Skip to main content

Interactively fill dataclass instances via the command line.

Project description

dc-input

PyPI License

Interactively fill dataclass instances via the command line. Features include nested schemas, repeatable containers, undo support, defaults, optional fields, and custom parsers. Useful for quick data entry, prototyping, or structured configuration; integrates easily with your own CLI tools.


Why dc-input?

If you’ve ever written a script that prompts for input, validates values, and parses the result, you’ve probably noticed how boilerplate-y and bug-prone this can be.

dc-input replaces all that with a single function call.

Installation

pip install dc-input

Quick Start

from dataclasses import dataclass
from dc_input import get_input

@dataclass
class User:
    name: str
    age: int | None

user = get_input(User)
print(user)

Usage

Define your dataclasses as usual, then call get_input() to interactively collect values. dc-input walks your dataclass schema and interactively prompts for values, handling nesting, repetition, defaults, and validation automatically. At any prompt, type .. to undo the previous input: this even works across nested schemas.

Complete Example

Below is a full, self-contained script that:

  • interactively collects data for a new music student
  • validates and parses input
  • appends the result to a JSON registry on disk

This is representative of how dc-input can be used in real projects.

Script

from __future__ import annotations

from dataclasses import dataclass, field, asdict
import datetime
import json
import os
from pathlib import Path
from pprint import pprint
import tempfile
from typing import Annotated, Any

from dc_input import get_input

STUDENTS_PATH = Path("students.json")


# ------------------------------------------------------------
# Schema
# ------------------------------------------------------------
@dataclass
class MusicStudent:
    id: int

    name: Name
    date_of_birth: Annotated[datetime.date, "DD/MM/YYYY"]
    address: Annotated[Address, "Must be a German address"]

    primary_instrument: Instrument
    secondary_instruments: Annotated[
        list[Instrument], "Other instruments the student may have experience with"
    ]

    comments: str | None


@dataclass
class Name:
    first: str
    middle: list[str]
    last: str

    full: str = field(init=False)

    def __post_init__(self):
        middle = f" {' '.join(name for name in self.middle)} " if self.middle else " "
        self.full = f"{self.first}{middle}{self.last}"


@dataclass
class Address:
    street: str
    street_number: int
    apartment: str | None
    zip_code: Annotated[int, "XXXXX"]
    city: str = "Berlin"


@dataclass
class Instrument:
    name: str
    start_date: Annotated[datetime.date | None, "DD/MM/YYYY"]
    comment: str | None


# ------------------------------------------------------------
# Helpers
# ------------------------------------------------------------
def parse_date_dmy(s: str) -> datetime.date:
    s = s.strip().replace(".", "/").replace("-", "/")
    try:
        day, month, year = map(int, s.split("/"))
    except Exception:
        raise ValueError("wrong format, must be DD/MM/YYYY")
    else:
        return datetime.date(year, month, day)


def json_default(obj: Any) -> Any:
    if isinstance(obj, datetime.date):
        return obj.isoformat()
    raise TypeError(f"Type not serializable: {type(obj)}")


# ------------------------------------------------------------
# Main function
# ------------------------------------------------------------
if __name__ == "__main__":
    # Get input
    parsers = {
        datetime.date: parse_date_dmy,
    }
    res = get_input(MusicStudent, parsers=parsers)
    res_dict = asdict(res)  # dataclasses → JSON-serializable dict

    # Deserialize student registry
    data: dict[str, list] = {"students": []}
    if STUDENTS_PATH.exists():
        with open(STUDENTS_PATH, "r", encoding="utf-8") as f:
            data = json.load(f)

    # Add session result to deserialized registry
    data.setdefault("students", [])
    data["students"].append(res_dict)

    # Serialize registry back to JSON and overwrite old file
    with tempfile.NamedTemporaryFile(
            "w", encoding="utf-8", delete=False, dir=STUDENTS_PATH.parent
    ) as tmp:
        json.dump(data, tmp, indent=2, default=json_default)
        tmp_name = tmp.name

    os.replace(tmp_name, STUDENTS_PATH)

    # Done
    print(f"\nNew student '{res.name.full}' added to {STUDENTS_PATH.name}:")
    pprint(res)

Interactive Session Example

asciicast

Final Result

New student 'Jakob Ludwig Felix Mendelssohn Bartholdy' added to students.json:
MusicStudent(id=14321,
             name=Name(first='Jakob',
                       middle=['Ludwig', 'Felix'],
                       last='Mendelssohn Bartholdy',
                       full='Jakob Ludwig Felix Mendelssohn Bartholdy'),
             date_of_birth=datetime.date(1809, 2, 3),
             address=Address(street='Jägerstraße',
                             street_number=51,
                             apartment=None,
                             zip_code=10117,
                             city='Berlin'),
             primary_instrument=Instrument(name='piano',
                                           start_date=datetime.date(1816, 4, 30),
                                           comment=None),
             secondary_instruments=[Instrument(name='violin',
                                               start_date=None,
                                               comment=None),
                                    Instrument(name='ukulele',
                                               start_date=None,
                                               comment='student proclaimed '
                                                       '"uke is life", find out '
                                                       'what that means')],
             comments='seems v. talented')

Roadmap

  • Extensive testing (help welcome, see below!)
  • Adapter for attrs
  • Adapters for pydantic and sqlalchemy (if feasible)
  • Translations
  • User-customizable UX

Contributions

Testing

Help with testing is very welcome.

For anyone so inclined:

  • create the craziest schema you can
  • log the result
    logging.basicConfig(level="DEBUG")
    logger = logging.getLogger("dc_input")

Suggestions

Over here: https://github.com/jdvanwijk/dc-input/discussions

Pull Requests

This library is not open for PRs yet.

Donations

I do like coffee: https://buymeacoffee.com/janebelvanwijk

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

dc_input-0.2.4.tar.gz (21.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

dc_input-0.2.4-py3-none-any.whl (26.4 kB view details)

Uploaded Python 3

File details

Details for the file dc_input-0.2.4.tar.gz.

File metadata

  • Download URL: dc_input-0.2.4.tar.gz
  • Upload date:
  • Size: 21.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.5

File hashes

Hashes for dc_input-0.2.4.tar.gz
Algorithm Hash digest
SHA256 7299494e9041b49ba8a4190aa6804010fad927a3c185f53dd75d5c80f8ac7602
MD5 5cde2b2ed4174aa930acae434ec5bc91
BLAKE2b-256 b38d23430d475f5ae2a4a21a4219c6a22a0f7e566e441f5431d5503b0943f82f

See more details on using hashes here.

File details

Details for the file dc_input-0.2.4-py3-none-any.whl.

File metadata

  • Download URL: dc_input-0.2.4-py3-none-any.whl
  • Upload date:
  • Size: 26.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.5

File hashes

Hashes for dc_input-0.2.4-py3-none-any.whl
Algorithm Hash digest
SHA256 1683e36f0a59781ca86237d86469f91bf2a4282aa3d366841e71cbbd65186740
MD5 4203b0eb93250f452330f6e579ede448
BLAKE2b-256 37a5462cc2a7ee7894ef8a0b505fef3b9b35507d75ea967276a5351209626b31

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page