Awesome Data & AI Governance
Section: Hamilton
Entry
Appears in 10 awesome lists
| Python | - A scalable general purpose micro-framework for defining dataflows. You can use it to build dataframes, numpy matrices, python objects, ML models, etc. Embed Hamilton anywhere python runs, e.g. spark, airflow, jupyter, fastapi, python scripts, etc.
Section: Hamilton
Section: Workflow · A lightweight library to define data transformations as a directed-acyclic graph (DAG). If you like dbt for SQL transforms, you will like Hamilton for Python processing.
Section: Miscellaneous Tools · Lightweight library to author and manage reliable data transformations
Section: Libraries · "helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does."
Section: Workflow · A lightweight framework to represent ML/language model pipelines as a series of python functions.
Section: Tools · a lightweight library to define data transformations as a directed-acyclic graph (DAG). It helps author reliable feature engineering and machine learning pipelines, and more.
Section: Workflow Tools · A scalable general purpose micro-framework for defining dataflows.
Section: Pipeline frameworks & libraries · A python micro-framework for describing dataflows; runs anywhere python runs.
Section: Pipelines · A microframework for dataframe generation that applies Directed Acyclic Graphs specified by a flow of lazily evaluated Python functions.
Section: Computation · | Python | - A scalable general purpose micro-framework for defining dataflows. You can use it to build dataframes, numpy matrices, python objects, ML models, etc. Embed Hamilton anywhere python runs, e.g. spark, airflow, jupyter, fastapi, python scripts, etc.
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.