interfacy 0.6.3

Framework for building CLIs from Python callables

Interfacy

Interfacy is a CLI framework that turns Python functions, classes, and class instances into command-line interfaces. It derives the CLI from signatures, type annotations, and docstrings instead of making you define it twice.

Features

• Generate CLIs from functions, classes, class methods, and class instances.
• Nested subcommands and manual command groups with aliases.
• Type-driven parsing from annotations, with support for custom parsers.
• Model expansion for dataclasses, Pydantic models, and plain classes.
• --help text generated from docstrings.
• Highly customizable help output with multiple layouts, color themes, and configurable ordering.
• Stdin piping support with configurable routing to parameters.
• Optional tab completion via argcomplete.

Installation

From PyPI

pip install interfacy

uv add interfacy

From source

pip install git+https://github.com/zigai/interfacy.git

uv add "git+https://github.com/zigai/interfacy.git"

Quick Start

from interfacy import Interfacy

def greet(name: str, times: int = 1) -> None:
    """Print a greeting."""
    print(" ".join([f"Hello, {name}!" for _ in range(times)]))

if __name__ == "__main__":
    Interfacy().run(greet)

$ python app.py Ada
Hello, Ada!

$ python app.py Ada --times 2
Hello, Ada! Hello, Ada!

By default, required non-boolean parameters become positional arguments and optional parameters become flags.

Boolean flags follow the callable's name. Positive names keep paired toggle behavior, while negative-looking bool = False names become one-way flags:

def sync(disable_cache: bool = False, verbose: bool = False) -> None:
    ...

$ python app.py --disable-cache --verbose

--disable-cache is accepted without generating an inverse --cache alias.

Agent Skill

The official AI agent skill can be installed from this repo.

npx skills add https://github.com/zigai/interfacy/tree/master/interfacy/.agents/skills/interfacy

or

uvx library-skills

Class-Based Commands

Classes become command namespaces. __init__ parameters live at the command level and public methods become subcommands.

from interfacy import Interfacy

class Calculator:
    def __init__(self, precision: int = 2) -> None:
        self.precision = precision

    def add(self, a: float, b: float) -> float:
        return round(a + b, self.precision)

    def mul(self, a: float, b: float) -> float:
        return round(a * b, self.precision)

if __name__ == "__main__":
    Interfacy(print_result=True).run(Calculator)

$ python app.py --precision 3 add 1.2345 2.3445
3.579

Structured Parameters

Dataclasses, Pydantic models, and plain classes with typed __init__ parameters can be expanded into nested flags and reconstructed before execution.

from dataclasses import dataclass
from interfacy import Interfacy

@dataclass
class Address:
    city: str
    postal_code: int

@dataclass
class User:
    name: str
    age: int
    address: Address | None = None

def greet(user: User) -> str:
    return f"Hello {user.name}, age {user.age}"

if __name__ == "__main__":
    Interfacy(print_result=True).run(greet)

$ python app.py --user.name Ada --user.age 32
Hello Ada, age 32

Manual Groups

Use CommandGroup when your command tree is not naturally rooted in one callable:

from interfacy import CommandGroup, Interfacy

def clone(url: str) -> str:
    return f"clone:{url}"

class Releases:
    def cut(self, version: str) -> str:
        return f"cut:{version}"

ops = CommandGroup("ops", description="Operational commands")
ops.add_command(clone)
ops.add_command(Releases)

if __name__ == "__main__":
    Interfacy(print_result=True).run(ops)

Interfacy CLI Entrypoint

Interfacy also ships a CLI that can run an existing function, class, or class instance directly from a module or Python file:

$ interfacy app.py:greet Ada
$ interfacy app.py:greet --help
$ interfacy package.cli:Calculator add 1 2

The entrypoint supports configuration via TOML, loaded from ~/.config/interfacy/config.toml or INTERFACY_CONFIG.

usage: interfacy [--help] [--version] [--config-paths] [TARGET] ...

Interfacy is a framework for building CLIs from Python callables.

positional arguments:
  [TARGET]        Python file or module with a function/class/instance symbol
                  (e.g. main.py:main, pkg.cli:App, pkg.cli:service).
  ...             Arguments passed through to the target command.

options:
  --help                        Show this help message and exit
  --version                     show version and exit.
  --config-paths                print config file search paths and exit.

Use 'interfacy TARGET --help' to display the help text for the target.

License

MIT License