do not be rediculous about precision
our data really doesn't need all the decimal points that a float offers, turn it into a human readable thing. Change-Id: Ic7a204f2446dc0df6650c5fc4a3d744db8ef602a
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@ -125,12 +125,13 @@ def classifying_rate(fails, data, engine):
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url['timestamp'])
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classifying_rate = collections.defaultdict(int)
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classifying_rate['overall'] = ((float(count) / float(total)) * 100.0)
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classifying_rate['overall'] = "%.1f" % (
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(float(count) / float(total)) * 100.0)
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for job in bad_jobs:
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if bad_jobs[job] == 0 and total_job_failures[job] == 0:
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classifying_rate[job] = 0
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else:
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classifying_rate[job] = (
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classifying_rate[job] = "%.1f" % (
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100.0 -
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(float(bad_jobs[job]) / float(total_job_failures[job]))
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* 100.0)
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