refactored app to be more well factored

app/main.py

@@ -1,93 +1,24 @@
-# from fastapi import FastAPI, __version__
-
-# app = FastAPI()
-
-# @app.get("/")
-# async def root():
-#   return {"message": "Welcome to Measures LOFT solver service. v0.1"}
-
-# @app.get("/healthcheck")
-# async def health():
-#   content = {
-#     "maintainer": "Meazure Horizon Team",
-#     "git_repo": "https://github.com/yardstick/measure-solver",
-#     "server": "OK",
-#     "fastapi version": __version__,
-#     "app version": "0.1.0"
-#   }
-#   return content
-
-# @app.get('/readycheck')
-# async def ready():
-#   return 'OK!'  # just means we're on air
-
-# @app.post('/solve/')
-# async def solve(solver_run: SolverRun):
-#   response = Solution(
-#     response_id=randint(100,5000),
-#     forms=[Form(
-#       items=[item.id for item in solver_run.items]
-#     )]
-#   )
-#   return response
-
-# import os
-
-# from sqs_listener import SqsListener
-
-
-# class MyListener(SqsListener):
-#     def handle_message(self, body, attributes, messages_attributes):
-#         print(body)
-
-# listener = MyListener(os.environ['SOLVER_SQS_INGEST_QUEUE'], error_queue='my-error-queue', region_name='ca-central-1')
-# listener.listen()
-import boto3
-import json
-import time
 import os
 
-from pydantic import BaseModel
-from typing import Set, List, Optional, Dict
-from random import randint
+from services.loft import Loft
+from helpers import aws_helper
 
-from models.solver_run import SolverRun
-from models.solution import Solution
-from models.form import Form
+print("Starting Solver Service (v0.3.0)...")
 
-session = boto3.Session(
-  aws_access_key_id=os.environ['SOLVER_AWS_ACCESS_KEY_ID'],
-  aws_secret_access_key=os.environ['SOLVER_AWS_SECRET_ACCESS_KEY']
-)
-
-s3 = session.resource('s3', region_name=os.environ['SOLVER_AWS_REGION'])
-sqs = session.client('sqs', region_name=os.environ['SOLVER_AWS_REGION'])
-
-print("STARTING SOLVER APP")
 # listen to the solver queue
 while True:
-  msg = sqs.receive_message(
-    QueueUrl=os.environ['SOLVER_SQS_INGEST_QUEUE'],
-    MaxNumberOfMessages=1,
-    WaitTimeSeconds=1
-  )
+  msg = aws_helper.receive_message(os.environ['SOLVER_SQS_INGEST_QUEUE'])
 
   # get the item from the queue
-for message in msg.get("Messages", []):
-  print("NEW MESSAGE: ", message)
+  for message in msg.get("Messages", []):
+    # for now the solver service only supports Loft types
+    # this is here to allow us to create an extensible way to
+    # gather/manage/process data based on the particular needs
+    service = Loft(message)
+    service.process()
 
-  # upload the item to the processed bucket
-  # print("INGEST OBJ: ", s3.Object(bucket_name=os.environ['SOLVER_INGEST_BUCKET'],
-  #                                 key=body['Records'][0]['s3']['object']['key']).get()['Body'].read())
+    # delete message once process is complete
+    response = aws_helper.delete_message(os.environ['SOLVER_SQS_INGEST_QUEUE'], message['ReceiptHandle'])
 
-  s3.Bucket(os.environ['MEASURE_PROCESSED_BUCKET']).put_object(Key=str(time.time())+'.json', Body=json.dumps({
-    "example": "PROCESSED",
-    "time": time.time(),
-    "parent": message['MessageId']
-  }))
-
-  response = sqs.delete_message(
-    QueueUrl=os.environ['SOLVER_SQS_INGEST_QUEUE'],
-    ReceiptHandle=message['ReceiptHandle'],
-  )
-  print("MESSAGE PROCESSED: ", message['MessageId'])
+    # probably convert to logging, but maybe keep this to some extent
+    print("MESSAGE PROCESSED: ", message['MessageId'])