Streamlit - ECharts5

This is a fork repo of streamlit_echarts. Major changes to upstream:

1. rename package to streamlit-echarts5, you need to rename all import namespaces`
2. bump echarts to v5.5.1
3. bump react to v18
4. bump react-scripts to v5.0.1
5. remove React.useCallback since it is out of rules of hooks,it not recommend in loop or conditional. use normal callback to events ,but with React.memo(EchartsChart) to avoid event failling. It's seems good for all demo now,but not tested yet when event callback and props really change at the same time
6. React.memo component for performance, since streamlit.setComponentValue always rerender parent,and give a set props to a new object,but props not changed actually,React shallow compare treat a new object not equal to old one even their values are equal.egprops = {...props} will call rerender. No rerender in the two examples about events。
7. add notMerge param to func, mannually handle this,but with default value True
8. update python build system, use pyproject.toml to manage info, use pdm as venv manager.

Since I Changed too much deps , versions, mechanism, it's not tested egnough and not easy to be accepted by origin Repo. I won't create pull request to origin repo recently,but publish to pypi as streamlit-echarts5.
I won't frequently update this repository. If you have new feature request,try fork this repo when no response from issues

A Streamlit component to display ECharts.

Install

pip install streamlit-echarts5

Usage

This library provides 2 functions to display echarts :

• st_echarts to display charts from ECharts json options as Python dicts
• st_pyecharts to display charts from Pyecharts instances

Check out the demo and source code for more examples.

st_echarts example

from streamlit_echarts5 import st_echarts

options = {
    "xAxis": {
        "type": "category",
        "data": ["Mon", "Tue", "Wed", "Thu", "Fri", "Sat", "Sun"],
    },
    "yAxis": {"type": "value"},
    "series": [
        {"data": [820, 932, 901, 934, 1290, 1330, 1320], "type": "line"}
    ],
}
st_echarts(options=options)

st_pyecharts example

from pyecharts import options as opts
from pyecharts.charts import Bar
from streamlit_echarts5 import st_pyecharts

b = (
    Bar()
    .add_xaxis(["Microsoft", "Amazon", "IBM", "Oracle", "Google", "Alibaba"])
    .add_yaxis(
        "2017-2018 Revenue in (billion $)", [21.2, 20.4, 10.3, 6.08, 4, 2.2]
    )
    .set_global_opts(
        title_opts=opts.TitleOpts(
            title="Top cloud providers 2018", subtitle="2017-2018 Revenue"
        ),
        toolbox_opts=opts.ToolboxOpts(),
    )
)
st_pyecharts(b)

API

st_echarts API

st_echarts(
    options: Dict
    theme: Union[str, Dict]
    events: Dict[str, str]
    notMerge: bool = True
    height: str
    width: str
    renderer: str
    map: Map
    key: str
)

• options : Python dictionary that resembles the JSON counterpart of echarts options. For example the basic line chart in JS :

// JS code
option = {
  xAxis: {
    type: "category",
    data: ["Mon", "Tue", "Wed", "Thu", "Fri", "Sat", "Sun"],
  },
  yAxis: { type: "value" },
  series: [{ data: [820, 932, 901, 934, 1290, 1330, 1320], type: "line" }],
};

is represented in Python :

# Python code
option = {
    "xAxis": {
        "type": "category",
        "data": ["Mon", "Tue", "Wed", "Thu", "Fri", "Sat", "Sun"],
    },
    "yAxis": { "type": "value" },
    "series": [
        {"data": [820, 932, 901, 934, 1290, 1330, 1320], "type": "line" }
    ],
}

• theme : echarts theme. You can specify built-int themes or pass over style configuration as a Python dict.
• events : Python dictionary which maps an event to a Js function as string. For example :

{
    "click": "function(params) { console.log(params.name) }"
}

will get mapped to :

myChart.on("click", function (params) {
  console.log(params.name);
});

Return values from events are sent back to Python, for example:

option = {
    "xAxis": {
        "type": "category",
        "data": ["Mon", "Tue", "Wed", "Thu", "Fri", "Sat", "Sun"],
    },
    "yAxis": { "type": "value" },
    "series": [
        {"data": [820, 932, 901, 934, 1290, 1330, 1320], "type": "line" }
    ],
}
events = {
    "click": "function(params) { console.log(params.name); return params.name }",
    "dblclick":"function(params) { return [params.type, params.name, params.value] }"
}
value = st_echarts(option, events=events)
st.write(value)  # shows name on bar click and type+name+value on bar double click

The JS code needs to be a one-liner. You can use Javascript minifiers like https://javascript-minifier.com/ or https://www.minifier.org/ to transform your Javascript code to a one-liner.

