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

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>.
    """
    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()

    patient_collection = db.collection("patientData")
    test_collection = db.collection("testData")

    query = test_collection
    patient_docs = query.stream()

    data = []
    for patient_doc in patient_docs:
        patient_data = patient_doc.to_dict()
        patient_id = patient_data["_id"]

        test_docs = test_collection.where("_id", "==", patient_id).stream()

        for test_doc in test_docs:
            test_data = test_doc.to_dict()

            combined_data = {**patient_data, **test_data}

            for key, value in combined_data.items():
                if value == "" and key in patient_data:
                    combined_data[key] = patient_data[key]

            data.append(combined_data)

    df = pd.DataFrame(data)

    output_filename = "data.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)
    df = df.drop(['resultData', "reportUploadTime", "userImageURL", "testType", "birthYear", "testStatus", "reportPath", "createdBy", "csvPath", "result", "mobileId", "resultRatio", "localFlag", "led2", "led1"], axis=1)
    df.rename(columns={'deviceSerialNumber': "loginId", "calculatedRatio": "calibratedRatio"}, inplace = True)
    df.to_excel(writer, sheet_name = 'data', index=False)
    writer.close()

    # firebase_admin.delete_app(firebase_admin.get_app())

    # return 'df size {}!'.format(df.size)

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

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