streamlit-jupyter 0.3.1

Simple Python package to preview and develop streamlit apps in jupyter notebooks

streamlit-jupyter

Docs & links

• Detailed docs for this library can be found at ddobrinskiy.github.io/streamlit-jupyter

• ToDos on github project

• The rest of this README provides a quick overview of the library.

Install

pip install streamlit_jupyter

How to use

Take a look at our example notebook, streamlit version runs here

The main idea is for you do experiment and develop in your notebook, visually see all the pieces, and then convert the notebook to .py to be run by streamlit

start by importing streamlit and patching it with streamlit-jupyter:

import streamlit as st

from streamlit_jupyter import StreamlitPatcher, tqdm

StreamlitPatcher().jupyter()  # register streamlit with jupyter-compatible wrappers

And now develop your notebook as usual, but with the ability to use Streamlit widgets and components.

See how it works below, and check out the example notebook

Currently supported methods

Refer to excellent streamlit docs for more details on each method

method	docstring
st.cache_data	Implements the public st.cache_data API: the @st.cache_data decorator, and
st.cache_resource	Implements the public st.cache_resource API: the @st.cache_resource decorator,
st.cache	Legacy caching decorator (deprecated).
st.caption	Display text in small font.
st.checkbox	Display a checkbox widget.
st.code	Display a code block with optional syntax highlighting.
st.data_editor	Display a data editor widget.
st.dataframe	Display a dataframe as an interactive table.
st.date_input	Display a date input widget.
st.expander	Insert a multi-element container that can be expanded/collapsed.
st.header	Display text in header formatting.
st.json	Display object or string as a pretty-printed JSON string.
st.latex	Display mathematical expressions formatted as LaTeX.
st.markdown	Display string formatted as Markdown.
st.metric	Display a metric in big bold font, with an optional indicator of how the metric changed.
st.multiselect	Display a multiselect widget.
st.radio	Display a radio button widget.
st.selectbox	Display a select widget.
st.subheader	Display text in subheader formatting.
st.text_area	Display a multi-line text input widget.
st.text_input	Display a single-line text input widget.
st.text	Write fixed-width and preformatted text.
st.title	Display text in title formatting.
st.write	Write arguments to the app.

Currently unsupported methods

Most of the other methods are not supported yet.

If you need any of them, you have one of 2 options:

• please open an issue or a PR

• use them in your notebook regardless, they will still work once you convert your notebook to streamlit. You just won’t be able to preview them in jupyter.

How to contribute

To start with you need to create virtualenv with pipenv tool and the libraries from Pipfile:

pipenv shell 
pipenv install -d 

Install quatro, if you have Mac OS use homebrew:

brew install quarto

otherwise, check https://quarto.org/docs/download/

The next step is to install streamlit-jupyter from the repo

pip install -e "[dev]"

now you are all set, you can refer to Makefile to see examples with streamlit-jupyter. Simply run a command:

make all

Demonstration

	Jupyter	Streamlit
Markdown and headings
Interactive data entry
Pick and choose
Dataframes, caching and progress bars
Plots
Metrics