I am trying to write a lambda function that will tag ec2 instances that will go from pending to running state.
However, I have a problem reading the csv file that holds my ec2 instance tags. Currently, I have gone to where the lambda returns me the following result.
START RequestId: 6290699e-4018-4801-b7a8-6b5b46f26c2a Version: $LATEST
{'Key': 'Name1', 'Value': 'Machine-1'}
{'Key': 'Name2', 'Value': 'Machine-2'}
{'Key': 'Name3', 'Value': 'Machine-3'}
END RequestId: 6290699e-4018-4801-b7a8-6b5b46f26c2a
REPORT RequestId: 6290699e-4018-4801-b7a8-6b5b46f26c2a Duration: 3306.40 ms Billed Duration: 3307 ms Memory Size: 128 MB Max Memory Used: 88 MB Init Duration: 335.79 ms
However, I need a list of dictionaries.
myList = [{'Key': 'Name1', 'Value': 'Instance-1'}, {'Key': 'Name2', 'Value': 'Instance-2'}, {'Key': 'Name3', 'Value': 'Instance-3'}]
Because the rest of the code looks like the following
instance_id = event['detail']['instance-id']
response = ec2_client.create_tags(
Resources=[
instance_id,
],
Tags=[
{
'Key': 'Name',
'Value': 'event_bridge_lambda_tag'
},
]
)
At the moment, my lambda code looks like the following
import csv
import boto3
from collections import OrderedDict
def lambda_handler(event, context):
s3_client = boto3.client("s3")
ec2_client = boto3.client("ec2")
S3_BUCKET_NAME = "tag-holds-bucket"
FILE_NAME = "tags.csv"
s3_file = s3_client.get_object(Bucket=S3_BUCKET_NAME, Key=FILE_NAME)
file_content = s3_file['Body'].read().decode('utf-8').splitlines()
myList = list()
records = csv.DictReader(file_content)
for row in records:
#print(dict(row))
myList.append(row)
myList.append(row) -> gives me something like this as output
START RequestId: 618217d1-d1da-473f-b55e-77f1f7fe52dc Version: $LATEST
[OrderedDict([('Key', 'Name1'), ('Value', 'Instance-1')]), OrderedDict([('Key', 'Name2'), ('Value', 'Instance-2')]), OrderedDict([('Key', 'Name3'), ('Value', 'Instance-3')])]
END RequestId: 618217d1-d1da-473f-b55e-77f1f7fe52dc
REPORT RequestId: 618217d1-d1da-473f-b55e-77f1f7fe52dc Duration: 3128.39 ms Billed Duration: 3129 ms Memory Size: 128 MB Max Memory Used: 88 MB Init Duration: 330.02 ms
I don’t know how to reach such a state
myList = [{'Key': 'Name1', 'Value': 'Instance-1'}, {'Key': 'Name2', 'Value': 'Instance-2'}, {'Key': 'Name3', 'Value': 'Instance-3'}]
My cvs file looks like this
And rest of the lambda code
instance_id = event['detail']['instance-id']
response = ec2_client.create_tags(
Resources=[
instance_id,
],
Tags=[
{
'Key': 'Name',
'Value': 'event_bridge_lambda_tag'
},
]
)
2
Answers
csv.DictReader
returns adict
or anOrderedDict
depending on the Python version you are running.As seen in the documentation:
So it seems you are running Python < 3.8 in the lambda function. So you have 2 possibilities to have the output as a dict:
OrderedDict
to adict
in your code simply using dict method:my_dict = dict(myList)
One way to serialize
collections.OrderedDict
into a list of dictionaries is by usingjson
library.or you can just use list comprehension