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mirror of https://github.com/systemd/systemd-stable.git synced 2024-12-22 13:33:56 +03:00

[gdb-sd_dump_hashmaps.py] String Formatting Update (#7819)

Changes: % changed as .format()
This commit is contained in:
Batuhan Osman Taşkaya 2018-01-27 16:03:08 +03:00 committed by Zbigniew Jędrzejewski-Szmek
parent f3ad25df08
commit 7c4a807277

View File

@ -51,7 +51,7 @@ class sd_dump_hashmaps(gdb.Command):
t = ["plain", "ordered", "set"][int(h["type"])]
print "%s, %s, %s, %d, %d, %d, %s (%s:%d)" % (t, h["hash_ops"], bool(h["has_indirect"]), n_entries, d["max_entries"], n_buckets, d["func"], d["file"], d["line"])
print "{}, {}, {}, {}, {}, {}, {} ({}:{})".format(t, h["hash_ops"], bool(h["has_indirect"]), n_entries, d["max_entries"], n_buckets, d["func"], d["file"], d["line"])
if arg != "" and n_entries > 0:
dib_raw_addr = storage_ptr + (all_entry_sizes[h["type"]] * n_buckets)
@ -63,10 +63,10 @@ class sd_dump_hashmaps(gdb.Command):
for dib in sorted(iter(histogram)):
if dib != 255:
print "%3d %8d %f%% of entries" % (dib, histogram[dib], 100.0*histogram[dib]/n_entries)
print "{:>3} {:>8} {} of entries".format(dib, histogram[dib], 100.0*histogram[dib]/n_entries)
else:
print "%3d %8d %f%% of slots" % (dib, histogram[dib], 100.0*histogram[dib]/n_buckets)
print "mean DIB of entries: %f" % (sum([dib*histogram[dib] for dib in iter(histogram) if dib != 255])*1.0/n_entries)
print "{:>3} {:>8} {} of slots".format(dib, histogram[dib], 100.0*histogram[dib]/n_buckets)
print "mean DIB of entries: {}".format(sum([dib*histogram[dib] for dib in iter(histogram) if dib != 255])*1.0/n_entries)
blocks = []
current_len = 1
@ -87,9 +87,9 @@ class sd_dump_hashmaps(gdb.Command):
if len(blocks) > 1 and blocks[0][0] == blocks[0][1] and blocks[-1][0] == n_buckets - 1:
blocks[0][1] += blocks[-1][1]
blocks = blocks[0:-1]
print "max block: %s" % max(blocks, key=lambda a: a[1])
print "sum block lens: %d" % sum(b[1] for b in blocks)
print "mean block len: %f" % (1.0 * sum(b[1] for b in blocks) / len(blocks))
print "max block: {}".format(max(blocks, key=lambda a: a[1]))
print "sum block lens: {}".format(sum(b[1] for b in blocks))
print "mean block len: {}".format((1.0 * sum(b[1] for b in blocks) / len(blocks)))
d = d["debug_list_next"]