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Stop writing CLI validation. Parse it right the first time.

  • I have this bad habit. When something annoys me enough times,
    I end up building a library for it. This time, it was CLI validation code.

    See, I spend a lot of time reading other people's code. Open source projects,
    work stuff, random GitHub repos I stumble upon at 2 AM. And I kept noticing this
    thing: every CLI tool has the same ugly validation code tucked away somewhere.
    You know the kind:

    if (!opts.server && opts.port) {
      throw new Error("--port requires --server flag");
    }
    
    if (opts.server && !opts.port) {
      opts.port = 3000; // default port
    }
    
    // wait, what if they pass --port without a value?
    // what if the port is out of range?
    // what if...
    

    It's not even that this code is hard to write. It's that it's everywhere.
    Every project. Every CLI tool. The same patterns, slightly different flavors.
    Options that depend on other options. Flags that can't be used together.
    Arguments that only make sense in certain modes.

    And here's what really got me: we solved this problem years ago for other types
    of data. Just… not for CLIs.

    The problem with validation

    There's this blog post that completely changed how I think about parsing.
    It's called Parse, don't validate by Alexis King. The gist? Don't parse data
    into a loose type and then check if it's valid. Parse it directly into a type
    that can only be valid.

    Think about it. When you get JSON from an API, you don't just parse it as any
    and then write a bunch of if-statements. You use something like Zod to parse
    it directly into the shape you want. Invalid data? The parser rejects it. Done.

    But with CLIs? We parse arguments into some bag of properties and then spend
    the next 100 lines checking if that bag makes sense. It's backwards.

    So yeah, I built Optique. Not because the world desperately needed another CLI
    parser (it didn't), but because I was tired of seeing—and writing—the same
    validation code everywhere.

    Three patterns I was sick of validating

    Dependent options

    This one's everywhere. You have an option that only makes sense when another
    option is enabled.

    The old way? Parse everything, then check:

    const opts = parseArgs(process.argv);
    if (!opts.server && opts.port) {
      throw new Error("--port requires --server");
    }
    if (opts.server && !opts.port) {
      opts.port = 3000;
    }
    // More validation probably lurking elsewhere...
    

    With Optique, you just describe what you want:

    const config = withDefault(
      object({
        server: flag("--server"),
        port: option("--port", integer()),
        workers: option("--workers", integer())
      }),
      { server: false }
    );
    

    Here's what TypeScript infers for config's type:

    type Config = 
      | { readonly server: false }
      | { readonly server: true; readonly port: number; readonly workers: number }
    

    The type system now understands that when server is false, port literally
    doesn't exist. Not undefined, not null—it's not there. Try to access it and
    TypeScript yells at you. No runtime validation needed.

    Mutually exclusive options

    Another classic. Pick one output format: JSON, YAML, or XML. But definitely not
    two.

    I used to write this mess:

    if ((opts.json ? 1 : 0) + (opts.yaml ? 1 : 0) + (opts.xml ? 1 : 0) > 1) {
      throw new Error('Choose only one output format');
    }
    

    (Don't judge me, you've written something similar.)

    Now?

    const format = or(
      map(option("--json"), () => "json" as const),
      map(option("--yaml"), () => "yaml" as const),
      map(option("--xml"), () => "xml" as const)
    );
    

    The or() combinator means exactly one succeeds. The result is just
    "json" | "yaml" | "xml". A single string. Not three booleans to juggle.

    Environment-specific requirements

    Production needs auth. Development needs debug flags. Docker needs different
    options than local. You know the drill.

    Instead of a validation maze, you just describe each environment:

    const envConfig = or(
      object({
        env: constant("prod"),
        auth: option("--auth", string()),      // Required in prod
        ssl: option("--ssl"),
        monitoring: option("--monitoring", url())
      }),
      object({
        env: constant("dev"),
        debug: optional(option("--debug")),    // Optional in dev
        verbose: option("--verbose")
      })
    );
    

    No auth in production? Parser fails immediately. Trying to access --auth in
    dev mode? TypeScript won't let you—the field doesn't exist on that type.

    “But parser combinators though…”

    I know, I know. “Parser combinators” sounds like something you'd need
    a CS degree to understand.

    Here's the thing: I don't have a CS degree. Actually, I don't have any degree.
    But I've been using parser combinators for years because they're actually… not
    that hard? It's just that the name makes them sound way scarier than they are.

