands-on expertise in Spark’s core components. -
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Coraza
OWASP Coraza WAF is a golang modsecurity compatible firewall library
Coraza is an open-source, enterprise-grade, high-performance Web Application Firewall (WAF) ready to protect your beloved applications. It is written in Go, supports ModSecurity SecLang rulesets and is 100% compatible with the OWASP Core Rule Set. Coraza is a drop-in alternative to replace the soon-to-be abandoned Trustwave ModSecurity Engine and supports industry-standard SecLang rule sets. Coraza runs the OWASP Core Rule Set (CRS) to protect your web applications from a wide range of attacks, including the OWASP Top Ten, with a minimum of false alerts. CRS protects from many common attack categories including: SQL Injection (SQLi), Cross Site Scripting (XSS), PHP & Java Code Injection, HTTPoxy, Shellshock, Scripting/Scanner/Bot Detection & Metadata & Error Leakages. Coraza is a library at its core, with many integrations to deploy on-premise Web Application Firewall instances. -
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Cytoscape.js
Graph theory library for visualization and analysis
A fully featured graph library written in pure JS. Permissive open source license (MIT) for the core Cytoscape.js library and all first-party extensions. Used in commercial projects and open-source projects in production. Designed for users first, for both frontfacing app usecases and developer usecases. Highly optimized. Compatible with All modern browsers. Legacy browsers with ES5 and canvas support. ES5 and canvas support are required, and feature detection is used for optional performance enhancements. Browsers circa 2012 support ES5 fully: IE10, Chrome 23, Firefox 21, Safari 6 (caniuse). Browsers with partial but sufficient ES5 support also work, such as IE9 and Firefox 4. The documentation and examples are not optimized for old browsers, although the library itself is. Some demos may not work in old browsers in order to keep the demo code simple. -
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DASH V4
Blazing fast library to create a functional dashboard on ESP8266
DASH V4 is the 4th-gen blazing fast library to create a functional & real-time dashboard for ESP8266 & ESP32 microcontrollers. This library includes charts, display cards, interactive buttons and many more components to create a perfect dashboard that is accessible locally via your IoT device's IP. DASH does not require any kind of internet connection, everything is stored locally. -
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DCV Color Primitives
DCV Color Primitives Library
DCV Color Primitives is a library to perform image color model conversion. Aware of the underlying hardware and supplemental cpu extension sets (up to avx2). Support data coming from a single buffer or coming from multiple image planes. Support non-tightly packed data. Support images greater than 4GB (64 bit). Convert an image from bgra to nv12 (single plane) format containing yuv in BT601. You might want to propagate errors to the caller function or mix with some other error types. So far, buffers were sized taking into account the image pixel format and dimensions; However, you can use a function to compute how many bytes are needed to store an image of a given format and size. If your data is scattered in multiple buffers that are not necessarily contiguous, you can provide image planes. To take into account data which is not tightly packed, you can provide image strides. -
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DGL
Python package built to ease deep learning on graph
Build your models with PyTorch, TensorFlow or Apache MXNet. Fast and memory-efficient message passing primitives for training Graph Neural Networks. Scale to giant graphs via multi-GPU acceleration and distributed training infrastructure. DGL empowers a variety of domain-specific projects including DGL-KE for learning large-scale knowledge graph embeddings, DGL-LifeSci for bioinformatics and cheminformatics, and many others. We are keen to bringing graphs closer to deep learning researchers. We want to make it easy to implement graph neural networks model family. We also want to make the combination of graph based modules and tensor based modules (PyTorch or MXNet) as smooth as possible. DGL provides a powerful graph object that can reside on either CPU or GPU. It bundles structural data as well as features for a better control. We provide a variety of functions for computing with graph objects including efficient and customizable message passing primitives for Graph Neural Networks. -
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DXcharts Lite
Flexible open source financial charting library
