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Access resources on Amazon S3 as a File Object.

Project description

About

s3io is a minimalistic python module which provides file object access to data on S3.

All data manipulations are done via temporary local files - so you will actually work with local temp file which is a file object with all its methods supported.

Just keep in mind these facts:

  1. Reading: the whole file will be downloaded to local temporary location at entering the context.
  2. Writing: temp file will be provided at entering the context. Actual saving to S3 will be performed at exit from context. Thus such methods as flush will not influence the process of saving to S3.

Dependencies

Examples

s3io is intended to be used via context manager only.

There are three ways to provide access to s3:

  1. Directly providing s3_connection.
  2. Providing credentials: aws_access_key_id and aws_secret_access_key.
  3. Providing profile_name. This method is recommended to use. See boto docs for more info.

Reading file using existing S3 connection:

import s3io

s3 = boto.connect_s3()
with s3io.open('s3://<bucket>/<key>', s3_connection=s3) as s3_file:
    contents = s3_file.read()

Reading file using credentials:

credentials = dict(
    aws_access_key_id='<ACCESS_KEY>',
    aws_secret_access_key='<SECRET_KEY>',
)
with s3io.open('s3://<bucket>/<key>', **credentials) as s3_file:
    contents = s3_file.read()

Reading file using profile:

with s3io.open('s3://<bucket>/<key>', profile_name='<profile>') as s3_file:
    contents = s3_file.read()

Writing file using profile:

with s3io.open('s3://<bucket>/<key>', mode='w', profile_name='<profile>') as s3_file:
    s3_file.write('Some data.')

Exceptions

Possible exceptions:

  1. s3io.BucketNotFoundError
  2. s3io.KeyNotFoundError
  3. s3io.UrlParseError

Project details


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