Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/blackary/sis-extras
https://github.com/blackary/sis-extras
Last synced: 19 days ago
JSON representation
- Host: GitHub
- URL: https://github.com/blackary/sis-extras
- Owner: blackary
- License: mit
- Created: 2024-03-20T19:17:08.000Z (8 months ago)
- Default Branch: main
- Last Pushed: 2024-10-07T18:06:15.000Z (about 1 month ago)
- Last Synced: 2024-10-11T09:32:28.104Z (about 1 month ago)
- Language: Python
- Size: 119 KB
- Stars: 0
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.txt
Awesome Lists containing this project
README
# 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:
```bash
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
```python
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
```python
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")
```
