Table of contents

• Benefits of typelevel computation:
• Some use cases
• Validation, verification and contracts
• DSLs and embedded languages:
• Configuration and Settings
• All that glitters is not gold: typelevel drawbacks
• Who is the perfect audience for typelevel computation

Benefits of typelevel computation:

Type-level computation in TypeScript, or any statically typed language, offers several benefits that can improve code safety, maintainability, and developer productivity:

1. Compile-time safety: Type-level computation enables catching errors at compile time rather than runtime. This results in early detection of issues, reducing the likelihood of bugs and runtime errors in production code.

2. Improved code correctness: By using type-level computation, developers can define and enforce constraints, contracts, and invariants directly in the type system. This ensures that code adheres to specified rules, leading to more robust and correct software.

3. Enhanced developer experience: Type-level computation provides better tooling support, including autocomplete, type inference, and type checking. This helps developers write code more efficiently and with fewer errors, leading to a smoother development experience.

4. Refactoring confidence: Type-level computation helps maintain code consistency during refactoring. Since types accurately reflect the structure and constraints of data, refactoring tools can provide better guidance and ensure that changes don't violate existing contracts.

5. Documentation and self-documenting code: Type-level computation serves as a form of documentation by describing the shape and behavior of data directly in the code. Well-defined types act as self-documenting entities, making it easier for developers to understand code and collaborate effectively.

6. Code maintainability(double edged sword, see drawbacks section): Type-level computation promotes code maintainability by providing a clear and explicit representation of data structures, constraints, and transformations. This makes it easier to reason about code, identify potential issues, and make changes with confidence.

7. Reduced runtime overhead: Since type-level computations occur at compile time, there's no runtime overhead associated with type checking or validation. This can lead to improved performance, especially in performance-critical applications.

Overall, type-level computation offers significant benefits in terms of code safety, correctness, maintainability, and developer productivity, making it a valuable tool for building reliable and maintainable software systems.

Some use cases

Type-level programming in TypeScript offers several powerful capabilities that can be leveraged to solve a variety of problems at compile time. Here are some common use cases for type-level programming in TypeScript:

Validation, verification and contracts

Enforcing data validation rules at compile time, such as validating input parameters, ensuring correct usage of APIs, and preventing invalid states.

for example URL validation:

// Define a type for valid URL schemes
type ValidScheme = 'http' | 'https' | 'ftp' | 'ssh';

// Define a type for valid domains
type ValidDomain = 'example.com' | 'example.org' | 'example.net';

// Define a type-level function to validate URL scheme
type ValidateScheme<T extends string> = T extends `${ValidScheme}://${string}` ? T : never;

// Define a type-level function to validate domain
type ValidateDomain<T extends string> = T extends `${ValidScheme}://${ValidDomain}/${string}` ? T : never;

// Define a type-level function to validate query parameters
type ValidateQueryParams<T extends string> = T extends `${string}?${string}` ? T : never;

// Combine all validation functions into a single function
type ValidateURL<T extends string> = ValidateQueryParams<ValidateDomain<ValidateScheme<T>>>;

// Example usage:
type ValidURL = ValidateURL<'http://example.com/path?param=value'>;
type InvalidURL = ValidateURL<'http://invalid-url.com/path?param=value'>;

// This will work because ValidURL matches the URL pattern
const validURL: ValidURL = 'http://example.com/path?param=value';

// This will result in a compilation error because InvalidURL does not match the URL pattern
const invalidURL: InvalidURL = 'http://invalid-url.com/path?param=value'; // Error: Type '"http://invalid-url.com/path?param=value"' does not match the expected type 'never'

or any other contract in general:

// Define the contract for a user object
type UserContract = {
  id: string;
  name: string;
  age: number;
  address?: {
    street: string;
    city: string;
    postalCode: string;
  };
};

// Define a type-level function to enforce the contract
type EnforceContract<T> = T extends UserContract ? EnforceUser<T> : never;

// Define a helper type to enforce the contract for a user object
type EnforceUser<T> = {
  [K in keyof T]: K extends 'address' ? EnforceAddress<T[K]> : T[K];
};

// Define a helper type to enforce the contract for the address object
type EnforceAddress<T> = {
  [K in keyof T]: T[K];
};

// Example usage:
type ValidUser = EnforceContract<{
  id: string;
  name: string;
  age: number;
  address: {
    street: string;
    city: string;
    postalCode: string;
  };
}>;

type PartialUser = EnforceContract<{
  id: string;
  name: string;
  age: number;
  address?: {
    street: string;
    city: string;
    postalCode: string;
  };
}>;

type InvalidUser = EnforceContract<{
  id: string;
  name: string;
  age: string; // Invalid type
  address: {
    street: string;
    city: string;
    postalCode: string;
    country: string; // Invalid property
  };
}>;

