Claus Matzinger

Future Finance Labs, a fintech scaleup company, wants to expand its customer base by offering a lightning-fast exchange platform for professional traders. As its star developer, you’ll use the Rust programming language to create a prototype of the exchange that will accommodate high-frequency trading and serve as the foundation for additional future financial products.

You’ll build an interactive command line program that will constitute the core accounting structure for setting up accounts and manipulating data. You’ll create a matching engine that enables traders to find the best trading partners—and showcases the blazing-fast core of the exchange platform. You’ll extend your Rust HTTP API by setting up a warp web service that will interact with an additional trading platform, building a shared marketplace that will be a blueprint for additional Rust web services, small and large. When you’ve completed this series of liveProjects, you’ll have hands-on experience using the Rust type system to write fast, robust software, using data structures and iterators from the Rust standard library, working with mutability, applying borrowing and ownership, and asynchronous programming basics.

You’re the star developer for Future Finance Labs, a fintech scaleup whose partner consultants are so happy with the prototype of an exchange platform you’ve built that some of them have brought a trading firm on board. Your task is to extend your prototype to include a platform for trading futures that the firm would like to offer its clients. You’ll lay the web project foundation by moving the Rust code for the existing matching engine to a shared library, adding a skeleton project for the web server, and creating a Cargo workspace. You’ll set up a warp web service to interact with the trading platform, add JSON serialization to your types, and use asynchronous Rust programming to create handler functions. Then you’ll upgrade the existing command line interface to connect with your new service instead of the local variant via REST. When you’re finished, you’ll have built a complete Rust HTTP API that will be a blueprint for additional Rust web services, small and large.

Future Finance Labs is creating an exchange platform for professional traders in hopes of expanding its customer base. As the fintech company’s star developer, your task is to build a matching engine that enables traders to find the best trading partners. Using Rust, the company’s chosen programming language, you’ll build the trading platform, the backbone of the engine, tying the accounting and trading components together. You’ll create the commands that enable interactions with the trading platform, parse input, and display the transaction log to the user. When you’re done, you’ll have built a fully functional matching engine, and you’ll have practical experience working with complex Rust data structures and iterators as well as applying mutable borrowing and ownership.

Future Finance Labs has tasked you, its star developer, to create a prototype for an exchange platform that the fintech scaleup wants to offer to professional traders. You’ll build an interactive command line program that will serve as the core accounting structure for this lightning-fast exchange platform. Using Rust, the company’s chosen programming language, you’ll implement the required data structures for storing accounts as well as the functions for transactions between accounts. To validate the account structure and functions, you’ll design and implement unit tests. When you’re done, you’ll be a master of Rust fundamentals, including its various syntax aspects and operations, and you’ll be ready to advance to more complex Rust data structures and code.

In this liveProject, you’ll use some of the unique and lesser-known features of the Rust language to finish a prototype of a FinTech command line tool. You’ll step into the shoes of a developer working for Future Finance Labs, an exciting startup that’s aiming to disrupt mortgages, and help out with building its market-tracking backend. Your CTO has laid out the requirements for the minimum viable product, which must quickly process large amounts of stock pricing data and calculate key financial metrics in real time.

In this liveProject, you’ll implement the capability for your CLI tool to continuously poll the data source to create a stream of data over the command line. Once you’ve set up that functionality, you’ll integrate your new CLI into your company’s wider intelligence gathering system, which requires exposing an HTTP endpoint that provides the most recent performance indicators.

In this liveProject, you will complete a half-finished prototype tool designed to improve risk management in fund strategies. You’ll transform the existing code to use async programming, use concurrent requests to fetch and process data for the tool, and output data on the command line in a CSV format. Once you’ve built the basics, you’ll upgrade the CLI’s performance to concurrently fetch stock data every 30 seconds.