diff --git a/Changelog/index.html b/Changelog/index.html index 5d7c3ea..a96c8bc 100644 --- a/Changelog/index.html +++ b/Changelog/index.html @@ -641,9 +641,18 @@

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.

-
$ ./hello.py    --help
+
$ ./program.py --help
 usage: My application [-h] [-v] [--my-flag | --no-my-flag] [--my-number INT]
 
 This calculates something.
@@ -711,11 +711,15 @@ 
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.

 
my_number: 555
 

+
$ program.py --help
+...
+│ --my-number INT        This number is very important (default: 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.my_number}")
-    boolean = m.is_yes("Is that alright?")
+
with run(Env) as m:
+    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'
 The same in terminal'

@@ -729,55 +733,55 @@ 
Background

 * Running on a remote machine? Automatic regression to the text interface.

 
Installation

 
Install with a single command from PyPi.

-
pip install mininterface
+
pip install mininterface
 

 
Minimal installation

 
Should you need just the CLI part and you are happy with basic text dialogs, use these commands instead:

-
pip install --no-dependencies mininterface
-pip install tyro typing_extensions pyyaml
+
pip install --no-dependencies mininterface
+pip install tyro typing_extensions pyyaml
 

 
Docs

 
See the docs overview at https://cz-nic.github.io/mininterface/.

 
Examples

-
A powerful m.form dialog method accepts either a dataclass or a dict. Take a look on both.

+
A powerful m.form dialog method accepts either a dataclass or a dict. Take a look on both.

 
A complex dataclass.

-
from typing import Annotated
-from dataclasses import dataclass
-from mininterface.validators import not_empty
-from mininterface import run, Tag, Validation
-
-@dataclass
-class NestedEnv:
-  another_number: int = 7
-  """ This field is nested """
-
-@dataclass
-class Env:
-  nested_config: NestedEnv
-
-  mandatory_str: str
-  """ As there is no default value, you will be prompted automatically to fill up the field """
-
-  my_number: int | None = None
-  """ This is not just a dummy number, if left empty, it is None. """
-
-  my_string: str = "Hello"
-  """ A dummy string """
-
-  my_flag: bool = False
-  """ Checkbox test """
-
-  my_validated: Annotated[str, Validation(not_empty)] = "hello"
-  """ A validated field """
-
-m = run(Env, title="My program")
-# See some values
-print(m.env.nested_config.another_number)  # 7
-print(m.env)
-# Env(nested_config=NestedEnv(another_number=7), my_number=5, my_string='Hello', my_flag=False, my_validated='hello')
-
-# Edit values in a dialog
-m.form()
+
from typing import Annotated
+from dataclasses import dataclass
+from mininterface.validators import not_empty
+from mininterface import run, Tag, Validation
+
+@dataclass
+class NestedEnv:
+  another_number: int = 7
+  """ This field is nested """
+
+@dataclass
+class Env:
+  nested_config: NestedEnv
+
+  mandatory_str: str
+  """ As there is no default value, you will be prompted automatically to fill up the field """
+
+  my_number: int | None = None
+  """ This is not just a dummy number, if left empty, it is None. """
+
+  my_string: str = "Hello"
+  """ A dummy string """
+
+  my_flag: bool = False
+  """ Checkbox test """
+
+  my_validated: Annotated[str, Validation(not_empty)] = "hello"
+  """ A validated field """
+
+m = run(Env, title="My program")
+# See some values
+print(m.env.nested_config.another_number)  # 7
+print(m.env)
+# Env(nested_config=NestedEnv(another_number=7), my_number=5, my_string='Hello', my_flag=False, my_validated='hello')
+
+# Edit values in a dialog
+m.form()
 

 
As the attribute mandatory_str requires a value, a prompt appears automatically:

 
Complex example missing field

@@ -785,17 +789,17 @@ 
A complex dataclass.

 
Complex example

 
Form with paths

 
We have a dict with some paths. Here is how it looks.

-
from pathlib import Path
-from mininterface import run, Tag
-
-m = run(title="My program")
-my_dictionary = {
-  "paths": Tag("", annotation=list[Path]),
-  "default_paths": Tag([Path("/tmp"), Path("/usr")], annotation=list[Path])
-  }
-
-# Edit values in a dialog
-m.form(my_dictionary)
+
from pathlib import Path
+from mininterface import run, Tag
+
+m = run(title="My program")
+my_dictionary = {
+  "paths": Tag("", annotation=list[Path]),
+  "default_paths": Tag([Path("/tmp"), Path("/usr")], annotation=list[Path])
+  }
+
+# Edit values in a dialog
+m.form(my_dictionary)
 

 
List of paths

 
diff --git a/objects.inv b/objects.inv
index c4cce5e..c873901 100644
Binary files a/objects.inv and b/objects.inv differ
diff --git a/run/index.html b/run/index.html
index 55b3dc1..6048933 100644
--- a/run/index.html
+++ b/run/index.html
@@ -863,7 +863,7 @@ 
Run

           
             interface
             
-                  Type[Mininterface] | Literal['gui'] | Literal['tui']
+                  Type[Mininterface] | Literal['gui'] | Literal['tui'] | None
             
             
               

diff --git a/search/search_index.json b/search/search_index.json
index a02a9ab..0c202d8 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    \"\"\" 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    m = run(Env, prog=\"My application\")\n    m.form()\n    # Attributes are suggested by the IDE\n    # along with the hint text 'This number is very important'.\n    print(m.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.
 
