questionary

Python library to build pretty command line user prompts ✨

You need input from a user, e.g. how an output file should be named or if he really wants to execute that dangerous operation? This library will help you make the input prompts easy to read and answer for the user.

Quickstart

To install questionary, simply use pipenv (or pip, of course):

$ pipenv install questionary
✨🎂✨

Satisfaction guaranteed. Let's create a first question:

import questionary

questionary.select(
    "What do you want to do?",
    choices=[
        'Order a pizza',
        'Make a reservation',
        'Ask for opening hours'
    ]).ask()  # returns value of selection

This will create the following list, allowing the user to choose an option:

Documentation

1. Different question types

   The available question types are text, password, confirm, select, rawselect and checkbox.

2. Dict style question formulation

   Alterative style to create questions using a configuration dictionary.

3. Styling your prompts

   Customize how your questions look.

1. Different question types

text

A free text input for the user.

questionary.text("What's your first name").ask()

password

A free text input for the user where the input is not shown but replaced with ***.

questionary.password("What's your secret?").ask()

confirm

A yes or no question. The user can either confirm or deny.

questionary.confirm("Are you amazed?").ask()

select

A list of items to select a choice from. The user can pick one option and confirm it.

questionary.select(
    "What do you want to do?",
    choices=[
        "Order a pizza",
        "Make a reservation",
        "Ask for opening hours"
    ]).ask()

rawselect

A list of items to select a choice from. The user can pick one option using shortcuts and confirm it.

questionary.rawselect(
    "What do you want to do?",
    choices=[
        "Order a pizza",
        "Make a reservation",
        "Ask for opening hours"
    ]).ask()

checkbox

A list of items to select multiple choices from. The user can pick none, one or multiple options and confirm the selection.

questionary.checkbox(
    'Select toppings',
    choices=[
        "foo",
        "bar",
        "bazz"
    ]).ask()

2. Dict style question formulation

Instead of creating questions using the python functions, you can also create them using a configuration dictionary.

questions = [
    {
        'type': 'text',
        'name': 'phone',
        'message': "What's your phone number",
    },
    {
        'type': 'confirm',
        'message': 'Do you want to continue?',
        'name': 'continue',
        'default': True,
    }
]

answers = prompt(questions)

The returned answers will be a dict containing the responses, e.g. {"phone": "0123123", "continue": False, ""}. The questions will be prompted one after another and prompt will return once all of them are answered.

3. Styling your prompts

You can customize all the colors used for the prompts. Every part of the prompt has an identifier, which you can use to style it. Let's create our own custom style:

from prompt_toolkit.styles import Style

custom_style_fancy = Style([
    ('qmark', 'fg:#673ab7 bold'),     # token in front of the question
    ('question', 'bold'),             # question text
    ('answer', 'fg:#f44336 bold'),    # submitted answer text behind the question
    ('pointer', 'fg:#673ab7 bold'),   # pointer used in select and checkbox prompts
    ('selected', 'fg:#cc5454'),       # style for a selected item of a checkbox
    ('separator', 'fg:#cc5454'),      # separator in lists
    ('instruction', '')               # user instructions for select, rawselect, checkbox
])

To use our custom style, we need to pass it to the question type:

questionary.text("What's your phone number", style=custom_style_fancy).ask()

How to Contribute

1. Check for open issues or open a fresh issue to start a discussion around a feature idea or a bug. There is a Contributor Friendly tag for issues that should be ideal for people who are not very familiar with the codebase yet.
2. Fork the repository on GitHub to start making your changes to the master branch (or branch off of it).
3. Write a test which shows that the bug was fixed or that the feature works as expected.
4. Send a pull request and bug the maintainer until it gets merged and published. 🙂

Contributors

questionary is written and maintained by Tom Bocklisch. It is based on the great work of Oyetoke Toby.

Changelog

1.0.0

Initial public release of the library

Release Date: 14.12.18

• Added python interface
• Added dict style question creation
• Improved the documentation
• More tests and automatic travis test execution

License

Licensed under the MIT License. Copyright 2018 Tom Bocklisch. Copy of the license.