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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
 Using Nipype with Amazon Web Services (AWS)
Several groups have been successfully using Nipype on AWS. This procedure
involves setting a temporary cluster using StarCluster and potentially
transferring files to/from S3. The latter is supported by Nipype through
DataSink and S3DataGrabber.
Using DataSink with S3
The DataSink class now supports sending output data directly to an AWS S3
bucket. It does this through the introduction of several input attributes to the
DataSink interface and by parsing the base_directory attribute. This class
uses the boto3 and
botocore Python packages to
interact with AWS. To configure the DataSink to write data to S3, the user must
set the base_directory property to an S3-style filepath.
For example
Step1:  With the "s3
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Python Code:
from nipype.interfaces.io import DataSink
ds = DataSink()
ds.inputs.base_directory = 's3://mybucket/path/to/output/dir'
Explanation: Using Nipype with Amazon Web Services (AWS)
Several groups have been successfully using Nipype on AWS. This procedure
involves setting a temporary cluster using StarCluster and potentially
transferring files to/from S3. The latter is supported by Nipype through
DataSink and S3DataGrabber.
Using DataSink with S3
The DataSink class now supports sending output data directly to an AWS S3
bucket. It does this through the introduction of several input attributes to the
DataSink interface and by parsing the base_directory attribute. This class
uses the boto3 and
botocore Python packages to
interact with AWS. To configure the DataSink to write data to S3, the user must
set the base_directory property to an S3-style filepath.
For example:
End of explanation
ds.inputs.creds_path = '/home/neuro/aws_creds/credentials.csv'
ds.inputs.encrypt_bucket_keys = True
ds.local_copy = '/home/neuro/workflow_outputs/local_backup'
Explanation: With the "s3://" prefix in the path, the DataSink knows that the output
directory to send files is on S3 in the bucket "mybucket". "path/to/output/dir"
is the relative directory path within the bucket "mybucket" where output data
will be uploaded to (Note: if the relative path specified contains folders that
don’t exist in the bucket, the DataSink will create them). The DataSink treats
the S3 base directory exactly as it would a local directory, maintaining support
for containers, substitutions, subfolders, "." notation, etc. to route output
data appropriately.
There are four new attributes introduced with S3-compatibility: creds_path,
encrypt_bucket_keys, local_copy, and bucket.
End of explanation
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