• Funix automatically turns an ordinary Python function or class definition into a web app, which is accessible in a browser via a shareable link.
• Funix is the frontend/backend/fullstack engineer and the infra/ops engineer for AI/Data/Science solo stars like you.
• Funix is the no-/low-code solution for those who write the most core and innovative code.
• Funix is open-source and can be deployed on-premises.

• Startups: quickly build demos, iterate on MVPs, get user feedback and statistics, and pitch to investors or your mom.
• Generative AI: instantly allow people to interact your GenAI model or idea.
• STEM research: let people run your model and/or algorithm effortlessly.
• Data browser: an interface to page through your data.
• A/B test and data labeling: collect human labeling or preference.

• Minimalist and out-of-box: Make no or little addition to your existing code.
• CSS for Python: Widgets are generated automatically based on variable types according to a theme, rather than per-variable manually, for centralized, reusable, and consistent UI across apps.
• Non-intrusive and declarative: As JSON strings, UI configurations are separated from the core logic. Your code can still be run, imported, and called as usual.
• Seamlessly Pythonic: Map Python's native keywords to web app features, such as global for sessions, yield for streaming, and print for anything you wanna display in your app.
• Apps, not demos: Out of the box support for access control, user tracking and Do-Not-Track options, multipage apps with data passing, session management, reactiveness, backend telemetry, etc.

1. Install Funix (advanced installation options):

   pip install funix

2. Save the code below to a file called hello.py:

   def hello(your_name: str) -> str:
       return f"Hello, {your_name}."

3. Running this command

   $ funix hello.py

4. The app will pop in a browser on http://localhost:3000:

   

The Zen of Funix is to generate widgets for function I/Os based on their types, instead of manually picking and customizing the widget for each I/O. Funix to Python is like CSS to HTML or style class to LaTeX. UI stuff is not intermingled with the core logic but defined separately. The type-to-widget mapping is controlled by a theme and new types can be defined on top of existing types.

The example below shows how common UI compoents are generated from four Python-native data types: str, bool, Literal and range, as well as types in popular packages such as ipywidgets.Password. The example below further maps default values to placeholders in the UI widgets. From this example, we can see that developers need to learn nothing about Funix or do nothing to their existing code before they can get an app.

import typing # Python native 

import ipywidgets  # popular UI library 

def input_widgets_basic(
    prompt: str = "Who is Oppenheimer?",
    advanced_features: bool = True,
    model: typing.Literal['GPT-3.5', 'GPT-4.0', 'Falcon-7B'] = 'GPT-4.0',
    max_token: range(100, 200, 20) = 140,
    openai_key: ipywidgets.Password = "1234556",
    )  -> str:
    pass

The example below shows how pandas.DataFrame and matplotlib.figure.Figure that AI/data developers cannot be more familiar with are mapped to tables and charts in an app.

import pandas, matplotlib.pyplot
from numpy import arange, log
from numpy.random import random

def table_and_plot(
    df: pandas.DataFrame = pandas.DataFrame({
        "a": arange(500) + random(500)/5,
        "b": random(500)-0.5 + log(arange(500)+1),
        "c": log(arange(500)+1) })
    ) -> matplotlib.figure.Figure:

    fig = matplotlib.pyplot.figure()
    matplotlib.pyplot.plot(df["a"], df["b"], 'b')
    matplotlib.pyplot.plot(df["a"], df["c"], 'r')

    return fig

You can even continuously update a plot based on user input.

import funix 
import matplotlib.pyplot, matplotlib.figure
import numpy 

@funix.funix(
        autorun=True, 
)
def sine(omega: funix.hint.FloatSlider(0, 4, 0.1)) -> matplotlib.figure.Figure:
    fig = matplotlib.pyplot.figure()
    x = numpy.linspace(0, 20, 200)
    y = numpy.sin(x*omega)
    matplotlib.pyplot.plot(x, y, linewidth=5)
    return fig

Funix can turn each member method of a class into a page of an app. In two additional lines, the example below turn a class definition into a multi-page app with the OOP experience where the instantiation of an object of the class is done in a page corresponding to the constructor of the class and the member values of the object can be viewed and updated in other pages. No need to manually expose the member methods of the class.

