[Ready] Add video embeds of course to docs

docs/source/conf.py

@@ -54,6 +54,7 @@
     "notfound.extension",
     "sphinxcontrib.jquery",
     "sphinx.ext.intersphinx",
+    "sphinxcontrib.youtube",
 ]
 
 # enable autosummary plugin  (table of contents for modules/classes/class

docs/source/course/index.md

@@ -4,6 +4,11 @@ If you like to learn from video, you can follow our [hands-on course "Introducti
 
 The course is structured into sections and these are each broken into short videos that cover specific Kedro topics. You'll walk through the [spaceflights tutorial](../tutorial/spaceflights_tutorial.md) and get hands-on with the example. Along the way, you'll learn key Kedro concepts like datasets and the Kedro Data Catalog, nodes and pipelines, and configuration management.
 
+```{eval-rst}
+..  youtube:: DD7JuYKp6BA
+    :width: 100%
+```
+
 ## Who is this course for?
 
 This course is for data scientists, data engineers and machine learning engineers. You can be junior, mid-level or senior in your field of work. You're likely to be hands-on with projects, or a decision-maker who regularly makes design and implementation choices about Python data products.

docs/source/introduction/index.md

@@ -2,6 +2,11 @@
 
 Kedro is an open-source Python framework to create reproducible, maintainable, and modular data science code. It uses software engineering best practices to help you build production-ready data science pipelines.
 
+```{eval-rst}
+..  youtube:: PdNkECqvI58
+    :width: 100%
+```
+
 Kedro is hosted by the [LF AI & Data Foundation](https://lfaidata.foundation/), and you can find the [Kedro source code on GitHub](https://github.com/kedro-org/kedro).
 
 In the following chapters, you will learn [how to set up Kedro](../get_started/install.md) and discover the [key Kedro concepts](../get_started/kedro_concepts.md). You can then review the [spaceflights tutorial](../tutorial/tutorial_template.md) to get hands-on experience with a Kedro project.

docs/source/tutorial/add_another_pipeline.md

@@ -520,5 +520,4 @@ kedro run --runner=module.path.to.my.runner
 
 `ParallelRunner` performs task parallelisation via multiprocessing, while `ThreadRunner` is intended for use with remote execution engines such as [Spark](../integrations/pyspark_integration.md) and {class}`Dask<kedro-datasets:kedro_datasets.dask.ParquetDataset>`.
 
-
 You can find out more about the runners Kedro provides, and how to create your own, in the [pipeline documentation about runners](../nodes_and_pipelines/run_a_pipeline.md).

docs/source/tutorial/create_a_pipeline.md

@@ -20,6 +20,14 @@ The data processing pipeline prepares the data for model building by combining t
 ```{note}
 Kedro provides the `kedro pipeline create` command to add the skeleton code for a new pipeline. If you are writing a project from scratch and want to add a new pipeline, run the following from the terminal: `kedro pipeline create <pipeline_name>`. You do **not** need to do this in the spaceflights example as it is already supplied by the starter project.
 ```
+### Watch the video
+
+The [hands-on video course](../course/index.md#learn-kedro-with-hands-on-video) walks through data exploration and data processing for the spaceflights data. There are several videos in the playlist that cover the topic starting with the following:
+
+```{eval-rst}
+..  youtube:: bZD8N0yv3Fs
+    :width: 100%
+```
 
 ## Data preprocessing node functions
 
@@ -342,6 +350,13 @@ This command automatically opens a browser tab to serve the visualisation at `ht
 
 To exit, close the browser tab. To regain control of the terminal, enter `^+c` on Mac or `Ctrl+c` on Windows or Linux machines.
 
+### Watch the video
+
+```{eval-rst}
+..  youtube:: KWqSzbHgNW4
+    :width: 100%
+```
+
 ## Checkpoint
 
 This is an excellent place to take a breath and summarise what you have seen in the example so far.

docs/source/tutorial/set_up_data.md

@@ -116,6 +116,13 @@ When you have finished, close `ipython` session with `exit()`.
 
 ## Further information
 
+### Watch the video
+
+```{eval-rst}
+..  youtube:: rl2cncGxyts
+    :width: 100%
+```
+
 ### Custom data
 
 {py:mod}`Kedro supports numerous datasets <kedro-datasets:kedro_datasets>` out of the box, but you can also add support for any proprietary data format or filesystem.

docs/source/tutorial/spaceflights_tutorial.md

@@ -24,6 +24,12 @@ spaceflights_tutorial_faqs
 
 Photo by <a href="https://unsplash.com/@ivvndiaz">Ivan Diaz</a> on <a href="https://unsplash.com/s/photos/spaceship">Unsplash</a>
 
+## Watch the video
+
+```{eval-rst}
+..  youtube:: YBY2Lcz7Gw4
+    :width: 100%
+```
 
 ## Get help
 If you encounter an issue with the tutorial:

pyproject.toml

@@ -98,6 +98,7 @@ docs = [
     "ipykernel>=5.3, <7.0",
     "myst-parser>=1.0,<2.1",
     "Jinja2<3.2.0",
+    "sphinxcontrib-youtube",
 ]
 all = [ "kedro[test,docs]" ]