def __init__(
self,
filepath: str,
load_args: Dict[str, Any] = None,
save_args: Dict[str, Any] = None,
version: Version = None,
credentials: Dict[str, Any] = None,
fs_args: Dict[str, Any] = None,
) -> None:
"""Creates a new instance of ``TensorFlowModelDataset``.
Args:
filepath: Filepath to a TensorFlow model directory prefixed with a protocol
like `s3://`. If prefix is not provided `file` protocol (local filesystem)
will be used. The prefix should be any protocol supported by ``fsspec``.
Note: `http(s)` doesn't support versioning.
load_args: TensorFlow options for loading models.
Here you can find all available arguments:
https://www.tensorflow.org/api_docs/python/tf/keras/models/load_model
All defaults are preserved.
save_args: TensorFlow options for saving models.
Here you can find all available arguments:
https://www.tensorflow.org/api_docs/python/tf/keras/models/save_model
All defaults are preserved, except for "save_format", which is set to "tf".
version: If specified, should be an instance of
``kedro.io.core.Version``. If its ``load`` attribute is
None, the latest version will be loaded. If its ``save``
attribute is None, save version will be autogenerated.
credentials: Credentials required to get access to the underlying filesystem.
E.g. for ``GCSFileSystem`` it should look like `{'token': None}`.
fs_args: Extra arguments to pass into underlying filesystem class constructor
(e.g. `{"project": "my-project"}` for ``GCSFileSystem``).
"""
_fs_args = copy.deepcopy(fs_args) or {}
_credentials = copy.deepcopy(credentials) or {}
protocol, path = get_protocol_and_path(filepath, version)
if protocol == "file":
_fs_args.setdefault("auto_mkdir", True)
self._protocol = protocol
self._fs = fsspec.filesystem(self._protocol, **_credentials,
**_fs_args)
super().__init__(
filepath=PurePosixPath(path),
version=version,
exists_function=self._fs.exists,
glob_function=self._fs.glob,
)
self._tmp_prefix = "kedro_tensorflow_tmp" # temp prefix pattern
# Handle default load and save arguments
self._load_args = copy.deepcopy(self.DEFAULT_LOAD_ARGS)
if load_args is not None:
self._load_args.update(load_args)
self._save_args = copy.deepcopy(self.DEFAULT_SAVE_ARGS)
if save_args is not None:
self._save_args.update(save_args)
if self._save_args.get("save_format") == "h5":
self._tmpfile_callable = tempfile.NamedTemporaryFile # type: Callable
else:
self._tmpfile_callable = tempfile.TemporaryDirectory
def __init__(
self,
filepath: str,
fs_args: Dict[str, Any] = None,
credentials: Dict[str, Any] = None,
save_args: Dict[str, Any] = None,
version: Version = None,
overwrite: bool = False,
) -> None:
"""Creates a new instance of ``MatplotlibWriter``.
Args:
filepath: Filepath in POSIX format to save Matplotlib objects to, prefixed with a
protocol like `s3://`. If prefix is not provided, `file` protocol (local filesystem)
will be used. The prefix should be any protocol supported by ``fsspec``.
fs_args: Extra arguments to pass into underlying filesystem class constructor
(e.g. `{"project": "my-project"}` for ``GCSFileSystem``), as well as
to pass to the filesystem's `open` method through nested key `open_args_save`.
Here you can find all available arguments for `open`:
https://filesystem-spec.readthedocs.io/en/latest/api.html#fsspec.spec.AbstractFileSystem.open
All defaults are preserved, except `mode`, which is set to `wb` when saving.
credentials: Credentials required to get access to the underlying filesystem.
E.g. for ``S3FileSystem`` it should look like:
`{'key': '<id>', 'secret': '<key>'}}`
save_args: Save args passed to `plt.savefig`. See
https://matplotlib.org/api/_as_gen/matplotlib.pyplot.savefig.html
version: If specified, should be an instance of
``kedro.io.core.Version``. If its ``load`` attribute is
None, the latest version will be loaded. If its ``save``
attribute is None, save version will be autogenerated.
overwrite: If True, any existing image files will be removed.
Only relevant when saving multiple Matplotlib objects at
once.
"""
_credentials = deepcopy(credentials) or {}
_fs_args = deepcopy(fs_args) or {}
_fs_open_args_save = _fs_args.pop("open_args_save", {})
_fs_open_args_save.setdefault("mode", "wb")
protocol, path = get_protocol_and_path(filepath, version)
if protocol == "file":
_fs_args.setdefault("auto_mkdir", True)
self._protocol = protocol
self._fs = fsspec.filesystem(self._protocol, **_credentials,
**_fs_args)
super().__init__(
filepath=PurePosixPath(path),
version=version,
exists_function=self._fs.exists,
glob_function=self._fs.glob,
)
self._fs_open_args_save = _fs_open_args_save
# Handle default save arguments
self._save_args = deepcopy(self.DEFAULT_SAVE_ARGS)
if save_args is not None:
self._save_args.update(save_args)
if overwrite and version is not None:
warn("Setting `overwrite=True` is ineffective if versioning "
"is enabled, since the versioned path must not already "
"exist; overriding flag with `overwrite=False` instead.")
overwrite = False
self._overwrite = overwrite
def __init__(
self,
filepath: str,
load_args: Dict[str, Any] = None,
save_args: Dict[str, Any] = None,
version: Version = None,
credentials: Dict[str, Any] = None,
fs_args: Dict[str, Any] = None,
) -> None:
"""Creates a new instance of ``NetworkXDataSet``.