from funix import funix_class

@funix_class()  
class A:
    def __init__(self, a: int):
        self.a = a
        return f"`self.a` has been initialized to {self.a}"

    def update_a(self, b: int) -> str:
        self.a = b
        return f"`self.a` has been updated to {self.a}"

    def print_a(self) -> str:
        return f"The value of `self.a` is {self.a}"

A more advanced example of class is the wordle game. You can find the source code in examples/wordle.py. In less than 100 lines, you can build Wordle! The screenshot is as follows:

You can wrap any Python function into a web app in Funix. For example, you can take the ChatGPT demo code from OpenAI's APi reference and wrap it into a str-to-str function:

from openai import OpenAI

def ChatGPT(prompt: str) -> str:    
    client = OpenAI()

    completion = client.chat.completions.create(
        model="gpt-3.5-turbo",
        messages=[
            {"role": "user", "content": prompt}
        ]
    )
return completion.choices[0].message

which is turned into an app by Funix like below:

Funix to Python is like CSS to HTML or macros to LaTeX. It separates the core logic and the UI. All UI stuff is centrally defined in a JSON-based theme to avoid the repetitiveness of individually configuring widgets and keep a consistent look across apps. Consequently, a data scientist or a machine learning engineer does not need to think about anything UI. Just leave it to the UI team and Funix.

Below is an example of a theme file. It defines the widget choices based on variable types and tweaks the props of UI components (currently only MUI ones are supported). Funix exposes frontend components and their props to developers, requiring them to know nothing about frontend. To know more about how to define and apply a theme, please refer to the Themes section in the reference manual.

{
  "name": "test_theme",
  "widgets": {    // dict, map types to widgets
    "str": "inputbox", // using Funix' widget shorthand
    "int": "slider[0,100,2]", // using Funix' widget shorthand
    "float": {
        "widget": "@mui/material/Slider", // using MUI's widget
        // https://mui.com/material-ui/api/slider
        "props": {
            "min": 0,
            "max": 100,
            "step": 0.1
        }
    }, 
    "Literal": "radio"
  },
}

To introduce a new data type, just declare a new Python class, and use a decorator to let Funix know. You can associate the type with a widget either on-the-fly (below) or via a theme file.

from funix import funix, new_funix_type

@new_funix_type(
    widget = {
        "widget": "@mui/material/TextField",
        "props": {
            "type": "password",
            "placeholder": "Enter a secret here."
        }
    }
)
class blackout(str):
    def print(self):
        return self + " is the message."

@funix()
def hoho(x: blackout = "Funix Rocks!") -> str:
    return x.print()

if __name__ == "__main__":
    print (hoho(blackout('Fun'))) 

Funix repurposes some Python-native features to web features.

First, Funix won't let your docstring or print() function calls go to waste. They will appear in the input and output panels of the web app.

from funix import funix
@funix(
    print_to_web=True
)
def foo() -> None:
    """
    ## What a great app in Funix! 
    
    Funix won't let your docstring go to waste.
    """
    print("It supports **Markdown**.")
    print ("And <b>HTML</b>.")
    return None

To stream text to the web, simply use yield:

import time

def stream() -> str:
    """
    This function is used to test the stream feature of Funix.
    """
    message = "We the People of the United States, in Order to form a more perfect Union, establish Justice, insure domestic Tranquility, provide for the common defence, promote the general Welfare, and secure the Blessings of Liberty to ourselves and our Posterity, do ordain and establish this Constitution for the United States of America."

    for i in range(len(message)):
        time.sleep(0.01)
        yield message[0:i]

import funix

y = "The default value of y."

@funix.funix()
def set_y(x: str="123") -> str:
    global y
    y = x
    return "Y has been changed. Now check it in the get_y() page."


@funix.funix()
def get_y() -> str:
    return y

import funix

def first_action(x: int) -> int:
  return x - 1

def second_action(message: str) -> list[str]:
  return message.split(" ")

def third_action(x: int, y: int) -> dict:
  return {"x": x, "y": y}

@funix.funix(
  pre_fill={
    "a": first_action,
    "b": (second_action, -1),
    "c": (third_action, "x")
  }
)
def final_action(a: int, b: str, c: int) -> str:
    return f"{a} {b} {c}"

funix  my_app.py --secret  my_secret_token # use a token provided by you
# or 
funix  my_app.py --secret  True # randomly generate a token

$ funix hello.py --secret True
Secrets:
---------------
Name: hello
Secret: 8c9f55d0eb74adbb3c87a445ea0ae92f
Link: http://127.0.0.1:3000/hello?secret=8c9f55d0eb74adbb3c87a445ea0ae92f

More examples in Reference Manual or the ./examples folder.

