The simple module for putting and getting object from Amazon S3 compatible endpoints
Project description
httpx-s3-client
The simple module for putting and getting object from Amazon S3 compatible endpoints.
Installation
pip install httpx-s3-client
Usage
from http import HTTPStatus
from httpx import AsyncClient
from httpx_s3_client import S3Client
client = S3Client(
url="http://s3-url",
client=AsyncClient(),
access_key_id="key-id",
secret_access_key="hackme",
region="us-east-1"
)
# Upload str object to bucket "bucket" and key "str"
resp = await client.put("bucket/str", "hello, world")
assert resp.status_code == HTTPStatus.OK
# Upload bytes object to bucket "bucket" and key "bytes"
resp = await client.put("bucket/bytes", b"hello, world")
assert resp.status_code == HTTPStatus.OK
# Upload AsyncIterable to bucket "bucket" and key "iterable"
async def gen():
yield b'some bytes'
resp = await client.put("bucket/file", gen())
assert resp.status_code == HTTPStatus.OK
# Upload file to bucket "bucket" and key "file"
resp = await client.put_file("bucket/file", "/path_to_file" )
assert resp.status_code == HTTPStatus.OK
# Check object exists using bucket+key
resp = await client.head("bucket/key")
assert resp.status_code == HTTPStatus.OK
# Get object by bucket+key
resp = await client.get("bucket/key")
data = resp.content
# Delete object using bucket+key
resp = await client.delete("bucket/key")
assert resp == HTTPStatus.NO_CONTENT
# List objects by prefix
async for result in client.list_objects_v2("bucket/", prefix="prefix"):
# Each result is a list of metadata objects representing an object
# stored in the bucket.
do_work(result)
Bucket may be specified as subdomain or in object name:
import httpx
from httpx_s3_client import S3Client
client = S3Client(url="http://bucket.your-s3-host",
client=httpx.AsyncClient())
resp = await client.put("key", gen())
...
client = S3Client(url="http://your-s3-host",
client=httpx.AsyncClient())
resp = await client.put("bucket/key", gen())
...
client = S3Client(url="http://your-s3-host/bucket",
client=httpx.AsyncClient())
resp = await client.put("key", gen())
...
Auth may be specified with keywords or in URL:
import httpx
from httpx_s3_client import S3Client
client_credentials_as_kw = S3Client(
url="http://your-s3-host",
access_key_id="key_id",
secret_access_key="access_key",
client=httpx.AsyncClient(),
)
client_credentials_in_url = S3Client(
url="http://key_id:access_key@your-s3-host",
client=httpx.AsyncClient(),
)
Credentials
By default S3Client
trying to collect all available credentials from keyword
arguments like access_key_id=
and secret_access_key=
, after that from the
username and password from passed url
argument, so the nex step is environment
variables parsing and the last source for collection is the config file.
You can pass credentials explicitly using httpx_s3_client.credentials
module.
httpx_s3_client.credentials.StaticCredentials
import httpx
from httpx_s3_client import S3Client
from httpx_s3_client.credentials import StaticCredentials
credentials = StaticCredentials(
access_key_id='aaaa',
secret_access_key='bbbb',
region='us-east-1',
)
client = S3Client(
url="http://your-s3-host",
client=httpx.AsyncClient(),
credentials=credentials,
)
httpx_s3_client.credentials.URLCredentials
import httpx
from httpx_s3_client import S3Client
from httpx_s3_client.credentials import URLCredentials
url = "http://key@hack-me:your-s3-host"
credentials = URLCredentials(url, region="us-east-1")
client = S3Client(
url="http://your-s3-host",
client=httpx.AsyncClient(),
credentials=credentials,
)
httpx_s3_client.credentials.EnvironmentCredentials
import httpx
from httpx_s3_client import S3Client
from httpx_s3_client.credentials import EnvironmentCredentials
credentials = EnvironmentCredentials(region="us-east-1")
client = S3Client(
url="http://your-s3-host",
client=httpx.AsyncClient(),
credentials=credentials,
)
httpx_s3_client.credentials.ConfigCredentials
Using user config file:
import httpx
from httpx_s3_client import S3Client
from httpx_s3_client.credentials import ConfigCredentials
credentials = ConfigCredentials() # Will be used ~/.aws/credentials config
client = S3Client(
url="http://your-s3-host",
client=httpx.AsyncClient(),
credentials=credentials,
)
Using the custom config location:
import httpx
from httpx_s3_client import S3Client
from httpx_s3_client.credentials import ConfigCredentials
credentials = ConfigCredentials("~/.my-custom-aws-credentials")
client = S3Client(
url="http://your-s3-host",
client=httpx.AsyncClient(),
credentials=credentials,
)
httpx_s3_client.credentials.merge_credentials
This function collect all passed credentials instances and return a new one which contains all non-blank fields from passed instances. The first argument has more priority.
import httpx
from httpx_s3_client import S3Client
from httpx_s3_client.credentials import (
ConfigCredentials, EnvironmentCredentials, merge_credentials
)
credentials = merge_credentials(
EnvironmentCredentials(),
ConfigCredentials(),
)
client = S3Client(
url="http://your-s3-host",
client=httpx.AsyncClient(),
credentials=credentials,
)
httpx_s3_client.credentials.MetadataCredentials
Trying to get credentials from the metadata service:
import httpx
from httpx_s3_client import S3Client
from httpx_s3_client.credentials import MetadataCredentials
credentials = MetadataCredentials()
# start refresh credentials from metadata server
await credentials.start()
client = S3Client(
url="http://your-s3-host",
client=httpx.AsyncClient(),
)
await credentials.stop()
Multipart upload
For uploading large files multipart uploading can be used. It allows you to asynchronously upload multiple parts of a file to S3. S3Client handles retries of part uploads and calculates part hash for integrity checks.
import httpx
from httpx_s3_client import S3Client
client = S3Client(url="http://your-s3-host", client=httpx.AsyncClient())
await client.put_file_multipart(
"test/bigfile.csv",
headers={
"Content-Type": "text/csv",
},
workers_count=8,
)
Parallel download to file
S3 supports GET
requests with Range
header. It's possible to download
objects in parallel with multiple connections for speedup.
S3Client handles retries of partial requests and makes sure that file won't
be changed during download with ETag
header.
If your system supports pwrite
syscall (Linux, macOS, etc.) it will be used to
write simultaneously to a single file. Otherwise, each worker will have own file
which will be concatenated after downloading.
import httpx
from httpx_s3_client import S3Client
client = S3Client(url="http://your-s3-host", client=httpx.AsyncClient())
await client.get_file_parallel(
"dump/bigfile.csv",
"/home/user/bigfile.csv",
workers_count=8,
)
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