Skip to main content

No project description provided

Project description

A Pure Python, React-style Framework for Scaling Your Jupyter and Web Apps

solara logo

Come chat with us on Discord to ask questions or share your thoughts or creations!

Discord Shield

Introducing Solara

While there are many Python web frameworks out there, most are designed for small data apps or use paradigms unproven for larger scale. Code organization, reusability, and state tend to suffer as apps grow in complexity, resulting in either spaghetti code or offloading to a React application.

Solara addresses this gap. Using a React-like API, we don't need to worry about scalability. React has already proven its ability to support the world's largest web apps.

Solara uses a pure Python implementation of React (Reacton), creating ipywidget-based applications. These apps work both inside the Jupyter Notebook and as standalone web apps with frameworks like FastAPI. This paradigm enables component-based code and incredibly simple state management.

By building on top of ipywidgets, we automatically leverage an existing ecosystem of widgets and run on many platforms, including JupyterLab, Jupyter Notebook, Voilà, Google Colab, DataBricks, JetBrains Datalore, and more.

We care about developer experience. Solara will give your hot code reloading and type hints for faster development.

Installation

Run:

pip install solara

Or follow the Installation instructions for more detailed instructions.

First script

Put the following Python snippet in a file (we suggest sol.py), or put it in a Jupyter notebook cell:

import solara

# Declare reactive variables at the top level. Components using these variables
# will be re-executed when their values change.
sentence = solara.reactive("Solara makes our team more productive.")
word_limit = solara.reactive(10)


@solara.component
def Page():
    # Calculate word_count within the component to ensure re-execution when reactive variables change.
    word_count = len(sentence.value.split())

    solara.SliderInt("Word limit", value=word_limit, min=2, max=20)
    solara.InputText(label="Your sentence", value=sentence, continuous_update=True)

    # Display messages based on the current word count and word limit.
    if word_count >= int(word_limit.value):
        solara.Error(f"With {word_count} words, you passed the word limit of {word_limit.value}.")
    elif word_count >= int(0.8 * word_limit.value):
        solara.Warning(f"With {word_count} words, you are close to the word limit of {word_limit.value}.")
    else:
        solara.Success("Great short writing!")


# The following line is required only when running the code in a Jupyter notebook:
Page()

Run from the command line in the same directory where you put your file (sol.py):

$ solara run sol.py
Solara server is starting at http://localhost:8765

Or copy-paste this to a Jupyter notebook cell and execute it (the Page() expression at the end will cause it to automatically render the component in the notebook).

See this snippet run live at https://solara.dev/documentation/getting_started

Demo

The following demo app can be used to explore a dataset (build in or upload yourself) using a scatter plot. The plot can be interacted with to filter the dataset, and the filtered dataset can be downloaded.

Running in solara-server

The solara server is build on top of Starlette/FastAPI and runs standalone. Ideal for production use.

fastapi

Running in Jupyter

By building on top of ipywidgets, we automatically leverage an existing ecosystem of widgets and run on many platforms, including JupyterLab, Jupyter Notebook, Voilà, Google Colab, DataBricks, JetBrains Datalore, and more. This means our app can also run in Jupyter:

jupyter

Resources

Visit our main website or jump directly to the introduction

Introduction Quickstart

Note that the solara.dev website is created using Solara

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

solara-1.46.0.tar.gz (5.0 kB view details)

Uploaded Source

Built Distribution

solara-1.46.0-py3-none-any.whl (5.9 kB view details)

Uploaded Python 3

File details

Details for the file solara-1.46.0.tar.gz.

File metadata

  • Download URL: solara-1.46.0.tar.gz
  • Upload date:
  • Size: 5.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: python-httpx/0.28.1

File hashes

Hashes for solara-1.46.0.tar.gz
Algorithm Hash digest
SHA256 e855bc018eefb2368a98cd1c7f39bc457e6ce5317fe3aa1a7b9408b81b3a0cea
MD5 2383e81aa675761ed791e90ec156b250
BLAKE2b-256 0af7c828eb79f386dddd694f6f2ced258a41a9b7f114ad22cdf5b4b7761ddbfd

See more details on using hashes here.

File details

Details for the file solara-1.46.0-py3-none-any.whl.

File metadata

  • Download URL: solara-1.46.0-py3-none-any.whl
  • Upload date:
  • Size: 5.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: python-httpx/0.28.1

File hashes

Hashes for solara-1.46.0-py3-none-any.whl
Algorithm Hash digest
SHA256 ef05ba988bb7acf84543b3cd0fe3b8da3684457b5125bd67f8a826470cc3208e
MD5 7ef761b694e5aa833026ddb30c2f0d12
BLAKE2b-256 d6e428b8f3ac555d012362cd8f3c196c3104eb4112b9b41f2975c2fbed6169a5

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page