diff options
Diffstat (limited to 'resources')
| -rw-r--r-- | resources/tools/presentation/generator_cpta.py | 52 | ||||
| -rw-r--r-- | resources/tools/presentation/generator_plots.py | 458 | ||||
| -rw-r--r-- | resources/tools/presentation/generator_tables.py | 8 | ||||
| -rw-r--r-- | resources/tools/presentation/input_data_parser.py | 12 | ||||
| -rw-r--r-- | resources/tools/presentation/pal_utils.py | 10 | ||||
| -rw-r--r-- | resources/tools/presentation/specification_CPTA.yaml | 8 | ||||
| -rw-r--r-- | resources/tools/presentation/specification_parser.py | 2 |
7 files changed, 56 insertions, 494 deletions
diff --git a/resources/tools/presentation/generator_cpta.py b/resources/tools/presentation/generator_cpta.py index 511800a988..a308f64e2e 100644 --- a/resources/tools/presentation/generator_cpta.py +++ b/resources/tools/presentation/generator_cpta.py @@ -146,7 +146,7 @@ def generate_cpta(spec, data): def _generate_trending_traces(in_data, job_name, build_info, - show_trend_line=True, name=u"", color=u""): + name=u"", color=u""): """Generate the trending traces: - samples, - outliers, regress, progress @@ -155,13 +155,11 @@ def _generate_trending_traces(in_data, job_name, build_info, :param in_data: Full data set. :param job_name: The name of job which generated the data. :param build_info: Information about the builds. - :param show_trend_line: Show moving median (trending plot). :param name: Name of the plot :param color: Name of the color for the plot. :type in_data: OrderedDict :type job_name: str :type build_info: dict - :type show_trend_line: bool :type name: str :type color: str :returns: Generated traces (list) and the evaluated result. @@ -183,7 +181,7 @@ def _generate_trending_traces(in_data, job_name, build_info, str_key = str(key) date = build_info[job_name][str_key][0] hover_str = (u"date: {date}<br>" - u"value [Mpps]: {value:.3f}<br>" + u"average [Mpps]: {value:.3f}<br>" u"stdev [Mpps]: {stdev:.3f}<br>" u"{sut}-ref: {build}<br>" u"csit-ref: mrr-{period}-build-{build_nr}<br>" @@ -216,8 +214,9 @@ def _generate_trending_traces(in_data, job_name, build_info, for key, value in zip(xaxis, data_y_pps): data_pd[key] = value - anomaly_classification, avgs_pps = classify_anomalies(data_pd) + anomaly_classification, avgs_pps, stdevs_pps = classify_anomalies(data_pd) avgs_mpps = [avg_pps / 1e6 for avg_pps in avgs_pps] + stdevs_mpps = [stdev_pps / 1e6 for stdev_pps in stdevs_pps] anomalies = OrderedDict() anomalies_colors = list() @@ -258,23 +257,30 @@ def _generate_trending_traces(in_data, job_name, build_info, ) traces = [trace_samples, ] - if show_trend_line: - trace_trend = plgo.Scatter( - x=xaxis, - y=avgs_mpps, - mode=u"lines", - line={ - u"shape": u"linear", - u"width": 1, - u"color": color, - }, - showlegend=False, - legendgroup=name, - name=f"{name}", - text=[f"trend [Mpps]: {avg:.3f}" for avg in avgs_mpps], - hoverinfo=u"text+name" + trend_hover_text = list() + for idx in range(len(data_x)): + trend_hover_str = ( + f"trend [Mpps]: {avgs_mpps[idx]:.3f}<br>" + f"stdev [Mpps]: {stdevs_mpps[idx]:.3f}" ) - traces.append(trace_trend) + trend_hover_text.append(trend_hover_str) + + trace_trend = plgo.Scatter( + x=xaxis, + y=avgs_mpps, + mode=u"lines", + line={ + u"shape": u"linear", + u"width": 1, + u"color": color, + }, + showlegend=False, + legendgroup=name, + name=f"{name}", + text=trend_hover_text, + hoverinfo=u"text+name" + ) + traces.append(trace_trend) trace_anomalies = plgo.Scatter( x=list(anomalies.keys()), @@ -354,8 +360,8 @@ def _generate_all_charts(spec, input_data): # Transform the data logging.info( - f" Creating the data set for the {graph.get(u'type', u'')} " - f"{graph.get(u'title', u'')}." + f" Creating the data set for the {graph.get(u'type', u'')} " + f"{graph.get(u'title', u'')}." ) if graph.get(u"include", None): diff --git a/resources/tools/presentation/generator_plots.py b/resources/tools/presentation/generator_plots.py index 89eb1c6521..c1e5bed893 100644 --- a/resources/tools/presentation/generator_plots.py +++ b/resources/tools/presentation/generator_plots.py @@ -27,7 +27,6 @@ import pandas as pd import plotly.offline as ploff import plotly.graph_objs as plgo -from plotly.subplots import make_subplots from plotly.exceptions import PlotlyError from pal_utils import mean, stdev @@ -55,12 +54,9 @@ def generate_plots(spec, data): generator = { u"plot_nf_reconf_box_name": plot_nf_reconf_box_name, u"plot_perf_box_name": plot_perf_box_name, - u"plot_lat_err_bars_name": plot_lat_err_bars_name, u"plot_tsa_name": plot_tsa_name, u"plot_http_server_perf_box": plot_http_server_perf_box, u"plot_nf_heatmap": plot_nf_heatmap, - u"plot_lat_hdrh_bar_name": plot_lat_hdrh_bar_name, - u"plot_lat_hdrh_percentile": plot_lat_hdrh_percentile, u"plot_hdrh_lat_by_percentile": plot_hdrh_lat_by_percentile } @@ -79,111 +75,6 @@ def generate_plots(spec, data): logging.info(u"Done.") -def plot_lat_hdrh_percentile(plot, input_data): - """Generate the plot(s) with algorithm: plot_lat_hdrh_percentile - specified in the specification file. - - :param plot: Plot to generate. - :param input_data: Data to process. - :type plot: pandas.Series - :type input_data: InputData - """ - - # Transform the data - plot_title = plot.get(u"title", u"") - logging.info( - f" Creating the data set for the {plot.get(u'type', u'')} " - f"{plot_title}." - ) - data = input_data.filter_tests_by_name( - plot, params=[u"latency", u"parent", u"tags", u"type"]) - if data is None or len(data[0][0]) == 0: - logging.error(u"No data.") - return - - fig = plgo.Figure() - - # Prepare the data for the plot - directions = [u"W-E", u"E-W"] - for color, test in enumerate(data[0][0]): - try: - if test[u"type"] in (u"NDRPDR",): - if u"-pdr" in plot_title.lower(): - ttype = u"PDR" - elif u"-ndr" in plot_title.lower(): - ttype = u"NDR" - else: - logging.warning(f"Invalid test type: {test[u'type']}") - continue - name = re.sub(REGEX_NIC, u"", test[u"parent"]. - replace(u'-ndrpdr', u''). - replace(u'2n1l-', u'')) - for idx, direction in enumerate( - (u"direction1", u"direction2", )): - try: - hdr_lat = test[u"latency"][ttype][direction][u"hdrh"] - # TODO: Workaround, HDRH data must be aligned to 4 - # bytes, remove when not needed. - hdr_lat += u"=" * (len(hdr_lat) % 4) - xaxis = list() - yaxis = list() - hovertext = list() - decoded = hdrh.histogram.HdrHistogram.decode(hdr_lat) - for item in decoded.get_recorded_iterator(): - percentile = item.percentile_level_iterated_to - if percentile != 100.0: - xaxis.append(100.0 / (100.0 - percentile)) - yaxis.append(item.value_iterated_to) - hovertext.append( - f"Test: {name}<br>" - f"Direction: {directions[idx]}<br>" - f"Percentile: {percentile:.5f}%<br>" - f"Latency: {item.value_iterated_to}uSec" - ) - fig.add_trace( - plgo.Scatter( - x=xaxis, - y=yaxis, - name=name, - mode=u"lines", - legendgroup=name, - showlegend=bool(idx), - line=dict( - color=COLORS[color] - ), - hovertext=hovertext, - hoverinfo=u"text" - ) - ) - except hdrh.codec.HdrLengthException as err: - logging.warning( - f"No