S3Fs — S3Fs 2023.12.2+1.g34a3219.dirty documentation (2024)

Examples

Simple locate and read a file:

>>> import s3fs>>> s3 = s3fs.S3FileSystem(anon=True)>>> s3.ls('my-bucket')['my-file.txt']>>> with s3.open('my-bucket/my-file.txt', 'rb') as f:...  print(f.read())b'Hello, world'

(see also walk and glob)

Reading with delimited blocks:

>>> s3.read_block(path, offset=1000, length=10, delimiter=b'\n')b'A whole line of text\n'

Writing with blocked caching:

>>> s3 = s3fs.S3FileSystem(anon=False) # uses default credentials>>> with s3.open('mybucket/new-file', 'wb') as f:...  f.write(2*2**20 * b'a')...  f.write(2*2**20 * b'a') # data is flushed and file closed>>> s3.du('mybucket/new-file'){'mybucket/new-file': 4194304}

Because S3Fs faithfully copies the Python file interface it can be usedsmoothly with other projects that consume the file interface like gzip orpandas.

>>> with s3.open('mybucket/my-file.csv.gz', 'rb') as f:...  g = gzip.GzipFile(fileobj=f) # Decompress data with gzip...  df = pd.read_csv(g) # Read CSV file with Pandas

Integration

The libraries intake, pandas and dask accept URLs with the prefix“s3://”, and will use s3fs to complete the IO operation in question. TheIO functions take an argument storage_options, which will be passedto S3FileSystem, for example:

df = pd.read_excel("s3://bucket/path/file.xls", storage_options={"anon": True})

This gives the chance to pass any credentials or other necessaryarguments needed to s3fs.

Async

s3fs is implemented using aiobotocore, and offers async functionality.A number of methods of S3FileSystem are async, for for each of these,there is also a synchronous version with the same name and lack of a _prefix.

If you wish to call s3fs from async code, then you should passasynchronous=True, loop= to the constructor (the latter is optional,if you wish to use both async and sync methods). You must also explicitlyawait the client creation before making any S3 call.

async def run_program(): s3 = S3FileSystem(..., asynchronous=True) session = await s3.set_session() ... # perform work await session.close()asyncio.run(run_program()) # or call from your async code

Concurrent async operations are also used internally for bulk operationssuch as pipe/cat, get/put, cp/mv/rm. The async calls arehidden behind a synchronisation layer, so are designed to be calledfrom normal code. If you are notusing async-style programming, you do not need to know about how thisworks, but you might find the implementation interesting.

Multiprocessing

When using Python’s multiprocessing, the start method must be set to eitherspawn or forkserver. fork is not safe to use because of the open socketsand async thread used by s3fs, and may lead tohard-to-find bugs and occasional deadlocks. Read more about the availablestart methods.

Limitations

This project is meant for convenience, rather than feature completeness.The following are known current omissions:

• file access is always binary (although readline and iterating by lineare possible)

• no permissions/access-control (i.e., no chmod/chown methods)

Logging

The logger named s3fs provides information about the operations of the filesystem. To quickly see all messages, you can set the environment variableS3FS_LOGGING_LEVEL=DEBUG. The presence of this environment variable willinstall a handler for the logger that prints messages to stderr and set the loglevel to the given value. More advance logging configuration is possible usingPython’s standard logging framework.

Credentials

The AWS key and secret may be provided explicitly when creating an S3FileSystem.A more secure way, not including the credentials directly in code, is to allowboto to establish the credentials automatically. Boto will try the followingmethods, in order:

• AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, and AWS_SESSION_TOKENenvironment variables

• configuration files such as ~/.aws/credentials

• for nodes on EC2, the IAM metadata provider

You can specify a profile using s3fs.S3FileSystem(profile='PROFILE').Otherwise sf3s will use authentication via boto environment variables.

In a distributed environment, it is not expected that raw credentials shouldbe passed between machines. In the explicitly provided credentials case, themethod S3FileSystem.get_delegated_s3pars() can be used to obtain temporary credentials.When not using explicit credentials, it should be expected that every machinealso has the appropriate environment variables, config files or IAM rolesavailable.

