缓存:Memcached Redis
一.Memcached
Memcached 是一个高性能的分布式内存对象缓存系统,用于动态Web应用以减轻数据库负载。它通过在内存中缓存数据和对象来减少读取数据库的次数,从而提高动态、数据库驱动网站的速度。Memcached基于一个存储键/值对的hashmap。其守护进程(daemon )是用C写的,但是客户端可以用任何语言来编写,并通过memcached协议与守护进程通信。
1、Memcached安装配置
#安装倚赖包
yum install libevent-devel
#安装软件
yum -y install memcached
#启动服务
/usr/bin/memcached -d -u root -l 192.168.7.102 -m 1024 -p 11211
#命令解释
'''
启动Memcache 常用参数
-p <num> 设置TCP端口号(默认不设置为: 11211)
-U <num> UDP监听端口(默认: 11211, 0 时关闭)
-l <ip_addr> 绑定地址(默认:所有都允许,无论内外网或者本机更换IP,有安全隐患,若设置为127.0.0.1就只能本机访问)
-d 以daemon方式运行
-u <username> 绑定使用指定用于运行进程<username>
-m <num> 允许最大内存用量,单位M (默认: 64 MB)
-P <file> 将PID写入文件<file>,这样可以使得后边进行快速进程终止, 需要与-d 一起使用
'''
2、Memcached命令
#测试连接Memcached
telnet hostip port
telnet 192.168.7.102 11211
#例子
'''
telnet 192.168.7.102 11211
Trying 192.168.7.102...
Connected to 192.168.7.102.
Escape character is '^]'. #连接成功之后输入命令即可
''' 存储命令: set/add/replace/append/prepend/cas
获取命令: get/gets
其他命令: delete/stats..
3、python操作Memcached
#linxu下安装pip
yum -y install pip
#安装python操作Memcached模块
pip install python-memcached
4、Memcached常用操作
import memcache #导入模块
mc = memcache.Client(['10.211.55.4:12000'], debug=True) #连接memcached
mc.set("foo", "bar")#插入一条数据
ret = mc.get('foo')#获取一条数据的值
print ret
5、Memcached源码
class Client(threading.local):
"""Object representing a pool of memcache servers. See L{memcache} for an overview. In all cases where a key is used, the key can be either:
1. A simple hashable type (string, integer, etc.).
2. A tuple of C{(hashvalue, key)}. This is useful if you want
to avoid making this module calculate a hash value. You may
prefer, for example, to keep all of a given user's objects on
the same memcache server, so you could use the user's unique
id as the hash value. @group Setup: __init__, set_servers, forget_dead_hosts,
disconnect_all, debuglog
@group Insertion: set, add, replace, set_multi
@group Retrieval: get, get_multi
@group Integers: incr, decr
@group Removal: delete, delete_multi
@sort: __init__, set_servers, forget_dead_hosts, disconnect_all,
debuglog,\ set, set_multi, add, replace, get, get_multi,
incr, decr, delete, delete_multi
"""
_FLAG_PICKLE = 1 << 0
_FLAG_INTEGER = 1 << 1
_FLAG_LONG = 1 << 2
_FLAG_COMPRESSED = 1 << 3 _SERVER_RETRIES = 10 # how many times to try finding a free server. # exceptions for Client
class MemcachedKeyError(Exception):
pass class MemcachedKeyLengthError(MemcachedKeyError):
pass class MemcachedKeyCharacterError(MemcachedKeyError):
pass class MemcachedKeyNoneError(MemcachedKeyError):
pass class MemcachedKeyTypeError(MemcachedKeyError):
pass class MemcachedStringEncodingError(Exception):
pass def __init__(self, servers, debug=0, pickleProtocol=0,
pickler=pickle.Pickler, unpickler=pickle.Unpickler,
compressor=zlib.compress, decompressor=zlib.decompress,
pload=None, pid=None,
server_max_key_length=None, server_max_value_length=None,
dead_retry=_DEAD_RETRY, socket_timeout=_SOCKET_TIMEOUT,
cache_cas=False, flush_on_reconnect=0, check_keys=True):
"""Create a new Client object with the given list of servers. @param servers: C{servers} is passed to L{set_servers}.
@param debug: whether to display error messages when a server
can't be contacted.
@param pickleProtocol: number to mandate protocol used by
(c)Pickle.
@param pickler: optional override of default Pickler to allow
subclassing.
@param unpickler: optional override of default Unpickler to
allow subclassing.
@param pload: optional persistent_load function to call on
pickle loading. Useful for cPickle since subclassing isn't
allowed.
@param pid: optional persistent_id function to call on pickle
storing. Useful for cPickle since subclassing isn't allowed.
@param dead_retry: number of seconds before retrying a
blacklisted server. Default to 30 s.
@param socket_timeout: timeout in seconds for all calls to a
server. Defaults to 3 seconds.
@param cache_cas: (default False) If true, cas operations will
be cached. WARNING: This cache is not expired internally, if
you have a long-running process you will need to expire it
manually via client.reset_cas(), or the cache can grow
unlimited.
@param server_max_key_length: (default SERVER_MAX_KEY_LENGTH)
Data that is larger than this will not be sent to the server.
@param server_max_value_length: (default
SERVER_MAX_VALUE_LENGTH) Data that is larger than this will
not be sent to the server.
@param flush_on_reconnect: optional flag which prevents a
scenario that can cause stale data to be read: If there's more
than one memcached server and the connection to one is
interrupted, keys that mapped to that server will get
reassigned to another. If the first server comes back, those
keys will map to it again. If it still has its data, get()s
can read stale data that was overwritten on another
server. This flag is off by default for backwards
compatibility.
@param check_keys: (default True) If True, the key is checked
to ensure it is the correct length and composed of the right
characters.
"""
super(Client, self).__init__()
self.debug = debug
self.dead_retry = dead_retry
self.socket_timeout = socket_timeout
self.flush_on_reconnect = flush_on_reconnect
self.set_servers(servers)
self.stats = {}
self.cache_cas = cache_cas
self.reset_cas()
self.do_check_key = check_keys # Allow users to modify pickling/unpickling behavior
self.pickleProtocol = pickleProtocol
self.pickler = pickler
self.unpickler = unpickler
self.compressor = compressor
self.decompressor = decompressor
self.persistent_load = pload
self.persistent_id = pid
self.server_max_key_length = server_max_key_length
if self.server_max_key_length is None:
self.server_max_key_length = SERVER_MAX_KEY_LENGTH
self.server_max_value_length = server_max_value_length
if self.server_max_value_length is None:
self.server_max_value_length = SERVER_MAX_VALUE_LENGTH # figure out the pickler style
file = BytesIO()
try:
pickler = self.pickler(file, protocol=self.pickleProtocol)
self.picklerIsKeyword = True
except TypeError:
self.picklerIsKeyword = False def _encode_key(self, key):
if isinstance(key, tuple):
if isinstance(key[1], six.text_type):
return (key[0], key[1].encode('utf8'))
elif isinstance(key, six.text_type):
return key.encode('utf8')
return key def _encode_cmd(self, cmd, key, headers, noreply, *args):
cmd_bytes = cmd.encode() if six.PY3 else cmd
fullcmd = [cmd_bytes, b' ', key] if headers:
if six.PY3:
headers = headers.encode()
fullcmd.append(b' ')
fullcmd.append(headers) if noreply:
fullcmd.append(b' noreply') if args:
fullcmd.append(b' ')
fullcmd.extend(args)
return b''.join(fullcmd) def reset_cas(self):
"""Reset the cas cache. This is only used if the Client() object was created with
"cache_cas=True". If used, this cache does not expire
internally, so it can grow unbounded if you do not clear it
yourself.
"""
self.cas_ids = {} def set_servers(self, servers):
"""Set the pool of servers used by this client. @param servers: an array of servers.
Servers can be passed in two forms:
1. Strings of the form C{"host:port"}, which implies a
default weight of 1.
