first commit

app/logs/app.log

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+2025-02-08 10:29:28,697 - INFO - Home page accessed.
+2025-02-08 10:35:45,991 - INFO - Home page accessed.
+2025-02-08 10:37:00,452 - INFO - Home page accessed.
+2025-02-08 10:37:59,156 - INFO - Home page accessed.
+2025-02-08 10:38:14,407 - INFO - Fetched stats for Asia
+2025-02-08 10:40:38,126 - INFO - Home page accessed.

app/models/continent.py

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+from pydantic import BaseModel, Field
+
+class ContinentStats(BaseModel):
+    Max: str = Field(description="Max population of a country in the continent")
+    Min: str = Field(description="Min population of a country in the continent")
+    Avgerage: str = Field(description="Average population in the continent")
+    Area: str = Field(description="Total area of the continent")
+    Sum: str = Field(description="Total population of the continent")
+    density: str = Field(description="Population density of the continent")
+    model_config = {
+        "json_schema_extra": {
+            "examples": [
+                {
+                    "continent": "Asia",
+                    "total_population": 4641054775,
+                    "total_area": 44579000,
+                    "continent_population_density": 104.1,
+                    "max_population": {"country": "China", "population": 1411778724},
+                    "min_population": {"country": "Maldives", "population": 521874},
+                    "avg_population": 92821192
+                }
+            ]
+        }
+    }

app/routers/stats.py

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+import pandas as pd
+from fastapi import APIRouter, HTTPException
+from app.models.continent import ContinentStats
+from app.utils.logger import logger
+
+# Router instance
+router = APIRouter()
+
+# Load the CSV data
+file_path = "C:/Users/keerthi/Downloads/world_population.csv"
+df = pd.read_csv(file_path)
+
+@router.get("/{continent}", response_model=ContinentStats)
+def get_continent_stats(continent: str):
+    try:
+        # The logic for calculating stats (same as your current code)
+    
+
+        max_population = df.groupby('Continent')['Population'].max()
+        min_population = df.groupby('Continent')['Population'].min()
+        max_country = df.groupby('Continent')['Country'].max()
+        min_country = df.groupby('Continent')['Country'].min()
+        average_population = df.groupby('Continent')['Population'].mean()
+        total_area = df.groupby('Continent')['Area'].sum()
+        total_population = df.groupby('Continent')['Population'].sum() # Prepare the response
+        response = {}
+
+        # Max population and country
+        max_pop = max_population[continent]
+        max_pop_country = max_country[continent]
+        response["Max"] = f"{continent}'s maximum population is {max_pop} in {max_pop_country}"
+
+        # Min population and country
+        min_pop = min_population[continent]
+        min_pop_country = min_country[continent]
+        response["Min"] = f"{continent}'s minimum population is {min_pop} in {min_pop_country}"
+
+        # Average population
+        avg_pop = average_population[continent]
+        response["Avgerage"] = f"{continent}'s average population is {avg_pop}"
+
+        # Area
+        area = total_area[continent]
+        response["Area"] = f"{continent}'s total area is {area}"
+
+        # Total population
+        total_pop = total_population[continent]
+        response["Sum"] = f"{continent}'s total population is {total_pop}"
+
+        # Population density
+        continent_density = total_population / total_area
+        response["density"] = f"{continent}'s population density is {continent_density[continent]}"
+
+        # Log the request and result
+        logger.info(f"Fetched stats for {continent}")
+        
+        return response
+
+        if continent not in df['Continent'].values:
+            raise HTTPException(status_code=404, detail=f"Continent '{continent}' not found")
+    except Exception as e:
+        logger.error(f"Error occurred while fetching stats for {continent}: {e}")
+        raise HTTPException(status_code=500, detail="Internal Server Error")

app/utils/logger.py

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+import logging
+
+# Logging configuration
+logging.basicConfig(
+    level=logging.INFO,
+    format="%(asctime)s - %(levelname)s - %(message)s",
+    handlers=[
+        logging.FileHandler("C:/java lab/python/pandas/pydantic/app/logs/app.log"),  # Log to a file
+        logging.StreamHandler()  # Log to console
+    ]
+)
+
+logger = logging.getLogger(__name__)

main.py

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+from fastapi import FastAPI
+from app.routers import stats
+from app.utils.logger import logger
+
+app = FastAPI()
+
+# Include the stats router
+app.include_router(stats.router)
+
+@app.get("/")
+def home():
+    logger.info("Home page accessed.")
+    return {"message": "Welcome to the Home Page"}
+