Monadyssey NPM

Overview

monadyssey is the foundational module, its purpose is to addresses challenges such as retrying operations, managing structured error handling, and building declarative, reusable workflows. By leveraging type safety and functional paradigms, it encourages predictable and maintainable code.

Documentation

Explore the documentation for specific features:

IO: Manage side effects, handle errors consistently, and compose asynchronous operations using the IO data type.

Installation

To use monadyssey in your project, install it via npm:

npm install monadyssey

Features

Declarative Asynchronous Control

Monadyssey offers tools like Schedule and configurable retry policies to manage retries, delays, and timeouts. These utilities allow developers to define how operations behave in the face of failures or recurring tasks without unnecessary complexity.

Explicit Error Handling

The IO type encapsulates asynchronous computations while explicitly modeling success and failure states. This ensures errors are handled predictably, enabling recovery and transformation in a controlled manner.

Functional Data Structures

The library provides data structures that align with functional programming principles:

NonEmptyList: A collection guaranteed to contain at least one element, ensuring safe and predictable operations.
Either: A type representing computations that may produce a result (Right) or an error (Left).
Option: An abstraction for optional values, offering a safer alternative to null or undefined.

Composability

The library emphasizes the composability of workflows, enabling developers to combine, sequence, or parallelize operations. This approach promotes the creation of complex behaviors from smaller, reusable components.

Lazy and Deferred Computations

The Eval type enables deferred or lazy evaluation of computations, optimizing performance and providing fine-grained control over execution.

Environment-Based Dependencies

The Reader type provides a structured way to inject dependencies or shared configurations into computations, ensuring clean separation of concerns and improving testability.