diff --git a/Mininterface/index.html b/Mininterface/index.html index 9ab29db..660ed02 100644 --- a/Mininterface/index.html +++ b/Mininterface/index.html @@ -869,6 +869,62 @@

Prompt the user to input a number. Empty input = 0.

+
m = run()  # receives a Mininterface object
+m.ask_number("What's your age?")
+
+

Ask number dialog

+ + +

Parameters:

+ + + + + + + + + + + + + + + + + +
NameTypeDescriptionDefault
text + str + +
+

The question text.

+
+ 		+ required +
+ + +

Returns:

+ + + + + + + + + + + + + +
TypeDescription
+ int + +
+

Number

+
+
@@ -908,7 +964,7 @@

You can denote the choices in many ways. Either put options in an iterable:

-
from mininterface import run, Tag
+
from mininterface import run
 m = run()
 m.choice([1, 2])
 

diff --git a/Overview/index.html b/Overview/index.html
index e4ce188..b751365 100644
--- a/Overview/index.html
+++ b/Overview/index.html
@@ -1,589 +1,307 @@
 
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-        Overview - Mininterface
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+

 

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+ + + \ No newline at end of file diff --git a/index.html b/index.html index 38e6d9f..340ab5d 100644 --- a/index.html +++ b/index.html @@ -486,19 +486,19 @@

Mininterface – ac @dataclass class Env: - """Set of options.""" + """ This calculates something. """ - test: bool = False - """ My testing flag """ + my_flag: bool = False + """ This switches the functionality """ - important_number: int = 4 + my_number: int = 4 """ This number is very important """ if __name__ == "__main__": env = run(Env, prog="My application").env # Attributes are suggested by the IDE # along with the hint text 'This number is very important'. - print(env.important_number) + print(env.my_number)

Contents

You got CLI

It was all the code you need. No lengthy blocks of code imposed by an external dependency. Besides the GUI/TUI, you receive powerful YAML-configurable CLI parsing.

+

TODO regenerate output and all the images +TODO it seems that input missing dataclass fields is broken, it just shows it must be set via cli

$ ./hello.py
 usage: My application [-h] [--test | --no-test] [--important-number INT]
 
-Set of options.
+This calculates something.
 
 ╭─ options ──────────────────────────────────────────────────────────╮
 │ -h, --help              show this help message and exit            │
@@ -525,12 +527,12 @@ 
You got CLI

You got config file management

Loading config file is a piece of cake. Alongside program.py, put program.yaml and put there some of the arguments. They are seamlessly taken as defaults.

-
important_number: 555
+
my_number: 555
 

 
You got dialogues

 
Check out several useful methods to handle user dialogues. Here we bound the interface to a with statement that redirects stdout directly to the window.

 
with run(Env) as m:
-    print(f"Your important number is {m.env.important_number}")
+    print(f"Your important number is {m.env.my_number}")
     boolean = m.is_yes("Is that alright?")
 

 
Small window with the text 'Your important number'
@@ -540,7 +542,7 @@ 
Background

 
Writing a small and useful program might be a task that takes fifteen minutes. Adding a CLI to specify the parameters is not so much overhead. But building a simple GUI around it? HOURS! Hours spent on researching GUI libraries, wondering why the Python desktop app ecosystem lags so far behind the web world. All you need is a few input fields validated through a clickable window... You do not deserve to add hundred of lines of the code just to define some editable fields. Mininterface is here to help.

 
The config variables needed by your program are kept in cozy dataclasses. Write less! The syntax of tyro does not require any overhead (as its argparse alternatives do). You just annotate a class attribute, append a simple docstring and get a fully functional application:
 * Call it as program.py --help to display full help.
-* Use any flag in CLI: program.py --test  causes env.test be set to True.
+* Use any flag in CLI: program.py --my-flag  causes env.my_flag be set to True.
 * The main benefit: Launch it without parameters as program.py to get a full working window with all the flags ready to be edited.
 * Running on a remote machine? Automatic regression to the text interface.

 
Installation

diff --git a/run/index.html b/run/index.html
index 7c6ce6d..0115a99 100644
--- a/run/index.html
+++ b/run/index.html
@@ -664,7 +664,7 @@ 
Run

                 
If some required fields are missing at startup, we ask for them in a UI instead of program exit.

 
@dataclass
 class Env:
-required_number: int
+    required_number: int
 m = run(Env, ask_for_missing=True)
 

 
$ program.py  # omitting --required-number
diff --git a/search/search_index.json b/search/search_index.json
index 9bd0c0b..85775e5 100644
--- a/search/search_index.json
+++ b/search/search_index.json
@@ -1 +1 @@
-{"config":{"lang":["en"],"separator":"[\\s\\-]+","pipeline":["stopWordFilter"]},"docs":[{"location":"","title":"Mininterface \u2013 access to GUI, TUI, CLI and config files","text":"
Write the program core, do not bother with the input/output.
 
 
 
Check out the code, which is surprisingly short, that displays such a window or its textual fallback.
 
from dataclasses import dataclass\nfrom mininterface import run\n\n@dataclass\nclass Env:\n    \"\"\"Set of options.\"\"\"\n\n    test: bool = False\n    \"\"\" My testing flag \"\"\"\n\n    important_number: int = 4\n    \"\"\" This number is very important \"\"\"\n\nif __name__ == \"__main__\":\n    env = run(Env, prog=\"My application\").env\n    # Attributes are suggested by the IDE\n    # along with the hint text 'This number is very important'.\n    print(env.important_number)\n
"},{"location":"#contents","title":"Contents","text":"
     
  • You got CLI
    •  
  • You got config file management
    •  
  • You got dialogues
    •  
  • Background
    •  
  • Installation
    •  
  • Docs
    •  
  • Examples
    •  
"},{"location":"#you-got-cli","title":"You got CLI","text":"
It was all the code you need. No lengthy blocks of code imposed by an external dependency. Besides the GUI/TUI, you receive powerful YAML-configurable CLI parsing.
 
$ ./hello.py\nusage: My application [-h] [--test | --no-test] [--important-number INT]\n\nSet of options.\n\n\u256d\u2500 options \u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256e\n\u2502 -h, --help              show this help message and exit            \u2502\n\u2502 --test, --no-test       My testing flag (default: False)           \u2502\n\u2502 --important-number INT  This number is very important (default: 4) \u2502\n\u2570\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256f\n
"},{"location":"#you-got-config-file-management","title":"You got config file management","text":"
Loading config file is a piece of cake. Alongside program.py, put program.yaml and put there some of the arguments. They are seamlessly taken as defaults.
 
important_number: 555\n
"},{"location":"#you-got-dialogues","title":"You got dialogues","text":"
Check out several useful methods to handle user dialogues. Here we bound the interface to a with statement that redirects stdout directly to the window.
 
with run(Env) as m:\n    print(f\"Your important number is {m.env.important_number}\")\n    boolean = m.is_yes(\"Is that alright?\")\n
 
 
"},{"location":"#background","title":"Background","text":"
Wrapper between the tyro argparse replacement and tkinter_form that converts dicts into a GUI.
 
Writing a small and useful program might be a task that takes fifteen minutes. Adding a CLI to specify the parameters is not so much overhead. But building a simple GUI around it? HOURS! Hours spent on researching GUI libraries, wondering why the Python desktop app ecosystem lags so far behind the web world. All you need is a few input fields validated through a clickable window... You do not deserve to add hundred of lines of the code just to define some editable fields. Mininterface is here to help.
 