Args:
filepath: Filepath in POSIX format to the NetworkX graph JSON file.
load_args: Arguments passed on to ```networkx.node_link_graph``.
See the details in
https://networkx.github.io/documentation/networkx-1.9.1/reference/generated/networkx.readwrite.json_graph.node_link_graph.html
save_args: Arguments passed on to ```networkx.node_link_data``.
See the details in
https://networkx.github.io/documentation/networkx-1.9.1/reference/generated/networkx.readwrite.json_graph.node_link_data.html
version: If specified, should be an instance of
``kedro.io.core.Version``. If its ``load`` attribute is
None, the latest version will be loaded. If its ``save``
attribute is None, save version will be autogenerated.
credentials: Credentials required to get access to the underlying filesystem.
E.g. for ``GCSFileSystem`` it should look like `{"token": None}`.
fs_args: Extra arguments to pass into underlying filesystem class constructor
(e.g. `{"project": "my-project"}` for ``GCSFileSystem``), as well as
to pass to the filesystem's `open` method through nested keys
`open_args_load` and `open_args_save`.
Here you can find all available arguments for `open`:
https://filesystem-spec.readthedocs.io/en/latest/api.html#fsspec.spec.AbstractFileSystem.open
All defaults are preserved, except `mode`, which is set to `r` when loading
and to `w` when saving.
"""
_fs_args = deepcopy(fs_args) or {}
_fs_open_args_load = _fs_args.pop("open_args_load", {})
_fs_open_args_save = _fs_args.pop("open_args_save", {})
_credentials = deepcopy(credentials) or {}
protocol, path = get_protocol_and_path(filepath, version)
if protocol == "file":
_fs_args.setdefault("auto_mkdir", True)
self._protocol = protocol
self._fs = fsspec.filesystem(self._protocol, **_credentials,
**_fs_args)
super().__init__(
filepath=PurePosixPath(path),
version=version,
exists_function=self._fs.exists,
glob_function=self._fs.glob,
)
# Handle default load and save arguments
self._load_args = deepcopy(self.DEFAULT_LOAD_ARGS)
if load_args is not None:
self._load_args.update(load_args)
self._save_args = deepcopy(self.DEFAULT_SAVE_ARGS)
if save_args is not None:
self._save_args.update(save_args)
_fs_open_args_save.setdefault("mode", "w")
self._fs_open_args_load = _fs_open_args_load
self._fs_open_args_save = _fs_open_args_save
def __init__(
self,
filepath: str,
load_args: Dict[str, Any] = None,
save_args: Dict[str, Any] = None,
version: Version = None,
credentials: Dict[str, Any] = None,
fs_args: Dict[str, Any] = None,
) -> None:
"""Creates a new instance of ``EmailMessageDataSet`` pointing to a concrete text file
on a specific filesystem.
Args:
filepath: Filepath in POSIX format to a text file prefixed with a protocol like `s3://`.
If prefix is not provided, `file` protocol (local filesystem) will be used.
The prefix should be any protocol supported by ``fsspec``.
Note: `http(s)` doesn't support versioning.
load_args: ``email`` options for parsing email messages (arguments passed
into ``email.parser.Parser.parse``). Here you can find all available arguments:
https://docs.python.org/3/library/email.parser.html#email.parser.Parser.parse
If you would like to specify options for the `Parser`,
you can include them under the "parser" key. Here you can
find all available arguments:
https://docs.python.org/3/library/email.parser.html#email.parser.Parser
All defaults are preserved, but "policy", which is set to ``email.policy.default``.
save_args: ``email`` options for generating MIME documents (arguments passed into
``email.generator.Generator.flatten``). Here you can find all available arguments:
https://docs.python.org/3/library/email.generator.html#email.generator.Generator.flatten
If you would like to specify options for the `Generator`,
you can include them under the "generator" key. Here you can
find all available arguments:
https://docs.python.org/3/library/email.generator.html#email.generator.Generator
All defaults are preserved.
version: If specified, should be an instance of
``kedro.io.core.Version``. If its ``load`` attribute is
None, the latest version will be loaded. If its ``save``
attribute is None, save version will be autogenerated.
credentials: Credentials required to get access to the underlying filesystem.
E.g. for ``GCSFileSystem`` it should look like `{"token": None}`.
fs_args: Extra arguments to pass into underlying filesystem class constructor
(e.g. `{"project": "my-project"}` for ``GCSFileSystem``), as well as
to pass to the filesystem's `open` method through nested keys
`open_args_load` and `open_args_save`.
Here you can find all available arguments for `open`:
https://filesystem-spec.readthedocs.io/en/latest/api.html#fsspec.spec.AbstractFileSystem.open
All defaults are preserved, except `mode`, which is set to `r` when loading
and to `w` when saving.
"""
_fs_args = deepcopy(fs_args) or {}
_fs_open_args_load = _fs_args.pop("open_args_load", {})
_fs_open_args_save = _fs_args.pop("open_args_save", {})
_credentials = deepcopy(credentials) or {}
protocol, path = get_protocol_and_path(filepath, version)
self._protocol = protocol
if protocol == "file":
_fs_args.setdefault("auto_mkdir", True)
self._fs = fsspec.filesystem(self._protocol, **_credentials,
**_fs_args)
super().__init__(
filepath=PurePosixPath(path),
version=version,
exists_function=self._fs.exists,
glob_function=self._fs.glob,
)
# Handle default load arguments
self._load_args = deepcopy(self.DEFAULT_LOAD_ARGS)
if load_args is not None:
self._load_args.update(load_args)
self._parser_args = self._load_args.pop("parser", {"policy": default})
# Handle default save arguments
self._save_args = deepcopy(self.DEFAULT_SAVE_ARGS)
if save_args is not None:
self._save_args.update(save_args)
self._generator_args = self._save_args.pop("generator", {})
_fs_open_args_load.setdefault("mode", "r")
_fs_open_args_save.setdefault("mode", "w")
self._fs_open_args_load = _fs_open_args_load
self._fs_open_args_save = _fs_open_args_save
def __init__(
self,
filepath: str,
load_args: Dict[str, Any] = None,
save_args: Dict[str, Any] = None,
version: Version = None,
credentials: Dict[str, Any] = None,
fs_args: Dict[str, Any] = None,
) -> None:
"""Creates a new instance of ``ParquetDataSet`` pointing to a concrete Parquet file
on a specific filesystem.