Why choose DXcharts Lite? - User-friendly interface. DXcharts Lite provides a seamless intuitive user experience with automatic scale zoom, mouse wheel zoom, and chart scrolling. - Versatile chart types. The Lite version supports eight chart types. The platform streams real-time data updates allowing users to stay on top of market movements. - Comprehensive market coverage. DXcharts Lite provides a wide-ranging selection of asset classes and extensive market coverage. This includes a variety of financial instruments such as stocks, forex, cryptocurrencies, and more. - Efficiency and speed. The platform uses HTML5 based on canvas to ensure smooth chart loading and data processing. - Snapshots. The snapshot feature is a handy tool that allows users to take and share chart snapshots anywhere. - Customisation. The platform offers users the ability to personalise their workspace allowing traders to customise their own theme or choose between the predefined dark or white ones. -
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Day.js
Fast, immutable 2kB alternative to Moment.js with the same modern API
Day.js is a fast, immutable, minimalist JavaScript library for parsing, validating, manipulating, and displaying dates and times for modern browsers. Its API is largely compatible with that of Moment.js, so if you know how to use Moment.js you’ll know how to use Day.js. Why opt for Day.js? Because it’s at just 2kB it involves less JavaScript to download, parse and execute, and more time for your code. Day.js is also immutable, chainable and has great support for internationalization. It currently supports all browsers. -
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DeepPavlov
A library for deep learning end-to-end dialog systems and chatbots
DeepPavlov makes it easy for beginners and experts to create dialogue systems. The best place to start is with user-friendly tutorials. They provide quick and convenient introduction on how to use DeepPavlov with complete, end-to-end examples. No installation needed. Guides explain the concepts and components of DeepPavlov. Follow step-by-step instructions to install, configure and extend DeepPavlov framework for your use case. DeepPavlov is an open-source framework for chatbots and virtual assistants development. It has comprehensive and flexible tools that let developers and NLP researchers create production-ready conversational skills and complex multi-skill conversational assistants. Use BERT and other state-of-the-art deep learning models to solve classification, NER, Q&A and other NLP tasks. DeepPavlov Agent allows building industrial solutions with multi-skill integration via API services. -
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DeepXDE
A library for scientific machine learning & physics-informed learning
DeepXDE is a library for scientific machine learning and physics-informed learning. DeepXDE includes the following algorithms. Physics-informed neural network (PINN). Solving different problems. Solving forward/inverse ordinary/partial differential equations (ODEs/PDEs) [SIAM Rev.] Solving forward/inverse integro-differential equations (IDEs) [SIAM Rev.] fPINN: solving forward/inverse fractional PDEs (fPDEs) [SIAM J. Sci. Comput.] NN-arbitrary polynomial chaos (NN-aPC): solving forward/inverse stochastic PDEs (sPDEs) [J. Comput. Phys.] PINN with hard constraints (hPINN): solving inverse design/topology optimization [SIAM J. Sci. Comput.] Residual-based adaptive sampling [SIAM Rev., arXiv] Gradient-enhanced PINN (gPINN) [Comput. Methods Appl. Mech. Eng.] PINN with multi-scale Fourier features [Comput. Methods Appl. Mech. Eng.] -
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Devilbox
A modern Docker LAMP stack and MEAN stack for local development
Devilbox is a modern and flexible LAMP and MEAN stack environment powered by Docker. It provides a pre-configured, customizable setup for web development, supporting a wide range of services like Apache, Nginx, PHP, MySQL, and MongoDB. Devilbox is designed to be a one-stop solution for developers who need a consistent and portable development environment, eliminating the need to manually configure servers. -
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Dragonboat
A feature complete and high performance multi-group Raft library in Go
Dragonboat is a high-performance multi-group Raft consensus library in pure Go. Consensus algorithms such as Raft provides fault tolerance by allowing a system to continue to operate as long as the majority of member servers are available. For example, a Raft shard of 5 servers can make progress even if 2 servers fail. It also appears to clients as a single entity with strong data consistency always provided. All Raft replicas can be used to handle read requests for aggregated read throughput. Dragonboat handles all technical difficulties associated with Raft to allow users to just focus on their application domains. It is also very easy to use, our step-by-step examples can help new users to master it in half an hour. Easy to use pure-Go APIs for building Raft based applications. Feature complete and scalable multi-group Raft implementation. Disk based and memory based state machine support. Fully pipelined and TLS mutual authentication support. -
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DynaMix
A new take on polymorphism
