[Python-checkins] Summarize stats: Increase number of predecessor/successor pairs shown from 3 to 5. (GH-92853)

markshannon webhook-mailer at python.org
Tue May 17 05:59:34 EDT 2022


https://github.com/python/cpython/commit/93fc14933b8605c8df23073574048408df61b538
commit: 93fc14933b8605c8df23073574048408df61b538
branch: main
author: Mark Shannon <mark at hotpy.org>
committer: markshannon <mark at hotpy.org>
date: 2022-05-17T10:59:24+01:00
summary:

Summarize stats: Increase number of predecessor/successor pairs shown from 3 to 5. (GH-92853)

files:
M Tools/scripts/summarize_stats.py

diff --git a/Tools/scripts/summarize_stats.py b/Tools/scripts/summarize_stats.py
index 91b190114008e..f66fc7b684594 100644
--- a/Tools/scripts/summarize_stats.py
+++ b/Tools/scripts/summarize_stats.py
@@ -315,7 +315,7 @@ def emit_pair_counts(opcode_stats, total):
         emit_table(("Pair", "Count:", "Self:", "Cumulative:"),
             rows
         )
-    with Section("Predecessor/Successor Pairs", summary="Top 3 predecessors and successors of each opcode"):
+    with Section("Predecessor/Successor Pairs", summary="Top 5 predecessors and successors of each opcode"):
         predecessors = collections.defaultdict(collections.Counter)
         successors = collections.defaultdict(collections.Counter)
         total_predecessors = collections.Counter()
@@ -334,10 +334,10 @@ def emit_pair_counts(opcode_stats, total):
             pred_rows = succ_rows = ()
             if total1:
                 pred_rows = [(opname[pred], count, f"{count/total1:.1%}")
-                             for (pred, count) in predecessors[i].most_common(3)]
+                             for (pred, count) in predecessors[i].most_common(5)]
             if total2:
                 succ_rows = [(opname[succ], count, f"{count/total2:.1%}")
-                             for (succ, count) in successors[i].most_common(3)]
+                             for (succ, count) in successors[i].most_common(5)]
             with Section(name, 3, f"Successors and predecessors for {name}"):
                 emit_table(("Predecessors", "Count:", "Percentage:"),
                     pred_rows



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