The config variables needed by your program are kept in cozy dataclasses. Write less! The syntax of tyro does not require any overhead (as its argparse alternatives do). You just annotate a class attribute, append a simple docstring and get a fully functional application: * Call it as program.py --help to display full help. * Use any flag in CLI: program.py --test  causes env.test be set to True. * The main benefit: Launch it without parameters as program.py to get a full working window with all the flags ready to be edited. * Running on a remote machine? Automatic regression to the text interface.
"},{"location":"#installation","title":"Installation","text":"
Install with a single command from PyPi.
 
pip install mininterface\n
"},{"location":"#docs","title":"Docs","text":"
See the docs overview at https://cz-nic.github.io/mininterface/.
"},{"location":"#examples","title":"Examples","text":""},{"location":"#a-complex-dataclass","title":"A complex dataclass.","text":"
from typing import Annotated\nfrom dataclasses import dataclass\nfrom mininterface.validators import not_empty\nfrom mininterface import run, Tag, Validation\n\n@dataclass\nclass NestedEnv:\n  another_number: int = 7\n  \"\"\" This field is nested \"\"\"\n\n@dataclass\nclass Env:\n  nested_config: NestedEnv\n\n  mandatory_str: str\n  \"\"\" As there is not default value, you will be prompted automatically to fill up the field \"\"\"\n\n  my_number: int | None = None\n  \"\"\" This is not just a dummy number, if left empty, it is None. \"\"\"\n\n  my_string: str = \"Hello\"\n  \"\"\" A dummy string \"\"\"\n\n  my_flag: bool = False\n  \"\"\" Checkbox test \"\"\"\n\n  my_validated: Annotated[str, Validation(not_empty)] = \"hello\"\n  \"\"\" A validated field \"\"\"\n\nm = run(Env, title=\"My program\")\n# See some values\nprint(m.env.nested_config.another_number)  # 7\nprint(m.env)\n# Env(nested_config=NestedEnv(another_number=7), my_number=5, my_string='Hello', my_flag=False, my_validated='hello')\n\n# Edit values in a dialog\nm.form()\n
"},{"location":"#form-with-paths","title":"Form with paths","text":"
We have a dict with some paths. Here is how it looks.
 
from pathlib import Path\nfrom mininterface import run, Tag\n\nm = run(title=\"My program\")\nmy_dictionary = {\n  \"paths\": Tag(\"\", annotation=list[Path]),\n  \"default_paths\": Tag([Path(\"/tmp\"), Path(\"/usr\")], annotation=list[Path])\n  }\n\n# Edit values in a dialog\nm.form(my_dictionary)\n
 
"},{"location":"Changelog/","title":"Changelog","text":"
Due to an early stage of development, changes are tracked in commit messages only.
"},{"location":"Experimental/","title":"Experimental","text":""},{"location":"Experimental/#mininterface.experimental.SubmitButton","title":"SubmitButton","text":"
Create a button. When clicked, the form submits.         If submission succeeds (validation checks pass), its value becomes True.
 
from pathlib import Path\nfrom mininterface import run, Tag\nfrom mininterface.experimental import SubmitButton\n\nm = run()\nout = m.form({\n    \"File name\": Tag(\"/tmp\", annotation=Path),\n    \"Append text\": {\n        \"My text\": \"\",\n        \"Append now\": SubmitButton()\n    },\n    \"Duplicate\": {\n        \"Method\": Tag(\"twice\", choices=[\"twice\", \"thrice\"]),\n        \"Duplicate now\": SubmitButton()\n    }\n})\n# Clicking on 'Append now' button\nprint(out)\n# {'File name': PosixPath('/tmp'),\n# 'Append text': {'My text': '', 'Append now': True},\n# 'Duplicate': {'Method': 'twice', 'Duplicate now': False}}\n
 
"},{"location":"Facet/","title":"Facet","text":"
A frontend side of the interface. While a dialog is open,     this allows to set frontend properties like the heading.
 
Read Tag.facet to see how to access from the front-end side. Read Mininterface.facet to see how to access from the back-end side.
"},{"location":"Facet/#mininterface.facet.Facet.set_title","title":"set_title(text)","text":"
Set the main heading.
"},{"location":"Facet/#mininterface.facet.Facet.submit","title":"submit()","text":"
Submits the whole form
"},{"location":"Mininterface/","title":"Mininterface","text":"
The base interface.     You get one through mininterface.run which fills CLI arguments and config file to mininterface.env     or you can create one directly (without benefiting from the CLI parsing).
 Raise 
Cancelled: A SystemExit based exception noting that the program exits without a traceback, ex. if user hits the escape.
 Raise 
InterfaceNotAvailable: Interface failed to init, ex. display not available in GUI.
"},{"location":"Mininterface/#mininterface.Mininterface.env","title":"env: EnvClass = EnvInstance","text":"
Parsed arguments, fetched from cli.     Contains whole configuration (previously fetched from CLI and config file).
 
$ program.py --number 10\n
 
from dataclasses import dataclass\nfrom mininterface import run\n\n@dataclass\nclass Env:\n    number: int = 3\n    text: str = \"\"\n\nm = run(Env)\nprint(m.env.number)  # 10\n
"},{"location":"Mininterface/#mininterface.Mininterface.facet","title":"facet: Facet = MinFacet()","text":"
Access to the UI facet from the back-end side. (Read Tag.facet to access from the front-end side.)
 
from mininterface import run\nwith run(title='My window title') as m:\n    m.facet.set_title(\"My form title\")\n    m.form({\"My form\": 1})\n
 
"},{"location":"Mininterface/#mininterface.Mininterface.__enter__","title":"__enter__()","text":"
When used in the with statement, the GUI window does not vanish between dialogs and it redirects the stdout to a text area.
"},{"location":"Mininterface/#mininterface.Mininterface.alert","title":"alert(text)","text":"
Prompt the user to confirm the text.
"},{"location":"Mininterface/#mininterface.Mininterface.ask","title":"ask(text)","text":"
Prompt the user to input a text.
"},{"location":"Mininterface/#mininterface.Mininterface.ask_number","title":"ask_number(text)","text":"
Prompt the user to input a number. Empty input = 0.
"},{"location":"Mininterface/#mininterface.Mininterface.choice","title":"choice(choices, title='', _guesses=None, skippable=True, launch=True, _multiple=True, default=None)","text":"
Prompt the user to select. Useful for a menu creation.
 
Parameters:
 Name Type Description Default choices ChoicesType 
You can denote the choices in many ways. Either put options in an iterable:
 
from mininterface import run, Tag\nm = run()\nm.choice([1, 2])\n
 
 
Or to a dict {name: value}. Then name are used as labels.
 
m.choice({\"one\": 1, \"two\": 2})  # returns 1\n
 
Alternatively, you may specify the names in Tags.
 
m.choice([Tag(1, name=\"one\"), Tag(2, name=\"two\")])  # returns 1\n
 
 required title str 
Form title
 '' default str | None 
The value of the checked choice.
 
m.choice({\"one\": 1, \"two\": 2}, default=2)  # returns 2\n
 
 None skippable bool 
If there is a single option, choose it directly, without a dialog.
 True launch bool 
If the chosen value is a callback, we directly call it. Then, the function returns None.
 True 
Returns:
 Type Description TagValue | list[TagValue] | Any 
The chosen value.
 TagValue | list[TagValue] | Any 
If launch=True and the chosen value is a callback, we call it and return its result.
"},{"location":"Mininterface/#mininterface.Mininterface.form","title":"form(form=None, title='')","text":"
Prompt the user to fill up whole form.
 
Parameters:
 Name Type Description Default form FormDictOrEnv | None 
Dict of {labels: value}. The form widget infers from the default value type. The dict can be nested, it can contain a subgroup. The value might be a Tag that allows you to add descriptions. If None, the self.env is being used as a form, allowing the user to edit whole configuration.     (Previously fetched from CLI and config file.) A checkbox example: {\"my label\": Tag(True, \"my description\")}
 None title str 
Optional form title
 '' 
Returns:
 Type Description FormDictOrEnv | EnvClass 
dict or dataclass: If the form is null, the output is self.env.
 
If the form is a dict, the output is another dict. Whereas the original form stays intact (with the values update), we return a new raw dict with all values resolved (all Tag objects are resolved to their value).
 
original = {\"my label\": Tag(True, \"my description\")}\noutput = m.form(original)  # Sets the label to False in the dialog\n\n# Original dict was updated\nprint(original[\"my label\"])  # Tag(False, \"my description\")\n\n# Output dict is resolved, contains only raw values\nprint(output[\"my label\"])  # False\n
 
Why this behaviour? You need to do some validation, hence you put Tag objects in the input dict. Then, you just need to work with the values.
 
original = {\"my label\": Tag(True, \"my description\")}\noutput = m.form(original)  # Sets the label to False in the dialog\noutput[\"my_label\"]\n
 
In the case you are willing to re-use the dict, you need not to lose the definitions, hence you end up with accessing via the .val.
 
original = {\"my label\": Tag(True, \"my description\")}\n\nfor i in range(10):\n    m.form(original, f\"Attempt {i}\")\n    print(\"The result\", original[\"my label\"].val)\n
"},{"location":"Mininterface/#mininterface.Mininterface.is_yes","title":"is_yes(text)","text":"
Display confirm box, focusing yes.
 
m = run()\nprint(m.is_yes(\"Is that alright?\"))  # True/False\n
 
"},{"location":"Mininterface/#mininterface.Mininterface.is_no","title":"is_no(text)","text":"
Display confirm box, focusing no.
"},{"location":"Overview/","title":"Overview","text":""},{"location":"Overview/#basic-usage","title":"Basic usage","text":"
Use a common dataclass, a Pydantic BaseModel or an attrs model to store the configuration. Wrap it to the run method that returns an interface m. Access the configuration via m.env or use it to prompt the user m.is_yes(\"Is that alright?\").
 
