update readme, set version to 0.0.3

Author: jeffbaumes

streamlit-layoutr/README.md

@@ -1,49 +1,66 @@
-# Streamlit Component Vue Vite Template
+# Streamlit Layoutr Component
 
-A template for creating Streamlit Components. It uses Vue 3 to code the frontend and Vite to serve the files locally during development, as well as bundle and compile them for production.
+A Streamlit Component for Layoutr based on a template for creating Streamlit Components. It uses Vue 3 to code the frontend and Vite to serve the files locally during development, as well as bundle and compile them for production.
 
 This repo contains templates and example code for creating [Streamlit](https://streamlit.io) Components. For complete information, please see the [Streamlit Components documentation](https://docs.streamlit.io/en/latest/streamlit_components.html)!
 
-## Quickstart
+## Development
 
-Ensure you have [Python 3.6+](https://www.python.org/downloads/), [Node.js](https://nodejs.org) and [npm](https://docs.npmjs.com/downloading-and-installing-node-js-and-npm) installed.
+To develop the component, you need to have Node.js and npm installed. You can download them from [nodejs.org](https://nodejs.org/).
 
-1. Clone this repository:
+1. Go to the `frontend` directory and initialize and run the component template frontend:
 ``` bash
-git clone git@github.com:gabrieltempass/streamlit-component-vue-vite-template.git
-```
-
-2. Go to the `frontend` directory and initialize and run the component template frontend:
-``` bash
-cd streamlit-component-vue-vite-template/streamlit_layoutr/frontend
+cd streamlit_layoutr/frontend
 ```
 ``` bash
 npm install
 npm run dev
 ```
 
-3. From a separate terminal, go to the repository root directory, create a new Python virtual environment, activate it and install Streamlit and the template as an editable package:
-``` bash
-cd streamlit-component-vue-vite-template
-```
+1. Set `_RELEASE = False` in `streamlit_layoutr/__init__.py`. This will pull the component live from `npm run dev` instead of the built version.
+
+1. From a separate terminal, go to the repository root directory, create a new Python virtual environment, activate it and install Streamlit and the template as an editable package:
 ``` bash
 python3 -m venv venv
 . venv/bin/activate
 pip install streamlit
 pip install -e .
 ```
 
-Still from the same separate terminal, run the example Streamlit app:
+1. Still from the same separate terminal, run the example Streamlit app:
 ``` bash
 streamlit run streamlit_layoutr/example.py
 ```
 
-If all goes well, you should see something like this:
+If all goes well, you should see a sample app that lets you upload JSON and see it displayed in a graph.
+
+## Deployment to PyPI
+
+To deploy the component to PyPI, you need to build the frontend and package it with the Python code.
 
-![Quickstart Success](quickstart.png)
+1. Update the version number in `setup.py`.
 
-Modify the frontend code at `streamlit_layoutr/frontend/src/MyComponent.vue`.
-Modify the Python code at `streamlit_layoutr/__init__.py`.
+2. Ensure `_RELEASE = True` in `streamlit_layoutr/__init__.py`.
+
+3. Build the frontend:
+``` bash
+cd streamlit_layoutr/frontend
+```
+``` bash
+npm run build
+```
+This will create a `dist` folder with the built files.
+
+4. Go to the root directory and build the package:
+``` bash
+python3 setup.py sdist bdist_wheel
+```
+
+5. Upload the package to PyPI (requires access to the PyPI account):
+``` bash
+pip install twine
+twine upload dist/*
+```
 
 ## References
 

streamlit-layoutr/setup.py

@@ -7,7 +7,7 @@
 
 setuptools.setup(
     name="streamlit-layoutr",
-    version="0.0.2",
+    version="0.0.3",
     author="Kitware",
     author_email="kitware@kitware.com",
     description="Streamlit component for graph visualization",