Table of contents
Modular Design
Hamilton offers a modular approach to building production-grade pipeline code, which improves maintainability and readability.
Ease of Use
The framework is designed to be user-friendly, allowing data scientists and engineers to quickly define and build complex data pipelines.
Integration
Hamilton easily integrates with existing data ecosystems and supports interoperability with other Apache projects.
Scalability
Hamilton is built to handle large-scale data processing tasks, making it suitable for enterprise-level applications.
Community Support
Being part of the Apache Software Foundation, Hamilton benefits from active community support and regular updates.
We have collected here some useful links to help you find out if Hamilton is good.
Check the traffic stats of Hamilton on SimilarWeb. The key metrics to look for are: monthly visits, average visit duration, pages per visit, and traffic by country. Moreoever, check the traffic sources. For example "Direct" traffic is a good sign.
Check the "Domain Rating" of Hamilton on Ahrefs. The domain rating is a measure of the strength of a website's backlink profile on a scale from 0 to 100. It shows the strength of Hamilton's backlink profile compared to the other websites. In most cases a domain rating of 60+ is considered good and 70+ is considered very good.
Check the "Domain Authority" of Hamilton on MOZ. A website's domain authority (DA) is a search engine ranking score that predicts how well a website will rank on search engine result pages (SERPs). It is based on a 100-point logarithmic scale, with higher scores corresponding to a greater likelihood of ranking. This is another useful metric to check if a website is good.
The latest comments about Hamilton on Reddit. This can help you find out how popualr the product is and what people think about it.
Yep. When I was designing https://github.com/dagworks-inc/hamilton part of the idea was to make it easy to understand what and where. That is, enable one to grep for function definitions and their downstream use easily, and where people can't screw this up. You'd be surprised how easy it is to make a code base where grep doesn't help you all that much (at... - Source: Hacker News / almost 2 years ago
Graph-based libraries for building ML/AI systems: - Burr -- build AI applications/agents as state machines https://github.com/dagworks-inc/burr Looking for feedback -- we had some good initial traction on HN, and are looking for OS users/contributors/people who are building complimentary tooling! - Source: Hacker News / almost 2 years ago
Hey HN โ Stefan and Elijah here from DAGWorks (http://dagworks.io/), weโre the authors of Hamilton (https://github.com/dagworks-inc/hamilton), an open-source library for building self-documenting, modular dataflows in python that works for data, ML, LLM pipelines, & even web-workflows. Weโve been developing this UI for a while and weโre excited to say we... - Source: Hacker News / about 2 years ago
In this post, weโll show how your team can turn any utility function(s) into reusable IPython Jupyter magics for a better notebook experience. As an example, weโll use Hamilton, my open source library, to motivate the creation of a magic that facilitates better development ergonomics for using it. You neednโt know what Hamilton is to understand this post. - Source: dev.to / over 2 years ago
This is me. I drive an open source library Hamilton that people doing time-series/ML work love to use. I'm building a paid product around it at DAGWorks, and I'm after feedback on our current version. Can I entice anyone to:. Source: about 3 years ago
From a nuts and bolts perspective, I've been thinking of building some reactivity on top of https://github.com/dagworks-inc/hamilton (author here) that could get at this. (If you have a use case that could be documented, I'd appreciate it.). - Source: Hacker News / about 3 years ago
Otherwise, I'm biased here, but check out https://github.com/dagworks-inc/hamilton - it could be your universal layer that expresses how things should flow, that is orchestration system agnostic, which would make it easy to migrate between systems easily. Source: over 3 years ago
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