👩‍🏫 Advanced NLP with spaCy: A free online course
# Advanced NLP with spaCy: A free online course

This repo contains both an [**online course**](https://course.spacy.io), as well
as its modern open-source web framework. In the course, you'll learn how to use
[spaCy](https://spacy.io) to build advanced natural language understanding
systems, using both rule-based and machine learning approaches. The front-end is
powered by [Gatsby](http://gatsbyjs.org/), [Reveal.js](https://revealjs.com) and
[Plyr](https://github.com/sampotts/plyr), and the back-end code execution uses
[Binder](https://mybinder.org) 💖 It's all open-source and published under the
MIT license (code and framework) and CC BY-NC (spaCy course materials).

_This course is mostly intended for **self-study**. Yes, you can cheat – the
solutions are all in this repo, there's no penalty for clicking "Show hints" or
"Show solution", and you can mark an exercise as done when you think it's done._

[![Azure Pipelines](https://img.shields.io/azure-devops/build/explosion-ai/public/10/master.svg?logo=azure-devops&style=flat-square)](https://dev.azure.com/explosion-ai/public/_build?definitionId=10)
![Netlify Status](https://api.netlify.com/api/v1/badges/2eae6a1a-d7a3-437e-a700-61e32d7d991b/deploy-status)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/explosion/spacy-course/master)

## 💬 Languages and Translations

| Language                                     | Text Examples<sup>1</sup> | Source                                                       | Authors                                                                                                                                                                                                                                                                                                                                                                                                                                              |
| -------------------------------------------- | ------------------------- | ------------------------------------------------------------ | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **[English](https://course.spacy.io/en)**    | English                   | [`chapters/en`](chapters/en), [`exercises/en`](exercises/en) | [@ines](https://github.com/ines)                                                                                                                                                                                                                                                                                                                                                                                                                     |
| **[German](https://course.spacy.io/de)**     | German                    | [`chapters/de`](chapters/de), [`exercises/de`](exercises/de) | [@ines](https://github.com/ines), [@Jette16](https://github.com/Jette16)                                                                                                                                                                                                                                                                                                                                                                             |
| **[Spanish](https://course.spacy.io/es)**    | Spanish                   | [`chapters/es`](chapters/es), [`exercises/es`](exercises/es) | [@mariacamilagl](https://github.com/mariacamilagl), [@damian-romero](https://github.com/damian-romero)                                                                                                                                                                                                                                                                                                                                               |
| **[French](https://course.spacy.io/fr)**     | French                    | [`chapters/fr`](chapters/fr), [`exercises/fr`](exercises/fr) | [@datakime](https://github.com/datakime)                                                                                                                                                                                                                                                                                                                                                                                                             |
| **[Japanese](https://course.spacy.io/ja)**   | Japanese                  | [`chapters/ja`](chapters/ja), [`exercises/ja`](exercises/ja) | [@tamuhey](https://github.com/tamuhey), [@hiroshi-matsuda-rit](https://github.com/hiroshi-matsuda-rit), [@icoxfog417](https://github.com/icoxfog417), [@akirakubo](https://github.com/akirakubo), [@forest1988](https://github.com/forest1988), [@ao9mame](https://github.com/ao9mame), [@matsurih](https://github.com/matsurih), [@HiromuHota](https://github.com/HiromuHota), [@mei28](https://github.com/mei28), [@polm](https://github.com/polm) |
| **[Chinese](https://course.spacy.io/zh)**    | Chinese                   | [`chapters/zh`](chapters/zh), [`exercises/zh`](exercises/zh) | [@crownpku](https://github.com/crownpku)                                                                                                                                                                                                                                                                                                                                                                                                             |
| **[Portuguese](https://course.spacy.io/pt)** | English                   | [`chapters/pt`](chapters/pt), [`exercises/pt`](exercises/pt) | [@Cristianasp](https://github.com/Cristianasp)                                                                                                                                                                                                                                                                                                                                                                                                       |

If you spot a mistake, I always appreciate
[pull requests](https://github.com/explosion/spacy-course/pulls)!

**1.** This is the language used for the text examples and resources used in the
exercises. For example, the German version of the course also uses German text
examples and models. It's not always possible to translate all code examples, so
some translations may still use and analyze English text as part of the course.

### Related resources

- 📚 **Prefer notebooks?** Check out
  [the Jupyter notebook version](https://github.com/cristianasp/spacy) of this
  course, put together by [@cristianasp](https://github.com/cristianasp).

## 💁 FAQ

#### Is this related to the spaCy course on DataCamp?

I originally developed the content for DataCamp, but I wanted to make a free
version to make it available to more people, and so you don't have to sign up
for their service. As a weekend project, I ended up putting together my own
little app to present the exercises and content in a fun and interactive way.

#### Can I use this to build my own course?

Probably, yes! If you've been looking for a DIY way to publish your materials, I
hope that my little framework can be useful. Because so many people expressed
interest in this, I put together some starter repos that you can fork and adapt:

- 🐍 Python:
  [`ines/course-starter-python`](https://github.com/ines/course-starter-python)
- 🇷 R: [`ines/course-starter-r`](https://github.com/ines/course-starter-r)

#### Why the different licenses?

The source of the app, UI components and Gatsby framework for building
interactive courses is licensed as MIT, like pretty much all of my open-source
software. The course materials themselves (slides and chapters), are licensed
under CC BY-NC. This means that you can use them freely – you just can't make
money off them.