2. Tuples of the form C{("host:port", weight)}, where
C{weight} is an integer weight value. """
self.servers = [_Host(s, self.debug, dead_retry=self.dead_retry,
socket_timeout=self.socket_timeout,
flush_on_reconnect=self.flush_on_reconnect)
for s in servers]
self._init_buckets() def get_stats(self, stat_args=None):
"""Get statistics from each of the servers. @param stat_args: Additional arguments to pass to the memcache
"stats" command. @return: A list of tuples ( server_identifier,
stats_dictionary ). The dictionary contains a number of
name/value pairs specifying the name of the status field
and the string value associated with it. The values are
not converted from strings.
"""
data = []
for s in self.servers:
if not s.connect():
continue
if s.family == socket.AF_INET:
name = '%s:%s (%s)' % (s.ip, s.port, s.weight)
elif s.family == socket.AF_INET6:
name = '[%s]:%s (%s)' % (s.ip, s.port, s.weight)
else:
name = 'unix:%s (%s)' % (s.address, s.weight)
if not stat_args:
s.send_cmd('stats')
else:
s.send_cmd('stats ' + stat_args)
serverData = {}
data.append((name, serverData))
readline = s.readline
while 1:
line = readline()
if not line or line.strip() == 'END':
break
stats = line.split(' ', 2)
serverData[stats[1]] = stats[2] return(data) def get_slabs(self):
data = []
for s in self.servers:
if not s.connect():
continue
if s.family == socket.AF_INET:
name = '%s:%s (%s)' % (s.ip, s.port, s.weight)
elif s.family == socket.AF_INET6:
name = '[%s]:%s (%s)' % (s.ip, s.port, s.weight)
else:
name = 'unix:%s (%s)' % (s.address, s.weight)
serverData = {}
data.append((name, serverData))
s.send_cmd('stats items')
readline = s.readline
while 1:
line = readline()
if not line or line.strip() == 'END':
break
item = line.split(' ', 2)
# 0 = STAT, 1 = ITEM, 2 = Value
slab = item[1].split(':', 2)
# 0 = items, 1 = Slab #, 2 = Name
if slab[1] not in serverData:
serverData[slab[1]] = {}
serverData[slab[1]][slab[2]] = item[2]
return data def flush_all(self):
"""Expire all data in memcache servers that are reachable."""
for s in self.servers:
if not s.connect():
continue
s.flush() def debuglog(self, str):
if self.debug:
sys.stderr.write("MemCached: %s\n" % str) def _statlog(self, func):
if func not in self.stats:
self.stats[func] = 1
else:
self.stats[func] += 1 def forget_dead_hosts(self):
"""Reset every host in the pool to an "alive" state."""
for s in self.servers:
s.deaduntil = 0 def _init_buckets(self):
self.buckets = []
for server in self.servers:
for i in range(server.weight):
self.buckets.append(server) def _get_server(self, key):
if isinstance(key, tuple):
serverhash, key = key
else:
serverhash = serverHashFunction(key) if not self.buckets:
return None, None for i in range(Client._SERVER_RETRIES):
server = self.buckets[serverhash % len(self.buckets)]
if server.connect():
# print("(using server %s)" % server,)
return server, key
serverhash = serverHashFunction(str(serverhash) + str(i))
return None, None def disconnect_all(self):
for s in self.servers:
s.close_socket() def delete_multi(self, keys, time=0, key_prefix='', noreply=False):
"""Delete multiple keys in the memcache doing just one query. >>> notset_keys = mc.set_multi({'a1' : 'val1', 'a2' : 'val2'})
>>> mc.get_multi(['a1', 'a2']) == {'a1' : 'val1','a2' : 'val2'}
>>> mc.delete_multi(['key1', 'key2'])
>>> mc.get_multi(['key1', 'key2']) == {} This method is recommended over iterated regular L{delete}s as
it reduces total latency, since your app doesn't have to wait
for each round-trip of L{delete} before sending the next one. @param keys: An iterable of keys to clear
@param time: number of seconds any subsequent set / update
commands should fail. Defaults to 0 for no delay.
@param key_prefix: Optional string to prepend to each key when
sending to memcache. See docs for L{get_multi} and
L{set_multi}.
@param noreply: optional parameter instructs the server to not send the
reply.
@return: 1 if no failure in communication with any memcacheds.
@rtype: int
""" self._statlog('delete_multi') server_keys, prefixed_to_orig_key = self._map_and_prefix_keys(
keys, key_prefix) # send out all requests on each server before reading anything
dead_servers = [] rc = 1
for server in six.iterkeys(server_keys):
bigcmd = []
write = bigcmd.append
extra = ' noreply' if noreply else ''
if time is not None:
for key in server_keys[server]: # These are mangled keys
write("delete %s %d%s\r\n" % (key, time, extra))
else:
for key in server_keys[server]: # These are mangled keys
write("delete %s%s\r\n" % (key, extra))
try:
server.send_cmds(''.join(bigcmd))
except socket.error as msg:
rc = 0
if isinstance(msg, tuple):
msg = msg[1]
server.mark_dead(msg)
dead_servers.append(server) # if noreply, just return
if noreply:
return rc # if any servers died on the way, don't expect them to respond.
for server in dead_servers:
del server_keys[server] for server, keys in six.iteritems(server_keys):
try:
for key in keys:
server.expect("DELETED")
except socket.error as msg:
if isinstance(msg, tuple):
msg = msg[1]
server.mark_dead(msg)
rc = 0
return rc def delete(self, key, time=0, noreply=False):
'''Deletes a key from the memcache. @return: Nonzero on success.
@param time: number of seconds any subsequent set / update commands
should fail. Defaults to None for no delay.
@param noreply: optional parameter instructs the server to not send the
reply.
@rtype: int
'''
return self._deletetouch([b'DELETED', b'NOT_FOUND'], "delete", key,
time, noreply) def touch(self, key, time=0, noreply=False):
'''Updates the expiration time of a key in memcache. @return: Nonzero on success.
@param time: Tells memcached the time which this value should
expire, either as a delta number of seconds, or an absolute
unix time-since-the-epoch value. See the memcached protocol
docs section "Storage Commands" for more info on <exptime>. We
default to 0 == cache forever.
@param noreply: optional parameter instructs the server to not send the
reply.
@rtype: int
'''
return self._deletetouch([b'TOUCHED'], "touch", key, time, noreply) def _deletetouch(self, expected, cmd, key, time=0, noreply=False):
key = self._encode_key(key)
if self.do_check_key:
self.check_key(key)
server, key = self._get_server(key)
if not server:
return 0
self._statlog(cmd)
if time is not None and time != 0:
fullcmd = self._encode_cmd(cmd, key, str(time), noreply)
else:
fullcmd = self._encode_cmd(cmd, key, None, noreply) try:
server.send_cmd(fullcmd)
if noreply:
return 1
line = server.readline()
if line and line.strip() in expected:
return 1
self.debuglog('%s expected %s, got: %r'
% (cmd, ' or '.join(expected), line))
except socket.error as msg:
if isinstance(msg, tuple):
msg = msg[1]
server.mark_dead(msg)
return 0 def incr(self, key, delta=1, noreply=False):
"""Increment value for C{key} by C{delta} Sends a command to the server to atomically increment the
value for C{key} by C{delta}, or by 1 if C{delta} is
unspecified. Returns None if C{key} doesn't exist on server,
otherwise it returns the new value after incrementing. Note that the value for C{key} must already exist in the
memcache, and it must be the string representation of an
integer. >>> mc.set("counter", "20") # returns 1, indicating success
>>> mc.incr("counter")
>>> mc.incr("counter") Overflow on server is not checked. Be aware of values
approaching 2**32. See L{decr}. @param delta: Integer amount to increment by (should be zero
or greater). @param noreply: optional parameter instructs the server to not send the
reply. @return: New value after incrementing, no None for noreply or error.
@rtype: int
"""
return self._incrdecr("incr", key, delta, noreply) def decr(self, key, delta=1, noreply=False):
"""Decrement value for C{key} by C{delta} Like L{incr}, but decrements. Unlike L{incr}, underflow is
checked and new values are capped at 0. If server value is 1,
a decrement of 2 returns 0, not -1. @param delta: Integer amount to decrement by (should be zero
or greater). @param noreply: optional parameter instructs the server to not send the
reply. @return: New value after decrementing, or None for noreply or error.
