h4

from __future__ import with_statement
from alembic import context
from sqlalchemy import engine_from_config, pool
from logging.config import fileConfig

from models import Base

config = context.config

fileConfig(config.config_file_name)

gamame

#!/usr/bin/env python
"""Split large file into multiple pieces for upload to S3.

S3 only supports 5Gb files for uploading directly, so for larger CloudBioLinux
box images we need to use boto's multipart file support.

This parallelizes the task over available cores using multiprocessing.

Usage:
  s3_multipart_upload.py <file_to_transfer> <bucket_name> [<s3_key_name>]