add cloud function my_function

cloud-functions/python/functions/main.py

@@ -1,83 +1,68 @@
-# Deploy with `firebase deploy`
+import functions_framework
-
+# from google.cloud.firestore_v1.base_query import FieldFilter
-from firebase_functions import https_fn
+# from firebase_admin import initialize_app, credentials, firestore
-from firebase_admin import initialize_app, firestore
-import pandas as pd
-import datetime
-import sys
-import platform
 import os
+from datetime import datetime
+import pickle
+# import pandas as pd
 
-# initialize_app()
+@functions_framework.http
-#
+def my_function(request):
-#
+    """HTTP Cloud Function.
-# @https_fn.on_request()
+    Args:
-# def on_request_example(req: https_fn.Request) -> https_fn.Response:
+        request (flask.Request): The request object.
-#     return https_fn.Response("Hello world!")
+        <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)
 
-# @https_fn.on_request(
+    headers = {
-#     cors=options.CorsOptions(
+        'Access-Control-Allow-Origin': '*'
-#         cors_origins=[r"firebase\.com$", r"https://flutter\.com"],
+    }
-#         cors_methods=["get", "post"],
-#     )
-# )
 
-initialize_app()
+    with open('label_encoder.pkl', 'rb') as label_encoder_file:
+      loaded_label_encoder = pickle.load(label_encoder_file)
 
-@https_fn.on_request()
+    with open('gaussian_naive_bayes_model.pkl', 'rb') as model_file:
-def consolidation(req: https_fn.Request) -> https_fn.Response:
+      loaded_model = pickle.load(model_file)
 
-    path_delim = "/"
+    input_data = pd.DataFrame({'calculatedRatio': 0.231057205, 'deviceRatio': 0.231057205,'led1Buffer': 23776.33, 'led2Buffer': 26401.67, 
+      'led1Sample': 16286, 'led2Sample': 6952.67}, index=[0])
 
-    db = firestore.client()
+    predicted_result = loaded_model.predict(input_data)
+    print(predicted_result.item())
     
-    patient_collection = db.collection("patientData")
+#     db = firestore.client()
-    test_collection = db.collection("testData")
+#     source_collection = "testData"
 
-    start_date = req.query.start_date
+    # # Get all documents from the source collection
-    print("start_date", start_date)
+    # source_docs = db.collection(source_collection).where(filter=FieldFilter("createdAt", ">=", datetime.today().strftime("%Y-%m-%d"))).stream()
-    end_date = req.query.end_date
+    # count = 0
-    print("end_date", end_date)
+    # for doc in source_docs:
+    #     # Extract the document ID
+    #     doc_id = doc.id
+    #     print(doc_id)
 
+    #     # Get the document data
+    #     doc_data = doc.to_dict()
 
-    query = test_collection # test_collection.where(filter=FieldFilter("testTime", ">=", start_date)).where(filter=FieldFilter("testTime", "<", end_date))
+    #     try:
-    patient_docs = query.stream()
+    #         # Delete the document from the source collection
+    #         db.collection(source_collection).document(doc_id).delete()
+    #         print(f"Document with ID '{doc_id}' updated")
+    #         count = count + 1
+    #     except Exception as e:
+    #         print(f"Error deleting document with ID '{doc_id}' from the source collection: {e}")
     
-    data = []
+    return ('prediction applied: {}!'.format(0), 200, headers)
-    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"
-    df.to_csv(output_filename, index=False)
-
-    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.to_excel(writer, sheet_name = 'data', index=False)
-    writer.close()
-
-    firebase_admin.delete_app(firebase_admin.get_app())
-
-    
-    # return https_fn.Response(response = send_file(output_path))
-
-    return https_fn.Response("Ok!")

cloud-functions/python/functions/requirements.txt

@@ -3,3 +3,4 @@ firebase_functions~=0.1.0
 pandas==2.0.3
 openpyxl==3.1.2
 firebase-admin==6.2.0
+scikit-learn==1.3.1