$ ./hello.py    --help\nusage: My application [-h] [-v] [--my-flag | --no-my-flag] [--my-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\u2500\u2500\u2500\u2500\u2500\u256e\n\u2502 -h, --help             show this help message and exit                  \u2502\n\u2502 -v, --verbose          Verbosity level. Can be used twice to increase.  \u2502\n\u2502 --my-flag, --no-my-flag                                                 \u2502\n\u2502                        This switches the functionality (default: False) \u2502\n\u2502 --my-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\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":"#minimal-installation","title":"Minimal installation","text":"
Should you need just the CLI part and you are happy with basic text dialogs, use these commands instead:
 
pip install --no-dependencies mininterface\npip install tyro typing_extensions pyyaml\n
"},{"location":"#docs","title":"Docs","text":"
See the docs overview at https://cz-nic.github.io/mininterface/.
"},{"location":"#examples","title":"Examples","text":"
A powerful m.form dialog method accepts either a dataclass or a dict. Take a look on both.
"},{"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 no 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
 
As the attribute mandatory_str requires a value, a prompt appears automatically:
 
 
Then, full form appears:
 
"},{"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":""},{"location":"Changelog/#070","title":"0.7.0","text":"
     
  • hidden --integrate-to-system argument
    •  
  • interfaces migrated to mininterface.interfaces to save around 50 ms starting time due to lazy loading
    •  
  • SubcommandPlaceholder
    •  
"},{"location":"Exceptions/","title":"Exceptions","text":"
Exceptions that might make sense to be used outside the library.
"},{"location":"Exceptions/#mininterface.exceptions.Cancelled","title":"Cancelled","text":"
User has cancelled. A SystemExit based exception noting that the program exits without a traceback, ex. if user hits the escape or closes the window.
"},{"location":"Exceptions/#mininterface.exceptions.ValidationFail","title":"ValidationFail","text":"
Signal to the form that submit failed and we want to restore it.
"},{"location":"Exceptions/#mininterface.exceptions.InterfaceNotAvailable","title":"InterfaceNotAvailable","text":"
Interface failed to init, ex. display not available in GUI. Or the underlying dependency was uninstalled.
"},{"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(_post_submit=None)","text":"
Submits the whole form.
 
```python from mininterface import run, Tag
 
def callback(tag: Tag):     tag.facet.submit()
 
m = run() out = m.form({     \"My choice\": Tag(choices=[\"one\", \"two\"], on_change=callback) })
"},{"location":"Facet/#mininterface.facet.Facet.submit--continue-here-immediately-after-clicking-on-a-radio-button","title":"continue here immediately after clicking on a radio button","text":""},{"location":"Helper-types/","title":"Helper types","text":""},{"location":"Helper-types/#mininterface.tag.ValidationResult","title":"ValidationResult = bool | ErrorMessage","text":"
Callback validation result is either boolean or an error message.
"},{"location":"Helper-types/#mininterface.tag.ErrorMessage","title":"ErrorMessage = TypeVar('ErrorMessage')","text":"
A string, callback validation error message.
"},{"location":"Helper-types/#mininterface.tag.TagValue","title":"TagValue = TypeVar('TagValue', bound=Any)","text":"
Any value. It is being wrapped by a Tag.
"},{"location":"Helper-types/#mininterface.tag.ChoicesType","title":"ChoicesType = list[TagValue] | tuple[TagValue] | set[TagValue] | dict[ChoiceLabel, TagValue] | list[Enum] | Type[Enum]","text":"
You can denote the choices in many ways. Either put options in an iterable or to a dict {labels: value}. Values might be Tags as well.
 
See mininterface.choice or Tag.choices for examples.
"},{"location":"Helper-types/#mininterface.form_dict.DataClass","title":"DataClass = TypeVar('DataClass')","text":"
Any dataclass. Or a pydantic model or attrs.
"},{"location":"Helper-types/#mininterface.form_dict.EnvClass","title":"EnvClass = TypeVar('EnvClass', bound=DataClass)","text":"
Any dataclass. Its instance will be available through [miniterface.env] after CLI parsing.
"},{"location":"Interfaces/","title":"Interfaces","text":""},{"location":"Interfaces/#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 from mininterface.interfaces import *.
 
Apart from the default Mininterface, the base interface the others are fully compatible with, several interfaces exist:
 
How to invoke a specific interface.
 
from mininterface.interfaces import TuiInterface\n\nwith TuiInterface(\"My program\") as m:\n    number = m.ask_number(\"Returns number\")\n
"},{"location":"Interfaces/#guiinterface-tkinterface","title":"GuiInterface = TkInterface","text":"
A tkinter window.
"},{"location":"Interfaces/#tuiinterface","title":"TuiInterface","text":"
An interactive terminal.
"},{"location":"Interfaces/#textualinterface","title":"TextualInterface","text":"
If textual installed, rich and mouse clickable interface is used.
"},{"location":"Interfaces/#textinterface","title":"TextInterface","text":"
Plain text only interface with no dependency as a fallback.
"},{"location":"Interfaces/#replinterface","title":"ReplInterface","text":"
A debug terminal. Invokes a breakpoint after every dialog.
"},{"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(None, self.env)","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
 
 
Alternatively, you may use an Enum.
 
class Color(Enum):\n    RED = \"red\"\n    GREEN = \"green\"\n    BLUE = \"blue\"\n\nm.choice(Color)\n
 
 
Alternatively, you may use an Enum instance.
 
class Color(Enum):\n    RED = \"red\"\n    GREEN = \"green\"\n    BLUE = \"blue\"\n\nm.choice(Color.BLUE)\n
 
 
Alternatively, you may use an Enum instances list.
 
m.choice([Color.GREEN, Color.BLUE])\n
 
 required title str 
Form title
 '' default str | TagValue | 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 and return its return value.
 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.
 
Info
 
To tackle a more detailed form, see Tag.choices.
"},{"location":"Mininterface/#mininterface.Mininterface.form","title":"form(form=None, title='', *, submit=True)","text":"
Prompt the user to fill up an arbitrary form.
 
Use scalars, enums, enum instances, objects like datetime, Paths or their list.
 
from enum import Enum\nfrom mininterface import run, Tag\n\nclass Color(Enum):\n    RED = \"red\"\n    GREEN = \"green\"\n    BLUE = \"blue\"\n\nm = run()\nout = m.form({\n    \"my_number\": 1,\n    \"my_boolean\": True,\n    \"my_enum\": Color,\n    \"my_tagged\": Tag(\"\", name='Tagged value', description='Long hint'),\n    \"my_path\": Path(\"/tmp\"),\n    \"my_paths\": [Path(\"/tmp\")],\n    \"My enum with default\": Color.BLUE\n})\n
 
 
