请详细回答如何在Python中实现线程安全，根据常见场景分别解答，要求每个场景的解答必须为独立段落，并且包含标题、内容和示例代码。
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1. **使用锁（Lock）实现线程安全**

   在多线程环境下，共享资源的访问可能会导致数据竞争。使用Python的`threading.Lock`可以确保同一时间只有一个线程可以访问共享资源。

   **示例代码：**
   ```python
   import threading

   lock = threading.Lock()
   shared_resource = 0

   def increment():
       global shared_resource
       with lock:
           shared_resource += 1

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

   for thread in threads:
       thread.join()

   print(f"Shared resource value: {shared_resource}")
   ```

2. **使用条件变量（Condition）实现线程同步**

   条件变量用于线程之间的通信，一个线程可以等待某个条件变量，另一个线程可以在满足条件时通知等待的线程。

   **示例代码：**
   ```python
   import threading

   condition = threading.Condition()
   shared_resource = 0

   def consumer():
       global shared_resource
       with condition:
           while shared_resource == 0:
               condition.wait()
           shared_resource -= 1
           print(f"Consumed, remaining: {shared_resource}")

   def producer():
       global shared_resource
       with condition:
           shared_resource += 1
           condition.notify()
           print(f"Produced, total: {shared_resource}")

   threads = []
   for i in range(5):
       threads.append(threading.Thread(target=consumer))
       threads.append(threading.Thread(target=producer))

   for thread in threads:
       thread.start()

   for thread in threads:
       thread.join()
   ```

3. **使用队列（Queue）实现生产者-消费者模式**

   `queue.Queue`是线程安全的队列实现，适用于生产者-消费者模式。生产者将数据放入队列，消费者从队列中取出数据。

   **示例代码：**
   ```python
   import queue
   import threading

   q = queue.Queue()

   def consumer():
       while True:
           item = q.get()
           if item is None:
               break
           print(f"Consumed: {item}")
           q.task_done()

   def producer():
       for i in range(10):
           q.put(i)
           print(f"Produced: {i}")

   threads = []
   for i in range(2):
       t = threading.Thread(target=consumer)
       threads.append(t)
       t.start()

   producer()
   q.join()

   for i in range(2):
       q.put(None)

   for thread in threads:
       thread.join()
   ```

4. **使用线程局部存储（ThreadLocal）避免共享状态**

   通过`threading.local()`可以创建线程局部存储，每个线程都有自己的独立存储空间，避免共享状态带来的线程安全问题。

   **示例代码：**
   ```python
   import threading

   thread_local = threading.local()

   def set_value(value):
       thread_local.value = value

   def get_value():
       return thread_local.value

   def thread_task(value):
       set_value(value)
       print(f"Thread {threading.current_thread().name} value: {get_value()}")

   threads = []
   for i in range(5):
       thread = threading.Thread(target=thread_task, args=(i,))
       threads.append(thread)
       thread.start()

   for thread in threads:
       thread.join()
   ```

这些场景展示了如何在Python中通过不同的方式实现线程安全，每种方法都有其适用的场景和优缺点。
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