Introduction
This section explores four progressive approaches to handling effectful domain workflows in F#, each building upon the limitations of the previous one. Understanding this evolution will help you choose the right pattern for managing dependencies and side effects in your functional applications.
The Challenge
In object-oriented programming, the building blocks are objects and classes. When a class collaborates with other classes, these collaborators are called dependencies. Managing these dependencies effectively—especially when they involve side effects like database access, HTTP calls, or file I/O—is crucial for building testable, maintainable applications.
Four Approaches
This introduction presents four progressive solutions to the dependency problem:
–
Pass dependencies as inputs
Widely adopted, simple
Async leak, runtime configuration
program V1
Abstract dependencies as data
Testability, separation of what/how
Monolithic instruction type
program V2
Separate instructions by domain
Better organization, domain isolation
All domains still coupled in Program type
program V3
Effect handlers with type safety
Complete domain isolation, vertical slicing
More components, higher complexity
Prerequisites
To get the most out of this introduction, you should be familiar with F# basics:
Functional programming concepts: pure functions, side effects
Types: discriminated unions, records
Pattern matching
Computation expressions—at least
async
If not, you can consult my free e-book F# Training.
How to Read This Introduction
Each page builds upon the previous one:
Start with Dependency Injection to understand the baseline approach and its limitations.
Progress through Dependency Interpretation to see how functional programming addresses these limitations.
Explore Free Monad to understand domain separation.
Conclude with Algebraic Effects to see the most advanced pattern.
You can also jump directly to a specific approach if you're already familiar with the earlier patterns.
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