DynaMix (Dynamic Mixins) is an alternative take on object-oriented programming and dynamic polymorphism. It lets users compose and modify polymorphic objects at run time. The main target language is C++, but C is also supported. The library is a means to create a project's architecture rather than achieve its purpose. It helps with extensibility, readability, scalability, and interoperability. It focuses on maximal performance and minimal memory overhead. The library uses the type dynamix::object as a placeholder, whose instances can be extended with existing classes (mixins), thus providing a particular instance with the mixin features of all those types. Likely the most important types of mixin features are messages: functional objects that in C++-OOP terms can be thought of as methods. Mixin features are overridable and use late binding and singular dispatch. Unicasts and multicasts are possible. -
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Dynamic Data
Reactive collections based on Rx.Net
Rx is extremely powerful but out of the box provides nothing to assist with managing collections. In most applications, there is a need to update the collections dynamically. Typically a collection is loaded and after the initial load, asynchronous updates are received. The original collection will need to reflect these changes. In simple scenarios the code is simple. However, typical applications are much more complicated and may apply a filter, transform the original dto and apply a sort. Even with these simple everyday operations, the complexity of the code is quickly magnified. Dynamic data has been developed to remove the tedious code of dynamically maintaining collections. It has grown to become functionally very rich with at least 60 collection-based operations which amongst other things enable filtering, sorting, grouping, joining different sources, transforms, binding, pagination, data virtualization, expiration, disposal management plus more. -
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Earth Engine API
Python and JavaScript bindings for calling the Earth Engine API
The Earth Engine API provides Python and JavaScript client libraries for Google Earth Engine, a planetary-scale geospatial analysis platform. With it, users compose lazy, server-side computations over massive catalogs of satellite imagery and vector datasets without handling raw files locally. The API exposes functional operators for map algebra, reducers, joins, and machine learning that scale transparently on Earth Engine’s backend. Developers authenticate once, work interactively in notebooks or the Code Editor, and export results to Cloud Storage, Drive, or asset collections. Visualization helpers render tiled layers and charts so analysts can iterate quickly on workflows like land-cover mapping, change detection, or time-series analysis. By combining petabyte-scale data with concise functional transforms, the API turns complex remote-sensing pipelines into reproducible scripts that are easy to share. -
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Easy3D
Efficient library for processing 3D data
Easy3D is a lightweight, easy-to-use, and efficient library for processing and rendering 3D data, implemented in C++ with Python bindings. It is designed for tasks such as 3D modeling, geometry processing, and rendering, emphasizing simplicity and efficiency. Easy3D serves as a valuable tool for research, education, and the development of sophisticated 3D applications, providing a solid foundation for handling 3D data. -
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EasyExcel
Lightweight Java library developed by Alibaba for reading and writing
EasyExcel is a Java library focused on reading and writing Excel files with very low memory usage, making it suitable for large datasets that overwhelm traditional APIs. It uses streaming/event-driven parsing to avoid loading entire workbooks into memory, and it maps rows to Java objects via simple annotations. Writers support multiple sheets, custom styles, merged cells, and template-based filling so production reports remain maintainable. The API emphasizes developer ergonomics: callbacks are straightforward, converters handle common type transformations, and header/column mapping is explicit. It integrates cleanly into Spring/enterprise stacks, often as part of import/export pipelines or scheduled report generation. By optimizing both performance and ease of use, EasyExcel reduces operational risk around big Excel jobs in web services and back-office tools. -
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Ebiten
A dead simple 2D game library for Go