#### I want to help translate this course into my language. How can I contribute?

First, thanks so much, this is really cool and valuable to the community 🙌 I've
tried to set up the course structure so it's easy to add different languages:
language-specific files are organized into directories in
[`exercises`](exercises) and [`chapters`](chapters), and other language specific
texts are available in [`locale.json`](locale.json). If you want to contribute,
there are two different ways to get involved:

1. Start a community translation project. This is the easiest,
   no-strings-attached way. You can fork the repo, copy-paste the English
   version, change the
   [language code](https://www.loc.gov/standards/iso639-2/php/code_list.php),
   start translating and invite others to contribute (if you like). If you're
   looking for contributors, feel free to open an issue here or tag
   [@spacy_io](https://twitter.com/spacy_io) on Twitter so we can help get the
   word out. We're also happy to answer your questions on the issue tracker.

2. Make us an offer. We're open to commissioning translations for different
   languages, so if you're interested, email us at
   [contact@explosion.ai](mailto:contact@explosion.ai) and include your offer,
   estimated time schedule and a bit about you and your background (and any
   technical writing or translation work you've done in the past, if available).
   It doesn't matter where you're based, but you should be able to issue
   invoices as a freelancer or similar, depending on your country.

#### I want to help create an audio/video tutorial for an existing translation. How can I get involved?

Again, thanks, this is super cool! While the
[English](https://www.youtube.com/watch?v=THduWAnG97k) and
[German](https://www.youtube.com/watch?v=K1elwpgDdls) videos also include a
video recording, it's not a requirement and we'd be happy to just provide an
audio track alongside the slides. We'd take care of the postprocessing and video
editing, so all we need is the audio recording. If you feel comfortable
recording yourself reading out the slide notes in your language, email us at
[contact@explosion.ai](mailto:contact@explosion.ai) and make us an offer and
include a bit about you and similar work you've done in the past, if available.

## 🎛 Usage & API

### Running the app

To start the local development server, install [Gatsby](https://gatsbyjs.org)
and then all other dependencies, then use `npm run dev` to start the development
server. Make sure you have at least Node 10.15 installed.

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

If running with docker just run `make build` and then `make gatsby-dev`

### How it works

When building the site, Gatsby will look for `.py` files and make their contents
available to query via GraphQL. This lets us use the raw code within the app.
Under the hood, the app uses [Binder](https://mybinder.org) to serve up an image
with the package dependencies, including the spaCy models. By calling into
[JupyterLab](https://jupyterlab.readthedocs.io/en/stable/), we can then execute
code using the active kernel. This lets you edit the code in the browser and see
the live results. Also see my [`juniper`](https://github.com/ines/juniper) repo
for more details on the implementation.

To validate the code when the user hits "Submit", I'm 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 msg
__msg__ = msg
__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. I'm also making
[`wasabi`](https://github.com/ines/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:

```python
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."
    )
```

With this approach, it's not _always_ possible to validate the input perfectly –
there are too many options and we want to avoid false positives.

#### Running automated tests

The automated tests make sure that the provided solution code is compatible with
the test file that's used to validate submissions. The test suite is powered by
the [`pytest`](https://docs.pytest.org/en/latest/) framework and runnable test
files are generated automatically in a directory `__tests__` before the test
session starts. See the [`conftest.py`](conftest.py) for implementation details.

```bash
# Install requirements
pip install -r binder/requirements.txt
# Run the tests (will generate the files automatically)
python -m pytest __tests__
```

If running with docker just run `make build` and then `make pytest`

### Directory Structure

```yaml
├── binder
|   └── requirements.txt  # Python dependency requirements for Binder
├── chapters              # chapters, grouped by language
|   ├── en                # English chapters, one Markdown file per language
|   |   └── slides        # English slides, one Markdown file per presentation
|   └── ...               # other languages
├── exercises             # code files, tests and assets for exercises
|   ├── en                # English exercises, solutions, tests and data
|   └── ...               # other languages
├── public                # compiled site
├── src                   # Gatsby/React source, independent from content
├── static                # static assets like images, available in slides/chapters
├── locale.json           # translations of meta and UI text
├── meta.json             # course metadata
└── theme.sass            # UI theme colors and settings
```

### Setting up Binder

The [`requirements.txt`](binder/requirements.txt) in the repository defines the
packages that are installed when building it with Binder. For this course, I'm
using the source repo as the Binder repo, as it allows to keep everything in one
place. It also lets the exercises reference and load other files (e.g. JSON),
which will be copied over into the Python environment. I build the binder from a
branch `binder`, though, which I only update if Binder-relevant files change.
Otherwise, every update to `master` would trigger an image rebuild.

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](https://mybinder.org), 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.

![Binder](https://user-images.githubusercontent.com/13643239/39412757-a518d416-4c21-11e8-9dad-8b4cc14737bc.png)

### File formats

#### Chapters

Chapters are placed in [`/chapters`](/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:

```yaml
---
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`](/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:

```yaml
---
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:

```markdown
---
type: slide
---

# 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.                                  |

```markdown
<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".                                  |

```markdown
<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). |

```markdown
<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.                                                     |

```markdown
<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). |
