go-go-web VS gray-matter

[metadata] name = gogoweb version = 1.0.3 author = Katie Liu author_email = [email protected] description = Command-line tool that converts .txt or .md files into .html files. long_description = file: README.md long_description_content_type = text/markdown url = https://github.com/kliu57/go-go-web project_urls = Bug Tracker = https://github.com/kliu57/go-go-web/issues classifiers = Programming Language :: Python :: 3 License :: OSI Approved :: MIT License Operating System :: OS Independent [options] package_dir = = src packages = find: python_requires = >=3.7 [options.packages.find] where = src

For this lab exercise I had the opportunity to add unit tests to a classmate's project and experience their CI workflow. For this exercise I worked on go-go-web by kliu57. Go-Go Web is written in Python and uses the pytest testing framework. This was my first time writing tests for pytest, but I found the pytest docs helpful. However, more helpful was the information provided in the associated issue and the tests already written, which helped me write the test I needed in the author's preferences.

This week, I am using Continuous Integration to automatically lint and test my open source project whenever the code is pulled or pushed to GitHub!

This week I want to add a new feature to my text to HTML converter, go-go-web. The feature I plan to add is Markdown Front Matter support. When a user converts an .md file to .html using my program, my program would be able to convert Front Matter in the .md file into metadata tag content in the resulting .html file.

I chose to write my program in Python while she used Java. Aside from syntax differences, she has much more exception handling in her code compared to mine. It made me think that I should add more exception handling to my own code. Having another person test my code definitely helps to find more issues. She discovered that I missed implementing the spec for deleting the default output folder at the start of the run. Also, she uses a VS Code extension called Pylint which helped to find many problems with my code. Pylint found many issues with my code which were not best practice, such as not specifying an encoding when reading from a file, or using an f-string that does not have any interpolated variables.

Next is shifting towards what they're calling App Router. The previous itteration, known as Pages Router is not compatible with those shiny new React Server Components I mentioned earlier. The main difference to me was using simple fetch and async/await syntax to fetch the server side props. In this case, I had a node script that relied on fs to retrieve the markdown files and a library called gray-matter to retrieve their YAML metadata properties. Then all I had to do was transform my [slug] page into an async function and call the function that fetched the posts from the filesystem.

Processes and Chunks Content: Using tools like gray-matter and remark (with strip-markdown), the plugin extracts frontmatter (such as titles and tags) and converts the Markdown into plain text. Then it splits this content into manageable chunks (with configurable maximum chunk size) while preserving metadata like file paths.

We'll start by initializing a Node project inside a chosen folder (nodejs-blog for me) with and installing a couple of dependencies that I feel like will make our lives easier, like Express, EJS, Marked, the good ol' body-parser and gray-matter.

When updating the front matter I use gray-matter to make it a easy process. The code will check if there is a voice and quiz section in the event, and if so add new tags in the front matter part.

Writing in markdown is super convenient, and supported by just about any text editor. To convert these .md files to browser-ready HTML, I wrote a simple little Node.js script using two great npm packages called gray-matter and showdown.

Next, install gray-matter to extract metadata from the front matter of markdown files, and marked to convert the markdown files to HTML:

It turns out that Docusaurus uses an open source JavaScript parser called gray-matter to parse the front matter from markdown files! After installing gray-matter using npm and them importing it into the markdownUtils.ts file, all it takes is calling the matter method and passing the markdown file contents to get returned an Object with data and content (the data being the front matter and the content being the rest of the markdown file contents).

Although we are building a custom table of contents, we won't have to write everything from scratch. To separate the Markdown/MDX content from the front matter, we'll use the Gray-matter package. It is optional in case you don't have front matter in your Markdown files. To process the Markdown itself, we'll use the Remark package. We'll also need the unist-util-visit package for traversing node trees and mdast-util-to-string for getting the text content of a node.

In this article we walk you through the process of creating a simple blog app using the popular React framework NextJS, gray-matter and next-mdx-remote.

In order to get post information (such as author, title, date, etc.) from our HTML without having them be apart of our rendered post we need a way to parse YAML front matter, this is where gray-matter comes in hand.