Getting started!
A comprehensive, fast, pure-Python memcached client library.
Basic Usage
from pymemcache.client.base import Client
client = Client(('localhost', 11211))
client.set('some_key', 'some_value')
result = client.get('some_key')
Using a memcached cluster
This will use a consistent hashing algorithm to choose which server to set/get the values from. It will also automatically rebalance depending on if a server goes down.
from pymemcache.client.hash import HashClient
client = HashClient([
('127.0.0.1', 11211),
('127.0.0.1', 11212)
])
client.set('some_key', 'some value')
result = client.get('some_key')
Serialization
import json
from pymemcache.client.base import Client
def json_serializer(key, value):
if type(value) == str:
return value, 1
return json.dumps(value), 2
def json_deserializer(key, value, flags):
if flags == 1:
return value
if flags == 2:
return json.loads(value)
raise Exception("Unknown serialization format")
client = Client(('localhost', 11211), serializer=json_serializer,
deserializer=json_deserializer)
client.set('key', {'a':'b', 'c':'d'})
result = client.get('key')
pymemcache provides a default pickle-based serializer:
from pymemcache.client.base import Client
from pymemcache import serde
class Foo(object):
pass
client = Client(('localhost', 11211),
serializer=serde.python_memcache_serializer,
deserializer=serde.python_memcache_deserializer)
client.set('key', Foo())
result client.get('key')
The serializer uses the highest pickle protocol available. In order to make sure multiple versions of Python can read the protocol version, you can specify the version with get_python_memcache_serializer
client = Client(('localhost', 11211),
serializer=serde.get_python_memcache_serializer(pickle_version=2),
deserializer=serde.python_memcache_deserializer)
Deserialization with python3
def json_deserializer(key, value, flags):
if flags == 1:
return value.decode('utf-8')
if flags == 2:
return json.loads(value.decode('utf-8'))
raise Exception("Unknown serialization format")
Key Constraints
This client implements the ASCII protocol of memcached. This means keys should not contain any of the following illegal characters: > Keys cannot have spaces, new lines, carriage returns, or null characters. We suggest that if you have unicode characters, or long keys, you use an effective hashing mechanism before calling this client. At Pinterest, we have found that murmur3 hash is a great candidate for this. Alternatively you can set allow_unicode_keys to support unicode keys, but beware of what unicode encoding you use to make sure multiple clients can find the same key.
Best Practices
- Always set the connect_timeout and timeout arguments in the :py:class:`pymemcache.client.base.Client` constructor to avoid blocking your process when memcached is slow. You might also want to enable the no_delay option, which sets the TCP_NODELAY flag on the connection's socket.
- Use the "noreply" flag for a significant performance boost. The "noreply" flag is enabled by default for "set", "add", "replace", "append", "prepend", and "delete". It is disabled by default for "cas", "incr" and "decr". It obviously doesn't apply to any get calls.
- Use get_many and gets_many whenever possible, as they result in less round trip times for fetching multiple keys.
- Use the "ignore_exc" flag to treat memcache/network errors as cache misses on calls to the get* methods. This prevents failures in memcache, or network errors, from killing your web requests. Do not use this flag if you need to know about errors from memcache, and make sure you have some other way to detect memcache server failures.