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Designing type-safe sync/async mode support in TypeScript

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  • I recently added sync/async mode support to Optique, a type-safe CLI parser
    for TypeScript. It turned out to be one of the trickier features I've
    implemented—the object() combinator alone needed to compute a combined mode
    from all its child parsers, and TypeScript's inference kept hitting edge cases.

    What is Optique?

    Optique is a type-safe, combinatorial CLI parser for TypeScript, inspired by
    Haskell's optparse-applicative. Instead of decorators or builder patterns,
    you compose small parsers into larger ones using combinators, and TypeScript
    infers the result types.

    Here's a quick taste:

    import { object } from "@optique/core/constructs";
    import { argument, option } from "@optique/core/primitives";
    import { string, integer } from "@optique/core/valueparser";
    import { run } from "@optique/run";
    
    const cli = object({
      name: argument(string()),
      count: option("-n", "--count", integer()),
    });
    
    // TypeScript infers: { name: string; count: number | undefined }
    const result = run(cli);  // sync by default
    

    The type inference works through arbitrarily deep compositions—in most cases,
    you don't need explicit type annotations.

    How it started

    Lucas Garron (@lgarron@mastodon.social) opened an issue requesting
    async support for shell completions. He wanted to provide
    <kbd>Tab</kbd>-completion suggestions by running shell commands like
    git for-each-ref to list branches and tags.

    // Lucas's example: fetching Git branches and tags in parallel
    const [branches, tags] = await Promise.all([
      $`git for-each-ref --format='%(refname:short)' refs/heads/`.text(),
      $`git for-each-ref --format='%(refname:short)' refs/tags/`.text(),
    ]);
    

    At first, I didn't like the idea. Optique's entire API was synchronous, which
    made it simpler to reason about and avoided the “async infection” problem where
    one async function forces everything upstream to become async. I argued that
    shell completion should be near-instantaneous, and if you need async data, you
    should cache it at startup.

    But Lucas pushed back. The filesystem is a database, and many useful
    completions inherently require async work—Git refs change constantly, and
    pre-caching everything at startup doesn't scale for large repos. Fair point.

    What I needed to solve

    So, how do you support both sync and async execution modes in a composable
    parser library while maintaining type safety?

    The key requirements were:

    • parse() returns T or Promise<T>
    • complete() returns T or Promise<T>
    • suggest() returns Iterable<T> or AsyncIterable<T>
    • When combining parsers, if any parser is async, the combined result
      must be async
    • Existing sync code should continue to work unchanged

    The fourth requirement is the tricky one. Consider this:

    const syncParser = flag("--verbose");
    const asyncParser = option("--branch", asyncValueParser);
    
    // What's the type of this?
    const combined = object({ verbose: syncParser, branch: asyncParser });
    

    The combined parser should be async because one of its fields is async.
    This means we need type-level logic to compute the combined mode.

    Five design options

    I explored five different approaches, each with its own trade-offs.

    Option A: conditional types with mode parameter

    Add a mode type parameter to Parser and use conditional types:

    type Mode = "sync" | "async";
    
    type ModeValue<M extends Mode, T> = M extends "async" ? Promise<T> : T;
    
    interface Parser<M extends Mode, TValue, TState> {
      parse(context: ParserContext<TState>): ModeValue<M, ParserResult<TState>>;
      // ...
    }
    

    The challenge is computing combined modes:

    type CombineModes<T extends Record<string, Parser<any, any, any>>> =
      T[keyof T] extends Parser<infer M, any, any>
        ? M extends "async" ? "async" : "sync"
        : never;
    

    Option B: mode parameter with default value

    A variant of Option A, but place the mode parameter first with a default
    of "sync":

    interface Parser<M extends Mode = "sync", TValue, TState> {
      readonly $mode: M;
      // ...
    }
    

    The default value maintains backward compatibility—existing user code keeps
    working without changes.

    Option C: separate interfaces

    Define completely separate Parser and AsyncParser interfaces with
    explicit conversion:

    interface Parser<TValue, TState> { /* sync methods */ }
    interface AsyncParser<TValue, TState> { /* async methods */ }
    
    function toAsync<T, S>(parser: Parser<T, S>): AsyncParser<T, S>;
    

    Simpler to understand, but requires code duplication and explicit conversions.

