kedro.extras.datasets.pandas.GenericDataSet¶
- class kedro.extras.datasets.pandas.GenericDataSet(filepath, file_format, load_args=None, save_args=None, version=None, credentials=None, fs_args=None)[source]¶
pandas.GenericDataSet loads/saves data from/to a data file using an underlying filesystem (e.g.: local, S3, GCS). It uses pandas to dynamically select the appropriate type of read/write target on a best effort basis.
Example usage for the YAML API:
cars: type: pandas.GenericDataSet file_format: csv filepath: s3://data/01_raw/company/cars.csv load_args: sep: "," na_values: ["#NA", NA] save_args: index: False date_format: "%Y-%m-%d"
This second example is able to load a SAS7BDAT file via the
pd.read_sas
method. Trying to save this dataset will raise aDataSetError
since pandas does not provide an equivalentpd.DataFrame.to_sas
write method.flights: type: pandas.GenericDataSet file_format: sas filepath: data/01_raw/airplanes.sas7bdat load_args: format: sas7bdat
Example usage for the Python API:
from kedro.extras.datasets.pandas import GenericDataSet import pandas as pd data = pd.DataFrame({'col1': [1, 2], 'col2': [4, 5], 'col3': [5, 6]}) data_set = GenericDataSet(filepath="test.csv", file_format='csv') 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, file_format, load_args=None, save_args=None, version=None, credentials=None, fs_args=None)[source]¶
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.- Parameters
filepath (
str
) – 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 byfsspec
. 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 (
str
) – 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 (
Optional
[Dict
[str
,Any
]]) – 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 (
Optional
[Dict
[str
,Any
]]) – 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 (
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 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.
- 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