SQL using Python | Set 3 (Handling large data)

It is recommended to go through SQL using Python | Set 1 and SQL using Python and SQLite | Set 2

In the previous articles the records of the database were limited to small size and single tuple. This article will explain how to write & fetch large data from the database using module SQLite3 covering all exceptions.
A simple way is to execute the query and use fetchall(). This has been already discussed in SET 1.

• executescript()
  This is a convenience method for executing multiple SQL statements at once. It executes the SQL script it gets as a parameter.

  Syntax:sqlite3.connect.executescript(script)

  import sqlite3
  
  # Connection with the DataBase
  # 'library.db'
  connection = sqlite3.connect("library.db")
  cursor = connection.cursor()
  
  # SQL piece of code Executed
  # SQL piece of code Executed
  cursor.executescript("""
      CREATE TABLE people(
          firstname,
          lastname,
          age
      );
  
      CREATE TABLE book(
          title,
          author,
          published
      );
  
      INSERT INTO
      book(title, author, published)
      VALUES (
          'Dan Clarke''s GFG Detective Agency',
          'Sean Simpsons',
          1987
      );
      """)
  
  sql = """
  SELECT COUNT(*) FROM book;"""
  
  cursor.execute(sql)
  
  # The output in fetched and returned
  # as a List by fetchall()
  result = cursor.fetchall()
  print(result)
  
  sql = """
  SELECT * FROM book;"""
  
  cursor.execute(sql)
  
  result = cursor.fetchall()
  print(result)
  
  # Changes saved into database
  connection.commit()
  
  # Connection closed(broken)
  # with DataBase
  connection.close()

  Output:

  
  
  

  [(1,)]
  [("Dan Clarke's GFG Detective Agency", 'Sean Simpsons', 1987)]
  

  Note: This piece of code may not work on online interpreters, due to permission privileges to create/write database.

• executemany()
  It is often the case when, large amount of data has to be inserted into database from Data Files(for simpler case take Lists, arrays). It would be simple to iterate the code many a times than write every time, each line into database. But the use of loop would not be suitable in this case, the below example shows why. Syntax and use of executemany() is explained below and how it can be used like a loop.

  import sqlite3
  
  # Connection with the DataBase
  # 'library.db'
  connection = sqlite3.connect("library.db")
  cursor = connection.cursor()
  
  # SQL piece of code Executed
  cursor.execute("""
  
      CREATE TABLE book(
          title,
          author,
          published);""")
  
  List = [('A', 'B', 2008), ('C', 'D', 2008),
                            ('E', 'F', 2010)]
  
  connection. executemany("""
  
      INSERT INTO
      book(title, author, published)
      VALUES (?, ?, ?)""", List)
  
  sql = """
        SELECT * FROM book;"""
  cursor.execute(sql)
  result = cursor.fetchall()
  for x in result:
      print(x)
  
  # Changes saved into database
  connection.commit()
  
  # Connection closed(broken)
  # with DataBase
  connection.close()

  Output:

  Traceback (most recent call last):
    File "C:/Users/GFG/Desktop/SQLITE3.py", line 16, in 
      List[2][3] =[['A', 'B', 2008], ['C', 'D', 2008], ['E', 'F', 2010]]
  NameError: name 'List' is not defined
  

  The use of executemany(), can make the piece of code functional.

  import sqlite3
  
  # Connection with the DataBase
  # 'library.db'
  connection = sqlite3.connect("library.db")
  cursor = connection.cursor()
  
  # SQL piece of code Executed
  cursor.execute("""
      CREATE TABLE book(
          title,
          author,
          published);""")
  
  List = [('A', 'B', 2008), ('C', 'D', 2008),
                            ('E', 'F', 2010)]
  
  connection. executemany("""
      INSERT INTO
      book(title, author, published)
      VALUES (?, ?, ?)""", List)
  
  sql = """
  SELECT * FROM book;"""
  cursor.execute(sql)
  result = cursor.fetchall()
  for x in result:
      print(x)
  
  # Changes saved into database
  connection.commit()
  
  # Connection closed(broken)
  # with DataBase
  connection.close()

  Output:

  ('A', 'B', 2008)
  ('C', 'D', 2008)
  ('E', 'F', 2010)
  

• Fetch Large Data

  import sqlite3
  
  # Connection created with the
  # database using sqlite3.connect()
  connection = sqlite3.connect("company.db")
  cursor = connection.cursor()
  
  # Create Table command executed
  sql = """
          CREATE TABLE employee (
          ID INTEGER PRIMARY KEY,
          fname VARCHAR(20),
          lname VARCHAR(30),
          gender CHAR(1),
          dob DATE);"""
  cursor.execute(sql)
  
  # Single Tuple inserted
  sql = """
          INSERT INTO employee
          VALUES (1007, "Will", "Olsen", "M", "24-SEP-1865");"""
  cursor.execute(sql)
  
  # Multiple Rows inserted
  List = [(1008, 'Rkb', 'Boss', 'M', "27-NOV-1864"),
          (1098, 'Sak', 'Rose', 'F', "27-DEC-1864"),
          (1908, 'Royal', 'Bassen', "F", "17-NOV-1894")]
  
  connection. executemany(
          "INSERT INTO employee VALUES (?, ?, ?, ?, ?)", List)
  
  print("Method-1\n")
  
  # Multiple Rows fetched from
  # the Database
  for row in connection.execute('SELECT * FROM employee ORDER BY ID'):
          print (row)
  
  print("\nMethod-2\n")
  
  # Method-2 to fetch multiple
  # rows
  sql = """
          SELECT * FROM employee ORDER BY ID;"""
  
  cursor.execute(sql)
  result = cursor.fetchall()
  
  for x in result:
      print(x)
  
  connection.commit()
  connection.close()

  Output:

  Method-1
  
  (1007, 'Will', 'Olsen', 'M', '24-SEP-1865')
  (1008, 'Rkb', 'Boss', 'M', '27-NOV-1864')
  (1098, 'Sak', 'Rose', 'F', '27-DEC-1864')
  (1908, 'Royal', 'Bassen', 'F', '17-NOV-1894')
  
  Method-2
  
  (1007, 'Will', 'Olsen', 'M', '24-SEP-1865')
  (1008, 'Rkb', 'Boss', 'M', '27-NOV-1864')
  (1098, 'Sak', 'Rose', 'F', '27-DEC-1864')
  (1908, 'Royal', 'Bassen', 'F', '17-NOV-1894')
  

  Note: This piece of code may not work on online interpreters, due to permission privileges to create/write database.