Awesome Data Analysis
Section: Tools · Workflow orchestration for building resilient data pipelines.
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Appears in 11 awesome lists
Workflow management system that makes it easy to take your data pipelines and add semantics like retries, logging, dynamic mapping, caching, failure notifications, and more.
Section: Tools · Workflow orchestration for building resilient data pipelines.
Section: Miscellaneous Tools · Workflow management system for modern data stacks
Section: Workflow Management/Engines · "a workflow orchestration framework for building resilient data pipelines in Python."
Section: Workflow Engine · Modern, developer-friendly orchestration tool optimized for data pipelines and complex workflows.
Section: Workflow · The easiest way to automate your data.
Section: 8. MLOps / LLMOps & Production · Workflow orchestration framework for building resilient data and ML pipelines. Python-native with modern observability and 200+ integrations. Apache 2.0 licensed.
Section: General · ] - A workflow management system designed for modern infrastructure.
Section: Data Pipeline · Workflow management system that makes it easy to take your data pipelines and add semantics like retries, logging, dynamic mapping, caching, failure notifications, and more.
Section: Job Schedulers · A modern workflow orchestration framework that makes it easy to build, schedule and monitor robust data pipelines.
Section: Prefect (32 · 24K) - Prefect is a workflow orchestration framework for building resilient.. Apache-2 · (👨💻 770 · 🔀 2.5K · 📦 8.5K):
Section: Data Science and Analytics · Prefect is a workflow orchestration framework for building resilient data pipelines in Python.
Comet's open-source AI observability and evaluation platform: deep tracing of LLM calls, conversation logging, and agent activity, plus built-in eval metrics, prompt versioning, guardrails, and the Opik Agent Optimizer. Worth including because it unifies observability, verification, and…
Python module for building complex pipelines of batch jobs. Handles dependency resolution, workflow management, visualization, and Hadoop integration. Built at Spotify and battle-tested in production. Apache 2.0 licensed.
"Use airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command line utilities make performing complex surgeries on DAGs a snap. The rich user interface makes it…
A fast and simple framework for building and running distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library. ray.io
Cloud-native orchestration platform for developing and maintaining data assets including ML models. Declarative programming model with integrated lineage and observability. Apache 2.0 licensed.
Build and share delightful machine learning apps, all in Python. The de facto standard for creating interactive ML demos with automatic UI generation from function signatures. Powers thousands of Hugging Face Spaces.