Repository: kedro-org/kedro
File: kedro/io/kedro_data_catalog.py (Python)

Code before:
        """Create a ``KedroDataCatalog`` instance from configuration. This is a
        factory method used to provide developers with a way to instantiate
        ``KedroDataCatalog`` with configuration parsed from configuration files.

        Args:
            catalog: A dictionary whose keys are the dataset names and
                the values are dictionaries with the constructor arguments
                for classes implementing ``AbstractDataset``. The dataset
                class to be loaded is specified with the key ``type`` and their
                fully qualified class name. All ``kedro.io`` dataset can be
                specified by their class name only, i.e. their module name
                can be omitted.
            credentials: A dictionary containing credentials for different
                datasets. Use the ``credentials`` key in a ``AbstractDataset``
                to refer to the appropriate credentials as shown in the example
                below.
            load_versions: A mapping between dataset names and versions
                to load. Has no effect on datasets without enabled versioning.
            save_version: Version string to be used for ``save`` operations
                by all datasets with enabled versioning. It must: a) be a
                case-insensitive string that conforms with operating system
                filename limitations, b) always return the latest version when
                sorted in lexicographical order.

        Returns:
            An instantiated ``DataCatalog`` containing all specified
            datasets, created and ready to use.

        Raises:
            DatasetNotFoundError: When `load_versions` refers to a dataset that doesn't
                exist in the catalog.

        Example:
        ::

            >>> config = {
            >>>     "cars": {
            >>>         "type": "pandas.CSVDataset",
            >>>         "filepath": "cars.csv",
            >>>         "save_args": {
            >>>             "index": False
            >>>         }
            >>>     },
            >>>     "boats": {
            >>>         "type": "pandas.CSVDataset",
            >>>         "filepath": "s3://aws-bucket-name/boats.csv",
            >>>         "credentials": "boats_credentials",
            >>>         "save_args": {
            >>>             "index": False
            >>>         }
            >>>     }

Review comment (suggestion):
```suggestion
            An instantiated ``KedroDataCatalog`` containing all specified
```


Code after:
        """Create a ``KedroDataCatalog`` instance from configuration. This is a
        factory method used to provide developers with a way to instantiate
        ``KedroDataCatalog`` with configuration parsed from configuration files.

        Args:
            catalog: A dictionary whose keys are the dataset names and
                the values are dictionaries with the constructor arguments
                for classes implementing ``AbstractDataset``. The dataset
                class to be loaded is specified with the key ``type`` and their
                fully qualified class name. All ``kedro.io`` dataset can be
                specified by their class name only, i.e. their module name
                can be omitted.
            credentials: A dictionary containing credentials for different
                datasets. Use the ``credentials`` key in a ``AbstractDataset``
                to refer to the appropriate credentials as shown in the example
                below.
            load_versions: A mapping between dataset names and versions
                to load. Has no effect on datasets without enabled versioning.
            save_version: Version string to be used for ``save`` operations
                by all datasets with enabled versioning. It must: a) be a
                case-insensitive string that conforms with operating system
                filename limitations, b) always return the latest version when
                sorted in lexicographical order.

        Returns:
            An instantiated ``KedroDataCatalog`` containing all specified
            datasets, created and ready to use.

        Raises:
            DatasetNotFoundError: When `load_versions` refers to a dataset that doesn't
                exist in the catalog.

        Example:
        ::

            >>> config = {
            >>>     "cars": {
            >>>         "type": "pandas.CSVDataset",
            >>>         "filepath": "cars.csv",
            >>>         "save_args": {
            >>>             "index": False
            >>>         }
            >>>     },
            >>>     "boats": {
            >>>         "type": "pandas.CSVDataset",
            >>>         "filepath": "s3://aws-bucket-name/boats.csv",
            >>>         "credentials": "boats_credentials",
            >>>         "save_args": {
            >>>             "index": False
            >>>         }
            >>>     }