From 56ea6a34330faf7e7b8cffef075855f9a51d6cd8 Mon Sep 17 00:00:00 2001 From: Pritimay Sarkar Date: Wed, 24 Jan 2024 17:38:55 +0530 Subject: [PATCH] move to folder --- .../{ => consolidation}/consolidation.py | 29 ++++++++++++++----- 1 file changed, 22 insertions(+), 7 deletions(-) rename cloud-functions/python/functions/{ => consolidation}/consolidation.py (65%) diff --git a/cloud-functions/python/functions/consolidation.py b/cloud-functions/python/functions/consolidation/consolidation.py similarity index 65% rename from cloud-functions/python/functions/consolidation.py rename to cloud-functions/python/functions/consolidation/consolidation.py index a5a5826..e77422f 100644 --- a/cloud-functions/python/functions/consolidation.py +++ b/cloud-functions/python/functions/consolidation/consolidation.py @@ -2,6 +2,7 @@ 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 @@ -65,7 +66,18 @@ def consolidation(request): test_data = test_doc.to_dict() data.append(test_data) - df = pd.DataFrame(data) + test_df = pd.DataFrame(data) + + query = db.collection("patientData").where(filter=FieldFilter("createdAt", ">=", start_date)).where(filter=FieldFilter("createdAt", "<", end_date)) + data = [] + docs = query.stream() + for doc in docs: + row_data = doc.to_dict() + data.append(row_data) + + user_df = pd.DataFrame(data) + + df = pd.merge(test_df, user_df, on='_id') output_filename = f'data_{datetime.today().strftime("%d_%m_%Y_%H_%M")}.xlsx' @@ -73,13 +85,16 @@ def consolidation(request): 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 = df[["_id", "errorMessages", "classificationResult", "prdClassification", "predictedDenovixRatio", "calculatedRatio", "deviceRatio", "kitSerial", "abs1", "led1Average", "led1Buffer", "led1Sample", "abs2", "led2Average", "led2Buffer", "led2Sample", "abs3", "led3Average", "led3Buffer", "led3Sample", "abs4", "led4Average", "led4Buffer", "led4Sample", "batteryLevel", "batteryVoltage", "deviceId", "deviceSerialNumber", "name", "testTime"]] - df.rename(columns={'deviceSerialNumber': "loginId"}, inplace = True) - # df = df.reindex(sorted(df.columns), axis=1) - - df = df.drop_duplicates() + 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_y", "testTime"] + common_columns = [col for col in column_names if col in df.columns] + df = df[common_columns] + + df.rename(columns={'deviceSerialNumber': "loginId", "name_y": "name"}, 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()