Learn Clojurescript, Mongodb and Reactfire

mongodb

[In our last lesson](https://egghead.io/lessons/mongodb-group-by-and-sum-in-mongodb?pl=mongodb-aggregation-framework-3e5d), we saw how we can use `$group` operator to simulate `GROUP BY` operations that you might be aware from SQL. A minor gimmick with `$group` is that it only works with the scalar field values and not arrays. There might be times when you would want to group by some array fields; in this lesson, we learn how to do that using `$unwind` operator

Here is the list of operators that we cover in this lesson:

- [$unwind](https://docs.mongodb.com/manual/reference/operator/aggregation/unwind/index.html)
- [$group](https://docs.mongodb.com/manual/reference/operator/aggregation/group/index.html)
- [$sort](https://docs.mongodb.com/manual/reference/operator/aggregation/sort/index.html)
- [$limit](https://docs.mongodb.com/manual/reference/operator/aggregation/limit/index.html)

You can see the list of all the [available operators in the MongoDB docs](https://docs.mongodb.com/manual/reference/operator/aggregation/).


Perform Group Operations on Array Fields in MongoDB

In this lesson, we learn how to group documents in a collection using `$group` operator similar to `GROUP BY` in SQL. We also look at `$sum` operator and see how we can use it to count the number of documents as well as get sum of some field in our grouped results.

Here is the list of operators that we cover in this lesson:

* [`$group`](https://docs.mongodb.com/manual/reference/operator/aggregation/group/index.html)
* [`$sum`](https://docs.mongodb.com/manual/reference/operator/aggregation/sum/index.html)
* [`$sort`](https://docs.mongodb.com/manual/reference/operator/aggregation/sort/index.html)

You can see the list of all the [available operators in the MongoDB docs](https://docs.mongodb.com/manual/reference/operator/aggregation/).


Group By and Sum in MongoDB

Unlike the relational databases, MongoDB doesn't allow you to join collections using the simple `find` queries, but you can write the join queries using the aggregation framework. In this lesson, we learn how to join two collections to get the data in the format we want.

The aggregation operators that we cover in this video are:

- [`$lookup`](https://docs.mongodb.com/manual/reference/operator/aggregation/lookup/index.html)
- [`$project`](https://docs.mongodb.com/manual/reference/operator/aggregation/project/index.html)
- [`$arrayElemAt`](https://docs.mongodb.com/manual/reference/operator/aggregation/arrayElemAt/index.html)

You can see the list of all the [available operators in the MongoDB docs.](https://docs.mongodb.com/manual/reference/operator/aggregation/)

Write Joins in MongoDB

Mongoose provides a straight-forward, schema-based solution to model your application data. It includes built-in type casting, validation, query building, business logic hooks and more, out of the box.

mongoose

One of the great things about NoSQL databases is that you do not have to decide on your data schema while developing. As you get closer to production though, you'll often want to more clearly define the shape of the data you are working with.

Enforce Schemas in MongoDB using Mongoose Models

MongoDB has a quite powerful aggregation framework that allows you to write data processing pipelines. Documents in the MongoDB collection go through a series of stages or a pipeline that transforms them into an aggregated result. In this short video series, you will learn how to write aggregations in MongoDB.

MongoDB Aggregation Framework

In our last lesson, we learnt the basics of MongoDB aggregation and saw how we can [find and manipulate data](https://egghead.io/lessons/mongodb-find-and-manipulate-data-using-aggregation-in-mongodb). In this continuation, we will see how we can sort, skip and limit records during our aggregation stages.

The aggregation stages/operators covered in this video are:

* [`$sort`](https://docs.mongodb.com/manual/reference/operator/aggregation/sort/index.html)
* [`$skip`](https://docs.mongodb.com/manual/reference/operator/aggregation/skip/index.html)
* [`$limit`](https://docs.mongodb.com/manual/reference/operator/aggregation/limit/index.html)

You can see the list of all the [available operators in the MongoDB docs.](https://docs.mongodb.com/manual/reference/operator/aggregation/)

Sort, Skip and Limit Records in MongoDB Aggregation

Aggregation in MongoDB is really powerful and allows you to create solid pipelines to extract and transform data. This is an introductory video that aims to demonstrate the basics of aggregation — we will see how to create some basic pipeline to extract data using `$match` and manipulate the output using `$project` stages.