To do any advanced things, stick the value to a powerful Tag or its subclassed types. Ex. for a validation only, use its Validation alias.
 
At last, use Facet to tackle the interface from the back-end (m) or the front-end (Tag) side.
"},{"location":"Overview/#supported-types","title":"Supported types","text":"
Various types are supported:
 
     
  • scalars
    •  
  • functions
    •  
  • well-known objects (Path, datetime)
    •  
  • iterables (like list[Path])
    •  
  • custom classes (somewhat)
    •  
  • union types (like int | None)
    •  
 
Take a look how it works with the variables organized in a dataclass:
 
from dataclasses import dataclass\nfrom pathlib import Path\n\nfrom mininterface import run\n\n\n@dataclass\nclass Env:\n    my_number: int = 1\n    \"\"\" A dummy number \"\"\"\n    my_boolean: bool = True\n    \"\"\" A dummy boolean \"\"\"\n    my_conditional_number: int | None = None\n    \"\"\" A number that can be null if left empty \"\"\"\n    my_path: Path = Path(\"/tmp\")\n    \"\"\" A dummy path \"\"\"\n\n\nm = run(Env)  # m.env contains an Env instance\nm.form()  # Prompt a dialog; m.form() without parameter edits m.env\nprint(m.env)\n# Env(my_number=1, my_boolean=True, my_path=PosixPath('/tmp'),\n#  my_point=<__main__.Point object at 0x7ecb5427fdd0>)\n
 
 
Variables organized in a dict:
 
Along scalar types, there is (basic) support for common iterables or custom classes.
 
from mininterface import run\n\nclass Point:\n    def __init__(self, i: int):\n        self.i = i\n\n    def __str__(self):\n        return str(self.i)\n\n\nvalues = {\"my_number\": 1,\n          \"my_list\": [1, 2, 3],\n          \"my_point\": Point(10)\n          }\n\nm = run()\nm.form(values)  # Prompt a dialog\nprint(values)  # {'my_number': 2, 'my_list': [2, 3], 'my_point': <__main__.Point object...>}\nprint(values[\"my_point\"].i)  # 100\n
 
"},{"location":"Overview/#nested-configuration","title":"Nested configuration","text":"
You can easily nest the configuration. (See also Tyro Hierarchical Configs).
 
Just put another dataclass inside the config file:
 
@dataclass\nclass FurtherConfig:\n    token: str\n    host: str = \"example.org\"\n\n@dataclass\nclass Config:\n    further: FurtherConfig\n\n...\nprint(config.further.host)  # example.org\n
 
The attributes can by defaulted by CLI:
 
$./program.py --further.host example.net\n
 
And in a YAML config file. Note that you are not obliged to define all the attributes, a subset will do. (Ex. you do not need to specify token too.)
 
further:\n  host: example.com\n
"},{"location":"Overview/#all-possible-interfaces","title":"All possible interfaces","text":"
Normally, you get an interface through mininterface.run but if you do not wish to parse CLI and config file, you can invoke one directly.
 
Several interfaces exist:
 
     
  • Mininterface \u2013 The base interface the others are fully compatible with.
    •  
  • GuiInterface \u2013 A tkinter window.
    •  
  • TuiInterface \u2013 An interactive terminal.
    •  
  • TextualInterface \u2013 If textual installed, rich interface is used.
    •  
  • TextInterface \u2013 Plain text only interface with no dependency as a fallback.
    •  
  • ReplInterface \u2013 A debug terminal. Invokes a breakpoint after every dialog.
    •  
 
How to invoke a specific interface.
 
with TuiInterface(\"My program\") as m:\n    number = m.ask_number(\"Returns number\")\n
"},{"location":"Standalone/","title":"Standalone","text":"
When invoked directly, it creates simple GUI dialogs.
 
$ mininterface  --help\nusage: Mininterface [-h] [OPTIONS]\n\nSimple GUI dialog. Outputs the value the user entered.\n\n\u256d\u2500 options \u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256e\n\u2502 -h, --help              show this help message and exit                                   \u2502\n\u2502 --alert STR             Display the OK dialog with text. (default: '')                    \u2502\n\u2502 --ask STR               Prompt the user to input a text. (default: '')                    \u2502\n\u2502 --ask-number STR        Prompt the user to input a number. Empty input = 0. (default: '') \u2502\n\u2502 --is-yes STR            Display confirm box, focusing yes. (default: '')                  \u2502\n\u2502 --is-no STR             Display confirm box, focusing no. (default: '')                   \u2502\n\u2570\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256f\n
 
You can fetch a value to i.e. a bash script.
 
$ mininterface  --ask-number \"What's your age?\"  # GUI or TUI window invoked\n18\n
 
 
"},{"location":"Tag/","title":"Tag","text":"
Wrapper around a value that encapsulates a description, validation etc. When you provide a value to an interface, you may instead use this object.
 
Bridge between the input values and a UI widget. The widget is created with the help of this object, then transforms the value back (str to int conversion etc).
"},{"location":"Tag/#mininterface.Tag.val","title":"val: TagValue = None","text":"
The value wrapped by Tag.
 
from mininterface import run, Tag\n\ntag = Tag(True, \"This is my boolean\", bool)\nm = run()\nm.form({\"My boolean\": tag})\nprint(tag.val)  # True/False\nprint()\n
 
 
The encapsulated value is True, tag.description is 'This is my boolean', tag.annotation is bool and 'My boolean' is used as tag.name.
"},{"location":"Tag/#mininterface.Tag.description","title":"description: str = ''","text":"
The description displayed in the UI.
"},{"location":"Tag/#mininterface.Tag.annotation","title":"annotation: type | None = None","text":"
Used for validation (ex. to convert an empty string to None). If not set, will be determined automatically from the val type.
"},{"location":"Tag/#mininterface.Tag.name","title":"name: str | None = None","text":"
Name displayed in the UI.
"},{"location":"Tag/#mininterface.Tag.validation","title":"validation: Callable[[Tag], ValidationResult | tuple[ValidationResult, TagValue]] | None = None","text":"
When the user submits the form, the values are validated (and possibly transformed) with a callback function.     If the validation fails, user is prompted to edit the value.     Return True if validation succeeded or False or an error message when it failed.
 
ValidationResult is a bool or the error message (that implicitly means it has failed).
 
def check(tag: Tag):\n    if tag.val < 10:\n        return \"The value must be at least 10\"\nm.form({\"number\", Tag(12, validation=check)})\n
 
Either use a custom callback function or mininterface.validators.
 
from mininterface.validators import not_empty\nm.form({\"number\", Tag(\"\", validation=not_empty)})\n# User cannot leave the field empty.\n
 
You may use the validation in a type annotation. 
from mininterface import Tag, Validation\n@dataclass\nclass Env:\n    my_text: Annotated[str, Validation(not_empty) = \"will not be emtpy\"\n\n    # which is an alias for:\n    # my_text: Annotated[str, Tag(validation=not_empty)] = \"will not be emtpy\"\n
 
NOTE Undocumented feature, we can return tuple [ValidationResult, FieldValue] to set the self.val.
"},{"location":"Tag/#mininterface.Tag.choices","title":"choices: ChoicesType | None = None","text":"
Print the radio buttons. Constraint the value.
 
from dataclasses import dataclass\nfrom typing import Annotated\nfrom mininterface import run, Choices\n\n@dataclass\nclass Env:\n    foo: Annotated[\"str\", Choices(\"one\", \"two\")] = \"one\"\n\n    # `Choices` is an alias for `Tag(choices=)`\n\nm = run(Env)\nm.form()  # prompts a dialog\n
"},{"location":"Tag/#mininterface.Tag.on_change","title":"on_change: Callable[[Tag], Any] | None = None","text":"
Accepts a callback that launches whenever the value changes (if the validation succeeds). The callback runs while the dialog is still running. The return value of the callback is currently not used.
 
