secrets-env
Extension to the crystal lang ENV module to support reading secrets (by place-labs)
lithops
A multi-cloud framework for big data analytics and embarrassingly parallel jobs, that provides an universal API for building parallel applications in the cloud ☁️🚀 (by lithops-cloud)
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| secrets-env | lithops | |
|---|---|---|
| - | 2 | |
| 6 | 305 | |
| - | 3.3% | |
| 0.0 | 9.4 | |
| about 3 years ago | 9 days ago | |
| Crystal | Python | |
| MIT License | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.
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.
secrets-env
Posts with mentions or reviews of secrets-env.
We have used some of these posts to build our list of alternatives
and similar projects.
We haven't tracked posts mentioning secrets-env yet.
Tracking mentions began in Dec 2020.
lithops
Posts with mentions or reviews of lithops.
We have used some of these posts to build our list of alternatives
and similar projects.
- Lithops: A multi-cloud framework for embarrassingly parallel jobs
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[D] For those of you who don't own a GPU, how do you run your experiments or train your models?
At work for non-ML/non-GPU stuff I've been using Lithops for running code on dynamically-provisioned cloud resources (serverless or VM). It pickles your code & runtime variables, sends them to cloud storage, runs the code & downloads the results, all relatively transparently. You're just calling Python functions with Python objects on your local computer and not having to worry about deploying your code, packaging your data, etc. Better still, you can scale up for things like hyperparameter sweeps by just dispatching more calls in parallel, and it will provision more resources.
What are some alternatives?
When comparing secrets-env and lithops you can also consider the following projects:
FaaStRuby
treequeues - High performance queues for pytree objects.
gcf.cr - gcf.cr provides serverless execution and deployment of crystal language code in Google Cloud Functions
pyspark-on-aws-emr - The goal of this project is to offer an AWS EMR template using Spot Fleet and On-Demand Instances that you can use quickly. Just focus on writing pyspark code.
crystal_openfaas - OpenFaaS template for the crystal programming language
open-lambda - An open source serverless computing platform