Tableview data sources from csv, excel, pandas dataframe, MySQL or SQLite database

Ttkbootstrap Tableview using MySQL SQLite CSV Excel and DataFrame as data sources

Sample data from different Data Sources

Sample data in Excel, CSV, MySQL dump, SQLite databae, Pandas DataFrame

Number of columns to display

When we collect data from the source ( database table or Excel or CSV file ) we are not sure how many columns will be available. Here are some SQL which collects different number of columns from the table

SELECT id, name FROM student;

SELECT id, name, class FROM student;

SELECT * FROM student;

First and second query will collect two and three columns respectively from our student table. The third query will return all the columns of the student table.

This way we will not have any fixed number of columns and based on the source or data, we have to create the columns.

For our easy understanding let us create one list and use the elements as column headers. We can replace our list with data from Database table.

l1 = ['id', 'Name', 'Class', 'Mark', 'Gender']

Using this list we will add our columns and headers ( list elements ) to our Treeview.

Table Headers from Data source for Tableview

We will replace the list l1 in above code with our data column headers and for that we have used our MySQL table. Note that souce can be SQLite or Excel or Pandas DataFrame or any other source.

Creating the Tableview

dv = ttk.tableview.Tableview(
    master=my_w,
    paginated=True,
    searchable=False,
    bootstyle=PRIMARY,
    pagesize=10,
    height=10,
    coldata=l1,
    rowdata=r_set,
    stripecolor=(colors.light, None),
)

dv.grid(row=0, column=0, padx=5, pady=5)  # Tableview is placed

We need to create two variables ( l1 and r_set ) , one is list of headers and other one is list of row data.
Let us work with different data sources. Based on the requirment any part of the code can be un-commented to include as source.

MySQL database table as data source

from sqlalchemy import create_engine, text

my_conn = create_engine("mysql+mysqldb://userid:pw@localhost/my_db")
my_conn = my_conn.connect()  # Connection object

r_set = my_conn.execute(text('SELECT * FROM student'))

l1 = [r for r in r_set.keys()]  # List of column headers
r_set = [list(r) for r in r_set]

# l1=['id','Name','Class','Mark','Gender']

MySQL Database

SQLite database as data source

from sqlalchemy import create_engine, text

my_conn = create_engine("sqlite:///D:\\testing\\sqlite\\my_db.db")
my_conn = my_conn.connect()  # Connection object

r_set = my_conn.execute(text('SELECT * FROM student'))

l1 = [r for r in r_set.keys()]  # List of column headers
r_set = [list(r) for r in r_set]

SQLite Database

Pandas DataFrame as source

import pandas as pd 

df = pd.read_excel('D:\\student.xlsx')  # Create dataframe using xlsx file

l1 = list(df)  # List of column names as headers

r_set = df.to_numpy().tolist()  # Create list of lists using rows

Pandas DataFrame Pandas read_excel()

Excel file as source

from openpyxl import load_workbook

wb = load_workbook(filename='D:\\student.xlsx', read_only=True)
ws = wb['Sheet1']

r_set = [row for row in ws.iter_rows(values_only=True)]

l1 = r_set.pop(0)  # Collect the first row as column headers

wb.close()  # Close the workbook after reading

Openpyxl to Manage Excel files

csv file as data source

import csv

file = open('D:\\student.csv')  # File object for student.csv file

csvreader = csv.reader(file)

l1 = []
l1 = next(csvreader)  # Column headers as first row

r_set = [row for row in csvreader]

json file as data source

import json
import urllib.request

# Fetch and parse JSON data
url = "https://www.plus2net.com/php_tutorial/student.json"
with urllib.request.urlopen(url) as response:
    data = json.load(response)

# Define column headers
l1 = [{"text": key.capitalize(), "stretch": True} for key in data[0].keys()]

# Define row data
r_set = [tuple(student.values()) for student in data]

JSON data format

Integrating Tabelview with Data

This step is after collecting the data from sources ( l1 , r_set ).

dv.build_table_data(l1, r_set)  # adding column and row data
dv.load_table_data() # refresh the table view with data
dv.autofit_columns() # Adjust with available space 
dv.autoalign_columns() # String left and Numbers to right

import ttkbootstrap as ttk
from ttkbootstrap.tableview import Tableview
from ttkbootstrap.constants import *

my_w = ttk.Window()
my_w.geometry("400x300")  # width and height
colors = my_w.style.colors  # for using alternate colours

dv = ttk.tableview.Tableview(
    master=my_w,
    paginated=True,
    searchable=True,
    bootstyle=SUCCESS,
    pagesize=10,
    height=10,
    stripecolor=(colors.light, None),
)
dv.grid(row=0, column=0, padx=5, pady=5)  # Tableview is placed
# MySQL as data source
from sqlalchemy import create_engine,text  # for MySql and SQLite database