In the following example, we alter the heading title according to the chosen value.
 
from mininterface import run, Tag\n\ndef callback(tag: Tag):\n    tag.facet.set_title(f\"Value changed to {tag.val}\")\n\nm = run()\nm.facet.set_title(\"Click the checkbox\")\nm.form({\n    \"My choice\": Tag(choices=[\"one\", \"two\"], on_change=callback)\n})\n
 
 
"},{"location":"Tag/#mininterface.Tag.facet","title":"facet: Optional[Facet] = None","text":"
Access to the UI facet from the front-end side. (Read Mininterface.facet to access from the back-end side.)
 
Set the UI facet from within a callback, ex. a validator.
 
from mininterface import run, Tag\n\ndef my_check(tag: Tag):\n    tag.facet.set_title(\"My form title\")\n    return \"Validation failed\"\n\nwith run(title='My window title') as m:\n    m.form({\"My form\": Tag(1, validation=my_check)})\n
 
This happens when you click ok.
 
"},{"location":"Tag/#mininterface.Tag.original_val","title":"original_val = None","text":"
Meant to be read only in callbacks. The original value, preceding UI change. Handy while validating.
 
def check(tag.val):\n    if tag.val != tag.original_val:\n        return \"You have to change the value.\"\nm.form({\"number\", Tag(8, validation=check)})\n
"},{"location":"Tag/#mininterface.Tag.update","title":"update","text":"
UI value \u2192 Tag value \u2192 original value. (With type conversion and checks.)
 
Parameters:
 Name Type Description Default ui_value TagValue 
The value as it has been updated in a UI. Update accordingly the value in the original linked dict/object the mininterface was invoked with.
 
Validates the type and do the transformation. (Ex: Some values might be nulled from \"\".)
 required 
Returns:
 Type Description bool 
bool, whether the value is alright or whether the revision is needed.
"},{"location":"Tag/#mininterface.Choices","title":"Choices(*choices)","text":"
An alias, see Tag.choices
"},{"location":"Tag/#helper-types","title":"Helper types","text":""},{"location":"Tag/#mininterface.tag.ValidationResult","title":"ValidationResult = bool | ErrorMessage","text":"
Callback validation result is either boolean or an error message.
"},{"location":"Tag/#mininterface.tag.ErrorMessage","title":"ErrorMessage = TypeVar('ErrorMessage')","text":"
A string, callback validation error message.
"},{"location":"Tag/#mininterface.tag.TagValue","title":"TagValue = TypeVar('TagValue')","text":"
Any value.
"},{"location":"Types/","title":"Types","text":""},{"location":"Types/#mininterface.types.PathTag","title":"PathTag","text":"
Use this helper object to select files.
 
In the following example, we see that it is not always needed to use this object.
 
     
  • File 1 \u2013 plain detection, button to a file picker appeared.
    •  
  • File 2 \u2013 the same.
    •  
  • File 3 \u2013 we specified multiple paths can be selected.
    •  
 
from pathlib import Path\nfrom mininterface import run, Tag\nfrom mininterface.aliases import PathTag\n\nm = run()\nout = m.form({\n    \"File 1\": Path(\"/tmp\"),\n    \"File 2\": Tag(\"\", annotation=Path),\n    \"File 3\": PathTag([Path(\"/tmp\")], multiple=True),\n})\nprint(out)\n# {'File 1': PosixPath('/tmp'), 'File 2': PosixPath('.'), 'File 3': [PosixPath('/tmp')]}\n
 
"},{"location":"Types/#mininterface.types.PathTag.multiple","title":"multiple: str = False","text":"
The user can select multiple files.
"},{"location":"Types/#mininterface.types.Validation","title":"Validation(check)","text":"
Alias to Tag(validation=...)
 
from mininterface import Tag, Validation\n@dataclass\nclass Env:\n    my_text: Annotated[str, Validation(not_empty) = \"will not be emtpy\"\n\n    # which is an alias for:\n    # my_text: Annotated[str, Tag(validation=not_empty)] = \"will not be emtpy\"\n
 
Parameters:
 Name Type Description Default check Callable[[Tag], ValidationResult | tuple[ValidationResult, TagValue]] 
Callback function.
 required"},{"location":"Types/#mininterface.types.Choices","title":"Choices(*choices)","text":"
An alias, see Tag.choices
"},{"location":"Validation/","title":"Validation","text":"
We recommend to use the dataclass and validate with the Annotated keyword. We use a Validation type here.
 
from typing import Annotated\nfrom mininterface.validators import not_empty\nfrom mininterface import Validation\n\n@dataclass\nclass Env:\n    test: Annotated[str, Validation(not_empty)] = \"hello\"\n
 
Under the hood, this is just a Tag.
 
@dataclass\nclass Env:\n    test: Annotated[str, Tag(validation=not_empty)] = \"hello\"\n
 
Why we used it in an Annotated statement? To preserve the date type.
 
@dataclass\nclass Env:\n    my_string: Tag = Tag(\"hello\", validation=not_empty)\n\nm = run(Env)\nprint(type(m.env.my_string))  # Tag\nprint(m.env.my_string.val)  # hello\n
"},{"location":"Validation/#validators","title":"validators","text":"
Functions suitable for Tag validation. When the user submits a value whose validation fails, they are prompted to edit the value.
 
m = run()\nmy_dict = m.form({\"my_text\", Tag(\"\", validation=validators.not_empty)})\nmy_dict[\"my_text\"]  # You can be sure the value is not empty here.\n
 
Note that alternatively to this module, you may validate with Pydantic or an attrs model.
 
from pydantic import BaseModel, Field\n\nclass MyModel(BaseModel):\n    restrained: str = Field(default=\"hello\", max_length=5)\n
 
import attr\nfrom attr.validators import max_len\n\n@attr.s\nclass AttrsModel:\n    restrained: str = attr.ib(default=\"hello\", validator=max_len(5))\n
"},{"location":"Validation/#mininterface.validators.not_empty","title":"not_empty(tag)","text":"
Assures that Tag the user has written a value and did not let the field empty.
 
from mininterface import Tag, validators, run\n\nm = run()\nm.form({\"my_text\": Tag(\"\", validation=validators.not_empty)})\n# User cannot leave the string field empty.\n
 
When submitting an empty value, a warning appears:
 
 
Note that for Path, an empty string is converted to an empty Path('.'), hence '.' too is considered as an empty input and the user is not able to set '.' as a value. This does not seem to me as a bad behaviour as in CLI you clearly see the CWD, whereas in a UI the CWD is not evident.
 
Parameters:
 Name Type Description Default tag Tag required"},{"location":"Validation/#mininterface.validators.limit","title":"limit(maxOrMin=None, max_=None, lt=None, gt=None, transform=False)","text":"
Limit a number range or a string length.
 
Either use as limit(maximum) or limit(minimum, maximum).
 
Parameters:
 Name Type Description Default maximum int 
limit(maximum) \u2013 from zero (including) to maximum (including)
 required minimum int 
limit(minimum, maximum) \u2013 From minimum (including) to maximum (including)
 required lt float | None 
lesser than
 None gt float | None 
greater than
 None transform bool 
If the value is not withing the limit, transform it to a boundary. 
from mininterface import run, Tag\nfrom mininterface.validators import limit\n\nm = run()\nm.form({\"my_number\": Tag(2, validation=limit(1, 10, transform=True))})\n# Put there '50' \u2192 transformed to 10 and dialog reappears\n# with 'Value must be between 1 and 10.'\n
 
 False"},{"location":"run/","title":"Run","text":"
The main access, start here. Wrap your configuration dataclass into run to access the interface. An interface is chosen automatically, with the preference of the graphical one, regressed to a text interface for machines without display. Besides, if given a configuration dataclass, the function enriches it with the CLI commands and possibly with the default from a config file if such exists. It searches the config file in the current working directory, with the program name ending on .yaml, ex: program.py will fetch ./program.yaml.
 
