rocketry VS Mage

Intuitive scheduling framework: https://rocketry.readthedocs.io/

One easy option would be to use Rocketry, it's pure Python:

It has bunch of features: logical scheduling syntax, parallelism/concurrency, dynamic parametization, log to database etc. You can read from the docs: https://rocketry.readthedocs.io/

It's the creator of Rocketry, Red Mail and Red Box again. This week I thought to make it easier to integrate command-line programs to your Python applications.

If you don't need fancy UIs (or you can create those yourself), I have heard some people are replacing Airflow with Rocketry. Rocketry is very easy to set up and use and its scheduling mechanics are pretty advanced.

If you need a scheduler (that also supports custom conditions like "run when there is X amount of emails"), I have another library for that: Rocketry

Smtplib is a pain to work with (which is the reason I wrote Red Mail). For the scheduling, I also happen to have a library that is often useful for this sorts of problems: https://rocketry.readthedocs.io

I have been thinking of creating an algo using Rocketry at some point. It's very easy to create custom conditions and combine these with logical statement. For example, you could set your algo (a function) running when volatility is x amount and you have y amount balance.

I have been tackling the same problem and it has recently gained popularilty. In case you want to take a look at Rocketry: https://github.com/Miksus/rocketry

In the coming years, Mage will create a cooperative experience so that developers can build data pipelines with their team and level up together. After that journey, Mage will go on an epic quest to create the 1st open world community experience in the data universe.

Link to original blog: https://www.mage.ai/blog/data-sources-ep-2-aws-s3-to-postgres-data-sync-using-singer

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

You're invited to participate in the very first Mage Battlegrounds: Craft insights from real-time customer behavior analysis, a 24-hour virtual hackathon hosted by Shashank Mishra! This data engineering competition will take place on Saturday, April 15, 2023 beginning at 11am (PST). This will be a global event open to all participants who register.

Try this feature: https://github.com/mage-ai/mage-ai/issues/1166

Seeing if we can use it in https://github.com/mage-ai/mage-ai

That being said there’s a solid family of services just breaking ground that make the local pipeline deployment easier (check out https://www.mage.ai, which does have a clear path to cloud deployment of locally developed pipes, it just isn’t well documented yet, and also https://www.neuronsphere.io - which doesn’t have a public solution YET (they’re internally testing an alpha) but they built a cloud deployable solution for their paying customers and working to release one for freemium use)

7️⃣ mage-ai/mage-ai

Yes, check out how Mage does it: https://github.com/mage-ai/mage-ai/tree/master/mage_integrations/mage_integrations/destinations/delta_lake_s3