quickparser 0.1.2

Create lightweight CLI arg parsers from pydantic models

Quickparser

Create lightweight CLI arg parsers from pydantic models.

This provides a clean, declarative way to create a command-line interface by allowing you to define the interface using Pydantic models.

For example,

from pydantic import BaseModel, Field
from quickparser import parser

@parser
class SimpleModel(BaseModel):
    """
    Example CLI for demonstration.
    """
    name: str
    age: int = Field(default=30)
    hobby: str | None
    employed: bool

args = SimpleModel.parse()

Is the equivalent of the following argparse code:

import argparse

parser = argparse.ArgumentParser(description="Example CLI for demonstration.")
parser.add_argument("--name", type=str, required=True)
parser.add_argument("--age", type=int, default=30)
parser.add_argument("--hobby", type=str, default=None)
parser.add_argument("--employed", action="store_true")
args = parser.parse_args()

Installation

pip install quickparser

Usage

We can take the example above and put it into an example.py script to demonstrate the basic usage:

# example.py
from pydantic import BaseModel, Field
from quickparser import parser


@parser
class SimpleModel(BaseModel):
    """
    Example CLI for demonstration.
    """
    name: str
    age: int = Field(default=30)
    hobby: str | None
    employed: bool

if __name__ == "__main__":
    args = SimpleModel.parse()
    print(args)

This script can be run from the command line, and it will parse the arguments provided to it. For example:

python example.py --name John --age 25 --hobby "reading" --employed

This will output:

SimpleModel(name='John', age=25, hobby='reading', employed=True)

Built on top of argparse, the parser provided automatically includes a help message, type casting based on type hints, default values, and required vs optional arguments. Help can be accessed by running the script with the --help flag:

python example.py --help