"""
my_conn = create_engine("mysql+mysqldb://id:pw@localhost/my_tutorial") # update details
my_conn = my_conn.connect()
r_set = my_conn.execute(text("SELECT * FROM student ")) # Change the query 
l1 = [r for r in r_set.keys()]  # List of Column headers
r_set = [list(r) for r in r_set]  # List of rows of data
"""
# SQlite database as datasource
"""
my_conn = create_engine("sqlite:///D:\\testing\\sqlite\\my_db.db") # Update your path
my_conn = my_conn.connect()
r_set = my_conn.execute(text("SELECT * FROM student")) 
l1 = [r for r in r_set.keys()]  # List of column headers
r_set = [list(r) for r in r_set]
"""
# Pandas dataframe as source
"""
import pandas as pd
df = pd.read_excel("I:\data\student.xlsx")  # create dataframe using xlsx file
l1 = list(df)  # List of column names as headers
r_set = df.to_numpy().tolist()  # Create list of list using rows
"""
# Excel file as source
"""
from openpyxl import load_workbook
wb = load_workbook(filename="I:\data\student.xlsx", read_only=True)
ws = wb["student"]
r_set = [row for row in ws.iter_rows(values_only=True)]
l1 = r_set.pop(0)  # Collect the first row as column headers
wb.close()  # Close the workbook after reading
"""
# CSV file as source
import csv

file = open("I:\data\student.csv")  # file object for student.csv file
csvreader = csv.reader(file)
l1 = []
l1 = next(csvreader)  # column headers as first row
r_set = [row for row in csvreader]

# Integrate the data source to Tableview
dv.build_table_data(l1, r_set)  # adding column and row data
dv.load_table_data()  # refresh the table view with data
dv.autofit_columns()  # Adjust with available space
dv.autoalign_columns()  # String left and Numbers to right

my_w.mainloop()

Keeping a separate Data Source file

We can keep all the data sources in a different file and use only two variables l1 and r_set. From our main file we can call these two variables like this.

from ttk_table_sources import r_set, l1

This will help in better maintenance of the code and same source can be used in different modules.

'''
r_set = [
    [1, "John Deo", "Four", 75, "female"],
    [2, "Max Ruin", "Three", 85, "male"],
    [3, "Arnold", "Three", 55, "male"],
    [4, "Krish Star", "Four", 60, "female"],
    [5, "John Mike", "Four", 60, "female"],
    [6, "Alex John", "Four", 55, "male"],
    [7, "My John Rob", "Five", 78, "male"],
    [8, "Asruid", "Five", 85, "male"],
    [9, "Tes Qry", "Six", 78, "male"],
    [10, "Big John", "Four", 55, "female"],
]

l1 = ["id", "name", "class", "mark", "gender"]
'''
# MySQL as data source

from sqlalchemy import create_engine ,text # for MySql and SQLite database


my_conn = create_engine("mysql+mysqldb://id:pw@localhost/my_tutorial")
my_conn = my_conn.connect()
r_set = my_conn.execute(text("SELECT * FROM student"))  # Change the query
l1 = [r for r in r_set.keys()]  # List of Column headers
r_set = [list(r) for r in r_set]  # List of rows of data

# SQlite database as datasource
"""
my_conn = create_engine("sqlite:///D:\\testing\\sqlite\\my_db.db")
my_conn = my_conn.connect()
r_set = my_conn.execute(text("SELECT * FROM student") )
l1 = [r for r in r_set.keys()]  # List of column headers
r_set = [list(r) for r in r_set]
"""
# Pandas dataframe as source
"""
import pandas as pd
df = pd.read_excel("I:\data\student.xlsx")  # create dataframe using xlsx file
l1 = list(df)  # List of column names as headers
r_set = df.to_numpy().tolist()  # Create list of list using rows
"""
# Excel file as source
"""
from openpyxl import load_workbook
wb = load_workbook(filename="I:\data\student.xlsx", read_only=True)
ws = wb["student"]
r_set = [row for row in ws.iter_rows(values_only=True)]
l1 = r_set.pop(0)  # Collect the first row as column headers
wb.close()  # Close the workbook after reading
"""
# CSV file as source
"""
import csv

file = open("F:\data\student.csv")  # file object for student.csv file
csvreader = csv.reader(file)
l1 = []
l1 = next(csvreader)  # column headers as first row
r_set = [row for row in csvreader]
"""

import ttkbootstrap as ttk
from ttkbootstrap.tableview import Tableview
from ttkbootstrap.constants import *
from ttk_table_sources import r_set, l1

my_w = ttk.Window()
my_w.geometry("400x300")  # width and height
colors = my_w.style.colors  # for using alternate colours

dv = ttk.tableview.Tableview(
    master=my_w,
    paginated=True,
    searchable=False,
    bootstyle=SUCCESS,
    pagesize=10,
    height=10,
    stripecolor=(colors.light, None),
)
dv.grid(row=0, column=0, padx=5, pady=5)  # Tableview is placed

# Integrate the data source to Tableview
marks = [int(r[3]) for r in r_set]  # List of all marks column
dv.build_table_data(l1, r_set)  # adding column and row data
dv.insert_row("end", values=["-", "-SUM-", "All", sum(marks), "All"])
dv.insert_row("end", values=["-", "-MAX-", "All", max(marks), "All"])
dv.load_table_data()  # refresh the table view with data
dv.autofit_columns()  # Adjust with available space
dv.autoalign_columns()  # String left and Numbers to right
my_w.mainloop()

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Subhendu Mohapatra

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