# streamlit-jupyter
<!-- WARNING: THIS FILE WAS AUTOGENERATED! DO NOT EDIT! -->
<img src="./images/logo.png" width=99%>
[](https://github.com/ddobrinskiy/streamlit-jupyter/actions)
[](https://ddobrinskiy-jupyter.streamlit.app/)
## Docs & links
- Detailed docs for this library can be found at
[ddobrinskiy.github.io/streamlit-jupyter](https://ddobrinskiy.github.io/streamlit-jupyter)
- ToDos on [github
project](https://github.com/users/ddobrinskiy/projects/4/views/1)
- The rest of this README provides a quick overview of the library.
## Install
``` sh
pip install streamlit_jupyter
```
## How to use
Take a look at our [example notebook](./examples/99_example.ipynb),
streamlit version runs
[here](https://ddobrinskiy-jupyter.streamlit.app/)
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:
``` python
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](./examples/99_example.ipynb)
## Currently supported methods
Refer to excellent [streamlit
docs](https://docs.streamlit.io/library/api-reference) 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 **un**supported 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:
``` shell
pipenv shell
pipenv install -d
```
Install quatro, if you have Mac OS use homebrew:
``` shell
brew install quarto
```
otherwise, check https://quarto.org/docs/download/
The next step is to install streamlit-jupyter from the repo
``` shell
pip install -e "[dev]"
```
now you are all set, you can refer to Makefile to see examples with
streamlit-jupyter. Simply run a command:
``` shell
make all
```
## Demonstration
| | <img src="./images/favicon_jupyter.ico" width="30" /> Jupyter | <img src="./images/favicon_streamlit.ico" height="25" /> Streamlit |
|:--:|:--:|:--:|
| Markdown and headings |  |  |
| Interactive data entry |  |  |
| Pick and choose |  |  |
| Dataframes, caching and progress bars |  |  |
| Plots |  |  |
| Metrics |  |  |
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