sprout

Sprout is a Jinja2-based project generator with a Python manifest.

Instead of configuring prompts in YAML, you write sprout.py:

from sprout import Question

questions = [
    Question(key="project_name", prompt="Project name"),
]

That single manifest drives interactive prompts, CLI flags, validation and conditional questions.

Template files go in template/. .jinja files are rendered, everything else is copied.

Works with local templates, Git repos, or owner/repo GitHub shorthand.

Every question becomes a CLI flag so you can script it too:

sprout new <template-path> <project-path>
sprout new <template-path> <project-path> --project-name demo

Install

uv tool install sprout-template

Usage

sprout init [directory]
sprout add <template-source> [--name <trusted-name>]
sprout list
sprout new <template> <project-path> [--force] [--<question-flag> <value> ...]

new accepts a local template path, Git URL, owner/repo GitHub shorthand, or a trusted name added with sprout add. Pass values for question flags to skip those prompts:

sprout new <template-path> <project-path> --project-name demo

Use sprout new <template> --help to show template-specific flags.

Initialize a template

Create a minimal sprout.py and template/README.md.jinja scaffold in the current directory:

sprout init

Pass a directory to initialize it elsewhere. Existing scaffold files are never overwritten.

Trusted templates

Store a reusable name for any supported template source:

sprout add zigai/python-project-template --name python
sprout new python ./my-project
sprout list

Template structure

The source root must contain sprout.py.

The only required name is questions.

from sprout import Question

questions = [
    Question(key="project_name", prompt="Project name"),
]

Optional names are template_dir, style, extensions, title, cli_boolean_style, should_skip_file(...), and apply(context).

Question model

Each Question describes one answer:

from sprout import Question

Question(
    key="project_name",
    prompt="Project name",
    help="Used for package metadata and generated paths",
    default="demo",
)

key is the answer dictionary key. It also becomes the CLI flag name.

project_name -> --project-name

Choices

Use choices when the answer should come from a closed list:

from sprout import Question

questions = [
    Question(
        key="package_manager",
        prompt="Package manager",
        choices=[("uv", "uv"), ("pip", "pip")],
        default="uv",
    ),
]

Multiselect

from sprout import Question

questions = [
    Question(
        key="workflow",
        prompt="Workflows",
        choices=[("tests", "Tests"), ("lint", "Lint")],
        multiselect=True,
    ),
]

From the CLI:

sprout new <template-path> <project-path> --workflow tests --workflow lint

Booleans

Use the built-in yes/no helper:

from sprout import Question

questions = [
    Question.yes_no(
        key="git_init",
        prompt="Initialize Git?",
        default=True,
    ),
]

By default, yes/no questions are exposed as Boolean CLI flags:

sprout new <template-path> <project-path> --git-init
sprout new <template-path> <project-path> --no-git-init

If a template should use explicit yes/no values instead, opt into that style in sprout.py:

cli_boolean_style = "yes-no"

Then the CLI accepts values for yes/no questions:

sprout new <template-path> <project-path> --git-init yes
sprout new <template-path> <project-path> --git-init no

Conditional flow

when can be a boolean or a callable that receives the answers collected so far:

from sprout import Question

questions = [
    Question.yes_no(
        key="create_github_repo",
        prompt="Create GitHub repository?",
        default=False,
    ),
    Question(
        key="github_repo_visibility",
        prompt="GitHub repository visibility",
        choices=[("private", "Private"), ("public", "Public")],
        default="private",
        when=lambda answers: bool(answers.get("create_github_repo")),
    ),
]

Defaults, parsers, and validators

Defaults can be static values or callables. Use default="" for a text prompt that should accept a blank answer.

from sprout import Question

questions = [
    Question(
        key="package_name",
        prompt="Package name",
        default=lambda answers: str(answers["project_name"]).replace("-", "_"),
    ),
]

Validators return (valid, message):

from sprout import Question, validate_repository_url

questions = [
    Question(
        key="repository_url",
        prompt="Repository URL",
        validators=[validate_repository_url],
    ),
]

Sprout includes validators for repository URLs, GitHub repository URLs, repository names, npm package names, and semantic versions.

Destination-aware questions

When question definitions need runtime context, make questions callable:

from pathlib import Path
from jinja2 import Environment
from sprout import Question


def questions(env: Environment, destination: Path) -> list[Question]:
    return [
        Question(
            key="project_name",
            prompt="Project name",
            default=destination.name,
        ),
    ]

The callable must accept exactly two positional parameters: env and destination.

Rendering

Default rendering uses template_dir, or template when no directory is declared.

template_dir = "template"

Skipping files

should_skip_file receives a path relative to template_dir and the final answers:

from sprout import NO_LICENSE


def should_skip_file(relative_path: str, answers: dict[str, object]) -> bool:
    return relative_path == "LICENSE.jinja" and answers.get("license") == NO_LICENSE

Jinja environment

Set Jinja2 extension classes with extensions:

from sprout import CurrentYearExtension, GitDefaultsExtension

extensions = [GitDefaultsExtension, CurrentYearExtension]

When extensions is omitted, the default environment includes Git defaults:

• git_user_name
• git_user_email
• github_username

Include GitDefaultsExtension explicitly when you provide a custom extension list and still want those globals.

CurrentYearExtension exposes:

• current_year

Prompt title and style

title = "Generate a Python package"

from sprout import ManifestContext


def title(context: ManifestContext) -> str | None:
    return f"Generate project in {context.destination}"

The title is evaluated before answers are collected. For prompt appearance, assign style to a sprout.Style instance.

Custom generation

Most templates should use the default renderer, but you can define apply(context) when generation needs custom file creation, post-processing, or post-generation actions.

from sprout import ManifestContext, render_templates


def apply(context: ManifestContext):
    return render_templates(
        context.env,
        context.template_dir,
        context.destination,
        context.answers,
        render_paths=True,
    )

apply must accept exactly one context parameter. It may return None, one path, or a sequence of paths for the generated-files summary.

Programmatic APIs raise SproutError subclasses for expected operational failures. Catch the specific error when recovery differs by failure type, or catch SproutError at an application boundary. The sprout CLI translates these errors into concise process-exit messages.

Examples

• python-project-template.

License

MIT License