Prompting - the fancy way
Project description
ItsPrompt
Do you ever feel the need to ask a user of your code for an input?
Using input()
is easy, but is it great?
Do you want to give the user a selection list, a yes-or-no question, or maybe a multiline input field?
And do you think all of this should be done easily, without caring to much how it all works?
Then you are right here! ItsPrompt gives you the ability to ask the user for input, the fancy way.
ItsPrompt tries to be an easy-to-use module for managing prompts for the user. You task is to create a great program, not how to ask the user for input. That is why ItsPrompt is there to take care of this problem, so you can focus on the important things!
TOC
A small, thankful note
This project is not the first to accomplish the above mentioned tasks. There is another package, PyInquirer
, which
inspired me to build ItsPrompt.
On my way to create a small program I came to a point were I needed a simple GUI, and I tried PyInquirer
.
Unfortunately, at the current time it is not actively maintained and a bit outdated. I thought of updating it, but then
I thought "Isn't it easier to just create my own version?" - And so I did!
ItsPrompt is not a copy or a fork of PyInquirer
. I built this module from the ground up, without ever looking deep
into the source code of PyInquirer
.
On my way to build this package, I learned a lot about prompt-toolkit
, and all of this just because of PyInquirer
!
Thanks!
Features
- many prompt types (more details below):
- select
- raw_select
- expand
- checkbox
- confirm
- input
- table
- big feature set
- simple, pythonic syntax
- a helpful toolbar with error messages
- customizable style with
prompt-toolkit
Installation
This package is hosted on pypi, so the installation is as simple as it can get:
python3 -m pip install ItsPrompt
This will install ItsPrompt
without pandas. If you want to use TablePrompt
(see table) with
pandas.DataFrame
, you can install pandas support either by:
- installing pandas separately
- install
ItsPrompt
viapip install ItsPrompt[df]
Usage
Import the Prompt
class:
from ItsPrompt.prompt import Prompt
Now you can ask the user any type of prompt by calling the specific function from the Prompt
class, e.g.:
result = Prompt.input('What is your name?')
print(result)
You see how easy it is?
Prompt types
As mentioned above, ItsPrompt has multiple prompt types. All of them can be accessed via the Prompt
class.
select
Prompt.select(
question='question',
options=('option1', ('option2', 'opt2')),
default='option1',
style=my_style,
)
additional information on the function arguments can be found in the docstring
raw_select
Prompt.raw_select(
question='question',
options=('option1', ('option2', 'opt2')),
default='opt2',
allow_keyboard=True,
style=my_style,
)
additional information on the function arguments can be found in the docstring
expand
Prompt.expand(
question='question',
options=('option1', ('2', 'option2', 'opt2')),
default='opt2',
allow_keyboard=True,
style=my_style,
)
additional information on the function arguments can be found in the docstring
checkbox
Prompt.checkbox(
question='question',
options=('option1', ('option2', 'opt2')),
pointer_at=1,
default_checked='option1',
min_selections=1,
style=my_style,
)
additional information on the function arguments can be found in the docstring
confirm
Prompt.confirm(
question='question',
default=False,
style=my_style,
)
additional information on the function arguments can be found in the docstring
input
Prompt.input(
question='question',
default='something',
multiline=False,
show_symbol='*', # not compatible with complete, completer
validate=validation_function,
complete=['completion1', 'completion2'], # either use complete
completer=my_completer, # or completer
completion_show_multicolumn=True,
style=my_style,
)
additional information on the function arguments can be found in the docstring
table
Prompt.table(
question="something",
data={"0": ["something"]},
style=my_style,
)
# or, after having installed pandas
Prompt.table(
question='something',
data=DataFrame(['something']),
style=my_style,
)
additional information on the function arguments can be found in the docstring
Additional Features and Tips
Options
The options
is always a tuple
containing str
and tuple
objects.
If an option is given as a str
, this will be used as the options display name and the id, which will be returned when
selecting this option.
In case of expand
, the first character of the str
will be used as its key.
If an option is given as a tuple
, the first value will be the options name, the second value the options id to return.
In case of expand
, the first value will be the key, the second value the name and the third value the id.
Data
The table
prompt takes a mandatory data
argument, which needs to be a pandas.DataFrame
.
This DataFrame
is used as the content of the table. The user may change the fields of the table. The output of
the table
prompt is a pandas.DataFrame
with the user given values.
Currently, the output will convert all input values to a str
, so int
, bool
, ... will be converted to strings. This
is a current limitation of the way the table is displayed, but may later be updated.
Another limitation of the table
prompt is the use of styling in the DataFrame
fields. All styling tags will be
displayed as-is, so a <u>...</u>
will not be underlined, but rather displayed as its shown.
Styling
ItsPrompt uses prompt-toolkit
for its prompts. This module not only provides an easy way to interact with the
command line, but also a full set of styling features.