@rtype: int
"""
return self._incrdecr("decr", key, delta, noreply) def _incrdecr(self, cmd, key, delta, noreply=False):
key = self._encode_key(key)
if self.do_check_key:
self.check_key(key)
server, key = self._get_server(key)
if not server:
return None
self._statlog(cmd)
fullcmd = self._encode_cmd(cmd, key, str(delta), noreply)
try:
server.send_cmd(fullcmd)
if noreply:
return
line = server.readline()
if line is None or line.strip() == b'NOT_FOUND':
return None
return int(line)
except socket.error as msg:
if isinstance(msg, tuple):
msg = msg[1]
server.mark_dead(msg)
return None def add(self, key, val, time=0, min_compress_len=0, noreply=False):
'''Add new key with value. Like L{set}, but only stores in memcache if the key doesn't
already exist. @return: Nonzero on success.
@rtype: int
'''
return self._set("add", key, val, time, min_compress_len, noreply) def append(self, key, val, time=0, min_compress_len=0, noreply=False):
'''Append the value to the end of the existing key's value. Only stores in memcache if key already exists.
Also see L{prepend}. @return: Nonzero on success.
@rtype: int
'''
return self._set("append", key, val, time, min_compress_len, noreply) def prepend(self, key, val, time=0, min_compress_len=0, noreply=False):
'''Prepend the value to the beginning of the existing key's value. Only stores in memcache if key already exists.
Also see L{append}. @return: Nonzero on success.
@rtype: int
'''
return self._set("prepend", key, val, time, min_compress_len, noreply) def replace(self, key, val, time=0, min_compress_len=0, noreply=False):
'''Replace existing key with value. Like L{set}, but only stores in memcache if the key already exists.
The opposite of L{add}. @return: Nonzero on success.
@rtype: int
'''
return self._set("replace", key, val, time, min_compress_len, noreply) def set(self, key, val, time=0, min_compress_len=0, noreply=False):
'''Unconditionally sets a key to a given value in the memcache. The C{key} can optionally be an tuple, with the first element
being the server hash value and the second being the key. If
you want to avoid making this module calculate a hash value.
You may prefer, for example, to keep all of a given user's
objects on the same memcache server, so you could use the
user's unique id as the hash value. @return: Nonzero on success.
@rtype: int @param time: Tells memcached the time which this value should
expire, either as a delta number of seconds, or an absolute
unix time-since-the-epoch value. See the memcached protocol
docs section "Storage Commands" for more info on <exptime>. We
default to 0 == cache forever. @param min_compress_len: The threshold length to kick in
auto-compression of the value using the compressor
routine. If the value being cached is a string, then the
length of the string is measured, else if the value is an
object, then the length of the pickle result is measured. If
the resulting attempt at compression yeilds a larger string
than the input, then it is discarded. For backwards
compatability, this parameter defaults to 0, indicating don't
ever try to compress. @param noreply: optional parameter instructs the server to not
send the reply.
'''
return self._set("set", key, val, time, min_compress_len, noreply) def cas(self, key, val, time=0, min_compress_len=0, noreply=False):
'''Check and set (CAS) Sets a key to a given value in the memcache if it hasn't been
altered since last fetched. (See L{gets}). The C{key} can optionally be an tuple, with the first element
being the server hash value and the second being the key. If
you want to avoid making this module calculate a hash value.
You may prefer, for example, to keep all of a given user's
objects on the same memcache server, so you could use the
user's unique id as the hash value. @return: Nonzero on success.
@rtype: int @param time: Tells memcached the time which this value should
expire, either as a delta number of seconds, or an absolute
unix time-since-the-epoch value. See the memcached protocol
docs section "Storage Commands" for more info on <exptime>. We
default to 0 == cache forever. @param min_compress_len: The threshold length to kick in
auto-compression of the value using the compressor
routine. If the value being cached is a string, then the
length of the string is measured, else if the value is an
object, then the length of the pickle result is measured. If
the resulting attempt at compression yeilds a larger string
than the input, then it is discarded. For backwards
compatability, this parameter defaults to 0, indicating don't
ever try to compress. @param noreply: optional parameter instructs the server to not
send the reply.
'''
return self._set("cas", key, val, time, min_compress_len, noreply) def _map_and_prefix_keys(self, key_iterable, key_prefix):
"""Compute the mapping of server (_Host instance) -> list of keys to
stuff onto that server, as well as the mapping of prefixed key
-> original key.
"""
key_prefix = self._encode_key(key_prefix)
# Check it just once ...
key_extra_len = len(key_prefix)
if key_prefix and self.do_check_key:
self.check_key(key_prefix) # server (_Host) -> list of unprefixed server keys in mapping
server_keys = {} prefixed_to_orig_key = {}
# build up a list for each server of all the keys we want.
for orig_key in key_iterable:
if isinstance(orig_key, tuple):
# Tuple of hashvalue, key ala _get_server(). Caller is
# essentially telling us what server to stuff this on.
# Ensure call to _get_server gets a Tuple as well.
serverhash, key = orig_key key = self._encode_key(key)
if not isinstance(key, six.binary_type):
# set_multi supports int / long keys.
key = str(key)
if six.PY3:
key = key.encode('utf8')
bytes_orig_key = key # Gotta pre-mangle key before hashing to a
# server. Returns the mangled key.
server, key = self._get_server(
(serverhash, key_prefix + key)) orig_key = orig_key[1]
else:
key = self._encode_key(orig_key)
if not isinstance(key, six.binary_type):
# set_multi supports int / long keys.
key = str(key)
if six.PY3:
key = key.encode('utf8')
bytes_orig_key = key
server, key = self._get_server(key_prefix + key) # alert when passed in key is None
if orig_key is None:
self.check_key(orig_key, key_extra_len=key_extra_len) # Now check to make sure key length is proper ...
if self.do_check_key:
self.check_key(bytes_orig_key, key_extra_len=key_extra_len) if not server:
continue if server not in server_keys:
server_keys[server] = []
server_keys[server].append(key)
prefixed_to_orig_key[key] = orig_key return (server_keys, prefixed_to_orig_key) def set_multi(self, mapping, time=0, key_prefix='', min_compress_len=0,
noreply=False):
'''Sets multiple keys in the memcache doing just one query. >>> notset_keys = mc.set_multi({'key1' : 'val1', 'key2' : 'val2'})
>>> mc.get_multi(['key1', 'key2']) == {'key1' : 'val1',
... 'key2' : 'val2'} This method is recommended over regular L{set} as it lowers
the number of total packets flying around your network,
reducing total latency, since your app doesn't have to wait
for each round-trip of L{set} before sending the next one. @param mapping: A dict of key/value pairs to set. @param time: Tells memcached the time which this value should
expire, either as a delta number of seconds, or an
absolute unix time-since-the-epoch value. See the
memcached protocol docs section "Storage Commands" for
more info on <exptime>. We default to 0 == cache forever. @param key_prefix: Optional string to prepend to each key when
sending to memcache. Allows you to efficiently stuff these
keys into a pseudo-namespace in memcache: >>> notset_keys = mc.set_multi(
... {'key1' : 'val1', 'key2' : 'val2'},
... key_prefix='subspace_')
>>> len(notset_keys) == 0
True
>>> mc.get_multi(['subspace_key1',
... 'subspace_key2']) == {'subspace_key1': 'val1',
... 'subspace_key2' : 'val2'}
True Causes key 'subspace_key1' and 'subspace_key2' to be
set. Useful in conjunction with a higher-level layer which
applies namespaces to data in memcache. In this case, the
return result would be the list of notset original keys,
prefix not applied. @param min_compress_len: The threshold length to kick in
auto-compression of the value using the compressor
routine. If the value being cached is a string, then the
length of the string is measured, else if the value is an
object, then the length of the pickle result is
measured. If the resulting attempt at compression yeilds a
larger string than the input, then it is discarded. For
backwards compatability, this parameter defaults to 0,
indicating don't ever try to compress. @param noreply: optional parameter instructs the server to not
send the reply. @return: List of keys which failed to be stored [ memcache out
of memory, etc. ]. @rtype: list
'''
self._statlog('set_multi') server_keys, prefixed_to_orig_key = self._map_and_prefix_keys(
six.iterkeys(mapping), key_prefix) # send out all requests on each server before reading anything
dead_servers = []
notstored = [] # original keys. for server in six.iterkeys(server_keys):
bigcmd = []
write = bigcmd.append
try:
for key in server_keys[server]: # These are mangled keys
store_info = self._val_to_store_info(
mapping[prefixed_to_orig_key[key]],
min_compress_len)
if store_info:
flags, len_val, val = store_info
headers = "%d %d %d" % (flags, time, len_val)
fullcmd = self._encode_cmd('set', key, headers,
noreply,
b'\r\n', val, b'\r\n')
write(fullcmd)
else:
notstored.append(prefixed_to_orig_key[key])
server.send_cmds(b''.join(bigcmd))
except socket.error as msg:
if isinstance(msg, tuple):
msg = msg[1]
server.mark_dead(msg)
dead_servers.append(server) # if noreply, just return early
if noreply:
return notstored # if any servers died on the way, don't expect them to respond.