Parameters:
 Name Type Description Default form DataClass | Type[DataClass] | FormDict | None 
We accept a dataclass type, a dataclass instance, a dict or None.
 
     
  • If dict, we expect a 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.
    •  
 
A checkbox example: {\"my label\": Tag(True, \"my description\")}
 
     
  • 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.)
    •  
 None title str 
Optional form title
 '' submit str | bool 
Set the submit button text (by default 'Ok') or hide it with False.
 True 
Returns:
 Name Type Description dataclass FormDict | DataClass | EnvClass 
If the form is null, the output is self.env.
 dataclass FormDict | DataClass | EnvClass 
If the form is a dataclass type or a dataclass instance, the output is the dataclass instance.
 dict FormDict | DataClass | EnvClass 
If the form is a dict, the output is another dict.
 
Whereas the original dict stays intact (with the values updated), 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?\").
 
There are a lot of supported types you can use, not only scalars and well-known objects (Path, datetime), but also functions, iterables (like list[Path]) and union types (like int | None). To do even more advanced things, stick the value to a powerful Tag or its subclasses. 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/#ide-suggestions","title":"IDE suggestions","text":"
The immediate benefit is the type suggestions you see in an IDE. Imagine following code:
 
from dataclasses import dataclass\nfrom mininterface import run\n\n@dataclass\nclass Env:\n    my_paths: list[Path]\n    \"\"\" The user is forced to input Paths. \"\"\"\n\n\n@dataclass\nclass Dialog:\n    my_number: int = 2\n    \"\"\" A number \"\"\"\n
 
Now, accessing the main env will trigger the hint. 
 
Calling the form with an empty parameter will trigger editing the main env
 
 
Putting there a dict will return the dict too.
 
 
Putting there a dataclass type causes it to be resolved.
 
 
Should you have a resolved dataclass instance, put it there.
 
 
As you see, its attributes are hinted alongside their description.
 
 
Should the dataclass cannot be easily investigated by the IDE (i.e. a required field), just annotate the output.
 
"},{"location":"Overview/#bash-completion","title":"Bash completion","text":"
Run your program with a hidden --integrate-to-system flag and a tutorial will install bash completion.
 
"},{"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":"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":"Subcommands/","title":"Subcommands","text":"
Dealing with CLI subcommands, from mininterface.subcommands import *
"},{"location":"Subcommands/#mininterface.subcommands.Command","title":"Command","text":"
The Command is automatically run while instantanied.
 
Experimental \u2013 how should it receive _facet?
 
Put list of Commands to the mininterface.run and divide your application into different sections. Alternative to argparse subcommands.
 
Commands might inherit from the same parent to share the common attributes.
"},{"location":"Subcommands/#mininterface.subcommands.Command--subcommandplaceholder","title":"SubcommandPlaceholder","text":"
What if I need to use my program Special placeholder class SubcommandPlaceholder. This special class let the user to choose the subcommands via UI, while still benefiniting from default CLI arguments.
"},{"location":"Subcommands/#mininterface.subcommands.Command--the-cli-behaviour","title":"The CLI behaviour:","text":"
     
  • ./program.py -> UI started with subcommand choice
    •  
  • ./program.py subcommand --flag -> special class SubcommandPlaceholder allows defining a common --flag     while still starting UI with subcommand choice
    •  
  • ./program.py subcommand1 --flag -> program run
    •  
  • ./program.py subcommand1 -> fails to CLI for now
    •  
"},{"location":"Subcommands/#mininterface.subcommands.Command--an-example-of-command-usage","title":"An example of Command usage","text":"
from dataclasses import dataclass, field\nfrom pathlib import Path\nfrom mininterface import run\nfrom mininterface.exceptions import ValidationFail\nfrom mininterface.subcommands import Command, SubcommandPlaceholder\nfrom tyro.conf import Positional\n\n\n@dataclass\nclass SharedArgs(Command):\n    common: int\n    files: Positional[list[Path]] = field(default_factory=list)\n\n    def init(self):\n        self.internal = \"value\"\n\n\n@dataclass\nclass Subcommand1(SharedArgs):\n    my_local: int = 1\n\n    def run(self):\n        print(\"Common:\", self.common)  # user input\n        print(\"Number:\", self.my_local)  # 1 or user input\n        print(\"Internal:\", self.internal)\n        raise ValidationFail(\"The submit button blocked!\")\n\n\n@dataclass\nclass Subcommand2(SharedArgs):\n    def run(self):\n        self._facet.set_title(\"Button clicked\")  # you can access internal self._facet: Facet\n        print(\"Common files\", self.files)\n\n\nm = run([Subcommand1, Subcommand2, SubcommandPlaceholder])\nm.alert(\"App continue\")\n
 
Let's start the program, passing there common flags, all HTML files in a folder and setting --common to 7. 
$ program.py  subcommand *.html  --common 7\n
 
 
As you see, thanks to SubcommandPlaceholder, subcommand was not chosen yet. Click to the first button.
 
 
and the terminal got:
 
Common: 7\nNumber: 1\nInternal: value\n
 
Click to the second button.
 
 
Terminal output: 
Common files [PosixPath('page1.html'), PosixPath('page2.html')]\n
"},{"location":"Subcommands/#mininterface.subcommands.Command--powerful-automation","title":"Powerful automation","text":"
Note we use from tyro.conf import Positional to denote the positional argument. We did not have to write --files to put there HTML files.
"},{"location":"Subcommands/#mininterface.subcommands.Command.init","title":"init()","text":"
Just before the form appears. As the __post_init__ method is not guaranteed to run just once (internal CLI behaviour), you are welcome to override this method instead. You can use self._facet from within.
"},{"location":"Subcommands/#mininterface.subcommands.Command.run","title":"run()","text":"
This method is run automatically in CLI or by a button button it generates in a UI.
"},{"location":"Subcommands/#mininterface.subcommands.SubcommandPlaceholder","title":"SubcommandPlaceholder","text":"
Use this placeholder to choose the subcomannd via a UI.
"},{"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. It can be any value.
 
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.
 
Tip
 
If the Tag is nested, the info is fetched to the outer Tag. When updated, the inner Tag value updates accordingly.
 