Args:
filepath: Filepath in POSIX format to a Parquet file prefixed with a protocol like
`s3://`. If prefix is not provided, `file` protocol (local filesystem) will be used.
The prefix should be any protocol supported by ``fsspec``.
It can also be a path to a directory. If the directory is
provided then it can be used for reading partitioned parquet files.
Note: `http(s)` doesn't support versioning.
load_args: Additional options for loading Parquet file(s).
Here you can find all available arguments when reading single file:
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_parquet.html
Here you can find all available arguments when reading partitioned datasets:
https://arrow.apache.org/docs/python/generated/pyarrow.parquet.ParquetDataset.html#pyarrow.parquet.ParquetDataset.read
All defaults are preserved.
save_args: Additional saving options for `pyarrow.parquet.write_table` and
`pyarrow.Table.from_pandas`.
Here you can find all available arguments for `write_table()`:
https://arrow.apache.org/docs/python/generated/pyarrow.parquet.write_table.html?highlight=write_table#pyarrow.parquet.write_table
The arguments for `from_pandas()` should be passed through a nested
key: `from_pandas`. E.g.: `save_args = {"from_pandas": {"preserve_index": False}}`
Here you can find all available arguments for `from_pandas()`:
https://arrow.apache.org/docs/python/generated/pyarrow.Table.html#pyarrow.Table.from_pandas
version: If specified, should be an instance of
``kedro.io.core.Version``. If its ``load`` attribute is
None, the latest version will be loaded. If its ``save``
attribute is None, save version will be autogenerated.
credentials: Credentials required to get access to the underlying filesystem.
E.g. for ``GCSFileSystem`` it should look like `{"token": None}`.
fs_args: Extra arguments to pass into underlying filesystem class constructor
(e.g. `{"project": "my-project"}` for ``GCSFileSystem``), as well as
to pass to the filesystem's `open` method through nested keys
`open_args_load` and `open_args_save`.
Here you can find all available arguments for `open`:
https://filesystem-spec.readthedocs.io/en/latest/api.html#fsspec.spec.AbstractFileSystem.open
All defaults are preserved.
"""
_fs_args = deepcopy(fs_args) or {}
self._fs_open_args_load = _fs_args.pop("open_args_load", {})
_credentials = deepcopy(credentials) or {}
protocol, path = get_protocol_and_path(filepath, version)
if protocol == "file":
_fs_args.setdefault("auto_mkdir", True)
self._protocol = protocol
self._fs = fsspec.filesystem(self._protocol, **_credentials,
**_fs_args)
super().__init__(
filepath=PurePosixPath(path),
version=version,
exists_function=self._fs.exists,
glob_function=self._fs.glob,
)
self._from_pandas_args = {} # type: Dict[str, Any]
# Handle default load and save arguments
self._load_args = deepcopy(self.DEFAULT_LOAD_ARGS)
if load_args is not None:
self._load_args.update(load_args)
self._save_args = deepcopy(self.DEFAULT_SAVE_ARGS)
if save_args is not None:
self._from_pandas_args.update(save_args.pop("from_pandas", {}))
self._save_args.update(save_args)
def __init__(
self,
filepath: str,
backend: str = "pickle",
load_args: Dict[str, Any] = None,
save_args: Dict[str, Any] = None,
version: Version = None,
credentials: Dict[str, Any] = None,
fs_args: Dict[str, Any] = None,
) -> None:
"""Creates a new instance of ``PickleDataSet`` pointing to a concrete Pickle
file on a specific filesystem. ``PickleDataSet`` supports two backends to
serialize/deserialize objects: `pickle` and `joblib`.
Args:
filepath: Filepath to a Pickle file prefixed with a protocol like `s3://`.
If prefix is not provided, `file` protocol (local filesystem) will be used.
The prefix should be any protocol supported by ``fsspec``.
Note: `http(s)` doesn't support versioning.
backend: Backend to use, must be one of ['pickle', 'joblib']. Defaults to 'pickle'.
load_args: Pickle options for loading pickle files.
Here you can find all available arguments for different backends:
pickle.load: https://docs.python.org/3/library/pickle.html#pickle.load
joblib.load: https://joblib.readthedocs.io/en/latest/generated/joblib.load.html
All defaults are preserved.
save_args: Pickle options for saving pickle files.
Here you can find all available arguments for different backends:
pickle.dump: https://docs.python.org/3/library/pickle.html#pickle.dump
joblib.dump: https://joblib.readthedocs.io/en/latest/generated/joblib.dump.html
All defaults are preserved.
version: If specified, should be an instance of
``kedro.io.core.Version``. If its ``load`` attribute is
None, the latest version will be loaded. If its ``save``
attribute is None, save version will be autogenerated.
credentials: Credentials required to get access to the underlying filesystem.