// This will work because ValidUser matches the UserContract
const validUser: ValidUser = {
  id: '1',
  name: 'John',
  age: 30,
  address: {
    street: '123 Main St',
    city: 'Anytown',
    postalCode: '12345',
  },
};

// This will work because PartialUser matches the UserContract
const partialUser: PartialUser = {
  id: '2',
  name: 'Jane',
  age: 25,
};

// This will result in a compilation error because InvalidUser does not match the UserContract
const invalidUser: InvalidUser = {
  id: '3',
  name: 'Doe',
  age: '25', // Error: Type 'string' is not assignable to type 'number'
  address: {
    street: '456 Elm St',
    city: 'Othertown',
    postalCode: '54321',
    country: 'USA', // Error: Object literal may only specify known properties, and 'country' does not exist in type 'EnforceAddress<{ street: string; city: string; postalCode: string; }>'
  },
};

DSLs and embedded languages:

Type-level computation can significantly benefit the creation of Domain-Specific Languages (DSLs) by enforcing constraints, ensuring correctness, and providing a high level of abstraction. Let's consider an example of creating a DSL for building SQL queries using type-level computation in TypeScript.

We'll define a DSL that allows users to construct SQL queries fluently with type safety, ensuring that only valid SQL constructs are used. We'll use mapped types, conditional types, and generics to achieve this.

// Define a type representing SQL operators
type SQLOperator = '=' | '<' | '>' | '<=' | '>=' | 'LIKE';

// Define a type representing SQL conditions
type SQLCondition<T extends string> = {
  field: T;
  operator: SQLOperator;
  value: string;
};

// Define a type representing SQL query options
type SQLOptions<T extends string> = {
  select: string[];
  from: T;
  where?: SQLCondition<T>[];
};

// Define a type-level function to validate SQL conditions
type ValidateSQLCondition<T extends string, U extends SQLCondition<T>> = U['field'] extends keyof U
  ? U['operator'] extends SQLOperator
    ? U
    : never
  : never;

// Define a type-level function to validate SQL query options
type ValidateSQLOptions<T extends string> = {
  [K in keyof T]: T[K] extends string[] ? T[K] : never;
} extends {
  select: string[];
  from: string;
}
  ? SQLOptions<T>
  : never;

// Define a DSL for building SQL queries
class SQLQueryBuilder<T extends string> {
  private options: ValidateSQLOptions<T>;

  constructor(options: ValidateSQLOptions<T>) {
    this.options = options;
  }

  select(...fields: string[]): SQLQueryBuilder<T> {
    return new SQLQueryBuilder<T>({ ...this.options, select: fields });
  }

  from(table: T): SQLQueryBuilder<T> {
    return new SQLQueryBuilder<T>({ ...this.options, from: table });
  }

  where(condition: ValidateSQLCondition<T, SQLCondition<T>>): SQLQueryBuilder<T> {
    const conditions = this.options.where ? [...this.options.where, condition] : [condition];
    return new SQLQueryBuilder<T>({ ...this.options, where: conditions });
  }

  build(): string {
    const { select, from, where } = this.options;
    let query = `SELECT ${select.join(', ')} FROM ${from}`;
    if (where) {
      const whereClause = where.map(c => `${c.field} ${c.operator} '${c.value}'`).join(' AND ');
      query += ` WHERE ${whereClause}`;
    }
    return query;
  }
}

// Example usage
const query = new SQLQueryBuilder('users')
  .select('id', 'name')
  .from('users')
  .where({ field: 'age', operator: '>', value: '18' })
  .build();

console.log(query);

In this example:

• We define types representing SQL operators (SQLOperator) and SQL conditions (SQLCondition).
• We define a type-level function (ValidateSQLCondition) to validate SQL conditions against the expected structure.
• We define a type-level function (ValidateSQLOptions) to validate SQL query options against the expected structure.
• We implement a DSL for building SQL queries (SQLQueryBuilder) using generics and type-level computation to ensure correctness and type safety.
• We demonstrate the usage of the DSL by constructing an SQL query with fluent syntax while enforcing type safety and correctness at compile time.

This DSL provides a high level of abstraction and type safety, ensuring that only valid SQL constructs are used when building queries. Type-level computation helps enforce constraints and ensures correctness in the DSL, providing a more robust and reliable solution for constructing SQL queries in TypeScript.

Configuration and Settings

Managing configuration settings and ensuring consistency and correctness across different parts of the application, such as environment-specific configurations or feature toggles.

