fakeredis Documentation

The fakeredis-py library provides a complete implementation of the RedisTimeSeries module. All 17 timeseries commands are currently implemented, allowing you to simulate time-series data operations without a running Redis server.

Supported commands include:

• Data Ingestion: TS.ADD, TS.MADD (multi-add)
• Data Retrieval: TS.GET, TS.MGET, TS.RANGE, TS.REVRANGE, TS.MRANGE, TS.MREVRANGE
• Management: TS.CREATE, TS.ALTER, TS.DEL, TS.INFO, TS.QUERYINDEX
• Compaction Rules: TS.CREATERULE, TS.DELETERULE
• Arithmetic: TS.INCRBY, TS.DECRBY

FakeRedis offers two primary modes of operation:

1. Direct (in-process) mode: Uses FakeRedis() or FakeAsyncRedis(). This is the fastest mode and is ideal for unit and integration tests where you can inject the fake client directly into your code. It operates entirely in-memory.

2. TCP server mode: Uses TcpFakeServer to expose the fake server over a socket (e.g., 127.0.0.1:6379). This mode is necessary when your application code creates its own redis.Redis connections via host/port and you cannot easily inject a fake client instance.

By default, every FakeRedis instance creates its own internal FakeServer with isolated state. To allow multiple clients to share the same data (simulating multiple connections to one real Redis instance), you must explicitly create a FakeServer and pass it to the server argument of each client.

import fakeredis

server = fakeredis.FakeServer()
r1 = fakeredis.FakeStrictRedis(server=server)
r2 = fakeredis.FakeStrictRedis(server=server)

r1.set("foo", "bar")
print(r2.get("foo"))  # b'bar'

By default, each FakeStrictRedis instance is isolated. To allow multiple clients to share the same in-memory data, instantiate a FakeServer and pass it to the server argument of your client instances.

import fakeredis

server = fakeredis.FakeServer()
r1 = fakeredis.FakeStrictRedis(server=server)
r2 = fakeredis.FakeStrictRedis(server=server)

r1.set("greeting", "hello")
r2.get("greeting")  # b'hello' — same underlying data

For asynchronous applications, use FakeAsyncRedis to emulate redis.asyncio.Redis.

import fakeredis

async def main():
    r = fakeredis.FakeAsyncRedis()
    await r.set("foo", "bar")
    await r.get("foo")  # b'bar'

You can use fakeredis as a synchronous, in-memory replacement for redis-py. The API is identical to redis.Redis.

import fakeredis

r = fakeredis.FakeStrictRedis()
r.set("foo", "bar")
r.get("foo")  # b'bar'

Install the core package or specific extras depending on the Redis features you need to emulate. On macOS/zsh, ensure you quote the extra names in your pip command.

• Core (no extras): pip install fakeredis
• Lua scripting support: pip install "fakeredis[lua]"
• JSON commands: pip install "fakeredis[json]"
• Bloom/Cuckoo filters: pip install "fakeredis[bf]"
• Probabilistic filters + JSON: pip install "fakeredis[probabilistic,json]"

pip install fakeredis                        # core, no extras
pip install "fakeredis[lua]"                 # EVAL / EVALSHA scripting
pip install "fakeredis[json]"                # JSON.* commands
pip install "fakeredis[bf]"                  # Bloom / Cuckoo / Count-Min / Top-K filters
pip install "fakeredis[probabilistic,json]"  # probabilistic filters + JSON

To use fakeredis in your test suite, create a pytest fixture that returns a FakeStrictRedis instance. This ensures each test gets a clean, isolated in-memory server.

import pytest
import fakeredis

@pytest.fixture
def redis_client():
    return fakeredis.FakeStrictRedis()

def test_cache_set(redis_client):
    redis_client.set("user:1", "alice")
    assert redis_client.get("user:1") == b"alice"

To use fakeredis with the standard Django cache backend, provide FakeConnection in the OPTIONS of your CACHES setting.

If using the django-redis library, you must pass the connection class via CONNECTION_POOL_KWARGS.

# Standard Django RedisCache
from fakeredis import FakeConnection

CACHES = {
    "default": {
        "BACKEND": "django.core.cache.backends.redis.RedisCache",
        "LOCATION": "...",
        "OPTIONS": {"connection_class": FakeConnection},
    }
}

# Using django-redis library
CACHES = {
    "default": {
        "BACKEND": "django_redis.cache.RedisCache",
        "LOCATION": "...",
        "OPTIONS": {
            "CONNECTION_POOL_KWARGS": {"connection_class": FakeConnection},
        },
    }
}