    Option D: union return types for suggest() only

    The minimal approach. Only allow suggest() to be async:

    interface Parser<TValue, TState> {
      parse(context: ParserContext<TState>): ParserResult<TState>;  // always sync
      suggest(context: ParserContext<TState>, prefix: string):
        Iterable<Suggestion> | AsyncIterable<Suggestion>;  // can be either
    }
    

    This addresses the original use case but doesn't help if async parse() is
    ever needed.

    Option E: fp-ts style HKT simulation

    Use the technique from fp-ts to simulate Higher-Kinded Types:

    interface URItoKind<A> {
      Identity: A;
      Promise: Promise<A>;
    }
    
    type Kind<F extends keyof URItoKind<any>, A> = URItoKind<A>[F];
    
    interface Parser<F extends keyof URItoKind<any>, TValue, TState> {
      parse(context: ParserContext<TState>): Kind<F, ParserResult<TState>>;
    }
    

    The most flexible approach, but with a steep learning curve.

    Testing the idea

    Rather than commit to an approach based on theoretical analysis, I created
    a prototype to test how well TypeScript handles the type inference in practice.
    I published my findings in the GitHub issue:

    Both approaches correctly handle the “any async → all async” rule at the
    type level. (…) Complex conditional types like
    ModeValue<CombineParserModes<T>, ParserResult<TState>> sometimes require
    explicit type casting in the implementation. This only affects library
    internals. The user-facing API remains clean.

    The prototype validated that Option B (explicit mode parameter with default)
    would work. I chose it for these reasons:

    • Backward compatible: The default "sync" keeps existing code working
    • Explicit: The mode is visible in both types and runtime (via a $mode
      property)
    • Debuggable: Easy to inspect the current mode at runtime
    • Better IDE support: Type information is more predictable

    How CombineModes works

    The CombineModes type computes whether a combined parser should be sync or
    async:

    type CombineModes<T extends readonly Mode[]> = "async" extends T[number]
      ? "async"
      : "sync";
    

    This type checks if "async" is present anywhere in the tuple of modes.
    If so, the result is "async"; otherwise, it's "sync".

    For combinators like object(), I needed to extract modes from parser
    objects and combine them:

    // Extract the mode from a single parser
    type ParserMode<T> = T extends Parser<infer M, unknown, unknown> ? M : never;
    
    // Combine modes from all values in a record of parsers
    type CombineObjectModes<T extends Record<string, Parser<Mode, unknown, unknown>>> =
      CombineModes<{ [K in keyof T]: ParserMode<T[K]> }[keyof T][]>;
    

    Runtime implementation

    The type system handles compile-time safety, but the implementation also needs
    runtime logic. Each parser has a $mode property that indicates its execution
    mode:

    const syncParser = option("-n", "--name", string());
    console.log(syncParser.$mode);  // "sync"
    
    const asyncParser = option("-b", "--branch", asyncValueParser);
    console.log(asyncParser.$mode);  // "async"
    

    Combinators compute their mode at construction time:

    function object<T extends Record<string, Parser<Mode, unknown, unknown>>>(
      parsers: T
    ): Parser<CombineObjectModes<T>, ObjectValue<T>, ObjectState<T>> {
      const parserKeys = Reflect.ownKeys(parsers);
      const combinedMode: Mode = parserKeys.some(
        (k) => parsers[k as keyof T].$mode === "async"
      ) ? "async" : "sync";
    
      // ... implementation
    }
    

    Refining the API

    Lucas suggested an important refinement during our
    discussion. Instead of having run() automatically choose between sync and
    async based on the parser mode, he proposed separate functions:

    Perhaps run(…) could be automatic, and runSync(…) and runAsync(…) could
    enforce that the inferred type matches what is expected.

    So we ended up with:

    • run(): automatic based on parser mode
    • runSync(): enforces sync mode at compile time
    • runAsync(): enforces async mode at compile time
    // Automatic: returns T for sync parsers, Promise<T> for async
    const result1 = run(syncParser);  // string
    const result2 = run(asyncParser);  // Promise<string>
    
    // Explicit: compile-time enforcement
    const result3 = runSync(syncParser);  // string
    const result4 = runAsync(asyncParser);  // Promise<string>
    
    // Compile error: can't use runSync with async parser
    const result5 = runSync(asyncParser);  // Type error!
    

