kedro.extras.datasets.pickle.PickleDataSet¶
- class kedro.extras.datasets.pickle.PickleDataSet(filepath, backend='pickle', load_args=None, save_args=None, version=None, credentials=None, fs_args=None)[source]¶
PickleDataSet
loads/saves data from/to a Pickle file using an underlying filesystem (e.g.: local, S3, GCS). The underlying functionality is supported by the specified backend library passed in (defaults to thepickle
library), so it supports all allowed options for loading and saving pickle files.Example usage for the YAML API:
test_model: # simple example without compression type: pickle.PickleDataSet filepath: data/07_model_output/test_model.pkl backend: pickle final_model: # example with load and save args type: pickle.PickleDataSet filepath: s3://your_bucket/final_model.pkl.lz4 backend: joblib credentials: s3_credentials save_args: compress: lz4
Example usage for the Python API:
from kedro.extras.datasets.pickle import PickleDataSet import pandas as pd data = pd.DataFrame({'col1': [1, 2], 'col2': [4, 5], 'col3': [5, 6]}) data_set = PickleDataSet(filepath="test.pkl", backend="pickle") data_set.save(data) reloaded = data_set.load() assert data.equals(reloaded) data_set = PickleDataSet(filepath="test.pickle.lz4", backend="compress_pickle", load_args={"compression":"lz4"}, save_args={"compression":"lz4"}) data_set.save(data) reloaded = data_set.load() assert data.equals(reloaded)
Attributes
Methods
exists
()Checks whether a data set's output already exists by calling the provided _exists() method.
from_config
(name, config[, load_version, ...])Create a data set instance using the configuration provided.
load
()Loads data by delegation to the provided load method.
release
()Release any cached data.
Compute the version the dataset should be loaded with.
Compute the version the dataset should be saved with.
save
(data)Saves data by delegation to the provided save method.
- DEFAULT_LOAD_ARGS: Dict[str, Any] = {}¶
- DEFAULT_SAVE_ARGS: Dict[str, Any] = {}¶
- __init__(filepath, backend='pickle', load_args=None, save_args=None, version=None, credentials=None, fs_args=None)[source]¶
Creates a new instance of
PickleDataSet
pointing to a concrete Pickle file on a specific filesystem.PickleDataSet
supports custom backends to serialise/deserialise objects.- Example backends that are compatible (non-exhaustive):
pickle
joblib
dill
compress_pickle
- Example backends that are incompatible:
torch
- Parameters
filepath (
str
) – 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 byfsspec
. Note: http(s) doesn’t support versioning.backend (
str
) – Backend to use, must be an import path to a module which satisfies thepickle
interface. That is, contains a load and dump function. Defaults to ‘pickle’.load_args (
Optional
[Dict
[str
,Any
]]) – 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/index.html#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 (
Optional
[Dict
[str
,Any
]]) – 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/index.html#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 (
Optional
[Version
]) – If specified, should be an instance ofkedro.io.core.Version
. If itsload
attribute is None, the latest version will be loaded. If itssave
attribute is None, save version will be autogenerated.credentials (
Optional
[Dict
[str
,Any
]]) – Credentials required to get access to the underlying filesystem. E.g. forGCSFileSystem
it should look like {“token”: None}.fs_args (
Optional
[Dict
[str
,Any
]]) – Extra arguments to pass into underlying filesystem class constructor (e.g. {“project”: “my-project”} forGCSFileSystem
), 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.
- exists()¶
Checks whether a data set’s output already exists by calling the provided _exists() method.
- Return type
bool
- Returns
Flag indicating whether the output already exists.
- Raises
DatasetError – when underlying exists method raises error.
- classmethod from_config(name, config, load_version=None, save_version=None)¶
Create a data set instance using the configuration provided.
- Parameters
name – Data set name.
config – Data set config dictionary.
load_version – Version string to be used for
load
operation if the data set is versioned. Has no effect on the data set if versioning was not enabled.save_version – Version string to be used for
save
operation if the data set is versioned. Has no effect on the data set if versioning was not enabled.
- Returns
An instance of an
AbstractDataset
subclass.- Raises
DatasetError – When the function fails to create the data set from its config.
- load()¶
Loads data by delegation to the provided load method.
- Return type
TypeVar
(_DO
)- Returns
Data returned by the provided load method.
- Raises
DatasetError – When underlying load method raises error.
- release()¶
Release any cached data.
- Raises
DatasetError – when underlying release method raises error.
- Return type
None
- resolve_load_version()¶
Compute the version the dataset should be loaded with.
- Return type
str | None
- resolve_save_version()¶
Compute the version the dataset should be saved with.
- Return type
str | None
- save(data)¶
Saves data by delegation to the provided save method.
- Parameters
data (
TypeVar
(_DI
)) – the value to be saved by provided save method.- Raises
DatasetError – when underlying save method raises error.
FileNotFoundError – when save method got file instead of dir, on Windows.
NotADirectoryError – when save method got file instead of dir, on Unix.
- Return type
None