Kedro

Latest version: v0.19.11

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0.18.8

Not secure
Major features and improvements
* Added `KEDRO_LOGGING_CONFIG` environment variable, which can be used to configure logging from the beginning of the `kedro` process.
* Removed logs folder from the kedro new project template. File-based logging will remain but just be level INFO and above and go to project root instead.


Bug fixes and other changes
* Improvements to Jupyter E2E tests.
* Added full `kedro run` CLI command to session store to improve run reproducibility using `Kedro-Viz` experiment tracking.

Documentation changes
* Improvements to documentation about configuration.
* Improvements to Sphinx toolchain including incrementing to use a newer version.
* Improvements to documentation on visualising Kedro projects on Databricks, and additional documentation about the development workflow for Kedro projects on Databricks.
* Updated Technical Steering Committee membership documentation.
* Revised documentation section about linting and formatting and extended to give details of `flake8` configuration.
* Updated table of contents for documentation to reduce scrolling.
* Expanded FAQ documentation.
* Added a 404 page to documentation.
* Added deprecation warnings about the removal of `kedro.extras.datasets`.

Community contributions
Many thanks to the following Kedroids for contributing PRs to this release:

* [MaximeSteinmetz](https://github.com/MaximeSteinmetz)

0.18.7

Not secure
Major features and improvements
* Added new Kedro CLI `kedro jupyter setup` to setup Jupyter Kernel for Kedro.
* `kedro package` now includes the project configuration in a compressed `tar.gz` file.
* Added functionality to the `OmegaConfigLoader` to load configuration from compressed files of `zip` or `tar` format. This feature requires `fsspec>=2023.1.0`.
* Significant improvements to on-boarding documentation that covers setup for new Kedro users. Also some major changes to the spaceflights tutorial to make it faster to work through. We think it's a better read. Tell us if it's not.

Bug fixes and other changes
* Added a guide and tooling for developing Kedro for Databricks.
* Implemented missing dict-like interface for `_ProjectPipeline`.

0.18.6

Not secure
A regression introduced in Kedro version `0.18.5` caused the `Kedro-Viz` console to fail to show experiment tracking correctly. If you experienced this issue, you will need to:
* upgrade to Kedro version `0.18.6`
* delete any erroneous session entries created with Kedro 0.18.5 from your session_store.db stored at `<project-path>/data/session_store.db`.

Thanks to Kedroids tomohiko kato, [tsanikgr](https://github.com/tsanikgr) and [maddataanalyst](https://github.com/maddataanalyst) for very detailed reports about the bug.

0.18.5

Not secure
> This release introduced a bug that causes a failure in experiment tracking within the `Kedro-Viz` console. We recommend that you use Kedro version `0.18.6` in preference.

Major features and improvements
* Added new `OmegaConfigLoader` which uses `OmegaConf` for loading and merging configuration.
* Added the `--conf-source` option to `kedro run`, allowing users to specify a source for project configuration for the run.
* Added `omegaconf` syntax as option for `--params`. Keys and values can now be separated by colons or equals signs.
* Added support for generator functions as nodes, i.e. using `yield` instead of return.
* Enable chunk-wise processing in nodes with generator functions.
* Save node outputs after every `yield` before proceeding with next chunk.
* Fixed incorrect parsing of Azure Data Lake Storage Gen2 URIs used in datasets.
* Added support for loading credentials from environment variables using `OmegaConfigLoader`.
* Added new `--namespace` flag to `kedro run` to enable filtering by node namespace.
* Added a new argument `node` for all four dataset hooks.
* Added the `kedro run` flags `--nodes`, `--tags`, and `--load-versions` to replace `--node`, `--tag`, and `--load-version`.

Bug fixes and other changes
* Commas surrounded by square brackets (only possible for nodes with default names) will no longer split the arguments to `kedro run` options which take a list of nodes as inputs (`--from-nodes` and `--to-nodes`).
* Fixed bug where `micropkg` manifest section in `pyproject.toml` isn't recognised as allowed configuration.
* Fixed bug causing `load_ipython_extension` not to register the `%reload_kedro` line magic when called in a directory that does not contain a Kedro project.
* Added `anyconfig`'s `ac_context` parameter to `kedro.config.commons` module functions for more flexible `ConfigLoader` customizations.
* Change reference to `kedro.pipeline.Pipeline` object throughout test suite with `kedro.modular_pipeline.pipeline` factory.
* Fixed bug causing the `after_dataset_saved` hook only to be called for one output dataset when multiple are saved in a single node and async saving is in use.
* Log level for "Credentials not found in your Kedro project config" was changed from `WARNING` to `DEBUG`.
* Added safe extraction of tar files in `micropkg pull` to fix vulnerability caused by [CVE-2007-4559](https://github.com/advisories/GHSA-gw9q-c7gh-j9vm).
* Documentation improvements
* Bug fix in table font size
* Updated API docs links for datasets
* Improved CLI docs for `kedro run`
* Revised documentation for visualisation to build plots and for experiment tracking
* Added example for loading external credentials to the Hooks documentation

