Learn Chai, Microsoft and Openapi

Just about every tool in our accessibility auditing toolkit can help us identify any issues with sufficient color contrast ratio on a web page.  The react-axe library and axe browser extension both report findings on all elements with insufficient contrast ratios.  The tota11y browser extension will annotate any elements with their contrast ratios and color those that are insufficient in red.  

Additionally, we need to use our experience tools to see what some of our users out there may we seeing.  We need to test with high contrast browser extensions as well as the display settings in Windows and Mac.  If our users with visual impairments are using these tools we need to see what our application looks like using them because we may find that under a certain mode some things may suddenly be harder to read or virtually invisible.

## Resources
* https://www.scottohara.me/blog/2019/02/12/high-contrast-aria-and-images.html

Test for Insufficient Color Contrast Accessibility Issues

We should not use color alone as the only visual means of conveying information, indicating an action, prompting a response, or distinguishing a visual element.  Users may not be able to see/understand the differences in color and require additional indicators.

Along with color, use additional indicators such as:
* typography
* shapes
* grids
* spaces
* and/or allocate more weight to important elements

## References:
* http://www.particletree.com/features/interfaces-and-color-blindness/
* https://www.smashingmagazine.com/2014/10/color-contrast-tips-and-tools-for-accessibility/

Use More than Color Alone to Convey Information in a Web Page

Express is a minimal and flexible Node.js web application framework that provides a robust set of features for web and mobile applications.

express

To replicate your production application its helpful when developing a local NodeJS Express application is running under SSL. 

There are some web technologies which do not play nicely with standard http and its likely to become more common e.g. Web Push Notifications.

This lesson will show you how to create a local SSL certificate for localhost and then convert it into a format that will work with Express.  It will also show you how to make sure that Chrome will trust it.

This lesson is for Windows as it uses a powershell command, as well as the Microsoft Management Console (MMC)
 

Create Local SSL Certificates for an Express App on Windows

Microsoft Windows is a group of several graphical operating system families, all of which are developed, marketed, and sold by Microsoft. Each family caters to a certain sector of the computing industry.

microsoft

For a production Windows server it makes sense to run NodeJS applications as a Windows service.  This way they can be automatically restarted if the server is rebooted.

It also makes it easier to use monitoring tools like datadog to detect if there are issues with the service which is critical for production systems.

Install a Node.js Application as a Windows Service

Chai is a BDD / TDD assertion library for node and the browser that can be delightfully paired with any javascript testing framework.

chai

In this lesson, you will learn how to verify your API server is returning HTTP 400 responses when clients submit incorrect data. Returning HTTP 400 ensures that your clients are notified of the incorrect usage. Testing for them ensures your API returns errors instead of incorrect responses when supplied with incorrect data.

Test for HTTP 400 responses with Mocha and Chai

In this lesson, we will use Chai's request method to test our Node application's API responses.
By the end of this lesson, you will know how to:
- install the prerequisites to use mocha and chai in your application
- test for HTTP status response codes
- test for a string of text on a page
- test for a json response and validate the properties of the object
- write tests that not only verify the response of your application, but the behavior as well


Test Node RESTful API with Mocha and Chai

Open API Initiative (OAI) is focused on creating, evolving and promoting a vendor neutral API Description Format based on the Swagger Specification

openapi

Swagger is a project used to describe restful APIs using the OpenAPI Specification. It allows you to document your API so consumers understand the endpoints, parameters, and responses. In this lesson, I'll show you how to install the swagger command line tool, create a new API project using swagger, and introduce you to the swagger API editor.

Create an API with Swagger

There are a lot of great monitoring tools available for Node.js. It is also incredibly easy to build monitoring into your application. In this lesson, we will add precision monitoring to the function calls in the Todo API server, log it to the console, and persist those results to Elasticsearch where they can later be reviewed, graphed, and analyzed.

Build Monitoring into your API Server

In this lesson, I will show you how to update a simple, skeleton React application to work with the Todo API server built with Swagger. Using existing components, you will learn how to display all Todo items, update an existing Todo item, and add a new Todo item.

Connect an existing React application to an API server created with Swagger

The last step before deploying your new API server into production is to load test it. Load testing allows you to better understand the performance characteristics as well as forecast load and capacity. Fortunately, load testing is incredibly easy and I'll show you exactly how to create a load test plan, test the response from the API server to ensure it is responding correctly, and scale your test up to simulate as many users as needed.

Perform Load Tests on an API Server using Apache jmeter

This lesson shows you how to delete a Todo item from Elasticsearch using the Todo ID from the URL parameters according to the specifications defined in your Swagger API docs.

Create a Node.js function for an HTTP DELETE request for a Swagger API

This lesson will teach you how to create the javascript functions defined by the Swagger specification to return all Todo items to the client when requested with an HTTP GET method.

Create a Node.js function for an HTTP GET request for a Swagger API

This lesson shows you how to create the functions defined in the Todo API specification to create new Todo items when received in HTTP POST methods. You will also see the errors you will get when CORS is not properly configured and how to resolve them by installing the NPM CORS package.

Create a Node.js function for an HTTP POST request for a Swagger API

This lesson will teach you how to update a Todo item in Elasticsearch when received from an HTTP PUT method in your API server built with Swagger.

Create a Node.js function for an HTTP PUT request for a Swagger API

In this lesson, you will learn how to create a function in your Node.js Todo API server that gets the ID of the Todo item being requested from the URL and retrieve the Todo item from Elasticsearch.

Create a Node.js function for an HTTP GET request with URL parameters

In this lesson, you will learn how to define an HTTP GET endpoint using Swagger with URL parameters to identify the ID of the Todo item being requested.

