fastapi

api.py

@@ -1,4 +1,4 @@
-from fastapi import FastAPI
+from fastapi import FastAPI 
 from scripts.database.db_connection import db_connection, ss_dataset, adzuna_dataset, muse_dataset
 from scripts.plot_analyse import usecase,  computation
 
@@ -13,109 +13,3 @@
     redoc_url="/api/redoc"
 )
 
-# Create a global Elasticsearch connection
-es = db_connection()
-"""_summary_
-Elasticsearch serves as the data store and querying engine for our use case endpoints 
-(get_usecase1 and get_usecase2). so keeping it here.
-Returns:
-    _type_: _description_
-"""
-
-index_name = "job_list"
-
-@api.get("/")
-def read_root():
-    """Root endpoint to welcome users."""
-    return {"message": "Welcome to the Job Market API!"}
-
-@api.get("/load_data")
-def load_data():
-    """
-    Endpoint to load data into Elasticsearch.
-
-    Returns:
-        dict: A dictionary containing the result of loading data into Elasticsearch.
-    """
-    try:
-        # Get the absolute path of the current directory
-        current_dir = os.path.dirname(os.path.abspath(__file__))
-        # Construct the path to the processed_data directory
-        read_file_path = os.path.join(current_dir, "data", "processed_data")
-
-        ss_result = ss_dataset(read_file_path, es)
-        adzuna_result = adzuna_dataset(read_file_path, es)
-        muse_result = muse_dataset(read_file_path, es)
-
-        return {
-            "ss_result": ss_result,
-            "adzuna_result": adzuna_result,
-            "muse_result": muse_result
-        }
-    except Exception as e:
-        # Log the exception for debugging purposes
-        print(f"An unexpected error occurred: {str(e)}")
-        # Return a more specific error message
-        return {"error": "Failed to load data into Elasticsearch."}
-
-@api.get("/usecase1")
-def get_usecase1():
-    """
-    Endpoint to execute and retrieve results for use case 1.
-
-    Returns:
-        dict: A dictionary containing the result of use case 1.
-    """
-    try:
-        host = "localhost"
-        port = "9200"
-        # Connect to Elasticsearch
-        es = db_connection(host, port)
-        # Define the search query for use case 1
-        query = usecase(1)
-        # Execute the search query and get the response
-        response = es.search(index=index_name, body=query)
-        # Get the required data
-        analysis_data = response["aggregations"]["job_posted_counts"]["buckets"]
-        # Convert JSON data to DataFrame and perform computation
-        df = pd.json_normalize(analysis_data)
-        result_df = computation(1, df)
-        # Return the results
-        return result_df.to_dict(orient='records')
-    except Exception as e:
-        # Log and return error message
-        print(f"An unexpected error occurred: {str(e)}")
-        return {"error": "Failed to execute use case 1."}
-
-@api.get("/usecase2")
-def get_usecase2():
-    """
-    Endpoint to execute and retrieve results for use case 2.
-
-    Returns:
-        dict: A dictionary containing the result of use case 2.
-    """
-    try:
-        host = "localhost"
-        port = "9200"
-        # Connect to Elasticsearch
-        es = db_connection(host, port)
-        # Define the search query for use case 2
-        query = usecase(2)
-        # Execute the search query and get the response
-        response = es.search(index=index_name, body=query)
-        # Get the required data
-        analysis_data = response["aggregations"]["companies"]["buckets"]
-        # Convert JSON data to DataFrame and perform computation
-        df = pd.json_normalize(analysis_data)
-        result_df = computation(2, df)
-        # Return the results
-        return result_df.to_dict(orient='records')
-    except Exception as e:
-        # Log and return error message
-        print(f"An unexpected error occurred: {str(e)}")
-        return {"error": "Failed to execute use case 2."}
-
-if __name__ == "__main__":
-    import uvicorn
-    uvicorn.run(api, host="0.0.0.0", port=8000)