How to use _get_hostnames_in_bucket method in autotest

Best Python code snippet using autotest_python Github


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...528 plot_info = MetricsPlot(query_dict, plot_type, inverted_series,529 normalize_to, drilldown_callback)530 figure, area_data = _create_metrics_plot_helper(plot_info, extra_text)531 return _create_image_html(figure, area_data, plot_info)532def _get_hostnames_in_bucket(hist_data, bucket):533 """\534 Get all the hostnames that constitute a particular bucket in the histogram.535 hist_data: list containing tuples of (hostname, pass_rate)536 bucket: tuple containing the (low, high) values of the target bucket537 """538 return [hostname for hostname, pass_rate in hist_data539 if bucket[0] <= pass_rate < bucket[1]]540def _create_qual_histogram_helper(plot_info, extra_text=None):541 """\542 Create a machine qualification histogram of the given data.543 plot_info: a QualificationHistogram544 extra_text: text to show at the upper-left of the graph545 TODO(showard): move much or all of this into methods on546 QualificationHistogram547 """548 cursor = readonly_connection.cursor()549 cursor.execute(plot_info.query)550 if not cursor.rowcount:551 raise NoDataError('query did not return any data')552 # Lists to store the plot data.553 # hist_data store tuples of (hostname, pass_rate) for machines that have554 # pass rates between 0 and 100%, exclusive.555 # no_tests is a list of machines that have run none of the selected tests556 # no_pass is a list of machines with 0% pass rate557 # perfect is a list of machines with a 100% pass rate558 hist_data = []559 no_tests = []560 no_pass = []561 perfect = []562 # Construct the lists of data to plot563 for hostname, total, good in cursor.fetchall():564 if total == 0:565 no_tests.append(hostname)566 continue567 if good == 0:568 no_pass.append(hostname)569 elif good == total:570 perfect.append(hostname)571 else:572 percentage = 100.0 * good / total573 hist_data.append((hostname, percentage))574 interval = plot_info.interval575 bins = range(0, 100, interval)576 if bins[-1] != 100:577 bins.append(bins[-1] + interval)578 figure, height = _create_figure(_SINGLE_PLOT_HEIGHT)579 subplot = figure.add_subplot(1, 1, 1)580 # Plot the data and get all the bars plotted581 _,_, bars = subplot.hist([data[1] for data in hist_data],582 bins=bins, align='left')583 bars +=[-interval], len(no_pass),584 width=interval, align='center')585 bars +=[bins[-1]], len(perfect),586 width=interval, align='center')587 bars +=[-3 * interval], len(no_tests),588 width=interval, align='center')589 buckets = [(bin, min(bin + interval, 100)) for bin in bins[:-1]]590 # set the x-axis range to cover all the normal bins plus the three "special"591 # ones - N/A (3 intervals left), 0% (1 interval left) ,and 100% (far right)592 subplot.set_xlim(-4 * interval, bins[-1] + interval)593 subplot.set_xticks([-3 * interval, -interval] + bins + [100 + interval])594 subplot.set_xticklabels(['N/A', '0%'] +595 ['%d%% - <%d%%' % bucket for bucket in buckets] +596 ['100%'], rotation=90, size='small')597 # Find the coordinates on the image for each bar598 x = []599 y = []600 for bar in bars:601 x.append(bar.get_x())602 y.append(bar.get_height())603 f = subplot.plot(x, y, linestyle='None')[0]604 upper_left_coords = f.get_transform().transform(zip(x, y))605 bottom_right_coords = f.get_transform().transform(606 [(x_val + interval, 0) for x_val in x])607 # Set the title attributes608 titles = ['%d%% - <%d%%: %d machines' % (bucket[0], bucket[1], y_val)609 for bucket, y_val in zip(buckets, y)]610 titles.append('0%%: %d machines' % len(no_pass))611 titles.append('100%%: %d machines' % len(perfect))612 titles.append('N/A: %d machines' % len(no_tests))613 # Get the hostnames for each bucket in the histogram614 names_list = [_get_hostnames_in_bucket(hist_data, bucket)615 for bucket in buckets]616 names_list += [no_pass, perfect]617 if plot_info.filter_string:618 plot_info.filter_string += ' AND '619 # Construct the list of drilldown parameters to be passed when the user620 # clicks on the bar.621 params = []622 for names in names_list:623 if names:624 hostnames = ','.join(_quote(hostname) for hostname in names)625 hostname_filter = 'hostname IN (%s)' % hostnames626 full_filter = plot_info.filter_string + hostname_filter627 params.append({'type': 'normal',628 'filterString': full_filter})...

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