This package executes sequences written in Python and provides control mechanisms to them.
Our Python base image contains only the necessary libraries to operate. It's perfect for those who need a lightweight image for running Sequences written in Python.
Our TensorFlow image enables the use of GPU, which is ideal for intensive computations such as machine learning.
Specify python docker image used by Instances when starting sth
sth --runner-py-image <image>
To take advantage of the GPU features, you need to run Sequence with the appropriate limits. For example:
si seq start --limits "{\"gpu\": true}
This package is part of Scramjet Transform Hub.
Scramjet Transform Hub is a deployment and execution platform. Once installed on a server, it will allow you to start your programs and keep them running on a remote machine. You will be able to start programs in the background or connect to them and see their output directly on your terminal. You will be able to pipe your local data to the program, as if it was running from your terminal. You can start your server in AWS, Google Cloud or Azure, start it on your local machine, install it on a Raspberry Pi or wherever else you'd like.
There's no limit what you can use it for. You want a stock checker? A chat bot? Maybe you'd like to automate your home? Retrieve sensor data? Maybe you have a lot of data and want to transfer and wrangle it? You have a database of cities and you'd like to enrich your data? You do machine learning and you want to train your set while the data is fetched in real time? Hey, you want to use it for something else and ask us if that's a good use? Ask us via email or hop on our Scramjet Discord!
- Scramjet, the company behind Transform Hub
- The Scramjet Framework - functional reactive stream processing framework
- The Transform Hub repo on github
- You can see the Scramjet Transform Hub API docs here
- You can see the CLI documentation here, but
si helpshould also be quite effective. - Don't forget to ⭐ this repo if you like it,
subscribeto releases and keep visiting us for new versions and updates. - You can open an issue - file a bug report or a feature request here
This module is licensed under AGPL-3.0 license.
The Scramjet Transform Hub project is dual-licensed under the AGPL-3.0 and MIT licenses. Parts of the project that are linked with your programs are MIT licensed, the rest is AGPL.
We accept valid contributions and we will be publishing a more specific project roadmap so contributors can propose features and also help us implement them. We kindly ask you that contributed commits are Signed-Off git commit --sign-off.
We provide support for contributors via test cases. If you expect a certain type of workflow to be officially supported, please specify and implement a test case in Gherkin format in bdd directory and include it in your pull request. More info about our BDD test you will find here.
The project need's your help! There's lots of work to do and we have a lot of plans. If you want to help and be part of the Scramjet team, please reach out to us, on discord or email us: opensource@scramjet.org.
Do you like this project? It helped you to reduce time spent on delivering your solution? You are welcome to buy us a coffee ☕ Thanks a lot! ;)
- There's also a Paypal donation link if you prefer that:
