Feeding the Dog in a Timely Manner

# Create Compliance DYNAMIC TOLERANCE Policy
#
# Main function, establishes a connection to DataTrails using an App Registration then uses that
# to create a Compliance DYNAMIC TOLERANCE 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 (
    CompliancePolicyDynamicTolerance,
)
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 DYNAMIC TOLERANCE policy creation.

* Connect to DataTrails with client ID and client secret
* Creates a Compliance DYNAMIC TOLERANCE 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 DYNAMIC TOLERANCE compliance policy for Fed/Feed Events. If time between
    Feed/Fed Events is .5 greater than the average time between similar Events in
    the past week, then Golden Retriever Asset is out of compliance.
    """
    dynamic_tolerance_policy = arch.compliance_policies.create(
        CompliancePolicyDynamicTolerance(
            description="Average time between Fed/Feed Events",
            display_name="Outlying Feed Events",
            asset_filter=[
                ["attributes.arc_display_type=Golden Retriever"],
            ],
            event_display_type="Feed",
            closing_event_display_type="Fed",
            dynamic_window=604800,
            dynamic_variability=0.5,
        )
    )
    print("DYNAMIC_TOLERANCE_POLICY:", json_dumps(dynamic_tolerance_policy, indent=4))
    return dynamic_tolerance_policy

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

Refresh token

DYNAMIC_TOLERANCE_POLICY: {
    "identity": "compliance_policies/d02099fa-adb5-43b3-b2d6-60bf54ad247a",
    "compliance_type": "COMPLIANCE_DYNAMIC_TOLERANCE",
    "description": "Average time between Fed/Feed Events",
    "display_name": "Outlying Feed Events",
    "asset_filter": [
        {
            "or": [
                "attributes.arc_display_type=Golden Retriever"
            ]
        }
    ],
    "event_display_type": "Feed",
    "closing_event_display_type": "Fed",
    "time_period_seconds": "0",
    "dynamic_window": "604800",
    "dynamic_variability": 0.5,
    "richness_assertions": []
}
Compliance_Policy {
    "identity": "compliance_policies/d02099fa-adb5-43b3-b2d6-60bf54ad247a",
    "compliance_type": "COMPLIANCE_DYNAMIC_TOLERANCE",
    "description": "Average time between Fed/Feed Events",
    "display_name": "Outlying Feed Events",
    "asset_filter": [
        {
            "or": [
                "attributes.arc_display_type=Golden Retriever"
            ]
        }
    ],
    "event_display_type": "Feed",
    "closing_event_display_type": "Fed",
    "time_period_seconds": "0",
    "dynamic_window": "604800",
    "dynamic_variability": 0.5,
    "richness_assertions": []
}