RabbitMQ works #42

plot-weather-microservice/plot_weather/plot_graph/server.py

@@ -0,0 +1,109 @@
+import pika, sys, os
+import gzip
+from locale import CODESET
+from logging import handlers
+import urllib
+from datetime import datetime
+
+import nexradaws
+import pyart
+import base64
+import io
+
+import pytz
+from matplotlib import pyplot as plt
+from rest_framework.utils import json
+
+# from .views import PlotAPIView
+ # establish connection with rabbitmq server 
+connection = pika.BlockingConnection(pika.ConnectionParameters('orionRabbit'))
+channel = connection.channel()
+print(" Connected to RBmq server")
+
+#create/ declare queue
+channel.queue_declare(queue='plot_rx')
+
+def fetchData(files):
+    templocation = 'aws_files'
+    conn = nexradaws.NexradAwsInterface()
+    central_timezone = pytz.timezone('US/Central')
+    print(files)
+    file_list = files.split("/")
+    print("Files list=",file_list)
+    file = urllib.request.urlretrieve('https://noaa-nexrad-level2.s3.amazonaws.com/' + files, "aws_files/"+file_list[4])
+    if 'gz' in file_list[4]:
+        filename = gzip.open('aws_files/' + file_list[4])
+    else:
+        filename = 'aws_files/' + file_list[4]
+    return filename
+
+def createGraph(filename):
+    filename = fetchData(filename)
+    radar = pyart.io.read_nexrad_archive(filename)
+    display = pyart.graph.RadarDisplay(radar)
+    fig = plt.figure(figsize=(6, 5))
+
+    # plot super resolution reflectivity
+    ax = fig.add_subplot(111)
+    display.plot('reflectivity', 0, title='NEXRAD Reflectivity', vmin=-32, vmax=64, colorbar_label='', ax=ax)
+    display.plot_range_ring(radar.range['data'][-1] / 1000., ax=ax)
+    display.set_limits(xlim=(-500, 500), ylim=(-500, 500), ax=ax)
+    return plt
+
+
+
+#The input received from the MQ will be passed to this function
+def process_req(request):
+    b64 = []
+    json_data = json.loads(request)
+    print(json_data)
+    #uri = json_data['uri']
+    for i in range(len(json_data)):
+        fname = json_data[i]
+        print(fname)
+        plt = createGraph(fname)
+        flike = io.BytesIO()
+        plt.savefig(flike)
+        b64.append(base64.b64encode(flike.getvalue()).decode())
+
+    """resp = {
+        'id':json_data['entryId'],
+        'uri':b64
+    }"""
+
+    # Add the mq response code
+
+    #return Response(resp)
+    #Remove this line if not required
+    return b64
+
+    # subscribe a callback function to the queue. This callback function is called by the pika library
+    # It does the work and sends the response back.
+def on_request(ch, method, props, body):
+    # our message content will be in body 
+    # n = int(body) 
+
+    print(" [.] Received this data %s", body)
+
+    # instead of fib here our plot graph function should be called and response should be saved here 
+    # response = fib(n) 
+    response = process_req(body)
+    # response = fib(12)
+
+
+    ch.basic_publish(exchange='', routing_key=props.reply_to, properties=pika.BasicProperties(correlation_id = props.correlation_id), body=str(response))
+    ch.basic_ack(delivery_tag=method.delivery_tag)
+
+# We might want to run more than one server process. 
+# In order to spread the load equally over multiple servers we need to set the prefetch_count setting.
+channel.basic_qos(prefetch_count=1)
+
+# We declare a callback "on_request" for basic_consume, the core of the RPC server. It's executed when the request is received.
+channel.basic_consume(queue='plot_rx', on_message_callback=on_request)
+
+print(" [x] Awaiting RPC requests")
+channel.start_consuming()
+channel.close()
+
+
+

