commit_message : "Added files"

Dockerfile

@@ -23,6 +23,8 @@ ENV PATH="/home/user/.local/bin:$PATH"
 
 WORKDIR /app
 
+RUN pip install --upgrade pip
+
 COPY --chown=user ./requirements.txt requirements.txt
 RUN pip install --no-cache-dir --upgrade -r requirements.txt
 

backend/api/main.py

@@ -4,8 +4,6 @@ import sys
 src_directory = os.path.abspath(os.path.join(os.path.dirname(__file__), "../..", "backend"))
 sys.path.append(src_directory)
 from modules import home_page
-from api.schema import CountryDetails
-from utils import logger
 
 app = FastAPI()
 
@@ -25,68 +23,12 @@ def display_countries():
     countries = home_page.display_countries(df)
     return countries.tolist()
 
-@app.get("/ShowContinentwithHighestPopulation")
-def display_cont_with_high_pop():
-    highest_pop = home_page.continent_with_highest_population(df)
-    return  highest_pop
+@app.get("/ShowContinentStats/{attribute}/{stat_type}")
+def display_continent_stats(attribute:str, stat_type:str):
+    continent_stats = home_page.continent_stat(df, attribute, stat_type)
+    return continent_stats
 
-@app.get("/ShowContinentwithLowestPopulation")
-def display_cont_with_high_pop():
-    lowest_pop = home_page.continent_with_lowest_population(df)
-    return  lowest_pop
-
-@app.get("/ShowCountrywithHighestPopulation")
-def display_country_with_high_pop():
-    highest_pop = home_page.country_with_highest_population(df)
-    return  highest_pop
-
-@app.get("/ShowCountrywithLowestPopulation")
-def display_country_with_high_pop():
-    lowest_pop = home_page.country_with_lowest_population(df)
-    return  lowest_pop
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-# highest_pop = home_page.display_countries(df).tolist()
-# print(type(highest_pop))
-
-# @app.get("/")
-# def home():
-#     return end_points.welcome_msg()
-    
-# @app.get('/{continent}')
-# def present_countries(continent : str):
-#     return home_page.list_country_by_continent(df, continent)
-
-
-# @app.get("/{continent}/{data_type}/{stat}") 
-# def get_stats_of_cont(continent:str, data_type : str, stat:str):
-#     return home_page.get_stat_by_continent(df,continent,data_type,stat)
-
-# @app.get("/{key}/{value}")
-# def get_stats_of_cont(key : str ,value : str):
-#     return home_page.get_continent_with_max_value(df, key, value)
-
-
-  
+@app.get("/ShowCountryStats/{attribute}/{stat_type}")
+def display_country_stats(attribute : str, stat_type : str):
+    country_stats = home_page.country_stat(df, attribute,stat_type)
+    return country_stats

backend/modules/home_page.py

@@ -30,118 +30,101 @@ def display_countries(dataframe):
     logger.log("Displaying the list of countries in the data")
     return countries
 
-def continent_with_highest_population(dataframe):
-    highest= dataframe.groupby('Continent')['Population'].agg(total_population = 'sum')
-    max_continent = highest.idxmax().item()
-    max_population = highest.max().item()
-    result = {max_continent:max_population}
-    logger.log("Displaying the continent with highest population in the data")
-    return result
-
-def continent_with_lowest_population(dataframe):
-    lowest= dataframe.groupby('Continent')['Population'].agg(total_population = 'sum')
-    min_continent = lowest.idxmin().item()
-    min_population = lowest.min().item()
-    result = {min_continent:min_population}
-    logger.log("Displaying the continent with lowest population in the data")
-    return result
-
-def country_with_lowest_population(dataframe):
-    index= dataframe['Population'].idxmin()
-    min_country = dataframe['Country'][index]
-    min_population = dataframe['Population'][index]
-    result = {min_country:min_population.item()}
-    logger.log("Displaying the country with lowest population in the data")
-    return result
-
-def country_with_highest_population(dataframe):
-    index= dataframe['Population'].idxmax()
-    max_country = dataframe['Country'][index]
-    max_population = dataframe['Population'][index]
-    result = {max_country:max_population.item()}
-    logger.log("Displaying the country with highest population in the data")
-    return result
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-def list_country_by_continent(dataframe,continent):
+def continent_stat(dataframe, attribute="Population", stat_type="highest"):
     try:
-        df_countries = dataframe[dataframe['Continent'] == continent]
-        countries= df_countries['Country'].to_list()
-        logger.log("Separated data by continent")
-        return countries
+        if 'Continent' not in dataframe.columns or attribute not in dataframe.columns:
+            return ValueError(f"Dataframe must contain 'Continent' and '{attribute}' columns.")
+        
+        continent_stats = dataframe.groupby('Continent')[attribute].agg(total_attribute='sum')
+
+        if stat_type == "highest":
+            continent = continent_stats.idxmax().item()
+            value = continent_stats.max().item()
+            logger.log(f"Displaying the continent with the highest {attribute}: {continent} with {attribute} {value}")
+
+        elif stat_type == "lowest":
+            continent = continent_stats.idxmin().item()
+            value = continent_stats.min().item()
+            logger.log(f"Displaying the continent with the lowest {attribute}: {continent} with {attribute} {value}")
+
+        else:
+            raise ValueError("Invalid stat_type. Use 'highest' or 'lowest'.")
+        
+        return {continent: value}
+    
     except Exception as e:
-        return f"{e}"
-
-def get_stat_by_continent(df ,continent: str, data_type: str, stat: str , ):
+        logger.log(f"Error in continent_stat: {str(e)}")
+        return {"error": str(e)}
+
+def country_stat(dataframe, attribute : str = "Population", stat_type :str = "highest"):
+    try : 
+        if stat_type.lower() == "highest":
+            index= dataframe[attribute].idxmax()
+        elif stat_type.lower() == "lowest":
+            index= dataframe[attribute].idxmin()
+
+        country = dataframe['Country'][index]
+        requested_attribute = dataframe[attribute][index]
+        result = {country:requested_attribute.item()}
+        logger.log(f"Displaying the country with {stat_type} {attribute} in the data")
+        return result
+    except Exception as e:
+        return f"Unable to fetch the data. Error {e}"
 
