dagster-sklearn
dagster
| dagster-sklearn | dagster | |
|---|---|---|
| 3 | 46 | |
| 40 | 10,215 | |
| - | 2.1% | |
| 0.0 | 10.0 | |
| about 1 year ago | 5 days ago | |
| Python | Python | |
| - | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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dagster-sklearn
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Scheduling tools for ETL and ML flow
I would give dagster a look. It has a built-in native scheduler and is cross-platform. It is general purpose, so your team can grow with it and tackle broader set of use cases if needed. If you struggle to get started after reading their docs/tutorials, you can take a look at my personal repo. Ive gotten a few feedback that my example has been very useful in getting started. I know they revamped their docs recently, but havent looked at their tutorial again or looked to see if they provided an intermediate level full example yet, so I need to get back in there to see.
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Dagster Tutorials/Presentations
Hey! I've recently started to use dagster and it's been great with its 0.11.x releases. I am still a newbie with it and maybe only use 20% of its features and abstractions. Here's my work-in-progress personal Github repo. Not sure if you'll learn much from it.
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Is anyone trying to switch out of data science, and if so, what jobs are you applying for?
I have created a trivial, contrived scikit-learn example using dagster so that people have an idea of how it can be used.
dagster
- Experience with Dagster.io?
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Dagster tutorials
My recommendation is to continue on with the tutorial, then look at one of the larger example projects especially the ones named “project_”, and you should understand most of it. Of what you don't understand and you're curious about, look into the relevant concept page for the functions in the docs.
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The Dagster Master Plan
I found this example that helped me - https://github.com/dagster-io/dagster/tree/master/examples/project_fully_featured/project_fully_featured
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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
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The Why and How of Dagster User Code Deployment Automation
In Helm terms: there are 2 charts, namely the system: dagster/dagster (values.yaml), and the user code: dagster/dagster-user-deployments (values.yaml). Note that you have to set dagster-user-deployments.enabled: true in the dagster/dagster values-yaml to enable this.
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Best Orchestration Tool to run dbt projects?
Dagster seemed really cool when I looked into it as an alternative to airflow. I especially like the software defined assets and built-in lineage which I haven't seen in any other tool. However it seems it does not support RBAC which is a pretty big issue if you want a self-service type of architecture, see https://github.com/dagster-io/dagster/issues/2219. It does seem like it's available in their hosted version, but I wanted to run it myself on k8s.
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dbt Cloud Alternatives?
Dagster? https://dagster.io
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What's the best thing/library you learned this year ?
One that I haven't seen on here yet: dagster
- Anyone have an example of a project where a handful of the more popular Python tools are used? (E.g. airbyte, airflow, dbt, and pandas)
- Can we take a moment to appreciate how much of dataengineering is open source?
What are some alternatives?
Dask - Parallel computing with task scheduling
Prefect - The easiest way to build, run, and monitor data pipelines at scale.
ploomber - The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
yellowbrick - Visual analysis and diagnostic tools to facilitate machine learning model selection.
Mage - 🧙 The modern replacement for Airflow. Mage is an open-source data pipeline tool for transforming and integrating data. https://github.com/mage-ai/mage-ai
best-of-ml-python - 🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
airbyte - The leading data integration platform for ETL / ELT data pipelines from APIs, databases & files to data warehouses, data lakes & data lakehouses. Both self-hosted and Cloud-hosted.
dagster-example-pipeline - Template Dagster repo using poetry and a single Docker container; works well with CICD
MLflow - Open source platform for the machine learning lifecycle
meltano
OpenLineage - An Open Standard for lineage metadata collection