tag = Tag(Tag(True))\n
"},{"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 / select box. 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    # `Choices` is an alias for `Tag(choices=)`\n\nm = run(Env)\nm.form()  # prompts a dialog\n
 
 
Info
 
When dealing with a simple use case, use the mininterface.choice dialog.
"},{"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.set_val","title":"set_val","text":"
Sets the value without any checks.
"},{"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":"Types/","title":"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":"Types/#mininterface.types.CallbackTag","title":"CallbackTag","text":"
Callback function is guaranteed to receives the Tag as a parameter.
 
Warning
 
Experimental. May change.
 
For the following examples, we will use these custom callback functions: 
from mininterface import run\n\ndef callback_raw():\n    \"\"\" Dummy function \"\"\"\n    print(\"Priting text\")\n    return 50\n\ndef callback_tag(tag: Tag):\n    \"\"\" Receives a tag \"\"\"\n    print(\"Printing\", type(tag))\n    return 100\n\nm = run()\n
 
Use as buttons in a form: 
m.form({\"Button\": callback_raw})\nm.form({\"Button\": CallbackTag(callback_tag)})\n
 
 
Via form, we receive the function handler: 
out = m.form({\n    \"My choice\": Tag(choices=[callback_raw, CallbackTag(callback_tag)])\n})\nprint(out)  # {'My choice': <function callback_raw at 0x7ae5b3e74ea0>}\n
 
Via choice, we receive the function output:
 
out = m.choice({\n    \"My choice1\": callback_raw,\n    \"My choice2\": CallbackTag(callback_tag),\n    # Not supported: \"My choice3\": Tag(callback_tag, annotation=CallbackTag),\n})\nprint(out)  # output of callback0 or callback_tag, ex:\n#    Printing <class 'mininterface.types.CallbackTag'>\n#    100\n
 
 
You may use callback in a dataclass. 
@dataclass\nclass Callbacks:\n    p1: Callable = callback0\n    p2: Annotated[Callable, CallbackTag(description=\"Foo\")] = callback_tag\n    # Not supported: p3: CallbackTag = callback_tag\n    # Not supported: p4: CallbackTag = field(default_factory=CallbackTag(callback_tag))\n    # Not supported: p5: Annotated[Callable, Tag(description=\"Bar\", annotation=CallbackTag)] = callback_tag\n\nm = run(Callbacks)\nm.form()\n
"},{"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 within 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_or_list Type[EnvClass] | list[Type[Command]] | None 
     
  • dataclass Dataclass with the configuration. Their values will be modified with the CLI arguments.
    •  
  • list of Commands let you create multiple commands within a single program, each with unique options.
    •  
  • None You need just the dialogs, no CLI/config file parsing.
    •  
 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] | Literal['gui'] | Literal['tui'] 
Which interface to prefer. By default, we use the GUI, the fallback is the TUI. You may write \"gui\" or \"tui\" literal or pass a specific Mininterface type, see the full list of possible interfaces.
 None args Optional[Sequence[str]] 
Parse arguments from a sequence instead of the command line.
 None 
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).
 
from dataclasses import dataclass\nfrom mininterface import run\n\n@dataclass\nclass Env:\n    my_number: int = 4\n\nwith run(Env) as m:\n    print(f\"Your important number is {m.env.my_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    m = run(Env, prog=\"My application\")\n    m.form()\n    # Attributes are suggested by the IDE\n    # along with the hint text 'This number is very important'.\n    print(m.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.
 
$ ./program.py --help\nusage: My application [-h] [-v] [--my-flag | --no-my-flag] [--my-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\u2500\u2500\u2500\u2500\u2500\u256e\n\u2502 -h, --help             show this help message and exit                  \u2502\n\u2502 -v, --verbose          Verbosity level. Can be used twice to increase.  \u2502\n\u2502 --my-flag, --no-my-flag                                                 \u2502\n\u2502                        This switches the functionality (default: False) \u2502\n\u2502 --my-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\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
 
$ program.py --help\n...\n\u2502 --my-number INT        This number is very important (default: 555)     \u2502\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":"#minimal-installation","title":"Minimal installation","text":"
Should you need just the CLI part and you are happy with basic text dialogs, use these commands instead:
 
pip install --no-dependencies mininterface\npip install tyro typing_extensions pyyaml\n
"},{"location":"#docs","title":"Docs","text":"
See the docs overview at https://cz-nic.github.io/mininterface/.
"},{"location":"#examples","title":"Examples","text":"
A powerful m.form dialog method accepts either a dataclass or a dict. Take a look on both.
"},{"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 no 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
 
As the attribute mandatory_str requires a value, a prompt appears automatically:
 
 
Then, full form appears:
 
"},{"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":""},{"location":"Changelog/#071-2024-11-27","title":"0.7.1 (2024-11-27)","text":"
     
  • GUI scrollbars if window is bigger than the screen
    •  
  • non-interactive session support
    •  
  • datetime support
    •  
  • nested generics support (a tuple in a list)
    •  
"},{"location":"Changelog/#070-2024-11-08","title":"0.7.0 (2024-11-08)","text":"
     
  • hidden --integrate-to-system argument
    •  
  • interfaces migrated to mininterface.interfaces to save around 50 ms starting time due to lazy loading
    •  
  • SubcommandPlaceholder
    •  
"},{"location":"Exceptions/","title":"Exceptions","text":"
Exceptions that might make sense to be used outside the library.
"},{"location":"Exceptions/#mininterface.exceptions.Cancelled","title":"Cancelled","text":"
User has cancelled. A SystemExit based exception noting that the program exits without a traceback, ex. if user hits the escape or closes the window.
"},{"location":"Exceptions/#mininterface.exceptions.ValidationFail","title":"ValidationFail","text":"
Signal to the form that submit failed and we want to restore it.
"},{"location":"Exceptions/#mininterface.exceptions.InterfaceNotAvailable","title":"InterfaceNotAvailable","text":"
Interface failed to init, ex. display not available in GUI. Or the underlying dependency was uninstalled.
"},{"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(_post_submit=None)","text":"
Submits the whole form.
 