Breaking changes to the API

Community contributions
Many thanks to the following Kedroids for contributing PRs to this release:

* [adamfrly](https://github.com/adamfrly)
* [corymaklin](https://github.com/corymaklin)
* [Emiliopb](https://github.com/Emiliopb)
* [grhaonan](https://github.com/grhaonan)
* [JStumpp](https://github.com/JStumpp)
* [michalbrys](https://github.com/michalbrys)
* [sbrugman](https://github.com/sbrugman)

0.18.4

Not secure
Major features and improvements
* Make Kedro instantiate datasets from `kedro_datasets` with higher priority than `kedro.extras.datasets`. `kedro_datasets` is the namespace for the new `kedro-datasets` python package.
* The config loader objects now implement `UserDict` and the configuration is accessed through `conf_loader['catalog']`.
* You can configure config file patterns through `settings.py` without creating a custom config loader.
* Added the following new datasets:

| Type | Description | Location |
| ------------------------------------ | -------------------------------------------------------------------------- | -------------------------------- |
| `svmlight.SVMLightDataSet` | Work with svmlight/libsvm files using scikit-learn library | `kedro.extras.datasets.svmlight` |
| `video.VideoDataSet` | Read and write video files from a filesystem | `kedro.extras.datasets.video` |
| `video.video_dataset.SequenceVideo` | Create a video object from an iterable sequence to use with `VideoDataSet` | `kedro.extras.datasets.video` |
| `video.video_dataset.GeneratorVideo` | Create a video object from a generator to use with `VideoDataSet` | `kedro.extras.datasets.video` |
* Implemented support for a functional definition of schema in `dask.ParquetDataSet` to work with the `dask.to_parquet` API.

Bug fixes and other changes
* Fixed `kedro micropkg pull` for packages on PyPI.
* Fixed `format` in `save_args` for `SparkHiveDataSet`, previously it didn't allow you to save it as delta format.
* Fixed save errors in `TensorFlowModelDataset` when used without versioning; previously, it wouldn't overwrite an existing model.
* Added support for `tf.device` in `TensorFlowModelDataset`.
* Updated error message for `VersionNotFoundError` to handle insufficient permission issues for cloud storage.
* Updated Experiment Tracking docs with working examples.
* Updated `MatplotlibWriter`, `text.TextDataSet`, `plotly.PlotlyDataSet` and `plotly.JSONDataSet` docs with working examples.
* Modified implementation of the Kedro IPython extension to use `local_ns` rather than a global variable.
* Refactored `ShelveStore` to its own module to ensure multiprocessing works with it.
* `kedro.extras.datasets.pandas.SQLQueryDataSet` now takes optional argument `execution_options`.
* Removed `attrs` upper bound to support newer versions of Airflow.
* Bumped the lower bound for the `setuptools` dependency to <=61.5.1.

Minor breaking changes to the API

0.18.3

Not secure
Major features and improvements
* Implemented autodiscovery of project pipelines. A pipeline created with `kedro pipeline create <pipeline_name>` can now be accessed immediately without needing to explicitly register it in `src/<package_name>/pipeline_registry.py`, either individually by name (e.g. `kedro run --pipeline=<pipeline_name>`) or as part of the combined default pipeline (e.g. `kedro run`). By default, the simplified `register_pipelines()` function in `pipeline_registry.py` looks like:

python
def register_pipelines() -> Dict[str, Pipeline]:
"""Register the project's pipelines.

Returns:
A mapping from pipeline names to ``Pipeline`` objects.
"""
pipelines = find_pipelines()
pipelines["__default__"] = sum(pipelines.values())
return pipelines


* The Kedro IPython extension should now be loaded with `%load_ext kedro.ipython`.
* The line magic `%reload_kedro` now accepts keywords arguments, e.g. `%reload_kedro --env=prod`.
* Improved resume pipeline suggestion for `SequentialRunner`, it will backtrack the closest persisted inputs to resume.

Bug fixes and other changes

* Changed default `False` value for rich logging `show_locals`, to make sure credentials and other sensitive data isn't shown in logs.
* Rich traceback handling is disabled on Databricks so that exceptions now halt execution as expected. This is a workaround for a [bug in `rich`](https://github.com/Textualize/rich/issues/2455).
* When using `kedro run -n [some_node]`, if `some_node` is missing a namespace the resulting error message will suggest the correct node name.
* Updated documentation for `rich` logging.
* Updated Prefect deployment documentation to allow for reruns with saved versioned datasets.
* The Kedro IPython extension now surfaces errors when it cannot load a Kedro project.
* Relaxed `delta-spark` upper bound to allow compatibility with Spark 3.1.x and 3.2.x.
* Added `gdrive` to list of cloud protocols, enabling Google Drive paths for datasets.
* Added svg logo resource for ipython kernel.

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