    I'd been using them for other stuff—parsing config files, DSLs, whatever.
    But somehow it never clicked that you could use them for CLI parsing until
    I saw Haskell's optparse-applicative. That was a real “wait, of course”
    moment. Like, why are we doing this any other way?

    Turns out it's stupidly simple. A parser is just a function. Combinators are
    just functions that take parsers and return new parsers. That's it.

    // This is a parser
    const port = option("--port", integer());
    
    // This is also a parser (made from smaller parsers)
    const server = object({
      port: port,
      host: option("--host", string())
    });
    
    // Still a parser (parsers all the way down)
    const config = or(server, client);
    

    No monads. No category theory. Just functions. Boring, beautiful functions.

    TypeScript does the heavy lifting

    Here's the thing that still feels like cheating: I don't write types for my CLI
    configs anymore. TypeScript just… figures it out.

    const cli = or(
      command("deploy", object({
        action: constant("deploy"),
        environment: argument(string()),
        replicas: option("--replicas", integer())
      })),
      command("rollback", object({
        action: constant("rollback"),
        version: argument(string()),
        force: option("--force")
      }))
    );
    
    // TypeScript infers this type automatically:
    type Cli = 
      | { 
          readonly action: "deploy"
          readonly environment: string
          readonly replicas: number
        }
      | { 
          readonly action: "rollback"
          readonly version: string
          readonly force: boolean
        }
    

    TypeScript knows that if action is "deploy", then environment exists but
    version doesn't. It knows replicas is a number. It knows force is
    a boolean. I didn't tell it any of this.

    This isn't just about nice autocomplete (though yeah, the autocomplete is great).
    It's about catching bugs before they happen. Forget to handle a new option
    somewhere? Code won't compile.

    What actually changed for me

    I've been dogfooding this for a few weeks. Some real talk:

    I delete code now. Not refactor. Delete. That validation logic that used to
    be 30% of my CLI code? Gone. It feels weird every time.

    Refactoring isn't scary. Want to know something that usually terrifies me?
    Changing how a CLI takes its arguments. Like going from --input file.txt to
    just file.txt as a positional argument. With traditional parsers,
    you're hunting down validation logic everywhere. With this?
    You change the parser definition, TypeScript immediately shows you every place
    that breaks, you fix them, done. What used to be an hour of “did I catch
    everything?” is now “fix the red squiggles and move on.”

    My CLIs got fancier. When adding complex option relationships doesn't mean
    writing complex validation, you just… add them. Mutually exclusive groups?
    Sure. Context-dependent options? Why not. The parser handles it.

    The reusability is real too:

    const networkOptions = object({
      host: option("--host", string()),
      port: option("--port", integer())
    });
    
    // Reuse everywhere, compose differently
    const devServer = merge(networkOptions, debugOptions);
    const prodServer = merge(networkOptions, authOptions);
    const testServer = merge(networkOptions, mockOptions);
    

    But honestly? The biggest change is trust. If it compiles, the CLI logic works.
    Not “probably works” or “works unless someone passes weird arguments.”
    It just works.

    Should you care?

    If you're writing a 10-line script that takes one argument, you don't need this.
    process.argv[2] and call it a day.

    But if you've ever:

    • Had validation logic get out of sync with your actual options
    • Discovered in production that certain option combinations explode
    • Spent an afternoon tracking down why --verbose breaks when used with
      --json
    • Written the same “option A requires option B” check for the fifth time

    Then yeah, maybe you're tired of this stuff too.

    Fair warning: Optique is young. I'm still figuring things out, the API might
    shift a bit. But the core idea—parse, don't validate—that's solid.
    And I haven't written validation code in months.

    Still feels weird. Good weird.

    Try it or don't

    If this resonates:

    I'm not saying Optique is the answer to all CLI problems. I'm just saying
    I was tired of writing the same validation code everywhere, so I built something
    that makes it unnecessary.

    Take it or leave it. But that validation code you're about to write?
    You probably don't need it.

  • System shared this topic on
  • I have this bad habit. When something annoys me enough times,
    I end up building a library for it. This time, it was CLI validation code.

    See, I spend a lot of time reading other people's code. Open source projects,
    work stuff, random GitHub repos I stumble upon at 2 AM. And I kept noticing this
    thing: every CLI tool has the same ugly validation code tucked away somewhere.
    You know the kind:

    if (!opts.server && opts.port) {
      throw new Error("--port requires --server flag");
    }
    
    if (opts.server && !opts.port) {
      opts.port = 3000; // default port
    }
    
    // wait, what if they pass --port without a value?
    // what if the port is out of range?
    // what if...
    

