Bump up version to 0.17.0 (#924)

docs/source/03_tutorial/02_tutorial_template.md

@@ -34,7 +34,7 @@ isort>=4.3.21, <5.0 # Used for linting code with `kedro lint`
 jupyter~=1.0 # Used to open a Kedro-session in Jupyter Notebook & Lab
 jupyter_client>=5.1.0, <7.0 # Used to open a Kedro-session in Jupyter Notebook & Lab
 jupyterlab==0.31.1 # Used to open a Kedro-session in Jupyter Lab
-kedro==0.16.6
+kedro==0.17.0
 kedro-viz~=3.1
 nbstripout==0.3.3 # Strips the output of a Jupyter Notebook and writes the outputless version to the original file
 pytest-cov~=2.5 # Produces test coverage reports
@@ -53,10 +53,10 @@ The dependencies above may be sufficient for some projects, but for the spacefli
 pip install kedro[pandas.CSVDataSet,pandas.ExcelDataSet]
 ```
 
-Alternatively, if you need to, you can edit `src/requirements.txt` directly to modify your list of dependencies by replacing the requirement `kedro==0.16.6` with the following (your version of Kedro may be different):
+Alternatively, if you need to, you can edit `src/requirements.txt` directly to modify your list of dependencies by replacing the requirement `kedro==0.17.0` with the following (your version of Kedro may be different):
 
