sis-extras 0.1.3

Python package to make it easy to develop beautiful, performant streamlit-in-snowflake apps

sis-extras

Overview

The sis-extras package provides a set of Python utilities designed to help you develop beautiful, performant streamlit-in-snowflake apps.

Currently, this package includes modules for managing database connections (connection.py) and creating interactive data tiles (formatting.py).

Installation

To install sis-extras, you can use pip:

pip install sis-extras

Modules

connection.py

This module handles connections to Snowflake databases, providing functionality to manage sessions and execute SQL queries directly, returning results in a Pandas DataFrame format.

Key Functions:

• SnowparkConnection: Manages Snowflake database connections.
• get_data_frame_from_raw_sql: Executes a SQL query and returns the results as a Pandas DataFrame.
• get_pandas_df: Converts a Snowpark DataFrame to a Pandas DataFrame.
• join_cached: Provides a cached mechanism for joining two Snowpark DataFrames.

formatting.py

This module aids in the visualization of data using Streamlit, Altair, and Plotly, focusing on creating interactive tiles that can display data, charts, and SQL queries.

Key Functions:

• tile: Creates a tile in Streamlit that can display a chart, data preview, SQL query, and a description.
• tile_ctx: A context manager version of tile for more flexible content management within a tile.
• altair_time_series: Generates a time series chart using Altair, designed to handle specific formatting and tooltip requirements.

Usage Examples

Using SnowparkConnection

from sis_extras.connection import get_table, get_data_frame_from_raw_sql, get_pandas_df

# Use Snowpark API

table = get_table("your_table").limit(10)

table_pd = get_pandas_df(table)

st.write(table_pd)

# Use SQL

table_pd = get_data_frame_from_raw_sql("SELECT * FROM your_table")

st.write(table_pd)

Creating a Data Tile

from sis_extras.formatting import tile
import pandas as pd
import altair as alt

# Sample DataFrame

data = pd.DataFrame({
    'x': range(10),
    'y': range(10)
})

# Sample Chart

chart = alt.Chart(data).mark_line().encode(
    x='x',
    y='y'
)

# Create a tile with data and chart

tile(data, "Sample Tile", chart=chart, sql="SELECT x, y FROM your_table")