Parameters:
 Name Type Description Default env_class Type[EnvClass] | None 
Dataclass with the configuration. Their values will be modified with the CLI arguments.
 None ask_on_empty_cli bool 
If program was launched with no arguments (empty CLI), invokes self.form() to edit the fields. (Withdrawn when ask_for_missing happens.) 
@dataclass\nclass Env:\nnumber: int = 3\ntext: str = \"\"\nm = run(Env, ask_on_empty=True)\n
 
$ program.py  #  omitting all parameters\n# Dialog for `number` and `text` appears\n$ program.py --number 3\n# No dialog appears\n
 False title str 
The main title. If not set, taken from prog or program name.
 '' config_file Path | str | bool 
File to load YAML to be merged with the configuration. You do not have to re-define all the settings in the config file, you can choose a few. If set to True (default), we try to find one in the current working dir, whose name stem is the same as the program's. Ex: program.py will search for program.yaml. If False, no config file is used.
 True add_verbosity bool 
Adds the verbose flag that automatically sets the level to logging.INFO (-v) or logging.DEBUG (-vv).
 
import logging\nlogger = logging.getLogger(__name__)\n\nm = run(Env, add_verbosity=True)\nlogger.info(\"Info shown\") # needs `-v` or `--verbose`\nlogger.debug(\"Debug not shown\")  # needs `-vv`\n# $ program.py --verbose\n# Info shown\n
 
$ program.py --verbose\nInfo shown\n
 True ask_for_missing bool 
If some required fields are missing at startup, we ask for them in a UI instead of program exit.
 
@dataclass\nclass Env:\nrequired_number: int\nm = run(Env, ask_for_missing=True)\n
 
$ program.py  # omitting --required-number\n# Dialog for `required_number` appears\n
 True interface Type[Mininterface] 
Which interface to prefer. By default, we use the GUI, the fallback is the TUI. See the full list of possible interfaces.
 GuiInterface or TuiInterface Kwargs 
The same as for argparse.ArgumentParser.
 
Returns:
 Type Description Mininterface[EnvClass] 
An interface, ready to be used.
 
You cay context manager the function by a with statement. The stdout will be redirected to the interface (ex. a GUI window).
 
with run(Env) as m:\n    print(f\"Your important number is {m.env.important_number}\")\n    boolean = m.is_yes(\"Is that alright?\")\n
 
 
"}]}
\ No newline at end of file
+{"config":{"lang":["en"],"separator":"[\\s\\-]+","pipeline":["stopWordFilter"]},"docs":[{"location":"","title":"Mininterface \u2013 access to GUI, TUI, CLI and config files","text":"
Write the program core, do not bother with the input/output.
 
 
 
Check out the code, which is surprisingly short, that displays such a window or its textual fallback.
 
from dataclasses import dataclass\nfrom mininterface import run\n\n@dataclass\nclass Env:\n    \"\"\" This calculates something. \"\"\"\n\n    my_flag: bool = False\n    \"\"\" This switches the functionality \"\"\"\n\n    my_number: int = 4\n    \"\"\" This number is very important \"\"\"\n\nif __name__ == \"__main__\":\n    env = run(Env, prog=\"My application\").env\n    # Attributes are suggested by the IDE\n    # along with the hint text 'This number is very important'.\n    print(env.my_number)\n
"},{"location":"#contents","title":"Contents","text":"
     
  • You got CLI
    •  
  • You got config file management
    •  
  • You got dialogues
    •  
  • Background
    •  
  • Installation
    •  
  • Docs
    •  
  • Examples
    •  
"},{"location":"#you-got-cli","title":"You got CLI","text":"
It was all the code you need. No lengthy blocks of code imposed by an external dependency. Besides the GUI/TUI, you receive powerful YAML-configurable CLI parsing.
 
TODO regenerate output and all the images TODO it seems that input missing dataclass fields is broken, it just shows it must be set via cli
 
$ ./hello.py\nusage: My application [-h] [--test | --no-test] [--important-number INT]\n\nThis calculates something.\n\n\u256d\u2500 options \u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256e\n\u2502 -h, --help              show this help message and exit            \u2502\n\u2502 --test, --no-test       My testing flag (default: False)           \u2502\n\u2502 --important-number INT  This number is very important (default: 4) \u2502\n\u2570\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256f\n
"},{"location":"#you-got-config-file-management","title":"You got config file management","text":"
Loading config file is a piece of cake. Alongside program.py, put program.yaml and put there some of the arguments. They are seamlessly taken as defaults.
 
my_number: 555\n
"},{"location":"#you-got-dialogues","title":"You got dialogues","text":"
Check out several useful methods to handle user dialogues. Here we bound the interface to a with statement that redirects stdout directly to the window.
 
with run(Env) as m:\n    print(f\"Your important number is {m.env.my_number}\")\n    boolean = m.is_yes(\"Is that alright?\")\n
 
 
"},{"location":"#background","title":"Background","text":"
Wrapper between the tyro argparse replacement and tkinter_form that converts dicts into a GUI.
 
Writing a small and useful program might be a task that takes fifteen minutes. Adding a CLI to specify the parameters is not so much overhead. But building a simple GUI around it? HOURS! Hours spent on researching GUI libraries, wondering why the Python desktop app ecosystem lags so far behind the web world. All you need is a few input fields validated through a clickable window... You do not deserve to add hundred of lines of the code just to define some editable fields. Mininterface is here to help.
 
The config variables needed by your program are kept in cozy dataclasses. Write less! The syntax of tyro does not require any overhead (as its argparse alternatives do). You just annotate a class attribute, append a simple docstring and get a fully functional application: * Call it as program.py --help to display full help. * Use any flag in CLI: program.py --my-flag  causes env.my_flag be set to True. * The main benefit: Launch it without parameters as program.py to get a full working window with all the flags ready to be edited. * Running on a remote machine? Automatic regression to the text interface.
"},{"location":"#installation","title":"Installation","text":"
Install with a single command from PyPi.
 
pip install mininterface\n
"},{"location":"#docs","title":"Docs","text":"
See the docs overview at https://cz-nic.github.io/mininterface/.
"},{"location":"#examples","title":"Examples","text":""},{"location":"#a-complex-dataclass","title":"A complex dataclass.","text":"
from typing import Annotated\nfrom dataclasses import dataclass\nfrom mininterface.validators import not_empty\nfrom mininterface import run, Tag, Validation\n\n@dataclass\nclass NestedEnv:\n  another_number: int = 7\n  \"\"\" This field is nested \"\"\"\n\n@dataclass\nclass Env:\n  nested_config: NestedEnv\n\n  mandatory_str: str\n  \"\"\" As there is not default value, you will be prompted automatically to fill up the field \"\"\"\n\n  my_number: int | None = None\n  \"\"\" This is not just a dummy number, if left empty, it is None. \"\"\"\n\n  my_string: str = \"Hello\"\n  \"\"\" A dummy string \"\"\"\n\n  my_flag: bool = False\n  \"\"\" Checkbox test \"\"\"\n\n  my_validated: Annotated[str, Validation(not_empty)] = \"hello\"\n  \"\"\" A validated field \"\"\"\n\nm = run(Env, title=\"My program\")\n# See some values\nprint(m.env.nested_config.another_number)  # 7\nprint(m.env)\n# Env(nested_config=NestedEnv(another_number=7), my_number=5, my_string='Hello', my_flag=False, my_validated='hello')\n\n# Edit values in a dialog\nm.form()\n
"},{"location":"#form-with-paths","title":"Form with paths","text":"
We have a dict with some paths. Here is how it looks.
 
from pathlib import Path\nfrom mininterface import run, Tag\n\nm = run(title=\"My program\")\nmy_dictionary = {\n  \"paths\": Tag(\"\", annotation=list[Path]),\n  \"default_paths\": Tag([Path(\"/tmp\"), Path(\"/usr\")], annotation=list[Path])\n  }\n\n# Edit values in a dialog\nm.form(my_dictionary)\n
 
"},{"location":"Changelog/","title":"Changelog","text":"
Due to an early stage of development, changes are tracked in commit messages only.
"},{"location":"Experimental/","title":"Experimental","text":""},{"location":"Experimental/#mininterface.experimental.SubmitButton","title":"SubmitButton","text":"
Create a button. When clicked, the form submits.         If submission succeeds (validation checks pass), its value becomes True.
 
from pathlib import Path\nfrom mininterface import run, Tag\nfrom mininterface.experimental import SubmitButton\n\nm = run()\nout = m.form({\n    \"File name\": Tag(\"/tmp\", annotation=Path),\n    \"Append text\": {\n        \"My text\": \"\",\n        \"Append now\": SubmitButton()\n    },\n    \"Duplicate\": {\n        \"Method\": Tag(\"twice\", choices=[\"twice\", \"thrice\"]),\n        \"Duplicate now\": SubmitButton()\n    }\n})\n# Clicking on 'Append now' button\nprint(out)\n# {'File name': PosixPath('/tmp'),\n# 'Append text': {'My text': '', 'Append now': True},\n# 'Duplicate': {'Method': 'twice', 'Duplicate now': False}}\n
 
"},{"location":"Facet/","title":"Facet","text":"
A frontend side of the interface. While a dialog is open,     this allows to set frontend properties like the heading.
 