```python from mininterface import run, Tag
 
def callback(tag: Tag):     tag.facet.submit()
 
m = run() out = m.form({     \"My choice\": Tag(choices=[\"one\", \"two\"], on_change=callback) })
"},{"location":"Facet/#mininterface.facet.Facet.submit--continue-here-immediately-after-clicking-on-a-radio-button","title":"continue here immediately after clicking on a radio button","text":""},{"location":"Helper-types/","title":"Helper types","text":""},{"location":"Helper-types/#mininterface.tag.ValidationResult","title":"ValidationResult = bool | ErrorMessage","text":"
Callback validation result is either boolean or an error message.
"},{"location":"Helper-types/#mininterface.tag.ErrorMessage","title":"ErrorMessage = TypeVar('ErrorMessage')","text":"
A string, callback validation error message.
"},{"location":"Helper-types/#mininterface.tag.TagValue","title":"TagValue = TypeVar('TagValue', bound=Any)","text":"
Any value. It is being wrapped by a Tag.
"},{"location":"Helper-types/#mininterface.tag.ChoicesType","title":"ChoicesType = list[TagValue] | tuple[TagValue] | set[TagValue] | dict[ChoiceLabel, TagValue] | list[Enum] | Type[Enum]","text":"
You can denote the choices in many ways. Either put options in an iterable or to a dict {labels: value}. Values might be Tags as well.
 
