import yaml
from decouple import config
import dynatraceAPI
import pandas as pd
from pagination import Pagionation
from key_request_parser import krparser

from datetime import datetime, timedelta
import datetime
import re


def getSLO(ENV, DTAPIToken, DTENV):
    # DTENV = base url
    # DTAPIToken = sec token
    dtclient = dynatraceAPI.Dynatrace(DTENV, DTAPIToken)
    my_params_report = {"pageSize": 25}
    # gets all slos and filter later
    api_url_report = "/api/v2/slo"
    pages = dtclient.returnPageination(api_url_report, my_params_report, "slo")
    df = pd.DataFrame(pages.elements)
    df["env"] = ENV
    return df


def previous_week_range(date: datetime):
    start_date = date + timedelta(-date.weekday(), weeks=-1)
    end_date = date + timedelta(-date.weekday() - 1)
    return start_date, end_date


def main():
    # Get All SLOs

    reportItem = {}
    with open("./environment.yaml") as file:
        env_doc = yaml.safe_load(file)

    for env, doc in env_doc.items():
        token = dict(doc[2])
        url = dict(doc[1])

        if config(token.get("env-token-name")) != "":
            print("Gather data, hold on a minute")
            DTTOKEN = config(token.get("env-token-name"))
            DTURL = url.get("env-url")

            # krp = krparser.KRParser(krparser.KROption.VALIDATE_EXISTS | krparser.KROption.VALIDATE_HASDATA ,DTURL, DTTOKEN)

            slosF = getSLO(env, DTTOKEN, DTURL)
            slosF = slosF[slosF["name"].str.startswith("TP_")]

            # parse the metric Expression to get Services and Requests

            krs = []
            krp = krparser.KRParser(
                krparser.KROption.VALIDATE_EXISTS
                | krparser.KROption.VALIDATE_HASDATA
                | krparser.KROption.RESOLVESERVICES,
                DTURL,
                DTTOKEN,
            )

            for index, row in slosF.iterrows():
                krs.append(krp.parseBySLO(row))

            # x = 0

            # SLO Name | SERVICE | PROCESS GRUPPE | TAGS
            #                   {"sloname": {
            #                     "sloname":$sloname$,
            #                     "services":[{
            #                                    "serviceName": "$servicename$"
            #                                  }]
            #                   },
            #                   "sloname": {
            #                     "sloname":$sloname$,
            #                     "services":[{
            #                                    "serviceName": "$servicename$"
            #                                  }]

            for kr in krs:
                reportItem[kr.metadata["sloName"]] = {}
                reportItem[kr.metadata["sloName"]]["sloname"] = kr.metadata["sloName"]
                reportItem[kr.metadata["sloName"]]["services"] = []

                reportItem[kr.metadata["sloName"]]["services"].append(
                    {"serviceName": "$servicename$"}
                )

                extract_services_and_requests(kr.metadata["metricExpression"])

            print(reportItem)
            # filtering the SLO dataframe based on those dates and the service name


def extract_services_and_requests(metric_expression: str):
    services = []
    requests = []

    result = metric_expression.split("entityName.in")
    regex_pattern = r"~(.*?)~"
    method_list = ["GET", "POST", "http"]
    for x in result:
        matches = re.findall(regex_pattern, x)
        for match in matches:
            if match != "SERVICE":
                # TODO: not working properly. fix needed
                res = any(ele in match for ele in method_list)
                if res:
                    requests.extend(matches)
                else:
                    services.extend(matches)

    print(f"services: {services}")
    print("-" * 80)
    print(f"requests: {requests}")
    return result


if __name__ == "__main__":
    main()