MemorystoreRedis

A Redis cluster running on Google Cloud's Memorystore service.

Like all Resources, this class configures itself across multiple Environments.

For more information see the official documentation.

NOTE: This resource can only be accessed from within the same VPC it is created in. Use ComputeEngineRedis to create a Redis instance that can be accessed from outside the VPC.

Example Usage

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import launchflow as lf
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# Automatically creates / connects to a Memorystore Redis cluster in your GCP project
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memorystore = lf.gcp.MemorystoreRedis("my-redis-cluster")
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# Set a key-value pair
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client = memorystore.redis()
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client.set("my-key", "my-value")
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# Async compatible
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async_client = await memorystore.redis_async()
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await async_client.set("my-key", "my-value")
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initialization

Create a new Memorystore Redis resource.

Args:

• name (str): The name of the Redis VM resource. This must be globally unique.
• memory_size_gb (int): The memory size of the Redis instance in GB. Defaults to 1.

inputs

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MemorystoreRedis.inputs(environment_state: EnvironmentState) -> MemoryStoreInputs
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Get the inputs for the Memorystore Redis resource.

Args:

• environment_state (EnvironmentState): The environment to get inputs for

Returns:

• MemoryStoreInputs: The inputs for the Memorystore Redis resource.

django_settings

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MemorystoreRedis.django_settings()
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Returns a Django settings dictionary for connecting to the Memorystore Redis cluster.

Example usage:

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import launchflow as lf
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memorystore = lf.gcp.MemorystoreRedis("my-redis-cluster")
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# settings.py
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CACHES = {
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    # Connect Django's cache backend to the Memorystore Redis cluster
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    "default": memorystore.django_settings(),
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}
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redis

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MemorystoreRedis.redis()
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Get a Generic Redis Client object from the redis-py library.

Returns:

• The Generic Redis Client from the redis-py library.

redis_async

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async MemorystoreRedis.redis_async()
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Get an Async Redis Client object from the redis-py library.

Returns:

• The Async Redis Client object from the redis-py library.