for server in dead_servers:
del server_keys[server] # short-circuit if there are no servers, just return all keys
if not server_keys:
return(mapping.keys()) for server, keys in six.iteritems(server_keys):
try:
for key in keys:
if server.readline() == 'STORED':
continue
else:
# un-mangle.
notstored.append(prefixed_to_orig_key[key])
except (_Error, socket.error) as msg:
if isinstance(msg, tuple):
msg = msg[1]
server.mark_dead(msg)
return notstored def _val_to_store_info(self, val, min_compress_len):
"""Transform val to a storable representation. Returns a tuple of the flags, the length of the new value, and
the new value itself.
"""
flags = 0
if isinstance(val, six.binary_type):
pass
elif isinstance(val, six.text_type):
val = val.encode('utf-8')
elif isinstance(val, int):
flags |= Client._FLAG_INTEGER
val = '%d' % val
if six.PY3:
val = val.encode('ascii')
# force no attempt to compress this silly string.
min_compress_len = 0
elif six.PY2 and isinstance(val, long):
flags |= Client._FLAG_LONG
val = str(val)
if six.PY3:
val = val.encode('ascii')
# force no attempt to compress this silly string.
min_compress_len = 0
else:
flags |= Client._FLAG_PICKLE
file = BytesIO()
if self.picklerIsKeyword:
pickler = self.pickler(file, protocol=self.pickleProtocol)
else:
pickler = self.pickler(file, self.pickleProtocol)
if self.persistent_id:
pickler.persistent_id = self.persistent_id
pickler.dump(val)
val = file.getvalue() lv = len(val)
# We should try to compress if min_compress_len > 0
# and this string is longer than our min threshold.
if min_compress_len and lv > min_compress_len:
comp_val = self.compressor(val)
# Only retain the result if the compression result is smaller
# than the original.
if len(comp_val) < lv:
flags |= Client._FLAG_COMPRESSED
val = comp_val # silently do not store if value length exceeds maximum
if (self.server_max_value_length != 0 and
len(val) > self.server_max_value_length):
return(0) return (flags, len(val), val) def _set(self, cmd, key, val, time, min_compress_len=0, noreply=False):
key = self._encode_key(key)
if self.do_check_key:
self.check_key(key)
server, key = self._get_server(key)
if not server:
return 0 def _unsafe_set():
self._statlog(cmd) if cmd == 'cas' and key not in self.cas_ids:
return self._set('set', key, val, time, min_compress_len,
noreply) store_info = self._val_to_store_info(val, min_compress_len)
if not store_info:
return(0)
flags, len_val, encoded_val = store_info if cmd == 'cas':
headers = ("%d %d %d %d"
% (flags, time, len_val, self.cas_ids[key]))
else:
headers = "%d %d %d" % (flags, time, len_val)
fullcmd = self._encode_cmd(cmd, key, headers, noreply,
b'\r\n', encoded_val) try:
server.send_cmd(fullcmd)
if noreply:
return True
return(server.expect(b"STORED", raise_exception=True)
== b"STORED")
except socket.error as msg:
if isinstance(msg, tuple):
msg = msg[1]
server.mark_dead(msg)
return 0 try:
return _unsafe_set()
except _ConnectionDeadError:
# retry once
try:
if server._get_socket():
return _unsafe_set()
except (_ConnectionDeadError, socket.error) as msg:
server.mark_dead(msg)
return 0 def _get(self, cmd, key):
key = self._encode_key(key)
if self.do_check_key:
self.check_key(key)
server, key = self._get_server(key)
if not server:
return None def _unsafe_get():
self._statlog(cmd) try:
cmd_bytes = cmd.encode() if six.PY3 else cmd
fullcmd = b''.join((cmd_bytes, b' ', key))
server.send_cmd(fullcmd)
rkey = flags = rlen = cas_id = None if cmd == 'gets':
rkey, flags, rlen, cas_id, = self._expect_cas_value(
server, raise_exception=True
)
if rkey and self.cache_cas:
self.cas_ids[rkey] = cas_id
else:
rkey, flags, rlen, = self._expectvalue(
server, raise_exception=True
) if not rkey:
return None
try:
value = self._recv_value(server, flags, rlen)
finally:
server.expect(b"END", raise_exception=True)
except (_Error, socket.error) as msg:
if isinstance(msg, tuple):
msg = msg[1]
server.mark_dead(msg)
return None return value try:
return _unsafe_get()
except _ConnectionDeadError:
# retry once
try:
if server.connect():
return _unsafe_get()
return None
except (_ConnectionDeadError, socket.error) as msg:
server.mark_dead(msg)
return None def get(self, key):
'''Retrieves a key from the memcache. @return: The value or None.
'''
return self._get('get', key) def gets(self, key):
'''Retrieves a key from the memcache. Used in conjunction with 'cas'. @return: The value or None.
'''
return self._get('gets', key) def get_multi(self, keys, key_prefix=''):
'''Retrieves multiple keys from the memcache doing just one query. >>> success = mc.set("foo", "bar")
>>> success = mc.set("baz", 42)
>>> mc.get_multi(["foo", "baz", "foobar"]) == {
... "foo": "bar", "baz": 42
... }
>>> mc.set_multi({'k1' : 1, 'k2' : 2}, key_prefix='pfx_') == [] This looks up keys 'pfx_k1', 'pfx_k2', ... . Returned dict
will just have unprefixed keys 'k1', 'k2'. >>> mc.get_multi(['k1', 'k2', 'nonexist'],
... key_prefix='pfx_') == {'k1' : 1, 'k2' : 2} get_mult [ and L{set_multi} ] can take str()-ables like ints /
longs as keys too. Such as your db pri key fields. They're
rotored through str() before being passed off to memcache,
with or without the use of a key_prefix. In this mode, the
key_prefix could be a table name, and the key itself a db
primary key number. >>> mc.set_multi({42: 'douglass adams',
... 46: 'and 2 just ahead of me'},
... key_prefix='numkeys_') == []
>>> mc.get_multi([46, 42], key_prefix='numkeys_') == {
... 42: 'douglass adams',
... 46: 'and 2 just ahead of me'
... } This method is recommended over regular L{get} as it lowers
the number of total packets flying around your network,
reducing total latency, since your app doesn't have to wait
for each round-trip of L{get} before sending the next one. See also L{set_multi}. @param keys: An array of keys. @param key_prefix: A string to prefix each key when we
communicate with memcache. Facilitates pseudo-namespaces
within memcache. Returned dictionary keys will not have this
prefix. @return: A dictionary of key/value pairs that were
available. If key_prefix was provided, the keys in the retured
dictionary will not have it present.
