import pandas as pd
from diagnosis.preprocess.utils import utils


def convert_slowlog_to_metrics(data: pd.DataFrame, start_ts, end_ts, sqlite_name):
    digest_data = collect_timestamps_for_digest(data)
    metric = utils.convert_to_metrics(digest_data, start_ts, end_ts, 120)
    sqlite_data = utils.build_data_for_sqlite(metric, start_ts, end_ts, 120)
    create_sql, insert_sql = utils.build_create_sql(
        sqlite_data, "slowlog_rate", "INTEGER", True)
    utils.create_sqlite(sqlite_name, create_sql, insert_sql, sqlite_data[1:])


def collect_timestamps_for_digest(data: pd.DataFrame):
    result = {}
    for index, row in data.iterrows():
        key = '"{}"'.format(row["digest"])
        value = int(row["time"])
        if key not in result:
            result[key] = []
        result[key].append(value)
    return result