import functions_framework
from firebase_functions import https_fn
# import firebase_admin
from firebase_admin import initialize_app, firestore
from google.cloud.firestore import FieldFilter
import pandas as pd
import datetime
import sys
import platform
import os
import io
from flask import send_file
from datetime import datetime

initialize_app()

@functions_framework.http
def consolidation(request):
    """HTTP Cloud Function.
    Args:
        request (flask.Request): The request object.
        <https://flask.palletsprojects.com/en/1.1.x/api/#incoming-request-data>
    Returns:
        The response text, or any set of values that can be turned into a
        Response object using `make_response`
        <https://flask.palletsprojects.com/en/1.1.x/api/#flask.make_response>.
    """

    if request.method == 'OPTIONS':
        headers = {
            'Access-Control-Allow-Origin': '*',
            'Access-Control-Allow-Methods': 'GET',
            'Access-Control-Allow-Headers': 'Content-Type',
            # 'Access-Control-Max-Age': '3600'
        }

        return ('', 204, headers)

    headers = {
        'Access-Control-Allow-Origin': '*'
    }

    request_json = request.get_json(silent=True)
    request_args = request.args

    if request_json and 'start_date' in request_json and 'end_date' in request_json:
        start_date = request_json['start_date']
        end_date = request_json['end_date']
    elif request_args and 'start_date' in request_args and 'end_date' in request_args:
        start_date = request_args['start_date']
        end_date = request_args['end_date']
    else:
        start_date = "2023-08-20"
        end_date = "2023-08-21"
      
    path_delim = "/"

    db = firestore.client()

    test_collection = db.collection("testData")

    data = []

    test_docs = test_collection.stream()
    for test_doc in test_docs:
        test_data = test_doc.to_dict()
        data.append(test_data)

    df = pd.DataFrame(data)

    output_filename = f'/tmp/data_{datetime.today().strftime("%d_%m_%Y_%H_%M")}.xlsx'

    output_path = os.getcwd() + path_delim + output_filename
    writer = pd.ExcelWriter(output_path, engine = 'openpyxl')
    df = df[(df['testTime'] > start_date) & (df['testTime'] <= end_date)]
    df = df.sort_values(by=['testTime'], ascending=False)
    
    column_names = ["_id", "classificationResult", "deviceRatioClass",  "prdClassification", "slopeRatioClass", "predictedDenovixRatio", "slopeRatio", "calculatedRatio", "deviceRatio", "kitSerial", "led1Gain1", "led1Gain2", "led1Gain4", "abs1", "led1Average", "led1Buffer", "led1Sample", "led2Gain1", "led2Gain2", "led2Gain4", "abs2", "led2Average", "led2Buffer", "led2Sample", "led3Gain1", "led3Gain2", "led3Gain4", "hb3", "abs3", "led3Average", "led3Buffer", "led3Sample", "led4Gain1", "led4Gain2", "led4Gain4", "hb4", "abs4", "led4Average", "led4Average", "led4Buffer", "led4Sample", "batteryLevel", "batteryVoltage", "solution", "concentration", "volume", "errorMessages", "deviceId", "deviceSerialNumber", "appVersion", "name", "testTime"]
    common_columns = [col for col in column_names if col in df.columns]
    df = df[common_columns]
    
    df.rename(columns={'deviceSerialNumber': "loginId"}, inplace = True)
    # df = df.reindex(sorted(df.columns), axis=1)

    df = df.drop_duplicates()
    
    df.to_excel(writer, sheet_name = 'data', index=False)
    writer.close()

    # firebase_admin.delete_app(firebase_admin.get_app())

    with open(output_path,'rb') as f:
        file_data = io.BytesIO(f.read())  

    # application/vnd.ms-excel
    return send_file(file_data, download_name= output_filename, mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet")