Hi everyone! Is there a way to access

namespace

in a python script the same way I can access e.g., parameters? For example, I can access parameters in a

py

script as such:

from kedro.framework.project import settings
CONFIG_LOADER = settings.CONFIG_LOADER_CLASS(conf_source=settings.CONF_SOURCE, **settings.CONFIG_LOADER_ARGS)
params = CONFIG_LOADER["parameters"]

But how can I access the namespace I pass when running

kedro run --pipeline data_preprocessing --namespace example_space

to for example - in the simplest form - be able to log "namespace is set to: example_space"? Thank you!!!

Someone will reply to you shortly. In the meantime, this might help:

I think you can retrieve this information from a hook and then set an environment variable. The nodes intentionally are not aware of IO or execution, they are designed to be pure python functions with no side effects

Thank you! I realised after your response that an initial hook I had previously set up was not even working and am now struggling to get hooks to work in general. I've followed the documentation - and am a bit lost as how to fix this problem as the hooks are correctly registered but still not triggered when I run the pipeline. Do you have any idea why hooks would be registered but still not be triggered when running the pipeline? Do namespaces influence

before/after_pipeline_run

hooks in any way? Some more context:

hooks.py

class PipelineStatusHookNew:
    def __init__(self):
        logger.info("PipelineStatusHookNew instantiated.")
        logger.info(f"Class instance: {self}")

...

    @hook_impl
    def before_pipeline_run(self, run_params, **kwargs):
        logger.info("before_pipeline_run triggered with run_params: %s", run_params)
        self.start_time = datetime.now(tz=timezone.utc)
        logger.info("Logged run start time for state management table update.")
...

CLI

You can see that that the

def __init__(self):

logs are being displayed but then the pipeline and nodes start running without triggering the

before_pipeline_run

method. And I've tried before/after pipeline/node etc. - logging things but also writing to an output file but nothing's happening.

kedro run --pipeline sample_testing_pipe --namespace industry

[03/07/25 15:33:04] INFO     Using 'conf/logging.yml' as logging configuration. You can change this by setting the KEDRO_LOGGING_CONFIG        __init__.py:270
                             environment variable accordingly.
2025-03-07 15:33:19,052 - hook_registry.hooks - INFO - PipelineStatusHookNew instantiated.
[03/07/25 15:33:19] INFO     PipelineStatusHookNew instantiated.                                                                                   hooks.py:16
2025-03-07 15:33:19,055 - hook_registry.hooks - INFO - Class instance: <hook_registry.hooks.PipelineStatusHookNew object at 0x162526620>
                    INFO     Class instance: <hook_registry.hooks.PipelineStatusHookNew object at 0x162526620>                                     hooks.py:17
                    WARNING  /Users/Marie_Cordes/.pyenv/versions/3.10.9/lib/python3.10/site-packages/kedro_viz/integrations/kedro/hooks.py:13: warnings.py:109
                             KedroDeprecationWarning: 'TRANSCODING_SEPARATOR' has been moved to 'kedro.pipeline.transcoding', and the alias
                             will be removed in Kedro 0.20.0
                               from kedro.pipeline.pipeline import TRANSCODING_SEPARATOR, _strip_transcoding

                    INFO     Kedro project classifications-v2                                                                                   session.py:329
                    INFO     Using synchronous mode for loading and saving data. Use the --async flag for potential performance gains. sequential_runner.py:74
                             <https://docs.kedro.org/en/stable/nodes_and_pipelines/run_a_pipeline.html#load-and-save-asynchronously>
                    INFO     Loading data from model_config_dev (SnowparkTableDataset)...                                                  data_catalog.py:390
[03/07/25 15:33:20] INFO     Loading data from params:industry.model_configs (MemoryDataset)...                                            data_catalog.py:390
                    INFO     Running node: fetch_model_configs_from_snowflake_node:                                                                node.py:367
                             fetch_model_configs([model_config_dev;params:industry.model_configs]) -> [industry.classifier_profiles]
...

<< proceeds to run the pipeline >>

src/classifications_v2/settings.py

from hook_registry.hooks import PipelineStatusHookNew
HOOKS = (PipelineStatusHookNew(),)

so it's a little to tell from these logs