README Guide: Updating the /learn Ecosystem with GitHub Webhooks
This guide outlines the process for managing updates within the /learn ecosystem, our content hub, using GitHub webhooks to automate content updates in our full-text search index and render markdown files in JavaScript.
Overview
Each folder within the /learn ecosystem represents a page or a section. These folders contain markdown files (.md) which constitute the content of the page. When changes are made to these markdown files, a GitHub trigger is activated, sending the updated file to a predefined webhook. This webhook then updates the content in our full-text search index. Finally, the updated markdown content is rendered in JavaScript on the website.
Prerequisites
- A GitHub repository with your markdown content structured in folders.
- Access to your web server or hosting service to set up a webhook listener.
- A full-text search service (like ElasticSearch) set up to index your content.
- Basic knowledge of JavaScript for rendering markdown files on the web.
Step 1: Organizing Your Content
- Structure your content in folders within the GitHub repository, where each folder represents a page or a section in the /learn ecosystem.
- Ensure all content is written in markdown files (.md) and properly named to reflect their purpose or content.
Step 2: Setting Up a GitHub Webhook
- In your GitHub repository, go to
Settings > Webhooks > Add webhook.
- Enter the Payload URL. This URL should point to the webhook listener on your server where updates will be received.
- Choose the content type as
application/json.
- Select
Just the push event for which events would trigger this webhook.
- Ensure the
Active checkbox is selected and create the webhook.
Step 3: Creating the Webhook Listener
- On your server, create a script that listens for POST requests at the URL specified in the GitHub webhook setup.
- When a POST request is received, parse the JSON payload to identify the updated markdown files.
- For each updated file, update its corresponding content in your full-text search index.
Example (pseudo-code):
app.post('/webhook-url', (req, res) => {
const updatedFiles = req.body.commits.map(commit => commit.modified);
updatedFiles.forEach(file => {
updateSearchIndex(file);
});
res.status(200).send('Update received');
});
Step 4: Updating the Full-Text Search Index
- Extract the content from the updated markdown files.
- Update the content in your full-text search index, ensuring it's searchable and properly indexed.
Step 5: Rendering Markdown in JavaScript
- Use a JavaScript library like
marked.js to convert markdown content to HTML.
- Fetch the updated markdown content from your full-text search index or directly from the GitHub repository if needed.
- Render the HTML content on the appropriate page within the /learn ecosystem.
Example (JavaScript):
fetch('path/to/markdown.md')
.then(response => response.text())
.then(markdown => {
const htmlContent = marked(markdown);
document.getElementById('content').innerHTML = htmlContent;
});
Conclusion
This guide provides a streamlined approach to automating content updates within the /learn ecosystem using GitHub webhooks, a full-text search index, and JavaScript. By following these steps, you can ensure that your content is always up-to-date and easily searchable by your audience.