w3resource

Python: List the tables of given SQLite database file

Python SQLite Database: Exercise-4 with Solution

Write a Python program to list the tables of given SQLite database file.

Sample Solution:

Python Code :

import sqlite3
from sqlite3 import Error
def sql_connection():
   try:
     conn = sqlite3.connect('mydatabase.db')
     return conn
   except Error:
     print(Error)
 
def sql_table(conn):
   cursorObj = conn.cursor()
# Create two tables
   cursorObj.execute("CREATE TABLE agent_master(agent_code char(6),agent_name char(40),working_area char(35),commission decimal(10,2),phone_no char(15) NULL);")
   cursorObj.execute("CREATE TABLE temp_agent_master(agent_code char(6),agent_name char(40),working_area char(35),commission decimal(10,2),phone_no char(15) NULL);")
   print("List of tables:")
   cursorObj.execute("SELECT name FROM sqlite_master WHERE type='table';")
   print(cursorObj.fetchall())
   conn.commit()
sqllite_conn = sql_connection()
sql_table(sqllite_conn)
if (sqllite_conn):
 sqllite_conn.close()
 print("\nThe SQLite connection is closed.")

Sample Output:

List of tables:
[('agent_master',), ('temp_agent_master',)]

The SQLite connection is closed.

Python Code Editor:

Have another way to solve this solution? Contribute your code (and comments) through Disqus.

Previous: Write a Python program to connect a database and create a SQLite table within the database.
Next: Write a Python program to create a table and insert some records in that table. Finally selects all rows from the table and display the records.

What is the difficulty level of this exercise?

Test your Python skills with w3resource's quiz

Python: Tips of the Day

Creates a dictionary with the same keys as the provided dictionary and values generated by running the provided function for each value:

Example:

def tips_map_values(obj, fn):
  ret = {}
  for key in obj.keys():
    ret[key] = fn(obj[key])
  return ret
users = {
  'Owen': { 'user': 'Owen', 'age': 29 },
  'Eddie': { 'user': 'Eddie', 'age': 15 }
}

print(tips_map_values(users, lambda u : u['age'])) # {'Owen': 29, 'Eddie': 15}

Output:

{'Owen': 29, 'Eddie': 15}