plot-weather-microservice/plot_weather/plot_graph/views.py

@@ -1,126 +1,128 @@
-import gzip
-from locale import CODESET
-import urllib
-from datetime import datetime
-import pika, sys, os
-
-import nexradaws
-import pyart
-import base64
-import io
-
-import pytz
-from matplotlib import pyplot as plt
-from rest_framework.utils import json
-from rest_framework.views import APIView
-from rest_framework.response import Response
-
- # Create your views here.
-class PlotAPIView(APIView):
-
-    def fetchData(self, files):
-        templocation = 'aws_files'
-        conn = nexradaws.NexradAwsInterface()
-        central_timezone = pytz.timezone('US/Central')
-        print(files)
-        file_list = files.split("/")
-        print("Files list=",file_list)
-        file = urllib.request.urlretrieve('https://noaa-nexrad-level2.s3.amazonaws.com/' + files, "aws_files/"+file_list[4])
-        if 'gz' in file_list[4]:
-            filename = gzip.open('aws_files/' + file_list[4])
-        else:
-            filename = 'aws_files/' + file_list[4]
-        return filename
-
-    def createGraph(self, filename):
-        filename = self.fetchData(filename)
-        radar = pyart.io.read_nexrad_archive(filename)
-        display = pyart.graph.RadarDisplay(radar)
-        fig = plt.figure(figsize=(6, 5))
-
-        # plot super resolution reflectivity
-        ax = fig.add_subplot(111)
-        display.plot('reflectivity', 0, title='NEXRAD Reflectivity', vmin=-32, vmax=64, colorbar_label='', ax=ax)
-        display.plot_range_ring(radar.range['data'][-1] / 1000., ax=ax)
-        display.set_limits(xlim=(-500, 500), ylim=(-500, 500), ax=ax)
-        return plt
-
-    #The input received from the MQ will be passed to this function
-    def post(self, request):
-        b64 = []
-        json_str = json.dumps(request.data)
-        json_data = json.loads(json_str)
-        #uri = json_data['uri']
-        for i in range(len(json_data)):
-            fname = json_data[i]
-            print(fname)
-            plt = self.createGraph(fname)
-            flike = io.BytesIO()
-            plt.savefig(flike)
-            b64.append(base64.b64encode(flike.getvalue()).decode())
-
-        """resp = {
-            'id':json_data['entryId'],
-            'uri':b64
-        }"""
-
-        # Add the mq response code
-
-        #return Response(resp)
-        #Remove this line if not required
-        return Response(b64,content_type='image/jpg')
-
-
-
-""""
-RABBITMQ CODE
-
-"""""
-# establish connection with rabbitmq server 
-connection = pika.BlockingConnection(pika.ConnectionParameters('localhost'))
-channel = connection.channel()
-
-#create/ declare queue
-channel.queue_declare(queue='plot_queue')
-
-
-# subscribe a callback function to the queue. This callback function is called by the pika library
-# It does the work and sends the response back.
-def on_request(ch, method, props, body):
-        # our message content will be in body 
-        n = int(body) 
-
-        print(" [.] fib(%s)" % n)
-
-        # instead of fib here our plot graph function should be called and response should be saved here 
-        response = fib(n) 
-
-        ch.basic_publish(exchange='',
-                        routing_key=props.reply_to,
-                        properties=pika.BasicProperties(correlation_id = \
-                                                            props.correlation_id),
-                        body=str(response))
-        ch.basic_ack(delivery_tag=method.delivery_tag)
-
-# We might want to run more than one server process. 
-# In order to spread the load equally over multiple servers we need to set the prefetch_count setting.
-channel.basic_qos(prefetch_count=1)
+from .server import *
+
+# import gzip
+# from locale import CODESET
+# import urllib
+# from datetime import datetime
+# import pika, sys, os
+
+# import nexradaws
+# import pyart
+# import base64
+# import io
+
+# import pytz
+# from matplotlib import pyplot as plt
+# from rest_framework.utils import json
+# from rest_framework.views import APIView
+# from rest_framework.response import Response
+
+#  # Create your views here.
+# class PlotAPIView(APIView):
+
+#     def fetchData(self, files):
+#         templocation = 'aws_files'
+#         conn = nexradaws.NexradAwsInterface()
+#         central_timezone = pytz.timezone('US/Central')
+#         print(files)
+#         file_list = files.split("/")
+#         print("Files list=",file_list)
+#         file = urllib.request.urlretrieve('https://noaa-nexrad-level2.s3.amazonaws.com/' + files, "aws_files/"+file_list[4])
+#         if 'gz' in file_list[4]:
+#             filename = gzip.open('aws_files/' + file_list[4])
+#         else:
+#             filename = 'aws_files/' + file_list[4]
+#         return filename
+
+#     def createGraph(self, filename):
+#         filename = self.fetchData(filename)
+#         radar = pyart.io.read_nexrad_archive(filename)
+#         display = pyart.graph.RadarDisplay(radar)
+#         fig = plt.figure(figsize=(6, 5))
+
+#         # plot super resolution reflectivity
+#         ax = fig.add_subplot(111)
+#         display.plot('reflectivity', 0, title='NEXRAD Reflectivity', vmin=-32, vmax=64, colorbar_label='', ax=ax)
+#         display.plot_range_ring(radar.range['data'][-1] / 1000., ax=ax)
+#         display.set_limits(xlim=(-500, 500), ylim=(-500, 500), ax=ax)
+#         return plt
+
+#     #The input received from the MQ will be passed to this function
+#     def post(self, request):
+#         b64 = []
+#         json_str = json.dumps(request.data)
+#         json_data = json.loads(json_str)
+#         #uri = json_data['uri']
+#         for i in range(len(json_data)):
+#             fname = json_data[i]
+#             print(fname)
+#             plt = self.createGraph(fname)
+#             flike = io.BytesIO()
+#             plt.savefig(flike)
+#             b64.append(base64.b64encode(flike.getvalue()).decode())
+
+#         """resp = {
+#             'id':json_data['entryId'],
+#             'uri':b64
+#         }"""
+
+#         # Add the mq response code
+
+#         #return Response(resp)
+#         #Remove this line if not required
+#         return Response(b64,content_type='image/jpg')
+
+
+
+# """"
+# RABBITMQ CODE
+
+# """""
+# # establish connection with rabbitmq server 
+# connection = pika.BlockingConnection(pika.ConnectionParameters('localhost'))
+# channel = connection.channel()
+
+# #create/ declare queue
+# channel.queue_declare(queue='plot_queue')
+
+
+# # subscribe a callback function to the queue. This callback function is called by the pika library
+# # It does the work and sends the response back.
+# def on_request(ch, method, props, body):
+#         # our message content will be in body 
+#         n = int(body) 
+
+#         print(" [.] fib(%s)" % n)
+
+#         # instead of fib here our plot graph function should be called and response should be saved here 
+#         response = fib(n) 
+
+#         ch.basic_publish(exchange='',
+#                         routing_key=props.reply_to,
+#                         properties=pika.BasicProperties(correlation_id = \
+#                                                             props.correlation_id),
+#                         body=str(response))
+#         ch.basic_ack(delivery_tag=method.delivery_tag)
+
+# # We might want to run more than one server process. 
+# # In order to spread the load equally over multiple servers we need to set the prefetch_count setting.
+# channel.basic_qos(prefetch_count=1)
 
