Managing AWS using boto made easy

Save the file easyboto.py in the same directory from where you are running python. Or the import statement will fail.

1. import module

from easyboto import connect

2. initialize the class with login credentials. Access and Secret key of your AWS account is required.

x = connect('xxx', 'yyy')

3. Describe the current running cluster

x.showCluster()

4. start a new cluster based on the latest snapshot

x.startCluster()

5. This does not actually delete the cluster for security reasons. It shows the command to do so :)

x.deleteCluster()

6. show all backup snapshots

x.showSnapshot()

7. create a snapshot of the current cluster

x.startSnapshot()

8. delete a given snapshot. Snapshot name is required.

x.deleteSnapshot('name_of_snap')

9. Execute any Redshift query

x.runQuery('select * from school1_oct_sending limit 10')

10. list all ec2 instances and all images in default region (us-eash N. Virginia)

x.showEc2()

x.ShowImages()

11. Create an ec2 instance.

x.startEc2()

12. Terminate ec2 instance.

x.deleteEc2('instance_id')

13. Terminate all ec2 instances.

This does not actually delete all EC2 instances for security reasons. It shows the command to do so :)

x.deleteAllEc2()

14. List all buckets or files from a bucket

x.showBucket()

x.showBucket('bucket_name')

15. Upload file to a given bucket. Optionally specify S3 path

x.uploadFile('bucket_name', '/new/path', '/path/to/file.csv')

16. Download file

x.downloadFile('bucket_name', 'file.csv')

17. Delete a file from the bucket

x.deleteFile('bucket_name', 'file.csv')

18. List bucket lifeCycle if any:

x.showBucketLifeCycle()

a) show details of cluster, snapshot, buckets, files in bucket, bucket life Cycle, ec2 or images.

showCluster
showSnapshot
showBucket
showBucket('bucket_name')
showBucketLifeCycle
showEc2
showImages

b) Start a new cluster based on latest snapshot, create a snapshot of running cluster or start an ec2 instance

startCluster
startSnapshot
startEc2

c) delete a given ec2 instance or snapsshot. Statements are generated to delete all instances or to delete current cluster.

deleteEc2('instance_id_to_delete')
deleteAllEc2
deleteCluster
deleteSnapshot('snapshot_identifier_todelete')
deleteFile('bucket_name', 'file_name')

d) run any Redshift query

runQuery(my_query):

e) Upload or download a file to / from S3 bucket

uploadFile('bucket_name', '/path/to/file.csv')
downloadFile('bucket_name', 'file_name.csv')

modules required are boto and pandas. Optionally import psycopg2 if you want to run redshift queries.

from easyboto import myboto
x = myboto('your_access_key', 'your_secret_key')
x.showBucket()

pip install easyboto

easily save the output dict to mongodb test database, collection name: posts

y=x.showCluster()[0]

from pymongo import MongoClient
client = MongoClient()
db = client.test
db.posts.insert_one(y)

db.posts.find_one()

If the function returns dataframe then it is easy to copy the data from pandas to mongodb

df=x.showSnapshot()
db.posts.insert_many(df.to_dict('records'))

you may need to correct the data

df["region"] = df["region"].map(lambda x: str(x).split(':')[-1:])