or invalid data for HDRHistogram for the test " - f"{name}\n{err}" - ) - continue - else: - logging.warning(f"Invalid test type: {test[u'type']}") - continue - except (ValueError, KeyError) as err: - logging.warning(repr(err)) - - layout = deepcopy(plot[u"layout"]) - - layout[u"title"][u"text"] = \ - f"<b>Latency:</b> {plot.get(u'graph-title', u'')}" - fig[u"layout"].update(layout) - - # Create plot - file_type = plot.get(u"output-file-type", u".html") - logging.info(f" Writing file {plot[u'output-file']}{file_type}.") - try: - # Export Plot - ploff.plot(fig, show_link=False, auto_open=False, - filename=f"{plot[u'output-file']}{file_type}") - except PlotlyError as err: - logging.error(f" Finished with error: {repr(err)}") - - def plot_hdrh_lat_by_percentile(plot, input_data): """Generate the plot(s) with algorithm: plot_hdrh_lat_by_percentile specified in the specification file. @@ -336,182 +227,6 @@ def plot_hdrh_lat_by_percentile(plot, input_data): continue -def plot_lat_hdrh_bar_name(plot, input_data): - """Generate the plot(s) with algorithm: plot_lat_hdrh_bar_name - specified in the specification file. - - :param plot: Plot to generate. - :param input_data: Data to process. - :type plot: pandas.Series - :type input_data: InputData - """ - - # Transform the data - plot_title = plot.get(u"title", u"") - logging.info( - f" Creating the data set for the {plot.get(u'type', u'')} " - f"{plot_title}." - ) - data = input_data.filter_tests_by_name( - plot, params=[u"latency", u"parent", u"tags", u"type"]) - if data is None or len(data[0][0]) == 0: - logging.error(u"No data.") - return - - # Prepare the data for the plot - directions = [u"W-E", u"E-W"] - tests = list() - traces = list() - for idx_row, test in enumerate(data[0][0]): - try: - if test[u"type"] in (u"NDRPDR",): - if u"-pdr" in plot_title.lower(): - ttype = u"PDR" - elif u"-ndr" in plot_title.lower(): - ttype = u"NDR" - else: - logging.warning(f"Invalid test type: {test[u'type']}") - continue - name = re.sub(REGEX_NIC, u"", test[u"parent"]. - replace(u'-ndrpdr', u''). - replace(u'2n1l-', u'')) - histograms = list() - for idx_col, direction in enumerate( - (u"direction1", u"direction2", )): - try: - hdr_lat = test[u"latency"][ttype][direction][u"hdrh"] - # TODO: Workaround, HDRH data must be aligned to 4 - # bytes, remove when not needed. - hdr_lat += u"=" * (len(hdr_lat) % 4) - xaxis = list() - yaxis = list() - hovertext = list() - decoded = hdrh.histogram.HdrHistogram.decode(hdr_lat) - total_count = decoded.get_total_count() - for item in decoded.get_recorded_iterator(): - xaxis.append(item.value_iterated_to) - prob = float(item.count_added_in_this_iter_step) / \ - total_count * 100 - yaxis.append(prob) - hovertext.append( - f"Test: {name}<br>" - f"Direction: {directions[idx_col]}<br>" - f"Latency: {item.value_iterated_to}uSec<br>" - f"Probability: {prob:.2f}%<br>" - f"Percentile: " - f"{item.percentile_level_iterated_to:.2f}" - ) - marker_color = [COLORS[idx_row], ] * len(yaxis) - marker_color[xaxis.index( - decoded.get_value_at_percentile(50.0))] = u"red" - marker_color[xaxis.index( - decoded.get_value_at_percentile(90.0))] = u"red" - marker_color[xaxis.index( - decoded.get_value_at_percentile(95.0))] = u"red" - histograms.append( - plgo.Bar( - x=xaxis, - y=yaxis, - showlegend=False, - name=name, - marker={u"color": marker_color}, - hovertext=hovertext, - hoverinfo=u"text" - ) - ) - except hdrh.codec.HdrLengthException as err: - logging.warning( - f"No or invalid data for HDRHistogram