kedro.extras.datasets.pandas.SQLQueryDataSet¶

class kedro.extras.datasets.pandas.SQLQueryDataSet(sql=None, credentials=None, load_args=None, fs_args=None, filepath=None, execution_options=None)[source]¶

SQLQueryDataSet loads data from a provided SQL query. It uses pandas.DataFrame internally, so it supports all allowed pandas options on read_sql_query. Since Pandas uses SQLAlchemy behind the scenes, when instantiating SQLQueryDataSet one needs to pass a compatible connection string either in credentials (see the example code snippet below) or in load_args. Connection string formats supported by SQLAlchemy can be found here: https://docs.sqlalchemy.org/en/13/core/engines.html#database-urls

It does not support save method so it is a read only data set. To save data to a SQL server use SQLTableDataSet.

Example usage for the YAML API:

shuttle_id_dataset:
  type: pandas.SQLQueryDataSet
  sql: "select shuttle, shuttle_id from spaceflights.shuttles;"
  credentials: db_credentials

Advanced example using the stream_results and chunksize options to reduce memory usage:

shuttle_id_dataset:
  type: pandas.SQLQueryDataSet
  sql: "select shuttle, shuttle_id from spaceflights.shuttles;"
  credentials: db_credentials
  execution_options:
    stream_results: true
  load_args:
    chunksize: 1000

Sample database credentials entry in credentials.yml:

db_credentials:
  con: postgresql://scott:tiger@localhost/test

Example usage for the Python API:

from kedro.extras.datasets.pandas import SQLQueryDataSet
import pandas as pd

data = pd.DataFrame({"col1": [1, 2], "col2": [4, 5],
                     "col3": [5, 6]})
sql = "SELECT * FROM table_a"
credentials = {
    "con": "postgresql://scott:tiger@localhost/test"
}
data_set = SQLQueryDataSet(sql=sql,
                           credentials=credentials)

sql_data = data_set.load()

Attributes

engines

Methods

`create_connection`(connection_str)	Given a connection string, create singleton connection to be used across all instances of SQLQueryDataSet that need to connect to the same source.
`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.

__init__(sql=None, credentials=None, load_args=None, fs_args=None, filepath=None, execution_options=None)[source]¶

Creates a new SQLQueryDataSet.

Parameters

sql (Optional[str]) – The sql query statement.
credentials (Optional[Dict[str, Any]]) – A dictionary with a SQLAlchemy connection string. Users are supposed to provide the connection string ‘con’ through credentials. It overwrites con parameter in load_args and save_args in case it is provided. To find all supported connection string formats, see here: https://docs.sqlalchemy.org/en/13/core/engines.html#database-urls
load_args (Optional[Dict[str, Any]]) – Provided to underlying pandas read_sql_query function along with the connection string. To find all supported arguments, see here: https://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_sql_query.html To find all supported connection string formats, see here: https://docs.sqlalchemy.org/en/13/core/engines.html#database-urls
fs_args (Optional[Dict[str, Any]]) – 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.
filepath (Optional[str]) – A path to a file with a sql query statement.
execution_options (Optional[Dict[str, Any]]) – A dictionary with non-SQL advanced options for the connection to be applied to the underlying engine. To find all supported execution options, see here: https://docs.sqlalchemy.org/en/12/core/connections.html#sqlalchemy.engine.Connection.execution_options Note that this is not a standard argument supported by pandas API, but could be useful for handling large datasets.

Raises

DatasetError – When either sql or con parameters is empty.

classmethod create_connection(connection_str)[source]¶

Given a connection string, create singleton connection to be used across all instances of SQLQueryDataSet that need to connect to the same source.

Return type: None

engines: Dict[str, Any] = {}¶

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

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