##开发前准备 ###安装python sdk 1、通过git下载SDK到本地
git clone http://git.op.ksyun.com/bailingzhou/ks3-python-sdk.git
2、进入ks3-python-sdk目录
cd ks3-python-sdk
3、安装SDK
python setup.py install
###创建一个connection 注：（[AccessKeyID和AccessKeySecret])
ACCESS_KEY_ID：金山云提供的ACCESS KEY ID
SECRET_ACCESS_KEY：金山云提供的SECRET KEY ID
YOUR_REGION_ENDPOINT: 金山云提供的各个Region的域名,参考 KS3文档中心
from ks3.connection import Connection
ak = 'YOUR_ACCESS_KEY'
sk = 'YOUR_SECRET_KEY'
c = Connection(ak, sk, host='YOUR_REGION_ENDPOINT')
###运行环境 适用于2.6、2.7的Python版本
##安全性 ###使用场景 由于在App端明文存储AccessKeyID、AccessKeySecret是极不安全的，因此推荐的使用场景如下图所示：
###KingSoftS3Client初始化
- 利用AccessKeyID、AccessKeySecret初始化
对应的初始化代码如下：
[[KingSoftS3Client initialize] connectWithAccessKey:strAccessKey withSecretKey:strSecretKey];
##SDK介绍及使用
###资源管理操作
- List Buckets 列出客户所有的Bucket信息
- Create Bucket 创建一个新的Bucket
- Delete Bucket 删除指定Bucket
- Get Bucket ACL 获取Bucket的ACL
- Put Bucket ACL 设置Bucket的ACL
- Get Object 下载Object数据
- Put Object 上传Object数据
- List Objects 列举Bucket内的Object
- Get Object ACL 获得Bucket的acl
- Put Object ACL 上传object的acl
- Upload Part 上传分块
###Service操作
####List Buckets：
列出客户所有的 Bucket 信息
buckets = c.get_all_buckets()
for b in buckets:
print b.name
###Bucket操作
####Create Bucket：
创建一个新的Bucket
在建立了连接后，可以创建一个bucket。bucket在s3中是一个用于储存key/value的容器。用户可以将所有的数据存储在一个bucket里，也可以为不同种类数据创建相应的bucket。
bucket_name = "YOUR_BUCKET_NAME"
b = c.create_bucket(bucket_name)
注：这里如果出现409 conflict错误，说明请求的bucket name有冲突，因为bucket name是全局唯一的
####Delete Bucket:
删除指定Bucket
删除一个bucket可以通过delete_bucket方法实现。
c.delete_bucket(bucket_name)
如果bucket下面存在key，那么需要首先删除所有key
b = c.get_bucket(bucket_name)
for k in b.list():
k.delete()
c.delete_bucket(bucket_name)
####Get Bucket ACL:
获取Bucket的ACL
acp = b.get_acl()
>>> acp
<Policy: MTM1OTk4ODE= (owner) = FULL_CONTROL>
>>> acp.acl
<ks3.acl.ACL object at 0x23cf750>
>>> acp.acl.grants
[<ks3.acl.Grant object at 0xf63810>]
>>> for grant in acp.acl.grants:
... print grant.permission, grant.display_name, grant.email_address, grant.id
...
####Put Bucket ACL:
*设置Bucket的ACL
//设置bucket的权限
b.set_acl("public-read")
###Object操作
####Get Object： 下载该Object数据
下载object，并且作为字符串返回
from ks3.connection import Connection
bucket_name = "YOUR_BUCKET_NAME"
key_name = "YOUR_KEY_NAME"
b = c.get_bucket(bucket_name)
k = b.get_key(key_name)
s = k.get_contents_as_string()
print s
下载object，并且保存到文件中
k.get_contents_to_filename("/root/KS3SDK_download_test")
####Put Oobject 上传Object数据
将指定目录的文件上传
bucket_name = "YOUR_BUCKET_NAME"
key_name = "YOUR_KEY_NAME"
b = c.get_bucket(bucket_name)
k = b.new_key(key_name)
k.set_contents_from_filename("/root/KS3SDK_upload_test")
将字符串所谓value上传
k.set_contents_from_string('This is a test of S3')
####List Oobject 列举Bucket内的Object
b = c.get_bucket(bucket_name)
keys = b.list()
列举Bucket内的目录
from ks3.prefix import Prefix
from ks3.key import Key
b = c.get_bucket(bucket_name)
keys = b.list(delimiter='/')
for k in keys:
if isinstance(k,Key):
print 'file:%s' % k.name
elif isinstance(k,Prefix):
print 'dir:%s' % k.name
####Get Object ACL 获得Object的acl
b = c.get_bucket(bucket_name)
policy = b.get_acl(key_name)
print policy.to_xml()
####Put Object ACL
b.set_acl("public-read", test_key)
####Upload Part： 分块上传
如果你想上传一个大文件，你可以将它分成几个小份，逐个上传，s3会按照顺序把它们合成一个最终的object。整个过程需要几步来完成，下面的demo程序是通过python的FileChunkIO模块来实现的。所以可能需要首先运行pip install FileChunkIO来安装。
>>> import math, os
>>> from ks3.connection import Connection
>>> from filechunkio import FileChunkIO
# Connect to S3
>>> bucket_name = "YOUR_BUCKET_NAME"
>>> c = Connection(ak, sk)
>>> b = c.get_bucket(bucket_name)
# Get file info
>>> source_path = 'path/to/your/file.ext'
>>> source_size = os.stat(source_path).st_size
# Create a multipart upload request
>>> mp = b.initiate_multipart_upload(os.path.basename(source_path))
# Use a chunk size of 50 MiB (feel free to change this)
>>> chunk_size = 52428800
>>> chunk_count = int(math.ceil(source_size / chunk_size))
# Send the file parts, using FileChunkIO to create a file-like object
# that points to a certain byte range within the original file. We
# set bytes to never exceed the original file size.
>>> for i in range(chunk_count + 1):
>>> offset = chunk_size * i
>>> bytes = min(chunk_size, source_size - offset)
>>> with FileChunkIO(source_path, 'r', offset=offset,
bytes=bytes) as fp:
>>> mp.upload_part_from_file(fp, part_num=i + 1)
# Finish the upload
>>> mp.complete_upload()