    I applied the same pattern to parse()/parseSync()/parseAsync() and
    suggest()/suggestSync()/suggestAsync() in the facade functions.

    Creating async value parsers

    With the new API, creating an async value parser for Git branches looks
    like this:

    import type { Suggestion } from "@optique/core/parser";
    import type { ValueParser, ValueParserResult } from "@optique/core/valueparser";
    
    function gitRef(): ValueParser<"async", string> {
      return {
        $mode: "async",
        metavar: "REF",
        parse(input: string): Promise<ValueParserResult<string>> {
          return Promise.resolve({ success: true, value: input });
        },
        format(value: string): string {
          return value;
        },
        async *suggest(prefix: string): AsyncIterable<Suggestion> {
          const { $ } = await import("bun");
          const [branches, tags] = await Promise.all([
            $`git for-each-ref --format='%(refname:short)' refs/heads/`.text(),
            $`git for-each-ref --format='%(refname:short)' refs/tags/`.text(),
          ]);
          for (const ref of [...branches.split("\n"), ...tags.split("\n")]) {
            const trimmed = ref.trim();
            if (trimmed && trimmed.startsWith(prefix)) {
              yield { kind: "literal", text: trimmed };
            }
          }
        },
      };
    }
    

    Notice that parse() returns Promise.resolve() even though it's synchronous.
    This is because the ValueParser<"async", T> type requires all methods to use
    async signatures. Lucas pointed out this is a minor ergonomic issue. If only
    suggest() needs to be async, you still have to wrap parse() in a Promise.

    I considered per-method mode granularity (e.g., ValueParser<ParseMode, SuggestMode, T>), but the implementation complexity would multiply
    substantially. For now, the workaround is simple enough:

    // Option 1: Use Promise.resolve()
    parse(input) {
      return Promise.resolve({ success: true, value: input });
    }
    
    // Option 2: Mark as async and suppress the linter
    // biome-ignore lint/suspicious/useAwait: sync implementation in async ValueParser
    async parse(input) {
      return { success: true, value: input };
    }
    

    What it cost

    Supporting dual modes added significant complexity to Optique's internals.
    Every combinator needed updates:

    • Type signatures grew more complex with mode parameters
    • Mode propagation logic had to be added to every combinator
    • Dual implementations were needed for sync and async code paths
    • Type casts were sometimes necessary in the implementation to satisfy
      TypeScript

    For example, the object() combinator went from around 100 lines to around
    250 lines. The internal implementation uses conditional logic based on the
    combined mode:

    if (combinedMode === "async") {
      return {
        $mode: "async" as M,
        // ... async implementation with Promise chains
        async parse(context) {
          // ... await each field's parse result
        },
      };
    } else {
      return {
        $mode: "sync" as M,
        // ... sync implementation
        parse(context) {
          // ... directly call each field's parse
        },
      };
    }
    

    This duplication is the cost of supporting both modes without runtime overhead
    for sync-only use cases.

    Lessons learned

    Listen to users, but validate with prototypes

    My initial instinct was to resist async support. Lucas's persistence and
    concrete examples changed my mind, but I validated the approach with a
    prototype before committing. The prototype revealed practical issues (like
    TypeScript inference limits) that pure design analysis would have missed.

    Backward compatibility is worth the complexity

    Making "sync" the default mode meant existing code continued to work
    unchanged. This was a deliberate choice. Breaking changes should require
    user action, not break silently.

    Unified mode vs per-method granularity

    I chose unified mode (all methods share the same sync/async mode) over
    per-method granularity. This means users occasionally write
    Promise.resolve() for methods that don't actually need async, but the
    alternative was multiplicative complexity in the type system.

    Designing in public

    The entire design process happened in a public GitHub issue. Lucas, Giuseppe,
    and others contributed ideas that shaped the final API. The
    runSync()/runAsync() distinction came directly from Lucas's feedback.

    Conclusion

    This was one of the more challenging features I've implemented in Optique.
    TypeScript's type system is powerful enough to encode the “any async means all
    async” rule at compile time, but getting there required careful design work and
    prototyping.

    What made it work: conditional types like ModeValue<M, T> can bridge the gap
    between sync and async worlds. You pay for it with implementation complexity,
    but the user-facing API stays clean and type-safe.

