+gd4ddlZGddejZdS)NceZdZdZdS) S3FileSystema `datasets.filesystems.S3FileSystem` is a subclass of [`s3fs.S3FileSystem`](https://s3fs.readthedocs.io/en/latest/api.html). Users can use this class to access S3 as if it were a file system. It exposes a filesystem-like API (ls, cp, open, etc.) on top of S3 storage. Provide credentials either explicitly (`key=`, `secret=`) or with boto's credential methods. See botocore documentation for more information. If no credentials are available, use `anon=True`. Args: anon (`bool`, default to `False`): Whether to use anonymous connection (public buckets only). If `False`, uses the key/secret given, or boto's credential resolver (client_kwargs, environment, variables, config files, EC2 IAM server, in that order). key (`str`): If not anonymous, use this access key ID, if specified. secret (`str`): If not anonymous, use this secret access key, if specified. token (`str`): If not anonymous, use this security token, if specified. use_ssl (`bool`, defaults to `True`): Whether to use SSL in connections to S3; may be faster without, but insecure. If `use_ssl` is also set in `client_kwargs`, the value set in `client_kwargs` will take priority. s3_additional_kwargs (`dict`): Parameters that are used when calling S3 API methods. Typically used for things like ServerSideEncryption. client_kwargs (`dict`): Parameters for the botocore client. requester_pays (`bool`, defaults to `False`): Whether `RequesterPays` buckets are supported. default_block_size (`int`): If given, the default block size value used for `open()`, if no specific value is given at all time. The built-in default is 5MB. default_fill_cache (`bool`, defaults to `True`): Whether to use cache filling with open by default. Refer to `S3File.open`. default_cache_type (`str`, defaults to `bytes`): If given, the default `cache_type` value used for `open()`. Set to `none` if no caching is desired. See fsspec's documentation for other available `cache_type` values. version_aware (`bool`, defaults to `False`): Whether to support bucket versioning. If enable this will require the user to have the necessary IAM permissions for dealing with versioned objects. cache_regions (`bool`, defaults to `False`): Whether to cache bucket regions. Whenever a new bucket is used, it will first find out which region it belongs to and then use the client for that region. asynchronous (`bool`, defaults to `False`): Whether this instance is to be used from inside coroutines. config_kwargs (`dict`): Parameters passed to `botocore.client.Config`. **kwargs: Other parameters for core session. session (`aiobotocore.session.AioSession`): Session to be used for all connections. This session will be used inplace of creating a new session inside S3FileSystem. For example: `aiobotocore.session.AioSession(profile='test_user')`. skip_instance_cache (`bool`): Control reuse of instances. Passed on to `fsspec`. use_listings_cache (`bool`): Control reuse of directory listings. Passed on to `fsspec`. listings_expiry_time (`int` or `float`): Control reuse of directory listings. Passed on to `fsspec`. max_paths (`int`): Control reuse of directory listings. Passed on to `fsspec`. Examples: Listing files from public S3 bucket. ```py >>> import datasets >>> s3 = datasets.filesystems.S3FileSystem(anon=True) # doctest: +SKIP >>> s3.ls('public-datasets/imdb/train') # doctest: +SKIP ['dataset_info.json.json','dataset.arrow','state.json'] ``` Listing files from private S3 bucket using `aws_access_key_id` and `aws_secret_access_key`. ```py >>> import datasets >>> s3 = datasets.filesystems.S3FileSystem(key=aws_access_key_id, secret=aws_secret_access_key) # doctest: +SKIP >>> s3.ls('my-private-datasets/imdb/train') # doctest: +SKIP ['dataset_info.json.json','dataset.arrow','state.json'] ``` Using `S3Filesystem` with `botocore.session.Session` and custom `aws_profile`. ```py >>> import botocore >>> from datasets.filesystems import S3Filesystem >>> s3_session = botocore.session.Session(profile_name='my_profile_name') >>> s3 = S3FileSystem(session=s3_session) # doctest: +SKIP ``` Loading dataset from S3 using `S3Filesystem` and [`load_from_disk`]. ```py >>> from datasets import load_from_disk >>> from datasets.filesystems import S3Filesystem >>> s3 = S3FileSystem(key=aws_access_key_id, secret=aws_secret_access_key) # doctest: +SKIP >>> dataset = load_from_disk('s3://my-private-datasets/imdb/train', storage_options=s3.storage_options) # doctest: +SKIP >>> print(len(dataset)) 25000 ``` Saving dataset to S3 using `S3Filesystem` and [`Dataset.save_to_disk`]. ```py >>> from datasets import load_dataset >>> from datasets.filesystems import S3Filesystem >>> dataset = load_dataset("imdb") >>> s3 = S3FileSystem(key=aws_access_key_id, secret=aws_secret_access_key) # doctest: +SKIP >>> dataset.save_to_disk('s3://my-private-datasets/imdb/train', storage_options=s3.storage_options) # doctest: +SKIP ``` N)__name__ __module__ __qualname____doc__Alib/python3.11/site-packages/datasets/filesystems/s3filesystem.pyrrs"llllr r)s3fsrr r r r sO mmmmm4$mmmmmr