kedro_datasets.pandas.GBQQueryDataset

class kedro_datasets.pandas.GBQQueryDataset(sql=None, project=None, credentials=None, load_args=None, fs_args=None, filepath=None, metadata=None)

GBQQueryDataset loads data from a provided SQL query from Google BigQuery. It uses pandas.read_gbq which itself uses pandas-gbq internally to read from BigQuery table. Therefore it supports all allowed pandas options on read_gbq.

Example adding a catalog entry with the YAML API:

vehicles:
  type: pandas.GBQQueryDataset
  sql: "select shuttle, shuttle_id from spaceflights.shuttles;"
  project: my-project
  credentials: gbq-creds
  load_args:
    reauth: True

Example using Python API:

from kedro_datasets.pandas import GBQQueryDataset

sql = "SELECT * FROM dataset_1.table_a"

dataset = GBQQueryDataset(sql, project="my-project")

sql_data = dataset.load()

Attributes

DEFAULT_LOAD_ARGS

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.
save(data)	Saves data by delegation to the provided save method.

DEFAULT_LOAD_ARGS: dict[str, Any] = {}

__init__(sql=None, project=None, credentials=None, load_args=None, fs_args=None, filepath=None, metadata=None)

Creates a new instance of GBQQueryDataset.

Parameters:

• sql (Optional[str]) – The sql query statement.

• project (Optional[str]) – Google BigQuery Account project ID. Optional when available from the environment. https://cloud.google.com/resource-manager/docs/creating-managing-projects

• credentials (Union[dict[str, Any], Credentials, None]) – 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 (Optional[dict[str, Any]]) – 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 (Optional[dict[str, Any]]) – 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 (Optional[str]) – A path to a file with a sql query statement.

• metadata (Optional[dict[str, Any]]) – Any arbitrary metadata. This is ignored by Kedro, but may be consumed by users or external plugins.

Raises:

DatasetError – When sql and filepath parameters are either both empty or both provided, as well as when the save() method is invoked.

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 (str) – Data set name.

• config (dict[str, Any]) – Data set config dictionary.

• load_version (Optional[str]) – 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 (Optional[str]) – 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.

Return type:

AbstractDataset

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

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