 ```text
-kedro[pandas.CSVDataSet,pandas.ExcelDataSet]==0.16.6
+kedro[pandas.CSVDataSet,pandas.ExcelDataSet]==0.17.0
 ```
 
 Then run the following:

docs/source/04_kedro_project_setup/02_configuration.md

@@ -3,7 +3,7 @@
 
 This section contains detailed information about configuration, for which the relevant API documentation can be found in [kedro.config.ConfigLoader](/kedro.config.ConfigLoader)
 
-> *Note:* This documentation is based on `Kedro 0.16.6`, if you spot anything that is incorrect then please create an [issue](https://github.com/quantumblacklabs/kedro/issues) or pull request.
+> *Note:* This documentation is based on `Kedro 0.17.0`, if you spot anything that is incorrect then please create an [issue](https://github.com/quantumblacklabs/kedro/issues) or pull request.
 
 ## Local and base configuration
 

docs/source/05_data/01_data_catalog.md

@@ -1,6 +1,6 @@
 # The Data Catalog
 
-> *Note:* This documentation is based on `Kedro 0.16.6`, if you spot anything that is incorrect then please create an [issue](https://github.com/quantumblacklabs/kedro/issues) or pull request.
+> *Note:* This documentation is based on `Kedro 0.17.0`, if you spot anything that is incorrect then please create an [issue](https://github.com/quantumblacklabs/kedro/issues) or pull request.
 
 This section introduces `catalog.yml`, the project-shareable Data Catalog. The file is located in `conf/base` and is a registry of all data sources available for use by a project; it manages loading and saving of data.
 

docs/source/05_data/02_kedro_io.md

@@ -3,7 +3,7 @@
 
 In this tutorial, we cover advanced uses of the [Kedro IO](/kedro.io.rst) module to understand the underlying implementation. The relevant API documentation is [kedro.io.AbstractDataSet](/kedro.io.AbstractDataSet) and [kedro.io.DataSetError](/kedro.io.DataSetError).
 
-> *Note:* This documentation is based on `Kedro 0.16.6`, if you spot anything that is incorrect then please create an [issue](https://github.com/quantumblacklabs/kedro/issues) or pull request.
+> *Note:* This documentation is based on `Kedro 0.17.0`, if you spot anything that is incorrect then please create an [issue](https://github.com/quantumblacklabs/kedro/issues) or pull request.
 
 ## Error handling
 

docs/source/06_nodes_and_pipelines/01_nodes.md

@@ -4,7 +4,7 @@ In this section we introduce the concept of a node, for which the relevant API d
 
 Nodes are the building blocks of pipelines and represent tasks. Pipelines are used to combine nodes to build workflows, which range from simple machine learning workflows to end-to-end production workflows.
 
-> *Note:* This documentation is based on `Kedro 0.16.6`, if you spot anything that is incorrect then please create an [issue](https://github.com/quantumblacklabs/kedro/issues) or pull request.
+> *Note:* This documentation is based on `Kedro 0.17.0`, if you spot anything that is incorrect then please create an [issue](https://github.com/quantumblacklabs/kedro/issues) or pull request.
 
 You will first need to import libraries from Kedro and other standard tools to run the code snippets demonstrated below.
 

docs/source/06_nodes_and_pipelines/02_pipeline_introduction.md

@@ -1,6 +1,6 @@
 # Pipelines
 
-> *Note:* This documentation is based on `Kedro 0.16.6`, if you spot anything that is incorrect then please create an [issue](https://github.com/quantumblacklabs/kedro/issues) or pull request.
+> *Note:* This documentation is based on `Kedro 0.17.0`, if you spot anything that is incorrect then please create an [issue](https://github.com/quantumblacklabs/kedro/issues) or pull request.
 
 We previously introduced [Nodes](./01_nodes.md) as building blocks that represent tasks, and which can be combined in a pipeline to build your workflow.  A pipeline organises the dependencies and execution order of your collection of nodes, and connects inputs and outputs while keeping your code modular. The pipeline determines the node execution order by resolving dependencies and does *not* necessarily run the nodes in the order in which they are passed in.
 

docs/source/06_nodes_and_pipelines/03_modular_pipelines.md

@@ -1,6 +1,6 @@
 # Modular pipelines
 
-> *Note:* This documentation is based on `Kedro 0.16.6`, if you spot anything that is incorrect then please create an [issue](https://github.com/quantumblacklabs/kedro/issues) or pull request.
+> *Note:* This documentation is based on `Kedro 0.17.0`, if you spot anything that is incorrect then please create an [issue](https://github.com/quantumblacklabs/kedro/issues) or pull request.
 
 ## What are modular pipelines?
 

docs/source/07_extend_kedro/04_plugins.md

@@ -1,7 +1,7 @@
 # Kedro plugins
 
 
-> *Note:* This documentation is based on `Kedro 0.16.6`, if you spot anything that is incorrect then please create an [issue](https://github.com/quantumblacklabs/kedro/issues) or pull request.
+> *Note:* This documentation is based on `Kedro 0.17.0`, if you spot anything that is incorrect then please create an [issue](https://github.com/quantumblacklabs/kedro/issues) or pull request.
 
 Kedro plugins allow you to create new features for Kedro and inject additional commands into the CLI. Plugins are developed as separate Python packages that exist outside of any Kedro project.
 

docs/source/08_logging/01_logging.md

@@ -1,6 +1,6 @@
 # Logging
 
-> *Note:* This documentation is based on `Kedro 0.16.6`, if you spot anything that is incorrect then please create an [issue](https://github.com/quantumblacklabs/kedro/issues) or pull request.
+> *Note:* This documentation is based on `Kedro 0.17.0`, if you spot anything that is incorrect then please create an [issue](https://github.com/quantumblacklabs/kedro/issues) or pull request.
 
 Kedro uses, and facilitates, the use of Python’s `logging` library by providing a default logging configuration. This can be found in `conf/base/logging.yml` in every project generated using Kedro’s CLI `kedro new` command.
 

docs/source/08_logging/02_journal.md

