def main()

in src/responsibleai/rai_analyse/create_score_card.py [0:0]
61 lines of code
13 McCabe index (conditional complexity)

def main(args):
    dashboard_info = load_dashboard_info_file(args.rai_insights_dashboard)
    _logger.info("Constructor info: {0}".format(dashboard_info))

    insight_data = RaiInsightData(args.rai_insights_dashboard)
    with open(args.pdf_generation_config, "r") as json_file:
        config = json.load(json_file)

    if args.predefined_cohorts_json:
        with open(args.predefined_cohorts_json, "r") as json_file:
            cohorts_definition = json.load(json_file)
            cohorts_map = {
                c["name"]: c["cohort_filter_list"] for c in cohorts_definition
            }
            config["cohorts_definition"] = cohorts_map

    config = validate_and_correct_config(config, insight_data)

    for k, v in config["Metrics"].items():
        if "threshold" in v.keys():
            tt, ta = parse_threshold(v["threshold"])
            if tt and ta:
                config["Metrics"][k]["threshold"] = (tt, ta)
            else:
                config["Metrics"][k].pop("threshold")

    if not args.local:
        run = Run.get_context()
        run_details = run.get_details()
        ws = run.experiment.workspace
        wsid = f"/subscriptions/{ws.subscription_id}/resourceGroups/{ws.resource_group}/\
        providers/Microsoft.MachineLearningServices/workspaces/{ws.name}"
        dashboard_link = "https://ml.azure.com/model/analysis/{}/{}/?wsid={}".format(
            dashboard_info[DashboardInfo.RAI_INSIGHTS_MODEL_ID_KEY],
            dashboard_info[DashboardInfo.RAI_INSIGHTS_GATHER_RUN_ID_KEY],
            wsid,
        )

        if "startTimeUtc" not in run_details:
            # Get UTC from python datetime module if this is not available from run details
            startTimeUtc = datetime.utcnow().strftime('%Y-%m-%dT%H:%M:%S.%fZ')
        else:
            startTimeUtc = run_details["startTimeUtc"]

        config["runinfo"] = {
            "submittedBy": run_details["submittedBy"],
            "startTimeUtc": startTimeUtc,
            "dashboard_link": dashboard_link,
            "model_id": dashboard_info[DashboardInfo.RAI_INSIGHTS_MODEL_ID_KEY],
            "dashboard_title": dashboard_info[
                DashboardInfo.RAI_INSIGHTS_DASHBOARD_TITLE_KEY
            ],
        }

    if config["Model"]["ModelType"].lower() == "regression":
        wf = Workflow(insight_data, config, args, RegressionComponents)
    elif config["Model"]["ModelType"].lower() in ("classification", "multiclass"):
        wf = Workflow(insight_data, config, args, ClassificationComponents)
    else:
        raise ValueError(
            "Model type {} cannot be matched to a score card generation workflow".format(
                config["Model"]["ModelType"]
            )
        )

    wf.generate_pdf()

    if not args.local:
        add_properties_to_gather_run(
            dashboard_info, {"ScoreCardTitle": config["Model"]["ModelName"]}
        )
        run.upload_folder("scorecard", args.pdf_output_path)