from datetime import datetime

from CommonServerPython import *  # noqa: E402 lgtm [py/polluting-import]


def _get_incident():
    return demisto.incidents()[0]


def displayAnalyticalFeatures():
    incident = _get_incident()
    entityValue = ""
    anomalyName = ""
    riskDate = ""
    entityTypeId = 0
    displayData = []
    for label in incident["labels"]:
        if label["value"] is not None and label["type"] == "entityTypeId":
            entityTypeId = label["value"]
        if label["value"] is not None and label["type"] == "riskDate":
            riskDate = datetime.strptime(label["value"], "%m/%d/%Y %H:%M:%S").strftime("%Y-%m-%d")
        if label["value"] is not None and label["type"] == "entity":
            entityValue = label["value"]

    anomalies = incident["CustomFields"]["gracaseanomalydetails"]
    if int(entityTypeId) > 0:
        for anomalyDetailString in anomalies:
            anomalyName = ""
            for key in anomalyDetailString:
                if key is not None and key == "anomalyname":
                    anomalyName = anomalyDetailString[key]

            fromDate = riskDate
            toDate = riskDate

            res = execute_command(
                "gra-analytical-features-entity-value",
                {
                    "entityValue": entityValue,
                    "modelName": anomalyName,
                    "fromDate": fromDate,
                    "toDate": toDate,
                    "entityTypeId": entityTypeId,
                    "using": incident["sourceInstance"],
                },
            )
            if res is not None:
                for analyticalObj in res:
                    if analyticalObj is not None:
                        for key1 in analyticalObj:
                            if key1 == "analyticalFeatureValues":
                                analyticalFeatures = analyticalObj[key1]
                                if analyticalFeatures is not None:
                                    for feature in analyticalFeatures:
                                        displayData.append(
                                            {
                                                "Anomaly Name": anomalyName,
                                                "Analytical Feature": feature,
                                                "Count": len(analyticalFeatures[feature]),
                                                "Values": analyticalFeatures[feature],
                                            }
                                        )

        if len(displayData) > 0:
            data = {
                "Type": entryTypes["note"],
                "ContentsFormat": formats["markdown"],
                "Contents": displayData,
                "HumanReadable": tableToMarkdown(
                    None, displayData, headers=["Anomaly Name", "Analytical Feature", "Count", "Values"]
                ),
            }
            return_results(data)


def main():
    try:
        displayAnalyticalFeatures()
    except Exception as ex:
        return_error(f"Failed to execute gra-analytical-feature-display. Error: {ex!s}")


if __name__ in ("__main__", "__builtin__", "builtins"):  # pragma: no cover
    main()