    It's not even that this code is hard to write. It's that it's everywhere.
    Every project. Every CLI tool. The same patterns, slightly different flavors.
    Options that depend on other options. Flags that can't be used together.
    Arguments that only make sense in certain modes.

    And here's what really got me: we solved this problem years ago for other types
    of data. Just… not for CLIs.

    The problem with validation

    There's this blog post that completely changed how I think about parsing.
    It's called Parse, don't validate by Alexis King. The gist? Don't parse data
    into a loose type and then check if it's valid. Parse it directly into a type
    that can only be valid.

    Think about it. When you get JSON from an API, you don't just parse it as any
    and then write a bunch of if-statements. You use something like Zod to parse
    it directly into the shape you want. Invalid data? The parser rejects it. Done.

    But with CLIs? We parse arguments into some bag of properties and then spend
    the next 100 lines checking if that bag makes sense. It's backwards.

    So yeah, I built Optique. Not because the world desperately needed another CLI
    parser (it didn't), but because I was tired of seeing—and writing—the same
    validation code everywhere.

    Three patterns I was sick of validating

    Dependent options

    This one's everywhere. You have an option that only makes sense when another
    option is enabled.

    The old way? Parse everything, then check:

    const opts = parseArgs(process.argv);
    if (!opts.server && opts.port) {
      throw new Error("--port requires --server");
    }
    if (opts.server && !opts.port) {
      opts.port = 3000;
    }
    // More validation probably lurking elsewhere...
    

    With Optique, you just describe what you want:

    const config = withDefault(
      object({
        server: flag("--server"),
        port: option("--port", integer()),
        workers: option("--workers", integer())
      }),
      { server: false }
    );
    

    Here's what TypeScript infers for config's type:

    type Config = 
      | { readonly server: false }
      | { readonly server: true; readonly port: number; readonly workers: number }
    

    The type system now understands that when server is false, port literally
    doesn't exist. Not undefined, not null—it's not there. Try to access it and
    TypeScript yells at you. No runtime validation needed.

    Mutually exclusive options

    Another classic. Pick one output format: JSON, YAML, or XML. But definitely not
    two.

    I used to write this mess:

    if ((opts.json ? 1 : 0) + (opts.yaml ? 1 : 0) + (opts.xml ? 1 : 0) > 1) {
      throw new Error('Choose only one output format');
    }
    

    (Don't judge me, you've written something similar.)

    Now?

    const format = or(
      map(option("--json"), () => "json" as const),
      map(option("--yaml"), () => "yaml" as const),
      map(option("--xml"), () => "xml" as const)
    );
    

    The or() combinator means exactly one succeeds. The result is just
    "json" | "yaml" | "xml". A single string. Not three booleans to juggle.

    Environment-specific requirements

    Production needs auth. Development needs debug flags. Docker needs different
    options than local. You know the drill.

    Instead of a validation maze, you just describe each environment:

    const envConfig = or(
      object({
        env: constant("prod"),
        auth: option("--auth", string()),      // Required in prod
        ssl: option("--ssl"),
        monitoring: option("--monitoring", url())
      }),
      object({
        env: constant("dev"),
        debug: optional(option("--debug")),    // Optional in dev
        verbose: option("--verbose")
      })
    );
    

    No auth in production? Parser fails immediately. Trying to access --auth in
    dev mode? TypeScript won't let you—the field doesn't exist on that type.

    “But parser combinators though…”

    I know, I know. “Parser combinators” sounds like something you'd need
    a CS degree to understand.

    Here's the thing: I don't have a CS degree. Actually, I don't have any degree.
    But I've been using parser combinators for years because they're actually… not
    that hard? It's just that the name makes them sound way scarier than they are.

    I'd been using them for other stuff—parsing config files, DSLs, whatever.
    But somehow it never clicked that you could use them for CLI parsing until
    I saw Haskell's optparse-applicative. That was a real “wait, of course”
    moment. Like, why are we doing this any other way?

    Turns out it's stupidly simple. A parser is just a function. Combinators are
    just functions that take parsers and return new parsers. That's it.

    // This is a parser
    const port = option("--port", integer());
    
    // This is also a parser (made from smaller parsers)
    const server = object({
      port: port,
      host: option("--host", string())
    });
    
    // Still a parser (parsers all the way down)
    const config = or(server, client);
    

    No monads. No category theory. Just functions. Boring, beautiful functions.

