Python S3 Concat

S3 Concat is used to concatenate many small files in an s3 bucket into fewer larger files.

Install

pip install s3-concat

Usage

Command Line

$ s3-concat -h

Import

from s3_concat import S3Concat

bucket = 'YOUR_BUCKET_NAME'
path_to_concat = 'PATH_TO_FILES_TO_CONCAT'
concatenated_file = 'FILE_TO_SAVE_TO.json'
# Setting this to a size will always add a part number at the end of the file name
min_file_size = '50MB'  # ex: FILE_TO_SAVE_TO-1.json, FILE_TO_SAVE_TO-2.json, ...
# Setting this to None will concat all files into a single file
# min_file_size = None  ex: FILE_TO_SAVE_TO.json

# Init the job
job = S3Concat(bucket, concatenated_file, min_file_size,
               content_type='application/json',
              #  session=boto3.session.Session(),  # For custom aws session
              # s3_client_kwargs={}  # Use to pass arguments allowed by the s3 client: https://boto3.amazonaws.com/v1/documentation/api/latest/reference/core/session.html
               )
# Add files, can call multiple times to add files from other directories
job.add_files(path_to_concat)
# Add a single file at a time
job.add_file('some/file_key.json')
# Only use small_parts_threads if you need to. See Advanced Usage section below.
job.concat(small_parts_threads=4)

Advanced Usage

Depending on your use case, you may want to use small_parts_threads.

• small_parts_threads is only used when the files you are trying to concat are less then 5MB. Due to the limitations of the s3 multipart_upload api (see Limitations below) any files less then 5MB need to be download locally, concated together, then re uploaded. By setting this thread count it will download the parts in parallel for faster creation of the concatination process.

The values set for these arguments depends on your use case and the system you are running this on.

Limitations

This uses the multipart upload of s3 and its limits are https://docs.aws.amazon.com/AmazonS3/latest/dev/qfacts.html