    Optique 0.9.0 with async support is currently in pre-release testing. If
    you'd like to try it, check out PR #70 or install the pre-release:

    npm  add       @optique/core@0.9.0-dev.212 @optique/run@0.9.0-dev.212
    deno add --jsr @optique/core@0.9.0-dev.212 @optique/run@0.9.0-dev.212
    

    Feedback is welcome!

  • hongminhee@hollo.socialundefined hongminhee@hollo.social shared this topic on

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    @tanuki no but I'll take a look, thanks for the recommendation 🙇
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    Consider Git's -C option: git -C /path/to/repo checkout <TAB> When you hit <kbd>Tab</kbd>, Git completes branch names from /path/to/repo, not your current directory. The completion is context-aware—it depends on the value of another option. Most CLI parsers can't do this. They treat each option in isolation, so completion for --branch has no way of knowing the --repo value. You end up with two unpleasant choices: either show completions for all possible branches across all repositories (useless), or give up on completion entirely for these options. Optique 0.10.0 introduces a dependency system that solves this problem while preserving full type safety. Static dependencies with or() Optique already handles certain kinds of dependent options via the or() combinator: import { flag, object, option, or, string } from "@optique/core"; const outputOptions = or( object({ json: flag("--json"), pretty: flag("--pretty"), }), object({ csv: flag("--csv"), delimiter: option("--delimiter", string()), }), ); TypeScript knows that if json is true, you'll have a pretty field, and if csv is true, you'll have a delimiter field. The parser enforces this at runtime, and shell completion will suggest --pretty only when --json is present. This works well when the valid combinations are known at definition time. But it can't handle cases where valid values depend on runtime input—like branch names that vary by repository. Runtime dependencies Common scenarios include: A deployment CLI where --environment affects which services are available A database tool where --connection affects which tables can be completed A cloud CLI where --project affects which resources are shown In each case, you can't know the valid values until you know what the user typed for the dependency option. Optique 0.10.0 introduces dependency() and derive() to handle exactly this. The dependency system The core idea is simple: mark one option as a dependency source, then create derived parsers that use its value. import { choice, dependency, message, object, option, string, } from "@optique/core"; function getRefsFromRepo(repoPath: string): string[] { // In real code, this would read from the Git repository return ["main", "develop", "feature/login"]; } // Mark as a dependency source const repoParser = dependency(string()); // Create a derived parser const refParser = repoParser.derive({ metavar: "REF", factory: (repoPath) => { const refs = getRefsFromRepo(repoPath); return choice(refs); }, defaultValue: () => ".", }); const parser = object({ repo: option("--repo", repoParser, { description: message`Path to the repository`, }), ref: option("--ref", refParser, { description: message`Git reference`, }), }); The factory function is where the dependency gets resolved. It receives the actual value the user provided for --repo and returns a parser that validates against refs from that specific repository. Under the hood, Optique uses a three-phase parsing strategy: Parse all options in a first pass, collecting dependency values Call factory functions with the collected values to create concrete parsers Re-parse derived options using those dynamically created parsers This means both validation and completion work correctly—if the user has already typed --repo /some/path, the --ref completion will show refs from that path. Repository-aware completion with @optique/git The @optique/git package provides async value parsers that read from Git repositories. Combined with the dependency system, you can build CLIs with repository-aware completion: import { command, dependency, message, object, option, string, } from "@optique/core"; import { gitBranch } from "@optique/git"; const repoParser = dependency(string()); const branchParser = repoParser.deriveAsync({ metavar: "BRANCH", factory: (repoPath) => gitBranch({ dir: repoPath }), defaultValue: () => ".", }); const checkout = command( "checkout", object({ repo: option("--repo", repoParser, { description: message`Path to the repository`, }), branch: option("--branch", branchParser, { description: message`Branch to checkout`, }), }), ); Now when you type my-cli checkout --repo /path/to/project --branch <TAB>, the completion will show branches from /path/to/project. The defaultValue of "." means that if --repo isn't specified, it falls back to the current directory. Multiple dependencies Sometimes a parser needs values from multiple options. The deriveFrom() function handles this: import { choice, dependency, deriveFrom, message, object, option, } from "@optique/core"; function