See mininterface.choice or Tag.choices for examples.
"},{"location":"Helper-types/#mininterface.form_dict.DataClass","title":"DataClass = TypeVar('DataClass')","text":"
Any dataclass. Or a pydantic model or attrs.
"},{"location":"Helper-types/#mininterface.form_dict.EnvClass","title":"EnvClass = TypeVar('EnvClass', bound=DataClass)","text":"
Any dataclass. Its instance will be available through [miniterface.env] after CLI parsing.
"},{"location":"Interfaces/","title":"Interfaces","text":""},{"location":"Interfaces/#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 from mininterface.interfaces import *.
 
Apart from the default Mininterface, the base interface the others are fully compatible with, several interfaces exist:
 
How to invoke a specific interface.
 
from mininterface.interfaces import TuiInterface\n\nwith TuiInterface(\"My program\") as m:\n    number = m.ask_number(\"Returns number\")\n
"},{"location":"Interfaces/#guiinterface-tkinterface","title":"GuiInterface = TkInterface","text":"
A tkinter window.
"},{"location":"Interfaces/#tuiinterface","title":"TuiInterface","text":"
An interactive terminal.
"},{"location":"Interfaces/#textualinterface","title":"TextualInterface","text":"
If textual installed, rich and mouse clickable interface is used.
"},{"location":"Interfaces/#textinterface","title":"TextInterface","text":"
Plain text only interface with no dependency as a fallback.
 
When used in a with statement, the non-interactive session becomes interactive if possible, see the Mininterface enter method.
"},{"location":"Interfaces/#replinterface","title":"ReplInterface","text":"
A debug terminal. Invokes a breakpoint after every dialog.
"},{"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(None, self.env)","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":"
Usage within the with statement makes the program to attempt for the following benefits:
"},{"location":"Mininterface/#mininterface.Mininterface.__enter__--continual-window","title":"Continual window","text":"
Do not vanish between dialogs (the GUI window stays the same)
"},{"location":"Mininterface/#mininterface.Mininterface.__enter__--stdout-redirection","title":"Stdout redirection","text":"
Redirects the stdout to a text area instead of a terminal.
 
from mininterface import run\n\nwith run() as m:\n    print(\"This is a printed text\")\n    m.alert(\"Alert text\")\n
 
"},{"location":"Mininterface/#mininterface.Mininterface.__enter__--make-the-session-interactive","title":"Make the session interactive","text":"
If run from an interactive terminal or if a GUI is used, nothing special happens.
 
# $ ./program.py\nwith run() as m:\n    m.ask_number(\"What number\")\n
 
 
However, when run in a non-interactive session with TUI (ex. no display), TextInterface is used which is able to turn it into an interactive one.
 
piped_in = int(sys.stdin.read())\n\nwith run(interface=\"tui\") as m:\n    result = m.ask_number(\"What number\") + piped_in\nprint(result)\n
 
$ echo 2 | ./program.py\nWhat number: 3\n5\n
 
If the with statement is not used, the result is the same as if an interactive session is not available, like in a cron job. In that case, plain Mininterface is used.
 
piped_in = int(sys.stdin.read())\n\nm = run(interface=\"tui\")\nresult = m.ask_number(\"What number\") + piped_in\nprint(result)\n
 
echo 2 | ./program.py\nAsking: What number\n3\n
"},{"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
 
 
Alternatively, you may use an Enum.
 
class Color(Enum):\n    RED = \"red\"\n    GREEN = \"green\"\n    BLUE = \"blue\"\n\nm.choice(Color)\n
 
 
Alternatively, you may use an Enum instance.
 
class Color(Enum):\n    RED = \"red\"\n    GREEN = \"green\"\n    BLUE = \"blue\"\n\nm.choice(Color.BLUE)\n
 
 
Alternatively, you may use an Enum instances list.
 
m.choice([Color.GREEN, Color.BLUE])\n
 
 required title str 
Form title
 '' default str | TagValue | 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 and return its return value.
 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.
 
Info
 
To tackle a more detailed form, see Tag.choices.
"},{"location":"Mininterface/#mininterface.Mininterface.form","title":"form(form=None, title='', *, submit=True)","text":"
Prompt the user to fill up an arbitrary form.
 
Use scalars, enums, enum instances, objects like datetime, Paths or their list.
 
from enum import Enum\nfrom mininterface import run, Tag\n\nclass Color(Enum):\n    RED = \"red\"\n    GREEN = \"green\"\n    BLUE = \"blue\"\n\nm = run()\nout = m.form({\n    \"my_number\": 1,\n    \"my_boolean\": True,\n    \"my_enum\": Color,\n    \"my_tagged\": Tag(\"\", name='Tagged value', description='Long hint'),\n    \"my_path\": Path(\"/tmp\"),\n    \"my_paths\": [Path(\"/tmp\")],\n    \"My enum with default\": Color.BLUE\n})\n
 
 
Parameters:
 Name Type Description Default form DataClass | Type[DataClass] | FormDict | None 
We accept a dataclass type, a dataclass instance, a dict or None.
 
     
  • If dict, we expect a 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.
    •  
 
A checkbox example: {\"my label\": Tag(True, \"my description\")}
 
     
  • 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.)
    •  
 None title str 
Optional form title
 '' submit str | bool 
Set the submit button text (by default 'Ok') or hide it with False.
 True 
Returns:
 Name Type Description dataclass FormDict | DataClass | EnvClass 
If the form is null, the output is self.env.
 dataclass FormDict | DataClass | EnvClass 
If the form is a dataclass type or a dataclass instance, the output is the dataclass instance.
 dict FormDict | DataClass | EnvClass 
If the form is a dict, the output is another dict.
 