You can learn more about the available styling features in the documentation
of prompt-toolkit
: Styling.
ItsPrompt makes it a bit easier for you to style each component of a prompt. For every component, we give a separate
attribute in the PromptStyle
class, which you can style with valid prompt-toolkit
styling:
# examples for the different styling class components
Prompt.raw_select(
question='question',
options=(
'option',
'selected_option',
)
)
Prompt.input(
question='question',
default='grayout',
validate=lambda x: 'error',
)
ID | styling tag | default style |
---|---|---|
1 | question_mark |
fg:ansigreen |
2 | question |
* |
3 | option |
* |
4 | selected_option |
fg:ansicyan |
5 | tooltip |
fg:ansibrightblue bg:ansiwhite bold |
6 | text |
* |
7 | grayout |
fg:ansibrightblack |
8 | error |
fg:ansiwhite bg:ansired bold |
*These values are not changed from the default prompt-toolkit
values.
To create your own style, there are two ways:
Changing the default style
To change the default style, you need to import the default_style
and change its values:
from ItsPrompt.data.style import default_style
default_style.error = 'fg:ansired bg:ansiwhite'
This will automatically change the style of all prompts, which do not have an own style defined.
Creating your own style
To define your own style for a specific prompt, import PromptStyle
and create an object. Then assign it to the style
argument of a prompt.
from ItsPrompt.data.style import PromptStyle
my_style = PromptStyle(
question_mark='fg:ansiblue',
error='fg:ansired bg:ansiwhite',
)
All styles which are not given, will not be the same as the default style. Instead they will use the styling given
by prompt-toolkit
. If you want to change our default styles, then copy the default_style
and change your values,
instead of directly creating your own style:
from ItsPrompt.data.style import create_from_default
my_style = create_from_default()
my_style.error = 'fg:ansired bg:ansiwhite'
Warning! Not copying the default style and changing it instead will result in all prompts using your changes, as a variable is by default not a copy, but a reference to the same object!
Prompt Validation
The input
allows you to validate the input before submitting it. For every character the user types, the validation
will be run and a friendly error will be shown in the toolbar.
To use the validation feature, create a function which takes a str
as an argument and returns either a str
or None
.
def input_not_empty(input: str) -> str | None:
if len(input) == 0:
return 'Address can not be empty!'
Prompt.input(
...
validate = input_not_empty,
...
)
The str
argument will be the current user input, which can then be checked, but not changed!
If you want to show that the validation succeeded, return None
(or nothing). This will not trigger any errors.
If you want to show an error, return a str
with the errors text. Your text will be shown in the toolbar. As long as
the validation returns a str
, the user may not submit the input.
Prompt Completion
The input
prompt type supports auto completion as well.
If you use a completer, you are unable to use
show_symbol
!
To give auto completion options, there are three ways:
Creating a simple list of possible completions
Input
takes a list[str]
to use as simple word completions. Each str
in the list is a possible value to complete.
prompt.input(
...
completions = ['Mainstreet 4', 'Fifth way'],
...
)
Creating a nested dictionary of possible completions
You can use a dictionary for nested completions. Each "layer" will be a completion, after the first was accepted. For example:
completions = {
'1': {
'1.1': None,
'1.2': {
'1.2.1', '1.2.2'
}
},
'2': {
'2.1': {'2.1.1'}
}
}
prompt.input(
...
completions = completions,
...
)
The key of each entry is the completion that will be shown. The key is either None if there are no further completions or a new dict, where the key is the completion and the value is the next "layer", and so on...
For more information, the type signature of
CompletionDict
is:
dict[str, "CompletionDict | None"]
Using a given Completer by prompt-toolkit
or creating your own
In the background your completions will be mapped to a Completer
, provided by prompt-toolkit
.
If you need more customization, you can use a Completer
given by prompt-toolkit
or create your own completer. For
more information on this process, read
here: Completions in prompt-toolkit.
There are a number of completers available, for example:
PathCompleter
- automatically complete file system paths
ExecutableCompleter
- automatically complete executables in file system
WordCompleter
- As simple as it can get. Just completes the letters of the word, that are actually present (the
FuzzyCompleter
whichcompletions
uses in background completes based on a probability, and may show matches which are not exact).
- As simple as it can get. Just completes the letters of the word, that are actually present (the
- ...
To add your own completer to an input field, you can use the completer
argument:
prompt.input(
...
completer = my_completer,
...
)
completions
andcompleter
are mutually exclusive! You may not use both!
Further Information
If you need some easy examples, refer to example.py!
If you want to contribute, check out the projects repository: ItsPrompt!
If you got any other questions, or want to give an idea on how to improve ItsPrompt:
- visit our discussions: ItsPrompt Discussions!
- join our discord: TheItsProjects!
Puh, that was so much to read... But now, lets have fun with ItsPrompt!
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.