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SQL utilizzando Python | Set 3 (Gestione di dati di grandi dimensioni)

Si consiglia di passare SQL utilizzando Python | Insieme 1 E SQL utilizzando Python e SQLite | Insieme 2 Negli articoli precedenti i record del database erano limitati a piccole dimensioni e a tuple singole. Questo articolo spiegherà come scrivere e recuperare dati di grandi dimensioni dal database utilizzando il modulo SQLite3 che copre tutte le eccezioni. Un modo semplice è eseguire la query e utilizzare fetchall(). Questo è già stato discusso nel SET 1.
    eseguiscript() 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()
    Produzione: 
    [(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. eseguimolti() 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()
    Produzione: 
    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()
    Produzione: 
    ('A' 'B' 2008) ('C' 'D' 2008) ('E' 'F' 2010)
    Recupera dati di grandi dimensioni 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()
    Produzione: 
    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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