A Streamlit component to display ECharts.

• Python >= 3.10

uv pip install streamlit-echarts

To also use PyECharts charts with st_pyecharts:

uv pip install streamlit-echarts[pyecharts]

import streamlit as st
from streamlit_echarts 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": "bar"}],
}

st_echarts(options=options, height="400px")

Convenience wrapper that converts a PyECharts chart instance to a dict and calls st_echarts. Requires pip install streamlit-echarts[pyecharts]. Accepts the same parameters as st_echarts (replacing options with chart).

Wraps a JavaScript string so the frontend evaluates it as a live function rather than a plain string. Use wherever ECharts expects a callback (formatters, symbol sizes, color functions, …).

JsCode("function(params){ return params.value * 2 }")

Registers a GeoJSON map with ECharts. Pass the returned object to st_echarts(map=...) and reference map_name in a geo or map series.

Use on_select to enable structured selection events, similar to st.plotly_chart:

result = st_echarts(options=options, on_select="rerun", selection_mode="points", key="my_chart")

selected = result["selection"]
if selected["point_indices"]:
    st.write("Selected indices:", selected["point_indices"])

selection_mode accepts "points" (click), "box" (rect brush), "lasso" (polygon brush), or a tuple of multiple modes. See the demo app for more examples.

Install the optional pyecharts extra:

uv pip install streamlit-echarts[pyecharts]

Then use st_pyecharts to render PyECharts chart instances directly:

import streamlit as st
from pyecharts import options as opts
from pyecharts.charts import Bar
from streamlit_echarts 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"
        )
    )
)

st_pyecharts(b, height="500px")

st_pyecharts accepts the same parameters as st_echarts (theme, events, on_select, etc.). Under the hood it calls chart.dump_options() and passes the result to st_echarts.

Alternatively, you can convert PyECharts options manually without installing the extra:

import json
from streamlit_echarts import st_echarts

st_echarts(options=json.loads(b.dump_options()), height="500px")

A comprehensive demo application containing dozens of ECharts and PyECharts examples is available in the root of the repository. You can use it as an integration test to verify the component's functionality:

Note: You will need extra dependencies installed to run all examples in the demo:

uv pip install pyecharts pandas faker
uv run streamlit run demo_app.py

This project is in best-effort status — I occasionally add features I personally need through agentic coding, but I'm not actively reviewing larger issues or pull requests from the community. If you're looking to add a bigger feature, you're welcome to fork it!

Please add a thumbs up HERE if you wish to see a native implementation maintained by the Streamlit team.

See CONTRIBUTING.md for development setup, testing, building, and publishing.