def parse_ga_response()

in redash/query_runner/google_analytics.py [0:0]
48 lines of code
16 McCabe index (conditional complexity)

def parse_ga_response(response):
    columns = []
    for h in response["columnHeaders"]:
        if h["name"] in ("ga:date", "mcf:conversionDate"):
            h["dataType"] = "DATE"
        elif h["name"] == "ga:dateHour":
            h["dataType"] = "DATETIME"
        columns.append(
            {
                "name": h["name"],
                "friendly_name": h["name"].split(":", 1)[1],
                "type": types_conv.get(h["dataType"], "string"),
            }
        )

    rows = []
    for r in response.get("rows", []):
        d = {}
        for c, value in enumerate(r):
            column_name = response["columnHeaders"][c]["name"]
            column_type = [col for col in columns if col["name"] == column_name][0][
                "type"
            ]

            # mcf results come a bit different than ga results:
            if isinstance(value, dict):
                if "primitiveValue" in value:
                    value = value["primitiveValue"]
                elif "conversionPathValue" in value:
                    steps = []
                    for step in value["conversionPathValue"]:
                        steps.append(
                            "{}:{}".format(step["interactionType"], step["nodeValue"])
                        )
                    value = ", ".join(steps)
                else:
                    raise Exception("Results format not supported")

            if column_type == TYPE_DATE:
                value = datetime.strptime(value, "%Y%m%d")
            elif column_type == TYPE_DATETIME:
                if len(value) == 10:
                    value = datetime.strptime(value, "%Y%m%d%H")
                elif len(value) == 12:
                    value = datetime.strptime(value, "%Y%m%d%H%M")
                else:
                    raise Exception(
                        "Unknown date/time format in results: '{}'".format(value)
                    )

            d[column_name] = value
        rows.append(d)

    return {"columns": columns, "rows": rows}