def run(args):
push = Push(args.rev)
num_scheduled = len(push.scheduled_task_labels)
num_total = len(push.target_task_labels)
percentage = round(float(num_scheduled) / num_total * 100, 1)
all_regressions = push.get_possible_regressions("label") | push.get_likely_regressions("label")
return [[
'Tasks Scheduled',
'Tasks Total',
'Percentage',
'Total Hours (scheduled)',
'Backed Out',
'Regressions (possible)',
'Regressions (likely)',
'Caught',
'Missed',
], [
num_scheduled,
num_total,
percentage,
push.scheduled_duration,
push.backedout,
len(push.get_possible_regressions("label")),
len(push.get_likely_regressions("label")),
len(all_regressions & push.scheduled_task_labels),
len(all_regressions - push.scheduled_task_labels),
]]
def go(repo_dir):
with hglib.open(repo_dir) as hg:
revs = repository.get_revs(hg, -1000, -500)
commits = repository.hg_log(hg, revs)
backouts = list(
set(commit.backedoutby for commit in commits
if commit.ever_backedout))
backedouts = list(
set(commit.node for commit in commits if commit.ever_backedout))
likely_label_count = 0
possible_label_count = 0
likely_group_count = 0
possible_group_count = 0
backout_regressions = {}
for backout in tqdm(backouts):
p = Push(backout)
label_regressions = p.get_regressions("label")
likely_label_count += len(p.get_likely_regressions("label"))
possible_label_count += len(p.get_possible_regressions("label"))
group_regressions = p.get_regressions("group")
likely_group_count += len(p.get_likely_regressions("label"))
possible_group_count += len(p.get_possible_regressions("label"))
if len(label_regressions) > 0 or len(group_regressions) > 0:
backout_regressions[backout] = {
"label": label_regressions,
"group": group_regressions,
}
print(f"Likely labels for backouts: {likely_label_count}")
print(f"Likely groups for backouts: {likely_group_count}")
print(f"Possible labels for backouts: {possible_label_count}")
print(f"Possible groups for backouts: {possible_group_count}")
backedout_regressions = {}
for backedout in tqdm(backedouts):
p = Push(backedout)
label_regressions = p.get_regressions("label")
group_regressions = p.get_regressions("group")
if (len(p.get_likely_regressions("label")) == 0
or len(p.get_likely_regressions("group")) == 0):
backedout_regressions[backedout] = {
"label": label_regressions,
"group": group_regressions,
}
with open("backout_regressions.json", "w") as f:
json.dump(backout_regressions, f)
with open("backedout_regressions.json", "w") as f:
json.dump(backedout_regressions, f)
