#!/usr/bin/env python

#

# Copyright 2007 Google Inc.

#

# Licensed under the Apache License, Version 2.0 (the "License");

# you may not use this file except in compliance with the License.

# You may obtain a copy of the License at

#

#     http://www.apache.org/licenses/LICENSE-2.0

#

# Unless required by applicable law or agreed to in writing, software

# distributed under the License is distributed on an "AS IS" BASIS,

# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

# See the License for the specific language governing permissions and

# limitations under the License.

#

"""Memcache API.

Provides memcached-alike API to application developers to store

data in memory when reliable storage via the DataStore API isn't

required and higher performance is desired.

"""

import cStringIO

import math

import pickle

import types

from google.appengine.api import api_base_pb

from google.appengine.api import apiproxy_stub_map

from google.appengine.api.memcache import memcache_service_pb

from google.appengine.runtime import apiproxy_errors

MemcacheSetResponse = memcache_service_pb.MemcacheSetResponse

MemcacheSetRequest = memcache_service_pb.MemcacheSetRequest

MemcacheGetResponse = memcache_service_pb.MemcacheGetResponse

MemcacheGetRequest = memcache_service_pb.MemcacheGetRequest

MemcacheDeleteResponse = memcache_service_pb.MemcacheDeleteResponse

MemcacheDeleteRequest = memcache_service_pb.MemcacheDeleteRequest

MemcacheIncrementResponse = memcache_service_pb.MemcacheIncrementResponse

MemcacheIncrementRequest = memcache_service_pb.MemcacheIncrementRequest

MemcacheFlushResponse = memcache_service_pb.MemcacheFlushResponse

MemcacheFlushRequest = memcache_service_pb.MemcacheFlushRequest

MemcacheStatsRequest = memcache_service_pb.MemcacheStatsRequest

MemcacheStatsResponse = memcache_service_pb.MemcacheStatsResponse

DELETE_NETWORK_FAILURE = 0

DELETE_ITEM_MISSING = 1

DELETE_SUCCESSFUL = 2

MAX_KEY_SIZE = 250

MAX_VALUE_SIZE = 10 ** 6

STAT_HITS = 'hits'

STAT_MISSES = 'misses'

STAT_BYTE_HITS = 'byte_hits'

STAT_ITEMS = 'items'

STAT_BYTES = 'bytes'

STAT_OLDEST_ITEM_AGES = 'oldest_item_age'

FLAG_TYPE_MASK = 7

FLAG_COMPRESSED = 1 << 3

TYPE_STR = 0

TYPE_UNICODE = 1

TYPE_PICKLED = 2

TYPE_INT = 3

TYPE_LONG = 4

TYPE_BOOL = 5

def _key_string(key, key_prefix='', server_to_user_dict=None):

  """Utility function to handle different ways of requesting keys.

  Args:

    key: Either a string or tuple of (shard_number, string).  In Google App

      Engine the sharding is automatic so the shard number is ignored.

      To memcache, the key is just bytes (no defined encoding).

    key_prefix: Optional string prefix to prepend to key.

    server_to_user_dict: Optional dictionary to populate with a mapping of

      server-side key (which includes the key_prefix) to user-supplied key

      (which does not have the prefix).

  Returns:

    The key as a non-unicode string prepended with key_prefix. This is the key

    sent to and stored by the server.

  Raises:

    TypeError: If provided key isn't a string or tuple of (int, string)

      or key_prefix or server_to_user_dict are of the wrong type.

    ValueError: If the key, when translated to the server key, is more than

      250 bytes in length.

  """

  if type(key) is types.TupleType:

    key = key[1]

  if not isinstance(key, basestring):

    raise TypeError('Key must be a string instance, received %r' % key)

  if not isinstance(key_prefix, basestring):

    raise TypeError('key_prefix must be a string instance, received %r' %

                    key_prefix)

  server_key = key_prefix + key

  if isinstance(server_key, unicode):

    server_key = server_key.encode('utf-8')

  if len(server_key) > MAX_KEY_SIZE:

    raise ValueError('Keys may not be more than %d bytes in length, '

                     'received %d bytes' % (MAX_KEY_SIZE, len(server_key)))

  if server_to_user_dict is not None:

    if not isinstance(server_to_user_dict, dict):

      raise TypeError('server_to_user_dict must be a dict instance, ' +

                      'received %r' % key)

    server_to_user_dict[server_key] = key

  return server_key

def _validate_encode_value(value, do_pickle):

  """Utility function to validate and encode server keys and values.

