Merge branch 'master' into lazythread

1 files changed, 56 insertions, 0 deletions

diff --git a/kafka/partitioner.py b/kafka/partitioner.py
new file mode 100644
index 0000000..84db4d5
--- /dev/null
+++ b/kafka/partitioner.py
@@ -0,0 +1,56 @@
+from itertools import cycle
+
+
+class Partitioner(object):
+    """
+    Base class for a partitioner
+    """
+    def __init__(self, partitions):
+        """
+        Initialize the partitioner
+
+        partitions - A list of available partitions (during startup)
+        """
+        self.partitions = partitions
+
+    def partition(self, key, partitions):
+        """
+        Takes a string key and num_partitions as argument and returns
+        a partition to be used for the message
+
+        partitions - The list of partitions is passed in every call. This
+                     may look like an overhead, but it will be useful
+                     (in future) when we handle cases like rebalancing
+        """
+        raise NotImplemented('partition function has to be implemented')
+
+
+class RoundRobinPartitioner(Partitioner):
+    """
+    Implements a round robin partitioner which sends data to partitions
+    in a round robin fashion
+    """
+    def __init__(self, partitions):
+        self._set_partitions(partitions)
+
+    def _set_partitions(self, partitions):
+        self.partitions = partitions
+        self.iterpart = cycle(partitions)
+
+    def partition(self, key, partitions):
+        # Refresh the partition list if necessary
+        if self.partitions != partitions:
+            self._set_partitions(partitions)
+
+        return self.iterpart.next()
+
+
+class HashedPartitioner(Partitioner):
+    """
+    Implements a partitioner which selects the target partition based on
+    the hash of the key
+    """
+    def partition(self, key, partitions):
+        size = len(partitions)
+        idx = hash(key) % size
+        return partitions[idx]