Search Results for "squid-graph"
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Showing 64 open source projects for "squid-graph"
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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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Graph Node
Graph Node indexes data from blockchains such as Ethereum
The Graph is an indexing protocol for querying networks like Ethereum and IPFS. Anyone can build and publish open APIs, called subgraphs, making data easily accessible. Subgraphs can be composed into a global graph of all the world's public information. This data can be transformed, organized, and shared across applications for anyone to query with just a few keystrokes. -
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G6
A Graph Visualization Framework in JavaScript
G6 is graph visualization engine with simplicity and convenience. Based on the ability to customize, it provides a set of elegant graph visualization solutions and helps developers to build up applications for graph visualization, graph analysis, and graph editor. G6 is a complete graph visualization engine, which focuses on relational data. -
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Spring Data Neo4j
Provide support to increase developer productivity in Java
Spring Data Neo4j, part of the larger Spring Data family, provides easy configuration and access to Neo4j Graph Databases from Spring applications. It offers three different levels of abstraction to access the store. The Neo4j client, the Neo4j Template, and the Neo4j Repositories. Spring Data Neo4j offers advanced features to map annotated entity classes to the Neo4j Graph Database. The template programming model is equivalent to other Spring templates and builds the basis for interaction with the graph and is also used for the Spring Data repository support. ... -
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Apache Spark
A unified analytics engine for large-scale data processing
Apache Spark is a unified engine for large-scale data processing, offering APIs for batch jobs, streaming, machine learning, and graph computation. It builds on resilient distributed datasets (RDDs) and the newer DataFrame/Dataset abstractions to provide fault-tolerant, in-memory computation across clusters. Spark’s execution engine handles scheduling, shuffles, caching, and data locality so users can focus on transformations rather than infrastructure plumbing. -
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LibreNMS
Community-based GPL-licensed network monitoring system
Welcome to LibreNMS, a fully featured network monitoring system that provides a wealth of features and device support. LibreNMS is an auto-discovering PHP/MySQL/SNMP-based network monitoring that includes support for a wide range of network hardware and operating systems including Cisco, Linux, FreeBSD, Juniper, Brocade, Foundry, HP, and many more. -
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Clerk
Moldable Live Programming for Clojure
...Clerk notebooks are either regular Clojure namespaces (interspersed with markdown comments) or regular markdown files (interspersed with Clojure code fences). This also means Clerk notebooks are meant to be stored in source control. Clerk notebooks always evaluate from top to bottom. Clerk builds a dependency graph of Clojure vars and only recomputes the needed changes to keep the feedback loop fast. -
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RAG Anything
RAG-Anything: All-in-One RAG Framework
...Traditional RAG systems are typically limited to text and cannot effectively work across heterogeneous document layouts, but RAG-Anything addresses this by modeling multimodal content in ways that preserve cross-modal relationships and semantic context, often treating content elements as interconnected knowledge entities rather than separate data silos. The system uses a multi-stage pipeline (e.g., document parsing, content analysis, knowledge graph construction, intelligent retrieval) so queries can navigate across modalities with deeper understanding and relevance. -
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Graphene-Django
Integrate GraphQL into your Django project
...Our primary focus in this tutorial is to give a good understanding of how to connect models from Django ORM to Graphene object types. GraphQL presents your objects to the world as a graph structure rather than a more hierarchical structure to which you may be accustomed. In order to create this representation, Graphene needs to know about each type of object which will appear in the graph. -
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Apollo Server
Spec-compliant and production ready JavaScript GraphQL server
Apollo Server is an open-source, spec-compliant GraphQL server that's compatible with any GraphQL client, including Apollo Client. It's the best way to build a production-ready, self-documenting GraphQL API that can use data from any source. Apollo Server provides a simple API for integrating with any Node.js web framework or serverless environment. The @apollo/server package itself ships with a minimally-configurable, standalone web server that handles CORS and body parsing out of the box.... -
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gentelella
Free Bootstrap 4 Admin dashboard template
Gentelella Admin is a free-to-use Bootstrap admin template. This template uses the default Bootstrap 4 styles along with a variety of powerful jQuery plugins and tools to create a powerful framework for creating admin panels or back-end dashboards. The theme uses several libraries for charts, calendar, form validation, wizard-style interface, off-canvas navigation menu, text forms, date range, upload area, form autocomplete, range slider, progress bars, notifications, and much more. We would... -
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SEOTools
SEO Tools for Laravel
SEOTools is a package for Laravel 5.8+ and Lumen that provides helpers for some common SEO techniques. There are many SEO-related features, which you may need for your project. While this package provides support for the basic ones, others are out of its scope. You'll have to use separate packages for their integration. Using the same code in multiple places can be tedious, which is why this package includes a Macroable trait. This trait allows additional functionality to be added to a class... -
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Redpanda
Redpanda is a streaming data platform for developers
...We provide a very simple build system that uses your system libraries. We recommend users leverage our pre-built stable releases which are vetted, tested, and reproducible with exact versions of the entire transitive dependency graph, including exact compilers all built from source. The only thing we do not build yet is the Linux Kernel, but soon! -
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Checkov
Prevent cloud misconfigurations during build-time for Terraform
...Scan cloud resources in build-time for misconfigured attributes with a simple Python policy-as-code framework. Analyze relationships between cloud resources using Checkov’s graph-based YAML policies. Execute, test, and modify runner parameters in the context of a subject repository CI/CD and version control integrations. -
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Membrane Core
The core of Membrane Framework, multimedia processing framework
