How can I register kedro data catalog programmatically in Kedro 0.18?

For various reasons (mainly ability to dynamically construct file paths) I like to define the data catalog programatically, and not use yaml file to define datasets e.g.

DataCatalog(
    {"products": ParquetDataSet(filepath=f{PREFIX}/products.parquet") 
...
})

In kedro 0.17 there was an easy way to register the catalog in order to use it's datasets in pipeline definition, via register_catalog hook.

However in 0.18 this hook is absent and there is no RegistrationSpecs section among hook specifications.

What is there a way to replace register_catalog in kedro 0.18?

I searched the documentation and tried to implement catalog in yaml file, but that doesn't fit project's requirements. TemplatedConfigLoader is probably an option, but i does't allow to implement custom logic, constructing paths to datasets.

Not sure if this is the precise functionality that you're looking for, but I've been programmatically adding datasets by using a combination of after_context_created and after_catalog_created hooks.

Just create an "add" method for the dataset that you require and use the docs to see what args are needed. In the example below, I have my data in S3, so I created a method to grab my creds from credentials.yml and passed them to PickleDataSet.

import logging
from kedro.config import ConfigLoader
from kedro.framework.project import settings
from kedro.framework.hooks import hook_impl
from kedro.extras.datasets.pickle.pickle_dataset import PickleDataSet


class ProjectHooks:
    @property
    def _logger(self):
        return logging.getLogger(__name__)

    @hook_impl
    def after_context_created(self, context):
        self.project_path = context.project_path
        self._logger.info(f"Project path: {self.project_path}")

    def _get_credentials(self, key):
        conf_path = f"{self.project_path}/{settings.CONF_SOURCE}"
        conf_loader = ConfigLoader(conf_source=conf_path, env="local")
        return conf_loader.get("credentials*")[key]

    def add_pickle_dataset(self, name, folder, layer=None):
        self.catalog.add(
            data_set_name=name,
            data_set=PickleDataSet(
                filepath=f"s3://root/data/{folder}/{name}",
                credentials=self._get_credentials("dev_s3"),
            ),
            replace=True,
        )
        if layer:
            self.catalog.layers[layer].add(name)
        self._logger.info(f"Added dataset '{name}' to the data catalog.")

    @hook_impl
    def after_catalog_created(self, catalog):
        self.catalog = catalog
        datasets = self.catalog.load("params:datasets")
        for dataset in datasets:
            self.add_pickle_dataset(
                name=f"{dataset}",
                folder="07_model_output",
                layer="Model Output",
            )