import pandas as pd
import numpy as np
import os 
import requests
import sys
import zipfile,io
import time
import random
import json
school_name = r"sy24 BTS School List v2.csv"
all_school = r"sy24 title I list v2.csv"
df1 = pd.read_csv(all_school)
bts_school = pd.read_csv(school_name)
school_list = list(df1["school"])
school_dict = set(list(df1["school"]))
result_df = df1.copy()
result_df = result_df.iloc[:,0:2]
sz1,sz2 = result_df.shape
sz3,sz4 = bts_school.shape
result_df["Principal"] = [0]*sz1
result_df["Educator"] = [0]*sz1
result_df["BTS_SchoolList"] = ["NO"]*sz1

bts_school_dict = {}
for i in range(sz3):
    if bts_school.iloc[i,0] not in bts_school_dict:
        bts_school_dict[bts_school.iloc[i,0]] = set(bts_school.iloc[i,1])
        
    else:
        bts_school_dict[bts_school.iloc[i,0]].add(bts_school.iloc[i,1])
"""
This section is for api token, survey id, datacenter info,
"""
api_token = "cnfvvtLBU93Jlk9CVJMzJHqarMZeBVP7KfSlSY3U"
survey_id_2023 = "SV_0JrTQmOw07819rg"
survey_id = "SV_0B6bHCWd9hSE1eK"
datacenter = "ca1"


def get_survey_responses():
    # part 1 get progress id
    url1 = "https://yul1.qualtrics.com/API/v3/surveys/{0}/export-responses".format(survey_id)
    payload1 = { "format": "csv","useLabels":True } 
    headers1 = {
        "Content-Type": "application/json",
        "Accept": "application/json",
        "X-API-TOKEN": "cnfvvtLBU93Jlk9CVJMzJHqarMZeBVP7KfSlSY3U"
    }
    response1 = requests.post(url1, json=payload1, headers=headers1)
    r1_json = response1.json()
    try:
        progess_id = r1_json["result"]["progressId"]
        
    except:
        print("error on step1")

    time.sleep(random.random()*2+5.6)



    # part 2 get file id
    url2 = "https://yul1.qualtrics.com/API/v3/surveys/{0}/export-responses/{1}".format(survey_id,progess_id)

    headers2 = {
        "Accept": "application/json",
        "X-API-TOKEN": "cnfvvtLBU93Jlk9CVJMzJHqarMZeBVP7KfSlSY3U"
    }

    response2 = requests.get(url2, headers=headers2)
    r2_json = response2.json()
    try:
        file_id = r2_json["result"]["fileId"]
    except:
        print("error on step 2")

    time.sleep(random.random()*3+3.14)


    # part 3 get export file
    
    url3 ="https://yul1.qualtrics.com/API/v3/surveys/{0}/export-responses/{1}/file".format(survey_id,file_id)
    headers3 = {
        "Accept": "application/octet-stream, application/json",
        "X-API-TOKEN": "cnfvvtLBU93Jlk9CVJMzJHqarMZeBVP7KfSlSY3U"
    }

    response3 = requests.get(url3, headers=headers3)
    try:
        df = pd.read_csv(io.BytesIO(response3.content),compression='zip', header=0, sep=',', quotechar='"')
        df_new = df[df["Finished"]==True]
        
    except:
        df = []








    return df


def get_totalsize()->int:
    sz1,_= result_df.shape
    return sz1




def checkpassword(username:str,password:str)->int:
    if username == "admin" and password =="Checkit2024!":
        return 1
    else:
        return 0 


    return 0

def get_response_data(df,role,role_label,district_label,school_label)->dict:
    res = {}
    df_new = df.copy()
    df_new = df_new[df_new[str(role_label)]==role]
    col1 = list(df_new.columns)
    p1_school = 0
    p2_school = 0
    
    fd =[]
    for i in range(len(col1)):
        if school_label in col1[i]:
            fd.append(i)
    
    p1_school = fd[0]
    p2_school = fd[-1]
    dstr_loc = 0
    for i in range(len(col1)):
        if district_label in col1[i]:
            dstr_loc = i
            break
    
    
        
            
        
        
        
    sz1,_ = df_new.shape
    for i in range(sz1):
        temp_dstr = df_new.iloc[i,dstr_loc]
        try:
            temp_schl = (df_new.iloc[i,p1_school:p2_school+1].dropna())[0]
                
    
            if (temp_dstr not in res) :
                res[temp_dstr]= {temp_schl:1}
            else:
                if temp_schl not in res[temp_dstr]:
                    res[temp_dstr][temp_schl] = 1
                else:
                    res[temp_dstr][temp_schl] +=1
    
        except:
            pass
    
    


    return res

def get_responses_check_df(df,role_label,district_label,school_label):
    # better to do that in {key:{key:value}}
    # {district:{school:vcount}}
    prn_dict = get_response_data(df,"Principal",role_label,district_label,school_label)
    edu_dict = get_response_data(df,"Educator",role_label,district_label,school_label)
    sz1,_ = result_df.shape 
    for i in range(sz1):
        if "District" not in result_df.iloc[i,0]:
            try:
                result_df.iloc[i,2] = prn_dict["Chart School or Other"][result_df.iloc[i,1]]
                
            except:
                result_df.iloc[i,2] = "NO"
                
            try:
                result_df.iloc[i,3] = edu_dict["Charter School or Other"][result_df.iloc[i,1]]
                
            except:
                result_df.iloc[i,3] = "NO"
                
            
        
        else:
                
            try:
                result_df.iloc[i,2] = prn_dict[result_df.iloc[i,0]][result_df.iloc[i,1]]
                
            except:
                result_df.iloc[i,2] = "NO"
            
            try:
                result_df.iloc[i,3] = edu_dict[result_df.iloc[i,0]][result_df.iloc[i,1]]
            except:
                result_df.iloc[i,3] = "NO"
                
    
            if (result_df.iloc[i,0] in bts_school_dict) and (result_df.iloc[i,1] in bts_school_dict[result_df.iloc[i,0]]):
                result_df.iloc[i,4] = "YES"
            else:
                result_df.iloc[i,4] = "NO"
            
        
        #result_df.iloc[i,2] = "Yes" if (result_df.iloc[i,1] in prn_list )else "No"
        #result_df.iloc[i,3] = "Yes" if (result_df.iloc[i,1] in edu_list )else "No"
                
    
    

    return result_df


def get_responses_check_df_v2():
    
    return 






def get_dict_from_str(str1:str)->dict:

    return json.unload(str1)