Read Tag.facet to see how to access from the front-end side. Read Mininterface.facet to see how to access from the back-end side.
"},{"location":"Facet/#mininterface.facet.Facet.set_title","title":"set_title(text)","text":"
Set the main heading.
"},{"location":"Facet/#mininterface.facet.Facet.submit","title":"submit()","text":"
Submits the whole form
"},{"location":"Mininterface/","title":"Mininterface","text":"
The base interface.     You get one through mininterface.run which fills CLI arguments and config file to mininterface.env     or you can create one directly (without benefiting from the CLI parsing).
 Raise 
Cancelled: A SystemExit based exception noting that the program exits without a traceback, ex. if user hits the escape.
 Raise 
InterfaceNotAvailable: Interface failed to init, ex. display not available in GUI.
"},{"location":"Mininterface/#mininterface.Mininterface.env","title":"env: EnvClass = EnvInstance","text":"
Parsed arguments, fetched from cli.     Contains whole configuration (previously fetched from CLI and config file).
 
$ program.py --number 10\n
 
from dataclasses import dataclass\nfrom mininterface import run\n\n@dataclass\nclass Env:\n    number: int = 3\n    text: str = \"\"\n\nm = run(Env)\nprint(m.env.number)  # 10\n
"},{"location":"Mininterface/#mininterface.Mininterface.facet","title":"facet: Facet = MinFacet()","text":"
Access to the UI facet from the back-end side. (Read Tag.facet to access from the front-end side.)
 
from mininterface import run\nwith run(title='My window title') as m:\n    m.facet.set_title(\"My form title\")\n    m.form({\"My form\": 1})\n
 
"},{"location":"Mininterface/#mininterface.Mininterface.__enter__","title":"__enter__()","text":"
When used in the with statement, the GUI window does not vanish between dialogs and it redirects the stdout to a text area.
"},{"location":"Mininterface/#mininterface.Mininterface.alert","title":"alert(text)","text":"
Prompt the user to confirm the text.
"},{"location":"Mininterface/#mininterface.Mininterface.ask","title":"ask(text)","text":"
Prompt the user to input a text.
"},{"location":"Mininterface/#mininterface.Mininterface.ask_number","title":"ask_number(text)","text":"
Prompt the user to input a number. Empty input = 0.
 
m = run()  # receives a Mininterface object\nm.ask_number(\"What's your age?\")\n
 
 
Parameters:
 Name Type Description Default text str 
The question text.
 required 
Returns:
 Type Description int 
Number
"},{"location":"Mininterface/#mininterface.Mininterface.choice","title":"choice(choices, title='', _guesses=None, skippable=True, launch=True, _multiple=True, default=None)","text":"
Prompt the user to select. Useful for a menu creation.
 
Parameters:
 Name Type Description Default choices ChoicesType 
You can denote the choices in many ways. Either put options in an iterable:
 
from mininterface import run\nm = run()\nm.choice([1, 2])\n
 
 
Or to a dict {name: value}. Then name are used as labels.
 
m.choice({\"one\": 1, \"two\": 2})  # returns 1\n
 
Alternatively, you may specify the names in Tags.
 
m.choice([Tag(1, name=\"one\"), Tag(2, name=\"two\")])  # returns 1\n
 
 required title str 
Form title
 '' default str | None 
The value of the checked choice.
 
m.choice({\"one\": 1, \"two\": 2}, default=2)  # returns 2\n
 
 None skippable bool 
If there is a single option, choose it directly, without a dialog.
 True launch bool 
If the chosen value is a callback, we directly call it. Then, the function returns None.
 True 
Returns:
 Type Description TagValue | list[TagValue] | Any 
The chosen value.
 TagValue | list[TagValue] | Any 
If launch=True and the chosen value is a callback, we call it and return its result.
"},{"location":"Mininterface/#mininterface.Mininterface.form","title":"form(form=None, title='')","text":"
Prompt the user to fill up whole form.
 
Parameters:
 Name Type Description Default form FormDictOrEnv | None 
Dict of {labels: value}. The form widget infers from the default value type. The dict can be nested, it can contain a subgroup. The value might be a Tag that allows you to add descriptions. If None, the self.env is being used as a form, allowing the user to edit whole configuration.     (Previously fetched from CLI and config file.) A checkbox example: {\"my label\": Tag(True, \"my description\")}
 None title str 
Optional form title
 '' 
Returns:
 Type Description FormDictOrEnv | EnvClass 
dict or dataclass: If the form is null, the output is self.env.
 
If the form is a dict, the output is another dict. Whereas the original form stays intact (with the values update), we return a new raw dict with all values resolved (all Tag objects are resolved to their value).
 
original = {\"my label\": Tag(True, \"my description\")}\noutput = m.form(original)  # Sets the label to False in the dialog\n\n# Original dict was updated\nprint(original[\"my label\"])  # Tag(False, \"my description\")\n\n# Output dict is resolved, contains only raw values\nprint(output[\"my label\"])  # False\n
 
Why this behaviour? You need to do some validation, hence you put Tag objects in the input dict. Then, you just need to work with the values.
 
original = {\"my label\": Tag(True, \"my description\")}\noutput = m.form(original)  # Sets the label to False in the dialog\noutput[\"my_label\"]\n
 
In the case you are willing to re-use the dict, you need not to lose the definitions, hence you end up with accessing via the .val.
 
original = {\"my label\": Tag(True, \"my description\")}\n\nfor i in range(10):\n    m.form(original, f\"Attempt {i}\")\n    print(\"The result\", original[\"my label\"].val)\n
"},{"location":"Mininterface/#mininterface.Mininterface.is_yes","title":"is_yes(text)","text":"
Display confirm box, focusing yes.
 
m = run()\nprint(m.is_yes(\"Is that alright?\"))  # True/False\n
 
"},{"location":"Mininterface/#mininterface.Mininterface.is_no","title":"is_no(text)","text":"
Display confirm box, focusing no.
"},{"location":"Overview/","title":"Overview","text":"
Via the run function you get access to the CLI, possibly enriched from the config file. Then, you receive all data as m.env object and dialog methods in a proper UI.
 
graph LR\n    subgraph mininterface\n        run --> GUI\n        run --> TUI\n        run --> env\n        CLI --> run\n        id1[config file] --> CLI\n    end\n    program --> run\n
"},{"location":"Overview/#basic-usage","title":"Basic usage","text":"
Use a common dataclass, a Pydantic BaseModel or an attrs model to store the configuration. Wrap it to the run function that returns an interface m. Access the configuration via m.env or use it to prompt the user m.is_yes(\"Is that alright?\").
 
To do any advanced things, stick the value to a powerful Tag or its subclassed types. Ex. for a validation only, use its Validation alias.
 
At last, use Facet to tackle the interface from the back-end (m) or the front-end (Tag) side.
"},{"location":"Overview/#supported-types","title":"Supported types","text":"
Various types are supported:
 
     
  • scalars
    •  
  • functions
    •  
  • well-known objects (Path, datetime)
    •  
  • iterables (like list[Path])
    •  
  • custom classes (somewhat)
    •  
  • union types (like int | None)
    •  
 
Take a look how it works with the variables organized in a dataclass:
 
from dataclasses import dataclass\nfrom pathlib import Path\n\nfrom mininterface import run\n\n\n@dataclass\nclass Env:\n    my_number: int = 1\n    \"\"\" A dummy number \"\"\"\n    my_boolean: bool = True\n    \"\"\" A dummy boolean \"\"\"\n    my_conditional_number: int | None = None\n    \"\"\" A number that can be null if left empty \"\"\"\n    my_path: Path = Path(\"/tmp\")\n    \"\"\" A dummy path \"\"\"\n\n\nm = run(Env)  # m.env contains an Env instance\nm.form()  # Prompt a dialog; m.form() without parameter edits m.env\nprint(m.env)\n# Env(my_number=1, my_boolean=True, my_path=PosixPath('/tmp'),\n#  my_point=<__main__.Point object at 0x7ecb5427fdd0>)\n
 
 
Variables organized in a dict:
 
Along scalar types, there is (basic) support for common iterables or custom classes.
 
from mininterface import run\n\nclass Point:\n    def __init__(self, i: int):\n        self.i = i\n\n    def __str__(self):\n        return str(self.i)\n\n\nvalues = {\"my_number\": 1,\n          \"my_list\": [1, 2, 3],\n          \"my_point\": Point(10)\n          }\n\nm = run()\nm.form(values)  # Prompt a dialog\nprint(values)  # {'my_number': 2, 'my_list': [2, 3], 'my_point': <__main__.Point object...>}\nprint(values[\"my_point\"].i)  # 100\n
 
"},{"location":"Overview/#nested-configuration","title":"Nested configuration","text":"
You can easily nest the configuration. (See also Tyro Hierarchical Configs).
 