''' self._statlog('get_multi') server_keys, prefixed_to_orig_key = self._map_and_prefix_keys(
keys, key_prefix) # send out all requests on each server before reading anything
dead_servers = []
for server in six.iterkeys(server_keys):
try:
fullcmd = b"get " + b" ".join(server_keys[server])
server.send_cmd(fullcmd)
except socket.error as msg:
if isinstance(msg, tuple):
msg = msg[1]
server.mark_dead(msg)
dead_servers.append(server) # if any servers died on the way, don't expect them to respond.
for server in dead_servers:
del server_keys[server] retvals = {}
for server in six.iterkeys(server_keys):
try:
line = server.readline()
while line and line != b'END':
rkey, flags, rlen = self._expectvalue(server, line)
# Bo Yang reports that this can sometimes be None
if rkey is not None:
val = self._recv_value(server, flags, rlen)
# un-prefix returned key.
retvals[prefixed_to_orig_key[rkey]] = val
line = server.readline()
except (_Error, socket.error) as msg:
if isinstance(msg, tuple):
msg = msg[1]
server.mark_dead(msg)
return retvals def _expect_cas_value(self, server, line=None, raise_exception=False):
if not line:
line = server.readline(raise_exception) if line and line[:5] == b'VALUE':
resp, rkey, flags, len, cas_id = line.split()
return (rkey, int(flags), int(len), int(cas_id))
else:
return (None, None, None, None) def _expectvalue(self, server, line=None, raise_exception=False):
if not line:
line = server.readline(raise_exception) if line and line[:5] == b'VALUE':
resp, rkey, flags, len = line.split()
flags = int(flags)
rlen = int(len)
return (rkey, flags, rlen)
else:
return (None, None, None) def _recv_value(self, server, flags, rlen):
rlen += 2 # include \r\n
buf = server.recv(rlen)
if len(buf) != rlen:
raise _Error("received %d bytes when expecting %d"
% (len(buf), rlen)) if len(buf) == rlen:
buf = buf[:-2] # strip \r\n if flags & Client._FLAG_COMPRESSED:
buf = self.decompressor(buf)
flags &= ~Client._FLAG_COMPRESSED if flags == 0:
# Bare string
if six.PY3:
val = buf.decode('utf8')
else:
val = buf
elif flags & Client._FLAG_INTEGER:
val = int(buf)
elif flags & Client._FLAG_LONG:
if six.PY3:
val = int(buf)
else:
val = long(buf)
elif flags & Client._FLAG_PICKLE:
try:
file = BytesIO(buf)
unpickler = self.unpickler(file)
if self.persistent_load:
unpickler.persistent_load = self.persistent_load
val = unpickler.load()
except Exception as e:
self.debuglog('Pickle error: %s\n' % e)
return None
else:
self.debuglog("unknown flags on get: %x\n" % flags)
raise ValueError('Unknown flags on get: %x' % flags) return val def check_key(self, key, key_extra_len=0):
"""Checks sanity of key. Fails if: Key length is > SERVER_MAX_KEY_LENGTH (Raises MemcachedKeyLength).
Contains control characters (Raises MemcachedKeyCharacterError).
Is not a string (Raises MemcachedStringEncodingError)
Is an unicode string (Raises MemcachedStringEncodingError)
Is not a string (Raises MemcachedKeyError)
Is None (Raises MemcachedKeyError)
"""
if isinstance(key, tuple):
key = key[1]
if key is None:
raise Client.MemcachedKeyNoneError("Key is None")
if key is '':
if key_extra_len is 0:
raise Client.MemcachedKeyNoneError("Key is empty") # key is empty but there is some other component to key
return if not isinstance(key, six.binary_type):
raise Client.MemcachedKeyTypeError("Key must be a binary string") if (self.server_max_key_length != 0 and
len(key) + key_extra_len > self.server_max_key_length):
raise Client.MemcachedKeyLengthError(
"Key length is > %s" % self.server_max_key_length
)
if not valid_key_chars_re.match(key):
raise Client.MemcachedKeyCharacterError(
"Control/space characters not allowed (key=%r)" % key) Python-Memcached source code
Memcached
6、Memcached与Redis的不同
总结:
根据不同的场景来合理的使用不同的程序!各有优点。
Redis
redis是一个key-value存储系统。和Memcached类似,它支持存储的value类型相对更多,包括string(字符串)、list(链表)、set(集合)、zset(sorted set --有序集合)和hash(哈希类型)。这些数据类型都 支持push/pop、add/remove及取交集并集和差集及更丰富的操作,而且这些操作都是原子性的。在此基础上,redis支持各种不同方式的排 序。与memcached一样,为了保证效率,数据都是缓存在内存中。区别的是redis会周期性的把更新的数据写入磁盘或者把修改操作写入追加的记录文 件,并且在此基础上实现了master-slave(主从)同步。
1、Redis安装&操作
1、检查配置环境
检查gcc是否安装,如果没有安装:yum -y install gcc 2、下载安装Redis
cd /opt/
wget http://download.redis.io/releases/redis-3.0.4.tar.gz
#这里下载可以登录官网查看最新的Redis
tar -xvf redis-3.0.4.tar.gz
make
make install
cd /opt/redis-3.0.4/src/
make test 3、配置redis
cp /opt/redis-3.0.4/utils/redis_init_script /etc/init.d/redis #复制管理脚本
chmod +x /etc/init.d/redis
mkdir /etc/redis
cp /opt/redis-3.0.4/redis.conf /etc/redis/6379.conf 4、修改redis启动模式
默认Redis启动的时候是启动在前台的,把他改为启动在后台
vim /etc/redis/6379.conf
daemonize no 改为 daemonize yes 5、Redis加入到系统服务并设置为开机启动
首先修改Redis启动脚本:
vim /etc/init.d/redis
#chkconfig: 35 95 95 在第三行加上即可
##ubunctu
添加系统服务:chkconfig --add redis
设置开机启动:chkconfig redis on
检查服务状态:chkconfig --list redis 6、指定日志存放位置&PID文件&数据库文件存放位置(下一边写持久化)
vim /etc/redis/6379.conf logfile "/var/log/redis.log" 指定日志文件如果不指定就会在控制台输出
pidfile /var/run/redis_6379.pid
dir ./ 这个是指默认的持久化配置文件放在那里!建议修改下! pidfile如果不修改使用默认的话就会报错:
原因是在/etc/init.d/redis里指定的默认PID是:PIDFILE=/var/run/redis_${REDISPORT}.pid
但是默认配置文件:/etc/redis/6379.conf(咱们自己从解压包里复制的里的默认是:pidfile /var/run/redis.pid)
2、python操作Redis
#安装模块
pip install redis
#详见GitHub
https://github.com/WoLpH/redis-py
SET 设置Key
GET 判断Key的值
EXISTS 判断Key是否存在
KEYS * 显示所有的Key
DEL 删除指定Key
TYPE 获取Key类型 注:Redis是不区分大小写的,命令最好使用大写这样能区分是命令还是参数!
root@ubuntu:~# redis-cli
1、set的例子:
127.0.0.1:6379> set foo bar
OK
127.0.0.1:6379> get foo
"bar"
127.0.0.1:6379> set foo Bar
OK
127.0.0.1:6379> KEYS *
1) "foo"
127.0.0.1:6379> set name Jason
OK
127.0.0.1:6379> set name Jade
OK
127.0.0.1:6379> KEYS *
1) "foo"
2) "name"
127.0.0.1:6379> set hobby sport
OK
2、设置多个key value 然后使用使用keys * 去查看所有
127.0.0.1:6379> KEYS *
1) "foo"
2) "hobby"
3) "name"
127.0.0.1:6379> KEYS ?
(empty list or set)
127.0.0.1:6379> KEYS ?name
(empty list or set)
127.0.0.1:6379> KEYS ? name
(error) ERR wrong number of arguments for 'keys' command
KEY匹配方式:
?匹配单个
*匹配所有
3、判断key是否存在
判断Key是否存在使用:EXISTS 他返回的是整形:0不存在,1存在
127.0.0.1:6379> EXISTS name
(integer) 1
127.0.0.1:6379> EXISTS xxx
(integer) 0
4、删除KEY
127.0.0.1:6379> del name
(integer) 1(1是数量)
127.0.0.1:6379> EXISTS name
(integer) 0
删除多个测试下:
127.0.0.1:6379[1]> set test1 a
OK
127.0.0.1:6379[1]> set test2 a
OK
127.0.0.1:6379[1]> del test1 test2
(integer) 2
5、查看类型TYPE
只要用set类型就是字符串。查看类型命令用TYPE
127.0.0.1:6379> TYPE name
none
127.0.0.1:6379> TYPE hobby
string
127.0.0.1:6379> SELECT 1
OK
127.0.0.1:6379[1]> set age 23
OK
6、Keyspace
redis是支持多个实例的默认最多16个,可以修改配置文件来支持更多!
