def createDs3Obj(fileName):
size = os.stat(fileName).st_size
ds3ObjName = "prefix/" + fileName
fileMap[ds3ObjName] = fileName
return ds3.FileObject(ds3ObjName, size)
def getSize(fileName, prefix=""):
size = os.stat(pathForResource(fileName)).st_size
return ds3.FileObject(prefix + fileName, size)
def getSize(fileName, realFileName):
size = os.stat(realFileName).st_size
return ds3.FileObject(fileName, size)
# Copyright 2014-2017 Spectra Logic Corporation. All Rights Reserved.
# Licensed under the Apache License, Version 2.0 (the "License"). You may not use
# this file except in compliance with the License. A copy of the License is located at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# or in the "license" file accompanying this file.
# This file is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
# CONDITIONS OF ANY KIND, either express or implied. See the License for the
# specific language governing permissions and limitations under the License.
import os
import tempfile
from ds3 import ds3
client = ds3.createClientFromEnv()
bucketName = "sdkexamples"
objectName = "123456795.txt"
objlist = ds3.FileObjectList([ds3.FileObject(objectName)])
tapes = client.get_physical_placement_for_objects_spectra_s3(
ds3.GetPhysicalPlacementForObjectsSpectraS3Request(bucketName, objlist))
for tape in tapes.result['TapeList']:
print(tape)
# specific language governing permissions and limitations under the License.
import os
import tempfile
from ds3 import ds3
client = ds3.createClientFromEnv()
bucketName = "books"
# this example assumes that a bucket named "books" and the following objects exist on the server (these are the same objects as are on the server if they are not deleted at the end of the bulk put example)
fileList = ["beowulf.txt", "sherlock_holmes.txt", "tale_of_two_cities.txt", "ulysses.txt"]
bucketContents = client.get_bucket(ds3.GetBucketRequest(bucketName))
objectList = ds3.FileObjectList([ds3.FileObject(obj['Key']) for obj in bucketContents.result['ContentsList']])
bulkGetResult = client.get_bulk_job_spectra_s3(ds3.GetBulkJobSpectraS3Request(bucketName, objectList))
# create a set of the chunk ids which will be used to track
# what chunks have not been retrieved
chunkIds = set([x['ChunkId'] for x in bulkGetResult.result['ObjectsList']])
# create a dictionary to map our retrieved objects to temporary files
# if you want to keep the retreived files on disk, this is not necessary
tempFiles={}
# while we still have chunks to retrieve
while len(chunkIds) > 0:
# get a list of the available chunks that we can get
availableChunks = client.get_job_chunks_ready_for_client_processing_spectra_s3(
ds3.GetJobChunksReadyForClientProcessingSpectraS3Request(bulkGetResult.result['JobId']))
from ds3 import ds3
client = ds3.createClientFromEnv()
bucketName = "books"
# this example assumes that a bucket named "books" and the following objects exist on the server (these are the same objects as are on the server if they are not deleted at the end of the bulk put example)
fileList = [
"beowulf.txt", "sherlock_holmes.txt", "tale_of_two_cities.txt",
"ulysses.txt"
]
bucketContents = client.get_bucket(ds3.GetBucketRequest(bucketName))
objectList = ds3.FileObjectList(
map(lambda obj: ds3.FileObject(obj['Key']),
bucketContents.result['ContentsList']))
bulkGetResult = client.get_bulk_job_spectra_s3(
ds3.GetBulkJobSpectraS3Request(bucketName, objectList))
# create a set of the chunk ids which will be used to track
# what chunks have not been retrieved
chunkIds = set(map(lambda x: x['ChunkId'],
bulkGetResult.result['ObjectsList']))
# create a dictionary to map our retrieved objects to temporary files
# if you want to keep the retreived files on disk, this is not necessary
tempFiles = {}
# while we still have chunks to retrieve
while len(chunkIds) > 0: