DoIt VS Metaflow

DoIt Reviews

Metaflow Reviews

DoIt mentions (14)

• How do you deal with CI, project config, etc. falling out of sync across repos?

  I like mage for Go and doit for Python. Source: 5 months ago

• Show HN: Jeeves – A Pythonic Alternative to GNU Make

  An alternative to Scons could be Doit (), which if I remember correctly was built as a faster alternative to Scons. See also reasons of some users to prefer the later to other mentioned here: . - Source: Hacker News / 6 months ago

• Makefile Tricks for Python Projects

  Or use https://pydoit.org and a virtualenv and be happy. - Source: Hacker News / 12 months ago

• Write Posix Shell

  If you code in Python, your probably should use the language as much as possible and avoid calling shell commands. E.G: - manipulate the file system with pathlib - do hashes with hashlib - zip with zipfile - set error code with sys.exit - use os.environ for env vars - print to stderr with print(..., file=...) - sometimes you'll need to install lib. Like, if you want to manipulate a git repo, instead of calling the... - Source: Hacker News / about 1 year ago

• Alternatives to Makefile for Python

  I've been using Doit for a project which involves gathering together documents made up of multiple Markdown files and converting to multiple formats. It's really cool but has some irritations. It didn't end up being much simpler than Make for me. I'm interested in trying some of the alternatives people have posted. Source: over 1 year ago

Metaflow mentions (12)

• What are some open-source ML pipeline managers that are easy to use?

  I would recommend the following: - https://www.mage.ai/ - https://dagster.io/ - https://www.prefect.io/ - https://metaflow.org/ - https://zenml.io/home. Source: about 1 year ago

• Needs advice for choosing tools for my team. We use AWS.

  1) I've been looking into [Metaflow](https://metaflow.org/), which connects nicely to AWS, does a lot of heavy lifting for you, including scheduling. Source: about 1 year ago

• Selfhosted chatGPT with local contente

  Even for people who don't have an ML background there's now a lot of very fully-featured model deployment environments that allow self-hosting (kubeflow has a good self-hosting option, as do mlflow and metaflow), handle most of the complicated stuff involved in just deploying an individual model, and work pretty well off the shelf. Source: about 1 year ago

• [OC] Gender diversity in Tech companies

  They had to figure out video compression that worked at the volume that they wanted to deliver. They had to build and maintain their own CDN to be able to have a always available and consistent viewing experience. Don’t even get me started on the resiliency tools like hystrix that they were kind enough to open source. I mean, they have their own fucking data science framework and they’re looking into using neural... Source: over 1 year ago

• Going to Production with Github Actions, Metaflow and AWS SageMaker

  Github Actions, Metaflow and AWS SageMaker are awesome technologies by themselves however they are seldom used together in the same sentence, even less so in the same Machine Learning project. - Source: dev.to / almost 2 years ago