Search Results for "pipeline"
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Showing 53 open source projects for "pipeline"
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Pipeline Model Definition Plugin
Dfine CI/CD workflows using Jenkinsfile
The Pipeline Model Definition Plugin introduces Declarative Pipelines in Jenkins—offering a more structured, configuration-like syntax for defining CI/CD workflows using Jenkinsfile. It simplifies pipeline creation, gives clearer semantic error messages, supports post-build steps, and is fully extensible via APIs. -
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Union Pandera
Light-weight, flexible, expressive statistical data testing library
...Integrate seamlessly with the Python ecosystem. Overcome the initial hurdle of defining a schema by inferring one from clean data, then refine it over time. Identify the critical points in your data pipeline, and validate data going in and out of them. Build confidence in the quality of your data by defining schemas for complex data objects. -
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PortableGL
An implementation of OpenGL 3.x-ish in clean C
PortableGL is a single-header, software-only implementation of a subset of OpenGL (specifically the GL 2.1 pipeline), designed to run entirely on the CPU. This lightweight graphics library allows OpenGL-style rendering without GPU acceleration, making it ideal for educational use, debugging, embedded systems, and retro-style software rendering. Because it mirrors OpenGL syntax and design, it can act as a drop-in CPU renderer for testing or deploying 3D graphics on platforms without GPU support. -
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Best-of Python
A ranked list of awesome Python open-source libraries
...Libraries for loading, collecting, and extracting data from a variety of data sources and formats. Libraries for data batch- and stream-processing, workflow automation, job scheduling, and other data pipeline tasks. -
The AI-powered unified PSA-RMM platform for modern MSPs.SuperOps.ai is the only PSA-RMM platform powered by intelligent automation and thoughtfully crafted for the new-age MSP. The platform also helps MSPs manage their projects, clients, and IT documents from a single place.
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libplacebo
Official mirror of libplacebo
libplacebo is a flexible, high-performance graphics library built on top of Vulkan, designed to provide reusable GPU-accelerated components for media applications. It originated as a core part of the rendering pipeline for the mpv media player and has since grown into a standalone library used for tone mapping, dithering, color space conversion, and more. libplacebo is ideal for developers looking to integrate sophisticated video rendering and post-processing into their own applications with full control over shaders and rendering stages. -
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zshy
Bundler-free build tool for TypeScript libraries
...It reads configuration directly from package.json and standard TypeScript config files, doesn’t require its own config, and supports multi-entry libraries with deep wildcard exports. Originally created for building popular libraries such as Zod, zshy fills the niche for a straightforward, convention-over-configuration build pipeline for TypeScript packages. The tool copies non-JS assets, supports .tsx, and makes CLI packaging easy, helping maintain consistent library outputs with minimal boilerplate. -
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CoreNet
CoreNet: A library for training deep neural networks
...It focuses on enabling large-scale model training across clusters of GPUs and accelerators by optimizing data flow and parallelism strategies. CoreNet provides abstractions for data, tensor, and pipeline parallelism, allowing models to scale without code duplication or heavy manual configuration. Its distributed runtime manages synchronization, load balancing, and mixed-precision computation to maximize throughput while minimizing communication bottlenecks. CoreNet integrates tightly with Apple’s proprietary ML stack and hardware, serving as the foundation for research in computer vision, language models, and multimodal systems within Apple AI. ... -
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Stanza
Stanford NLP Python library for many human languages
...Starting from raw text to syntactic analysis and entity recognition, Stanza brings state-of-the-art NLP models to languages of your choosing. Stanza is a Python natural language analysis package. It contains tools, which can be used in a pipeline, to convert a string containing human language text into lists of sentences and words, to generate base forms of those words, their parts of speech and morphological features, to give a syntactic structure dependency parse, and to recognize named entities. The toolkit is designed to be parallel among more than 70 languages, using the Universal Dependencies formalism. ... -
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Mako
An extremely fast, production-grade web bundler based on Rust
Mako is a new web bundler for web apps, libraries, and frameworks. It's designed to be fast, reliable, and easy to use. It has been used in hundreds of projects in production by Ant Group, and other companies. If you are looking for a modern web bundler, Mako is the right choice. -
Securden Privileged Account ManagerDiscover and manage administrator, service, and web app passwords, keys, and identities. Automate management with approval workflows. Centrally control, audit, monitor, and record all access to critical IT assets.