for the test " - f"{name}\n{err}" - ) - continue - if len(histograms) == 2: - traces.append(histograms) - tests.append(name) - else: - logging.warning(f"Invalid test type: {test[u'type']}") - continue - except (ValueError, KeyError) as err: - logging.warning(repr(err)) - - if not tests: - logging.warning(f"No data for {plot_title}.") - return - - fig = make_subplots( - rows=len(tests), - cols=2, - specs=[ - [{u"type": u"bar"}, {u"type": u"bar"}] for _ in range(len(tests)) - ] - ) - - layout_axes = dict( - gridcolor=u"rgb(220, 220, 220)", - linecolor=u"rgb(220, 220, 220)", - linewidth=1, - showgrid=True, - showline=True, - showticklabels=True, - tickcolor=u"rgb(220, 220, 220)", - ) - - for idx_row, test in enumerate(tests): - for idx_col in range(2): - fig.add_trace( - traces[idx_row][idx_col], - row=idx_row + 1, - col=idx_col + 1 - ) - fig.update_xaxes( - row=idx_row + 1, - col=idx_col + 1, - **layout_axes - ) - fig.update_yaxes( - row=idx_row + 1, - col=idx_col + 1, - **layout_axes - ) - - layout = deepcopy(plot[u"layout"]) - - layout[u"title"][u"text"] = \ - f"<b>Latency:</b> {plot.get(u'graph-title', u'')}" - layout[u"height"] = 250 * len(tests) + 130 - - layout[u"annotations"][2][u"y"] = 1.06 - 0.008 * len(tests) - layout[u"annotations"][3][u"y"] = 1.06 - 0.008 * len(tests) - - for idx, test in enumerate(tests): - layout[u"annotations"].append({ - u"font": { - u"size": 14 - }, - u"showarrow": False, - u"text": f"<b>{test}</b>", - u"textangle": 0, - u"x": 0.5, - u"xanchor": u"center", - u"xref": u"paper", - u"y": 1.0 - float(idx) * 1.06 / len(tests), - u"yanchor": u"bottom", - u"yref": u"paper" - }) - - fig[u"layout"].update(layout) - - # Create plot - file_type = plot.get(u"output-file-type", u".html") - logging.info(f" Writing file {plot[u'output-file']}{file_type}.") - try: - # Export Plot - ploff.plot(fig, show_link=False, auto_open=False, - filename=f"{plot[u'output-file']}{file_type}") - except PlotlyError as err: - logging.error(f" Finished with error: {repr(err)}") - - def plot_nf_reconf_box_name(plot, input_data): """Generate the plot(s) with algorithm: plot_nf_reconf_box_name specified in the specification file. @@ -740,179 +455,6 @@ def plot_perf_box_name(plot, input_data): return -def plot_lat_err_bars_name(plot, input_data): - """Generate the plot(s) with algorithm: plot_lat_err_bars_name - specified in the specification file. - - :param plot: Plot to generate. - :param input_data: Data to process. - :type plot: pandas.Series - :type input_data: InputData - """ - - # Transform the data - plot_title = plot.get(u"title", u"") - logging.info( - f" Creating data set for the {plot.get(u'type', u'')} {plot_title}." - ) - data = input_data.filter_tests_by_name( - plot, params=[u"latency", u"parent", u"tags", u"type"]) - if data is None: - logging.error(u"No data.") - return - - # Prepare the data for the plot - y_tmp_vals = OrderedDict() - for job in data: - for build in job: - for test in build: - try: - logging.debug(f"test[u'latency']: {test[u'latency']}\n") - except ValueError as err: - logging.warning(repr(err)) - if y_tmp_vals.get(test[u"parent"], None) is None: - y_tmp_vals[test[u"parent"]] = [ - list(), # direction1, min - list(), # direction1, avg - list(), # direction1, max - list(), # direction2, min - list(), # direction2, avg - list() # direction2, max - ] - try: - if test[u"type"] not in (u"NDRPDR", ): - logging.warning(f"Invalid test type: {test[u'type']}") - continue - if u"-pdr" in plot_title.lower(): - ttype = u"PDR" - elif