typescript-best-practices

安装量: 1K
排名: #1325

安装

npx skills add https://github.com/0xbigboss/claude-code --skill typescript-best-practices

TypeScript Best Practices Pair with React Best Practices

When working with React components (.tsx, .jsx files or @react imports), always load react-best-practices alongside this skill. This skill covers TypeScript fundamentals; React-specific patterns (effects, hooks, refs, component design) are in the dedicated React skill.

Type-First Development

Types define the contract before implementation. Follow this workflow:

Define the data model - types, interfaces, and schemas first Define function signatures - input/output types before logic Implement to satisfy types - let the compiler guide completeness Validate at boundaries - runtime checks where data enters the system Make Illegal States Unrepresentable

Use the type system to prevent invalid states at compile time.

Discriminated unions for mutually exclusive states:

// Good: only valid combinations possible type RequestState = | { status: 'idle' } | { status: 'loading' } | { status: 'success'; data: T } | { status: 'error'; error: Error };

// Bad: allows invalid combinations like { loading: true, error: Error } type RequestState = { loading: boolean; data?: T; error?: Error; };

Branded types for domain primitives:

type UserId = string & { readonly __brand: 'UserId' }; type OrderId = string & { readonly __brand: 'OrderId' };

// Compiler prevents passing OrderId where UserId expected function getUser(id: UserId): Promise { / ... / }

function createUserId(id: string): UserId { return id as UserId; }

Const assertions for literal unions:

const ROLES = ['admin', 'user', 'guest'] as const; type Role = typeof ROLES[number]; // 'admin' | 'user' | 'guest'

// Array and type stay in sync automatically function isValidRole(role: string): role is Role { return ROLES.includes(role as Role); }

Required vs optional fields - be explicit:

// Creation: some fields required type CreateUser = { email: string; name: string; };

// Update: all fields optional type UpdateUser = Partial;

// Database row: all fields present type User = CreateUser & { id: UserId; createdAt: Date; };

Module Structure

Prefer smaller, focused files: one component, hook, or utility per file. Split when a file handles multiple concerns or exceeds ~200 lines. Colocate tests with implementation (foo.test.ts alongside foo.ts). Group related files by feature rather than by type.

Functional Patterns Prefer const over let; use readonly and Readonly for immutable data. Use array.map/filter/reduce over for loops; chain transformations in pipelines. Write pure functions for business logic; isolate side effects in dedicated modules. Avoid mutating function parameters; return new objects/arrays instead. Instructions Enable strict mode; model data with interfaces and types. Strong typing catches bugs at compile time. Every code path returns a value or throws; use exhaustive switch with never checks in default. Unhandled cases become compile errors. Propagate errors with context; catching requires re-throwing or returning a meaningful result. Hidden failures delay debugging. Handle edge cases explicitly: empty arrays, null/undefined inputs, boundary values. Defensive checks prevent runtime surprises. Use await for async calls; wrap external calls with contextual error messages. Unhandled rejections crash Node processes. Add or update focused tests when changing logic; test behavior, not implementation details. Examples

Explicit failure for unimplemented logic:

export function buildWidget(widgetType: string): never { throw new Error(buildWidget not implemented for type: ${widgetType}); }

Exhaustive switch with never check:

type Status = "active" | "inactive";

export function processStatus(status: Status): string { switch (status) { case "active": return "processing"; case "inactive": return "skipped"; default: { const _exhaustive: never = status; throw new Error(unhandled status: ${_exhaustive}); } } }

Wrap external calls with context:

export async function fetchWidget(id: string): Promise { const response = await fetch(/api/widgets/${id}); if (!response.ok) { throw new Error(fetch widget ${id} failed: ${response.status}); } return response.json(); }

Debug logging with namespaced logger:

import debug from "debug";

const log = debug("myapp:widgets");

export function createWidget(name: string): Widget { log("creating widget: %s", name); const widget = { id: crypto.randomUUID(), name }; log("created widget: %s", widget.id); return widget; }

Runtime Validation with Zod Define schemas as single source of truth; infer TypeScript types with z.infer<>. Avoid duplicating types and schemas. Use safeParse for user input where failure is expected; use parse at trust boundaries where invalid data is a bug. Compose schemas with .extend(), .pick(), .omit(), .merge() for DRY definitions. Add .transform() for data normalization at parse time (trim strings, parse dates). Include descriptive error messages; use .refine() for custom validation logic. Examples

Schema as source of truth with type inference:

import { z } from "zod";

const UserSchema = z.object({ id: z.string().uuid(), email: z.string().email(), name: z.string().min(1), createdAt: z.string().transform((s) => new Date(s)), });

type User = z.infer;

Return parse results to callers (never swallow errors):

import { z, SafeParseReturnType } from "zod";

export function parseUserInput(raw: unknown): SafeParseReturnType { return UserSchema.safeParse(raw); }

// Caller handles both success and error: const result = parseUserInput(formData); if (!result.success) { setErrors(result.error.flatten().fieldErrors); return; } await submitUser(result.data);

Strict parsing at trust boundaries:

export async function fetchUser(id: string): Promise { const response = await fetch(/api/users/${id}); if (!response.ok) { throw new Error(fetch user ${id} failed: ${response.status}); } const data = await response.json(); return UserSchema.parse(data); // throws if API contract violated }

Schema composition:

const CreateUserSchema = UserSchema.omit({ id: true, createdAt: true }); const UpdateUserSchema = CreateUserSchema.partial(); const UserWithPostsSchema = UserSchema.extend({ posts: z.array(PostSchema), });

Configuration Load config from environment variables at startup; validate with Zod before use. Invalid config should crash immediately. Define a typed config object as single source of truth; avoid accessing process.env throughout the codebase. Use sensible defaults for development; require explicit values for production secrets. Examples

Typed config with Zod validation:

import { z } from "zod";

const ConfigSchema = z.object({ PORT: z.coerce.number().default(3000), DATABASE_URL: z.string().url(), API_KEY: z.string().min(1), NODE_ENV: z.enum(["development", "production", "test"]).default("development"), });

export const config = ConfigSchema.parse(process.env);

Access config values (not process.env directly):

import { config } from "./config";

const server = app.listen(config.PORT); const db = connect(config.DATABASE_URL);

Optional: type-fest

For advanced type utilities beyond TypeScript builtins, consider type-fest:

Opaque - cleaner branded types than manual & { __brand } pattern PartialDeep - recursive partial for nested objects ReadonlyDeep - recursive readonly for immutable data LiteralUnion - literals with autocomplete + string fallback SetRequired / SetOptional - targeted field modifications Simplify - flatten complex intersection types in IDE tooltips import type { Opaque, PartialDeep, SetRequired } from 'type-fest';

// Branded type (cleaner than manual approach) type UserId = Opaque;

// Deep partial for patch operations type UserPatch = PartialDeep;

// Make specific fields required type UserWithEmail = SetRequired, 'email'>;

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