Update handler and Dynamo DB

.gitignore

@@ -1,2 +1,3 @@
 *.mp4
-*.json
+*.json
+*.csv

handler.py

@@ -1,15 +1,16 @@
 import boto3
+import colorama
 import face_recognition
+import glob
 import os
 import pickle
+from botocore.exceptions import ClientError
 from termcolor import cprint
-import colorama
 
 colorama.init()
 input_bucket = 'inputbucket-cse546'
-output_bucket = "546proj2output"
+output_bucket = "outputbucket-cse546"
 encoding_filename = "encoding"
-frames_path = os.path.join(os.getcwd(), "Frames")
 
 # Function to read the 'encoding' file
 def open_encoding(filename):
@@ -18,7 +19,14 @@ def open_encoding(filename):
 	file.close()
 	return data
 
-def face_recognition_handler(file_name):	
+def face_recognition_handler(file_name):
+
+	# 0. Build the baseline
+	frames_path = os.path.join(os.getcwd(), "Frames")
+	if not os.path.exists(frames_path):
+		os.makedirs(frames_path)
+
+
 	local_file_path = download_file_s3(file_name)
 	encoded_data = open_encoding(encoding_filename)
 
@@ -52,8 +60,32 @@ def face_recognition_handler(file_name):
 		if faceName:
 			break
 
-	# Search facename in DynamoDB
-	return faceName
+	# 3. Search facename in DynamoDB
+
+	result = search_in_dynamodb(facename=faceName)
+
+	# 4. Upload CSV file to S3 bucket.
+	upload_status = False
+	csvFileName = None
+	if result:
+		csvFileName = file_name.split('.')[0] + ".csv"
+		with open(f'{csvFileName}', 'w') as f:
+			f.writelines(result)
+
+		upload_csv_to_bucket(
+			csv_file=csvFileName)
+		upload_status = True
+
+	# 5. Clean Up if Step 4 succeeds
+	if upload_status:
+		# Remove all files in Frames folder
+		print("Clean up script starts...")
+		files = glob.glob(frames_path + "/*")
+		for f in files:
+			cprint(f"Deleting file {f}", "red")
+			os.remove(f)
+
+	return result
 
 
 # Define function to download file from S3 bucket
@@ -69,12 +101,43 @@ def download_file_s3(file_name):
 	return local_file_path
 
 
-if not os.path.exists(frames_path):
-	os.makedirs(frames_path)
+# Search for facename in Dynamo DB
+def search_in_dynamodb(facename):
+	dynamodb = boto3.resource('dynamodb')
+	table = dynamodb.Table('Student_data')
+	if facename:
+		response = table.get_item(Key={
+			"name": facename
+		})
+
+		return f"{response['Item']['name']},{response['Item']['major']},{response['Item']['year']}"
+	else:
+		return None
+
+# Upload csv file to S3 bucket
+def upload_csv_to_bucket(csv_file):
+	s3 = boto3.resource('s3')
+	bucket = s3.Bucket(output_bucket)
+
+	local_file_path = os.path.join(os.getcwd(), csv_file)
+	cprint(f"Local CSV path : {local_file_path}", "white")
+
+	if os.path.exists(local_file_path):
+		cprint(f'Uploading file to S3 : {output_bucket}', "blue")
+		try:
+			response = bucket.upload_file(local_file_path, csv_file)
+		except ClientError as e:
+			cprint(e, "red")
+			exit(-1)
+	else:
+		cprint(f"CSV file : {local_file_path} not found.", "red")
+		exit(-1)
 
 
 # This will change to actual format
 # face_recognition_handler(event, context)
 print(face_recognition_handler('test_0.mp4'))
 
+# print(search_in_dynamodb("president_biden"))
+
 

upload_data_to_dynamo.py

@@ -0,0 +1,63 @@
+import boto3
+import json
+import os
+import time
+from botocore.exceptions import ClientError
+
+dynamo_client = boto3.resource(service_name='dynamodb', region_name='us-east-1')
+table_name='Student_data'
+
+# delete table if it exists
+try:
+    student_data_table = dynamo_client.Table(table_name)
+    student_data_table.delete()
+
+    print(f"Deleting {student_data_table.name}...")
+    student_data_table.wait_until_not_exists()
+except ClientError as ce:
+    print(ce.response['Error'])
+
+# Create the table
+try:
+    dynamo_client.create_table(
+        TableName=table_name,
+        AttributeDefinitions=[
+            {
+                'AttributeName': 'name',
+                'AttributeType': 'S'
+            },
+        ],
+        TableClass='STANDARD',
+        KeySchema=[
+            {
+                'AttributeName': 'name',
+                'KeyType': 'HASH'
+            },
+        ],
+        BillingMode='PROVISIONED',
+        ProvisionedThroughput={
+            'ReadCapacityUnits': 5,
+            'WriteCapacityUnits': 5
+        },
+    )
+
+    print(f'Table {table_name} successfully created')
+except ClientError as ce:
+    print(ce.response['Error'])
+    exit(-1)
+
+
+student_data_table = dynamo_client.Table(table_name)
+
+student_data_table.wait_until_exists()
+
+if os.path.exists('./student_data.json'):
+    data = json.load(open('./student_data.json'))
+else:
+    print('File student.json does not exist')
+    exit(-1)
+
+# Upload data to table
+for d in data:
+    print(f'Adding {d}')
+    student_data_table.put_item(Item=d)