• ChatPaper (It's like the popular ChatPDF. But in Funix, only 70 lines of code needed.)
• mFlux (synthetic biology)

  import os
  import IPython     
  import openai
  openai.api_key = os.environ.get("OPENAI_KEY")

  messages  = []  # list of dicts, dict keys: role, content, system

  def print_messages_html(messages):
      printout = ""
      for message in messages:
          if message["role"] == "user":
              align, left, name = "left", "0%", "You"
          elif message["role"] == "assistant":
              align, left, name = "right", "30%", "ChatGPT"
          printout += f'<div style="position: relative; left: {left}; width: 70%"><b>{name}</b>: {message["content"]}</div>'
      return printout

  import funix
  @funix.funix(
      direction="column-reverse",
  )
  def ChatGPT_multi_turn(current_message: str)  -> IPython.display.HTML:
      current_message = current_message.strip()
      messages.append({"role": "user", "content": current_message})
      completion = openai.ChatCompletion.create(
          messages=messages,
          model='gpt-3.5-turbo',
          max_tokens=100,
      )
      chatgpt_response = completion["choices"][0]["message"]["content"]
      messages.append({"role": "assistant", "content": chatgpt_response})

      # return print_messages_markdown(messages)
      return print_messages_html(messages)

from funix import funix                      # add line one
from funix.hint import Images                # add line two
import openai  # pip install openai

openai.api_key = os.environ.get("OPENAI_KEY")

@funix()                                     # add line three
def dalle(prompt: str = "a cat") -> Image:
    response = openai.Image.create(prompt=prompt)
    return response["data"][0]["url"]

examples/bioinformatics/vector_strip.py 👈 Click to see source code

import  io # Python's native

import PIL # the Python Image Library
import funix

@funix.funix(
    title="Convert color images to grayscale images",
)
def gray_it(image: funix.hint.BytesImage) -> funix.hint.Image:
    img = PIL.Image.open(io.BytesIO(image))
    gray = PIL.ImageOps.grayscale(img)
    output = io.BytesIO()
    gray.save(output, format="PNG")
    return output.getvalue()

examples/layout_easypost_shipping.py 👈 Click me to see source code

• From PyPI (stable, lacking the latest feature)

  pip install funix

• From GitHub (latest)

  pip -b develop install "git+https://github.com/TexteaInc/funix.git"

• Local development

  git clone -b develop https://github.com/TexteaInc/funix
  cd funix
  pip install -e .

  Add --prefix=~/.local if pip insists to install to system paths. See #24 and #23

In the last two cases above, you will need to compile the frontend by yourself. Suppose you are in the funix folder. Then run the following commands:

1. cd frontend
2. yarn install
3. yarn start

Our table widget uses advanced features in MUI Pro. If you have a MUI Pro license, you can build the frontend with MUI Pro by following the steps below:

1. Install Node.js and Yarn;
2. Create a file called .env in the frontend folder;
3. Add MUI_PRO_LICENSE_KEY=[your_key] to the file;
4. Run yarn funix:build to build the frontend;
5. Done!

Run the command below to see the command line options:

funix -h 

Besides starting Funix from the command line, you can also use a self-contained .py script:

import funix

@funix.funix()
def hello(your_name: str) -> str:
    return f"Hello, {your_name}."

if __name__ == "__main__":
    funix.run(__file__)

funix [module] --host [your_server_ip]

Funix is open-sourced under the MIT License. Community contribution is not only welcomed but desired. Feel free to fork and make a pull request when you are ready. You can also report bugs, suggest new features via the issue tracker or our Discord server.

Funix draws inspiration from FastAPI and Python-Fire: building software interfaces by inferring from function signatures containing type hints. We port this idea from the backend (FastAPI) or the terminal (Python-Fire) to the frontend. We also thank Streamlit, Gradio, PyWebIO, and Pynecone/Reflex. They inspired us. We are just too lazy to manually define widgets imperatively. Funix’s backend is implemented in Flask and the frontend in Material UI.

hello at funix dot io