@@ -1,7 +1,7 @@
 # Journal
 
 
-> *Note:* This documentation is based on `Kedro 0.16.6`, if you spot anything that is incorrect then please create an [issue](https://github.com/quantumblacklabs/kedro/issues) or pull request.
+> *Note:* This documentation is based on `Kedro 0.17.0`, if you spot anything that is incorrect then please create an [issue](https://github.com/quantumblacklabs/kedro/issues) or pull request.
 
 ## Overview
 
@@ -18,7 +18,7 @@ A context journal record captures all the necessary information to reproduce the
     "run_id": "2019-10-01T09.15.57.289Z",
     "project_path": "<path-to-project>/src/kedro-tutorial",
     "env": "local",
-    "kedro_version": "0.16.6",
+    "kedro_version": "0.17.0",
     "tags": [],
     "from_nodes": [],
     "to_nodes": [],

docs/source/09_development/01_set_up_vscode.md

@@ -1,7 +1,7 @@
 # Set up Visual Studio Code
 
 
-> *Note:* This documentation is based on `Kedro 0.16.6`, if you spot anything that is incorrect then please create an [issue](https://github.com/quantumblacklabs/kedro/issues) or pull request.
+> *Note:* This documentation is based on `Kedro 0.17.0`, if you spot anything that is incorrect then please create an [issue](https://github.com/quantumblacklabs/kedro/issues) or pull request.
 
 Start by opening a new project directory in VS Code and installing the Python plugin under **Tools and languages**:
 

docs/source/09_development/02_set_up_pycharm.md

@@ -1,6 +1,6 @@
 # Set up PyCharm
 
-> *Note:* This documentation is based on `Kedro 0.16.6`, if you spot anything that is incorrect then please create an [issue](https://github.com/quantumblacklabs/kedro/issues) or pull request.
+> *Note:* This documentation is based on `Kedro 0.17.0`, if you spot anything that is incorrect then please create an [issue](https://github.com/quantumblacklabs/kedro/issues) or pull request.
 
 This section will present a quick guide on how to configure [PyCharm](https://www.jetbrains.com/pycharm/) as a development environment for working on Kedro projects.
 

docs/source/09_development/03_commands_reference.md

@@ -1,6 +1,6 @@
 # Kedro's command line interface
 
-> *Note:* This documentation is based on `Kedro 0.16.6`, if you spot anything that is incorrect then please create an [issue](https://github.com/quantumblacklabs/kedro/issues) or pull request.
+> *Note:* This documentation is based on `Kedro 0.17.0`, if you spot anything that is incorrect then please create an [issue](https://github.com/quantumblacklabs/kedro/issues) or pull request.
 
 Kedro's command line interface (CLI) is used to give commands to Kedro via a terminal shell (such as the terminal app on macOS, or cmd.exe or PowerShell on Windows). You need to use the CLI to set up a new Kedro project, and to run it.
 
@@ -115,7 +115,7 @@ Returns output similar to the following, depending on the version of Kedro used
 | |/ / _ \/ _` | '__/ _ \
 |   <  __/ (_| | | | (_) |
 |_|\_\___|\__,_|_|  \___/
-v0.16.6
+v0.17.0
 
 kedro allows teams to create analytics
 projects. It is developed as part of

docs/source/09_development/04_lint.md

@@ -2,7 +2,7 @@
 
 To follow these instructions, you will need to install the  `pylint` package, subject to GPL licence.
 
-> *Note:* This documentation is based on `Kedro 0.16.6`, if you spot anything that is incorrect then please create an [issue](https://github.com/quantumblacklabs/kedro/issues) or pull request.
+> *Note:* This documentation is based on `Kedro 0.17.0`, if you spot anything that is incorrect then please create an [issue](https://github.com/quantumblacklabs/kedro/issues) or pull request.
 
 You can lint your project code to ensure code quality using the `kedro lint` command, your project is linted with [`black`](https://github.com/psf/black) (projects created with Python 3.6 and above), [`flake8`](https://gitlab.com/pycqa/flake8) and [`isort`](https://github.com/timothycrosley/isort). If you prefer to use [pylint](https://www.pylint.org/), a popular linting tool, then the sample commands you can use to help with this are included in the script below:
 

docs/source/09_development/05_debugging.md

@@ -1,6 +1,6 @@
 # Debugging
 
-> *Note:* This documentation is based on `Kedro 0.16.6`, if you spot anything that is incorrect then please create an [issue](https://github.com/quantumblacklabs/kedro/issues) or pull request.
+> *Note:* This documentation is based on `Kedro 0.17.0`, if you spot anything that is incorrect then please create an [issue](https://github.com/quantumblacklabs/kedro/issues) or pull request.
 
 ## Introduction
 

docs/source/10_deployment/08_databricks.md

@@ -1,7 +1,7 @@
 # Deployment to a Databricks cluster
 
 
-> *Note:* This documentation is based on `Kedro 0.16.6`, if you spot anything that is incorrect then please create an [issue](https://github.com/quantumblacklabs/kedro/issues) or pull request.
+> *Note:* This documentation is based on `Kedro 0.17.0`, if you spot anything that is incorrect then please create an [issue](https://github.com/quantumblacklabs/kedro/issues) or pull request.
 
 This tutorial uses the [PySpark Iris Kedro Starter](https://github.com/quantumblacklabs/kedro-starter-pyspark-iris) to illustrate how to bootstrap a Kedro project using Spark and deploy it to a [Databricks cluster on AWS](https://databricks.com/aws). It is split into 2 sections:
 
@@ -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~=0.16.6"
+pip install "kedro~=0.17.0"
 # name your project Iris Databricks when prompted for it
 kedro new --starter pyspark-iris
 ```
@@ -305,10 +305,10 @@ In your newly created notebook put each code snippet from below into a separate
 %sh rm -rf ~/projects/iris-databricks && git clone --single-branch --branch master 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 `0.16.6`
+* Install the latest version of Kedro compatible with version `0.17.0`
 
 ```console
-%pip install "kedro[spark.SparkDataSet]~=0.16.6"
+%pip install "kedro[spark.SparkDataSet]~=0.17.0"
 ```
 
