module documentation
DataCatalog stores instances of AbstractDataSet implementations to provide load and save capabilities from anywhere in the program. To use a DataCatalog, you need to instantiate it with a dictionary of data sets. Then it will act as a single point of reference for your calls, relaying load and save functions to the underlying data sets.
Constant | CATALOG |
Undocumented |
Constant | CREDENTIALS |
Undocumented |
Constant | WORDS |
Undocumented |
Class | _ |
Helper class to access underlying loaded datasets |
Function | _get |
Return a set of credentials from the provided credentials dict. |
Function | _resolve |
Return the dataset configuration where credentials are resolved using credentials dictionary provided. |
Function | _sub |
Replace non-word characters in data set names since Kedro 0.16.2. |
def _get_credentials(credentials_name:
str
, credentials: Dict[ str, Any]
) -> Dict[ str, Any]
:
(source)
¶
Return a set of credentials from the provided credentials dict.
Parameters | |
credentialsstr | Credentials name. |
credentials:Dict[ | A dictionary with all credentials. |
Returns | |
Dict[ | The set of requested credentials. |
Raises | |
KeyError | When a data set with the given name has not yet been registered. |
def _resolve_credentials(config:
Dict[ str, Any]
, credentials: Dict[ str, Any]
) -> Dict[ str, Any]
:
(source)
¶
Return the dataset configuration where credentials are resolved using credentials dictionary provided.
Parameters | |
config:Dict[ | Original dataset config, which may contain unresolved credentials. |
credentials:Dict[ | A dictionary with all credentials. |
Returns | |
Dict[ | The dataset config, where all the credentials are successfully resolved. |