Metadata-Version: 2.1
Name: bp-data-grid
Version: 1.0.5
Summary: Show data in data grid
Home-page: UNKNOWN
Author: Bluepineapple
Author-email: avinash@bluepineapple.io
License: UNKNOWN
Description: # Data Grid
        
        **Data Grid** is a Python package that allows you to effortlessly present tabular data in a visually appealing format. With built-in features such as client-side filtering, pagination, and export options, it provides a comprehensive solution for displaying and manipulating data.
        
        ## Features
        
        - **Tabular Data Display**: Easily present data in a grid-like structure for clear and organized visualization.
        - **Client-Side Filtering**: Enable users to quickly search and filter data within the grid, improving data exploration and analysis.
        - **Pagination:** Divide large datasets into manageable chunks, enabling smooth navigation and enhanced performance.
        - **Export Options**: Provide users with the ability to export grid data to various formats such as CSV or Excel, facilitating data sharing and external analysis.
        - **Data Masking**: Ensure data security by incorporating data masking capabilities during export, safeguarding sensitive information from unauthorized access.
        
        ## Installation
        
        You can install the **Data Grid** package from PyPI using pip:
        
        ```shell
        pip install bp-data-grid
        ```
        
        ## Usage
        
        To use the Data Grid component in your Streamlit application, follow these steps:
        
        1. Import the necessary modules:
        
        ```shell
        import data_grid as dg
        ```
        
        1. Add the **Data Grid** component to your application:
        
        ```shell
        dg.data_grid(
            title="Results",
            rows=rows,
            columns=columns,
        )
        ```
        
        1. Run your Streamlit application:
        
        ```shell
        streamlit run your_app.py
        ```
        
        ### Example
        
        ```shell
        import data_grid as dg
        
        columns = [
          {
            "field": "id",
            "headerName": "ID",
            "width": 90
          },
          {
            "field": "firstName",
            "headerName": "First Name",
            "width": 150,
            "editable": True
          },
          {
            "field": "lastName",
            "headerName": "Last Name",
            "width": 150,
            "editable": True
          },
          {
            "field": "age",
            "headerName": "Age",
            "type": "number",
            "width": 110,
            "editable": True
          }
        ]
        
        rows = [
            {"id": 1, "lastName": "Snow", "firstName": "Jon", "age": 35},
            {"id": 2, "lastName": "Lannister", "firstName": "Cersei", "age": 42},
            {"id": 3, "lastName": "Lannister", "firstName": "Jaime", "age": 45},
            {"id": 4, "lastName": "Stark", "firstName": "Arya", "age": 16},
            {"id": 5, "lastName": "Targaryen", "firstName": "Daenerys", "age": 90},
            {"id": 6, "lastName": "Melisandre", "firstName": "Tom", "age": 150},
            {"id": 7, "lastName": "Clifford", "firstName": "Ferrara", "age": 44},
            {"id": 8, "lastName": "Frances", "firstName": "Rossini", "age": 36},
            {"id": 9, "lastName": "Roxie", "firstName": "Harvey", "age": 65},
        ]
        
        dg.data_grid(
             title="Results",
             rows=rows,
             columns=columns,
             key="data_grid",
        )
        
        ```
        
        ## Screenshot
        
        ![Screenshot](https://i.ibb.co/NsfwfY6/eintrag-Streamlit.png "Screen Shot")
        
Platform: UNKNOWN
Requires-Python: >=3.8.10
Description-Content-Type: text/markdown
