simpledatatable 0.3.2

This package allows flet developers to easily import SQL, CSV, Excel or Json tables into flet's DataTable.

Simple DataTable

This is a third party package for a new framework Flet. Simple DataTable is capable of importing CSV, Excel, Json or SQL table into Flet's DataTable. Simple DataTable uses a few different libraries for serializtion that must be installed according to requirements.txt.

Simple DataTable returns DataTable instance, there is no hardcoded values and anything can be changed according to Flet docs

Installation

Note: Publishing this package on PyPi is not planned yet, so you need to clone the repo.

1. Clone the repository into your project directory

   pip install simpledatatable
   

And you're good to go!

Examples

• Importing a table from a CSV file

  import flet as ft
  from simpledt import CSVDataTable
  
  
  def main(page: ft.Page):
      csv = CSVDataTable("dataset/MOCK_DATA.csv")
      dt = csv.datatable
  
      page.add(dt)
  
  
  ft.app(target=main)
  

  

• Importing a table from a CSV url

  import flet as ft
  from simpledt import CSVDataTable
  
  
  def main(page: ft.Page):
      csv = CSVDataTable("https://raw.githubusercontent.com/kb22/Heart-Disease-Prediction/master/dataset.csv")
      dt = csv.datatable
  
      page.add(dt)
  
  
  ft.app(target=main)
  

  

• Importing a table from an Excel file

  import flet as ft
  from simpledt import ExcelDataTable
  
  
  def main(page: ft.Page):
      excel = ExcelDataTable('dataset/Excel_MOCK_DATA.xlsx')
      dt = excel.datatable
  
      page.add(dt)
  
  
  ft.app(target=main)
  

  

• Importing a table from a SQL table

  import flet as ft
  from simpledt import SQLDataTable
  
  
  def main(page: ft.Page):
      sql = SQLDataTable('sqlite', 'data.db', 'users')
      dt = sql.datatable
  
      page.add(dt)
  
  
  ft.app(target=main)
  

  

Attributes

Every class returns Flet's DataTable, list of DataRow and DataColumn instances as attributes, so they can be changed according to Flet docs

After initializing any of the classes, the following attributes are available

• datatable - is a serialized DataTable instance
• datarows - is a list of serialized DataRow instance included in datatable attribute.
• datacolumns - is a list of serialized DataColumn instance included in datatable attribute

General class

• DataFrame(source: pd.DataFrame | IO)

  DataFrame is a general class to serialize and display pandas dataframe. It can also serialize any type of file, like CSV, Json, Excel or SQL, but it's not recommended to directly pass names of those files. Insted, create your own pandas dataframe and pass it to DataFrame object as a source argument.

Shortcut classes

If you don't want to initialize your own pandas dataframe, you can use shortcut classes.

• CSVDataTable(csv_file: str)

  Takes a CSV file, or CSV url as an argument for serialization

• ExcelDataTable(excel_file: str)

  Takes an Excel file as an argument for serialization

• JsonDataTable(json_file: str)

  Takes a Json file as an argument for serialization

• SQLDataTable(sql_engine: str, database: str, table: str = None, statement: str = None user: str = None, password: str = None, host: str = None, port: int = None)

  Takes a SQL database details as an argument for serialization

  Required arguments

  • sql_engine is a literal which can be sqlite, mysql, postgresql
  • database is a database file, like data.sqlite3

  Note: You can provide one of the two arguments table or statement.

  • If table is provided, then every record from table is displayed
  • If you're comfortable with sql, you can write your own sql statement

  As for optional arguments, according to your choice of SQL, you can provide the following arguments

  • user
  • password
  • host
  • port