getAvailableServices(env: string, region: string): string[] { return [`${env}-api-${region}`, `${env}-web-${region}`]; } const envParser = dependency(choice(["dev", "staging", "prod"] as const)); const regionParser = dependency(choice(["us-east", "eu-west"] as const)); const serviceParser = deriveFrom({ dependencies: [envParser, regionParser] as const, metavar: "SERVICE", factory: (env, region) => { const services = getAvailableServices(env, region); return choice(services); }, defaultValues: () => ["dev", "us-east"] as const, }); const parser = object({ env: option("--env", envParser, { description: message`Deployment environment`, }), region: option("--region", regionParser, { description: message`Cloud region`, }), service: option("--service", serviceParser, { description: message`Service to deploy`, }), }); The factory receives values in the same order as the dependency array. If some dependencies aren't provided, Optique uses the defaultValues. Async support Real-world dependency resolution often involves I/O—reading from Git repositories, querying APIs, accessing databases. Optique provides async variants for these cases: import { dependency, string } from "@optique/core"; import { gitBranch } from "@optique/git"; const repoParser = dependency(string()); const branchParser = repoParser.deriveAsync({ metavar: "BRANCH", factory: (repoPath) => gitBranch({ dir: repoPath }), defaultValue: () => ".", }); The @optique/git package uses isomorphic-git under the hood, so gitBranch(), gitTag(), and gitRef() all work in both Node.js and Deno. There's also deriveSync() for when you need to be explicit about synchronous behavior, and deriveFromAsync() for multiple async dependencies. Wrapping up The dependency system lets you build CLIs where options are aware of each other—not just for validation, but for shell completion too. You get type safety throughout: TypeScript knows the relationship between your dependency sources and derived parsers, and invalid combinations are caught at compile time. This is particularly useful for tools that interact with external systems where the set of valid values isn't known until runtime. Git repositories, cloud providers, databases, container registries—anywhere the completion choices depend on context the user has already provided. This feature will be available in Optique 0.10.0. To try the pre-release: deno add jsr:@optique/core@0.10.0-dev.311 Or with npm: npm install @optique/core@0.10.0-dev.311 See the documentation for more details.
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    We've all been there. You start a quick TypeScript CLI with process.argv.slice(2), add a couple of options, and before you know it you're drowning in if/else blocks and parseInt calls. It works, until it doesn't. In this guide, we'll move from manual argument parsing to a fully type-safe CLI with subcommands, mutually exclusive options, and shell completion. The naïve approach: parsing process.argv Let's start with the most basic approach. Say we want a greeting program that takes a name and optionally repeats the greeting: // greet.ts const args = process.argv.slice(2); let name: string | undefined; let count = 1; for (let i = 0; i < args.length; i++) { if (args[i] === "--name" || args[i] === "-n") { name = args[++i]; } else if (args[i] === "--count" || args[i] === "-c") { count = parseInt(args[++i], 10); } } if (!name) { console.error("Error: --name is required"); process.exit(1); } for (let i = 0; i < count; i++) { console.log(`Hello, ${name}!`); } Run node greet.js --name Alice --count 3 and you'll get three greetings. But this approach is fragile. count could be NaN if someone passes --count foo, and we'd silently proceed. There's no help text. If someone passes --name without a value, we'd read the next option as the name. And the boilerplate grows fast with each new option. The traditional libraries You've probably heard of Commander.js and Yargs. They've been around for years and solve the basic problems: // With Commander.js import { program } from "commander"; program .requiredOption("-n, --name <n>", "Name to greet") .option("-c, --count <number>", "Number of times to greet", "1") .parse(); const opts = program.opts(); These libraries handle help text, option parsing, and basic validation. But they were designed before TypeScript became mainstream, and the type safety is bolted on rather than built in. The real problem shows up when you need mutually exclusive options. Say your CLI works either in "server mode" (with --port and --host) or "client mode" (with --url). With these libraries, you end up with a config object where all options are potentially present, and you're left writing runtime checks to ensure the user didn't mix incompatible flags. TypeScript can't help you because the types don't reflect the actual constraints. Enter Optique Optique takes a different approach. Instead of configuring options declaratively, you build parsers by composing smaller parsers together. The types flow naturally from this composition, so TypeScript always knows exactly what shape your parsed result will have. Optique works across