Define an HTTP GET Endpoint with URL Parameters for a Node.js Server with Swagger

In this lesson, you will learn how to create an HTTP GET endpoint for a node.js server using Swagger. This endpoint will be used to return all of the Todo items from Elasticsearch to the client.

Define an HTTP GET Endpoint for a Node.js API Server with Swagger

This lesson demonstrates how to access the ID of a Todo item being deleted from the URL parameters when used with an HTTP DELETE method.



Define an HTTP DELETE Endpoint for a Node.js API Server with Swagger

In this lesson, you will learn how to define HTTP POST operations for your Todo API server using Swagger. Creating the endpoint, passing the todo in the request body, and parsing the todo are all demonstrated.

Define an HTTP POST Endpoint for a Node.js Server with Swagger

In this lesson, you will learn how to define multiple parameters in the API specification to identify the ID of the Todo item being updated in the URL, as well as the contents for the updated Todo item in the body of the request.

Define an HTTP PUT Endpoint for a Node.js API Server with Swagger

APIs created with Swagger have a built-in mock function, allowing you to mock responses from your API prior to writing the backend code to make it functional. In addition to learning how to enable this feature, I will show you how to write your own functions to enhance the mock responses returned when using the Swagger mock feature.

Mock API Responses with Swagger

Speed up your bug-fixing process dramatically with Cursors Composer. Take a warning from your logs, search for relevant terms, then seamlessly import both the warning and search results into Composer. Add documentation and apply fixes to all search results in one go. This streamlined workflow resolves multiple issues rapidly, saving valuable development time.

Batch Fix Every File in Search Results with Cursor's Composer

 We map over the initial set of results then use `Promise.all` to efficiently fetch the details of each pokemon rendered in the table. This allows us to add more columns to our pokemon table.

Fetch and display row details with Promise.all in Tanstack Table

map over the initial set of results then use `Promise.all` to efficiently fetch the details of each pokemon rendered in the tanstack table

Create a custom hook to fetch remote data by passing a promise to the React 19 `use` hook. Then render this data in Tanstack Table by memoizing the results and passing them to `useReactTable`.

Render remote data in a Tanstack Table with React 19's use hook and a promise

Create a custom hook using React 19’s use to fetch data with a promise. Render it in a Tanstack Table by memoizing and using useReactTable.

You know when you're deep in the code trenches and need someone to challenge your assumptions? That's exactly what this is about.

Instead of waiting for someone to poke holes in your master plan, you can paste that strategy straight into AI Studio and let it pressure test your ideas. We're talking about using this tool to validate everything from your feature proposals to your ambitious refactoring strategies.

The real magic happens when you hit that microphone button. Now you're in a real-time verbal sparring match. It's like rubber duck debugging but the duck actually pushes back and makes you defend every architectural decision you've made.

Here's the workflow:
1. Drop your master plan into the system instructions
2. Tell the AI to challenge every assumption
3. Hit that mic and defend your choices like you mean it
4. Watch your plan either emerge stronger or get rightfully dismantled

This approach is perfect when you're:
- Stuck in your own head with a complex problem
- Need to validate if your approach holds water
- Want to catch edge cases before they catch you
- Looking for opportunities you might have missed because you're too close to the code

It's like having a senior dev on call 24/7, ready to challenge your ideas and push you to think deeper about your solutions.

Now go forth and get your ideas challenged. Your projects will thank you for it.


An Uncomfortable and Challenging Conversation with AI Studio

In this lesson, you'll learn how to effectively brainstorm your project ideas before working with AI agents. We'll cover:

1. The importance of having a clear plan before starting work with AI agents
2. Using traditional brainstorming techniques to gather your thoughts
3. Leveraging video recording to capture your brainstorming session
4. How to review and analyze websites for inspiration
5. Documenting likes, dislikes, and potential features for your project
6. Using AI tools (like AI Studio) to organize and process your recorded brainstorming session

The lesson emphasizes a modern approach to brainstorming that combines traditional techniques with video recording, making it easier to later process your ideas through AI tools. This method helps ensure that no ideas are lost and that your thoughts can be effectively organized by AI for future reference.

How to Brainstorm Your Project Features to Prepare for AI Agents

fast-check allows us to create composite generators that suit our testing needs. We'll generate two numbers to create a point simulating an X and Y and assert that the distance should always be greater than or equal to 0.

Generate composite objects with fast-check fc.record

Just using fast-check by itself can make you tests verbose and tough to read. Lucky for us there are many integrations with fast-check such as the `@fast-check/jest` package that will help remove some boilerplate from our test.

Tidy up your test with @fast-check/jest

Many people share .cursorrules files, but trying to craft your own from scratch is a huge pain. Instead, this lesson shows you how to grab ALL community-created .cursorrules files to build a custom rule set for your projects. We'll use Gitingest and Google AI Studio to gather these examples and generate an awesome starting point customized to your specific project.

Generate Custom .cursorrules for Your Project Based on Community Examples

The GitHub CLI allows you to search issues and filter on different criteria like amount of comments. This allows you to search for real-world situations and pains/solutions people have using different technology. 

With the GitHub CLI in hand we'll drop 100s of issues as context in Googles AI Studio and have Gemini determine the 10 most frequently asked questions. This will give us a sense of how people use a library and where people get hung up.

Search 100s of Issues with GitHub CLI as Context for AI Studio

I often find myself wondering how to use certain APIs in certain situations, and I have a couple of keywords that I try and search up on Google. 

What you can do in this situation is turn to GitHub and see how other people have actually used this code on public projects. The GitHub CLI enables us to run searches like this, and we can take the results and work on them programmatically.

Inside of Cursor with their Composer AI agent, we can search for the files we want, tell the agent to download them, and inspect them for better understanding of how those things work together.