Just put another dataclass inside the config file:
 
@dataclass\nclass FurtherConfig:\n    token: str\n    host: str = \"example.org\"\n\n@dataclass\nclass Env:\n    further: FurtherConfig\n\n...\nm = run(Env)\nprint(m.env.further.host)  # example.org\n
 
The attributes can by defaulted by CLI:
 
$./program.py --further.host example.net\n
 
And in a YAML config file. Note that you are not obliged to define all the attributes, a subset will do. (Ex. you do not need to specify token too.)
 
further:\n  host: example.com\n
"},{"location":"Overview/#all-possible-interfaces","title":"All possible interfaces","text":"
Normally, you get an interface through mininterface.run but if you do not wish to parse CLI and config file, you can invoke one directly.
 
Several interfaces exist:
 
     
  • Mininterface \u2013 The base interface the others are fully compatible with.
    •  
  • GuiInterface \u2013 A tkinter window.
    •  
  • TuiInterface \u2013 An interactive terminal.
    •  
  • TextualInterface \u2013 If textual installed, rich interface is used.
    •  
  • TextInterface \u2013 Plain text only interface with no dependency as a fallback.
    •  
  • ReplInterface \u2013 A debug terminal. Invokes a breakpoint after every dialog.
    •  
 
How to invoke a specific interface.
 
with TuiInterface(\"My program\") as m:\n    number = m.ask_number(\"Returns number\")\n
"},{"location":"Standalone/","title":"Standalone","text":"
When invoked directly, it creates simple GUI dialogs.
 
$ mininterface  --help\nusage: Mininterface [-h] [OPTIONS]\n\nSimple GUI dialog. Outputs the value the user entered.\n\n\u256d\u2500 options \u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256e\n\u2502 -h, --help              show this help message and exit                                   \u2502\n\u2502 --alert STR             Display the OK dialog with text. (default: '')                    \u2502\n\u2502 --ask STR               Prompt the user to input a text. (default: '')                    \u2502\n\u2502 --ask-number STR        Prompt the user to input a number. Empty input = 0. (default: '') \u2502\n\u2502 --is-yes STR            Display confirm box, focusing yes. (default: '')                  \u2502\n\u2502 --is-no STR             Display confirm box, focusing no. (default: '')                   \u2502\n\u2570\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u256f\n
 
You can fetch a value to i.e. a bash script.
 
$ mininterface  --ask-number \"What's your age?\"  # GUI or TUI window invoked\n18\n
 
 
"},{"location":"Tag/","title":"Tag","text":"
Wrapper around a value that encapsulates a description, validation etc. When you provide a value to an interface, you may instead use this object.
 
Bridge between the input values and a UI widget. The widget is created with the help of this object, then transforms the value back (str to int conversion etc).
"},{"location":"Tag/#mininterface.Tag.val","title":"val: TagValue = None","text":"
The value wrapped by Tag.
 
from mininterface import run, Tag\n\ntag = Tag(True, \"This is my boolean\", bool)\nm = run()\nm.form({\"My boolean\": tag})\nprint(tag.val)  # True/False\nprint()\n
 
 
The encapsulated value is True, tag.description is 'This is my boolean', tag.annotation is bool and 'My boolean' is used as tag.name.
"},{"location":"Tag/#mininterface.Tag.description","title":"description: str = ''","text":"
The description displayed in the UI.
"},{"location":"Tag/#mininterface.Tag.annotation","title":"annotation: type | None = None","text":"
Used for validation (ex. to convert an empty string to None). If not set, will be determined automatically from the val type.
"},{"location":"Tag/#mininterface.Tag.name","title":"name: str | None = None","text":"
Name displayed in the UI.
"},{"location":"Tag/#mininterface.Tag.validation","title":"validation: Callable[[Tag], ValidationResult | tuple[ValidationResult, TagValue]] | None = None","text":"
When the user submits the form, the values are validated (and possibly transformed) with a callback function.     If the validation fails, user is prompted to edit the value.     Return True if validation succeeded or False or an error message when it failed.
 
ValidationResult is a bool or the error message (that implicitly means it has failed).
 
def check(tag: Tag):\n    if tag.val < 10:\n        return \"The value must be at least 10\"\nm.form({\"number\", Tag(12, validation=check)})\n
 
Either use a custom callback function or mininterface.validators.
 
from mininterface.validators import not_empty\nm.form({\"number\", Tag(\"\", validation=not_empty)})\n# User cannot leave the field empty.\n
 
You may use the validation in a type annotation. 
from mininterface import Tag, Validation\n@dataclass\nclass Env:\n    my_text: Annotated[str, Validation(not_empty) = \"will not be emtpy\"\n\n    # which is an alias for:\n    # my_text: Annotated[str, Tag(validation=not_empty)] = \"will not be emtpy\"\n
 
NOTE Undocumented feature, we can return tuple [ValidationResult, FieldValue] to set the self.val.
"},{"location":"Tag/#mininterface.Tag.choices","title":"choices: ChoicesType | None = None","text":"
Print the radio buttons. Constraint the value.
 
from dataclasses import dataclass\nfrom typing import Annotated\nfrom mininterface import run, Choices\n\n@dataclass\nclass Env:\n    foo: Annotated[\"str\", Choices(\"one\", \"two\")] = \"one\"\n\n    # `Choices` is an alias for `Tag(choices=)`\n\nm = run(Env)\nm.form()  # prompts a dialog\n
"},{"location":"Tag/#mininterface.Tag.on_change","title":"on_change: Callable[[Tag], Any] | None = None","text":"
Accepts a callback that launches whenever the value changes (if the validation succeeds). The callback runs while the dialog is still running. The return value of the callback is currently not used.
 
In the following example, we alter the heading title according to the chosen value.
 
from mininterface import run, Tag\n\ndef callback(tag: Tag):\n    tag.facet.set_title(f\"Value changed to {tag.val}\")\n\nm = run()\nm.facet.set_title(\"Click the checkbox\")\nm.form({\n    \"My choice\": Tag(choices=[\"one\", \"two\"], on_change=callback)\n})\n
 
 
"},{"location":"Tag/#mininterface.Tag.facet","title":"facet: Optional[Facet] = None","text":"
Access to the UI facet from the front-end side. (Read Mininterface.facet to access from the back-end side.)
 
Set the UI facet from within a callback, ex. a validator.
 
from mininterface import run, Tag\n\ndef my_check(tag: Tag):\n    tag.facet.set_title(\"My form title\")\n    return \"Validation failed\"\n\nwith run(title='My window title') as m:\n    m.form({\"My form\": Tag(1, validation=my_check)})\n
 
This happens when you click ok.
 
"},{"location":"Tag/#mininterface.Tag.original_val","title":"original_val = None","text":"
Meant to be read only in callbacks. The original value, preceding UI change. Handy while validating.
 
def check(tag.val):\n    if tag.val != tag.original_val:\n        return \"You have to change the value.\"\nm.form({\"number\", Tag(8, validation=check)})\n
"},{"location":"Tag/#mininterface.Tag.update","title":"update","text":"
UI value \u2192 Tag value \u2192 original value. (With type conversion and checks.)
 
Parameters:
 Name Type Description Default ui_value TagValue 
The value as it has been updated in a UI. Update accordingly the value in the original linked dict/object the mininterface was invoked with.
 
