rx_list_keys
Usage
revoscalepy.rx_list_keys(src: revoscalepy.datasource.RxOdbcData.RxOdbcData,
key: str = None, version: str = None,
key_name: str = 'id', version_name: str = 'version')
Description
Retrieves object keys from ODBC data sources.
Details
Enumerates all keys or versions for a given key, depending on the parameters. When key is None, the function enumerates all unique keys in the table. Otherwise, it enumerates all versions for the given key. Returns a single column data frame.
The key and the version should be of some SQL character type (CHAR, VARCHAR, NVARCHAR, etc.) supported by the data source. The value column should be a binary type (VARBINARY for instance). Some conversions to other types might work, however, they are dependent on the ODBC driver and on the underlying package functions.
Arguments
value
The object being stored into the data source.
key
A character string identifying the object. The intended use is for the key+version to be unique.
version
None or a character string which carries the version of the object. Combined with key identifies the object.
key_name
Character string specifying the column name for the key in the underlying table.
value_name
Character string specifying the column name for the objects in the underlying table.
version_name
Character string specifying the column name for the version in the underlying table.
Returns
rx_read_object returns an object. rx_write_object and rx_delete_object return bool, True on success. rx_list_keys returns a single column data frame containing strings.
Example
from pandas import DataFrame
from numpy import random
from revoscalepy import RxOdbcData, rx_write_object, rx_read_object, rx_list_keys, rx_delete_object
connection_string = 'Driver=SQL Server;Server=.;Database=RevoTestDb;Trusted_Connection=True;'
dest = RxOdbcData(connection_string, table = "dataframe")
df = DataFrame(random.randn(10, 5))
status = rx_write_object(dest, key = "myDf", value = df)
read_obj = rx_read_object(dest, key = "myDf")
keys = rx_list_keys(dest)
rx_delete_object(dest, key = "myDf")