request-migrations
dagster
| request-migrations | dagster | |
|---|---|---|
| 1 | 46 | |
| 181 | 10,274 | |
| - | 2.7% | |
| 0.0 | 10.0 | |
| over 2 years ago | 3 days ago | |
| PHP | Python | |
| MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
request-migrations
-
API versioning has no “right way” (2017)
The key to doing migrations on the request is having the migrations live in single classes/files. It makes it very clean to have the app migrate from version 3 to version 12 with the 9 or so classes handing the response from one to the other.
I made a package a few years ago in PHP/Laravel that focuses on this: https://github.com/tomschlick/request-migrations
dagster
- Experience with Dagster.io?
-
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.
-
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
-
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
-
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.
-
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.
-
dbt Cloud Alternatives?
Dagster? https://dagster.io
-
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?
openclassify - OpenClassify is modular and most advanced open source classified platform build with Laravel 8.1 & PHP 8.2 Supported. Included Pyrocms
Prefect - The easiest way to build, run, and monitor data pipelines at scale.
atomic-locks-middleware - A package designed to ensure that only one request is processed at a time.
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
saloon - 🤠 Build beautiful API integrations and SDKs with Saloon
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
laravel-quickstart - Everything you need to start a production-ready Laravel+MariaDB+PostgreSQL+Bootstrap system, in 5 minutes or less! https://vimeo.com/254289186
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.
laravel-refresh-module-database - Laravel Refresh Database trait with Module Support for faster TDD by Module
MLflow - Open source platform for the machine learning lifecycle
Guzzle - Guzzle, an extensible PHP HTTP client
meltano