// Define a type for environment names
type Environment = 'development' | 'staging' | 'production';

// Define a type-level function to validate environment variables
type ValidateEnv<T extends Environment> = T extends Environment
  ? (
    T extends 'development' ? (Required<DevelopmentConfig> & Partial<DevelopmentConfig>) :
    T extends 'staging' ? (Required<StagingConfig> & Partial<StagingConfig>) :
    T extends 'production' ? (Required<ProductionConfig> & Partial<ProductionConfig>) :
    never
  )
  : never;

// Define configuration types for different environments
interface DevelopmentConfig {
  apiUrl: string;
  databaseUrl: string;
  loggingEnabled: boolean;
}

interface StagingConfig {
  apiUrl: string;
  databaseUrl: string;
  loggingEnabled: boolean;
}

interface ProductionConfig {
  apiUrl: string;
  databaseUrl: string;
  loggingEnabled: boolean;
}

// Example usage
const environment: Environment = process.env.NODE_ENV as Environment;

// Validate environment variables based on the current environment
type CurrentConfig = ValidateEnv<typeof environment>;

// Get the current configuration based on the environment
const config: CurrentConfig = {
  apiUrl: process.env.API_URL!,
  databaseUrl: process.env.DATABASE_URL!,
  loggingEnabled: process.env.LOGGING_ENABLED === 'true',
};

// Validate required configuration values
if (!config.apiUrl || !config.databaseUrl) {
  throw new Error('Missing required environment variables.');
}

// Usage example
console.log('Current API URL:', config.apiUrl);
console.log('Current Database URL:', config.databaseUrl);
console.log('Logging Enabled:', config.loggingEnabled);

All that glitters is not gold: typelevel drawbacks

While type-level computation in TypeScript offers significant benefits in terms of type safety, correctness, and abstraction, it also comes with some drawbacks:

1. Complexity: Type-level computation often involves advanced features of the TypeScript type system, such as conditional types, mapped types, and type inference. This can lead to complex type definitions and code that is difficult to understand, especially for developers who are not familiar with advanced type system features.

2. Compile Time: As the complexity of type-level computation increases, so does the time it takes for TypeScript to compile the code. Large and complex type definitions can significantly slow down the compilation process, leading to longer build times, especially in large codebases.

3. Error Messages: Error messages generated by the TypeScript compiler for type-level computation errors can sometimes be cryptic and difficult to understand. Debugging type-related issues and diagnosing errors in complex type definitions can be challenging, especially for less experienced developers.

4. Tooling Support: While modern IDEs and text editors provide excellent support for TypeScript, including features like auto-completion, type checking, and type inference, they may struggle to provide accurate and helpful suggestions for code involving complex type-level computation.

5. Learning Curve: Understanding and effectively using type-level computation requires a solid understanding of TypeScript's type system and its advanced features. Developers who are new to TypeScript or who have limited experience with static typing may find it challenging to grasp the concepts and best practices related to type-level computation.

6. Maintenance: Complex type definitions used for type-level computation can be challenging to maintain over time, especially as codebases evolve and requirements change. Refactoring type definitions and ensuring they remain consistent and up-to-date with the rest of the codebase can require significant effort and careful attention to detail.

Who is the perfect audience for typelevel computation

Type-level development, especially in languages like TypeScript, is suitable for developers who prioritize type safety, correctness, and maintainability in their codebases. Here are some characteristics of the perfect audience for type-level development:

1. Type Safety Advocates: Developers who value strong type systems and strive to catch errors at compile time rather than runtime. They appreciate the benefits of static type checking for improving code quality and reducing bugs.

2. Large-Scale Projects: Developers working on large-scale projects with complex requirements and a need for robust architecture. Type-level development helps manage complexity and ensures code correctness, making it ideal for such projects.

3. Library and Framework Authors: Developers who create libraries, frameworks, or APIs for others to use. Type-level development allows them to provide better type definitions, improving the developer experience for consumers of their libraries.

4. Teams Emphasizing Code Quality: Development teams that prioritize code quality, maintainability, and long-term sustainability. Type-level development encourages best practices, such as code consistency, documentation, and adherence to architectural patterns.

5. Functional Programming Enthusiasts: Developers familiar with functional programming concepts and techniques. Type-level development often aligns well with functional programming principles, such as immutability, purity, and compositionality.

6. Tooling and IDE Users: Developers who rely on modern IDEs and text editors with strong TypeScript support. Type-level development leverages IDE features like auto-completion, type inference, and type checking to enhance productivity.

7. Continuous Integration and Deployment (CI/CD) Practitioners: Developers who use CI/CD pipelines for automated testing, builds, and deployments. Type-level development facilitates early error detection and reduces the risk of introducing bugs during deployment.

8. TypeScript Experts: Developers with a deep understanding of TypeScript's type system and its advanced features. Type-level development requires familiarity with concepts like conditional types, mapped types, generics, and type inference.

9. Codebase Maintainability Advocates: Developers who prioritize codebase maintainability and seek to reduce technical debt over time. Type-level development encourages clean, understandable code that is easier to maintain and refactor.

10. Enthusiastic Learners: Developers eager to explore new techniques and improve their skills. Type-level development offers opportunities to delve into advanced TypeScript concepts and expand one's knowledge of software development.

Overall, the perfect audience for type-level development comprises developers and teams who value type safety, code quality, and maintainability, and who are willing to invest in learning and applying advanced TypeScript techniques to their projects.