Module: check_mk
Branch: master
Commit: f9be8af276fb07d66f7b84c475cbd10eb0c6a201
URL:
http://git.mathias-kettner.de/git/?p=check_mk.git;a=commit;h=f9be8af276fb07…
Author: Lars Michelsen <lm(a)mathias-kettner.de>
Date: Wed Sep 28 13:05:55 2016 +0200
prediction: Verbose logging cleanup
---
modules/prediction.py | 19 +++++++------------
1 file changed, 7 insertions(+), 12 deletions(-)
diff --git a/modules/prediction.py b/modules/prediction.py
index e476ebf..1a31b33 100644
--- a/modules/prediction.py
+++ b/modules/prediction.py
@@ -222,18 +222,15 @@ def get_predictive_levels(dsname, params, cf, levels_factor=1.0):
last_info = eval(file(info_file).read())
for k, v in params.items():
if last_info.get(k) != v:
- if opt_debug:
- sys.stderr.write("Prediction parameters have changed.\n")
+ verbose("Prediction parameters have changed")
last_info = None
break
except IOError:
- if opt_debug:
- sys.stderr.write("No previous prediction for group %s available.\n"
% timegroup)
+ verbose("No previous prediction for group %s available." % timegroup)
last_info = None
if last_info and last_info["time"] + period_info["valid"] *
period_info["slice"] < now:
- if opt_debug:
- sys.stderr.write("Prediction of %s outdated.\n" % timegroup)
+ verbose("Prediction of %s outdated" % timegroup)
last_info = None
if last_info:
@@ -249,16 +246,15 @@ def get_predictive_levels(dsname, params, cf, levels_factor=1.0):
try:
info = eval(file(dir + "/" + f).read())
if info["period"] != params["period"]:
- if opt_debug:
- sys.stderr.write("Removing obsolete prediction
%s\n" % f[:-5])
+ verbose("Removing obsolete prediction %s" % f[:-5])
os.remove(dir + "/" + f)
os.remove(dir + "/" + f[:-5])
except:
pass
- if opt_debug:
- sys.stderr.write("Computing prediction for time group %s.\n" %
timegroup)
+ verbose("Computing prediction for time group %s" % timegroup)
prediction = compute_prediction(pred_file, timegroup, params, period_info,
from_time, dsname, cf)
+
info = {
"time" : now,
"range" : (from_time, until_time),
@@ -267,6 +263,7 @@ def get_predictive_levels(dsname, params, cf, levels_factor=1.0):
"slice" : period_info["slice"],
}
info.update(params)
+
file(info_file, "w").write("%r\n" % info)
file(pred_file, "w").write("%r\n" % prediction)
@@ -302,8 +299,6 @@ def get_predictive_levels(dsname, params, cf, levels_factor=1.0):
else:
levels.append((None, None))
-
- # print levels
return ref_value, levels