Update docs in parallelize again.

diff --git a/src/pyutils/parallelize/parallelize.py b/src/pyutils/parallelize/parallelize.py
index 7071ef337269951dfb5fcf5eb828d1313441dc6d..0004f17d8a8bbab65e47dc9e6fa448cb5e83a618 100644 (file)
--- a/src/pyutils/parallelize/parallelize.py
+++ b/src/pyutils/parallelize/parallelize.py
@@ -74,18 +74,20 @@ do some setup work:
     If you're trying to set this up and struggling, email me at
     scott.gasch@gmail.com.  I'm happy to help.
 
-    What you get back when you call a decorated message is a
+    What you get back when you call a decorated function (using
+    threads, processes or a remote worker) is a
     :class:`pyutils.parallelize.smart_future.SmartFuture`.  This class
     attempts to transparently wrap a normal Python :class:`Future`
     (see
     https://docs.python.org/3/library/concurrent.futures.html#future-objects).
     If your code just uses the result of a `parallelized` method it
-    will block waiting on the result of the method as soon as it uses
-    the result in a manner that requires its value to be known
-    (e.g. using it in an expression, calling a method on it, hashing
-    it, etc...)  But you can do operations that do not require the
-    value to be known (e.g. storing it in a list, storing it as a
-    value in a dict, etc...) without blocking.
+    will block waiting on the result of the wrapped function as soon
+    as it uses that result in a manner that requires its value to be
+    known (e.g. using it in an expression, calling a method on it,
+    passing it into a method, hashing it / using it as a dict key,
+    etc...)  But you can do operations that do not require the value
+    to be known (e.g. storing it in a list, storing it as a value in a
+    dict, etc...) safely without blocking.
 
     There are two helper methods in
     :mod:`pyutils.parallelize.smart_future` to help deal with these
@@ -129,10 +131,12 @@ def parallelize(
         def my_function(a, b, c) -> int:
             ...do some slow / expensive work, e.g., an http request
 
+        # Run with background subprocess
         @p.parallelize(method=Method.PROCESS)
         def my_other_function(d, e, f) -> str:
             ...do more really expensive work, e.g., a network read
 
+        # Run in a helper process on another machine.
         @p.parallelize(method=Method.REMOTE)
         def my_other_other_function(g, h) -> int:
             ...this work will be distributed to a remote machine pool