Update kedro version (#2092)

CITATION.cff

@@ -17,8 +17,14 @@ authors:
   given-names: Tynan
 - family-names: Hoang
   given-names: Lim
+- family-names: Holzer
+  given-names: Jannic
 - family-names: Kanchwala
   given-names: Rashida
+- family-names: Katiyar
+  given-names: Ankita
+- family-names: Koh
+  given-names: Amanda
 - family-names: Mackay
   given-names: Andrew
 - family-names: Merali
@@ -33,9 +39,11 @@ authors:
   given-names: Nero
 - family-names: Schwarzmann
   given-names: Joel
+- family-names: Stichbury
+  given-names: Jo
 - family-names: Theisen
   given-names: Merel
 title: Kedro
-version: 0.18.3
-date-released: 2022-09-20
+version: 0.18.4
+date-released: 2022-12-05
 url: https://github.com/kedro-org/kedro

RELEASE.md

@@ -8,7 +8,15 @@
 
 ## Migration guide from Kedro 0.18.* to 0.19.*
 
-# Upcoming Release 0.18.4
+# Upcoming Release 0.18.5
+
+## Major features and improvements
+
+## Bug fixes and other changes
+
+## Breaking changes to the API
+
+# Release 0.18.4
 
 ## 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.
@@ -33,7 +41,7 @@
 * Updated Experiment Tracking docs with working examples.
 * Updated MatplotlibWriter Dataset, 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 it's own module to ensure multiprocessing works with it.
+* 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.

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~=0.18.3"
+pip install "kedro~=0.18.4"
 # 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 `0.18.3`
+* Install the latest version of Kedro compatible with version `0.18.4`
 
 ```console
-%pip install "kedro[spark.SparkDataSet]~=0.18.3"
+%pip install "kedro[spark.SparkDataSet]~=0.18.4"
 ```
 
 * 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
 | |/ / _ \/ _` | '__/ _ \
 |   <  __/ (_| | | | (_) |
 |_|\_\___|\__,_|_|  \___/
-v0.18.3
+v0.18.4
 
 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. `0.18.3.`. 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`.
+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. `0.18.4.`. 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

@@ -17,7 +17,7 @@ Don't forget to check the [tutorial FAQ](spaceflights_tutorial_faqs.md) if you r
 If you have not yet set up Kedro, do so by [following the guidelines to install Kedro](../get_started/install.md).
 
 ```{important}
-We recommend that you use the same version of Kedro that was most recently used to test this tutorial (0.18.3).
+We recommend that you use the same version of Kedro that was most recently used to test this tutorial (0.18.4).
 ```
 
 In your terminal window, navigate to the folder you want to store the project and type the following to create an empty project:
@@ -73,7 +73,7 @@ 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]==0.18.3   # Specify optional Kedro dependencies
+kedro[pandas.CSVDataSet, pandas.ExcelDataSet, pandas.ParquetDataSet]==0.18.4   # Specify optional Kedro dependencies
 kedro-viz~=5.0                                                                 # Visualise your pipelines
 scikit-learn~=1.0                                                              # For modelling in the data science pipeline
 ```

docs/source/visualisation/visualise_charts_with_plotly.md

@@ -10,7 +10,7 @@ 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]==0.18.3`
+`kedro[plotly.PlotlyDataSet, plotly.JSONDataSet]==0.18.4`
 
 
 You can view Plotly charts in Kedro-Viz when you use Kedro's plotly datasets.
@@ -155,7 +155,7 @@ 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]==0.18.3
+kedro[matplotlib.MatplotlibWriter]==0.18.4
 ```
 
 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__ = "0.18.3"
+__version__ = "0.18.4"
 
 
 import logging