使用INFO命令查看!
127.0.0.1:6379> KEYS *
1) "foo"
2) "hobby"
db0 :这个可以理解为命名空间。最多支持16个,使用SELECT 去切换
127.0.0.1:6379> select 1
OK
127.0.0.1:6379[1]> keys *
1) "age"
127.0.0.1:6379[1]>
127.0.0.1:6379[1]> INFO
# Server
redis_version:3.0.4
redis_git_sha1:00000000
redis_git_dirty:0
redis_build_id:433e5cc38595327e
redis_mode:standalone
os:Linux 3.13.0-34-generic x86_64
arch_bits:64
multiplexing_api:epoll
gcc_version:4.8.2
process_id:5382
run_id:590c6d9ba4596697d308aadaf58a95a4eceee2b4
tcp_port:6379
uptime_in_seconds:1457
uptime_in_days:0
hz:10
lru_clock:9400465
config_file:/etc/redis/6379.conf # Clients
connected_clients:1
client_longest_output_list:0
client_biggest_input_buf:0
blocked_clients:0 # Memory
used_memory:816240
used_memory_human:797.11K
used_memory_rss:7733248
used_memory_peak:816240
used_memory_peak_human:797.11K
used_memory_lua:36864
mem_fragmentation_ratio:9.47
mem_allocator:jemalloc-3.6.0 # Persistence
loading:0
rdb_changes_since_last_save:5
rdb_bgsave_in_progress:0
rdb_last_save_time:1469017701
rdb_last_bgsave_status:ok
rdb_last_bgsave_time_sec:0
rdb_current_bgsave_time_sec:-1
aof_enabled:0
aof_rewrite_in_progress:0
aof_rewrite_scheduled:0
aof_last_rewrite_time_sec:-1
aof_current_rewrite_time_sec:-1
aof_last_bgrewrite_status:ok
aof_last_write_status:ok # Stats
total_connections_received:2
total_commands_processed:21
instantaneous_ops_per_sec:0
total_net_input_bytes:595
total_net_output_bytes:219
instantaneous_input_kbps:0.00
instantaneous_output_kbps:0.00
rejected_connections:0
sync_full:0
sync_partial_ok:0
sync_partial_err:0
expired_keys:0
evicted_keys:0
keyspace_hits:3
keyspace_misses:1
pubsub_channels:0
pubsub_patterns:0
latest_fork_usec:759
migrate_cached_sockets:0 # Replication
role:master
connected_slaves:0
master_repl_offset:0
repl_backlog_active:0
repl_backlog_size:1048576
repl_backlog_first_byte_offset:0
repl_backlog_histlen:0 # CPU
used_cpu_sys:1.39
used_cpu_user:0.51
used_cpu_sys_children:0.00
used_cpu_user_children:0.00 # Cluster
cluster_enabled:0 # Keyspace
db0:keys=2,expires=0,avg_ttl=0
db1:keys=1,expires=0,avg_ttl=0
127.0.0.1:6379[1]>
3、常用操作
基本命令:
redis-py提供两个类Redis和StrictRedis用于实现Redis的命令,StrictRedis用于实现大部分官方的命令,并使用官方的语法和命令,Redis是StrictRedis的子类,用于向后兼容旧版本的redis-py
#r = redis.Redis 他是StrictRedis的子类,Redis继承了StrictRedis,所以一般我们都用Redis = Redis(StrictRedis):
#!/usr/bin/env python
# -*- coding:utf-8 -*-
# Author: Jason Wang import redis r = redis.Redis(host='10.211.55.5',port=6379) #设置连接的主机和端口
r.set('name','Jason')#添加一条记录
print(r.get('name'))#获取一条记录
连接池:
redis-py使用connection pool来管理对一个redis server的所有连接,避免每次建立、释放连接的开销。默认,每个Redis实例都会维护一个自己的连接池。可以直接建立一个连接池,然后作为参数 Redis,这样就可以实现多个Redis实例共享一个连接池。
#!/usr/bin/env python
# -*- coding:utf-8 -*-
# Author: Jason Wang import redis
rpool = redis.ConnectionPool(host='10.211.55.5',port=6379) #创建连接池连接对象 r = redis.Redis(connection_pool=rpool)#把创建的对象赋值给connection_pool
r.set('username','Jason') #添加一条记录
print(r.get('username'))#获取一条记录
管道:
redis-py默认在执行每次请求都会创建(连接池申请连接)和断开(归还连接池)一次连接操作,如果想要在一次请求中指定多个命令,则可以使用pipline实现一次请求指定多个命令,并且默认情况下一次pipline 是原子性操作。
原子操作(atomic operation)是不需要synchronized",这是Java多线程编程的老生常谈了。所谓原子操作是指不会被线程调度机制打断的操作;这种操作一旦开始,就一直运行到结束,中间不会有任何 context switch (切换到另一个线程)
pool = redis.ConnectionPool(host='10.211.55.5',port=6379)
r = redis.Redis(connection_pool=pool)
pipe = r.pipeline(transaction=True)
r.set('name','Jason')
r.set('age',18)
print(r.get('name'))
pipe.execute()
操作命令:
String操作,redis中的String在在内存中按照一个name对应一个value来存储。如图
set(name, value, ex=None, px=None, nx=False, xx=False)
在Redis中设置值,默认,不存在则创建,存在则修改
参数:
ex,过期时间(秒)
px,过期时间(毫秒)
nx,如果设置为True,则只有name不存在时,当前set操作才执行
xx,如果设置为True,则只有name存在时,岗前set操作才执行
setnx(name, value)
设置值,只有name不存在时,执行设置操作(添加)
setex(name, value, time)
# 设置值
# 参数:
# time,过期时间(数字秒 或 timedelta对象)
psetex(name, time_ms, value)
# 设置值
# 参数:
# time_ms,过期时间(数字毫秒 或 timedelta对象)
mset(*args, **kwargs),
mget(keys, *args)
#!/usr/bin/env python
# -*- coding:utf-8 -*-
# Author: Jason Wang import redis r = redis.Redis(host='10.211.55.5',port=6379)
# r.set('foo','Bar')
# print(r.get('foo'))
批量设置值
mset(k1=
'v1'
, k2=
'v2'
)
或
r.mset(name='jack',age=22)批量获取
mget({
'k1'
:
'v1'
,
'k2'
:
'v2'
})
如:
print(r.mget('name','age'))
##output
[b'jack', b'']
get(name)
获取值
import redis r = redis.Redis(host='10.211.55.5',port=6379)
r.set('foo','Bar')
print(r.get('foo'))
##output
b'Bar'
getset(name, value)
import redis r = redis.Redis(host='10.211.55.5',port=6379)
r.set('foo','Bar')
print(r.getset('foo', 'Bar1'))
print(r.get('foo'))
##output
b'Bar'
b'Bar1'
getrange(key, start, end)
# 获取子序列(根据字节获取,非字符)
# 参数:
# name,Redis 的 name
# start,起始位置(字节)
# end,结束位置(字节)
r = redis.Redis(host='10.211.55.5',port=6379)
r.set('foo','Bar')
print(r.getset('foo', 'Bar1'))
print(r.get('foo'))
print(r.getrange('foo',0,2))
##output
b'Bar'
b'Bar1'
b'Bar
setrange(name, offset, value)
# 修改字符串内容,从指定字符串索引开始向后替换(新值太长时,则向后添加)
# 参数:
# offset,字符串的索引,字节(一个汉字三个字节)
# value,要设置的值
r = redis.Redis(host='10.211.55.5',port=6379)
r.set('foo','Bar')
r.setrange('foo',0,'a')
print(r.get('foo'))
##output
b'aar'
setbit(name, offset, value)
# 对name对应值的二进制表示的位进行操作 # 参数:
# name,redis的name
# offset,位的索引(将值变换成二进制后再进行索引)
# value,值只能是 1 或 0 # 注:如果在Redis中有一个对应: n1 = "foo",
# 那么字符串foo的二进制表示为:01100110 01101111 01101111
# 所以,如果执行 setbit('n1', 7, 1),则就会将第7位设置为1,
# 那么最终二进制则变成 01100111 01101111 01101111,即:"goo" # 扩展,转换二进制表示: # source = "王健"
source = "foo" for i in source:
num = ord(i)
print(bin(num).replace('b','')) # 特别的,如果source是汉字 "王健"怎么办?