Ebiten is an open source game library for the Go programming language. Ebiten's simple API allows you to quickly and easily develop 2D games that can be deployed across multiple platforms. In Ebiten, everything is an image: the screen, data from an image file, and even offscreen items are all represented as image objects. Most rendering operations consist of drawing one image on top of another. Ebiten games work on desktop (Windows, macOS, Linux, and FreeBSD), web browsers (through WebAssembly), and even on mobile (Android and iOS)! Plus, Ebiten is implemented in pure Go on Windows, so Windows developers do not need to install a C compiler. Nintendo Switch™ is also supported! While Ebiten's drawing API is very simple, Ebiten games run very fast with GPU power. Multiple images are integrated into a texture atlas internally, and drawing operations are automatically performed in batch when possible. -
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Embla Carousel
A lightweight carousel library with fluid motion
A lightweight, customizable carousel library for smooth, touch-friendly interactions. -
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Emoji for Python
emoji terminal output for Python
Emoji for Python. This project was inspired by kyokomi. The entire set of Emoji codes as defined by the Unicode consortium is supported in addition to a bunch of aliases. By default, only the official list is enabled but doing emoji.emojize(language='alias') enables both the full list and aliases. By default, the language is English (language='en') but also supported languages are Spanish ('es'), Portuguese ('pt'), Italian ('it'), French ('fr'), German ('de'). The utils/get-codes-from-unicode-consortium.py may help when updating unicode_codes.py but is not guaranteed to work. Generally speaking it scrapes a table on the Unicode Consortium's website with BeautifulSoup and prints the contents to stdout in a more useful format. -
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Excelize
Go language library for reading and writing Microsoft Excel
Excelize is a library written in pure Go providing a set of functions that allow you to write to and read from XLAM / XLSM / XLSX / XLTM / XLTX files. With Excelize chart generation and management is as easy as a few lines of code. You can build charts based off data in your worksheet or generate charts without any data in your worksheet at all. Excelize provided streaming API for generating or reading data from a worksheet with huge amounts of data. Simply runs Excelize on macOS, Linux and Windows operating systems without a hustle. With Excelize chart generation and management is as easy as a few lines of code. You can build charts based on data in your worksheet or generate charts without any data in your worksheet at all. -
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Express ES2017 REST API Boilerplate
Express starter for building RESTful APIs
A boilerplate for building RESTful APIs with Node.js and Express, providing a pre-configured structure for efficient backend development. -
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Facexlib
FaceXlib aims at providing ready-to-use face-related functions
facexlib is a PyTorch-based library providing ready-to-use face-related functions, including detection, alignment, recognition, and more. It integrates state-of-the-art open-source methods for various face processing tasks. -
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FairChem
FAIR Chemistry's library of machine learning methods for chemistry
FAIRChem is a unified library for machine learning in chemistry and materials, consolidating data, pretrained models, demos, and application code into a single, versioned toolkit. Version 2 modernizes the stack with a cleaner core package and breaking changes relative to V1, focusing on simpler installs and a stable API surface for production and research. The centerpiece models (e.g., UMA variants) plug directly into the ASE ecosystem via a FAIRChem calculator, so users can run relaxations, molecular dynamics, spin-state energetics, and surface catalysis workflows with the same pretrained network by switching a task flag. Tasks span heterogeneous domains—catalysis (OC20-style), inorganic materials (OMat), molecules (OMol), MOFs (ODAC), and molecular crystals (OMC)—allowing one model family to serve many simulations. The README provides quick paths for pulling models (e.g., via Hugging Face access), then running energy/force predictions on GPU or CPU. -
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Faiss
Library for efficient similarity search and clustering dense vectors
Faiss is a library for efficient similarity search and clustering of dense vectors. It contains algorithms that search in sets of vectors of any size, up to ones that possibly do not fit in RAM. It also contains supporting code for evaluation and parameter tuning. Faiss is written in C++ with complete wrappers for Python/numpy. Some of the most useful algorithms are implemented on the GPU. It is developed by Facebook AI Research. Faiss contains several methods for similarity search. It assumes that the instances are represented as vectors and are identified by an integer, and that the vectors can be compared with L2 (Euclidean) distances or dot products. Vectors that are similar to a query vector are those that have the lowest L2 distance or the highest dot product with the query vector. It also supports cosine similarity, since this is a dot product on normalized vectors.