TypeScript's type compatibility is based on a structural type system rather than a nominal type system, meaning types are compatible as long as their structures match. For object types, compatibility requires that all properties of the target type exist in the source type and that their types are compatible. For function types, compatibility considers both parameters and return values: - Parameters follow bivariant rules. - Return values follow covariant rules. Class type compatibility is similar to objects, but private members from different declarations make them incompatible. Generic type compatibility depends on how the type parameters are used. Enums are compatible with numbers, but different enums are not compatible with each other. Union types must account for all possible types, while intersection types must satisfy all constituent types. Advanced types like index signatures, mapped types, and conditional types have specific compatibility rules. Type inference, contextual typing, and strict mode settings can also influence compatibility judgments.
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TypeScript enumeration type is a special data type used to define named constant collections. It is declared via the `enum` keyword and supports numeric enums, string enums, and heterogeneous enums. Numeric enum members default to incrementing from 0 but can be manually assigned values. String enums require explicit initialization and do not generate reverse mappings. Enums compile into bidirectional mapping objects, allowing access by name or value. Const enums are declared with `const enum` and are removed during compilation, retaining only the used values to reduce code volume. Enum members are categorized as constant members or computed members. Enums are suitable for replacing magic numbers, managing states, and representing configuration options but have limitations in type safety and potential code bloat. Compared to union types, enums support reverse mapping and iteration. Compared to object constants, enums provide better type safety. Best practices include choosing the appropriate enum type, following naming conventions, and considering performance impacts. Enums support declaration merging and namespace extension for adding static methods.
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In TypeScript, both `unknown` and `any` are top types but behave differently. `any` allows bypassing type checks, while `unknown` enforces type checking. Values of type `any` can be directly manipulated, whereas `unknown` requires type assertions or checks before use. `any` is suitable for migrating legacy code or interacting with third-party libraries, while `unknown` is better for handling uncertain data (e.g., API responses) to implement type-safe dynamic code. For function return types, `unknown` forces callers to handle type uncertainty, whereas `any` shifts responsibility to the caller. In generic programming, `unknown` is safer than `any` as it doesn’t compromise type system integrity. `unknown` works best with type guards, allowing gradual narrowing of the type scope. For error handling, `unknown` is the better choice, as it forces developers to explicitly handle unexpected types. From a development experience perspective, `unknown` offers better long-term benefits, though there’s no runtime performance difference.
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In TypeScript, the `never` and `void` types are used to represent function return values but have different semantics. `void` indicates that a function does not return a value, while `never` signifies that a function never returns normally. `void` is suitable for functions with no return value, such as logging functions, whereas `never` is used for functions that always throw an error or enter an infinite loop. `void` allows returning `undefined`, while `never` is a subtype of all types and can be assigned to any type, but no other type can be assigned to `never`. In union types, `void` is preserved, while `never` is ignored. In practice, `void` is commonly used for event handlers, and `never` is employed for exhaustive checks and advanced type utilities. Understanding their distinctions is crucial for writing type-safe code.
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TypeScript 4.1 introduced template literal types, enhancing the type system by allowing developers to manipulate types similarly to JavaScript template strings but at the type level. It uses backticks for wrapping and inserts other types via syntax, supporting string literal union types or recursive definitions. When interacting with union types, it computes all possible combinations. It provides built-in utility types like `Uppercase` and, when combined with mapped types, enables powerful type transformations. It supports type inference and pattern matching, with practical applications including type-safe CSS class names, event handling, API routing, and more. Advanced patterns like recursive template types and string parsing are possible, but performance considerations should be noted to avoid overuse. Combined with conditional types, it enables complex type operations and allows creating custom type guards to check string templates. However, there are limitations: dynamically generating infinite type combinations is not possible, complex templates may cause performance issues, and some pattern matching lacks flexibility.
