file uploading section added

script/core/handlers/min_max.py

+import pandas as pd
+
+
+def extract_min_max(collection_name):
+    datas = collection_name.find({})
+    dataframe = pd.DataFrame(list(datas))
+    # fetching min salary
+    min_salary = dataframe["salary"].min()
+    min_details = collection_name.find({"salary": min_salary}, {"_id": 0})
+    # fetching max salary
+    max_salary = dataframe["salary"].max()
+    max_details = collection_name.find({"salary": max_salary}, {"_id": 0})
+    # fetching average salary
+    avg_salary = dataframe["salary"].mean()
+    details = {"min": max_details, "max": min_details, "avg": avg_salary}
+    # converting details to json
+    json_string = pd.io.json.dumps(details, orient="records", indent=4)
+    with open('temp/details.json', 'w') as file:
+        file.write(json_string)
+    df = pd.read_json("temp/details.json")
+    # converting details to csv
+    csv_data = df.to_csv("temp/details.csv", index=False)
+    return csv_data

script/service/main.py

-import pandas as pd
-from fastapi import FastAPI
 import json
+from fastapi import FastAPI, Response
+from mongoengine import connect
 from script.config.appconfig import db_name
 from script.core.engine.models import table_1, insert_post
-from mongoengine import connect
+from script.core.handlers.min_max import extract_min_max
 from script.core.handlers.reading_csv import csv_read
 from script.util.mongo_util import mongo_connection
 
@@ -25,25 +25,10 @@ async def get_element():
 #         for getting mix max avg
 @app.get("/get_minmax", tags=['FIRST'])
 async def get_minmax():
-    datas = collection_name.find({})
-    dataframe = pd.DataFrame(list(datas))
-    # fetching min salary
-    min_salary = dataframe["salary"].min()
-    min_details = collection_name.find({"salary": min_salary}, {"_id": 0})
-    # fetching max salary
-    max_salary = dataframe["salary"].max()
-    max_details = collection_name.find({"salary": max_salary}, {"_id": 0})
-    # fetching average salary
-    avg_salary = dataframe["salary"].mean()
-    details = {"min": max_details, "max": min_details, "avg": avg_salary}
-    # converting details to json
-    json_string = pd.io.json.dumps(details, orient="records", indent=4)
-    with open('temp/details.json', 'w') as file:
-        file.write(json_string)
-    df = pd.read_json("temp/details.json")
-    # converting details to csv
-    df.to_csv("temp/details.csv", index=False)
-    return "data fetched"
+    csv_data = extract_min_max(collection_name)
+    return Response(content=csv_data, media_type="text/csv", headers={
+            "Content-Disposition": "attachment; filename=data.csv"
+        })
 
 
 # insert many -->post

temp/details.csv

@@ -4,4 +4,3 @@ min,max,avg
 ,,101695.24
 0.0,0.0,101695.24
 ,,101695.24
-