Spanner benchmarks: print() is a function in Python 3 (#5862)

Author: cclauss

bigquery/benchmark/benchmark.py

@@ -42,5 +42,5 @@
             raise Exception('found {0} columsn, expected {1}'.format(len(row), num_cols))
         num_rows += 1
     total_time = datetime.now() - start_time
-    print "query {0}: {1} rows, {2} cols, first byte {3} sec, total {4} sec"\
-        .format(query, num_rows, num_cols, first_byte_time.total_seconds(), total_time.total_seconds())
+    print("query {0}: {1} rows, {2} cols, first byte {3} sec, total {4} sec"
+        .format(query, num_rows, num_cols, first_byte_time.total_seconds(), total_time.total_seconds()))

spanner/benchmark/ycsb.py

@@ -147,38 +147,38 @@ def aggregate_metrics(latencies_ms, duration_ms, num_bucket):
                  latency in latencies_ms.iteritems()}
     overall_op_count = sum([op_count for op_count in op_counts.itervalues()])
 
-    print '[OVERALL], RunTime(ms), %f' % duration_ms
-    print '[OVERALL], Throughput(ops/sec), %f' % (float(overall_op_count) /
-                                                duration_ms * 1000.0)
+    print('[OVERALL], RunTime(ms), %f' % duration_ms)
+    print('[OVERALL], Throughput(ops/sec), %f' % (float(overall_op_count) /
+                                                duration_ms * 1000.0))
 
     for operation in op_counts.keys():
         operation_upper = operation.upper()
-        print '[%s], Operations, %d' % (operation_upper, op_counts[operation])
-        print '[%s], AverageLatency(us), %f' % (
-            operation_upper, numpy.average(latencies_ms[operation]) * 1000.0)
-        print '[%s], LatencyVariance(us), %f' % (
-            operation_upper, numpy.var(latencies_ms[operation]) * 1000.0)
-        print '[%s], MinLatency(us), %f' % (
-            operation_upper, min(latencies_ms[operation]) * 1000.0)
-        print '[%s], MaxLatency(us), %f' % (
-            operation_upper, max(latencies_ms[operation]) * 1000.0)
-        print '[%s], 95thPercentileLatency(us), %f' % (
+        print('[%s], Operations, %d' % (operation_upper, op_counts[operation]))
+        print('[%s], AverageLatency(us), %f' % (
+            operation_upper, numpy.average(latencies_ms[operation]) * 1000.0))
+        print('[%s], LatencyVariance(us), %f' % (
+            operation_upper, numpy.var(latencies_ms[operation]) * 1000.0))
+        print('[%s], MinLatency(us), %f' % (
+            operation_upper, min(latencies_ms[operation]) * 1000.0))
+        print('[%s], MaxLatency(us), %f' % (
+            operation_upper, max(latencies_ms[operation]) * 1000.0))
+        print('[%s], 95thPercentileLatency(us), %f' % (
             operation_upper,
-            numpy.percentile(latencies_ms[operation], 95.0) * 1000.0)
-        print '[%s], 99thPercentileLatency(us), %f' % (
+            numpy.percentile(latencies_ms[operation], 95.0) * 1000.0))
+        print('[%s], 99thPercentileLatency(us), %f' % (
             operation_upper,
-            numpy.percentile(latencies_ms[operation], 99.0) * 1000.0)
-        print '[%s], 99.9thPercentileLatency(us), %f' % (
+            numpy.percentile(latencies_ms[operation], 99.0) * 1000.0))
+        print('[%s], 99.9thPercentileLatency(us), %f' % (
             operation_upper,
-            numpy.percentile(latencies_ms[operation], 99.9) * 1000.0)
-        print '[%s], Return=OK, %d' % (operation_upper, op_counts[operation])
+            numpy.percentile(latencies_ms[operation], 99.9) * 1000.0))
+        print('[%s], Return=OK, %d' % (operation_upper, op_counts[operation]))
         latency_array = numpy.array(latencies_ms[operation])
         for j in range(num_bucket):
-            print '[%s], %d, %d' % (
+            print('[%s], %d, %d' % (
                 operation_upper, j,
-                ((j <= latency_array) & (latency_array < (j + 1))).sum())
-        print '[%s], >%d, %d' % (operation_upper, num_bucket,
-                                 (num_bucket <= latency_array).sum())
+                ((j <= latency_array) & (latency_array < (j + 1))).sum()))
+        print('[%s], >%d, %d' % (operation_upper, num_bucket,
+                                 (num_bucket <= latency_array).sum()))
 
 
 class WorkloadThread(threading.Thread):