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": "$servicename$"
                                 }]
 #                 {
                    "SLO 1": {
                     "sloname": "SLO 1",
                     "services": [
                   {
                     "serviceName": "Service 1",
                     "processGroup": "Process Group 1",
                     "tags": ["tag1", "tag2"]
                   },
                   {
                     "serviceName": "Service 2",
                     "processGroup": "Process Group 2",
                     "tags": ["tag3", "tag4"]
                    }
                ]
                    },
                     "SLO 2": {
                     "sloname": "SLO 2",
                      "services": [
                   {
                      "serviceName": "Service 3",
                     "processGroup": "Process Group 3",
                     "tags": ["tag5", "tag6"]
      }
    ]
  }
}
#
                  }} 
                   for kr in krs:
                      reportItem[kr.metadata.name]=
                   
                   # DEBUG
                   # print(krs)
                   for x in krs:
                        print(x.metadata)
                        
                        
                             # regex ~ XYZ ~

                             #filtering the SLO dataframe based on those dates and the service name
                             

# import datetime


# import re

#extract all the service names that start with "TP_"
metric_expression = 'sum(duration), filter(entity.service.name, beginsWith("TP_"))'
# Define regex pattern to match service names
regex_pattern = r'beginsWith\("TP_(.*?)"\)'
# Find all matches of pattern in metric expression
matches = re.findall(regex_pattern, metric_expression)

print(matches)

        
#get detail info service names
import requests
import json
environment_id = "ENVIRONMENT_ID"
api_token = "dt0c01.MBX344ELRJNDGSWGOSK3JBE5.KHJ6BLKLZ6UB6NKJQRXYINLDCKN36HGOK6ECYAOZ3REF2KHWM2NIBIKOITVXCWUT"
headers = {"Authorization": "Api-Token {}".format(api_token)}

# url = "https://xxu26128.live.dynatrace.com/api/v1/entity/services".format(environment_id)
params = {"filter": "displayName LIKE 'TP_%'"}

# response = requests.get(url, headers=headers, params=params)
# response_json = json.loads(response.text)

# for service in response_json["entities"]:
#     display_name = service["displayName"]
#     print("Service Name: {0}".format(display_name))



if __name__ == "__main__":
    main()