-# We declare a callback "on_request" for basic_consume, the core of the RPC server. It's executed when the request is received.
-channel.basic_consume(queue='plot_queue', on_message_callback=on_request)
+# # We declare a callback "on_request" for basic_consume, the core of the RPC server. It's executed when the request is received.
+# channel.basic_consume(queue='plot_queue', on_message_callback=on_request)
 
-print(" [x] Awaiting RPC requests")
-channel.start_consuming()
+# print(" [x] Awaiting RPC requests")
+# channel.start_consuming()
 
-print(' [*] Waiting for messages. To exit press CTRL+C')
-channel.start_consuming()
+# print(' [*] Waiting for messages. To exit press CTRL+C')
+# channel.start_consuming()
 
 
 
-def fib(n):
-    if n == 0:
-        return 0
-    elif n == 1:
-        return 1
-    else:
-        return fib(n - 1) + fib(n - 2)
+# def fib(n):
+#     if n == 0:
+#         return 0
+#     elif n == 1:
+#         return 1
+#     else:
+#         return fib(n - 1) + fib(n - 2)

plot-weather-microservice/plot_weather/plot_weather/settings.py

@@ -26,7 +26,9 @@
 # SECURITY WARNING: don't run with debug turned on in production!
 DEBUG = True
 
-ALLOWED_HOSTS = []
+ALLOWED_HOSTS = [
+    '*'
+]
 
 
 # Application definition

plot-weather-microservice/requirements.txt

@@ -4,4 +4,5 @@ nexradaws==1.1
 matplotlib==3.5.1
 scipy==1.7.3
 numpy==1.22.2
-pandas==1.4.0
+pandas==1.4.0
+pika==1.2.0