trainML client SDK and command line utilities
Project description
trainML Python SDK and Command Line Tools
Provides programmatic access to trainML platform.
Installation
Python 3.8 or above is required.
pip install trainml
Authentication
Prerequisites
You must have a valid trainML account. On the account settings page click the Create
button in the API Keys
section. This will automatically download a credentials.json
file. This file can only be generated once per API key. Treat this file as a password, as anyone with access to your API key will have the ability to create and control resources in your trainML account. You can deactivate any API key by clicking the Remove
button.
Creating resources on the trainML platform requires a non-zero credit balance. To purchase credits or sign-up for automatic credit top-ups, visit the billing page.
Methods
Credentials File
The easiest way to authenticate is to place the credentials file downloaded into the .trainml
folder of your home directory and ensure only you have access to it. From the directory that the credentials.json
file was downloaded, run the following command:
mkdir -p ~/.trainml
mv credentials.json ~/.trainml/credentials.json
chmod 600 ~/.trainml/credentials.json
Environment Variables
You can also use environment variables TRAINML_USER
and TRAINML_KEY
and set them to their respective values from the credentials.json
file.
export TRAINML_USER=<'user' field from credentials.json>
export TRAINML_KEY=<'key' field from credentials.json>
python create_job.py
Environment variables will override any credentials stored in ~/.trainml/credentials.json
Runtime Variables
API credentials can also be passed directly to the TrainML object constructor at runtime.
import trainml
trainml = trainml.TrainML(user="user field from credentials.json",key="key field from credentials.json>")
await trainml.jobs.create(...)
Passing credentials to the TrainML constructor will override all other methods for setting credentials.
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