Feeding the Dog

# Create Compliance CURRENT OUTSTANDING Policy
#
# Main function, establishes a connection to DataTrails using an App Registration then uses that
# to create a Compliance CURRENT OUTSTANDING Policy.
#
# Note: The purpose of DataTrails Jupyter Notebooks is to provide simplified examples that one can easily execute and digest.
# The DataTrails Python SDK is authored to work cleanly with more advanced coding techniques.
#
# DataTrails Python SDK: https://github.com/datatrails/datatrails-python
#

from json import dumps as json_dumps
from os import getenv

from archivist.archivist import Archivist
from archivist.compliance_policy_requests import (
    CompliancePolicyCurrentOutstanding,
)
from archivist.logger import set_logger

%reload_ext dotenv
%dotenv -o notebooks.env

# DATATRAILS_URL, DATATRAILS_APPREG_CLIENT, DATATRAILS_APPREG_SECRET are environment variables that represent connection parameters.
#
# DATATRAILS_URL = represents the url to the DataTrails application
# DATATRAILS_APPREG_CLIENT = represents the client ID from an Application Registration
# DATATRAILS_APPREG_SECRET = represents the client secret from an Application Registration
DATATRAILS_URL = getenv("DATATRAILS_URL")
DATATRAILS_APPREG_CLIENT = getenv("DATATRAILS_APPREG_CLIENT")
DATATRAILS_APPREG_SECRET = getenv("DATATRAILS_APPREG_SECRET")

"""
Main function of CURRENT OUTSTANDING policy creation.

* Connect to DataTrails with client ID and client secret
* Creates a Compliance CURRENT OUTSTANDING Policy
"""

# Optional call to set the logger level.  The argument can be either
# "INFO" or "DEBUG".  For more sophisticated logging control see our
# documentation.
set_logger("INFO")

# Initialize connection to DATATRAILS
print("Connecting to DATATRAILS")
print("DATATRAILS_URL", DATATRAILS_URL)
arch = Archivist(
    DATATRAILS_URL, (DATATRAILS_APPREG_CLIENT, DATATRAILS_APPREG_SECRET), max_time=300
)

Connecting to DATATRAILS
DATATRAILS_URL https://app.datatrails.ai

def create_compliance_policy(arch):
    """
    Creates a CURRENT OUTSTANDING compliance policy for feeding one's dog. If DataTrails sees a "Feed"
    event without a closing "Fed" event, then Golden Retriever Asset is out of compliance.
    """
    current_outstanding_policy = arch.compliance_policies.create(
        CompliancePolicyCurrentOutstanding(
            description="Ensuring my dog is fed",
            display_name="Feeding My Dog",
            asset_filter=[
                ["attributes.arc_display_type=Golden Retriever"],
            ],
            event_display_type="Feed",
            closing_event_display_type="Fed",
        )
    )
    print(
        "CURRENT_OUTSTANDING_POLICY:", json_dumps(current_outstanding_policy, indent=4)
    )
    return current_outstanding_policy

# Creates CURRENT OUTSTANDING compliance policy and prints result
compliance_policy = create_compliance_policy(arch)
print("Compliance_Policy", json_dumps(compliance_policy, indent=4))

Refresh token

CURRENT_OUTSTANDING_POLICY: {
    "identity": "compliance_policies/f896247e-bca5-4410-8c30-09adf81e9244",
    "compliance_type": "COMPLIANCE_CURRENT_OUTSTANDING",
    "description": "Ensuring my dog is fed",
    "display_name": "Feeding My Dog",
    "asset_filter": [
        {
            "or": [
                "attributes.arc_display_type=Golden Retriever"
            ]
        }
    ],
    "event_display_type": "Feed",
    "closing_event_display_type": "Fed",
    "time_period_seconds": "0",
    "dynamic_window": "0",
    "dynamic_variability": 0,
    "richness_assertions": []
}
Compliance_Policy {
    "identity": "compliance_policies/f896247e-bca5-4410-8c30-09adf81e9244",
    "compliance_type": "COMPLIANCE_CURRENT_OUTSTANDING",
    "description": "Ensuring my dog is fed",
    "display_name": "Feeding My Dog",
    "asset_filter": [
        {
            "or": [
                "attributes.arc_display_type=Golden Retriever"
            ]
        }
    ],
    "event_display_type": "Feed",
    "closing_event_display_type": "Fed",
    "time_period_seconds": "0",
    "dynamic_window": "0",
    "dynamic_variability": 0,
    "richness_assertions": []
}