sort the graph list by number of fails
this sorts the graph list by the number of fails found during the time period. That will naturally make the worst issues float to the top. Ensure our time span is a full 14 days. Change-Id: Ic26e7b2196b80fae969a768289e0550a46de8579
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@ -42,7 +42,7 @@ def main():
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ts = datetime(ts.year, ts.month, ts.day, ts.hour)
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# ms since epoch
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now = int(((ts - epoch).total_seconds()) * 1000)
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start = now - (7 * 24 * STEP)
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start = now - (14 * 24 * STEP)
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for query in classifier.queries:
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urlq = dict(search=query['query'],
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@ -54,9 +54,17 @@ def main():
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bug = dict(number=query['bug'],
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query=query['query'],
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logstash_query=logstash_query,
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fails=0,
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data=[])
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buglist.append(bug)
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results = classifier.hits_by_query(query['query'], size=3000)
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facets_for_fail = er_results.FacetSet()
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facets_for_fail.detect_facets(results,
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["build_status", "build_uuid"])
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if "FAILURE" in facets_for_fail:
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bug['fails'] = len(facets_for_fail['FAILURE'])
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facets = er_results.FacetSet()
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facets.detect_facets(results,
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["build_status", "timestamp", "build_uuid"])
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@ -70,6 +78,8 @@ def main():
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data.append([ts, 0])
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bug["data"].append(dict(label=status, data=data))
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buglist = sorted(buglist, key=lambda bug: -bug['fails'])
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out = open(args.output, 'w')
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out.write(json.dumps(buglist))
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out.close()
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