Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
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Updated
May 25, 2024 - Python
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
【Go DAG Schedule Framework】A simple way to build a pipeline with Go.
数据pipeline处理编排框架
Lightweight function pipeline (DAG) creation in pure Python for scientific workflows 🕸️🧪
Substrate Python SDK
A reactive notebook for Python — run reproducible experiments, execute as a script, deploy as an app, and version with git.
Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage and metadata. Runs and scales everywhere python does.
A distributed, fault-tolerant task queue
An experimental multi-tenant distributed system platform
Iris is an extensible asynchronous header-only framework written in pure modern C++, including a M:N task scheduler (with coroutine support for C++ 20 optionally) and an advanced DAG-based task dispatcher.
A high performance Python graph library implemented in Rust.
A scalable inference server for models optimized with OpenVINO™
Go Implementation of the Spacemesh protocol full node. 💾⏰💪
Workflow Engine for Kubernetes
🚀 JavaScript diagramming library that uses SVG and HTML for rendering.
Python library for learning the graphical structure of Bayesian networks, parameter learning, inference and sampling methods.
一个无任何第三方依赖的跨平台自定义编排执行步骤的API, 基于DAG实现了依赖步骤依次顺序执行、非依赖步骤并发执行的调度功能. 提供API远程操作方式,批量执行Shell、Powershell、Python等命令,轻松完成运行自动化运维脚本等常见管理任务,轮询进程、安装或卸载软件、更新应用程序以及安装补丁。
The easiest way to use Machine Learning. Mix and match underlying ML libraries and data set sources. Generate new datasets or modify existing ones with ease.
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