# 答:对于utf-8,每一个汉字占 3 个字节,那么 "王健" 则有 6个字节
# 对于汉字,for循环时候会按照 字节 迭代,那么在迭代时,将每一个字节转换 十进制数,然后再将十进制数转换成二进
getbit(name, offset)
# 获取name对应的值的二进制表示中的某位的值 (0或1)
bitcount(key, start=None, end=None)
# 获取name对应的值的二进制表示中 1 的个数
# 参数:
# key,Redis的name
# start,位起始位置
# end,位结束位置
bitop(operation, dest, *keys)
# 获取多个值,并将值做位运算,将最后的结果保存至新的name对应的值 # 参数:
# operation,AND(并) 、 OR(或) 、 NOT(非) 、 XOR(异或)
# dest, 新的Redis的name
# *keys,要查找的Redis的name # 如:
bitop("AND", 'new_name', 'n1', 'n2', 'n3')
# 获取Redis中n1,n2,n3对应的值,然后讲所有的值做位运算(求并集),然后将结果保存 new_name 对应的值中
strlen(name)
# 返回name对应值的字节长度(一个汉字3个字节)
incr(self, name, amount=1)
# 自增 name对应的值,当name不存在时,则创建name=amount,否则,则自增。 # 参数:
# name,Redis的name
# amount,自增数(必须是整数) # 注:同incrby
incrbyfloat(self, name, amount=1.0)
# 自增 name对应的值,当name不存在时,则创建name=amount,否则,则自增。 # 参数:
# name,Redis的name
# amount,自增数(浮点型)
decr(self, name, amount=1)
# 自减 name对应的值,当name不存在时,则创建name=amount,否则,则自减。 # 参数:
# name,Redis的name
# amount,自减数(整数)
append(key, value)
# 在redis name对应的值后面追加内容 # 参数:
key, redis的name
value, 要追加的字符串
Hash操作,redis中Hash在内存中的存储格式如下图:
hset(name, key, value)
# name对应的hash中设置一个键值对(不存在,则创建;否则,修改) # 参数:
# name,redis的name
# key,name对应的hash中的key
# value,name对应的hash中的value # 注:
# hsetnx(name, key, value),当name对应的hash中不存在当前key时则创建(相当于添加)
hmset(name, mapping)
# 在name对应的hash中批量设置键值对 # 参数:
# name,redis的name
# mapping,字典,如:{'k1':'v1', 'k2': 'v2'} # 如:
# r.hmset('xx', {'k1':'v1', 'k2': 'v2'})
hget(name,key)
# 在name对应的hash中获取根据key获取value
hmget(name, keys, *args)
# 在name对应的hash中获取多个key的值 # 参数:
# name,reids对应的name
# keys,要获取key集合,如:['k1', 'k2', 'k3']
# *args,要获取的key,如:k1,k2,k3 # 如:
# r.mget('xx', ['k1', 'k2'])
# 或
# print r.hmget('xx', 'k1', 'k2')
hgetall(name)
获取name对应hash的所有键值
hlen(name)
# 获取name对应的hash中键值对的个数
hkeys(name)
# 获取name对应的hash中所有的key的值
hvals(name)
# 获取name对应的hash中所有的value的值
hexists(name, key)
# 检查name对应的hash是否存在当前传入的key
hdel(name,*keys)
# 将name对应的hash中指定key的键值对删除
hincrby(name, key, amount=1)
# 自增name对应的hash中的指定key的值,不存在则创建key=amount
# 参数:
# name,redis中的name
# key, hash对应的key
# amount,自增数(整数)
hincrbyfloat(name, key, amount=1.0)
# 自增name对应的hash中的指定key的值,不存在则创建key=amount # 参数:
# name,redis中的name
# key, hash对应的key
# amount,自增数(浮点数) # 自增name对应的hash中的指定key的值,不存在则创建key=amount
hscan(name, cursor=0, match=None, count=None)
# 增量式迭代获取,对于数据大的数据非常有用,hscan可以实现分片的获取数据,并非一次性将数据全部获取完,从而放置内存被撑爆 # 参数:
# name,redis的name
# cursor,游标(基于游标分批取获取数据)
# match,匹配指定key,默认None 表示所有的key
# count,每次分片最少获取个数,默认None表示采用Redis的默认分片个数 # 如:
# 第一次:cursor1, data1 = r.hscan('xx', cursor=0, match=None, count=None)
# 第二次:cursor2, data1 = r.hscan('xx', cursor=cursor1, match=None, count=None)
# ...
# 直到返回值cursor的值为0时,表示数据已经通过分片获取完毕
hscan_iter(name, match=None, count=None)
# 利用yield封装hscan创建生成器,实现分批去redis中获取数据 # 参数:
# match,匹配指定key,默认None 表示所有的key
# count,每次分片最少获取个数,默认None表示采用Redis的默认分片个数 # 如:
# for item in r.hscan_iter('xx'):
# print item
List操作,redis中的List在在内存中按照一个name对应一个List来存储。如图:
lpush(name,values)
# 在name对应的list中添加元素,每个新的元素都添加到列表的最左边 # 如:
# r.lpush('oo', 11,22,33)
# 保存顺序为: 33,22,11 # 扩展:
# rpush(name, values) 表示从右向左操作
pushx(name,value)
# 在name对应的list中添加元素,每个新的元素都添加到列表的最左边 # 如:
# r.lpush('oo', 11,22,33)
# 保存顺序为: 33,22,11 # 扩展:
# rpush(name, values) 表示从右向左操作
lpushx(name,value)
# 在name对应的list中添加元素,只有name已经存在时,值添加到列表的最左边 # 更多:
# rpushx(name, value) 表示从右向左操作
llen(name)
# name对应的list元素的个数
linsert(name, where, refvalue, value))
# 在name对应的列表的某一个值前或后插入一个新值 # 参数:
# name,redis的name
# where,BEFORE或AFTER
# refvalue,标杆值,即:在它前后插入数据
# value,要插入的数据
r.lset(name, index, value)
# 对name对应的list中的某一个索引位置重新赋值 # 参数:
# name,redis的name
# index,list的索引位置
# value,要设置的值
r.lrem(name, value, num)
# 在name对应的list中删除指定的值 # 参数:
# name,redis的name
# value,要删除的值
# num, num=0,删除列表中所有的指定值;
# num=2,从前到后,删除2个;
# num=-2,从后向前,删除2个
lpop(name)
# 在name对应的列表的左侧获取第一个元素并在列表中移除,返回值则是第一个元素 # 更多:
# rpop(name) 表示从右向左操作
lindex(name, index)
在name对应的列表中根据索引获取列表元素
lrange(name, start, end)
# 在name对应的列表分片获取数据
# 参数:
# name,redis的name
# start,索引的起始位置
# end,索引结束位置
ltrim(name, start, end)
# 在name对应的列表中移除没有在start-end索引之间的值
# 参数:
# name,redis的name
# start,索引的起始位置
# end,索引结束位置
rpoplpush(src, dst)
# 从一个列表取出最右边的元素,同时将其添加至另一个列表的最左边
# 参数:
# src,要取数据的列表的name
# dst,要添加数据的列表的name
blpop(keys, timeout)
# 将多个列表排列,按照从左到右去pop对应列表的元素 # 参数:
# keys,redis的name的集合
# timeout,超时时间,当元素所有列表的元素获取完之后,阻塞等待列表内有数据的时间(秒), 0 表示永远阻塞 # 更多:
# r.brpop(keys, timeout),从右向左获取数据
brpoplpush(src, dst, timeout=0)
# 从一个列表的右侧移除一个元素并将其添加到另一个列表的左侧 # 参数:
# src,取出并要移除元素的列表对应的name
# dst,要插入元素的列表对应的name
# timeout,当src对应的列表中没有数据时,阻塞等待其有数据的超时时间(秒),0 表示永远阻塞
自定义增量迭代
# 由于redis类库中没有提供对列表元素的增量迭代,如果想要循环name对应的列表的所有元素,那么就需要:
# 1、获取name对应的所有列表
# 2、循环列表
# 但是,如果列表非常大,那么就有可能在第一步时就将程序的内容撑爆,所有有必要自定义一个增量迭代的功能: def list_iter(name):
"""
