PyNWB Mini Course

Running the app

To start the local development server, install Gatsby and then all other dependencies. This should serve up the app on localhost:8000.

npm install -g gatsby-cli  # Install Gatsby globally
npm install                # Install dependencies
npm run dev                # Run the development server

🎨 Customization

The app separates its source and content – so you usually shouldn't have to dig into the JavaScript source to change things. The following points of customization are available:

Location	Description
meta.json	General config settings, title, description etc.
theme.sass	Color theme.
binder/requirements.txt	Python requirements to install.
chapters	The chapters, one Markdown file per chapter.
slides	The slides, one Markdown file per slide deck.
static	Static assets like images, will be copied to the root.

meta.json

The following meta settings are available. Note that you have to re-start Gatsby to see the changes if you're editing it while the server is running.

Setting	Description
courseId	Unique ID of the course. Will be used when saving completed exercises to the browser's local storage.
title	The title of the course.
slogan	Course slogan, displayed in the page title on the front page.
description	Course description. Used for site meta and in footer.
bio	Author bio. Used in the footer.
siteUrl	URL of the deployed site (without trailing slash).
twitter	Author twitter handle, used in Twitter cards meta.
fonts	Google Fonts to load. Should be the font part of the URL in the embed string, e.g. Lato:400,400i,700,700i.
testTemplate	Template used to validate the answers. ${solution} will be replaced with the user code and ${test} with the contents of the test file.
juniper.repo	Repo to build on Binder in user/repo format. Usually the same as this repo.
juniper.branch	Branch to build. Ideally not master, so the image is not rebuilt every time you push.
juniper.lang	Code language for syntax highlighting.
juniper.kernelType	The name of the kernel to use.
juniper.debug	Logs additional debugging info to the console.
showProfileImage	Whether to show the profile image in the footer. If true, a file static/profile.jpg needs to be available.
footerLinks	List of objects with "text" and "url" to display as links in the footer.
theme	Currently only used for the progressive web app, e.g. as the theme color on mobile. For the UI theme, edit theme.sass.

Static assets

All files added to /static will become available at the root of the deployed site. So /static/image.jpg can be referenced in your course as /image.jpg. The following assets need to be available and can be customized:

File	Description
icon.png	Custom favicon.
logo.svg	The course logo.
profile.jpg	Photo or profile image.
social.jpg	Social image, displayed in Twitter and Facebook cards.
icon_check.svg	"Check" icon displayed on "Mark as completed" button.
icon_slides.svg	Icon displayed in the corner of a slides exercise.

✏️ Content

File formats

Chapters

Chapters are placed in /chapters and are Markdown files consisting of <exercise> components. They'll be turned into pages, e.g. /chapter1. In their frontmatter block at the top of the file, they need to specify type: chapter, as well as the following meta:

---
title: The chapter title
description: The chapter description
prev: /chapter1 # exact path to previous chapter or null to not show a link
next: /chapter3 # exact path to next chapter or null to not show a link
id: 2 # unique identifier for chapter
type: chapter # important: this creates a standalone page from the chapter
---

Slides

Slides are placed in /slides and are markdown files consisting of slide content, separated by ---. They need to specify the following frontmatter block at the top of the file:

---
type: slides
---

The first and last slide use a special layout and will display the headline in the center of the slide. Speaker notes (in this case, the script) can be added at the end of a slide, prefixed by Notes:. They'll then be shown on the right next to the slides. Here's an example slides file:

---
type: slides
---

# Processing pipelines

Notes: This is a slide deck about processing pipelines.

---

# Next slide

- Some bullet points here
- And another bullet point

<img src="/image.jpg" alt="An image located in /static" />

Custom Elements

When using custom elements, make sure to place a newline between the opening/closing tags and the children. Otherwise, Markdown content may not render correctly.

<exercise>

Container of a single exercise.

Argument	Type	Description
id	number / string	Unique exercise ID within chapter.
title	string	Exercise title.
type	string	Optional type. "slides" makes container wider and adds icon.
children	-	The contents of the exercise.

<exercise id="1" title="Introduction to spaCy">

Content goes here...

</exercise>

<codeblock>

Argument	Type	Description
id	number / string	Unique identifier of the code exercise.
source	string	Name of the source file (without file extension). Defaults to exc_${id} if not set.
solution	string	Name of the solution file (without file extension). Defaults to solution_${id} if not set.
test	string	Name of the test file (without file extension). Defaults to test_${id} if not set.
children	string	Optional hints displayed when the user clicks "Show hints".

<codeblock id="02_03">

This is a hint!

</codeblock>

<slides>

Container to display slides interactively using Reveal.js and a Markdown file.

Argument	Type	Description
source	string	Name of slides file (without file extension).

<slides source="chapter1_01_introduction-to-spacy">
</slides>

<choice>

Container for multiple-choice question.

Argument	Type	Description
id	string / number	Optional unique ID. Can be used if more than one choice question is present in one exercise.
children	nodes	Only <opt> components for the options.

<choice>

<opt text="Option one">You have selected option one! This is not good.</opt>
<opt text="Option two" correct="true">Yay! </opt>

</choice>

<opt>

A multiple-choice option.

Argument	Type	Description
text	string	The option text to be displayed. Supports inline HTML.
correct	string	"true" if the option is the correct answer.
children	string	The text to be displayed if the option is selected (explaining why it's correct or incorrect).

Setting up Binder

The requirements.txt in the repository defines the packages that are installed when building it with Binder. You can specify the binder settings like repo, branch and kernel type in the "juniper" section of the meta.json. I'd recommend running the very first build via the interface on the Binder website, as this gives you a detailed build log and feedback on whether everything worked as expected. Enter your repository URL, click "launch" and wait for it to install the dependencies and build the image.

Adding tests

To validate the code when the user hits "Submit", we're currently using a slightly hacky trick. Since the Python code is sent back to the kernel as a string, we can manipulate it and add tests – for example, exercise exc_01_02_01.py will be validated using test_01_02_01.py (if available). The user code and test are combined using a string template. At the moment, the testTemplate in the meta.json looks like this:

from wasabi import Printer
__msg__ = Printer()
__solution__ = """${solution}"""
${solution}

${test}
try:
    test()
except AssertionError as e:
    __msg__.fail(e)

If present, ${solution} will be replaced with the string value of the submitted user code. In this case, we're inserting it twice: once as a string so we can check whether the submission includes something, and once as the code, so we can actually run it and check the objects it creates. ${test} is replaced by the contents of the test file. It's also making wasabi's printer available as __msg__, so we can easily print pretty messages in the tests. Finally, the try/accept block checks if the test function raises an AssertionError and if so, displays the error message. This also hides the full error traceback (which can easily leak the correct answers).

A test file could then look like this:

def test():
    assert "spacy.load" in __solution__, "Are you calling spacy.load?"
    assert nlp.meta["lang"] == "en", "Are you loading the correct model?"
    assert nlp.meta["name"] == "core_web_sm", "Are you loading the correct model?"
    assert "nlp(text)" in __solution__, "Are you processing the text correctly?"
    assert "print(doc.text)" in __solution__, "Are you printing the Doc's text?"

    __msg__.good(
        "Well done! Now that you've practiced loading models, let's look at "
        "some of their predictions."
    )

The string answer is available as __solution__, and the test also has access to the solution code.

---

For more details on how it all works behind the scenes, see the original course repo.