move to folder

cloud-functions/python/functions/consolidation/consolidation.py

@@ -0,0 +1,107 @@
+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)
+
+    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'
+
+    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_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()
+
+    # 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")