Overview

Open source, Python-based tool to develop web applications lightning fast.

Documentation: https://dkedar7.github.io/fast_dash/
Source code: https://github.com/dkedar7/fast_dash/

Fast Dash is a Python module that makes the development of web applications fast and easy. It is built on top of Plotly Dash and can be used to build web interfaces for Machine Learning models or to showcase any proof of concept without the hassle of developing UI from scratch.

Simple example

Run your app with three simple steps:

from fast_dash import FastDash
from fast_dash.Components import Text

# Step 1: Define your model inference
def text_to_text_function(input_text):
    return input_text

# Step 2: Specify the input and output components
app = FastDash(callback_fn=text_to_text_function, 
                inputs=Text, 
                outputs=Text, 
                title='App title')

# Step 3: Run your app!
app.run()

# * Running on http://127.0.0.1:5000/ (Press CTRL+C to quit)

And just like that, we have a completely functional interactive app!

Output:

Simple example

In a similar way, we can add multiple input as well as output components at the same time.

from fast_dash import FastDash
from fast_dash.Components import Text, Slider

# Step 1: Define your model inference
def text_to_text_function(input_text, slider_value):
    processed_text = f'{input_text}. Slider value is {slider_value}.'
    return processed_text

# Step 2: Specify the input and output components
app = FastDash(callback_fn=text_to_text_function, 
                inputs=[Text, Slider], 
                outputs=Text,
                title='App title')

# Step 3: Run your app!
app.run()

# * Running on http://127.0.0.1:5000/ (Press CTRL+C to quit)

Simple example with multiple inputs

And with just a few more lines, we can add a title icon, subheader and social details.

...

app = FastDash(callback_fn=text_to_text_function, 
                inputs=[Text, Slider], 
                outputs=Text,
                title='App title',
                title_image_path='https://raw.githubusercontent.com/dkedar7/fast_dash/main/docs/assets/favicon.jpg',
                subheader='Build a proof-of-concept UI for your Python functions lightning fast.',
                github_url='https://github.com/dkedar7/fast_dash',
                linkedin_url='https://linkedin.com/in/dkedar7',
                twitter_url='https://twitter.com/dkedar')

...

Output:

Simple example with multiple inputs and details

Key features

Launch an app only by specifying the types of inputs and outputs.
Multiple input and output components simultaneously.
Flask-based backend allows easy scalability and customizability.
Build fast and iterate.

Some features are coming up in future releases:

More input and output components.
Deploy to Heroku and Google Cloud.
and many more.

Community

Fast Dash is built on open-source. You are encouraged to share your own projects, which will be highlighted on a common community gallery that's upcoming. Join us on Discord.

Credits

Fast Dash is inspired from gradio and built using Plotly Dash. Dash's Flask-based backend enables Fast Dash apps to scale easily and makes them highly compatibility with other integration services. Many documentation ideas and concepts are borrowed from FastAPI's docs project template.

The project template was created with Cookiecutter and zillionare/cookiecutter-pypackage.

Release files for fast-dash 0.1.2

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for fast-dash 0.1.2
File	Size	Uploaded
fast_dash-0.1.2.tar.gz	36.2 kB	Mar 7, 2022	Details

Built distribution (wheel)

Table of built distributions (wheels) for fast-dash 0.1.2
File	Interpreter	ABI	Platform	Reset
fast_dash-0.1.2-py3-none-any.whl 32.7 kB Mar 7, 2022	Python 3	none	any	Details

Total release size: 68.9 kB

Release files / fast_dash-0.1.2.tar.gz

Download URL	fast_dash-0.1.2.tar.gz
Size	36.2 kB
Tags	Source
SHA-256 checksum How to use checksums	`58c17fbb8b3ad178f18c47db7a64d9783a9d54c5efe1d3c027a28f9c28f26167`
BLAKE2b-256 checksum How to use checksums	`61dd44fe83fa1cf64122f2c94cab366e0d849c4045f6e98269caff3f916273a0`
Upload date	Mar 7, 2022
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/3.8.0 pkginfo/1.8.2 readme-renderer/33.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.63.0 importlib-metadata/4.11.2 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.9.10`

Release files / fast_dash-0.1.2-py3-none-any.whl

Download URL	fast_dash-0.1.2-py3-none-any.whl
Size	32.7 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`79ebddbc358caa09cc941c5cf3b5fead8ddbdc82f656dfed12e61c93f1e53074`
BLAKE2b-256 checksum How to use checksums	`129bba06e380a8d0a6019df29ae46ebf67268014648cae8c5d45bc06baf55cef`
Upload date	Mar 7, 2022
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/3.8.0 pkginfo/1.8.2 readme-renderer/33.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.63.0 importlib-metadata/4.11.2 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.9.10`