Get all keys in Redis database with python

Question

There is a post about a Redis command to get all available keys, but I would like to do it with Python.

Any way to do this?

Answer 1

Use scan_iter()

scan_iter() is superior to keys() for large numbers of keys because it gives you an iterator you can use rather than trying to load all the keys into memory.

I had a 1B records in my redis and I could never get enough memory to return all the keys at once.

SCANNING KEYS ONE-BY-ONE

Here is a python snippet using scan_iter() to get all keys from the store matching a pattern and delete them one-by-one:

import redis
r = redis.StrictRedis(host='localhost', port=6379, db=0)
for key in r.scan_iter("user:*"):
    # delete the key
    r.delete(key)

SCANNING IN BATCHES

If you have a very large list of keys to scan - for example, larger than >100k keys - it will be more efficient to scan them in batches, like this:

import redis
from itertools import izip_longest

r = redis.StrictRedis(host='localhost', port=6379, db=0)

# iterate a list in batches of size n
def batcher(iterable, n):
    args = [iter(iterable)] * n
    return izip_longest(*args)

# in batches of 500 delete keys matching user:*
for keybatch in batcher(r.scan_iter('user:*'),500):
    r.delete(*keybatch)

I benchmarked this script and found that using a batch size of 500 was 5 times faster than scanning keys one-by-one. I tested different batch sizes (3,50,500,1000,5000) and found that a batch size of 500 seems to be optimal.

Note that whether you use the scan_iter() or keys() method, the operation is not atomic and could fail part way through.

DEFINITELY AVOID USING XARGS ON THE COMMAND-LINE

I do not recommend this example I found repeated elsewhere. It will fail for unicode keys and is incredibly slow for even moderate numbers of keys:

redis-cli --raw keys "user:*"| xargs redis-cli del

In this example xargs creates a new redis-cli process for every key! that's bad.

I benchmarked this approach to be 4 times slower than the first python example where it deleted every key one-by-one and 20 times slower than deleting in batches of 500.