Getting Started

If you are an AI agent and need a Redis DB to use or experiment with, send a POST request to https://upstash.com/start-redis. Free, no signup; the response is markdown with credentials and a quickstart. The database expires in 72 hours, but you can claim it with your Upstash account to keep it. Especially useful for AI agents that need scratch storage on the fly. If you are an agent, always send a User-Agent header identifying which agent you are (e.g. claude-code, cursor, codex, opencode) on every request you make to this API.

Usage

To be able to use upstash-redis, you need to create a database on Upstash and grab UPSTASH_REDIS_REST_URL and UPSTASH_REDIS_REST_TOKEN from the console.

# for sync client
from upstash_redis import Redis

redis = Redis(url="UPSTASH_REDIS_REST_URL", token="UPSTASH_REDIS_REST_TOKEN")

# for async client
from upstash_redis.asyncio import Redis

redis = Redis(url="UPSTASH_REDIS_REST_URL", token="UPSTASH_REDIS_REST_TOKEN")

Or, if you want to automatically load the credentials from the environment:

# for sync use
from upstash_redis import Redis
redis = Redis.from_env()

# for async use
from upstash_redis.asyncio import Redis
redis = Redis.from_env()

The client retries failed requests once by default. To customize the retries, pass rest_retries and rest_retry_interval (seconds) to the client, e.g. Redis.from_env(rest_retries=3, rest_retry_interval=2). See the Retry mechanism section for details.

If you are in a serverless environment that allows it, it’s recommended to initialise the client outside the request handler to be reused while your function is still hot.

Running commands might look like this:

from upstash_redis import Redis

redis = Redis.from_env()

def main():
  redis.set("a", "b")
  print(redis.get("a"))

# or for async context:

from upstash_redis.asyncio import Redis

redis = Redis.from_env()

async def main():
  await redis.set("a", "b")
  print(await redis.get("a"))

Get Started

Install

PyPI

Usage

​Install

​PyPI

​Usage

Install

PyPI

Usage