管道与事务

了解如何使用 Redis 管道和事务

Redis 允许您将一系列命令一起批量发送到服务器。您可以使用两种类型的批量处理方式

管道通过在一次通信中将多个命令一起发送到服务器，从而避免了网络和处理开销。然后，服务器将所有响应打包在一次通信中发送回来。有关更多信息，请参阅管道页面。
事务保证所有包含的命令将执行完毕，而不被其他客户端的命令中断。有关更多信息，请参阅事务页面。

执行管道

要在管道中执行命令，首先需要创建一个管道对象，然后使用类似于标准命令方法（例如，set() 和 get()）的方法向其添加命令。命令在管道中进行缓冲，并且仅在您调用管道对象的 execute() 方法时执行。此方法返回一个列表，其中按顺序包含所有命令的结果。

请注意，管道的命令方法总是返回原始管道对象，因此您可以“链式”调用多个命令，如下面的示例所示

Python

"""
Code samples for vector database quickstart pages:
    https://redis.ac.cn/docs/latest/develop/get-started/vector-database/
"""
import redis

r = redis.Redis(decode_responses=True)

pipe = r.pipeline()

for i in range(5):
    pipe.set(f"seat:{i}", f"#{i}")

set_5_result = pipe.execute()
print(set_5_result)  # >>> [True, True, True, True, True]

pipe = r.pipeline()

# "Chain" pipeline commands together.
get_3_result = pipe.get("seat:0").get("seat:3").get("seat:4").execute()
print(get_3_result)  # >>> ['#0', '#3', '#4']

r.set("shellpath", "/usr/syscmds/")

with r.pipeline() as pipe:
    # Repeat until successful.
    while True:
        try:
            # Watch the key we are about to change.
            pipe.watch("shellpath")

            # The pipeline executes commands directly (instead of
            # buffering them) from immediately after the `watch()`
            # call until we begin the transaction.
            current_path = pipe.get("shellpath")
            new_path = current_path + ":/usr/mycmds/"

            # Start the transaction, which will enable buffering
            # again for the remaining commands.
            pipe.multi()

            pipe.set("shellpath", new_path)

            pipe.execute()

            # The transaction succeeded, so break out of the loop.
            break
        except redis.WatchError:
            # The transaction failed, so continue with the next attempt.
            continue

get_path_result = r.get("shellpath")
print(get_path_result)  # >>> '/usr/syscmds/:/usr/mycmds/'

r.set("shellpath", "/usr/syscmds/")


def watched_sequence(pipe):
    current_path = pipe.get("shellpath")
    new_path = current_path + ":/usr/mycmds/"

    pipe.multi()

    pipe.set("shellpath", new_path)


trans_result = r.transaction(watched_sequence, "shellpath")
print(trans_result)  # True

get_path_result = r.get("shellpath")
print(get_path_result)  # >>> '/usr/syscmds/:/usr/mycmds/'

执行事务

默认情况下，管道实际上会作为一个事务执行（也就是说，所有命令都在一个不间断的序列中执行）。但是，如果您需要关闭此行为，可以在创建管道时将 transaction 参数设置为 False

pipe = r.pipeline(transaction=False)

监视键以检测更改

Redis 支持乐观锁来避免对不同键的不一致更新。基本思想是在处理更新时，监视事务中使用的任何键的更改。如果监视的键确实发生了更改，您必须使用键的最新数据重新开始更新。有关乐观锁的更多信息，请参阅事务页面。

下面的示例展示了如何重复尝试对监视的键执行事务，直到成功为止。代码读取表示命令 shell 的 PATH 变量的字符串，然后在尝试写回之前向字符串附加新的命令路径。如果在写入之前监视的键被另一个客户端修改，事务将中止并抛出 WatchError 异常，然后循环再次执行以进行另一次尝试。否则，循环将成功终止。

Python

"""
Code samples for vector database quickstart pages:
    https://redis.ac.cn/docs/latest/develop/get-started/vector-database/
"""
import redis

r = redis.Redis(decode_responses=True)

pipe = r.pipeline()

for i in range(5):
    pipe.set(f"seat:{i}", f"#{i}")

set_5_result = pipe.execute()
print(set_5_result)  # >>> [True, True, True, True, True]

pipe = r.pipeline()

