it should not output anything in the shell. Everything is in $OUTDIR.
the 1st run is slower (as it starts with an empty cache), next runs should be way faster.
Add -v tp $OPTS to see the perfs of individual LP calls.
Compared to the branch, i'm currently running with smaller chunks because of this bug:
# Split the list of remaining source-ids into chunks of reasonable size to avoid timeouts.
# ~25 per request should be okay
- sz = 25
+ sz = 10
chunks = map(lambda i: new_sids[i:i+sz], xrange(0, len(new_sids), sz))
for chunk in chunks:
t = self.perf.start("getBuildSummariesForSourceIds(%d sids)" % len(chunk))
it's not particularly small anymore.
see lp:~fta/+junk/ppa-dashboard.trunk
here is how i run it (from within the branch) to create what's visible there: http:// people. ubuntu. com/~fta/ ppa-dashboard/
======= ======= ======= ======= ======= ==
OUTDIR=$(mktemp -d --tmpdir=.)
BIN=./dashboard.py
OPTS="--dir $OUTDIR --cachedir cache"
D1=$(date +%s) daily/stable, beta chromium- daily/ppa, dev stable. html mozillateam/ firefox- stable mozillateam/ thunderbird- stable mozilla- daily/ppa mozilla- security/ ppa
$BIN $OPTS -r --grouped --output chromium-daily.html chromium-
$BIN $OPTS -r --grouped --output mozillateam-
$BIN $OPTS mozillateam/ffox35
$BIN $OPTS -r ubuntu-
$BIN $OPTS -r ubuntu-
D2=$(date +%s)
DELTA=$(expr $D2 - $D1) %d-%H:% M:%S)" $DELTA sec" >> runtime.log ======= ======= ======= ======= =====
echo $(date +%Y/%m/
=======
it should not output anything in the shell. Everything is in $OUTDIR.
the 1st run is slower (as it starts with an empty cache), next runs should be way faster.
Add -v tp $OPTS to see the perfs of individual LP calls.
Compared to the branch, i'm currently running with smaller chunks because of this bug:
=== modified file 'dashboard.py'
--- dashboard.py 2010-10-24 18:35:20 +0000
+++ dashboard.py 2010-10-26 10:06:27 +0000
@@ -348,7 +348,7 @@
# Split the list of remaining source-ids into chunks of reasonable size to avoid timeouts. start(" getBuildSummari esForSourceIds( %d sids)" % len(chunk))
# ~25 per request should be okay
- sz = 25
+ sz = 10
chunks = map(lambda i: new_sids[i:i+sz], xrange(0, len(new_sids), sz))
for chunk in chunks:
t = self.perf.