JavaScript runtimes: Node.js, Deno, and Bun are all supported. The core parsing logic has no runtime-specific dependencies, so you can even use it in browsers if you need to parse CLI-like arguments in a web context. Let's rebuild our greeting program: import { object } from "@optique/core/constructs"; import { option } from "@optique/core/primitives"; import { integer, string } from "@optique/core/valueparser"; import { withDefault } from "@optique/core/modifiers"; import { run } from "@optique/run"; const parser = object({ name: option("-n", "--name", string()), count: withDefault(option("-c", "--count", integer({ min: 1 })), 1), }); const config = run(parser); // config is typed as { name: string; count: number } for (let i = 0; i < config.count; i++) { console.log(`Hello, ${config.name}!`); } Types are inferred automatically. config.name is string, not string | undefined. config.count is number, guaranteed to be at least 1. Validation is built in: integer({ min: 1 }) rejects non-integers and values below 1 with clear error messages. Help text is generated automatically, and the run() function handles errors and exits with appropriate codes. Install it with your package manager of choice: npm add @optique/core @optique/run # or: pnpm add, yarn add, bun add, deno add jsr:@optique/core jsr:@optique/run Building up: a file converter Let's build something more realistic: a file converter that reads from an input file, converts to a specified format, and writes to an output file. import { object } from "@optique/core/constructs"; import { optional, withDefault } from "@optique/core/modifiers"; import { argument, option } from "@optique/core/primitives"; import { choice, string } from "@optique/core/valueparser"; import { run } from "@optique/run"; const parser = object({ input: argument(string({ metavar: "INPUT" })), output: option("-o", "--output", string({ metavar: "FILE" })), format: withDefault( option("-f", "--format", choice(["json", "yaml", "toml"])), "json" ), pretty: option("-p", "--pretty"), verbose: option("-v", "--verbose"), }); const config = run(parser, { help: "both", version: { mode: "both", value: "1.0.0" }, }); // config.input: string // config.output: string // config.format: "json" | "yaml" | "toml" // config.pretty: boolean // config.verbose: boolean The type of config.format isn't just string. It's the union "json" | "yaml" | "toml". TypeScript will catch typos like config.format === "josn" at compile time. The choice() parser is useful for any option with a fixed set of valid values: log levels, output formats, environment names, and so on. You get both runtime validation (invalid values are rejected with helpful error messages) and compile-time checking (TypeScript knows the exact set of possible values). Mutually exclusive options Now let's tackle the case that trips up most CLI libraries: mutually exclusive options. Say our tool can either run as a server or connect as a client, but not both: import { object, or } from "@optique/core/constructs"; import { withDefault } from "@optique/core/modifiers"; import { argument, constant, option } from "@optique/core/primitives"; import { integer, string, url } from "@optique/core/valueparser"; import { run } from "@optique/run"; const parser = or( // Server mode object({ mode: constant("server"), port: option("-p", "--port", integer({ min: 1, max: 65535 })), host: withDefault(option("-h", "--host", string()), "0.0.0.0"), }), // Client mode object({ mode: constant("client"), url: argument(url()), }), ); const config = run(parser); The or() combinator tries each alternative in order. The first one that successfully parses wins. The constant() parser adds a literal value to the result without consuming any input, which serves as a discriminator. TypeScript infers a discriminated union: type Config = | { mode: "server"; port: number; host: string } | { mode: "client"; url: URL }; Now you can write type-safe code that handles each mode: if (config.mode === "server") { console.log(`Starting server on ${config.host}:${config.port}`); } else { console.log(`Connecting to ${config.url.hostname}`); } Try accessing config.url in the server branch. TypeScript won't let you. The compiler knows that when mode is "server", only port and host exist. This is the key difference from configuration-based libraries. With Commander or Yargs, you'd get a type like { port?: number; host?: string; url?: string } and have to check at runtime which combination of fields is actually present. With Optique, the types match the actual constraints of your CLI. Subcommands For larger tools, you'll want subcommands. Optique handles this with the command() parser: import { object, or } from "@optique/core/constructs"; import { optional } from "@optique/core/modifiers"; import { argument, command, constant, option } from "@optique/core/primitives"; import { string } from "@optique/core/valueparser"; import { run } from "@optique/run"; const parser = or( command("add", object({ action: constant("add"), key: argument(string({ metavar: "KEY" })), value: argument(string({ metavar: "VALUE" })), })), command("remove", object({ action: constant("remove"), key: argument(string({ metavar: "KEY" })), })), command("list", object({ action: constant("list"), pattern: optional(option("-p", "--pattern", string())), })), ); const result = run(parser, { help: "both" }); switch (result.action) { case "add": console.log(`Adding ${result.key}=${result.value}`); break; case "remove": console.log(`Removing ${result.key}`); break; case "list": console.log(`Listing${result.pattern ? ` (filter: ${result.pattern})` : ""}`); break; } Each subcommand gets its own help text. Run myapp add --help and you'll see only the options relevant to add. Run myapp --help and you'll see a summary of all available commands. The pattern here is the same as mutually exclusive options: or() to combine alternatives, constant() to add a discriminator. This consistency is one of Optique's strengths. Once you understand the basic combinators, you can build arbitrarily complex CLI structures by composing them. Shell completion Optique has built-in shell completion for Bash, zsh, fish, PowerShell, and Nushell. Enable it by passing completion: "both" to run(): const config = run(parser, { help: "both", version: { mode: "both", value: "1.0.0" }, completion: "both", }); Users can then generate completion scripts: $ myapp --completion bash >> ~/.bashrc $ myapp --completion zsh >> ~/.zshrc $ myapp --completion fish > ~/.config/fish/completions/myapp.fish The completions are context-aware. They know about your subcommands, option values, and choice() alternatives. Type myapp --format <TAB> and you'll see json, yaml, toml as suggestions. Type myapp a<TAB> and it'll complete to myapp add. Completion support is often an afterthought in CLI tools, but it makes a real difference in user experience. With Optique, you get it essentially for free. Integrating with validation libraries Already using Zod for validation in your project? The @optique/zod package lets you reuse those schemas as CLI value parsers: import { z } from "zod"; import { zod } from "@optique/zod"; import { option } from "@optique/core/primitives"; const email = option("--email", zod(z.string().email())); const port = option("--port", zod(z.coerce.number().int().min(1).max(65535))); Your existing validation logic just works. The Zod error messages are passed through to the user, so you get the same helpful feedback you're used to. Prefer Valibot? The @optique/valibot package works the same way: import * as v from "valibot"; import { valibot } from "@optique/valibot"; import { option } from "@optique/core/primitives"; const email = option("--email", valibot(v.pipe(v.string(), v.email()))); Valibot's bundle size is significantly smaller than Zod's (~10KB vs ~52KB), which can matter for CLI tools where startup time is noticeable. Tips A few things I've learned building CLIs with Optique: Start simple. Begin with object() and basic options. Add or() for mutually exclusive groups only when you need them. It's easy to over-engineer CLI parsers. Use descriptive metavars. Instead of string(), write string({ metavar: "FILE" }) or string({ metavar: "URL" }). The metavar appears in help text and error messages, so it's worth the extra few characters. Leverage withDefault(). It's better than making options optional and checking for undefined everywhere. Your code becomes cleaner when you can assume values are always present. Test your parser. Optique's core parsing functions work without process.argv, so you can unit test your parser logic: import { parse } from "@optique/core/parser"; const result = parse(parser, ["--name", "Alice", "--count", "3"]); if (result.success) { assert.equal(result.value.name, "Alice"); assert.equal(result.value.count, 3); } This is especially valuable for complex parsers with many edge cases. Going further We've covered the fundamentals, but Optique has more to offer: Async value parsers for validating against external sources, like checking if a Git branch exists or if a URL is reachable Path validation with path() for checking file existence, directory structure, and file extensions Custom value parsers for domain-specific types (though Zod/Valibot integration is usually easier) Reusable option groups with merge() for sharing common options across subcommands The @optique/temporal package for parsing dates and times using the Temporal API Check out the documentation for the full picture. The tutorial walks through the concepts in more depth, and the cookbook has patterns for common scenarios. That's it Building CLIs in TypeScript doesn't have to mean fighting with types or writing endless runtime validation. Optique lets you express constraints in a way that TypeScript actually understands, so the compiler catches mistakes before they reach production. The source is on GitHub, and packages are available on both npm and JSR. Questions or feedback? Find me on the fediverse or open an issue on the GitHub repo.
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    CLIパーサーの新しい記事を書きました。--reporterの値によって--output-fileが必須になったり禁止になったり…そういう関係、型で表現できたら楽じゃないですか? https://zenn.dev/hongminhee/articles/201ca6d2e57764 #TypeScript #CLI #Optique