Migration guide

See the release notes on GitHub for comprehensive information about the content of each Kedro release.

Migrate an existing project that uses Kedro 0.18.* to use 0.19.*

Custom syntax for --params was removed

Kedro 0.19.0 removed the custom Kedro syntax for --params. To update, you need to use the OmegaConf syntax instead by replacing : with =.

If you used this command to pass parameters to kedro run:

kedro run --params=param_key1:value1,param_key2:2.0

You should now use the following:

kedro run --params=param_key1=value1,param_key2=2.0

For more information see “How to specify parameters at runtime”.

create_default_data_set() was removed from Runner

Kedro 0.19 removed the create_default_data_set() method in the Runner. To overwrite the default dataset creation, you need to use the new Runner class argument extra_dataset_patterns instead.

On class instantiation, pass the extra_dataset_patterns argument, and overwrite the default MemoryDataset creation as follows:

from kedro.runner import ThreadRunner

runner = ThreadRunner(extra_dataset_patterns={"{default}": {"type": "MyCustomDataset"}})

project_version was removed

Kedro 0.19 removed project_version in pyproject.toml. Use kedro_init_version instead:

[tool.kedro]
package_name = "my_project"
project_name = "my project"
- project_version = "0.19.1"
+ kedro_init_version = "0.19.1"

Datasets changes in 0.19

The layer attribute in catalog.yml has moved

From 0.19, the layer attribute at the top level has been moved inside the metadata -> kedro-viz attribute. You need to update catalog.yml accordingly.

The following catalog.yml entry changes from the following in 0.18.x code:

companies:
  type: pandas.CSVDataSet
  filepath: data/01_raw/companies.csv
  layer: raw

to this in 0.19.x:

companies:
  type: pandas.CSVDataset
  filepath: data/01_raw/companies.csv
  metadata:
    kedro-viz:
      layer: raw

See See the Kedro-Viz documentation for more information.

For APIDataset, the requests-specific arguments in catalog.yml have moved

From 0.19, if you use APIDataset, you need to move all requests-specific arguments, such as params, headers, in the hierarchy to sit under load_args. The url and method arguments are not affected.

For example the following APIDataset in catalog.yml changes from the following in 0.18.x code:

us_corn_yield_data:
  type: api.APIDataSet
  url: https://quickstats.nass.usda.gov
  credentials: usda_credentials
  params:
    key: SOME_TOKEN
    format: JSON

to this in 0.19.x:

us_corn_yield_data:
  type: api.APIDataSet
  url: https://quickstats.nass.usda.gov
  credentials: usda_credentials
  load_args:
    params:
      key: SOME_TOKEN
      format: JSON

Dataset renaming

In 0.19.0 we renamed dataset and error classes to follow the Kedro lexicon.

  • Dataset classes ending with DataSet are replaced by classes that end with Dataset.

  • Error classes starting with DataSet are replaced by classes that start with Dataset.

All the classes below are also importable from kedro.io; only the module where they are defined is listed as the location.

Type

Removed Alias

Location

AbstractDataset

AbstractDataSet

kedro.io.core

AbstractVersionedDataset

AbstractVersionedDataSet

kedro.io.core

CachedDataset

CachedDataSet

kedro.io.cached_dataset

LambdaDataset

LambdaDataSet

kedro.io.lambda_dataset

MemoryDataset

MemoryDataSet

kedro.io.memory_dataset

DatasetError

DataSetError

kedro.io.core

DatasetAlreadyExistsError

DataSetAlreadyExistsError

kedro.io.core

DatasetNotFoundError

DataSetNotFoundError

kedro.io.core

All other dataset classes are removed from the core Kedro repository (kedro.extras.datasets)

You now need to install and import datasets from the kedro-datasets package instead.

Configuration changes in 0.19

The ConfigLoader and TemplatedConfigLoader classes were deprecated in Kedro 0.18.12 and were removed in Kedro 0.19.0. To use that release or later, you must now adopt the OmegaConfigLoader. The configuration migration guide outlines the primary distinctions between the old loaders and the OmegaConfigLoader, and provides step-by-step instructions on updating your code base to use the new class effectively.

Changes to the default environments

The default configuration environment has changed in 0.19 and needs to be declared in settings.py explicitly if you have custom arguments. For example, if you use CONFIG_LOADER_ARGS in settings.py to read Spark configuration, you need to add base_env and default_run_env explicitly.

Before 0.19.x:

CONFIG_LOADER_ARGS = {
#       "base_env": "base",
#       "default_run_env": "local",
    "config_patterns": {
        "spark": ["spark*", "spark*/**"],
    }
}

In 0.19.x:

CONFIG_LOADER_ARGS = {
      "base_env": "base",
      "default_run_env": "local",
          "config_patterns": {
              "spark": ["spark*", "spark*/**"],
          }
}

If you didn’t use CONFIG_LOADER_ARGS in your code, this change is not needed because Kedro sets it by default.

Logging

logging.yml is now independent of Kedro’s run environment and used only if KEDRO_LOGGING_CONFIG is set to point to it. The documentation on logging describes in detail how logging works in Kedro and how it can be customised.