张贴答案。我花了相当长的时间来弄清楚所有这些，所以希望它会为你们中的一些人节省保存时间。Redisearch确实是一项令人惊叹的技术，值得许多人使用。
首先，你必须创建一个索引来使用redisearch：

from redis.commands.search.query import Query
from redis.commands.search.field import TextField, NumericField
from redis.commands.search.indexDefinition import IndexDefinition, IndexType
from redis.commands.search.aggregation import AggregateRequest, Asc, Desc

import redis

client = redis.Redis(
        host=redis_host,
        port=redis_port,
        password=redis_password,
        decode_responses=True,
    )

index_name = 'idx:flowers'
index = client.ft(index_name)

#  check if index exists if not then create
try:
    index.info()
except:
    schema = (
        TextField('name', weight=0.7),  #  textfields can also be sortable
        TextField('type'),
        NumericField('length', sortable=True),  #  numericfields cannot have weights
        NumericField('rating', sortable=True),
    )
    #  index creation. 
    #  using IndexDefinition(prefix= will index automagically all redis keys that have this prefix
    client.ft(index_name).create_index(schema, definition=IndexDefinition(prefix=['flower:']))

    #  since the index is new we need to load the data (if it does not exist on redis already)

    flowers = [
        {'name': 'gladiola', 'type': 'cactus', 'length': 22, 'rating': 3.57, 'color': 'violet'},
        {'name': 'eleanor', 'type': 'cactus,pine', 'length': 15, 'rating': 4.34, 'color': 'brown'},
        {'name': 'loveme', 'type': 'berry', 'length': 13, 'rating': 5, 'color': 'blue'},
    ]

    for i, flower in enumerate(flowers):
        pipe = client.pipeline()
        pipe.hset(name='flower:' + str(i), key='name', value=flower['name'])
        pipe.hset(name='flower:' + str(i), key='type', value=flower['type'])
        pipe.hset(name='flower:' + str(i), key='length', value=flower['length'])
        pipe.hset(name='flower:' + str(i), key='rating', value=flower['rating'])
        pipe.hset(name='flower:' + str(i), key='color', value=flower['color'])
        pipe.execute()

所有这些散列都将被索引，因为它们的键具有前缀'flower：'
搜索：

#  first we need to get the index we are going to work with
index = client.ft(index_name)

#  wildcard search from both sides on all searchable fields
results = index.search(Query('*actu*'))  
results = results.docs
for result in results:
    print(result.__dict__)

#  sort by a sortable field in ascending order (you can sort by a non-sortable field but it will be slower)
results = index.search(Query('*actu*').sort_by(field='length', asc=True))

#  pagination. 'num' is size of the page
results = index.search(Query('*actu*').paging(offset=0, num=10))

#  search a specific field
results = index.search(Query('@name:*actu*'))

#  search specific fields - OR operation
results = index.search(Query('@name|type:*actu*'))

#  search specific fields - AND operation
results = index.search(Query('@name:*actu* @type:*actu*'))

#  sort by multiple fields - length and rating. We need to use Aggregation to achieve this
request = AggregateRequest(
    query='@name|type:*actu*'
    ).sort_by(
        Asc('@length'), 
        Desc('@rating'), 
    ).limit(  #  pagination
        0, 10
    ).load(  #  we need to indicate the fields we want to get in results
        '@name', 
        '@type', 
        '@length', 
        '@rating', 
        '@color', 
    )
#  perform aggregate search
results = index.aggregate(request)
print(results.rows)

指出错误和改进，我很乐意编辑答案。