Working with Keyspaces

Usually when working with Redis, developers often group a collection of keys that are similar under a keyspace. Use a key pattern with a prefix and curly braces around the unique identifier for that record. For example, for a list of followers for user ids 1 and 2, I might have keys F{1} and F{2}.

This keyspace functions as a virtual table, like what you might have in a typical RDBMS. Except that each key is really independent. We just use a naming convention to group them together.

Example of a Sorted Set Keyspace

RedPipe gives you a way to easily manipulate these keyspaces.

Here’s an example of a sorted set:

class Followers(redpipe.SortedSet):
    keyspace = 'F'
    connection = 'default'

key1 = '1'
key2 = '2'
with redpipe.pipeline(name='default') as pipe:
    f = Followers(pipe=pipe)
    f.zadd(key1, 'a', score=1)
    f.zadd(key2, 'a', score=2)
    f1_members = f.zrange(key1, 0, -1)
    f2_members = f.zrange(key2, 0, -1)
    pipe.execute()

print(f1_members)
print(f2_members)

We can specify what named connection we want to use with the connection variable. Or you can omit it if you are using just one default connection to redis.

You will notice the interface provided by the keyspace object redpipe.SortedSet looks just like redis-py functions. Except it omits the name of the key. That’s because the key name is already specified in the constructor.

Supported Keyspace Types

All of the redis-py sorted set functions are exposed on the in the example above.

In a similar way, we support the other Redis primitives:

• strings
• sets
• lists
• hashes
• sorted sets
• hyperloglog
• geo (in progress)

The supported commands are limited to single key operations.

Fields in Hashes

Often you want to store data in Hashes that maps to a particular data type. For example, a boolean flag, an integer, or a float. Redis stores all the values as byte strings and doesn’t interpret. We can set up explicit mappings for these data types in redpipe.Hash. This is not required but it makes life easier.

class User(redpipe.Hash):
    keyspace = 'U'
    fields = {
        'first_name': redpipe.StringField,
        'last_name': redpipe.StringField,
        'admin': redpipe.BooleanField,
        'last_seen': redpipe.FloatField,
    }

You can see we defined a few fields and gave them types that we can use in python. The fields will perform basic data validation on the input and correctly serialize and deserialize from a Redis hash key.

key = '1'
with redpipe.autoexec() as pipe:
    u = User(pipe=pipe)
    data = {
        'first_name': 'Fred',
        'last_name': 'Flitstone',
        'admin': True,
        'last_seen': time.time(),
    }
    u.hmset(key, data)
    ref = u.hgetall(key)

assert(ref == data)

You can see this allows us to set booleans, ints and other data types into the hash and get the same values back.