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TypeScript enhances code type safety through type guards and type narrowing mechanisms. Type guards are runtime checks used to determine the specific type of a variable, while type narrowing refers to the compiler automatically reducing the type scope of a variable based on the check results. The `typeof` type guard checks JavaScript types, and `instanceof` is suitable for custom classes or built-in objects. Custom type guards are implemented via type predicate functions. Discriminated unions use shared tag properties for narrowing. Truthiness narrowing handles values that might be `null` or `undefined`. Equality narrowing is particularly useful for literal types. The `in` operator checks object properties to achieve narrowing. Type assertions force narrowing without runtime checks. Control flow analysis tracks variable type changes. The `never` type is used for exhaustive checks to ensure all possible types are handled. In generics, type narrowing requires attention to type parameter constraints. Type narrowing may have limitations in complex logic or asynchronous code.
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TypeScript's type inference mechanism allows the compiler to automatically determine variable types without explicit annotations, including primitive types and complex objects. Function return values and contextual type inference are particularly useful in specific scenarios, such as event handler functions and array method callbacks. Type assertions enable developers to override the compiler's inference, with two syntax forms: angle brackets and the `as` syntax, commonly used when handling DOM elements and API response data. Unlike type declarations, type assertions do not actually convert types and may lead to runtime errors. Best practices include prioritizing type inference, avoiding unnecessary type assertions, and performing type checks on external data. Advanced techniques like `const` assertions, the `satisfies` operator, and type predicates can enhance type safety.
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TypeScript's conditional types and distributive conditional types are advanced features in the type system that enable dynamic derivation of complex type relationships based on input types. Conditional types use a ternary expression-like syntax to implement type-level conditional judgments, often combined with generics to create dynamic type inference. Distributive conditional types automatically distribute over union types, breaking them into multiple conditional type combinations, which is particularly useful for filtering union types. The `infer` keyword allows declaring temporary type variables within conditional types to capture deep type information. In practical applications, conditional types can be used for React prop handling, Redux action type processing, and more. Recursive conditional types support self-referencing and can handle nested structures. Combined with template literal types, they enable string manipulation. However, overly complex conditional types may impact performance, requiring optimization. When combined with mapped types, conditional types can create flexible type transformation utilities, enhancing type programming capabilities.
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TypeScript's index signatures and mapped types are powerful tools for handling dynamic properties and type transformations. Index signatures, using the `[key: KeyType]: ValueType` syntax, allow objects to have flexible structures, supporting key types like `string`, `number`, and `symbol`. Mapped types, on the other hand, generate new types by iterating over union types with the `in` keyword. Combining these two can significantly enhance code flexibility. Index signatures are ideal for handling dynamic data, such as API responses and array-like objects, while mapped types can create utility types like `Partial` and `Readonly`, and even integrate with conditional types for complex transformations. Advanced techniques include using the `as` clause to rename keys and performing deep recursive transformations. In practice, it's essential to balance type safety and flexibility, avoiding overuse of index signatures. A best practice is to prioritize precise types and resort to the `Record` utility type when necessary. Typical use cases include configuration object handling and enum conversions. Type gymnastics examples demonstrate advanced patterns like deep `Readonly` and key-value flipping. Together, these features strengthen TypeScript's type system capabilities.
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In TypeScript, type aliases and interfaces are the two primary ways to define custom types. Type aliases, declared with the `type` keyword, can represent primitive types, union types, tuples, and more, while interfaces, declared with `interface`, focus on describing the shape of objects. Interfaces support `extends` inheritance and declaration merging, whereas type aliases use intersection types for composition and cannot be redeclared. Both can be implemented by classes, but type aliases are more suitable for complex types like recursive structures and union types. Interfaces may offer better performance in large-scale projects. In practice, interfaces are preferred when declaration merging is needed, while type aliases are chosen for non-object types like unions or tuples. Library type definitions often prioritize interfaces for easier extensibility. Type aliases support advanced features like conditional and mapped types, whereas interfaces align more with traditional object-oriented thinking when describing class structures. Both exhibit similar type compatibility and overlap in most use cases.
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