E.g. for ``GCSFileSystem`` it should look like `{"token": None}`.
fs_args: Extra arguments to pass into underlying filesystem class constructor
(e.g. `{"project": "my-project"}` for ``GCSFileSystem``), as well as
to pass to the filesystem's `open` method through nested keys
`open_args_load` and `open_args_save`.
Here you can find all available arguments for `open`:
https://filesystem-spec.readthedocs.io/en/latest/api.html#fsspec.spec.AbstractFileSystem.open
All defaults are preserved, except `mode`, which is set to `wb` when saving.
Raises:
ValueError: If ``backend`` is not one of ['pickle', 'joblib'].
ImportError: If ``backend`` library could not be imported.
"""
if backend not in self.BACKENDS:
raise ValueError(
"'backend' should be one of {}, got '{}'.".format(
list(self.BACKENDS.keys()), backend
)
)
if not self.BACKENDS[backend]:
raise ImportError(
"Selected backend '{}' could not be "
"imported. Make sure it is installed.".format(backend)
)
_fs_args = deepcopy(fs_args) or {}
_fs_open_args_load = _fs_args.pop("open_args_load", {})
_fs_open_args_save = _fs_args.pop("open_args_save", {})
_credentials = deepcopy(credentials) or {}
protocol, path = get_protocol_and_path(filepath, version)
self._protocol = protocol
self._fs = fsspec.filesystem(self._protocol, **_credentials, **_fs_args)
super().__init__(
filepath=PurePosixPath(path),
version=version,
exists_function=self._fs.exists,
glob_function=self._fs.glob,
)
self._backend = backend
# Handle default load and save arguments
self._load_args = deepcopy(self.DEFAULT_LOAD_ARGS)
if load_args is not None:
self._load_args.update(load_args)
self._save_args = deepcopy(self.DEFAULT_SAVE_ARGS)
if save_args is not None:
self._save_args.update(save_args)
_fs_open_args_save.setdefault("mode", "wb")
self._fs_open_args_load = _fs_open_args_load
self._fs_open_args_save = _fs_open_args_save
def __init__(
self,
sql: str = None,
project: str = None,
credentials: Union[Dict[str, Any], Credentials] = None,
load_args: Dict[str, Any] = None,
fs_args: Dict[str, Any] = None,
filepath: str = None,
) -> None:
"""Creates a new instance of ``GBQQueryDataSet``.
Args:
sql: The sql query statement.
project: Google BigQuery Account project ID.
Optional when available from the environment.
https://cloud.google.com/resource-manager/docs/creating-managing-projects
credentials: Credentials for accessing Google APIs.
Either ``google.auth.credentials.Credentials`` object or dictionary with
parameters required to instantiate ``google.oauth2.credentials.Credentials``.
Here you can find all the arguments:
https://google-auth.readthedocs.io/en/latest/reference/google.oauth2.credentials.html
load_args: Pandas options for loading BigQuery table into DataFrame.
Here you can find all available arguments:
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_gbq.html
All defaults are preserved.
fs_args: Extra arguments to pass into underlying filesystem class constructor
(e.g. `{"project": "my-project"}` for ``GCSFileSystem``) used for reading the
SQL query from filepath.
filepath: A path to a file with a sql query statement.
Raises:
DataSetError: When ``sql`` and ``filepath`` parameters are either both empty
or both provided, as well as when the `save()` method is invoked.
"""
if sql and filepath:
raise DataSetError(
"`sql` and `filepath` arguments cannot both be provided."
"Please only provide one.")
if not (sql or filepath):
raise DataSetError(
"`sql` and `filepath` arguments cannot both be empty."
"Please provide a sql query or path to a sql query file.")
# Handle default load arguments
self._load_args = copy.deepcopy(self.DEFAULT_LOAD_ARGS)
if load_args is not None:
self._load_args.update(load_args)
self._project_id = project
if isinstance(credentials, dict):
credentials = Credentials(**credentials)
self._credentials = credentials
self._client = bigquery.Client(
project=self._project_id,
credentials=self._credentials,
location=self._load_args.get("location"),
)
# load sql query from arg or from file
if sql:
self._load_args["query"] = sql
self._filepath = None
else:
# filesystem for loading sql file
_fs_args = copy.deepcopy(fs_args) or {}
_fs_credentials = _fs_args.pop("credentials", {})
protocol, path = get_protocol_and_path(str(filepath))
self._protocol = protocol
self._fs = fsspec.filesystem(self._protocol, **_fs_credentials,
**_fs_args)
self._filepath = path
def __init__(
self,
filepath: str,
backend: str = "pickle",
load_args: Dict[str, Any] = None,
save_args: Dict[str, Any] = None,
version: Version = None,
credentials: Dict[str, Any] = None,
fs_args: Dict[str, Any] = None,
) -> None:
"""Creates a new instance of ``PickleDataSet`` pointing to a concrete Pickle
file on a specific filesystem. ``PickleDataSet`` supports custom backends to
serialize/deserialize objects.
Example backends that are compatible (non-exhaustive):
* `pickle`
* `joblib`
* `dill`
* `compress_pickle`
Example backends that are incompatible:
* `torch`
Args:
filepath: Filepath in POSIX format to a Pickle file prefixed with a protocol like
`s3://`. If prefix is not provided, `file` protocol (local filesystem) will be used.
The prefix should be any protocol supported by ``fsspec``.
Note: `http(s)` doesn't support versioning.
backend: Backend to use, must be an import path to a module which satisfies the
``pickle`` interface. That is, contains a `load` and `dump` function.
Defaults to 'pickle'.
load_args: Pickle options for loading pickle files.