u"-ndr" in plot_title.lower(): - ttype = u"NDR" - else: - logging.warning( - f"Invalid test type: {test[u'type']}" - ) - continue - y_tmp_vals[test[u"parent"]][0].append( - test[u"latency"][ttype][u"direction1"][u"min"]) - y_tmp_vals[test[u"parent"]][1].append( - test[u"latency"][ttype][u"direction1"][u"avg"]) - y_tmp_vals[test[u"parent"]][2].append( - test[u"latency"][ttype][u"direction1"][u"max"]) - y_tmp_vals[test[u"parent"]][3].append( - test[u"latency"][ttype][u"direction2"][u"min"]) - y_tmp_vals[test[u"parent"]][4].append( - test[u"latency"][ttype][u"direction2"][u"avg"]) - y_tmp_vals[test[u"parent"]][5].append( - test[u"latency"][ttype][u"direction2"][u"max"]) - except (KeyError, TypeError) as err: - logging.warning(repr(err)) - - x_vals = list() - y_vals = list() - y_mins = list() - y_maxs = list() - nr_of_samples = list() - for key, val in y_tmp_vals.items(): - name = re.sub(REGEX_NIC, u"", key.replace(u'-ndrpdr', u''). - replace(u'2n1l-', u'')) - x_vals.append(name) # dir 1 - y_vals.append(mean(val[1]) if val[1] else None) - y_mins.append(mean(val[0]) if val[0] else None) - y_maxs.append(mean(val[2]) if val[2] else None) - nr_of_samples.append(len(val[1]) if val[1] else 0) - x_vals.append(name) # dir 2 - y_vals.append(mean(val[4]) if val[4] else None) - y_mins.append(mean(val[3]) if val[3] else None) - y_maxs.append(mean(val[5]) if val[5] else None) - nr_of_samples.append(len(val[3]) if val[3] else 0) - - traces = list() - annotations = list() - - for idx, _ in enumerate(x_vals): - if not bool(int(idx % 2)): - direction = u"West-East" - else: - direction = u"East-West" - hovertext = ( - f"No. of Runs: {nr_of_samples[idx]}<br>" - f"Test: {x_vals[idx]}<br>" - f"Direction: {direction}<br>" - ) - if isinstance(y_maxs[idx], float): - hovertext += f"Max: {y_maxs[idx]:.2f}uSec<br>" - if isinstance(y_vals[idx], float): - hovertext += f"Mean: {y_vals[idx]:.2f}uSec<br>" - if isinstance(y_mins[idx], float): - hovertext += f"Min: {y_mins[idx]:.2f}uSec" - - if isinstance(y_maxs[idx], float) and isinstance(y_vals[idx], float): - array = [y_maxs[idx] - y_vals[idx], ] - else: - array = [None, ] - if isinstance(y_mins[idx], float) and isinstance(y_vals[idx], float): - arrayminus = [y_vals[idx] - y_mins[idx], ] - else: - arrayminus = [None, ] - traces.append(plgo.Scatter( - x=[idx, ], - y=[y_vals[idx], ], - name=x_vals[idx], - legendgroup=x_vals[idx], - showlegend=bool(int(idx % 2)), - mode=u"markers", - error_y=dict( - type=u"data", - symmetric=False, - array=array, - arrayminus=arrayminus, - color=COLORS[int(idx / 2)] - ), - marker=dict( - size=10, - color=COLORS[int(idx / 2)], - ), - text=hovertext, - hoverinfo=u"text", - )) - annotations.append(dict( - x=idx, - y=0, - xref=u"x", - yref=u"y", - xanchor=u"center", - yanchor=u"top", - text=u"E-W" if bool(int(idx % 2)) else u"W-E", - font=dict( - size=16, - ), - align=u"center", - showarrow=False - )) - - try: - # Create plot - file_type = plot.get(u"output-file-type", u".html") - logging.info(f" Writing file {plot[u'output-file']}{file_type}.") - layout = deepcopy(plot[u"layout"]) - if layout.get(u"title", None): - layout[u"title"] = f"<b>Latency:</b> {layout[u'title']}" - layout[u"annotations"] = annotations - plpl = plgo.Figure(data=traces, layout=layout) - - # Export Plot - ploff.plot( - plpl, - show_link=False, auto_open=False, - filename=f"{plot[u'output-file']}{file_type}" - ) - except PlotlyError as err: - logging.error( - f" Finished with error: {repr(err)}".replace(u"\n", u" ") - ) - return - - def plot_tsa_name(plot, input_data): """Generate the plot(s) with algorithm: plot_tsa_name diff --git a/resources/tools/presentation/generator_tables.py b/resources/tools/presentation/generator_tables.py index 08c9d55305..33cd763dca 100644 --- a/resources/tools/presentation/generator_tables.py +++ b/resources/tools/presentation/generator_tables.py @@ -866,7 +866,7 @@ def table_perf_trending_dash(table, input_data): if len(data_t) < 2: continue - classification_lst, avgs = classify_anomalies(data_t) + classification_lst, avgs, _ = classify_anomalies(data_t) win_size = min(len(data_t), table[u"window"]) long_win_size = min(len(data_t), table[u"long-trend-window"]) @@ -903,8 +903,8 @@ def table_perf_trending_dash(table, input_data): round(last_avg / 1e6, 2), rel_change_last, rel_change_long, - classification_lst[-win_size:].count(u"regression"), - classification_lst[-win_size:].count(u"progression")]) + classification_lst[-win_size+1:].count(u"regression"), + classification_lst[-win_size+1:].count(u"progression")]) tbl_lst.sort(key=lambda rel: rel[0]) @@ -1155,7 +1155,7 @@ def table_perf_trending_dash_html(table, input_data): attrib=dict(align=u"left" if c_idx == 0 else u"center") ) # Name: - if c_idx == 0: + if c_idx == 0 and table.get(u"add-links", True): ref = ET.SubElement( tdata, u"a", diff --git a/resources/tools/presentation/input_data_parser.py b/resources/tools/presentation/input_data_parser.py index 27db6a84d8..fc640875ce 100644 --- a/resources/tools/presentation/input_data_parser.py +++ b/resources/tools/presentation/input_data_parser.py @@ -1454,17 +1454,17 @@ class InputData: do_repeat -= 1 if not success: logging.error( - f"It is not possible to download the input data file from the " - f"job {job}, build {build[u'build']}, or it is damaged. " - f"Skipped." + f"It is not possible to download the input data file from the " + f"job {job}, build {build[u'build']}, or it is damaged. " + f"Skipped." ) if success: logging.info(f" Processing data from build {build[u'build']}") data = self._parse_tests(job, build) if data is None: logging.error( - f"Input data file from the job {job}, build " - f"{build[u'build']} is damaged. Skipped." + f"Input data file from the job {job}, build " + f"{build[u'build']} is damaged. Skipped." ) else: state = u"processed" @@ -1592,7 +1592,7 @@ class InputData: self._cfg.add_build(job, build) logging.info(f"Processing {job}: {build_nr:2d}: {local_file}") - data = self._parse_tests(job, build, list()) + data = self._parse_tests(job, build) if data is None: raise PresentationError( f"Error occurred while parsing the file {local_file}" diff --git a/resources/tools/presentation/pal_utils.py b/resources/tools/presentation/pal_utils.py index 98d5837989..86a6679918 100644 --- a/resources/tools/presentation/pal_utils.py +++ b/resources/tools/presentation/pal_utils.py @@ -262,7 +262,7 @@ def classify_anomalies(data): :param data: Full data set with unavailable samples replaced by nan. :type data: OrderedDict :returns: Classification and trend values - :rtype: 2-tuple, list of strings and list of floats + :rtype: 3-tuple, list of strings, list of floats and list of floats """ # Nan means something went wrong. # Use 0.0 to cause that being reported as a severe regression. @@ -273,13 +273,16 @@ def classify_anomalies(data): group_list.reverse() # Just to use .pop() for FIFO. classification = [] avgs = [] + stdevs = [] active_group = None values_left = 0 avg = 0.0 + stdv = 0.0 for sample in data.values(): if