Generating interfaces(CLI, Qt GUI, Dash web app) from a Python function.

Overview

oneFace is a Python library for automatically generating multiple interfaces(CLI, GUI, WebGUI) from a callable Python object.

Build Status codecov Documentation Install with PyPi

oneFace is an easy way to create interfaces in Python, just decorate your function and mark the type and range of the arguments:

from oneface import one, Arg

@one
def bmi(name: Arg(str),
        height: Arg(float, [100, 250]) = 160,
        weight: Arg(float, [0, 300]) = 50.0):
    BMI = weight / (height / 100) ** 2
    print(f"Hi {name}. Your BMI is: {BMI}")
    return BMI


# run cli
bmi.cli()
# or run qt_gui
bmi.qt_gui()
# or run dash web app
bmi.dash_app()

These code will generate the following interfaces:

CLI Qt Dash
CLI Qt Dash

Features

  • Generate CLI, Qt GUI, Dash Web app from a python function.
  • Automatically check the type and range of input parameters and pretty print them.
  • Easy extension of parameter types and GUI widgets.

Detail usage see the documentation and pythondig.

Installation

To install oneFace with complete dependency:

$ pip install oneface[all]

Or install with just qt or dash dependency:

$ pip install oneface[qt]  # qt
$ pip install oneface[dash]  # dash
Comments
  • Wrap CLI

    Wrap CLI

    Wrap a CLI program to a GUI/Web interface app.

    Using a .yaml as config to specify the arguments:

    # open_browser_oneface.yaml
    name: open_browser
    
    command: python -m webbrowser {is_tab} {url} 
    
    arguments:
    
      is_tab:
        type: bool
        true_content: "-t"
        false_content: ""
    
      url:
        type: str
    

    Launch the app with:

    $ python -m onface.wrap_cli run open_browser_oneface.yaml qt_gui
    

    It will get a GUI app.

    enhancement 
    opened by Nanguage 1
  • A Thanks Message

    A Thanks Message

    Hello, i am Onur, i am a CTO of a community that develop Blockchain based Decentralized Application Network. This repository have a very good idea. All contributor of this project and me should develop this project and use in the other project. Let's not stop developing.

    Onur Atakan ULUSOY - CTO of Decentra Network Community

    opened by onuratakan 1
  • Implicit Arg convert from Python builtin types

    Implicit Arg convert from Python builtin types

    Allow type annotation with python builtin types, for example:

    from oneface import one, Arg
    
    @one
    def bmi(name: str,
            height: (float, [100, 250]) = 160,
            weight: (float, [0, 300]) = 50.0):
        BMI = weight / (height / 100) ** 2
        print(f"Hi {name}. Your BMI is: {BMI}")
        return BMI
    
    # run cli
    bmi.cli()
    

    Let the annotation automatically convert to Arg when parse the parameters.

    enhancement 
    opened by Nanguage 1
  • Integrate generated qt window to a Qt app.

    Integrate generated qt window to a Qt app.

    import sys
    from oneface.qt import qt_window
    from oneface import one
    from qtpy import QtWidgets
    
    app = QtWidgets.QApplication([])
    
    
    @qt_window
    @one
    def add(a: int, b: int):
        return a + b
    
    @qt_window
    @one
    def mul(a: int, b: int):
        return a * b
    
    
    main_window = QtWidgets.QWidget()
    main_window.setWindowTitle("MyApp")
    main_window.setFixedSize(200, 100)
    layout = QtWidgets.QVBoxLayout(main_window)
    layout.addWidget(QtWidgets.QLabel("Apps:"))
    btn_open_add = QtWidgets.QPushButton("add")
    btn_open_mul = QtWidgets.QPushButton("mul")
    btn_open_add.clicked.connect(add.show)
    btn_open_mul.clicked.connect(mul.show)
    layout.addWidget(btn_open_add)
    layout.addWidget(btn_open_mul)
    main_window.show()
    
    sys.exit(app.exec())
    
    enhancement 
    opened by Nanguage 0
  • Dash: the 'plotly' result_result_type

    Dash: the 'plotly' result_result_type

    Allow render the result with ploty. The wraped function return a plotly figure object:

    from oneface import one, Arg
    import plotly.express as px
    import numpy as np
    
    @one
    def draw_random_points(n: Arg[int, [1, 10000]] = 100):
        x, y = np.random.random(n), np.random.random(n)
        fig = px.scatter(x=x, y=y)
        return fig
    
    draw_random_points.dash_app(
        result_show_type='plotly',
        debug=True)
    
    enhancement 
    opened by Nanguage 0
  • Flask integration of dash app

    Flask integration of dash app

    Embeding the generated dash app as a route of flask server.

    # demo_flask_integrate.py
    from flask import Flask
    from oneface.dash_app import flask_route
    from oneface.core import one
    
    server = Flask("test_dash_app")
    
    @flask_route(server, "/add")
    @one
    def add(a: int, b: int) -> int:
        return a + b
    
    @flask_route(server, "/mul")
    @one
    def mul(a: int, b: int) -> int:
        return a * b
    
    server.run("127.0.0.1", 8088)
    

    Run this will launch a flask server support run multiple dash app from different route.

    References:

    • https://blog.finxter.com/dash-flask/
    enhancement 
    opened by Nanguage 0
  • Define custom dash commpont to support complex input type.

    Define custom dash commpont to support complex input type.

    For example:

    from oneface import one, Arg
    from oneface.dash_app import App, InputItem
    from dash import dcc, html
    
    class Person:
        def __init__(self, name, age):
            self.name = name
            self.age = age
    
    
    def check_person_type(val, tp):
        return (
            isinstance(val, tp) and
            isinstance(val.name, str) and
            isinstance(val.age, int)
        )
    
    Arg.register_type_check(Person, check_person_type)
    Arg.register_range_check(Person, lambda val, range: range[0] <= val.age <= range[1])
    
    class PersonInputItem(InputItem):
        def get_input(self):
            if self.default:
                default_val = f"Person('{self.default.name}', {self.default.age})"
            else:
                default_val = ""
            return dcc.Input(
                placeholder="example: Person('age', 20)",
                type="text",
                value=default_val,
                style={
                    "width": "100%",
                    "height": "40px",
                    "margin": "5px",
                    "font-size": "20px",
                }
            )
    
    
    App.register_widget(Person, PersonInputItem)
    App.register_type_convert(Person, lambda s: eval(s))
    
    
    @one
    def print_person(person: Arg(Person, [0, 100]) = Person("Tom", 10)):
        print(f"{person.name} is {person.age} years old.")
    
    
    print_person.dash_app()
    
    

    This code using the serialized input Person, how to define a "Composite components" in dash to support Person input? Just like in Qt:

    image

    question 
    opened by Nanguage 0
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