# "Chain" pipeline commands together.
get_3_result = pipe.get("seat:0").get("seat:3").get("seat:4").execute()
print(get_3_result)  # >>> ['#0', '#3', '#4']

r.set("shellpath", "/usr/syscmds/")

with r.pipeline() as pipe:
    # Repeat until successful.
    while True:
        try:
            # Watch the key we are about to change.
            pipe.watch("shellpath")

            # The pipeline executes commands directly (instead of
            # buffering them) from immediately after the `watch()`
            # call until we begin the transaction.
            current_path = pipe.get("shellpath")
            new_path = current_path + ":/usr/mycmds/"

            # Start the transaction, which will enable buffering
            # again for the remaining commands.
            pipe.multi()

            pipe.set("shellpath", new_path)

            pipe.execute()

            # The transaction succeeded, so break out of the loop.
            break
        except redis.WatchError:
            # The transaction failed, so continue with the next attempt.
            continue

get_path_result = r.get("shellpath")
print(get_path_result)  # >>> '/usr/syscmds/:/usr/mycmds/'

r.set("shellpath", "/usr/syscmds/")


def watched_sequence(pipe):
    current_path = pipe.get("shellpath")
    new_path = current_path + ":/usr/mycmds/"

    pipe.multi()

    pipe.set("shellpath", new_path)


trans_result = r.transaction(watched_sequence, "shellpath")
print(trans_result)  # True

get_path_result = r.get("shellpath")
print(get_path_result)  # >>> '/usr/syscmds/:/usr/mycmds/'

由于这是一个常见的模式，该库包含一个名为 transaction() 的便捷方法，用于处理监视键、执行事务以及在必要时重试的代码。将实现您的主要事务代码的函数以及要监视的键传递给 transaction() 方法。下面的示例实现了与前一个示例相同的基础事务，但这回使用了 transaction()。请注意，transaction() 无法自动添加 multi() 调用，因此您仍然必须将其正确地放置在您的事务函数中。

Python

"""
Code samples for vector database quickstart pages:
    https://redis.ac.cn/docs/latest/develop/get-started/vector-database/
"""
import redis

r = redis.Redis(decode_responses=True)

pipe = r.pipeline()

for i in range(5):
    pipe.set(f"seat:{i}", f"#{i}")

set_5_result = pipe.execute()
print(set_5_result)  # >>> [True, True, True, True, True]

pipe = r.pipeline()

# "Chain" pipeline commands together.
get_3_result = pipe.get("seat:0").get("seat:3").get("seat:4").execute()
print(get_3_result)  # >>> ['#0', '#3', '#4']

r.set("shellpath", "/usr/syscmds/")

with r.pipeline() as pipe:
    # Repeat until successful.
    while True:
        try:
            # Watch the key we are about to change.
            pipe.watch("shellpath")

            # The pipeline executes commands directly (instead of
            # buffering them) from immediately after the `watch()`
            # call until we begin the transaction.
            current_path = pipe.get("shellpath")
            new_path = current_path + ":/usr/mycmds/"

            # Start the transaction, which will enable buffering
            # again for the remaining commands.
            pipe.multi()

            pipe.set("shellpath", new_path)

            pipe.execute()

            # The transaction succeeded, so break out of the loop.
            break
        except redis.WatchError:
            # The transaction failed, so continue with the next attempt.
            continue

get_path_result = r.get("shellpath")
print(get_path_result)  # >>> '/usr/syscmds/:/usr/mycmds/'

r.set("shellpath", "/usr/syscmds/")


def watched_sequence(pipe):
    current_path = pipe.get("shellpath")
    new_path = current_path + ":/usr/mycmds/"

    pipe.multi()

    pipe.set("shellpath", new_path)


trans_result = r.transaction(watched_sequence, "shellpath")
print(trans_result)  # True

get_path_result = r.get("shellpath")
print(get_path_result)  # >>> '/usr/syscmds/:/usr/mycmds/'

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