Replace custom blob gRPC API with ByteStream

client/third_party/cachetools/func.py

Index: client/third_party/cachetools/func.py
diff --git a/client/third_party/cachetools/func.py b/client/third_party/cachetools/func.py
new file mode 100644
index 0000000000000000000000000000000000000000..5a2ce847713eb2bd1c30cdbacff177dcdc59b75a
--- /dev/null
+++ b/client/third_party/cachetools/func.py
@@ -0,0 +1,106 @@
+"""`functools.lru_cache` compatible memoizing function decorators."""
+
+from __future__ import absolute_import
+
+import collections
+import functools
+import random
+import time
+
+try:
+    from threading import RLock
+except ImportError:
+    from dummy_threading import RLock
+
+from . import keys
+from .lfu import LFUCache
+from .lru import LRUCache
+from .rr import RRCache
+from .ttl import TTLCache
+
+__all__ = ('lfu_cache', 'lru_cache', 'rr_cache', 'ttl_cache')
+
+
+_CacheInfo = collections.namedtuple('CacheInfo', [
+    'hits', 'misses', 'maxsize', 'currsize'
+])
+
+
+def _cache(cache, typed=False):
+    def decorator(func):
+        key = keys.typedkey if typed else keys.hashkey
+        lock = RLock()
+        stats = [0, 0]
+
+        def cache_info():
+            with lock:
+                hits, misses = stats
+                maxsize = cache.maxsize
+                currsize = cache.currsize
+            return _CacheInfo(hits, misses, maxsize, currsize)
+
+        def cache_clear():
+            with lock:
+                try:
+                    cache.clear()
+                finally:
+                    stats[:] = [0, 0]
+
+        def wrapper(*args, **kwargs):
+            k = key(*args, **kwargs)
+            with lock:
+                try:
+                    v = cache[k]
+                    stats[0] += 1
+                    return v
+                except KeyError:
+                    stats[1] += 1
+            v = func(*args, **kwargs)
+            try:
+                with lock:
+                    cache[k] = v
+            except ValueError:
+                pass  # value too large
+            return v
+        functools.update_wrapper(wrapper, func)
+        if not hasattr(wrapper, '__wrapped__'):
+            wrapper.__wrapped__ = func  # Python 2.7
+        wrapper.cache_info = cache_info
+        wrapper.cache_clear = cache_clear
+        return wrapper
+    return decorator
+
+
+def lfu_cache(maxsize=128, typed=False):
+    """Decorator to wrap a function with a memoizing callable that saves
+    up to `maxsize` results based on a Least Frequently Used (LFU)
+    algorithm.
+
+    """
+    return _cache(LFUCache(maxsize), typed)
+
+
+def lru_cache(maxsize=128, typed=False):
+    """Decorator to wrap a function with a memoizing callable that saves
+    up to `maxsize` results based on a Least Recently Used (LRU)
+    algorithm.
+
+    """
+    return _cache(LRUCache(maxsize), typed)
+
+
+def rr_cache(maxsize=128, choice=random.choice, typed=False):
+    """Decorator to wrap a function with a memoizing callable that saves
+    up to `maxsize` results based on a Random Replacement (RR)
+    algorithm.
+
+    """
+    return _cache(RRCache(maxsize, choice), typed)
+
+
+def ttl_cache(maxsize=128, ttl=600, timer=time.time, typed=False):
+    """Decorator to wrap a function with a memoizing callable that saves
+    up to `maxsize` results based on a Least Recently Used (LRU)
+    algorithm with a per-item time-to-live (TTL) value.
+    """
+    return _cache(TTLCache(maxsize, ttl, timer), typed)