main.py

import asyncio
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
import requests
import pandas as pd
import json
import aiohttp

global data
app = FastAPI()

app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

# Declare the continuous function as an async function.
#async def your_continuous_function():
def your_continuous_function_old(X_Tenant):
    import pandas as pd
    while True:
        print("data fetcher running.....")
        
        # Initialize an empty DataFrame to store the combined data
        combined_df = pd.DataFrame()
        url = "https://dev3.api.curfox.parallaxtec.com/api/ml/order-metadata"
        
        payload = {}
        headers = {
          'Accept': 'application/json',
          'X-Tenant': X_Tenant,  #'royalexpress',
          'Authorization': 'Bearer eyJ0eXAiOiJKV1QiLCJhbGciOiJSUzI1NiJ9.eyJhdWQiOiIxIiwianRpIjoiZWQzYjVkN2JkNTU5YmQxNWNmYzdiNThhM2UyZDlmNGEyMGQzMDFjMWY4ZWVlNDY2ZDBlZTAxYmMzZmVjMTU1ZWNjNzMxOWUxMGUxZGY3NDMiLCJpYXQiOjE3MDIyNzIyMDcuNjg0OTE2LCJuYmYiOjE3MDIyNzIyMDcuNjg0OTIzLCJleHAiOjE3MzM4OTQ2MDcuNjczNDYyLCJzdWIiOiIxIiwic2NvcGVzIjpbXX0.NFZvGO0GjoD7u3FRiIewRRoWu7ouUmKTKnCei8LMwQWzLntBLYcj_Bs21amjcHtzdbQNyCovHSDHJQaLJnD04kY1JRAdDC_OLi2YiZoSvnSJxNjWiuC4kwNE59Ndwu3o2iAzB-nd1EvyMnU_na7WxICRP8OegrpM-_q6M-wgnv7igaNeWjdxnXdtxbr-Zz7N2Xv2skWZwoDce37kWvH1tK7eqMK0uWqqyhBpli22CmkKPduHUNKMNOEnGTskeDaTuX5za2Lr8CNa34_FdKu3Y5CrFMGDBHT_UGALocpr80_38iifXm7WDl6ZIA1iYy6dBvCTeoC_aFo1X5FIrFbJgMCokW4VH0Q2ljm9ty0W7ATAiKrM1GIVFS5Dir4A1KI3LSeE459SqZpqsoJmaU95zSYbfnU_oZ9UpvW59nFgD6yJ8hGHyYnjhCS0jmxk3cq93T9X1rNWo2t0A3XYXgqZYnZrZpdrSbn-JVoX_NW1QC6RtmAGm7AtZ3GBrzxwu3m_7MicMI7Tu4W6d2WD9kZjq0khBUrm2DVZJzN2BRmH-a7JkAqJ0icpHQ_2Tc6T-95axebp6QEmHHXBKILNNwWxucZ0l-Ny0TuUivqn0m9gSJJDkA8ssWyBkzzJ9fUeRmJGbUFTeemPhMrF3_cvTUZ0J7IC2CK7qWePcHPQ-sy0is4'
        }
        count = requests.request("GET", url, headers=headers).json()["data"]["order_count"]//200
        count = count + 2
        print(count)
        # Loop through pages 1 to 4
        for page in range(1,30):
            try:
              # Update the payload for each page
              url = "https://dev3.api.curfox.parallaxtec.com/api/ml/order-list?sort=id&paginate=200&page="+str(page)
        
              payload = {}
              headers = {
                'Accept': 'application/json',
                'X-Tenant': 'royalexpress',
              }
        
              response = requests.request("GET", url, headers=headers)
        
              import pandas as pd
              import json
        
              # Sample JSON response
              json_response = response.json()
              # Extracting 'data' for conversion
              data = json_response['data']
        
              df = pd.json_normalize(data)
        
              # Concatenate the current page's DataFrame with the combined DataFrame
              combined_df = pd.concat([combined_df, df], ignore_index=True)
            except:
              print("data over")
        print("data collected....")
        data = combined_df[combined_df['status.name'].isin(['RETURN TO CLIENT', 'DELIVERED'])]
        data = data[['delivery_possibility','status.name']]
        data = data[data['delivery_possibility'].between(0, 100)]
        return data
        #await asyncio.sleep(43200)  # Adjust the sleep interval as needed

# # Create a startup event.
# @app.on_event("startup")
# async def startup_event():
#     # Start the continuous function as a background task.
#     asyncio.create_task(your_continuous_function())

async def fetch_data(session, url, headers):
    async with session.get(url, headers=headers) as response:
        return await response.json()


