Mastering Python and MySQL: Advanced Transaction Handling and Stored Procedures

# Python and MySQL Advanced Journey: Mastering Transaction Handling and Stored Procedures

In the current IT industry, the combination of Python and MySQL has become a golden pair for data processing and business logic implementation. This chapter will review the basic knowledge of these two technologies, laying a solid foundation for understanding subsequent, more in-depth topics.

## 1.1 Python Basics
Python is an interpreted, high-level programming language, known for its simple syntax and powerful library support. For beginners, understanding Python's data types, control structures, and functions is crucial. In addition, proficiently mastering libraries for database operations in Python, such as `mysql-connector-python`, is the bridge that connects Python to MySQL.

## 1.2 MySQL Basics
As one of the most popular open-source relational database management systems, MySQL is renowned for its high performance, reliability, and ease of use. Mastering basic MySQL concepts such as databases, tables, indexes, and SQL statements is a prerequisite for any database-related work. Understanding how to use SQL for data queries, updates, deletions, and insertions is the focal point of this section.

## 1.3 Connecting Python to MySQL
This section will demonstrate how to connect to and manipulate MySQL databases within Python code. This process involves installing and configuring database drivers, creating database connections, executing SQL commands, and handling query results. These skills are necessary prerequisites for further exploring advanced topics such as transaction handling and stored procedures. Below is a simple code example illustrating how to connect to a MySQL database from a Python script:

import mysql.connector

# Create a connection
conn = mysql.connector.connect(
     host='localhost',
     user='yourusername',
     password='yourpassword',
     database='yourdatabase'
)

# Create a cursor
cursor = conn.cursor()

# Execute an SQL query
cursor.execute("SELECT VERSION()")

# Fetch the query result
result = cursor.fetchone()

# Print version information
print(result)

# Close the connection
cursor.close()
conn.close()

Before proceeding, ensure that you have installed the `mysql-connector-python` library, which can be done by running `pip install mysql-connector-python`. Mastering this basic knowledge will help you better understand subsequent chapters on the application of Python and MySQL in transaction handling and stored procedures.

# 2. Theory and Practice of Transaction Handling

## 2.1 Concepts and ACID Properties of Transactions

### 2.1.1 Basic Definition of a Transaction
A transaction is a logical unit of work in a database management system, consisting of one or more operations that are submitted to the system as a whole, either all succeeding or all failing. In computer science, especially in the fields of databases and programming, the concept of a transaction is crucial.

In databases, transactions ensure data consistency and integrity. They allow users to execute multiple operations without worrying about partial success or failure, providing reliability for data processing. Transactions are typically used to handle complex operations, such as fund transfers, ensuring that funds deducted from one account are successfully added to another, with no possibility of a partial transfer.

Transactions have the following characteristics:
- Atomicity: Transactions execute as a whole; all included operations must either all complete or all not occur.
- Consistency: Transactions must transition the database from one consistent state to another.
- Isolation: Transactions execute independently, without interference from other transactions.
- Durability: Once a transaction is committed, the changes are permanent, even in the event of system failure.

### 2.1.2 In-depth Analysis of ACID Properties
ACID represents the four basic characteristics of a transaction: Atomicity, Consistency, Isolation, and Durability. These properties are fundamental to database transactions and the key mechanisms that ensure transaction reliability.

**Atomicity** requires that all operations within a transaction are either fully completed or not completed at all. It ensures the indivisibility of a transaction, meaning that in the event of a failure, rollback operations can be used to undo the effects of the transaction, ensuring its integrity.

**Consistency** ensures that a transaction transitions the database from one valid state to another, without introducing erroneous data due to transaction execution. The consistency of the database is guaranteed by both application logic and database integrity constraints.

**Isolation** is a characteristic of transactions that run independently, preventing inconsistencies due to the concurrent execution of multiple transactions that would result from overlapping execution. The isolation level defines the extent to which a transaction might be affected by the operations of other transactions.

**Durability** means that once a transaction is committed, its modifications to the database should be permanent, even if a system failure occurs.

The ACID properties together ensure the reliability of database transactions. When implementing transactions, the system must ensure that these four properties are adhered to, maintaining the integrity and correctness of the database.