Whereas the original dict stays intact (with the values updated), 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?\").
 
There are a lot of supported types you can use, not only scalars and well-known objects (Path, datetime), but also functions, iterables (like list[Path]) and union types (like int | None). To do even more advanced things, stick the value to a powerful Tag or its subclasses. 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/#ide-suggestions","title":"IDE suggestions","text":"
The immediate benefit is the type suggestions you see in an IDE. Imagine following code:
 
from dataclasses import dataclass\nfrom mininterface import run\n\n@dataclass\nclass Env:\n    my_paths: list[Path]\n    \"\"\" The user is forced to input Paths. \"\"\"\n\n\n@dataclass\nclass Dialog:\n    my_number: int = 2\n    \"\"\" A number \"\"\"\n
 
Now, accessing the main env will trigger the hint. 
 
Calling the form with an empty parameter will trigger editing the main env
 
 
Putting there a dict will return the dict too.
 
 
Putting there a dataclass type causes it to be resolved.
 
 
Should you have a resolved dataclass instance, put it there.
 
 
As you see, its attributes are hinted alongside their description.
 
 
Should the dataclass cannot be easily investigated by the IDE (i.e. a required field), just annotate the output.
 
"},{"location":"Overview/#bash-completion","title":"Bash completion","text":"
Run your program with a hidden --integrate-to-system flag and a tutorial will install bash completion.
 
"},{"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":"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":"Subcommands/","title":"Subcommands","text":"
Dealing with CLI subcommands, from mininterface.subcommands import *
"},{"location":"Subcommands/#mininterface.subcommands.Command","title":"Command","text":"
The Command is automatically run while instantanied.
 
Experimental \u2013 how should it receive _facet?
 
Put list of Commands to the mininterface.run and divide your application into different sections. Alternative to argparse subcommands.
 
Commands might inherit from the same parent to share the common attributes.
"},{"location":"Subcommands/#mininterface.subcommands.Command--subcommandplaceholder","title":"SubcommandPlaceholder","text":"
What if I need to use my program Special placeholder class SubcommandPlaceholder. This special class let the user to choose the subcommands via UI, while still benefiniting from default CLI arguments.
"},{"location":"Subcommands/#mininterface.subcommands.Command--the-cli-behaviour","title":"The CLI behaviour:","text":"
     
  • ./program.py -> UI started with subcommand choice
    •  
  • ./program.py subcommand --flag -> special class SubcommandPlaceholder allows defining a common --flag     while still starting UI with subcommand choice
    •  
  • ./program.py subcommand1 --flag -> program run
    •  
  • ./program.py subcommand1 -> fails to CLI for now
    •  
"},{"location":"Subcommands/#mininterface.subcommands.Command--an-example-of-command-usage","title":"An example of Command usage","text":"
from dataclasses import dataclass, field\nfrom pathlib import Path\nfrom mininterface import run\nfrom mininterface.exceptions import ValidationFail\nfrom mininterface.subcommands import Command, SubcommandPlaceholder\nfrom tyro.conf import Positional\n\n\n@dataclass\nclass SharedArgs(Command):\n    common: int\n    files: Positional[list[Path]] = field(default_factory=list)\n\n    def init(self):\n        self.internal = \"value\"\n\n\n@dataclass\nclass Subcommand1(SharedArgs):\n    my_local: int = 1\n\n    def run(self):\n        print(\"Common:\", self.common)  # user input\n        print(\"Number:\", self.my_local)  # 1 or user input\n        print(\"Internal:\", self.internal)\n        raise ValidationFail(\"The submit button blocked!\")\n\n\n@dataclass\nclass Subcommand2(SharedArgs):\n    def run(self):\n        self._facet.set_title(\"Button clicked\")  # you can access internal self._facet: Facet\n        print(\"Common files\", self.files)\n\n\nm = run([Subcommand1, Subcommand2, SubcommandPlaceholder])\nm.alert(\"App continue\")\n
 
Let's start the program, passing there common flags, all HTML files in a folder and setting --common to 7. 
$ program.py  subcommand *.html  --common 7\n
 
 
As you see, thanks to SubcommandPlaceholder, subcommand was not chosen yet. Click to the first button.
 
 
and the terminal got:
 
Common: 7\nNumber: 1\nInternal: value\n
 
Click to the second button.
 
 
Terminal output: 
Common files [PosixPath('page1.html'), PosixPath('page2.html')]\n
"},{"location":"Subcommands/#mininterface.subcommands.Command--powerful-automation","title":"Powerful automation","text":"
Note we use from tyro.conf import Positional to denote the positional argument. We did not have to write --files to put there HTML files.
"},{"location":"Subcommands/#mininterface.subcommands.Command.init","title":"init()","text":"
Just before the form appears. As the __post_init__ method is not guaranteed to run just once (internal CLI behaviour), you are welcome to override this method instead. You can use self._facet from within.
"},{"location":"Subcommands/#mininterface.subcommands.Command.run","title":"run()","text":"
This method is run automatically in CLI or by a button button it generates in a UI.
"},{"location":"Subcommands/#mininterface.subcommands.SubcommandPlaceholder","title":"SubcommandPlaceholder","text":"
Use this placeholder to choose the subcomannd via a UI.
"},{"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. It can be any value.
 