  Args:

    value: Value to store in memcache. If it's a string, it will get passed

      along as-is. If it's a unicode string, it will be marked appropriately,

      such that retrievals will yield a unicode value. If it's any other data

      type, this function will attempt to pickle the data and then store the

      serialized result, unpickling it upon retrieval.

    do_pickle: Callable that takes an object and returns a non-unicode

      string containing the pickled object.

  Returns:

    Tuple (stored_value, flags) where:

      stored_value: The value as a non-unicode string that should be stored

        in memcache.

      flags: An integer with bits set from the FLAG_* constants in this file

        to indicate the encoding of the key and value.

  Raises:

    ValueError: If the encoded value is too large.

    pickle.PicklingError: If the value is not a string and could not be pickled.

    RuntimeError: If a complicated data structure could not be pickled due to

      too many levels of recursion in its composition.

  """

  flags = 0

  stored_value = value

  if isinstance(value, str):

    pass

  elif isinstance(value, unicode):

    stored_value = value.encode('utf-8')

    flags |= TYPE_UNICODE

  elif isinstance(value, bool):

    stored_value = str(int(value))

    flags |= TYPE_BOOL

  elif isinstance(value, int):

    stored_value = str(value)

    flags |= TYPE_INT

  elif isinstance(value, long):

    stored_value = str(value)

    flags |= TYPE_LONG

  else:

    stored_value = do_pickle(value)

    flags |= TYPE_PICKLED

  if len(stored_value) > MAX_VALUE_SIZE:

    raise ValueError('Values may not be more than %d bytes in length; '

                     'received %d bytes' % (MAX_VALUE_SIZE, len(stored_value)))

  return (stored_value, flags)

def _decode_value(stored_value, flags, do_unpickle):

  """Utility function for decoding values retrieved from memcache.

  Args:

    stored_value: The value as a non-unicode string that was stored.

    flags: An integer with bits set from the FLAG_* constants in this file

      that indicate the encoding of the key and value.

    do_unpickle: Callable that takes a non-unicode string object that contains

      a pickled object and returns the pickled object.

  Returns:

    The original object that was stored, be it a normal string, a unicode

    string, int, long, or a Python object that was pickled.

  Raises:

    pickle.UnpicklingError: If the value could not be unpickled.

  """

  assert isinstance(stored_value, str)

  assert isinstance(flags, (int, long))

  type_number = flags & FLAG_TYPE_MASK

  value = stored_value

  if type_number == TYPE_STR:

    return value

  elif type_number == TYPE_UNICODE:

    return value.decode('utf-8')

  elif type_number == TYPE_PICKLED:

    return do_unpickle(value)

  elif type_number == TYPE_BOOL:

    return bool(int(value))

  elif type_number == TYPE_INT:

    return int(value)

  elif type_number == TYPE_LONG:

    return long(value)

  else:

    assert False, "Unknown stored type"

  assert False, "Shouldn't get here."

class Client(object):

  """Memcache client object, through which one invokes all memcache operations.

  Several methods are no-ops to retain source-level compatibility

  with the existing popular Python memcache library.

  Any method that takes a 'key' argument will accept that key as a string

  (unicode or not) or a tuple of (hash_value, string) where the hash_value,

  normally used for sharding onto a memcache instance, is instead ignored, as

  Google App Engine deals with the sharding transparently. Keys in memcache are

  just bytes, without a specified encoding. All such methods may raise TypeError

  if provided a bogus key value and a ValueError if the key is too large.

  Any method that takes a 'value' argument will accept as that value any

  string (unicode or not), int, long, or pickle-able Python object, including

  all native types.  You'll get back from the cache the same type that you

  originally put in.

  """

  def __init__(self, servers=None, debug=0,

               pickleProtocol=pickle.HIGHEST_PROTOCOL,

               pickler=pickle.Pickler,

               unpickler=pickle.Unpickler,

               pload=None,

               pid=None,

               make_sync_call=apiproxy_stub_map.MakeSyncCall):

    """Create a new Client object.

