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SQL usando Python | Conjunto 3 (Manejo de datos de gran tamaño)

Se recomienda pasar SQL usando Python | Conjunto 1 y SQL usando Python y SQLite | Conjunto 2 En los artículos anteriores, los registros de la base de datos se limitaban a tamaños pequeños y a una sola tupla. Este artículo explicará cómo escribir y recuperar datos grandes de la base de datos utilizando el módulo SQLite3 que cubre todas las excepciones. Una forma sencilla es ejecutar la consulta y utilizar fetchall(). Esto ya se ha discutido en el SET 1.
    ejecutar script() 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)
    PYTHON
    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() 
    Producción:
    [(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. ejecutar muchos() 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. PYTHON
    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() 
    Producción:
    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. PYTHON
    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() 
    Producción:
    ('A' 'B' 2008) ('C' 'D' 2008) ('E' 'F' 2010) 
    Obtener datos grandes PYTHON
    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-1n') # Multiple Rows fetched from # the Database for row in connection.execute('SELECT * FROM employee ORDER BY ID'): print (row) print('nMethod-2n') # 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() 
    Producción:
    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.

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