    TypeScript does the heavy lifting

    Here's the thing that still feels like cheating: I don't write types for my CLI
    configs anymore. TypeScript just… figures it out.

    const cli = or(
      command("deploy", object({
        action: constant("deploy"),
        environment: argument(string()),
        replicas: option("--replicas", integer())
      })),
      command("rollback", object({
        action: constant("rollback"),
        version: argument(string()),
        force: option("--force")
      }))
    );
    
    // TypeScript infers this type automatically:
    type Cli = 
      | { 
          readonly action: "deploy"
          readonly environment: string
          readonly replicas: number
        }
      | { 
          readonly action: "rollback"
          readonly version: string
          readonly force: boolean
        }
    

    TypeScript knows that if action is "deploy", then environment exists but
    version doesn't. It knows replicas is a number. It knows force is
    a boolean. I didn't tell it any of this.

    This isn't just about nice autocomplete (though yeah, the autocomplete is great).
    It's about catching bugs before they happen. Forget to handle a new option
    somewhere? Code won't compile.

    What actually changed for me

    I've been dogfooding this for a few weeks. Some real talk:

    I delete code now. Not refactor. Delete. That validation logic that used to
    be 30% of my CLI code? Gone. It feels weird every time.

    Refactoring isn't scary. Want to know something that usually terrifies me?
    Changing how a CLI takes its arguments. Like going from --input file.txt to
    just file.txt as a positional argument. With traditional parsers,
    you're hunting down validation logic everywhere. With this?
    You change the parser definition, TypeScript immediately shows you every place
    that breaks, you fix them, done. What used to be an hour of “did I catch
    everything?” is now “fix the red squiggles and move on.”

    My CLIs got fancier. When adding complex option relationships doesn't mean
    writing complex validation, you just… add them. Mutually exclusive groups?
    Sure. Context-dependent options? Why not. The parser handles it.

    The reusability is real too:

    const networkOptions = object({
      host: option("--host", string()),
      port: option("--port", integer())
    });
    
    // Reuse everywhere, compose differently
    const devServer = merge(networkOptions, debugOptions);
    const prodServer = merge(networkOptions, authOptions);
    const testServer = merge(networkOptions, mockOptions);
    

    But honestly? The biggest change is trust. If it compiles, the CLI logic works.
    Not “probably works” or “works unless someone passes weird arguments.”
    It just works.

    Should you care?

    If you're writing a 10-line script that takes one argument, you don't need this.
    process.argv[2] and call it a day.

    But if you've ever:

    • Had validation logic get out of sync with your actual options
    • Discovered in production that certain option combinations explode
    • Spent an afternoon tracking down why --verbose breaks when used with
      --json
    • Written the same “option A requires option B” check for the fifth time

    Then yeah, maybe you're tired of this stuff too.

    Fair warning: Optique is young. I'm still figuring things out, the API might
    shift a bit. But the core idea—parse, don't validate—that's solid.
    And I haven't written validation code in months.

    Still feels weird. Good weird.

    Try it or don't

    If this resonates:

    I'm not saying Optique is the answer to all CLI problems. I'm just saying
    I was tired of writing the same validation code everywhere, so I built something
    that makes it unnecessary.

    Take it or leave it. But that validation code you're about to write?
    You probably don't need it.

    @hongminhee this is cool! I've never used NodeJS CLI apps, but I run into similar issues to the ones you described when using Python