    No parameters are required.

    Arguments:

      servers: Ignored; only for compatibility.

      debug: Ignored; only for compatibility.

      pickleProtocol: Pickle protocol to use for pickling the object.

      pickler: pickle.Pickler sub-class to use for pickling.

      unpickler: pickle.Unpickler sub-class to use for unpickling.

      pload: Callable to use for retrieving objects by persistent id.

      pid: Callable to use for determine the persistent id for objects, if any.

      make_sync_call: Function to use to make an App Engine service call.

        Used for testing.

    """

    self._pickle_data = cStringIO.StringIO()

    self._pickler_instance = pickler(self._pickle_data,

                                     protocol=pickleProtocol)

    self._unpickler_instance = unpickler(self._pickle_data)

    if pid is not None:

      self._pickler_instance.persistent_id = pid

    if pload is not None:

      self._unpickler_instance.persistent_load = pload

    def DoPickle(value):

      self._pickle_data.truncate(0)

      self._pickler_instance.clear_memo()

      self._pickler_instance.dump(value)

      return self._pickle_data.getvalue()

    self._do_pickle = DoPickle

    def DoUnpickle(value):

      self._pickle_data.truncate(0)

      self._pickle_data.write(value)

      self._pickle_data.seek(0)

      self._unpickler_instance.memo.clear()

      return self._unpickler_instance.load()

    self._do_unpickle = DoUnpickle

    self._make_sync_call = make_sync_call

  def set_servers(self, servers):

    """Sets the pool of memcache servers used by the client.

    This is purely a compatibility method.  In Google App Engine, it's a no-op.

    """

    pass

  def disconnect_all(self):

    """Closes all connections to memcache servers.

    This is purely a compatibility method.  In Google App Engine, it's a no-op.

    """

    pass

  def forget_dead_hosts(self):

    """Resets all servers to the alive status.

    This is purely a compatibility method.  In Google App Engine, it's a no-op.

    """

    pass

  def debuglog(self):

    """Logging function for debugging information.

    This is purely a compatibility method.  In Google App Engine, it's a no-op.

    """

    pass

  def get_stats(self):

    """Gets memcache statistics for this application.

    All of these statistics may reset due to various transient conditions. They

    provide the best information available at the time of being called.

    Returns:

      Dictionary mapping statistic names to associated values. Statistics and

      their associated meanings:

        hits: Number of cache get requests resulting in a cache hit.

        misses: Number of cache get requests resulting in a cache miss.

        byte_hits: Sum of bytes transferred on get requests. Rolls over to

          zero on overflow.

        items: Number of key/value pairs in the cache.

        bytes: Total size of all items in the cache.

        oldest_item_age: How long in seconds since the oldest item in the

          cache was accessed. Effectively, this indicates how long a new

          item will survive in the cache without being accessed. This is

          _not_ the amount of time that has elapsed since the item was

          created.

      On error, returns None.

    """

    request = MemcacheStatsRequest()

    response = MemcacheStatsResponse()

    try:

      self._make_sync_call('memcache', 'Stats', request, response)

    except apiproxy_errors.Error:

      return None

    if not response.has_stats():

      return None

    stats = response.stats()

    return {

      STAT_HITS: stats.hits(),

      STAT_MISSES: stats.misses(),

      STAT_BYTE_HITS: stats.byte_hits(),

      STAT_ITEMS: stats.items(),

      STAT_BYTES: stats.bytes(),

      STAT_OLDEST_ITEM_AGES: stats.oldest_item_age(),

    }

  def flush_all(self):

    """Deletes everything in memcache.

    Returns:

      True on success, False on RPC or server error.

    """

    request = MemcacheFlushRequest()

    response = MemcacheFlushResponse()

    try:

      self._make_sync_call('memcache', 'FlushAll', request, response)

    except apiproxy_errors.Error:

      return False

    return True

    """Looks up a single key in memcache.

    If you have multiple items to load, though, it's much more efficient

    to use get_multi() instead, which loads them in one bulk operation,

    reducing the networking latency that'd otherwise be required to do

    many serialized get() operations.

    Args:

      key: The key in memcache to look up.  See docs on Client

        for details of format.

    Returns:

      The value of the key, if found in memcache, else None.

