From b76bd7a7f6b8a3b2c97bfedc61f06f070ca56e2a Mon Sep 17 00:00:00 2001
From: Hendrik Makait <hendrik@coiled.io>
Date: Thu, 17 Aug 2023 12:42:17 +0200
Subject: [PATCH] Update docs

---
 distributed/shuffle/_rechunk.py | 11 ++++-------
 distributed/shuffle/_shuffle.py |  9 +++------
 2 files changed, 7 insertions(+), 13 deletions(-)

diff --git a/distributed/shuffle/_rechunk.py b/distributed/shuffle/_rechunk.py
index 0a28da5a4b..d9f3e17975 100644
--- a/distributed/shuffle/_rechunk.py
+++ b/distributed/shuffle/_rechunk.py
@@ -293,15 +293,14 @@ class ArrayRechunkRun(ShuffleRun[NDIndex, "np.ndarray"]):
     This object is responsible for splitting, sending, receiving and combining
     data shards.
 
-    It is entirely agnostic to the distributed system and can perform a shuffle
-    with other `Shuffle` instances using `rpc` and `broadcast`.
+    It is entirely agnostic to the distributed system and can perform a rechunk
+    with other run instances using `rpc``.
 
-    The user of this needs to guarantee that only `Shuffle`s of the same unique
-    `ShuffleID` interact.
+    The user of this needs to guarantee that only `ArrayRechunkRun`s of the same unique
+    `ShuffleID` and `run_id` interact.
 
     Parameters
     ----------
-    # FIXME
     worker_for:
         A mapping partition_id -> worker_address.
     old:
@@ -318,8 +317,6 @@ class ArrayRechunkRun(ShuffleRun[NDIndex, "np.ndarray"]):
         The scratch directory to buffer data in.
     executor:
         Thread pool to use for offloading compute.
-    loop:
-        The event loop.
     rpc:
         A callable returning a PooledRPCCall to contact other Shuffle instances.
         Typically a ConnectionPool.
diff --git a/distributed/shuffle/_shuffle.py b/distributed/shuffle/_shuffle.py
index 78cec1a740..e16340c639 100644
--- a/distributed/shuffle/_shuffle.py
+++ b/distributed/shuffle/_shuffle.py
@@ -342,14 +342,13 @@ class DataFrameShuffleRun(ShuffleRun[int, "pd.DataFrame"]):
     data shards.
 
     It is entirely agnostic to the distributed system and can perform a shuffle
-    with other `Shuffle` instances using `rpc` and `broadcast`.
+    with other run instances using `rpc`.
 
-    The user of this needs to guarantee that only `Shuffle`s of the same unique
-    `ShuffleID` interact.
+    The user of this needs to guarantee that only `DataFrameShuffleRun`s of the
+    same unique `ShuffleID` and `run_id` interact.
 
     Parameters
     ----------
-    # FIXME
     worker_for:
         A mapping partition_id -> worker_address.
     column:
@@ -364,8 +363,6 @@ class DataFrameShuffleRun(ShuffleRun[int, "pd.DataFrame"]):
         The scratch directory to buffer data in.
     executor:
         Thread pool to use for offloading compute.
-    loop:
-        The event loop.
     rpc:
         A callable returning a PooledRPCCall to contact other Shuffle instances.
         Typically a ConnectionPool.