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# lru_cache.py -- Simple LRU cache for dulwich

# Copyright (C) 2006, 2008 Canonical Ltd

#

# Dulwich is dual-licensed under the Apache License, Version 2.0 and the GNU

# General Public License as public by the Free Software Foundation; version 2.0

# or (at your option) any later version. You can redistribute it and/or

# modify it under the terms of either of these two licenses.

#

# 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.

#

# You should have received a copy of the licenses; if not, see

# <http://www.gnu.org/licenses/> for a copy of the GNU General Public License

# and <http://www.apache.org/licenses/LICENSE-2.0> for a copy of the Apache

# License, Version 2.0.

#

"""A simple least-recently-used (LRU) cache."""

_null_key = object()

class _LRUNode(object):

    """This maintains the linked-list which is the lru internals."""

    __slots__ = ('prev', 'next_key', 'key', 'value', 'cleanup', 'size')

    def __init__(self, key, value, cleanup=None):

        self.prev = None

        self.next_key = _null_key

        self.key = key

        self.value = value

        self.cleanup = cleanup

        # TODO: We could compute this 'on-the-fly' like we used to, and remove

        #       one pointer from this object, we just need to decide if it

        #       actually costs us much of anything in normal usage

        self.size = None

    def __repr__(self):

        if self.prev is None:

            prev_key = None

        else:

            prev_key = self.prev.key

        return '%s(%r n:%r p:%r)' % (self.__class__.__name__, self.key,

                                     self.next_key, prev_key)

    def run_cleanup(self):

        if self.cleanup is not None:

            self.cleanup(self.key, self.value)

        self.cleanup = None

        # Just make sure to break any refcycles, etc

        self.value = None

class LRUCache(object):

    """A class which manages a cache of entries, removing unused ones."""

    def __init__(self, max_cache=100, after_cleanup_count=None):

        self._cache = {}

        # The "HEAD" of the lru linked list

        self._most_recently_used = None

        # The "TAIL" of the lru linked list

        self._least_recently_used = None

        self._update_max_cache(max_cache, after_cleanup_count)

    def __contains__(self, key):

        return key in self._cache

    def __getitem__(self, key):

        cache = self._cache

        node = cache[key]

        # Inlined from _record_access to decrease the overhead of __getitem__

        # We also have more knowledge about structure if __getitem__ is

        # succeeding, then we know that self._most_recently_used must not be

        # None, etc.

        mru = self._most_recently_used

        if node is mru:

            # Nothing to do, this node is already at the head of the queue

            return node.value

        # Remove this node from the old location

        node_prev = node.prev

        next_key = node.next_key

        # benchmarking shows that the lookup of _null_key in globals is faster

        # than the attribute lookup for (node is self._least_recently_used)

        if next_key is _null_key:

            # 'node' is the _least_recently_used, because it doesn't have a

            # 'next' item. So move the current lru to the previous node.

            self._least_recently_used = node_prev

        else:

            node_next = cache[next_key]

            node_next.prev = node_prev

        node_prev.next_key = next_key

        # Insert this node at the front of the list

        node.next_key = mru.key

        mru.prev = node

        self._most_recently_used = node

        node.prev = None

        return node.value

    def __len__(self):

        return len(self._cache)

    def _walk_lru(self):

        """Walk the LRU list, only meant to be used in tests."""

        node = self._most_recently_used

        if node is not None:

            if node.prev is not None:

                raise AssertionError('the _most_recently_used entry is not'

                                     ' supposed to have a previous entry'

                                     ' %s' % (node,))

        while node is not None:

            if node.next_key is _null_key:

                if node is not self._least_recently_used:

                    raise AssertionError('only the last node should have'

                                         ' no next value: %s' % (node,))

                node_next = None

            else:

                node_next = self._cache[node.next_key]

                if node_next.prev is not node:

                    raise AssertionError('inconsistency found, node.next.prev'

                                         ' != node: %s' % (node,))

            if node.prev is None:

                if node is not self._most_recently_used:

                    raise AssertionError('only the _most_recently_used should'

                                         ' not have a previous node: %s'

                                         % (node,))

            else:

                if node.prev.next_key != node.key:

                    raise AssertionError('inconsistency found, node.prev.next'

                                         ' != node: %s' % (node,))

            yield node

            node = node_next

    def add(self, key, value, cleanup=None):

        """Add a new value to the cache.

        Also, if the entry is ever removed from the cache, call

        cleanup(key, value).

        :param key: The key to store it under

        :param value: The object to store

        :param cleanup: None or a function taking (key, value) to indicate

                        'value' should be cleaned up.

        """

        if key is _null_key:

            raise ValueError('cannot use _null_key as a key')

        if key in self._cache:

            node = self._cache[key]

            node.run_cleanup()

            node.value = value

            node.cleanup = cleanup

        else:

            node = _LRUNode(key, value, cleanup=cleanup)

            self._cache[key] = node

        self._record_access(node)

        if len(self._cache) > self._max_cache:

            # Trigger the cleanup

            self.cleanup()

    def cache_size(self):

        """Get the number of entries we will cache."""

        return self._max_cache

    def get(self, key, default=None):

        node = self._cache.get(key, None)

        if node is None:

            return default

        self._record_access(node)

        return node.value

    def keys(self):

        """Get the list of keys currently cached.

        Note that values returned here may not be available by the time you

        request them later. This is simply meant as a peak into the current

        state.

        :return: An unordered list of keys that are currently cached.

        """

        return self._cache.keys()

    def items(self):

        """Get the key:value pairs as a dict."""

        return dict((k, n.value) for k, n in self._cache.items())

    def cleanup(self):

        """Clear the cache until it shrinks to the requested size.

        This does not completely wipe the cache, just makes sure it is under

        the after_cleanup_count.

