Release/0.18.3

CITATION.cff

@@ -36,6 +36,6 @@ authors:
 - family-names: Theisen
   given-names: Merel
 title: Kedro
-version: 0.18.2
-date-released: 2022-06-07
+version: 0.18.3
+date-released: 2022-09-20
 url: https://github.com/kedro-org/kedro

RELEASE.md

@@ -8,8 +8,15 @@
 
 ## Migration guide from Kedro 0.18.* to 0.19.*
 
+# Upcoming Release 0.18.4
 
-# Upcoming Release 0.18.3
+## Major features and improvements
+
+## Bug fixes and other changes
+
+## Breaking changes to the API
+
+# Release 0.18.3
 
 ## 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:
@@ -28,20 +35,23 @@
 
 * 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
 
-* Use default `False` value for rich logging `set_locals`, to make sure credentials and other sensitive data isn't shown in logs.
+* 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.
-* Update documentation for `rich` logging.
+* 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.
 
 ## Upcoming deprecations for Kedro 0.19.0
 * The Kedro IPython extension will no longer be available as `%load_ext kedro.extras.extensions.ipython`; use `%load_ext kedro.ipython` instead.
+* `kedro jupyter convert`, `kedro build-docs`, `kedro build-reqs` and `kedro activate-nbstripout` will be deprecated.
 
 # Release 0.18.2
 

docs/source/deployment/databricks.md

@@ -34,7 +34,7 @@ conda create --name iris_databricks python=3.7 -y
 conda activate iris_databricks
 
 # install Kedro and create a new project
-pip install "kedro~=0.18.2"
+pip install "kedro~=0.18.3"
 # name your project Iris Databricks when prompted for it
 kedro new --starter pyspark-iris
 ```
@@ -169,10 +169,10 @@ In your newly-created notebook, put each of the below code snippets into a separ
 %sh rm -rf ~/projects/iris-databricks && git clone --single-branch --branch main https://${GITHUB_USER}:${GITHUB_TOKEN}@github.com/${GITHUB_USER}/<your-repo-name>.git ~/projects/iris-databricks
 ```
 
-* Install the latest version of Kedro compatible with version `0.18.2`
+* Install the latest version of Kedro compatible with version `0.18.3`
 
 ```console
-%pip install "kedro[spark.SparkDataSet]~=0.18.2"
+%pip install "kedro[spark.SparkDataSet]~=0.18.3"
 ```
 
 * Copy input data into DBFS

docs/source/development/commands_reference.md

@@ -114,7 +114,7 @@ Returns output similar to the following, depending on the version of Kedro used
 | |/ / _ \/ _` | '__/ _ \
 |   <  __/ (_| | | | (_) |
 |_|\_\___|\__,_|_|  \___/
-v0.18.2
+v0.18.3
 
 Kedro is a Python framework for
 creating reproducible, maintainable

docs/source/extend_kedro/plugins.md

@@ -84,7 +84,7 @@ setup(
 After that you can use this starter with `kedro new --starter=test_plugin_starter`.
 
 ```{note}
-If your starter lives on a git repository, by default Kedro attempts to use a tag or branch labelled with your version of Kedro, e.g. `0.18.2.`. This means that you can host different versions of your starter template on the same repository, and the correct one will automatically be used. If you do not wish to follow this structure, you should override it with the `checkout` flag, e.g. `kedro new --starter=test_plugin_starter --checkout=main`.
+If your starter lives on a git repository, by default Kedro attempts to use a tag or branch labelled with your version of Kedro, e.g. `0.18.3.`. This means that you can host different versions of your starter template on the same repository, and the correct one will automatically be used. If you do not wish to follow this structure, you should override it with the `checkout` flag, e.g. `kedro new --starter=test_plugin_starter --checkout=main`.
 ```
 
 ## Working with `click`

docs/source/tutorial/tutorial_template.md

@@ -29,7 +29,7 @@ ipython==7.0 # Used for an IPython session with `kedro ipython`
 isort~=5.0 # Used for linting code with `kedro lint`
 jupyter~=1.0 # Used to open a Kedro-session in Jupyter Notebook & Lab
 jupyterlab~=3.0 # Used to open a Kedro-session in Jupyter Lab
-kedro~=0.18.2
+kedro~=0.18.3
 nbstripout~=0.4 # Strips the output of a Jupyter Notebook and writes the outputless version to the original file
 pytest-cov~=3.0 # Produces test coverage reports
 pytest-mock>=1.7.1, <2.0 # Wrapper around the mock package for easier use with pytest
@@ -45,7 +45,7 @@ The dependencies above might be sufficient for some projects, but for this tutor
 Add the following lines to your `src/requirements.txt` file:
 
 ```text
-kedro[pandas.CSVDataSet, pandas.ExcelDataSet, pandas.ParquetDataSet]==0.18.2   # Specify optional Kedro dependencies
+kedro[pandas.CSVDataSet, pandas.ExcelDataSet, pandas.ParquetDataSet]==0.18.3   # Specify optional Kedro dependencies
 kedro-viz~=5.0                                                                 # Visualise your pipelines
 scikit-learn~=1.0                                                              # For modelling in the data science pipeline
 ```

docs/source/tutorial/visualise_pipeline.md

@@ -110,7 +110,7 @@ We have also used the Plotly integration to allow users to [visualise metrics fr
 
 You must update the `requirements.txt` file in your Kedro project and add the following datasets to enable Plotly for your project.
 
-`kedro[plotly.PlotlyDataSet, plotly.JSONDataSet]==0.18.2`
+`kedro[plotly.PlotlyDataSet, plotly.JSONDataSet]==0.18.3`
 
 
 You can view Plotly charts in Kedro-Viz when you use Kedro's plotly datasets.
@@ -248,7 +248,7 @@ The MatplotlibWriter dataset converts Matplotlib objects to image files. This me
 You can view Matplotlib charts in Kedro-Viz when you use the [Kedro MatplotLibWriter dataset](/kedro.extras.datasets.matplotlib.MatplotlibWriter). You must update the `src/requirements.txt` file in your Kedro project by adding the following dataset to enable Matplotlib for your project:
 
 ```
-kedro[matplotlib.MatplotlibWriter]==0.18.2
+kedro[matplotlib.MatplotlibWriter]==0.18.3
 ```
 
 To use this dataset, configure your plot in your Kedro node. The below functions should be added to the `nodes.py` and `pipeline.py` files respectively.

kedro/__init__.py

@@ -3,7 +3,7 @@
 configuration and pipeline assembly.
 """
 
-__version__ = "0.18.2"
+__version__ = "0.18.3"
 
 
 import logging