Registering Task

Every task is registered with tasks.register(name, spec?). The first argument is the task name; the optional second argument is a spec — a single keyed object describing the task. All forms below are variations of that one signature.

A spec is a plain object with a run field (the task body) plus any configuration fields (group, dependsOn, inputs, …) sitting directly alongside it:

import { tasks } from "nadle";

tasks.register("build", {
	run: async ({ context }) => {
		context.logger.log("Building…");
	},
	group: "CI",
	dependsOn: ["compile"]
});

Two shorthands cover the common cases: omit the spec entirely for an empty task, or pass a bare function when you only need a body.

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1. Empty Task

An empty task has no execution logic. It is typically used to define a logical grouping of other tasks or to act as a single entry point in the task graph.

This is useful when creating a high-level task that simply depends on other subtasks.

Example: To create a top-level build task that runs multiple subtasks for building different parts of your project, you can define it like this:

import { tasks } from "nadle";

tasks.register("build", {
	dependsOn: ["buildFrontend", "buildBackend"]
});

When a task only needs a name and nothing else, omit the spec entirely:

tasks.register("checkpoint");

2. Action Task

An action task includes inline logic that will be executed when the task runs. The task function can be synchronous or asynchronous.

Use this when the task logic is custom, simple, and doesn't need to be reused across multiple tasks.

When the body is all you need, pass the function directly as the second argument:

// Synchronous
import fs from "node:fs";

import { tasks } from "nadle";

tasks.register("clean", () => {
	if (fs.existsSync("dist")) {
		fs.rmSync("dist", { recursive: true });
		console.log("Cleaned dist/ directory.");
	} else {
		console.log("dist/ directory does not exist.");
	}
});

// Asynchronous
import { writeFile } from "node:fs/promises";

import { tasks } from "nadle";
import fetch from "node-fetch";

tasks.register("fetchData", async () => {
	const res = await fetch("https://jsonplaceholder.typicode.com/posts");
	const data = await res.json();
	await writeFile("data.json", JSON.stringify(data, null, 2));
	console.log("Fetched and saved data to data.json.");
});

To attach configuration to an inline task, use the full spec and put the body under run:

tasks.register("clean", {
	run: () => {
		fs.rmSync("dist", { recursive: true });
	},
	group: "Maintenance",
	description: "Remove build artifacts"
});

These kinds of tasks are ideal for setup steps, scripts, or one-off automation logic defined directly in the configuration file.

3. Reusable Task

Reusable tasks are based on predefined implementations—either built-in or custom—that accept options to customize behavior. This makes it easy to reuse logic across multiple tasks without duplicating code.

Pass the task implementation as run and its options as options:

import { tasks, CopyTask } from "nadle";

tasks.register("copy", {
	run: CopyTask,
	options: {
		from: "assets",
		into: "dist"
	}
});

options may be a plain value (as above) or a resolver — a function returning the options — when the values depend on the environment or other dynamic conditions:

tasks.register("copy", {
	run: CopyTask,
	options: () => ({ from: "assets", into: process.env.OUT_DIR ?? "dist" })
});

This pattern is especially useful for standardized operations like copying files, executing shell commands, or compiling code where the task logic stays the same, but the inputs or targets may vary.

Deferring the whole spec with lazy

Wrap a spec in lazy when the entire spec — not just options — should be computed on demand. The thunk runs at most once, the first time Nadle reads the task's configuration:

import { tasks, lazy } from "nadle";

tasks.register(
	"publish",
	lazy(() => ({
		run: async ({ context }) => {
			/* … */
		},
		workingDir: process.env.PACKAGE_DIR ?? "./packages/core"
	}))
);

Authoring specs programmatically with defineSpec

defineSpec is an identity helper that gives you full type inference when building a spec outside the register call — handy for sharing or generating specs programmatically. The result is passed straight to register:

import { tasks, defineSpec, ExecTask } from "nadle";

const lintSpec = defineSpec({
	run: ExecTask,
	options: { command: "eslint", args: ["."] },
	group: "Quality"
});

tasks.register("lint", lintSpec);