ProgrammingError:在线程中创建的SQLite对象只能在同一个线程中使用

Question

我对编程很新.我之前尝试过MySQL,但现在我第一次在python烧瓶网站上使用SQLite了.所以也许我使用MySQL语法而不是SQLite,但我似乎无法找到问题.

Piece of my code: 

@app.route('/register', methods=['GET', 'POST'])
def register():
    form = RegisterForm(request.form)
    if request.method=='POST' and form.validate():
        name =  form.name.data 
        email = form.email.data
        username = form.username.data
        password = sha256_crypt.encrypt(str(form.password.data))

        c.execute("INSERT INTO users(name,email,username,password) 
        VALUES(?,?,?,?)", (name, email, username, password))

        conn.commit

        conn.close()

The error:
 File "C:\Users\app.py", line 59, in register c.execute("INSERT INTO users(name,email,username,password) VALUES(?,?,?,?)", (name, email, username, password))
 ProgrammingError: SQLite objects created in a thread can only be used in that 
 same thread.The object was created in thread id 23508 and this is thread id 
 22640

这是否意味着我不能在HTML文件中使用名称,电子邮件用户名和密码？我该如何解决这个问题？

谢谢.

Answer 1

在与数据库建立连接的位置添加以下内容.

conn = sqlite3.connect('your.db', check_same_thread=False)

Answer 2

你的光标'c'不是在同一个线程中创建的; 它可能是在运行Flask应用程序时初始化的.

您可能希望以相同的方法生成SQLite对象(连接和光标),例如:

  @app.route('/')
  def dostuff():
    with sql.connect("database.db") as con:
      name = "bob"
      cur = con.cursor()
      cur.execute("INSERT INTO students (name) VALUES (?)",(name))
      con.commit()
      msg = "Done"

Answer 3

engine = create_engine(
'sqlite:///restaurantmenu.db',
connect_args={'check_same_thread': False}
)

为我工作

Answer 4

你可以试试这个：

engine=create_engine('sqlite:///data.db', echo=True, connect_args={"check_same_thread": False})

这对我有用

Answer 5

就我而言，我在创建 sqlite 引擎的两个 python 文件中遇到了同样的问题，因此可能在不同的线程上运行。在此处阅读 SQLAlchemy 文档，似乎在两个文件中都使用单例技术更好：

# maintain the same connection per thread
from sqlalchemy.pool import SingletonThreadPool
engine = create_engine('sqlite:///mydb.db',
                poolclass=SingletonThreadPool)

它不能解决所有情况，这意味着我偶尔会遇到相同的错误，但我可以轻松克服它，刷新浏览器页面。因为我只用它来调试我的代码，所以这对我来说没问题。对于更永久的解决方案，应该选择另一个数据库，如 PostgreSQL 或其他数据库

Answer 6

正如https://docs.python.org/3/library/sqlite3.html中提到的，并由 @Snidhi Sofpro 在评论中指出

默认情况下，check_same_thread 为 True，并且只有创建线程可以使用该连接。如果设置为 False，则返回的连接可以在多个线程之间共享。当使用具有相同连接的多个线程时，用户应将写入操作序列化，以避免数据损坏。

实现序列化的一种方法：

import threading
import sqlite3
import queue
import traceback
import time
import random

work_queue = queue.Queue()

def sqlite_worker():
    con = sqlite3.connect(':memory:', check_same_thread=False)
    cur = con.cursor()
    cur.execute('''
        CREATE TABLE IF NOT EXISTS test (
            id INTEGER PRIMARY KEY AUTOINCREMENT,
            text TEXT,
            source INTEGER,
            seq INTEGER
        )
    ''')
    while True:
        try:
            (sql, params), result_queue = work_queue.get()
            res = cur.execute(sql, params)
            con.commit()
            result_queue.put(res)
        except Exception as e:
            traceback.print_exc()

threading.Thread(target=sqlite_worker, daemon=True).start()

def execute_in_worker(sql, params):
    # you might not really need the results if you only use this
    # for writing unless you use something like https://www.sqlite.org/lang_returning.html
    result_queue = queue.Queue()
    work_queue.put(((sql, params), result_queue))
    return result_queue.get(timeout=5)

def insert_test_data(seq):
    time.sleep(random.randint(0, 100) / 100)
    execute_in_worker(
        'INSERT INTO test (text, source, seq) VALUES (?, ?, ?)',
        ['foo', threading.get_ident(), seq]
    )

threads = []
for i in range(10):
    thread = threading.Thread(target=insert_test_data, args=(i,))
    threads.append(thread)
    thread.start()

for thread in threads:
    thread.join()

for res in execute_in_worker('SELECT * FROM test', []):
    print(res)

# (1, 'foo', 139949462500928, 9)
# (2, 'foo', 139949496071744, 5)
# (3, 'foo', 139949479286336, 7)
# (4, 'foo', 139949487679040, 6)
# (5, 'foo', 139949854099008, 3)
# (6, 'foo', 139949470893632, 8)
# (7, 'foo', 139949862491712, 2)
# (8, 'foo', 139949845706304, 4)
# (9, 'foo', 139949879277120, 0)
# (10, 'foo', 139949870884416, 1)

正如您所看到的，数据是乱序插入的，但仍然是在循环中一一处理while。

• https://docs.python.org/3/library/queue.html
• https://docs.python.org/3/library/threading.html#threading.Thread.join
• https://docs.python.org/3/library/threading.html#threading.get_ident