You can pass in arguments that the backend load function specified accepts, e.g:
pickle.load: https://docs.python.org/3/library/pickle.html#pickle.load
joblib.load: https://joblib.readthedocs.io/en/latest/generated/joblib.load.html
dill.load: https://dill.readthedocs.io/en/latest/dill.html#dill._dill.load
compress_pickle.load:
https://lucianopaz.github.io/compress_pickle/html/api/compress_pickle.html#compress_pickle.compress_pickle.load
All defaults are preserved.
save_args: Pickle options for saving pickle files.
You can pass in arguments that the backend dump function specified accepts, e.g:
pickle.dump: https://docs.python.org/3/library/pickle.html#pickle.dump
joblib.dump: https://joblib.readthedocs.io/en/latest/generated/joblib.dump.html
dill.dump: https://dill.readthedocs.io/en/latest/dill.html#dill._dill.dump
compress_pickle.dump:
https://lucianopaz.github.io/compress_pickle/html/api/compress_pickle.html#compress_pickle.compress_pickle.dump
All defaults are preserved.
version: If specified, should be an instance of
``kedro.io.core.Version``. If its ``load`` attribute is
None, the latest version will be loaded. If its ``save``
attribute is None, save version will be autogenerated.
credentials: Credentials required to get access to the underlying filesystem.
E.g. for ``GCSFileSystem`` it should look like `{"token": None}`.
fs_args: Extra arguments to pass into underlying filesystem class constructor
(e.g. `{"project": "my-project"}` for ``GCSFileSystem``), as well as
to pass to the filesystem's `open` method through nested keys
`open_args_load` and `open_args_save`.
Here you can find all available arguments for `open`:
https://filesystem-spec.readthedocs.io/en/latest/api.html#fsspec.spec.AbstractFileSystem.open
All defaults are preserved, except `mode`, which is set to `wb` when saving.
Raises:
ValueError: If ``backend`` does not satisfy the `pickle` interface.
ImportError: If the ``backend`` module could not be imported.
"""
# We do not store `imported_backend` as an attribute to be used in `load`/`save`
# as this would mean the dataset cannot be deepcopied (module objects cannot be
# pickled). The import here is purely to raise any errors as early as possible.
# Repeated imports in the `load` and `save` methods should not be a significant
# performance hit as Python caches imports.
try:
imported_backend = importlib.import_module(backend)
except ImportError as exc:
raise ImportError(
f"Selected backend '{backend}' could not be imported. "
"Make sure it is installed and importable.") from exc
if not (hasattr(imported_backend, "load")
and hasattr(imported_backend, "dump")):
raise ValueError(
f"Selected backend '{backend}' should satisfy the pickle interface. "
"Missing one of `load` and `dump` on the backend.")
_fs_args = deepcopy(fs_args) or {}
_fs_open_args_load = _fs_args.pop("open_args_load", {})
_fs_open_args_save = _fs_args.pop("open_args_save", {})
_credentials = deepcopy(credentials) or {}
protocol, path = get_protocol_and_path(filepath, version)
if protocol == "file":
_fs_args.setdefault("auto_mkdir", True)
self._protocol = protocol
self._fs = fsspec.filesystem(self._protocol, **_credentials,
**_fs_args)
super().__init__(
filepath=PurePosixPath(path),
version=version,
exists_function=self._fs.exists,
glob_function=self._fs.glob,
)
self._backend = backend
# Handle default load and save arguments
self._load_args = deepcopy(self.DEFAULT_LOAD_ARGS)
if load_args is not None:
self._load_args.update(load_args)
self._save_args = deepcopy(self.DEFAULT_SAVE_ARGS)
if save_args is not None:
self._save_args.update(save_args)
_fs_open_args_save.setdefault("mode", "wb")
self._fs_open_args_load = _fs_open_args_load
self._fs_open_args_save = _fs_open_args_save
def __init__(
self,
filepath: str,
load_args: Dict[str, Any] = None,
save_args: Dict[str, Any] = None,
version: Version = None,
credentials: Dict[str, Any] = None,
fs_args: Dict[str, Any] = None,
) -> None:
"""Creates a new instance of ``GeoJSONDataSet`` pointing to a concrete GeoJSON file
on a specific filesystem fsspec.
Args:
filepath: Filepath in POSIX format to a GeoJSON file prefixed with a protocol like
`s3://`. If prefix is not provided `file` protocol (local filesystem) will be used.
The prefix should be any protocol supported by ``fsspec``.
Note: `http(s)` doesn't support versioning.
load_args: GeoPandas options for loading GeoJSON files.
Here you can find all available arguments:
https://geopandas.org/en/stable/docs/reference/api/geopandas.read_file.html
save_args: GeoPandas options for saving geojson files.
Here you can find all available arguments:
https://geopandas.org/en/stable/docs/reference/api/geopandas.GeoDataFrame.to_file.html
The default_save_arg driver is 'GeoJSON', all others preserved.
version: If specified, should be an instance of
``kedro.io.core.Version``. If its ``load`` attribute is
None, the latest version will be loaded. If its ``save``
credentials: credentials required to access the underlying filesystem.
Eg. for ``GCFileSystem`` it would look like `{'token': None}`.
fs_args: Extra arguments to pass into underlying filesystem class constructor
(e.g. `{"project": "my-project"}` for ``GCSFileSystem``), as well as
to pass to the filesystem's `open` method through nested keys
`open_args_load` and `open_args_save`.
Here you can find all available arguments for `open`:
https://filesystem-spec.readthedocs.io/en/latest/api.html#fsspec.spec.AbstractFileSystem.open
All defaults are preserved, except `mode`, which is set to `wb` when saving.