自定义redis列表增量迭代
:param name: redis中的name,即:迭代name对应的列表
:return: yield 返回 列表元素
"""
list_count = r.llen(name)
for index in range(list_count):
yield r.lindex(name, index) # 使用
for item in list_iter('pp'):
print(item)
Set操作,Set集合就是不允许重复的列表
sadd(name,values)
# name对应的集合中添加元素
scard(name)
获取name对应的集合中元素个数
sdiff(keys, *args)
在第一个name对应的集合中且不在其他name对应的集合的元素集合
sdiffstore(dest, keys, *args)
# 获取第一个name对应的集合中且不在其他name对应的集合,再将其新加入到dest对应的集合中
sismember(name, value)
# 检查value是否是name对应的集合的成员
smembers(name)
# 获取name对应的集合的所有成员
smove(src, dst, value)
# 将某个成员从一个集合中移动到另外一个集合
spop(name)
# 从集合的右侧(尾部)移除一个成员,并将其返回
srandmember(name, numbers)
从name对应的集合中随机获取 numbers 个元素
srem(name, values)
在name对应的集合中删除某些值
sunion(keys, *args)
# 获取多一个name对应的集合的并集
sunionstore(dest,keys, *args)
sunionstore(dest,keys, *args)
sscan(name, cursor=0, match=None, count=None)
sscan_iter(name, match=None, count=None)
# 同字符串的操作,用于增量迭代分批获取元素,避免内存消耗太大
有序集合,在集合的基础上,为每元素排序;元素的排序需要根据另外一个值来进行比较,所以,对于有序集合,每一个元素有两个值,即:值和分数,分数专门用来做排序。
zadd(name, *args, **kwargs)
# 在name对应的有序集合中添加元素
# 如:
# zadd('zz', 'n1', 1, 'n2', 2)
# 或
# zadd('zz', n1=11, n2=22)
zcard(name)
# 获取name对应的有序集合元素的数量
zcount(name, min, max)
# 获取name对应的有序集合中分数 在 [min,max] 之间的个数
zincrby(name, value, amount)
# 自增name对应的有序集合的 name 对应的分数
r.zrange( name, start, end, desc=False, withscores=False, score_cast_func=float)
# 按照索引范围获取name对应的有序集合的元素 # 参数:
# name,redis的name
# start,有序集合索引起始位置(非分数)
# end,有序集合索引结束位置(非分数)
# desc,排序规则,默认按照分数从小到大排序
# withscores,是否获取元素的分数,默认只获取元素的值
# score_cast_func,对分数进行数据转换的函数 # 更多:
# 从大到小排序
# zrevrange(name, start, end, withscores=False, score_cast_func=float) # 按照分数范围获取name对应的有序集合的元素
# zrangebyscore(name, min, max, start=None, num=None, withscores=False, score_cast_func=float)
# 从大到小排序
# zrevrangebyscore(name, max, min, start=None, num=None, withscores=False, score_cast_func=float)
zrank(name, value)
# 获取某个值在 name对应的有序集合中的排行(从 0 开始)
# 更多:
# zrevrank(name, value),从大到小排序
# 当有序集合的所有成员都具有相同的分值时,有序集合的元素会根据成员的 值 (lexicographical ordering)来进行排序,而这个命令则可以返回给定的有序集合键 key 中, 元素的值介于 min 和 max 之间的成员
# 对集合中的每个成员进行逐个字节的对比(byte-by-byte compare), 并按照从低到高的顺序, 返回排序后的集合成员。 如果两个字符串有一部分内容是相同的话, 那么命令会认为较长的字符串比较短的字符串要大 # 参数:
# name,redis的name
# min,左区间(值)。 + 表示正无限; - 表示负无限; ( 表示开区间; [ 则表示闭区间
# min,右区间(值)
# start,对结果进行分片处理,索引位置
# num,对结果进行分片处理,索引后面的num个元素 # 如:
# ZADD myzset 0 aa 0 ba 0 ca 0 da 0 ea 0 fa 0 ga
# r.zrangebylex('myzset', "-", "[ca") 结果为:['aa', 'ba', 'ca'] # 更多:
# 从大到小排序
# zrevrangebylex(name, max, min, start=None, num=None)
zrem(name, values)
# 删除name对应的有序集合中值是values的成员 # 如:zrem('zz', ['s1', 's2'])
zremrangebyrank(name, min, max)
# 根据排行范围删除
zremrangebyscore(name, min, max)
# 根据分数范围删除
zremrangebylex(name, min, max)
# 根据值返回删除
zscore(name, value)
# 获取name对应有序集合中 value 对应的分数
zinterstore(dest, keys, aggregate=None)
# 获取两个有序集合的交集,如果遇到相同值不同分数,则按照aggregate进行操作
# aggregate的值为: SUM MIN MAX
zunionstore(dest, keys, aggregate=None)
# 获取两个有序集合的并集,如果遇到相同值不同分数,则按照aggregate进行操作 # aggregate的值为: SUM MIN MAX
zscan(name, cursor=0, match=None, count=None, score_cast_func=float)
zscan_iter(name, match=None, count=None,score_cast_func=float)
# 同字符串相似,相较于字符串新增score_cast_func,用来对分数进行操作
其他常用操作
delete(*names)
# 根据删除redis中的任意数据类型
exists(name)
# 检测redis的name是否存在
keys(pattern='*')
# 根据模型获取redis的name # 更多:
# KEYS * 匹配数据库中所有 key 。
# KEYS h?llo 匹配 hello , hallo 和 hxllo 等。
# KEYS h*llo 匹配 hllo 和 heeeeello 等。
# KEYS h[ae]llo 匹配 hello 和 hallo ,但不匹配 hillo
expire(name ,time)
# 为某个redis的某个name设置超时时间
rename(src, dst)
# 对redis的name重命名为
move(name, db))
# 将redis的某个值移动到指定的db下
randomkey()
# 随机获取一个redis的name(不删除)
type(name)
# 获取name对应值的类型
scan(cursor=0, match=None, count=None)
scan_iter(match=None, count=None)
# 同字符串操作,用于增量迭代获取key
4.发布订阅
发布者:服务器
订阅者:Dashboad和数据处理
Demo如下:
#!/usr/bin/env python
# -*- coding:utf-8 -*- import redis class RedisHelper: def __init__(self):
self.__conn = redis.Redis(host='10.211.55.4')
self.chan_sub = 'fm104.5'
self.chan_pub = 'fm104.5' def public(self, msg):
self.__conn.publish(self.chan_pub, msg)
return True def subscribe(self):
pub = self.__conn.pubsub()
pub.subscribe(self.chan_sub)
pub.parse_response()
return pub
RedisHelper
订阅者:
#!/usr/bin/env python
# -*- coding:utf-8 -*- from monitor.RedisHelper import RedisHelper obj = RedisHelper()
redis_sub = obj.subscribe() while True:
msg= redis_sub.parse_response()
print msg
发布者:
#!/usr/bin/env python
# -*- coding:utf-8 -*- from monitor.RedisHelper import RedisHelper obj = RedisHelper()
obj.public('hello')
更多参见:https://github.com/andymccurdy/redis-py/
http://doc.redisfans.com/
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