import os
import firebase_admin
from firebase_admin import credentials
from firebase_admin import firestore
from google.cloud.firestore_v1.base_query import FieldFilter
import pandas as pd
import datetime
import sys
import platform
from datetime import datetime

if __name__ == "__main__":

    if platform.system() == 'Windows':
        path_delim = '\\'
    else:
        path_delim = '/'
    
    key_file_path = os.getcwd() + path_delim + "keys" + path_delim + "hpos-af3cc-firebase-adminsdk-n261k-2bfd463ec0.json"
    cred = credentials.Certificate(key_file_path)  # Replace with your own service account key path
    firebase_admin.initialize_app(cred)

    # Get a reference to the Firestore database
    db = firestore.client()

    # Specify the collections
    patient_collection = db.collection("patientData")
    test_collection = db.collection("testData")
    start_date = sys.argv[1] # '2023-01-12' #input("Please enter the start date (yyyy-mm-dd): ")
    end_date = sys.argv[2] #'2023-07-16' #input("Please enter the end date (yyyy-mm-dd): ")

    query = test_collection.where(filter=FieldFilter("testTime", ">=", start_date)).where(filter=FieldFilter("testTime", "<", end_date))
    patient_docs = query.stream()

    # Prepare data to store in CSV
    data = []
    for patient_doc in patient_docs:
        # print(patient_doc)
        patient_data = patient_doc.to_dict()
        patient_id = patient_data["_id"]

        # Query the document from testData collection based on the common _id
        test_docs = test_collection.where("_id", "==", patient_id).stream()

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

            # Combine the data from both collections into a single dictionary
            combined_data = {**patient_data, **test_data}

            # Fill empty fields in test_data with corresponding values from patient_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)

    # Convert the data to a DataFrame
    df = pd.DataFrame(data)
    print(df)
    print(df.size)

    # Save the DataFrame to a CSV file
    output_filename = f'data_{datetime.today().strftime("%d_%m_%Y_%H_%M")}.xlsx'
    df.to_csv(output_filename, index=False)

    downloads_dir = os.path.join(os.path.expanduser("~"), "Downloads")
    output_path = os.path.join(downloads_dir, 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"], axis=1)
    df = df[["_id", "calculatedRatio", "deviceId", "deviceRatio", "deviceType", "kitSerial", "led1Average", "led1Buffer", "led1Sample", "led2Average", "led2Buffer", "led2Sample", "location", "deviceSerialNumber", "name", "testTime"]]
    df.rename(columns={'deviceSerialNumber': "login_id", "calculatedRatio": "calibrated_ratio", "led1Buffer": "427_buffer_intensity", "led2Buffer": "555_buffer_intensity", "led1Sample": "427_sample_intensity", "led2Sample": "555_sample_intensity", "led1Average": "427_absorbance", "led2Average": "555_absorbance"}, inplace = True)
    df = df.reindex(sorted(df.columns), axis=1)
    df.to_excel(writer, sheet_name = 'data', index=False)
    writer.close()

    print(f"Data saved to '{output_path}'")

    # Close the Firebase Admin SDK
    firebase_admin.delete_app(firebase_admin.get_app())