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Experience Quality Coding
F# Development Starter Kit for Firebase Studio
Timeline FRP library
Timeline for 🍦VanJS
About
⭐Star on GitHub
🔷Unit 0🔷 Introduction to Quality Code
💡 Experience Quality Coding ✨
Pipeline Philosophy
Core Concept: The Data Transformation Pipeline
Other Fundamental Programming Concepts
The Unifying Potential of the Functional Pipeline
🔷Unit 1🔷 Building with Function
🔍 Overview - Unit 1
Control Flow
Understanding Control Flow: The Structured Programming Baseline
1. Sequence
2. Selection
3. Iteration
Recursion: The Foundation of Functional Iteration
Expressions
Pipelines and Expressions as Values
First-Class Functions
Higher-Order Functions (HOF)
Types and Lambda
Types: Ensuring Smooth Pipelines
First-Class Functions and Lambda Expressions
Generic Function Types: The Power of 'a -> 'b
Deconstructing HOF Types: From 'a -> 'b to Complex Signatures
Binary Operation
Binary Operations and the Pipeline Operator
Operators as Functions and Pipeline Flow
Currying and Partial Application: Functions Returning Functions
HOFs in Action: Type Signatures, flip, and Pipelines
Dependency Graph
How to Drive Your Code?
Code Driven by Dependency Graph
Self-Referential Structures on Dependency Graphs
Pure vs. Impure Functional Languages
Terms and Concepts
Understanding Functional Programming Terminology
🔷Unit 2🔷 Algebraic Structures
🔍 Overview - Unit 2
Basic Structures
Algebraic Structures and Pipeline Flow
Monoids
Associativity: Building Robust Structures
Semigroups: Our First Algebraic Structure
Identity Elements: The Neutral Value in Operations
Monoids: Semigroups with an Identity Element
Composition Laws
Function Composition: A Natural Monoid
Functors
Set Theory and Types: A Deeper Look
Container Types: Sets in Programming
Functor: Mapping between Functions
Monads
Another Bridge Between Worlds
The Kleisli Arrow
Monad: Another Bridge
Category Theory
Bringing It All Together: Functor & Monad
Beyond Simple Mapping: Preserving the Structure of Composition
Understanding Functors: Preserving the Monoid of Function Composition
The Monad Laws: Verifying the Kleisli Composition Monoid
🔷Unit 3🔷 Common Functors and Monads
🔍 Overview - Unit 3
Identity Monad
Identity Functor and Identity Monad
List Monad
Section 1: List Functor and Monad
List Functor
List Monad
Option Monad
Section 2: Option (Maybe) Functor and Monad
Option Functor
Option Monad
Result Monad
Section 3: Result (Either) Functor and Monad
Result (Either) Functor
Result (Either) Monad
IO Monad
Section 4: IO Functor and Monad
IO Functor
IO Monad
🔷Unit 4🔷 Parallel Computing/Concurrency
🔍 Overview - Unit 4
Yet Another Structure
Bringing It All Together: Functor & Monad (Revisit)
Introducing apply and map2
Lifting Binary Operations into Containers
Product or Pointwize(ZIP)
The Real-World Power of Parallel Processing Patterns
Applicative Functor
Applicative Functor: The Parallel Computable Structure
Applicative Functor Laws
Applicative Functor Laws For Us
Special Edition and Your Next Generation AI could Copy
The Fiction of Haskell's "Theoretical Superiority": A Critical Verification from a Category Theory Perspective and Its Educational Impact on Beginners
Special Edition and Your Next Generation AI could Copy
🔷Unit 5🔷 Timeline FRP
🔍 Overview - Unit 5
Core Concepts
Chapter 0: Immutable World
Chapter 1: FRP is like Spreadsheet
Chapter 2: Understanding Timeline<'a> and FRP Implementation
Chapter 3: Transforming Timelines and Introducing the Dependency Graph
Chapter 4: Handling I/O: Extending the Block Universe Model
Chapter 5: Robustness Through Algebraic Structure
Chapter 6: Dynamic Dependency Management and Automatic Resource Cleanup
Chapter 7: Full Automatic Resource Management via bind with AI Assistance
🔷Unit 6🔷 Combining Timelines
🔍 Overview - Unit 6
Null
Handling Absence: A Foundational Choice (null vs. Option)
Binding Chain
Asynchronous Event Chaining with bind
Stateful Unary Operations
Stateful Transformation with scan
Filtering Timelines with distinctUntilChanged
Combining Independent Timelines
Recap and Strategy for Binary Operations
Combining Timelines with combineLatestWith
Monoidal Combinations: TL.And & TL.Or
Aggregating Lists of Timelines
The "Map to Boolean, then Aggregate" Pattern
Case Study: Aggregating Asynchronous HTTP Request Outcomes
🔷Unit 7🔷 UI with Timeline JS
🔍 Overview - Unit 7
UI
0-ui
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