## 2.2 Methods for Managing Transactions in Python

### 2.2.1 Using Transaction Control Statements
In Python, transaction control can be managed using control statements of the database connection object. For MySQL databases, we typically use the `mysql.connector` module or the `pymysql` module to manipulate databases. Here is a basic example of using the `mysql.connector` module for transaction control:

import mysql.connector

# Connect to the database
conn = mysql.connector.connect(user='root', password='', host='localhost', database='test')
cursor = conn.cursor()

try:
     # Start the transaction
     conn.start_transaction()

     # Execute multiple SQL statements
     cursor.execute("INSERT INTO table1 (column1) VALUES (%s)", (value1,))
     cursor.execute("UPDATE table2 SET column2 = %s WHERE condition", (value2,))

     # ***
     ***mit()
except Exception as e:
     # Rollback the transaction in case of an error
     conn.rollback()
     print("Error occurred:", e)
finally:
     # Close the cursor and connection
     cursor.close()
     conn.close()

In this code, `conn.start_transaction()` marks the start of a transaction, and all subsequent SQL statements are executed within the context of the transaction. Only after calling `***mit()` are these operations permanently saved to the database. If an exception occurs during execution, `conn.rollback()` is called to undo all previous operations, ensuring data consistency.

### 2.2.2 Transaction Isolation Levels and Lock Mechanisms
MySQL offers different isolation levels to balance transaction independence and performance overhead. Isolation levels include:
- `READ UNCOMMITTED`: Read uncommitted, the lowest isolation level, allows for dirty reads.
- `READ COMMITTED`: Read committed, allows for non-repeatable reads.
- `REPEATABLE READ`: Repeatable read, prevents dirty reads and non-repeatable reads but may cause phantom reads.
- `SERIALIZABLE`: Serializable, the highest isolation level, fully serial execution, can prevent all issues but has the greatest performance impact.

In Python, the behavior of transactions can be changed by setting the transaction isolation level. For example, using `mysql.connector` to set the transaction isolation level:

# Connect to the database
conn = mysql.connector.connect(user='root', password='', host='localhost', database='test')
cursor = conn.cursor()

# Set the transaction isolation level
cursor.execute("SET TRANSACTION ISOLATION LEVEL READ COMMITTED")

# Other transaction operations...

In MySQL, locks are an important means of implementing isolation levels. Database locks are divided into shared locks (read locks) and exclusive locks (write locks):

- Shared Lock (Share Lock): Allows a transaction to read a row and prevents other transactions from obtaining an exclusive lock on the same dataset.
- Exclusive Lock (Exclusive Lock): Allows a transaction that has obtained an exclusive lock to update or delete data, preventing other transactions from obtaining a shared lock or exclusive lock on the same dataset.

When a transaction obtains an exclusive lock on a row, other transactions cannot obtain a shared lock or an exclusive lock on that row until the current transaction is committed or rolled back. When implementing transactions, the rational use of lock mechanisms can effectively control concurrent access and prevent data inconsistencies.

## 2.3 Case Study Analysis: Transaction Processing Application

### 2.3.1 Writing Transaction Processing Scripts
Suppose we have a simple bank transfer scenario where we need to transfer funds from account A to account B; we need to use transactions to ensure the atomicity and consistency of the entire operation.

First, create a simple database and two account tables:

CREATE TABLE accounts (
     account_id INT PRIMARY KEY,
     balance DECIMAL(10, 2) NOT NULL
);

INSERT INTO accounts (account_id, balance) VALUES (1, 1000.00);
INSERT INTO accounts (account_id, balance) VALUES (2, 500.00);

Then, we can write a Python script to perform the transfer operation:

import mysql.connector
from mysql.connector import Error

def transfer_funds(conn, from_account, to_account, amount):
     try:
         cursor = conn.cursor()

         # Start the transaction
         conn.start_transaction()

         # Query account A's balance
         cursor.execute("SELECT balance FROM accounts WHERE account_id = %s", (from_account,))
         balance = cursor.fetchone()
         if balance[0] < amount:
             raise ValueError("Insufficient funds")
         balance = balance[0] - amount

         # Update account A's b