kedro.extras.datasets.pandas.GBQTableDataSet¶
- class kedro.extras.datasets.pandas.GBQTableDataSet(dataset, table_name, project=None, credentials=None, load_args=None, save_args=None)[source]¶
GBQTableDataSetloads and saves data from/to Google BigQuery. It uses pandas-gbq to read and write from/to BigQuery table.Example usage for the YAML API:
vehicles: type: pandas.GBQTableDataSet dataset: big_query_dataset table_name: big_query_table project: my-project credentials: gbq-creds load_args: reauth: True save_args: chunk_size: 100
Example usage for the Python API:
from kedro.extras.datasets.pandas import GBQTableDataSet import pandas as pd data = pd.DataFrame({'col1': [1, 2], 'col2': [4, 5], 'col3': [5, 6]}) data_set = GBQTableDataSet('dataset', 'table_name', project='my-project') 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.
save(data)Saves data by delegation to the provided save method.
- DEFAULT_LOAD_ARGS: Dict[str, Any] = {}¶
- DEFAULT_SAVE_ARGS: Dict[str, Any] = {'progress_bar': False}¶
- __init__(dataset, table_name, project=None, credentials=None, load_args=None, save_args=None)[source]¶
Creates a new instance of
GBQTableDataSet.- Parameters:
dataset (
str) – Google BigQuery dataset.table_name (
str) – Google BigQuery table name.project (
Optional[str]) – Google BigQuery Account project ID. Optional when available from the environment. https://cloud.google.com/resource-manager/docs/creating-managing-projectscredentials (
Union[Dict[str,Any],Credentials,None]) – Credentials for accessing Google APIs. Eithergoogle.auth.credentials.Credentialsobject or dictionary with parameters required to instantiategoogle.oauth2.credentials.Credentials. Here you can find all the arguments: https://google-auth.readthedocs.io/en/latest/reference/google.oauth2.credentials.htmlload_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.save_args (
Optional[Dict[str,Any]]) – Pandas options for saving DataFrame to BigQuery table. Here you can find all available arguments: https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_gbq.html All defaults are preserved, but “progress_bar”, which is set to False.
- Raises:
DatasetError – When
load_args['location']andsave_args['location']are different.
- 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
loadoperation 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
saveoperation if the data set is versioned. Has no effect on the data set if versioning was not enabled.
- Returns:
An instance of an
AbstractDatasetsubclass.- 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