Validates the type and do the transformation. (Ex: Some values might be nulled from \"\".)
 required 
Returns:
 Type Description bool 
bool, whether the value is alright or whether the revision is needed.
"},{"location":"Tag/#mininterface.Choices","title":"Choices(*choices)","text":"
An alias, see Tag.choices
"},{"location":"Tag/#helper-types","title":"Helper types","text":""},{"location":"Tag/#mininterface.tag.ValidationResult","title":"ValidationResult = bool | ErrorMessage","text":"
Callback validation result is either boolean or an error message.
"},{"location":"Tag/#mininterface.tag.ErrorMessage","title":"ErrorMessage = TypeVar('ErrorMessage')","text":"
A string, callback validation error message.
"},{"location":"Tag/#mininterface.tag.TagValue","title":"TagValue = TypeVar('TagValue')","text":"
Any value.
"},{"location":"Types/","title":"Types","text":""},{"location":"Types/#mininterface.types.PathTag","title":"PathTag","text":"
Use this helper object to select files.
 
In the following example, we see that it is not always needed to use this object.
 
     
  • File 1 \u2013 plain detection, button to a file picker appeared.
    •  
  • File 2 \u2013 the same.
    •  
  • File 3 \u2013 we specified multiple paths can be selected.
    •  
 
from pathlib import Path\nfrom mininterface import run, Tag\nfrom mininterface.aliases import PathTag\n\nm = run()\nout = m.form({\n    \"File 1\": Path(\"/tmp\"),\n    \"File 2\": Tag(\"\", annotation=Path),\n    \"File 3\": PathTag([Path(\"/tmp\")], multiple=True),\n})\nprint(out)\n# {'File 1': PosixPath('/tmp'), 'File 2': PosixPath('.'), 'File 3': [PosixPath('/tmp')]}\n
 
"},{"location":"Types/#mininterface.types.PathTag.multiple","title":"multiple: str = False","text":"
The user can select multiple files.
"},{"location":"Types/#mininterface.types.Validation","title":"Validation(check)","text":"
Alias to Tag(validation=...)
 
from mininterface import Tag, Validation\n@dataclass\nclass Env:\n    my_text: Annotated[str, Validation(not_empty) = \"will not be emtpy\"\n\n    # which is an alias for:\n    # my_text: Annotated[str, Tag(validation=not_empty)] = \"will not be emtpy\"\n
 
Parameters:
 Name Type Description Default check Callable[[Tag], ValidationResult | tuple[ValidationResult, TagValue]] 
Callback function.
 required"},{"location":"Types/#mininterface.types.Choices","title":"Choices(*choices)","text":"
An alias, see Tag.choices
"},{"location":"Validation/","title":"Validation","text":"
We recommend to use the dataclass and validate with the Annotated keyword. We use a Validation type here.
 
from typing import Annotated\nfrom mininterface.validators import not_empty\nfrom mininterface import Validation\n\n@dataclass\nclass Env:\n    test: Annotated[str, Validation(not_empty)] = \"hello\"\n
 
Under the hood, this is just a Tag.
 
@dataclass\nclass Env:\n    test: Annotated[str, Tag(validation=not_empty)] = \"hello\"\n
 
Why we used it in an Annotated statement? To preserve the date type.
 
@dataclass\nclass Env:\n    my_string: Tag = Tag(\"hello\", validation=not_empty)\n\nm = run(Env)\nprint(type(m.env.my_string))  # Tag\nprint(m.env.my_string.val)  # hello\n
"},{"location":"Validation/#validators","title":"validators","text":"
Functions suitable for Tag validation. When the user submits a value whose validation fails, they are prompted to edit the value.
 
m = run()\nmy_dict = m.form({\"my_text\", Tag(\"\", validation=validators.not_empty)})\nmy_dict[\"my_text\"]  # You can be sure the value is not empty here.\n
 
Note that alternatively to this module, you may validate with Pydantic or an attrs model.
 
from pydantic import BaseModel, Field\n\nclass MyModel(BaseModel):\n    restrained: str = Field(default=\"hello\", max_length=5)\n
 
import attr\nfrom attr.validators import max_len\n\n@attr.s\nclass AttrsModel:\n    restrained: str = attr.ib(default=\"hello\", validator=max_len(5))\n
"},{"location":"Validation/#mininterface.validators.not_empty","title":"not_empty(tag)","text":"
Assures that Tag the user has written a value and did not let the field empty.
 
from mininterface import Tag, validators, run\n\nm = run()\nm.form({\"my_text\": Tag(\"\", validation=validators.not_empty)})\n# User cannot leave the string field empty.\n
 
When submitting an empty value, a warning appears:
 
 
Note that for Path, an empty string is converted to an empty Path('.'), hence '.' too is considered as an empty input and the user is not able to set '.' as a value. This does not seem to me as a bad behaviour as in CLI you clearly see the CWD, whereas in a UI the CWD is not evident.
 
Parameters:
 Name Type Description Default tag Tag required"},{"location":"Validation/#mininterface.validators.limit","title":"limit(maxOrMin=None, max_=None, lt=None, gt=None, transform=False)","text":"
Limit a number range or a string length.
 
Either use as limit(maximum) or limit(minimum, maximum).
 
Parameters:
 Name Type Description Default maximum int 
limit(maximum) \u2013 from zero (including) to maximum (including)
 required minimum int 
limit(minimum, maximum) \u2013 From minimum (including) to maximum (including)
 required lt float | None 
lesser than
 None gt float | None 
greater than
 None transform bool 
If the value is not withing the limit, transform it to a boundary. 
from mininterface import run, Tag\nfrom mininterface.validators import limit\n\nm = run()\nm.form({\"my_number\": Tag(2, validation=limit(1, 10, transform=True))})\n# Put there '50' \u2192 transformed to 10 and dialog reappears\n# with 'Value must be between 1 and 10.'\n
 
 False"},{"location":"run/","title":"Run","text":"
The main access, start here. Wrap your configuration dataclass into run to access the interface. An interface is chosen automatically, with the preference of the graphical one, regressed to a text interface for machines without display. Besides, if given a configuration dataclass, the function enriches it with the CLI commands and possibly with the default from a config file if such exists. It searches the config file in the current working directory, with the program name ending on .yaml, ex: program.py will fetch ./program.yaml.
 
Parameters:
 Name Type Description Default env_class Type[EnvClass] | None 
Dataclass with the configuration. Their values will be modified with the CLI arguments.
 None ask_on_empty_cli bool 
If program was launched with no arguments (empty CLI), invokes self.form() to edit the fields. (Withdrawn when ask_for_missing happens.) 
@dataclass\nclass Env:\nnumber: int = 3\ntext: str = \"\"\nm = run(Env, ask_on_empty=True)\n
 
$ program.py  #  omitting all parameters\n# Dialog for `number` and `text` appears\n$ program.py --number 3\n# No dialog appears\n
 False title str 
The main title. If not set, taken from prog or program name.
 '' config_file Path | str | bool 
File to load YAML to be merged with the configuration. You do not have to re-define all the settings in the config file, you can choose a few. If set to True (default), we try to find one in the current working dir, whose name stem is the same as the program's. Ex: program.py will search for program.yaml. If False, no config file is used.
 True add_verbosity bool 
Adds the verbose flag that automatically sets the level to logging.INFO (-v) or logging.DEBUG (-vv).
 
import logging\nlogger = logging.getLogger(__name__)\n\nm = run(Env, add_verbosity=True)\nlogger.info(\"Info shown\") # needs `-v` or `--verbose`\nlogger.debug(\"Debug not shown\")  # needs `-vv`\n# $ program.py --verbose\n# Info shown\n
 
$ program.py --verbose\nInfo shown\n
 True ask_for_missing bool 
If some required fields are missing at startup, we ask for them in a UI instead of program exit.
 
@dataclass\nclass Env:\n    required_number: int\nm = run(Env, ask_for_missing=True)\n
 
$ program.py  # omitting --required-number\n# Dialog for `required_number` appears\n
 True interface Type[Mininterface] 
Which interface to prefer. By default, we use the GUI, the fallback is the TUI. See the full list of possible interfaces.
 GuiInterface or TuiInterface Kwargs 
The same as for argparse.ArgumentParser.
 
Returns:
 Type Description Mininterface[EnvClass] 
An interface, ready to be used.
 
You cay context manager the function by a with statement. The stdout will be redirected to the interface (ex. a GUI window).
 
with run(Env) as m:\n    print(f\"Your important number is {m.env.important_number}\")\n    boolean = m.is_yes(\"Is that alright?\")\n
 
 
"}]}
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