"""
_fs_args = copy.deepcopy(fs_args) or {}
_fs_open_args_load = _fs_args.pop("open_args_load", {})
_fs_open_args_save = _fs_args.pop("open_args_save", {})
_credentials = copy.deepcopy(credentials) or {}
protocol, path = get_protocol_and_path(filepath, version)
self._protocol = protocol
if protocol == "file":
_fs_args.setdefault("auto_mkdir", True)
self._fs = fsspec.filesystem(self._protocol, **_credentials,
**_fs_args)
super().__init__(
filepath=PurePosixPath(path),
version=version,
exists_function=self._fs.exists,
glob_function=self._fs.glob,
)
self._load_args = copy.deepcopy(self.DEFAULT_LOAD_ARGS)
if load_args is not None:
self._load_args.update(load_args)
self._save_args = copy.deepcopy(self.DEFAULT_SAVE_ARGS)
if save_args is not None:
self._save_args.update(save_args)
_fs_open_args_save.setdefault("mode", "wb")
self._fs_open_args_load = _fs_open_args_load
self._fs_open_args_save = _fs_open_args_save
def __init__(
self,
filepath: str,
key: str,
load_args: Dict[str, Any] = None,
save_args: Dict[str, Any] = None,
version: Version = None,
credentials: Dict[str, Any] = None,
fs_args: Dict[str, Any] = None,
) -> None:
"""Creates a new instance of ``HDFDataSet`` pointing to a concrete hdf file
on a specific filesystem.
Args:
filepath: Filepath in POSIX format to a hdf file prefixed with a protocol like `s3://`.
If prefix is not provided, `file` protocol (local filesystem) will be used.
The prefix should be any protocol supported by ``fsspec``.
Note: `http(s)` doesn't support versioning.
key: Identifier to the group in the HDF store.
load_args: PyTables options for loading hdf files.
You can find all available arguments at:
https://www.pytables.org/usersguide/libref/top_level.html#tables.open_file
All defaults are preserved.
save_args: PyTables options for saving hdf files.
You can find all available arguments at:
https://www.pytables.org/usersguide/libref/top_level.html#tables.open_file
All defaults are preserved.
version: If specified, should be an instance of
``kedro.io.core.Version``. If its ``load`` attribute is
None, the latest version will be loaded. If its ``save``
attribute is None, save version will be autogenerated.
credentials: Credentials required to get access to the underlying filesystem.
E.g. for ``GCSFileSystem`` it should look like `{"token": None}`.
fs_args: Extra arguments to pass into underlying filesystem class constructor
(e.g. `{"project": "my-project"}` for ``GCSFileSystem``), as well as
to pass to the filesystem's `open` method through nested keys
`open_args_load` and `open_args_save`.
Here you can find all available arguments for `open`:
https://filesystem-spec.readthedocs.io/en/latest/api.html#fsspec.spec.AbstractFileSystem.open
All defaults are preserved, except `mode`, which is set `wb` when saving.
"""
_fs_args = deepcopy(fs_args) or {}
_fs_open_args_load = _fs_args.pop("open_args_load", {})
_fs_open_args_save = _fs_args.pop("open_args_save", {})
_credentials = deepcopy(credentials) or {}
protocol, path = get_protocol_and_path(filepath, version)
if protocol == "file":
_fs_args.setdefault("auto_mkdir", True)
self._protocol = protocol
self._fs = fsspec.filesystem(self._protocol, **_credentials,
**_fs_args)
super().__init__(
filepath=PurePosixPath(path),
version=version,
exists_function=self._fs.exists,
glob_function=self._fs.glob,
)
self._key = key
# Handle default load and save arguments
self._load_args = deepcopy(self.DEFAULT_LOAD_ARGS)
if load_args is not None:
self._load_args.update(load_args)
self._save_args = deepcopy(self.DEFAULT_SAVE_ARGS)
if save_args is not None:
self._save_args.update(save_args)
_fs_open_args_save.setdefault("mode", "wb")
self._fs_open_args_load = _fs_open_args_load
self._fs_open_args_save = _fs_open_args_save
def __init__(
self,
filepath: str,
engine: str = "xlsxwriter",
load_args: Dict[str, Any] = None,
save_args: Dict[str, Any] = None,
version: Version = None,
credentials: Dict[str, Any] = None,
fs_args: Dict[str, Any] = None,
) -> None:
"""Creates a new instance of ``ExcelDataSet`` pointing to a concrete Excel file
on a specific filesystem.
Args:
filepath: Filepath in POSIX format to a Excel file prefixed with a protocol like
`s3://`. If prefix is not provided, `file` protocol (local filesystem) will be used.
The prefix should be any protocol supported by ``fsspec``.
Note: `http(s)` doesn't support versioning.
engine: The engine used to write to excel files. The default
engine is 'xlsxwriter'.
load_args: Pandas options for loading Excel files.
Here you can find all available arguments:
https://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_excel.html
All defaults are preserved, but "engine", which is set to "xlrd".
Supports multi-sheet Excel files (include `sheet_name = None` in `load_args`).
save_args: Pandas options for saving Excel files.
Here you can find all available arguments:
https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.to_excel.html
All defaults are preserved, but "index", which is set to False.
If you would like to specify options for the `ExcelWriter`,
you can include them under the "writer" key. Here you can
find all available arguments:
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.ExcelWriter.html
version: If specified, should be an instance of
``kedro.io.core.Version``. If its ``load`` attribute is
None, the latest version will be loaded. If its ``save``
attribute is None, save version will be autogenerated.
credentials: Credentials required to get access to the underlying filesystem.