 * Copy input data into DBFS

docs/source/10_deployment/09_aws_sagemaker.md

@@ -1,7 +1,7 @@
 # How to integrate Amazon SageMaker into your Kedro pipeline
 
 
-> *Note:* This documentation is based on `Kedro 0.16.6`, if you spot anything that is incorrect then please create an [issue](https://github.com/quantumblacklabs/kedro/issues) or pull request.
+> *Note:* This documentation is based on `Kedro 0.17.0`, if you spot anything that is incorrect then please create an [issue](https://github.com/quantumblacklabs/kedro/issues) or pull request.
 
 This tutorial explains how to integrate a Kedro project with [Amazon SageMaker](https://aws.amazon.com/sagemaker/) in order to train a machine learning model. It shows how to build machine learning pipelines in Kedro and while taking advantage of the power of SageMaker for potentially compute-intensive machine learning tasks.
 

docs/source/11_tools_integration/01_pyspark.md

@@ -1,6 +1,6 @@
 # Build a Kedro pipeline with PySpark
 
-> *Note:* This documentation is based on `Kedro 0.16.6`, if you spot anything that is incorrect then please create an [issue](https://github.com/quantumblacklabs/kedro/issues) or pull request.
+> *Note:* This documentation is based on `Kedro 0.17.0`, if you spot anything that is incorrect then please create an [issue](https://github.com/quantumblacklabs/kedro/issues) or pull request.
 
 This page outlines some best practices when building a Kedro pipeline with [`PySpark`](https://spark.apache.org/docs/latest/api/python/index.html). It assumes a basic understanding of both Kedro and `PySpark`.
 

docs/source/11_tools_integration/02_ipython.md

@@ -1,6 +1,6 @@
 # Use Kedro with IPython and Jupyter Notebooks/Lab
 
-> *Note:* This documentation is based on `Kedro 0.16.6`, if you spot anything that is incorrect then please create an [issue](https://github.com/quantumblacklabs/kedro/issues) or pull request.
+> *Note:* This documentation is based on `Kedro 0.17.0`, if you spot anything that is incorrect then please create an [issue](https://github.com/quantumblacklabs/kedro/issues) or pull request.
 
 This section follows the [Iris dataset example](../02_get_started/05_example_project.md) and demonstrates how to use Kedro with IPython and Jupyter Notebooks / Lab. We also recommend a video that explains the transition from the use of vanilla Jupyter Notebooks to using Kedro, from [Data Engineer One](https://www.youtube.com/watch?v=dRnCovp1GRQ&t=50s&ab_channel=DataEngineerOne).
 

docs/source/12_faq/02_architecture_overview.md

@@ -1,7 +1,7 @@
 # Kedro architecture overview
 
 
-> *Note:* This documentation is based on `Kedro 0.16.6`, if you spot anything that is incorrect then please create an [issue](https://github.com/quantumblacklabs/kedro/issues) or pull request.
+> *Note:* This documentation is based on `Kedro 0.17.0`, if you spot anything that is incorrect then please create an [issue](https://github.com/quantumblacklabs/kedro/issues) or pull request.
 
 Here is a diagram showing high-level architecture of Kedro library:
 

kedro/__init__.py

@@ -31,7 +31,7 @@
 configuration and pipeline assembly.
 """
 
-__version__ = "0.16.6"
+__version__ = "0.17.0"
 
 
 import logging