        """

        # Make sure the cache is shrunk to the correct size

        while len(self._cache) > self._after_cleanup_count:

            self._remove_lru()

    def __setitem__(self, key, value):

        """Add a value to the cache, there will be no cleanup function."""

        self.add(key, value, cleanup=None)

    def _record_access(self, node):

        """Record that key was accessed."""

        # Move 'node' to the front of the queue

        if self._most_recently_used is None:

            self._most_recently_used = node

            self._least_recently_used = node

            return

        elif node is self._most_recently_used:

            # Nothing to do, this node is already at the head of the queue

            return

        # We've taken care of the tail pointer, remove the node, and insert it

        # at the front

        # REMOVE

        if node is self._least_recently_used:

            self._least_recently_used = node.prev

        if node.prev is not None:

            node.prev.next_key = node.next_key

        if node.next_key is not _null_key:

            node_next = self._cache[node.next_key]

            node_next.prev = node.prev

        # INSERT

        node.next_key = self._most_recently_used.key

        self._most_recently_used.prev = node

        self._most_recently_used = node

        node.prev = None

    def _remove_node(self, node):

        if node is self._least_recently_used:

            self._least_recently_used = node.prev

        self._cache.pop(node.key)

        # If we have removed all entries, remove the head pointer as well

        if self._least_recently_used is None:

            self._most_recently_used = None

        node.run_cleanup()

        # Now remove this node from the linked list

        if node.prev is not None:

            node.prev.next_key = node.next_key

        if node.next_key is not _null_key:

            node_next = self._cache[node.next_key]

            node_next.prev = node.prev

        # And remove this node's pointers

        node.prev = None

        node.next_key = _null_key

    def _remove_lru(self):

        """Remove one entry from the lru, and handle consequences.

        If there are no more references to the lru, then this entry should be

        removed from the cache.

        """

        self._remove_node(self._least_recently_used)

    def clear(self):

        """Clear out all of the cache."""

        # Clean up in LRU order

        while self._cache:

            self._remove_lru()

    def resize(self, max_cache, after_cleanup_count=None):

        """Change the number of entries that will be cached."""

        self._update_max_cache(max_cache,

                               after_cleanup_count=after_cleanup_count)

    def _update_max_cache(self, max_cache, after_cleanup_count=None):

        self._max_cache = max_cache

        if after_cleanup_count is None:

            self._after_cleanup_count = self._max_cache * 8 / 10

        else:

            self._after_cleanup_count = min(after_cleanup_count,

                                            self._max_cache)

        self.cleanup()

class LRUSizeCache(LRUCache):

    """An LRUCache that removes things based on the size of the values.

    This differs in that it doesn't care how many actual items there are,

    it just restricts the cache to be cleaned up after so much data is stored.

    The size of items added will be computed using compute_size(value), which

    defaults to len() if not supplied.

    """

    def __init__(self, max_size=1024*1024, after_cleanup_size=None,

                 compute_size=None):

        """Create a new LRUSizeCache.

        :param max_size: The max number of bytes to store before we start

            clearing out entries.

        :param after_cleanup_size: After cleaning up, shrink everything to this

            size.

        :param compute_size: A function to compute the size of the values. We

            use a function here, so that you can pass 'len' if you are just

            using simple strings, or a more complex function if you are using

            something like a list of strings, or even a custom object.

            The function should take the form "compute_size(value) => integer".

            If not supplied, it defaults to 'len()'

        """

        self._value_size = 0

        self._compute_size = compute_size

        if compute_size is None:

            self._compute_size = len

        self._update_max_size(max_size, after_cleanup_size=after_cleanup_size)

        LRUCache.__init__(self, max_cache=max(int(max_size/512), 1))

    def add(self, key, value, cleanup=None):

        """Add a new value to the cache.

        Also, if the entry is ever removed from the cache, call

        cleanup(key, value).

        :param key: The key to store it under

        :param value: The object to store

        :param cleanup: None or a function taking (key, value) to indicate

                        'value' should be cleaned up.

        """

        if key is _null_key:

            raise ValueError('cannot use _null_key as a key')

        node = self._cache.get(key, None)

        value_len = self._compute_size(value)

        if value_len >= self._after_cleanup_size:

            # The new value is 'too big to fit', as it would fill up/overflow

            # the cache all by itself

            if node is not None:

                # We won't be replacing the old node, so just remove it

                self._remove_node(node)

            if cleanup is not None:

                cleanup(key, value)

            return

        if node is None:

            node = _LRUNode(key, value, cleanup=cleanup)

            self._cache[key] = node

        else:

            self._value_size -= node.size

        node.size = value_len

        self._value_size += value_len

        self._record_access(node)

        if self._value_size > self._max_size:

            # Time to cleanup

            self.cleanup()

    def cleanup(self):

        """Clear the cache until it shrinks to the requested size.

        This does not completely wipe the cache, just makes sure it is under

        the after_cleanup_size.

        """

        # Make sure the cache is shrunk to the correct size

        while self._value_size > self._after_cleanup_size:

            self._remove_lru()

    def _remove_node(self, node):

        self._value_size -= node.size

        LRUCache._remove_node(self, node)

    def resize(self, max_size, after_cleanup_size=None):

        """Change the number of bytes that will be cached."""

        self._update_max_size(max_size, after_cleanup_size=after_cleanup_size)

        max_cache = max(int(max_size/512), 1)

        self._update_max_cache(max_cache)

    def _update_max_size(self, max_size, after_cleanup_size=None):

        self._max_size = max_size

        if after_cleanup_size is None:

            self._after_cleanup_size = self._max_size * 8 // 10

        else:

            self._after_cleanup_size = min(after_cleanup_size, self._max_size)