E.g. for ``GCSFileSystem`` it should look like `{"token": None}`.
fs_args: Extra arguments to pass into underlying filesystem class constructor
(e.g. `{"project": "my-project"}` for ``GCSFileSystem``), as well as
to pass to the filesystem's `open` method through nested keys
`open_args_load` and `open_args_save`.
Here you can find all available arguments for `open`:
https://filesystem-spec.readthedocs.io/en/latest/api.html#fsspec.spec.AbstractFileSystem.open
All defaults are preserved, except `mode`, which is set to `wb` when saving.
"""
_fs_args = deepcopy(fs_args) or {}
_fs_open_args_load = _fs_args.pop("open_args_load", {})
_fs_open_args_save = _fs_args.pop("open_args_save", {})
_credentials = deepcopy(credentials) or {}
protocol, path = get_protocol_and_path(filepath, version)
if protocol == "file":
_fs_args.setdefault("auto_mkdir", True)
self._protocol = protocol
self._fs = fsspec.filesystem(self._protocol, **_credentials,
**_fs_args)
super().__init__(
filepath=PurePosixPath(path),
version=version,
exists_function=self._fs.exists,
glob_function=self._fs.glob,
)
# Handle default load arguments
self._load_args = deepcopy(self.DEFAULT_LOAD_ARGS)
if load_args is not None:
self._load_args.update(load_args)
# Handle default save arguments
self._save_args = deepcopy(self.DEFAULT_SAVE_ARGS)
if save_args is not None:
self._save_args.update(save_args)
self._writer_args = self._save_args.pop("writer", {"engine": engine})
_fs_open_args_save.setdefault("mode", "wb")
self._fs_open_args_load = _fs_open_args_load
self._fs_open_args_save = _fs_open_args_save
def __init__(
self,
filepath: str,
load_args: Dict[str, Any] = None,
save_args: Dict[str, Any] = None,
version: Version = None,
credentials: Dict[str, Any] = None,
fs_args: Dict[str, Any] = None,
layer: str = None,
) -> None:
"""Creates a new instance of ``CSVDataSet`` pointing to a concrete CSV file
on a specific filesystem.
Args:
filepath: Filepath to a CSV file prefixed with a protocol like `s3://`.
If prefix is not provided, `file` protocol (local filesystem) will be used.
The prefix should be any protocol supported by ``fsspec``.
Note: `http(s)` doesn't support versioning.
load_args: Pandas options for loading CSV files.
Here you can find all available arguments:
https://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_csv.html
All defaults are preserved.
save_args: Pandas options for saving CSV files.
Here you can find all available arguments:
https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.to_csv.html
All defaults are preserved, but "index", which is set to False.
version: If specified, should be an instance of
``kedro.io.core.Version``. If its ``load`` attribute is
None, the latest version will be loaded. If its ``save``
attribute is None, save version will be autogenerated.
credentials: Credentials required to get access to the underlying filesystem.
E.g. for ``GCSFileSystem`` it should look like `{"token": None}`.
fs_args: Extra arguments to pass into underlying filesystem class.
E.g. for ``GCSFileSystem`` class: `{"project": "my-project", ...}`.
layer: The data layer according to the data engineering convention:
https://kedro.readthedocs.io/en/stable/06_resources/01_faq.html#what-is-data-engineering-convention
"""
_fs_args = deepcopy(fs_args) or {}
_credentials = deepcopy(credentials) or {}
protocol, path = get_protocol_and_path(filepath, version)
self._protocol = protocol
self._fs = fsspec.filesystem(self._protocol, **_credentials,
**_fs_args)
super().__init__(
filepath=PurePosixPath(path),
version=version,
exists_function=self._fs.exists,
glob_function=self._fs.glob,
)
self._layer = layer
# Handle default load and save arguments
self._load_args = deepcopy(self.DEFAULT_LOAD_ARGS)
if load_args is not None:
self._load_args.update(load_args)
self._save_args = deepcopy(self.DEFAULT_SAVE_ARGS)
if save_args is not None:
self._save_args.update(save_args)
def __init__(
self,
filepath: str,
file_format: str,
load_args: Dict[str, Any] = None,
save_args: Dict[str, Any] = None,
version: Version = None,
credentials: Dict[str, Any] = None,
fs_args: Dict[str, Any] = None,
):
"""Creates a new instance of ``GenericDataSet`` pointing to a concrete data file
on a specific filesystem. The appropriate pandas load/save methods are
dynamically identified by string matching on a best effort basis.
Args:
filepath: Filepath in POSIX format to a file prefixed with a protocol like `s3://`.
If prefix is not provided, `file` protocol (local filesystem) will be used.
The prefix should be any protocol supported by ``fsspec``.
Key assumption: The first argument of either load/save method points to a
filepath/buffer/io type location. There are some read/write targets such
as 'clipboard' or 'records' that will fail since they do not take a
filepath like argument.
file_format: String which is used to match the appropriate load/save method on a best
effort basis. For example if 'csv' is passed in the `pandas.read_csv` and
`pandas.DataFrame.to_csv` will be identified. An error will be raised unless
at least one matching `read_{file_format}` or `to_{file_format}` method is
identified.
load_args: Pandas options for loading files.
Here you can find all available arguments:
https://pandas.pydata.org/pandas-docs/stable/reference/io.html
All defaults are preserved.
save_args: Pandas options for saving files.