membrane_core is the foundation of the Membrane multimedia framework for Elixir, providing the abstractions and runtime needed to build real-time audio and video pipelines. It models media processing as a graph of lightweight, supervised OTP processes—elements connected by links—so work is isolated, fault-tolerant, and easy to scale or reconfigure at runtime. The core defines a clear lifecycle and callback API for elements, plus concepts like buffers, events, and capabilities/format negotiation to keep components interoperable and type-safe. ... -
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BentoML
Unified Model Serving Framework
...Parallelize compute-intense model inference workloads to scale separately from the serving logic. Adaptive batching dynamically groups inference requests for optimal performance. Orchestrate distributed inference graph with multiple models via Yatai on Kubernetes. Easily configure CUDA dependencies for running inference with GPU. Automatically generate docker images for production deployment. -
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Swinject
Dependency injection framework for Swift with iOS/macOS/Linux
Swinject is a lightweight dependency injection framework for Swift. Dependency injection (DI) is a software design pattern that implements Inversion of Control (IoC) for resolving dependencies. In the pattern, Swinject helps your app split into loosely-coupled components, which can be developed, tested, and maintained more easily. Swinject is powered by the Swift generic type system and first-class functions to define the dependencies of your app simply and fluently. Services must be... -
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MercuryMessaging
Framework to facilitate communication in the Unity game engine
...The toolkit contains the Mercury messaging framework, which is a messaging and organizational framework built around the Mercury Protocol. Unity organizes its rendered scene objects (known in Unity as GameObjects) using a standard scene graph (known in Unity as the Scene Hierarchy). While Unity is very powerful, it is fairly difficult to achieve nonspatial communication between scriptable components of GameObjects (in Unity, known as MonoBehaviours). -
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Visual Blocks
Visual Blocks for ML is a Google visual programming framework
Visual Blocks is a node-based, in-browser environment for building AI and data-processing workflows with drag-and-drop components. It lets you connect sources, transforms, models, and visualizers into a live graph, so changes propagate instantly and results are observable without writing glue code. Under the hood it leans on web-friendly runtimes (e.g., WebGPU/WebGL/WebNN or TensorFlow.js backends) to execute pipelines locally, which is great for demos, teaching, and privacy-sensitive prototypes. The block abstraction encourages modularity: you can package a preprocessor, a model, and a postprocessor as a reusable composite for others to slot into their graphs. ... -
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Smallpond
A lightweight data processing framework built on DuckDB and 3FS
smallpond is a lightweight distributed data processing framework built by DeepSeek, designed to scale DuckDB workloads over clusters using their 3FS (Fire-Flyer File System) backend. The idea is to preserve DuckDB’s fast analytics engine but lift it from single-node to multi-node settings, giving you the ability to operate on large datasets (e.g. petabyte scale) without moving to a heavyweight system like Spark. Users write Python-like code (via DataFrame APIs or SQL strings) to express... -
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Argo Workflows
Workflow engine for Kubernetes
...Define workflows where each step in the workflow is a container. Model multi-step workflows as a sequence of tasks or capture the dependencies between tasks using a directed acyclic graph (DAG). Easily run compute intensive jobs for machine learning or data processing in a fraction of the time using Argo Workflows on Kubernetes. Run CI/CD pipelines natively on Kubernetes without configuring complex software development products. Argo Workflows is the most popular workflow execution engine for Kubernetes. It can run 1000s of workflows a day, each with 1000s of concurrent tasks. ... -
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Jittor
Jittor is a high-performance deep learning framework
...Jittor also contains a wealth of high-performance model libraries, including image recognition, detection, segmentation, generation, differentiable rendering, geometric learning, reinforcement learning, etc. The front-end language is Python. Module Design and Dynamic Graph Execution is used in the front-end, which is the most popular design for deep learning framework interface. The back-end is implemented by high-performance languages, such as CUDA, C++. Jittor'op is similar to NumPy. Let's try some operations. We create Var a and b via operation jt.float32, and add them. Printing those variables shows they have the same shape and dtype. -
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Apache Flink
Stream processing framework with powerful stream
Apache Flink is a distributed engine for stateful computations over data streams and batches, designed for low-latency processing at scale. Its core runtime executes dataflow graphs with fine-grained backpressure and checkpointing, allowing applications to recover consistently from failures. Flink’s event-time model and watermarks enable accurate out-of-order processing, windowing, and complex time semantics that typical real-time systems struggle with. Developers program against high-level... -
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SageMaker Spark Container
Docker image used to run data processing workloads
...It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. It also supports a rich set of higher-level tools including Spark SQL for SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Structured Streaming for stream processing. The SageMaker Spark Container is a Docker image used to run batch data processing workloads on Amazon SageMaker using the Apache Spark framework. The container images in this repository are used to build the pre-built container images that are used when running Spark jobs on Amazon SageMaker using the SageMaker Python SDK. ... -
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VR Ax Java Sources & Build Projects
VR Adrix Java Works - Paged Lists - Action-Entity Model ...
Adrix.NT Java Works :: Sources & Build Projects includes - Paged Lists of Object & Iterators Library for Java - Action / Entity Model for Java - VR Ax AWT Clock Java Component - VR Multi Dimensions Array Library - VR MDArray List Manager Library - VR Adjacency (List | Matrix) Direct Graph Lib - VRJMosaic cells sliding game with automatic resolver - VR RectsWorld Sample Applic - VR Free Chess 2D Applic also contains - Other Utils Libraries - Demo and Test Applications - NetBeans build projects - and more ... (*) note: the libraries folder to build and run applications must be located on the same volume of the java applications its path name must be: \AX.VincentRadio\Java\SharedLib have fun Adrix.NT adrixnt@hotmail.it -
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TorchQuantum
A PyTorch-based framework for Quantum Classical Simulation
...Researchers on quantum algorithm design, parameterized quantum circuit training, quantum optimal control, quantum machine learning, and quantum neural networks. Dynamic computation graph, automatic gradient computation, fast GPU support, batch model terrorized processing.