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.
 
Tip
 
If the Tag is nested, the info is fetched to the outer Tag. When updated, the inner Tag value updates accordingly.
 
tag = Tag(Tag(True))\n
"},{"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 / select box. 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    # `Choices` is an alias for `Tag(choices=)`\n\nm = run(Env)\nm.form()  # prompts a dialog\n
 
 
Info
 
When dealing with a simple use case, use the mininterface.choice dialog.
"},{"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.set_val","title":"set_val","text":"
Sets the value without any checks.
"},{"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":"Types/","title":"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":"Types/#mininterface.types.CallbackTag","title":"CallbackTag","text":"
Callback function is guaranteed to receives the Tag as a parameter.
 
Warning
 
Experimental. May change.
 
For the following examples, we will use these custom callback functions: 
from mininterface import run\n\ndef callback_raw():\n    \"\"\" Dummy function \"\"\"\n    print(\"Priting text\")\n    return 50\n\ndef callback_tag(tag: Tag):\n    \"\"\" Receives a tag \"\"\"\n    print(\"Printing\", type(tag))\n    return 100\n\nm = run()\n
 
Use as buttons in a form: 
m.form({\"Button\": callback_raw})\nm.form({\"Button\": CallbackTag(callback_tag)})\n
 
 
Via form, we receive the function handler: 
out = m.form({\n    \"My choice\": Tag(choices=[callback_raw, CallbackTag(callback_tag)])\n})\nprint(out)  # {'My choice': <function callback_raw at 0x7ae5b3e74ea0>}\n
 
Via choice, we receive the function output:
 
out = m.choice({\n    \"My choice1\": callback_raw,\n    \"My choice2\": CallbackTag(callback_tag),\n    # Not supported: \"My choice3\": Tag(callback_tag, annotation=CallbackTag),\n})\nprint(out)  # output of callback0 or callback_tag, ex:\n#    Printing <class 'mininterface.types.CallbackTag'>\n#    100\n
 
 
You may use callback in a dataclass. 
@dataclass\nclass Callbacks:\n    p1: Callable = callback0\n    p2: Annotated[Callable, CallbackTag(description=\"Foo\")] = callback_tag\n    # Not supported: p3: CallbackTag = callback_tag\n    # Not supported: p4: CallbackTag = field(default_factory=CallbackTag(callback_tag))\n    # Not supported: p5: Annotated[Callable, Tag(description=\"Bar\", annotation=CallbackTag)] = callback_tag\n\nm = run(Callbacks)\nm.form()\n
"},{"location":"Types/#mininterface.types.PathTag","title":"PathTag","text":"
Contains a Path or their list. 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: bool = False","text":"
The user can select multiple files.
"},{"location":"Types/#mininterface.types.DatetimeTag","title":"DatetimeTag","text":"
Warning
 
Experimental. Still in development.
 
Datetime is supported.
 
from datetime import datetime\nfrom dataclasses import dataclass\nfrom mininterface import run\n\n@dataclass\nclass Env:\n    my_date: datetime\n\nm = run(Env)\n
 
The arrows change the day (or the datetime part the keyboard caret is currently editing).
 
 
In this code, we want only the date part.
 
from datetime import date\nfrom dataclasses import dataclass\nfrom mininterface import run\n\n@dataclass\nclass Env:\n    my_date: date\n\nm = run(Env)\n
 
After clicking the button (or hitting Ctrl+Shift+C), a calendar appear.
 
"},{"location":"Types/#mininterface.types.DatetimeTag.date","title":"date: bool = False","text":"
The date part is active
"},{"location":"Types/#mininterface.types.DatetimeTag.time","title":"time: bool = False","text":"
The time part is active
"},{"location":"Types/#mininterface.types.DatetimeTag.full_precision","title":"full_precision: Optional[bool] = None","text":"
Include full time precison, seconds, microseconds.
"},{"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 within 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_or_list Type[EnvClass] | list[Type[Command]] | None 
     
  • dataclass Dataclass with the configuration. Their values will be modified with the CLI arguments.
    •  
  • list of Commands let you create multiple commands within a single program, each with unique options.
    •  
  • None You need just the dialogs, no CLI/config file parsing.
    •  
 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] | Literal['gui'] | Literal['tui'] | None 
Which interface to prefer. By default, we use the GUI, the fallback is the TUI. You may write \"gui\" or \"tui\" literal or pass a specific Mininterface type, see the full list of possible interfaces.
 None args Optional[Sequence[str]] 
Parse arguments from a sequence instead of the command line.
 None 
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).
 
from dataclasses import dataclass\nfrom mininterface import run\n\n@dataclass\nclass Env:\n    my_number: int = 4\n\nwith run(Env) as m:\n    print(f\"Your important number is {m.env.my_number}\")\n    boolean = m.is_yes(\"Is that alright?\")\n
 
 
"}]}
\ No newline at end of file
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