• height / width : size of the div wrapper
• map : register a map using the dedicated Map class

from streamlit_echarts5 import Map
with open("USA.json", "r") as f:
    map = Map(
        "USA",
        json.loads(f.read()),
        {
            "Alaska": {"left": -131, "top": 25, "width": 15},
            "Hawaii": {"left": -110, "top": 28, "width": 5},
            "Puerto Rico": {"left": -76, "top": 26, "width": 2},
        },
    )
options = {...}
st_echarts(options, map=map)

You'll find a lot of GeoJSON data inside the source code of echarts-countries-js.

• renderer : SVG or canvas
• key : assign a fixed identity if you want to change its arguments over time and not have it be re-created.

st_pyecharts API

def st_pyecharts(
    chart: Base
    theme: Union[str, Dict]
    events: Dict[str, str]
    height: str
    width: str
    renderer: str
    map: Map
    key: str
)

• chart : Pyecharts instance

The docs for the remaining inputs are the same as its st_echarts counterpart.

Development

Install

• JS side

cd frontend
npm install

• Python side

conda create -n streamlit-echarts5 python=3.12
conda activate streamlit-echarts5
pip install -e .

Run

Both webpack dev server and Streamlit need to run for development mode.

• JS side

cd frontend
npm run dev

• Python side

Demo example is on https://github.com/andfanilo/streamlit-echarts-demo. But you need to change all import module from streamlit_echarts to streamlit_echarts5

git clone https://github.com/andfanilo/streamlit-echarts-demo
cd streamlit-echarts-demo/
# After you replace the import module,then run next shell
streamlit run app.py

build package

• Build frontend

cd frontend
npm run build

• Build wheel

# cd to project root
# ensure python env have 'build' installed
python -m build

Caveats

Theme definition

• Defining the theme in Pyecharts when instantiating chart like Bar(init_opts=opts.InitOpts(theme=ThemeType.LIGHT)) does not work, you need to call theme in st_pyecharts(c, theme=ThemeType.LIGHT).

On Javascript functions

This library also provides the JsCode util class directly from pyecharts.

This class is used to indicate javascript code by wrapping it with a specific placeholder. On the custom component side, we parse every value in options looking for this specific placeholder to determine whether a value is a JS function.

As such, if you want to pass JS functions as strings in your options, you should use the corresponding JsCode module to wrap code with this placeholder :

• In Python dicts representing the JSON option counterpart, wrap any JS string function with streamlit_echarts.JsCode by calling JsCode(function).js_code. It's a smaller version of pyecharts.commons.utils.JsCode so you don't need to install pyecharts to use it.

series: [
    {
        type: 'scatter', // this is scatter chart
        itemStyle: {
            opacity: 0.8
        },
        symbolSize: JsCode("function (val) { return val[2] * 40;}").js_code,
        data: [["14.616","7.241","0.896"],["3.958","5.701","0.955"],["2.768","8.971","0.669"],["9.051","9.710","0.171"],["14.046","4.182","0.536"],["12.295","1.429","0.962"],["4.417","8.167","0.113"],["0.492","4.771","0.785"],["7.632","2.605","0.645"],["14.242","5.042","0.368"]]
    }
]

• In Pyecharts, use pyecharts.commons.utils.JsCode directly, JsCode automatically calls .js_code when dumping options.

.set_series_opts(
        label_opts=opts.LabelOpts(
            position="right",
            formatter=JsCode(
                "function(x){return Number(x.data.percent * 100).toFixed() + '%';}"
            ),
        )
    )

Note: you need the JS string to be on one-line. You can use Javascript minifiers like https://javascript-minifier.com/ or https://www.minifier.org/ to transform your Javascript code to a one-liner.

st_pyecharts VS using pyecharts with components.html

While this package provides a st_pyecharts method, if you're using pyecharts you can directly embed your pyecharts visualization inside st.html by passing the output of the chart's .render_embed().

from pyecharts.charts import Bar
from pyecharts import options as opts
import streamlit.components.v1 as components

c = (Bar()
    .add_xaxis(["Microsoft", "Amazon", "IBM", "Oracle", "Google", "Alibaba"])
    .add_yaxis('2017-2018 Revenue in (billion $)', [21.2, 20.4, 10.3, 6.08, 4, 2.2])
    .set_global_opts(title_opts=opts.TitleOpts(title="Top cloud providers 2018", subtitle="2017-2018 Revenue"),
                     toolbox_opts=opts.ToolboxOpts())
    .render_embed() # generate a local HTML file
)
components.html(c, width=1000, height=1000)

Using st_pyecharts is still something you would want if you need to change data regularly without remounting the component, check for examples examples/app_pyecharts.py for Chart with randomization example.

Credits

• It's really a wrapper around echarts-for-react.