来自this 文档:
使用传输管理器
boto3 提供用于管理各种类型传输的接口
S3。功能包括:
自动管理分段和非分段上传
为了确保分段上传仅在绝对情况下发生
必要时,您可以使用 multipart_threshold 配置
参数:
使用以下 python 代码将文件上传到 s3 并管理自动分段上传。
import argparse
import boto3
import botocore
import os
import pandas as pd
from boto3.s3.transfer import TransferConfig
def environment_set(access_key,secret_access_key):
os.environ["AWS_ACCESS_KEY_ID"] = access_key
os.environ["AWS_SECRET_ACCESS_KEY"] = secret_access_key
def s3_upload_file(args):
while True:
try:
s3 = boto3.resource('s3')
GB = 1024 ** 3
# Ensure that multipart uploads only happen if the size of a transfer
# is larger than S3's size limit for nonmultipart uploads, which is 5 GB.
config = TransferConfig(multipart_threshold=5 * GB)
s3.meta.client.upload_file(args.path, args.bucket, os.path.basename(args.path),Config=config)
print "S3 Uploading successful"
break
except botocore.exceptions.EndpointConnectionError:
print "Network Error: Please Check your Internet Connection"
except Exception, e:
print e
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='UPLOAD A FILE TO PRE-EXISTING S3 BUCKET')
parser.add_argument('path', metavar='PATH', type=str,
help='Enter the Path to file to be uploaded to s3')
parser.add_argument('bucket', metavar='BUCKET_NAME', type=str,
help='Enter the name of the bucket to which file has to be uploaded')
parser.add_argument('cred', metavar='CREDENTIALS', type=str,
help='Enter the Path to credentials.csv, having AWS access key and secret access key')
args = parser.parse_args()
df = pd.read_csv(args.cred, header=None)
access_key = df.iloc[1,1]
secret_access_key = df.iloc[1,2]
environment_set(access_key,secret_access_key)
s3_upload_file(args)