kedro_datasets.pandas.SQLTableDataset¶
- class kedro_datasets.pandas.SQLTableDataset(table_name, credentials, load_args=None, save_args=None, metadata=None)[source]¶
SQLTableDatasetloads data from a SQL table and saves a pandas dataframe to a table. It usespandas.DataFrameinternally, so it supports all allowed pandas options onread_sql_tableandto_sqlmethods. Since Pandas uses SQLAlchemy behind the scenes, when instantiatingSQLTableDatasetone needs to pass a compatible connection string either incredentials(see the example code snippet below) or inload_argsandsave_args. Connection string formats supported by SQLAlchemy can be found here: https://docs.sqlalchemy.org/core/engines.html#database-urlsSQLTableDatasetmodifies 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_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
Methods
create_connection(connection_str)Given a connection string, create singleton connection to be used across all instances of
SQLTableDatasetthat 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, metadata=None)[source]¶
Creates a new
SQLTableDataset.- Parameters:
table_name (
str) – The table name to load or save data to. It overwrites name insave_argsandtable_nameparameters inload_args.credentials (
Dict[str,Any]) – A dictionary with aSQLAlchemyconnection string. Users are supposed to provide the connection string ‘con’ through credentials. It overwrites con parameter inload_argsandsave_argsin case it is provided. To find all supported connection string formats, see here: https://docs.sqlalchemy.org/core/engines.html#database-urlsload_args (
Optional[Dict[str,Any]]) – Provided to underlying pandasread_sql_tablefunction 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/core/engines.html#database-urlssave_args (
Optional[Dict[str,Any]]) – Provided to underlying pandasto_sqlfunction 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/core/engines.html#database-urls It hasindex=Falsein the default parameters.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 either
table_nameorconis empty.
- classmethod create_connection(connection_str)[source]¶
Given a connection string, create singleton connection to be used across all instances of
SQLTableDatasetthat 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
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