If none of the credential methods are available, only anonymous access willwork, and anon=True must be passed to the constructor.

Furthermore, S3FileSystem.current() will return the most-recently createdinstance, so this method could be used in preference to the constructor incases where the code must be agnostic of the credentials/config used.

S3 Compatible Storage

To use s3fs against an S3 compatible storage, like MinIO orCeph Object Gateway, you’ll probably need to pass extra parameters whencreating the s3fs filesystem. Here are some sample configurations:

For a self-hosted MinIO instance:

# When relying on auto discovery for credentials>>> s3 = s3fs.S3FileSystem( anon=False, endpoint_url='https://...' )# Or passing the credentials directly>>> s3 = s3fs.S3FileSystem( key='miniokey...', secret='asecretkey...', endpoint_url='https://...' )

It is also possible to set credentials through environment variables:

# export FSSPEC_S3_ENDPOINT_URL=https://...# export FSSPEC_S3_KEY='miniokey...'# export FSSPEC_S3_SECRET='asecretkey...'>>> s3 = s3fs.S3FileSystem()# or ...>>> f = fsspec.open("s3://minio-bucket/...")

For Storj DCS via the S3-compatible Gateway:

# When relying on auto discovery for credentials>>> s3 = s3fs.S3FileSystem( anon=False, endpoint_url='https://gateway.storjshare.io' )# Or passing the credentials directly>>> s3 = s3fs.S3FileSystem( key='accesskey...', secret='asecretkey...', endpoint_url='https://gateway.storjshare.io' )

For a Scaleway s3-compatible storage in the fr-par zone:

>>> s3 = s3fs.S3FileSystem( key='scaleway-api-key...', secret='scaleway-secretkey...', endpoint_url='https://s3.fr-par.scw.cloud', client_kwargs={ 'region_name': 'fr-par' })

For an OVH s3-compatible storage in the GRA zone:

>>> s3 = s3fs.S3FileSystem( key='ovh-s3-key...', secret='ovh-s3-secretkey...', endpoint_url='https://s3.GRA.cloud.ovh.net', client_kwargs={ 'region_name': 'GRA' }, config_kwargs={ 'signature_version': 's3v4' })

Requester Pays Buckets

Some buckets, such as the arXiv raw data, are configured so that therequester of the data pays any transfer fees. You must beauthenticated to access these buckets and (because these charges maybeunexpected) amazon requires an additional key on many of the APIcalls. To enable RequesterPays create your file system as

>>> s3 = s3fs.S3FileSystem(anon=False, requester_pays=True)

Serverside Encryption

For some buckets/files you may want to use some of s3’s server side encryptionfeatures. s3fs supports these in a few ways

>>> s3 = s3fs.S3FileSystem(...  s3_additional_kwargs={'ServerSideEncryption': 'AES256'})

This will create an s3 filesystem instance that will append theServerSideEncryption argument to all s3 calls (where applicable).

The same applies for s3.open. Most of the methods on the filesystem objectwill also accept and forward keyword arguments to the underlying calls. Themost recently specified argument is applied last in the case where boths3_additional_kwargs and a method’s **kwargs are used.

The s3.utils.SSEParams provides some convenient helpers for the serversideencryption parameters in particular. An instance can be passed instead of aregular python dictionary as the s3_additional_kwargs parameter.

Bucket Version Awareness

If your bucket has object versioning enabled then you can add version-aware supportto s3fs. This ensures that if a file is opened at a particular point in time thatversion will be used for reading.

This mitigates the issue where more than one user is concurrently reading and writingto the same object.

>>> s3 = s3fs.S3FileSystem(version_aware=True)# Open the file at the latest version>>> fo = s3.open('versioned_bucket/object')>>> versions = s3.object_version_info('versioned_bucket/object')# Open the file at a particular version>>> fo_old_version = s3.open('versioned_bucket/object', version_id='SOMEVERSIONID')

In order for this to function the user must have the necessary IAM permissions to performa GetObjectVersion

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