kedro.extras.datasets.pandas.SQLTableDataSet

class kedro.extras.datasets.pandas.SQLTableDataSet(table_name, credentials, load_args=None, save_args=None)

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

SQLTableDataSet modifies the save parameters and stores the data with no index. This is designed to make load and save methods symmetric.

Example usage for the YAML API:

shuttles_table_dataset:
  type: pandas.SQLTableDataSet
  credentials: db_credentials
  table_name: shuttles
  load_args:
    schema: dwschema
  save_args:
    schema: dwschema
    if_exists: replace

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 SQLTableDataSet
import pandas as pd

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

data_set.save(data)
reloaded = data_set.load()

assert data.equals(reloaded)

Attributes

DEFAULT_LOAD_ARGS
DEFAULT_SAVE_ARGS
engines

Methods

create_connection(connection_str)	Given a connection string, create singleton connection to be used across all instances of SQLTableDataSet 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.

DEFAULT_LOAD_ARGS: Dict[str, Any] = {}

DEFAULT_SAVE_ARGS: Dict[str, Any] = {'index': False}

__init__(table_name, credentials, load_args=None, save_args=None)

Creates a new SQLTableDataSet.

Parameters

• table_name (str) – The table name to load or save data to. It overwrites name in save_args and table_name parameters in load_args.

• credentials (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_table function along with the connection string. To find all supported arguments, see here: https://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_sql_table.html To find all supported connection string formats, see here: https://docs.sqlalchemy.org/en/13/core/engines.html#database-urls

• save_args (Optional[Dict[str, Any]]) – Provided to underlying pandas to_sql function along with the connection string. To find all supported arguments, see here: https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.to_sql.html To find all supported connection string formats, see here: https://docs.sqlalchemy.org/en/13/core/engines.html#database-urls It has index=False in the default parameters.

Raises

DatasetError – When either table_name or con is empty.

classmethod create_connection(connection_str)

Given a connection string, create singleton connection to be used across all instances of SQLTableDataSet 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