np.isnan(sample): classification.append(u"outlier") avgs.append(sample) + stdevs.append(sample) continue if values_left < 1 or active_group is None: values_left = 0 @@ -287,14 +290,17 @@ def classify_anomalies(data): active_group = group_list.pop() values_left = len(active_group.run_list) avg = active_group.stats.avg + stdv = active_group.stats.stdev classification.append(active_group.comment) avgs.append(avg) + stdevs.append(stdv) values_left -= 1 continue classification.append(u"normal") avgs.append(avg) + stdevs.append(stdv) values_left -= 1 - return classification, avgs + return classification, avgs, stdevs def convert_csv_to_pretty_txt(csv_file_name, txt_file_name, delimiter=u","): diff --git a/resources/tools/presentation/specification_CPTA.yaml b/resources/tools/presentation/specification_CPTA.yaml index 6f8dee1bef..5eb45e6336 100644 --- a/resources/tools/presentation/specification_CPTA.yaml +++ b/resources/tools/presentation/specification_CPTA.yaml @@ -915,6 +915,7 @@ input-file: "{DIR[STATIC,VPP]}/performance-trending-dashboard-1t1c-3n-hsw-ndr.csv" output-file: "{DIR[STATIC,VPP]}/performance-trending-dashboard-1t1c-3n-hsw-ndr.rst" testbed: "3n-hsw" + add-links: False - type: "table" @@ -923,6 +924,7 @@ input-file: "{DIR[STATIC,VPP]}/performance-trending-dashboard-1t1c-3n-hsw-pdr.csv" output-file: "{DIR[STATIC,VPP]}/performance-trending-dashboard-1t1c-3n-hsw-pdr.rst" testbed: "3n-hsw" + add-links: False # 3n-skx - @@ -964,6 +966,7 @@ input-file: "{DIR[STATIC,VPP]}/performance-trending-dashboard-2t1c-3n-skx-ndr.csv" output-file: "{DIR[STATIC,VPP]}/performance-trending-dashboard-2t1c-3n-skx-ndr.rst" testbed: "3n-skx" + add-links: False - type: "table" @@ -972,6 +975,7 @@ input-file: "{DIR[STATIC,VPP]}/performance-trending-dashboard-2t1c-3n-skx-pdr.csv" output-file: "{DIR[STATIC,VPP]}/performance-trending-dashboard-2t1c-3n-skx-pdr.rst" testbed: "3n-skx" + add-links: False # 2n-skx - @@ -1013,6 +1017,7 @@ input-file: "{DIR[STATIC,VPP]}/performance-trending-dashboard-2t1c-2n-skx-ndr.csv" output-file: "{DIR[STATIC,VPP]}/performance-trending-dashboard-2t1c-2n-skx-ndr.rst" testbed: "2n-skx" + add-links: False - type: "table" @@ -1021,6 +1026,7 @@ input-file: "{DIR[STATIC,VPP]}/performance-trending-dashboard-2t1c-2n-skx-pdr.csv" output-file: "{DIR[STATIC,VPP]}/performance-trending-dashboard-2t1c-2n-skx-pdr.rst" testbed: "2n-skx" + add-links: False # 2n-clx - @@ -1062,6 +1068,7 @@ input-file: "{DIR[STATIC,VPP]}/performance-trending-dashboard-2t1c-2n-clx-ndr.csv" output-file: "{DIR[STATIC,VPP]}/performance-trending-dashboard-2t1c-2n-clx-ndr.rst" testbed: "2n-clx" + add-links: False - type: "table" @@ -1070,6 +1077,7 @@ input-file: "{DIR[STATIC,VPP]}/performance-trending-dashboard-2t1c-2n-clx-pdr.csv" output-file: "{DIR[STATIC,VPP]}/performance-trending-dashboard-2t1c-2n-clx-pdr.rst" testbed: "2n-clx" + add-links: False - type: "table" diff --git a/resources/tools/presentation/specification_parser.py b/resources/tools/presentation/specification_parser.py index 302ce037ab..37b26eb0d5 100644 --- a/resources/tools/presentation/specification_parser.py +++ b/resources/tools/presentation/specification_parser.py @@ -535,7 +535,7 @@ class Specification: except ValueError: # defined as a range <start, build_type> build_end = self._get_build_number(job, build_end) - builds = [x for x in range(builds[u"start"], build_end + 1)] + builds = list(range(builds[u"start"], build_end + 1)) if max_builds and max_builds < len(builds): builds = builds[-max_builds:] if reverse: |