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pypipkg:pypi/kedro@1.1.x
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tessl/pypi-kedro

tessl install tessl/pypi-kedro@1.1.0

Kedro helps you build production-ready data and analytics pipelines

Agent Success

Agent success rate when using this tile

98%

Improvement

Agent success rate improvement when using this tile compared to baseline

1.32x

Baseline

Agent success rate without this tile

74%

task.mdevals/scenario-7/

Dataset Access Logger

A monitoring system that tracks and logs all dataset access operations (loads and saves) during pipeline execution.

Requirements

Build a system that monitors dataset operations by:

  1. Recording every time a dataset is loaded, including the dataset name and a timestamp
  2. Recording every time a dataset is saved, including the dataset name and a timestamp
  3. Providing a method to retrieve the complete access log as a list of dictionaries

Each log entry should be a dictionary containing:

  • dataset_name: Name of the dataset accessed
  • operation: Either "load" or "save"
  • timestamp: ISO 8601 formatted timestamp string

Test Cases

  • When a dataset is successfully loaded, a log entry is created with operation "load" @test
  • When a dataset is successfully saved, a log entry is created with operation "save" @test
  • Multiple dataset operations are logged in chronological order @test
  • The get_log method returns all recorded entries @test

Implementation

@generates

API

class DatasetAccessLogger:
    """Monitors and logs dataset access operations during pipeline execution."""

    def get_log(self) -> list[dict]:
        """
        Retrieve the complete access log.

        Returns:
            A list of dictionaries, each containing:
            - dataset_name (str): Name of the dataset
            - operation (str): Either "load" or "save"
            - timestamp (str): ISO 8601 formatted timestamp
        """
        pass

Dependencies { .dependencies }

kedro { .dependency }

Provides the pipeline and dataset lifecycle hook system.