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redis-rs
Redis library for rust
Redis-rs is a Rust library for interacting with Redis databases, offering high-performance data manipulation capabilities for Rust developers. -
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Librelancer
A re-implementation of Freelancer
Librelancer is an open-source reimplementation of the engine behind Freelancer, the iconic 2003 space trading and combat simulation game by Microsoft. Written in C# and powered by OpenGL and modern game development practices, Librelancer faithfully replicates the original gameplay while providing a flexible codebase for modding, analysis, and future enhancements. It supports original assets and is designed to be both a preservation project and a foundation for new space simulation games... -
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TensorFlow
TensorFlow is an open source library for machine learning
Originally developed by Google for internal use, TensorFlow is an open source platform for machine learning. Available across all common operating systems (desktop, server and mobile), TensorFlow provides stable APIs for Python and C as well as APIs that are not guaranteed to be backwards compatible or are 3rd party for a variety of other languages. The platform can be easily deployed on multiple CPUs, GPUs and Google's proprietary chip, the tensor processing unit (TPU). TensorFlow... -
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redis-py
Redis Python client
redis-py is the official Python client for interacting with Redis, the in-memory data structure store. It supports all Redis commands and data types, making it easy to build caching, messaging, or real-time analytics features in Python applications. With both synchronous and asyncio support, redis-py is suited for modern Python projects and integrates smoothly into web frameworks, task queues, and backend services. -
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Otter-Grader
A Python and R autograding solution
...It is designed to work with classes at any scale by abstracting away the autograding internals in a way that is compatible with any instructor's assignment distribution and collection pipeline. Otter supports local grading through parallel Docker containers, grading using the autograder platforms of 3rd party learning management systems (LMSs), the deployment of an Otter-managed grading virtual machine, and a client package that allows students to run public checks on their own machines. Otter is designed to grade Python scripts and Jupyter Notebooks, and is compatible with a few different LMSs, including Canvas and Gradescope. -
15
frugally-deep
A lightweight header-only library for using Keras (TensorFlow) models
...Quite fast on one CPU core, and you can run multiple predictions in parallel, thus utilizing as many CPUs as you like to improve the overall prediction throughput of your application/pipeline. -
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Google Cloud Dataflow Template Pipelines
Cloud Dataflow Google-provided templates for solving data tasks
DataflowTemplates is the source repository for Google-provided Dataflow templates that are intended to solve large-scale in-cloud data processing tasks without requiring users to build everything from scratch in a full development environment. The repository is centered on templated pipelines powered by Google Cloud Dataflow and Apache Beam, making it easier to run common integration and movement jobs such as data import, export, backup, restore, and bulk API operations. Its structure shows... -
17
Size Limit
Calculate the real cost to run your JS app or lib
...The tool is modular: it offers a CLI and multiple plugins (file, webpack, time) plus presets tailored to different use cases, from big single-page apps to small npm libraries. When integrated with GitHub Actions, CircleCI, or other CI systems, it runs on every commit or pull request, failing the pipeline if a change exceeds the configured budget. It can also annotate pull requests with comments that highlight how the bundle changed, making performance regressions visible to reviewers early. With the --why flag, size-limit can analyze what contributes most to bundle size and show a dependency breakdown (using Statoscope). -
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Siddhi Core Libraries
Stream Processing and Complex Event Processing Engine
Fully open source, cloud-native, scalable, micro streaming, and complex event processing system capable of building event-driven applications for use cases such as real-time analytics, data integration, notification management, and adaptive decision-making. Event processing logic can be written using Streaming SQL queries via graphical and source editors, to capture events from diverse data sources, process and analyze them, integrate with multiple services and data stores, and publish... -
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SageMaker Hugging Face Inference Toolkit
Library for serving Transformers models on Amazon SageMaker
SageMaker Hugging Face Inference Toolkit is an open-source library for serving Transformers models on Amazon SageMaker. This library provides default pre-processing, predict and postprocessing for certain Transformers models and tasks. It utilizes the SageMaker Inference Toolkit for starting up the model server, which is responsible for handling inference requests. For the Dockerfiles used for building SageMaker Hugging Face Containers, see AWS Deep Learning Containers. The SageMaker Hugging... -
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Job Recommend
The basics of building a job recommendation workflow
Job-Recommend explores the basics of building a job recommendation workflow, from data preparation to ranking simple candidate matches. It treats job postings and résumés as structured items and applies straightforward matching signals such as keywords, skills overlap, or vectorized features. The repository is educational in spirit, focusing on clarity rather than heavy infrastructure or opaque models. You can study how to transform raw text into features and how to evaluate simple... -
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Generative AI Examples
Generative AI Examples is a collection of GenAI examples
Efficiently integrate secure, performant, and cost-effective Generative AI workflows into business value. Detailed framework of composable building blocks for state-of-the-art generative AI systems including LLMs, data stores, and prompt engines. Architectural blueprints of retrieval-augmented generative AI component stack structure and end-to-end workflows. A four-step assessment for grading generative AI systems around performance, features, trustworthiness and enterprise-grade readiness. -
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SageMaker Spark
A Spark library for Amazon SageMaker
SageMaker Spark is an open-source Spark library for Amazon SageMaker. With SageMaker Spark you construct Spark ML Pipelines using Amazon SageMaker stages. These pipelines interleave native Spark ML stages and stages that interact with SageMaker training and model hosting. With SageMaker Spark, you can train on Amazon SageMaker from Spark DataFrames using Amazon-provided ML algorithms like K-Means clustering or XGBoost, and make predictions on DataFrames against SageMaker endpoints hosting... -
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Alpa
Training and serving large-scale neural networks
Alpa is a system for training and serving large-scale neural networks. Scaling neural networks to hundreds of billions of parameters has enabled dramatic breakthroughs such as GPT-3, but training and serving these large-scale neural networks require complicated distributed system techniques. Alpa aims to automate large-scale distributed training and serving with just a few lines of code. -
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Style2Paints
Sketch + style = paints
style2paints is an AI-assisted colorization system aimed primarily at line art and manga, turning monochrome drawings into colored illustrations with minimal manual effort. It combines automatic color inference with user guidance, letting artists nudge the model using sparse color hints, masks, or style references. The pipeline focuses on preserving line quality while spreading coherent colors and shading across regions that are often ambiguous to purely automatic methods. Iterative refinement is a core workflow: you can add or adjust hints, rerun inference, and progressively converge on a desired palette and lighting. Beyond flat fills, the model attempts plausible shading and highlights so the result feels less like a “paint bucket” and more like a finished illustration. ... -
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FairScale
PyTorch extensions for high performance and large scale training
...It introduced Fully Sharded Data Parallel (FSDP) style techniques that shard model parameters, gradients, and optimizer states across ranks to fit bigger models into the same memory budget. The library also provides pipeline parallelism, activation checkpointing, mixed precision, optimizer state sharding (OSS), and auto-wrapping policies that reduce boilerplate in complex distributed setups. Its components are modular, so teams can adopt just the sharding optimizer or the pipeline engine without rewriting their training loop. FairScale puts emphasis on correctness and debuggability, offering hook points, logging, and reference examples for common trainer patterns. ...