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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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    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!
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    We're excited to announce Optique 0.8.0! This release introduces powerful new features for building sophisticated CLI applications: the conditional() combinator for discriminated union patterns, the passThrough() parser for wrapper tools, and the new @optique/logtape package for seamless logging configuration. Optique is a type-safe combinatorial CLI parser for TypeScript, providing a functional approach to building command-line interfaces with composable parsers and full type inference. New conditional parsing with conditional() Ever needed to enable different sets of options based on a discriminator value? The new conditional() combinator makes this pattern first-class. It creates discriminated unions where certain options only become valid when a specific discriminator value is selected. import { conditional, object } from "@optique/core/constructs"; import { option } from "@optique/core/primitives"; import { choice, string } from "@optique/core/valueparser"; const parser = conditional( option("--reporter", choice(["console", "junit", "html"])), { console: object({}), junit: object({ outputFile: option("--output-file", string()) }), html: object({ outputFile: option("--output-file", string()) }), } ); // Result type: ["console", {}] | ["junit", { outputFile: string }] | ... Key features: Explicit discriminator option determines which branch is selected Tuple result [discriminator, branchValue] for clear type narrowing Optional default branch for when discriminator is not provided Clear error messages indicating which options are required for each discriminator value The conditional() parser provides a more structured alternative to or() for discriminated union patterns. Use it when you have an explicit discriminator option that determines which set of options is valid. See the conditional() documentation for more details and examples. Pass-through options with passThrough() Building wrapper CLI tools that need to forward unrecognized options to an underlying tool? The new passThrough() parser enables legitimate wrapper/proxy patterns by capturing unknown options without validation errors. import { object } from "@optique/core/constructs"; import { option, passThrough } from "@optique/core/primitives"; const parser = object({ debug: option("--debug"), extra: passThrough(), }); // mycli --debug --foo=bar --baz=qux // → { debug: true, extra: ["--foo=bar", "--baz=qux"] } Key features: Three capture formats: "equalsOnly" (default, safest), "nextToken" (captures --opt val pairs), and "greedy" (captures all remaining tokens) Lowest priority (−10) ensures explicit parsers always match first Respects -- options terminator in "equalsOnly" and "nextToken" modes Works seamlessly with object(), subcommands, and other combinators This feature is designed for building Docker-like CLIs, build tool wrappers, or any tool that proxies commands to another process. See the passThrough() documentation for usage patterns and best practices. LogTape logging integration The new @optique/logtape package provides seamless integration with LogTape, enabling you to configure logging through command-line arguments with various parsing strategies. # Deno deno add --jsr @optique/logtape @logtape/logtape # npm npm add @optique/logtape @logtape/logtape Quick start with the loggingOptions() preset: import { loggingOptions, createLoggingConfig } from "@optique/logtape"; import { object } from "@optique/core/constructs"; import { parse } from "@optique/core/parser"; import { configure } from "@logtape/logtape"; const parser = object({ logging: loggingOptions({ level: "verbosity" }), }); const args = ["-vv", "--log-output=-"]; const result = parse(parser, args); if (result.success) { const config = await createLoggingConfig(result.value.logging); await configure(config); } The package offers multiple approaches to control log verbosity: verbosity() parser: The classic -v/-vv/-vvv pattern where each flag increases verbosity (no flags → "warning", -v → "info", -vv → "debug", -vvv → "trace") debug() parser: Simple --debug/-d flag that toggles between normal and debug levels logLevel() value parser: Explicit --log-level=debug option for direct level selection logOutput() parser: Log output destination with - for console or file path for file output See the LogTape integration documentation for complete examples and configuration options. Bug fix: negative integers now accepted Fixed an issue where the integer() value parser rejected negative integers when using type: "number". The regex pattern has been updated from /^\d+$/ to /^-?\d+$/ to correctly handle values like -42. Note that type: "bigint" already accepted negative integers, so this change brings consistency between the two types. Installation # Deno deno add jsr:@optique/core # npm npm add @optique/core # pnpm pnpm add @optique/core # Yarn yarn add @optique/core # Bun bun add @optique/core For the LogTape integration: # Deno deno add --jsr @optique/logtape @logtape/logtape # npm npm add @optique/logtape @logtape/logtape # pnpm pnpm add @optique/logtape @logtape/logtape # Yarn yarn add @optique/logtape @logtape/logtape # Bun bun add @optique/logtape @logtape/logtape Looking forward Optique 0.8.0 continues our focus on making CLI development more expressive and type-safe. The conditional() combinator brings discriminated union patterns to the forefront, passThrough() enables new wrapper tool use cases, and the LogTape integration makes logging configuration a breeze. As always, all new features maintain full backward compatibility—your existing parsers continue to work unchanged. We're grateful to the community for feedback and suggestions. If you have ideas for future improvements or encounter any issues, please let us know through GitHub Issues. For more information about Optique and its features, visit the documentation or check out the full changelog.
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    Exciting news for #Fedify developers! We've just landed a major milestone for Fedify 2.0—the #CLI now runs natively on #Node.js and #Bun, not just #Deno (#456). If you install @fedify/cli@2.0.0-dev.1761 from npm, you'll get actual JavaScript that executes directly in your runtime, no more pre-compiled binaries from deno compile. This is part of our broader transition to Optique, a new cross-runtime CLI framework we've developed specifically for Fedify's needs (#374). This change means a more natural development experience regardless of your #JavaScript runtime preference. Node.js developers can now run the CLI tools directly through their familiar ecosystem, and the same goes for Bun users. While Fedify 2.0 isn't released yet, we're excited to share this progress with the community—feel free to try out the dev version and let us know how it works for you!