changes in buisness service

logs/backend.log

@@ -0,0 +1,5 @@
+2025-02-12 11:16:48,494 - INFO - CSV file loaded successfully.
+2025-02-12 11:16:48,817 - INFO - Started server process [19640]
+2025-02-12 11:16:48,820 - INFO - Waiting for application startup.
+2025-02-12 11:16:48,823 - INFO - Application startup complete.
+2025-02-12 11:16:48,825 - INFO - Uvicorn running on http://0.0.0.0:8000 (Press CTRL+C to quit)

routers/continent.py

@@ -1,9 +1,11 @@
 from fastapi import APIRouter
-from services.continent_services import get_continent_stats_service
+from services.continent_services import get_continent_data
 from models.pydantic_model import ContinentStats
 
 router = APIRouter()
 
 @router.get("/{continent}/", response_model=ContinentStats)
 def get_continent_stats(continent: str):
-    return get_continent_stats_service(continent)
+    return get_continent_data(continent)
+
+

services/continent_services.py

@@ -1,42 +1,49 @@
 import pandas as pd
-from fastapi import HTTPException
-from models.pydantic_model import ContinentStats
-from logger import logger
+# from backend.population_pandas import get_continents, get_continent_data
+from Backend.logger import logger
 
-# Load dataset
+import os
+
+# file_path = os.path.join(os.path.dirname(__file__), "../../data/world_population.csv")
+file_path = os.path.join(os.path.dirname(__file__), "../data/world_population.csv")
+# file_path = os.path.abspath(file_path)  # Convert to absolute path
+
+file_path = os.path.abspath(file_path)  # Convert to absolute path
 try:
-    df = pd.read_csv("data/world_population.csv")
-    logger.info("CSV file loaded successfully.")
+    df = pd.read_csv(file_path)
+    logger.info(f"CSV file loaded successfully from: {file_path}")
 except Exception as e:
-    logger.error(f"Failed to load CSV: {e}")
-    raise HTTPException(status_code=500, detail="Internal server error")
-
-# Aggregate statistics by continent
-continent_stats = df.groupby("Continent").agg(
-    Total_Countries=('Country', 'count'),
-    Total_Population=('Population', 'sum'),
-    Average_Population=('Population', 'mean'),
-    Total_Area=('Area', 'sum'),
-    max_population=('Population', 'max'),
-    min_population=('Population', 'min'),
-).reset_index()
-
-# Compute Population Density
-continent_stats["Population_Density"] = (
-    continent_stats["Total_Population"] / continent_stats["Total_Area"]
-)
-
-def get_continent_stats_service(continent: str) -> ContinentStats:
-    """
-    Fetch statistics for a given continent.
-    """
-    logger.info(f"Fetching statistics for continent: {continent}")
-
-    result = continent_stats[continent_stats["Continent"] == continent]
+    logger.error(f"Error loading CSV file from {file_path}: {e}")
+    df = None  # Prevent NameError if file loading fails
+
+if df is not None:
+    # Perform the aggregations only if df is successfully loaded
+    continent_stats = df.groupby("Continent").agg(
+        Total_Countries=('Country', 'count'),
+        Total_Population=('Population', 'sum'),
+        Average_Population=('Population', 'mean'),
+        Total_Area=('Area', 'sum'),
+        max_population=('Population', 'max'),
+        min_population=('Population', 'min'),
+        Country_Max_Population=('Population', lambda x: df.loc[x.idxmax(), 'Country']),
+        Country_Min_Population=('Population', lambda x: df.loc[x.idxmin(), 'Country'])
+    ).reset_index()
+
+    # Compute Population Density
+    continent_stats["Population_Density"] = (
+        continent_stats["Total_Population"] / continent_stats["Total_Area"]
+    )
+
+    logger.info("Data processing completed.")
+
+
+def get_continent_data(continent):
+    """Returns statistics for a specific continent."""
+    logger.info(f"Fetching data for continent: {continent}")
+    result = continent_stats[continent_stats["Continent"] == continent].squeeze()
 
     if result.empty:
-        logger.warning(f"Continent not found: {continent}")
-        raise HTTPException(status_code=404, detail="Continent not found")
+        logger.warning(f"No data found for continent: {continent}")
+        return {}
 
-    result_dict = result.iloc[0].to_dict()
-    return ContinentStats(**result_dict)
+    return result.to_dict()