Pipelines and transactions

Redis lets you send a sequence of commands to the server together in a batch. There are two types of batch that you can use:

• Pipelines avoid network and processing overhead by sending several commands to the server together in a single communication. The server then sends back a single communication with all the responses. See the [Pipelining]({{< relref "/develop/using-commands/pipelining" >}}) page for more information.
• Transactions guarantee that all the included commands will execute to completion without being interrupted by commands from other clients. See the [Transactions]({{< relref "develop/using-commands/transactions" >}}) page for more information.

Execute a pipeline

To execute commands in a pipeline, you first create a pipeline object and then add commands to it using methods that resemble the standard command methods (for example, set() and get()). The commands are buffered in the pipeline and only execute when you call the execute() method on the pipeline object. This method returns a list that contains the results from all the commands in order.

Note that the command methods for a pipeline always return the original pipeline object, so you can "chain" several commands together, as the example below shows:

{{< clients-example set="pipe_trans_tutorial" step="basic_pipe" lang_filter="Python" description="Foundational: Use pipelines to batch multiple commands together and reduce network round trips" difficulty="beginner" >}} {{< /clients-example >}}

Execute a transaction

A pipeline actually executes as a transaction by default (that is to say, all commands are executed in an uninterrupted sequence). However, if you need to switch this behavior off, you can set the transaction parameter to False when you create the pipeline:

pipe = r.pipeline(transaction=False)

Watch keys for changes

Redis supports optimistic locking to avoid inconsistent updates to different keys. The basic idea is to watch for changes to any keys that you use in a transaction while you are processing the updates. If the watched keys do change, you must restart the updates with the latest data from the keys. See [Transactions]({{< relref "develop/using-commands/transactions" >}}) for more information about optimistic locking.

The example below shows how to repeatedly attempt a transaction with a watched key until it succeeds. The code reads a string that represents a PATH variable for a command shell, then appends a new command path to the string before attempting to write it back. If the watched key is modified by another client before writing, the transaction aborts with a WatchError exception, and the loop executes again for another attempt. Otherwise, the loop terminates successfully.

{{< clients-example set="pipe_trans_tutorial" step="trans_watch" lang_filter="Python" description="Optimistic locking: Use WATCH to monitor keys for changes and retry transactions when conflicts occur" difficulty="intermediate" >}} {{< /clients-example >}}

Because this is a common pattern, the library includes a convenience method called transaction() that handles the code to watch keys, execute the transaction, and retry if necessary. Pass transaction() a function that implements your main transaction code, and also pass the keys you want to watch. The example below implements the same basic transaction as the previous example but this time using transaction(). Note that transaction() can't add the multi() call automatically, so you must still place this correctly in your transaction function.

{{< clients-example set="pipe_trans_tutorial" step="watch_conv_method" lang_filter="Python" description="Optimistic locking with convenience method: Use the transaction() helper to simplify watched transaction patterns" difficulty="intermediate" >}} {{< /clients-example >}}