def send_lambda_request(fn, tests, encounter_id, player):
awslambda = boto.connect_awslambda(aws_access_key_id=AWS_ACCESS_KEY,
aws_secret_access_key=AWS_SECRET_KEY)
player_fn = fn
battle_tests = tests
battle_test_string = "[" + ",".join(battle_tests) + "]"
data = {
"fn": base64.b64encode(player_fn),
"tests": base64.b64encode(battle_test_string),
"encounter_id": encounter_id,
"player": player
}
awslambda.invoke_async("BattleJSTesting", json.dumps(data))
def configure_lambda(stream):
"""
Configure Lambda function to use Kinesis
"""
print("Configured AWS Lambda service")
IAM_ROLE_ARN = get_iam_role_arn()
aws_lambda = boto.connect_awslambda()
event_source = kinesis_stream(stream)
response_add_event_source = aws_lambda.add_event_source(event_source,
FUNCTION_NAME,
IAM_ROLE_ARN,
batch_size=100,
parameters=None)
event_source_id = response_add_event_source['UUID']
while response_add_event_source['IsActive'] != 'true':
print('Waiting for the event source to become active')
sleep(5)
response_add_event_source = aws_lambda.get_event_source(event_source_id)
print('Added Kinesis as event source for Lambda function')
import os
from time import sleep
from zipfile import ZipFile
import boto
from boto.kinesis.exceptions import ResourceInUseException
import config
# To enable logging:
# boto.set_stream_logger('boto')
# Initialize the AWS clients.
sns = boto.connect_sns()
kinesis = boto.connect_kinesis()
aws_lambda = boto.connect_awslambda()
ml = boto.connect_machinelearning()
lambda_execution_policy = open('lambdaExecutionPolicyTemplate.json').read().format(**config.AWS)
aws_account_id = config.AWS["awsAccountId"]
region = config.AWS["region"]
kinesis_stream = config.AWS["kinesisStream"]
sns_topic = config.AWS["snsTopic"]
lambda_function_name = config.AWS["lambdaFunctionName"]
lambda_execution_role = config.AWS["lambdaExecutionRole"]
lambda_trust_policy = '{"Statement":[{"Effect":"Allow","Principal":{"Service":"lambda.amazonaws.com"},"Action":"sts:AssumeRole"}]}'
def role_exists(iam, role_name):
import os
from time import sleep
from zipfile import ZipFile
# To enable logging:
# boto.set_stream_logger('boto')
def read_file_as_string_then_format(file_name, args):
with open(file_name) as file_handle:
return file_handle.read().format(**args)
# Initialize the AWS clients.
sns = boto.connect_sns()
kinesis = boto.connect_kinesis()
aws_lambda = boto.connect_awslambda()
ml = boto.connect_machinelearning()
# Load the config file.
with open('create-lambda-function.config') as config:
config = json.load(config)
lambda_execution_policy = read_file_as_string_then_format('lambdaExecutionPolicyTemplate.json', config)
lambda_invocation_policy = read_file_as_string_then_format('lambdaInvocationPolicyTemplate.json', config)
aws_account_id = config["awsAccountId"]
region = config["region"]
kinesis_stream = config["kinesisStream"]
sns_topic = config["snsTopic"]
import sys
sys.path.append(".") # Adds higher directory to python modules path.
import base64
import boto
import settings
iam_client = boto.connect_iam(
aws_access_key_id=settings.AWS_ACCESS_KEY_ID,
aws_secret_access_key=settings.AWS_SECRET_ACCESS_KEY)
lambda_client = boto.connect_awslambda(
aws_access_key_id=settings.AWS_ACCESS_KEY_ID,
aws_secret_access_key=settings.AWS_SECRET_ACCESS_KEY)
env_variables = dict() # Environment Variables
with open('data/lambda.zip', 'rb') as f:
zipped_code = base64.b64encode(f.read())
role = iam_client.get_role('lambda_basic_execution')
lambda_client.upload_function(
'stee_eye_prepare_json', zipped_code, 'python3.6',
role['get_role_response']['get_role_result']['role']['arn'],
'main.handler', 'event')
def setUp(self):
self.awslambda = boto.connect_awslambda()
