Book Image

Learn Bosque Programming

By : Sebastian Kaczmarek, Joel Ibaceta
Book Image

Learn Bosque Programming

By: Sebastian Kaczmarek, Joel Ibaceta

Overview of this book

Bosque is a new high-level programming language inspired by the impact of structured programming in the 1970s. It adopts the TypeScript syntax and ML semantics and is designed for writing code that is easy to reason about for humans and machines. With this book, you'll understand how Bosque supports high productivity and cloud-first development by removing sources of accidental complexity and introducing novel features. This short book covers all the language features that you need to know to work with Bosque programming. You'll learn about basic data types, variables, functions, operators, statements, and expressions in Bosque and become familiar with advanced features such as typed strings, bulk algebraic data operations, namespace declarations, and concept and entity declarations. This Bosque book provides a complete language reference for learning to program with Bosque and understanding the regularized programming paradigm. You'll also explore real-world examples that will help you to reinforce the knowledge you've acquired. Additionally, you'll discover more advanced topics such as the Bosque project structure and contributing to the project. By the end of this book, you'll have learned how to configure the Bosque environment and build better and reliable software with this exciting new open-source language.
Table of Contents (22 chapters)
1
Section 1: Introduction
5
Section 2: The Bosque Language Overview
10
Section 3: Practicing Bosque
15
Section 4: Exploring Advanced Features

Improving the code

First things first, let's focus on the types. Just by looking at the code, it's not quite clear what we mean every time we use List<Float64>. Sometimes, it means the "inputs vector," and sometimes the "weights vector." It would be much more readable if we had a custom type definition that would speak for itself. Let's create two additional types:

typedef WeightsVector = List<Float64>;
typedef InputsVector = List<Float64>;

As you can see, they are both the same, but they serve for better readability. Let's apply this change in the code. The weights vector is used in the Perceptron entity, the train function, and both entrypoint functions. Look at the following examples to see how they change.

In the Perceptron entity, we must change the field weights definition to look like this:

field weights: WeightsVector;

Here, we have replaced the List<Int> type with the WeightsVector one.

Another...