Pygwalker 0.3.7 release!

About Pygwalker 0.3.7

1. Support communication in streamlit

Pygwalker have supported some features that existed on jupyter:

  • save chart config
  • use duckdb as compute engine(support bigger datas)

But, since streamlit is a long-running service that may be exposed to the public Internet, I hope everyone can refer the best practices of pygwalker in streamlit.

demo code:
online url:

import pandas as pd
import streamlit.components.v1 as components
import streamlit as st
from pygwalker.api.streamlit import init_streamlit_comm, get_streamlit_html

    page_title="Use Pygwalker In Streamlit",

st.title("Use Pygwalker In Streamlit(support communication)")

# Initialize pygwalker communication

# When using `use_kernel_calc=True`, you should cache your pygwalker html, if you don't want your memory to explode
def get_pyg_html(df: pd.DataFrame) -> str:
    # When you need to publish your application, you need set `debug=False`,prevent other users to write your config file.
    # If you want to use feature of saving chart config, set `debug=True`
    html = get_streamlit_html(df, spec="./gw0.json", use_kernel_calc=True, debug=False)
    return html

def get_df() -> pd.DataFrame:
    return pd.read_csv("")

df = get_df()

components.html(get_pyg_html(df), width=1300, height=1000, scrolling=True)

finally, Please read the comments in the demo code carefully before using new pygwalker in streamlit.

2.Support use database as datasource

Pygwalker support use database as datasource(currently in experimental stage).

You can use snowflake as your datasource and compute engine.


from pygwalker.data_parsers.database_parser import Connector

conn = Connector(
    "SELECT * FROM bike_share"

walker = pyg.walk(conn)

In the current version, we don’t recommend publishing pygwalker using Connector to the public network.