async def your_continuous_function(X_Tenant):
    combined_df = pd.DataFrame()
    base_url = "https://dev3.api.curfox.parallaxtec.com/api/ml/order-list"
    headers = {
        'Accept': 'application/json',
        'X-Tenant': X_Tenant,
        'Authorization': 'Bearer eyJ0eXAiOiJKV1QiLCJhbGciOiJSUzI1NiJ9.eyJhdWQiOiIxIiwianRpIjoiZWQzYjVkN2JkNTU5YmQxNWNmYzdiNThhM2UyZDlmNGEyMGQzMDFjMWY4ZWVlNDY2ZDBlZTAxYmMzZmVjMTU1ZWNjNzMxOWUxMGUxZGY3NDMiLCJpYXQiOjE3MDIyNzIyMDcuNjg0OTE2LCJuYmYiOjE3MDIyNzIyMDcuNjg0OTIzLCJleHAiOjE3MzM4OTQ2MDcuNjczNDYyLCJzdWIiOiIxIiwic2NvcGVzIjpbXX0.NFZvGO0GjoD7u3FRiIewRRoWu7ouUmKTKnCei8LMwQWzLntBLYcj_Bs21amjcHtzdbQNyCovHSDHJQaLJnD04kY1JRAdDC_OLi2YiZoSvnSJxNjWiuC4kwNE59Ndwu3o2iAzB-nd1EvyMnU_na7WxICRP8OegrpM-_q6M-wgnv7igaNeWjdxnXdtxbr-Zz7N2Xv2skWZwoDce37kWvH1tK7eqMK0uWqqyhBpli22CmkKPduHUNKMNOEnGTskeDaTuX5za2Lr8CNa34_FdKu3Y5CrFMGDBHT_UGALocpr80_38iifXm7WDl6ZIA1iYy6dBvCTeoC_aFo1X5FIrFbJgMCokW4VH0Q2ljm9ty0W7ATAiKrM1GIVFS5Dir4A1KI3LSeE459SqZpqsoJmaU95zSYbfnU_oZ9UpvW59nFgD6yJ8hGHyYnjhCS0jmxk3cq93T9X1rNWo2t0A3XYXgqZYnZrZpdrSbn-JVoX_NW1QC6RtmAGm7AtZ3GBrzxwu3m_7MicMI7Tu4W6d2WD9kZjq0khBUrm2DVZJzN2BRmH-a7JkAqJ0icpHQ_2Tc6T-95axebp6QEmHHXBKILNNwWxucZ0l-Ny0TuUivqn0m9gSJJDkA8ssWyBkzzJ9fUeRmJGbUFTeemPhMrF3_cvTUZ0J7IC2CK7qWePcHPQ-sy0is4'
    }
    
    async with aiohttp.ClientSession() as session:
        # Fetch the order count to determine the number of pages
        order_metadata_url = "https://dev3.api.curfox.parallaxtec.com/api/ml/order-metadata"
        metadata_response = await fetch_data(session, order_metadata_url, headers)
        order_count = metadata_response["data"]["order_count"] // 200 + 2
        
        tasks = []
        for page in range(1, 30):
            page_url = f"{base_url}?sort=id&paginate=200&page={page}"
            tasks.append(fetch_data(session, page_url, headers))
        
        responses = await asyncio.gather(*tasks)
        
        for json_response in responses:
            data = json_response.get('data', [])
            if data:
                df = pd.json_normalize(data)
                combined_df = pd.concat([combined_df, df], ignore_index=True)
        
        # After processing, you can return the DataFrame as a response or save it as needed.
        # Here, for example, we're just returning the number of rows fetched.
        
        print("data collected....")
        data = combined_df[combined_df['status.name'].isin(['RETURN TO CLIENT', 'DELIVERED'])]
        data = data[['delivery_possibility','status.name']]
        data = data[data['delivery_possibility'].between(0, 100)]
        return data


@app.get("/kpi_results")
async def read_root(X_Tenant):
    data = await your_continuous_function(X_Tenant)
    status_counts_more_than_80 = data[data['delivery_possibility'] > 80]['status.name'].value_counts()
    
    status_counts_50_to_80 = data[(data['delivery_possibility'] >= 50) & (data['delivery_possibility'] <= 80)]['status.name'].value_counts()
    
    status_counts_30_to_49 = data[(data['delivery_possibility'] >= 30) & (data['delivery_possibility'] <= 49)]['status.name'].value_counts()
    
    status_counts_below_30 = data[data['delivery_possibility'] < 30]['status.name'].value_counts()
    print(status_counts_more_than_80,status_counts_50_to_80,status_counts_30_to_49,status_counts_below_30)
    
    try:    
        status_counts_more_than_80_0 = int(status_counts_more_than_80[0])
    except:
        status_counts_more_than_80_0 = 0
        
    try:    
        status_counts_more_than_80_1 = int(status_counts_more_than_80[1])
    except:
        status_counts_more_than_80_1 = 0

        

    try:    
        status_counts_50_to_80_0 = int(status_counts_50_to_80[0])
    except:
        status_counts_50_to_80_0 = 0
        
    try:    
        status_counts_50_to_80_1 = int(status_counts_50_to_80[1])
    except:
        status_counts_50_to_80_1 = 0



        

    try:    
        status_counts_30_to_49_0 = int(status_counts_30_to_49[0])
    except:
        status_counts_30_to_49_0 = 0
        
    try:    
        status_counts_30_to_49_1 = int(status_counts_30_to_49[1])
    except:
        status_counts_30_to_49_1 = 0


        

    try:    
        status_counts_below_30_0 = int(status_counts_below_30[0])
    except:
        status_counts_below_30_0 = 0
        
    try:    
        status_counts_below_30_1 = int(status_counts_below_30[1])
    except:
        status_counts_below_30_1 = 0
        
    kpi_result = {
            "kpi_result": {
                "status_counts_more_than_80": {  
                    "correct_values": status_counts_more_than_80_0,
                    "incorrect_values": status_counts_more_than_80_1
                },
                "status_counts_50_to_80": {
                    "correct_values": status_counts_50_to_80_0,
                    "incorrect_values": status_counts_50_to_80_1
                },
                "status_counts_30_to_49": {
                    "correct_values": status_counts_30_to_49_0,
                    "incorrect_values": status_counts_30_to_49_1
                },
                "status_counts_below_30": {
                    "correct_values": status_counts_below_30_0,
                    "incorrect_values": status_counts_below_30_1
                }
            }
        }
    return kpi_result