    """

    request = MemcacheGetRequest()

    request.add_key(_key_string(key))

    response = MemcacheGetResponse()

    try:

      self._make_sync_call('memcache', 'Get', request, response)

    except apiproxy_errors.Error:

      return None

    if not response.item_size():

      return None

    return _decode_value(response.item(0).value(),

                         response.item(0).flags(),

                         self._do_unpickle)

    """Looks up multiple keys from memcache in one operation.

    This is the recommended way to do bulk loads.

    Args:

      keys: List of keys to look up.  Keys may be strings or

        tuples of (hash_value, string).  Google App Engine

        does the sharding and hashing automatically, though, so the hash

        value is ignored.  To memcache, keys are just series of bytes,

        and not in any particular encoding.

      key_prefix: Prefix to prepend to all keys when talking to the server;

        not included in the returned dictionary.

    Returns:

      A dictionary of the keys and values that were present in memcache.

      Even if the key_prefix was specified, that key_prefix won't be on

      the keys in the returned dictionary.

    """

    request = MemcacheGetRequest()

    response = MemcacheGetResponse()

    user_key = {}

    for key in keys:

      request.add_key(_key_string(key, key_prefix, user_key))

    try:

      self._make_sync_call('memcache', 'Get', request, response)

    except apiproxy_errors.Error:

      return {}

    return_value = {}

    for returned_item in response.item_list():

      value = _decode_value(returned_item.value(), returned_item.flags(),

                            self._do_unpickle)

      return_value[user_key[returned_item.key()]] = value

    return return_value

    """Deletes a key from memcache.

    Args:

      key: Key to delete.  See docs on Client for detils.

      seconds: Optional number of seconds to make deleted items 'locked'

        for 'add' operations. Value can be a delta from current time (up to

        1 month), or an absolute Unix epoch time.  Defaults to 0, which means

        items can be immediately added.  With or without this option,

        a 'set' operation will always work.  Float values will be rounded up to

        the nearest whole second.

    Returns:

      DELETE_NETWORK_FAILURE (0) on network failure,

      DELETE_ITEM_MISSING (1) if the server tried to delete the item but

      didn't have it, or

      DELETE_SUCCESSFUL (2) if the item was actually deleted.

      This can be used as a boolean value, where a network failure is the

      only bad condition.

    """

    if not isinstance(seconds, (int, long, float)):

      raise TypeError('Delete timeout must be a number.')

    if seconds < 0:

      raise ValueError('Delete timeout must be non-negative.')

    request = MemcacheDeleteRequest()

    response = MemcacheDeleteResponse()

    delete_item = request.add_item()

    delete_item.set_key(_key_string(key))

    delete_item.set_delete_time(int(math.ceil(seconds)))

    try:

      self._make_sync_call('memcache', 'Delete', request, response)

    except apiproxy_errors.Error:

      return DELETE_NETWORK_FAILURE

    assert response.delete_status_size() == 1, 'Unexpected status size.'

    if response.delete_status(0) == MemcacheDeleteResponse.DELETED:

      return DELETE_SUCCESSFUL

    elif response.delete_status(0) == MemcacheDeleteResponse.NOT_FOUND:

      return DELETE_ITEM_MISSING

    assert False, 'Unexpected deletion status code.'

    """Delete multiple keys at once.

    Args:

      keys: List of keys to delete.

      seconds: Optional number of seconds to make deleted items 'locked'

        for 'add' operations. Value can be a delta from current time (up to

        1 month), or an absolute Unix epoch time.  Defaults to 0, which means

        items can be immediately added.  With or without this option,

        a 'set' operation will always work.  Float values will be rounded up to

        the nearest whole second.

      key_prefix: Prefix to put on all keys when sending specified

        keys to memcache.  See docs for get_multi() and set_multi().

    Returns:

      True if all operations completed successfully.  False if one

      or more failed to complete.

    """

    if not isinstance(seconds, (int, long, float)):

      raise TypeError('Delete timeout must be a number.')

    if seconds < 0:

      raise ValueError('Delete timeout must not be negative.')

    request = MemcacheDeleteRequest()

    response = MemcacheDeleteResponse()

    for key in keys:

      delete_item = request.add_item()

      delete_item.set_key(_key_string(key, key_prefix=key_prefix))