Here you can find all available arguments:
https://pandas.pydata.org/pandas-docs/stable/reference/io.html
All defaults are preserved, but "index", which is set to False.
version: If specified, should be an instance of
``kedro.io.core.Version``. If its ``load`` attribute is
None, the latest version will be loaded. If its ``save``
attribute is None, save version will be autogenerated.
credentials: Credentials required to get access to the underlying filesystem.
E.g. for ``GCSFileSystem`` it should look like `{"token": None}`.
fs_args: Extra arguments to pass into underlying filesystem class constructor
(e.g. `{"project": "my-project"}` for ``GCSFileSystem``), as well as
to pass to the filesystem's `open` method through nested keys
`open_args_load` and `open_args_save`.
Here you can find all available arguments for `open`:
https://filesystem-spec.readthedocs.io/en/latest/api.html#fsspec.spec.AbstractFileSystem.open
All defaults are preserved, except `mode`, which is set to `r` when loading
and to `w` when saving.
Raises:
DataSetError: Will be raised if at least less than one appropriate
read or write methods are identified.
"""
self._file_format = file_format.lower()
_fs_args = deepcopy(fs_args) or {}
_fs_open_args_load = _fs_args.pop("open_args_load", {})
_fs_open_args_save = _fs_args.pop("open_args_save", {})
_credentials = deepcopy(credentials) or {}
protocol, path = get_protocol_and_path(filepath)
if protocol == "file":
_fs_args.setdefault("auto_mkdir", True)
self._protocol = protocol
self._fs = fsspec.filesystem(self._protocol, **_credentials,
**_fs_args)
super().__init__(
filepath=PurePosixPath(path),
version=version,
exists_function=self._fs.exists,
glob_function=self._fs.glob,
)
self._load_args = deepcopy(self.DEFAULT_LOAD_ARGS)
if load_args is not None:
self._load_args.update(load_args)
self._save_args = deepcopy(self.DEFAULT_SAVE_ARGS)
if save_args is not None:
self._save_args.update(save_args)
_fs_open_args_save.setdefault("mode", "w")
self._fs_open_args_load = _fs_open_args_load
self._fs_open_args_save = _fs_open_args_save
def _exists(self) -> bool:
protocol = get_protocol_and_path(self._filepath)[0]
file_system = fsspec.filesystem(protocol=protocol, **self.fs_args)
return file_system.exists(self._filepath)
def __init__(self, filepath: str, credentials: Dict[str, Any],
fs_args: Dict[str, Any]):
_, path = get_protocol_and_path(filepath)
self._fs = gcsfs.GCSFileSystem(projec=fs_args["project"],
token=credentials["id_token"])
self._filepath = PurePosixPath(path)
def __init__(
self,
filepath: str,
load_args: Dict[str, Any] = None,
save_args: Dict[str, Any] = None,
version: Version = None,
credentials: Dict[str, Any] = None,
fs_args: Dict[str, Any] = None,
) -> None:
"""Creates a new instance of ``JSONDataSet`` pointing to a concrete JSON file
on a specific filesystem.
Args:
filepath: Filepath to a JSON file prefixed with a protocol like `s3://`.
If prefix is not provided `file` protocol (local filesystem) will be used.
The prefix should be any protocol supported by ``fsspec``.
Note: `http(s)` doesn't support versioning.
load_args: Pandas options for loading JSON files.
Here you can find all available arguments:
https://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_json.html
All defaults are preserved.
save_args: Pandas options for saving JSON files.
Here you can find all available arguments:
https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.to_json.html
All defaults are preserved, but "index", which is set to False.
version: If specified, should be an instance of
``kedro.io.core.Version``. If its ``load`` attribute is
None, the latest version will be loaded. If its ``save``
attribute is None, save version will be autogenerated.
credentials: Credentials required to get access to the underlying filesystem.
E.g. for ``GCSFileSystem`` it should look like `{'token': None}`.
fs_args: Extra arguments to pass into underlying filesystem class constructor
(e.g. `{"project": "my-project"}` for ``GCSFileSystem``), as well as
to pass to the filesystem's `open` method through nested keys
`open_args_load` and `open_args_save`.
Here you can find all available arguments for `open`:
https://filesystem-spec.readthedocs.io/en/latest/api.html#fsspec.spec.AbstractFileSystem.open
All defaults are preserved, except `mode`, which is set to `r` when loading
and to `w` when saving.
"""
_fs_args = deepcopy(fs_args) or {}
_fs_open_args_load = _fs_args.pop("open_args_load", {})
_fs_open_args_save = _fs_args.pop("open_args_save", {})
_credentials = deepcopy(credentials) or {}
protocol, path = get_protocol_and_path(filepath, version)
self._protocol = protocol
self._fs = fsspec.filesystem(self._protocol, **_credentials, **_fs_args)
super().__init__(
filepath=PurePosixPath(path),
version=version,
exists_function=self._fs.exists,
glob_function=self._fs.glob,
)
# Handle default load and save arguments
self._load_args = deepcopy(self.DEFAULT_LOAD_ARGS)
if load_args is not None:
self._load_args.update(load_args)
self._save_args = deepcopy(self.DEFAULT_SAVE_ARGS)
if save_args is not None:
self._save_args.update(save_args)
_fs_open_args_load.setdefault("mode", "r")
_fs_open_args_save.setdefault("mode", "w")
self._fs_open_args_load = _fs_open_args_load
self._fs_open_args_save = _fs_open_args_save
def __init__(self, filepath: str) -> None:
protocol, path = get_protocol_and_path(filepath=filepath)
self._protocol = protocol
self._filepath = PurePath(path)
self._filesystem = fsspec.filesystem(protocol=protocol)