The aggregation stages/operators covered in this video are:

* [`$match`](https://docs.mongodb.com/manual/reference/operator/aggregation/match/index.html)
* [`$project`](https://docs.mongodb.com/manual/reference/operator/aggregation/project/index.html)
* [`$concat`](https://docs.mongodb.com/manual/reference/operator/aggregation/concat/)

You can see the list of all the [available operators in the MongoDB docs](https://docs.mongodb.com/manual/reference/operator/aggregation/)


Find and Manipulate Data using Aggregation in MongoDB

Clojure is a dynamic, general-purpose programming language, combining the approachability and interactive development of a scripting language with an efficient and robust infrastructure for multithreaded programming. Clojure is a compiled language, yet remains completely dynamic – every feature supported by Clojure is supported at runtime. Clojure provides easy access to the Java frameworks, with optional type hints and type inference, to ensure that calls to Java can avoid reflection.

clojure

In this lesson I show what a Clojure keyword is and why we prefer them as keys in maps; and the three ways we can look up a value in a map.

Keywords and Map Lookup in Clojure and ClojureScript

ClojureScript is a compiler for Clojure that targets JavaScript. It emits JavaScript code which is compatible with the advanced compilation mode of the Google Closure optimizing compiler.

clojurescript

In this lesson I show you how to get and manipulate command-line arguments in Clojure/ClojureScript by writing a small program that greets you by name. I also show how comments are delimited, how to get a value out of a sequence, how to bind a symbol to a value, and how to define a function.

Handle command-line arguments in ClojureScript


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

express

Mongoose allows you to easily select resources by ID from your MongoDB. This is an important aspect to creating an API.

Select by ID with Mongoose and Express

Learn how to import data into your MongoDB and then use Express to serve a simple Node.js API.

First API with Node.js, Express and MongoDB

 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

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.

John Lindquist

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.

Search All of GitHub's Code and Pass the Results to AI Agents in Cursor

Implement virtual scrolling to handle large datasets in an HTML table. Start with a basic table that renders 10,000 rows of data. The browser can struggle with this amount of DOM nodes to render at one time, especially on low end devices. 

We implement tanstack react virtual to render only the necessary amount of rows the user is viewing. The implementation includes proper column sizing, accessibility considerations, and convenient scroll controls, resulting in a smooth and performant table experience regardless of the dataset size.

Create a row virtualized HTML table with Tanstack Virtual

Learn how to implement virtual scrolling in React tables using TanStack Table and Tanstack Virtual with the useWindowVirtualizer React hook.

The most difficult tasks will require the strongest AI models. And those models simply aren't available as AI agents inside of your tooling. So the best workflows are to drag and drop the files you need to be changed and analyzed inside of a reasoning model such as OpenAI's O1 Pro, then letting it create a giant plan for your dumber AI agents to work on. The key here is that instead of just copying and pasting the entire plan into Cursors Composer or your AI agent, it's to create a file inside of your project and ask your agent to tackle the plan one step at a time. This allows you ample opportunity between each step to test and verify the micro steps along the way. Otherwise, as I've experienced many times, a session can go way off track and you burn a lot of time and burn a lot of AI requests Cursors Composer and it starts churning through a plan Cursors Composer and making lots of unwanted changes. Cursors Composer and it's to guide an AI agent to hold its hand along the way, especially through the most complex tasks. Cursors Composer and the most complex tasks Cursors Composer and the most complex tasks require a step-by-step plan.

Planning AI Agent Sessions with Reasoning Models

AI agents will inevitably make mistakes—it's just a matter of when. A key tool in your toolbox, once they do make mistakes after working on a problem for a while, is to use **git diff** to capture all of the changes they've made. 

Once you have those changes in a text file, you have a portable document that you can test against other AI models. This allows you to move the problem into smarter reasoning models with smaller context windows, helping you isolate and focus on the issue at hand.

**git diff** has been invaluable when working with AI agents because they'll often make many good changes but also slip in one tiny error. Finding that one small mistake is **git diff**’s superpower.

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