Boon Amber Python SDK v2
An SDK for Boon Amber sensor analytics
- Website: boonlogic.com
- Documentation: Boon Docs Main Page
- SDK Functional Breakdown: amber-python-sdk classes and methods
Installation
The Boon Amber SDK is a Python 3 project and can be installed via pip.
pip install boonamber
Credentials setup
Note: An account in the Boon Amber cloud must be obtained from Boon Logic to use the Amber SDK.
The license key and secret key should be placed in a file named ~/.Amber.license whose contents are the following:
{
"default": {
"license-key": "AMBER-ACCOUNT-LICENSE",
"secret-key": "AMBER-ACCOUNT-SECRET",
"server": "https://v2.amber.boonlogic.com"
}
}
The ~/.Amber.license file will be consulted by the Amber SDK to find and authenticate your account credentials with the Amber server. Profile configurations may also be set through a set of environment variables or kwargs when the AmberV2Client object is created.
Connectivity test
The following Python script provides a basic proof-of-connectivity:
import sys
import json
from boonamber import AmberV2Client, ApiException
try:
# Use ~/.Amber.license file and "default" profile
amber = AmberV2Client()
version_info = amber.get_version()
except ApiException as e:
print(f"Error: {e}")
sys.exit(1)
print(json.dumps(version_info.to_dict(), indent=4))
Running the connect-example.py script should yield output like the following:
$ python connect-example.py
{
"release": "0.0.405",
"api-version": "/v2",
"builder": "ec74f421",
"expert-api": "dee23681",
"expert-common": "300a588e",
"nano-secure": "61c431e2",
"swagger-ui": "914af396"
}
where the dictionary {}
lists all sensors that currently exist under the given Boon Amber account.
Full Example
Example to demonstrate each API call
Fusion Example
Example to demonstrate submitting data via the label for individual features of a fusion vector.
Advanced CSV file processor
Example of streaming a .csv file. Full Amber analytic results will be displayed after each streaming request.
stream-advanced-v2.py
output_current.csv
Pretrain example
Example of pretraining a .csv file