-    if continent.lower() == "NorthAmerica".lower():
-        continent = "North America"
-    if continent.lower() == "SouthAmerica".lower():
-        continent = "South America"
+    
 
-    valid_stats = ['max', 'min', 'mean' , 'sum' , 'count']
-    if stat not in valid_stats:
-        return f"Invalid stat. Please use one of the following: {valid_stats}."
+# def list_country_by_continent(dataframe,continent):
+#     try:
+#         df_countries = dataframe[dataframe['Continent'] == continent]
+#         countries= df_countries['Country'].to_list()
+#         logger.log("Separated data by continent")
+#         return countries
+#     except Exception as e:
+#         return f"{e}"
+
+# def get_stat_by_continent(df ,continent: str, data_type: str, stat: str , ):
+
+#     if continent.lower() == "NorthAmerica".lower():
+#         continent = "North America"
+#     if continent.lower() == "SouthAmerica".lower():
+#         continent = "South America"
+
+#     valid_stats = ['max', 'min', 'mean' , 'sum' , 'count']
+#     if stat not in valid_stats:
+#         return f"Invalid stat. Please use one of the following: {valid_stats}."
     
-    continent_population_stats = df.groupby('Continent')[data_type].agg(
-        Maximum='max', Minimum='min', Average = 'mean',Total='sum' , Number_of_Countries = 'count')
+#     continent_population_stats = df.groupby('Continent')[data_type].agg(
+#         Maximum='max', Minimum='min', Average = 'mean',Total='sum' , Number_of_Countries = 'count')
     
-    continent_countries = df[df['Continent'] == continent]
+#     continent_countries = df[df['Continent'] == continent]
 
-    if continent not in continent_population_stats.index:
-        return f"Continent '{continent}' not found in the data."
+#     if continent not in continent_population_stats.index:
+#         return f"Continent '{continent}' not found in the data."
     
-    if stat == 'max':
-        population_result = continent_population_stats.loc[continent]['Maximum']
-        country_id = continent_countries.loc[continent_countries[data_type].idxmax()]
-        country_name = country_id['Country']
-        population_value = country_id[data_type]
-        return f"{continent}'s {stat} {data_type} is {int(population_result)}. Country: {country_name} , {data_type} :{population_value}"
-    if stat == 'min':  
-        population_result = continent_population_stats.loc[continent]['Minimum']
-        country_id = continent_countries.loc[continent_countries[data_type].idxmin()]
-        country_name = country_id['Country']
-        population_value = country_id[data_type]
-        return f"{continent}'s {stat} {data_type} is {int(population_result)}. Country: {country_name} , {data_type} :{population_value}"
-    if stat == 'mean':
-        population_result = continent_population_stats.loc[continent]['Average']
-        return f"{continent}'s average {data_type} is {int(population_result)}"
-    if stat == 'sum':
-        population_result = continent_population_stats.loc[continent]['Total']
-        return f"{continent}'s total {data_type} is {int(population_result)}"
-    if stat == 'count' :
-        population_result = continent_population_stats.loc[continent]['Number_of_Countries']
-        return f"Total countries in {continent} is {int(population_result)}"
+#     if stat == 'max':
+#         population_result = continent_population_stats.loc[continent]['Maximum']
+#         country_id = continent_countries.loc[continent_countries[data_type].idxmax()]
+#         country_name = country_id['Country']
+#         population_value = country_id[data_type]
+#         return f"{continent}'s {stat} {data_type} is {int(population_result)}. Country: {country_name} , {data_type} :{population_value}"
+#     if stat == 'min':  
+#         population_result = continent_population_stats.loc[continent]['Minimum']
+#         country_id = continent_countries.loc[continent_countries[data_type].idxmin()]
+#         country_name = country_id['Country']
+#         population_value = country_id[data_type]
+#         return f"{continent}'s {stat} {data_type} is {int(population_result)}. Country: {country_name} , {data_type} :{population_value}"
+#     if stat == 'mean':
+#         population_result = continent_population_stats.loc[continent]['Average']
+#         return f"{continent}'s average {data_type} is {int(population_result)}"
+#     if stat == 'sum':
+#         population_result = continent_population_stats.loc[continent]['Total']
+#         return f"{continent}'s total {data_type} is {int(population_result)}"
+#     if stat == 'count' :
+#         population_result = continent_population_stats.loc[continent]['Number_of_Countries']
+#         return f"Total countries in {continent} is {int(population_result)}"
     
-def get_continent_with_max_value(dataframe, key, value):
-    max_id = dataframe[value].idxmax()
-    value_num = dataframe[value][max_id]
-    value_country = dataframe[key][max_id]
-    return f"{value_country}'s max {value} is {value_num}"
-
-
+# def get_continent_with_max_value(dataframe, key, value):
+#     max_id = dataframe[value].idxmax()
+#     value_num = dataframe[value][max_id]
+#     value_country = dataframe[key][max_id]
+#     return f"{value_country}'s max {value} is {value_num}"