aerostat-launcher 0.0.2

A simple CLI tool to deploy your Machine Learning models to cloud, with a public API to use.

Aerostat

Aerostat is a simple CLI tool to deploy your Machine Learning models to cloud, with a public API to use.

Get started

Installation

The name Aerostat has been used by another PyPI project, please install this package with:

pip install aerostat-launcher

Once installed, it can be used directly via aerostat. Most likely you will need to run this module with python -m prefix since it is not included in $PATH.

To deploy your model, there are only three commands needed: install, login, and deploy.

Setup

Run the following command, and it will install all the dependencies needed to run Aerostat.

python -m aerostat install

To login to Aerostat, you need to run the following command:

python -m aerostat login

You will be prompted to choose an existing AWS credentials, or enter a new one. The AWS account used needs to have AdministratorAccess.

Deploy

To deploy your model, you need to dump your model to a file with pickle, and run the following command:

python -m aerostat deploy

You will be prompted to enter:

• the path to your model file
• the input columns of your model
• the ML library used for your model

Or you can provide these information as command line options like:

python -m aerostat deploy --model-path /path/to/model --input-columns "['col1','col2','col3']" --python-dependencies scikit-learn

Roadmap

• Deploy a model to AWS Lambda
• Improve error handling, including login checks
• Improve user interface, including rewrite prompts with Rich, use more colors and emojis
• Return deployment info and simple test demo with HTTP GET request
• Make it a pip installable package
• Handle AWS authentication from the CLI
• Support deploying to GCP