import logging
import csv
-import prettytable
-import plotly.offline as ploff
-import plotly.graph_objs as plgo
-import plotly.exceptions as plerr
from collections import OrderedDict
from datetime import datetime
from copy import deepcopy
-from utils import archive_input_data, execute_command, classify_anomalies
+import prettytable
+import plotly.offline as ploff
+import plotly.graph_objs as plgo
+import plotly.exceptions as plerr
+
+from pal_utils import archive_input_data, execute_command, classify_anomalies
# Command to build the html format of the report
-HTML_BUILDER = 'sphinx-build -v -c conf_cpta -a ' \
- '-b html -E ' \
- '-t html ' \
- '-D version="{date}" ' \
- '{working_dir} ' \
- '{build_dir}/'
+HTML_BUILDER = u'sphinx-build -v -c conf_cpta -a ' \
+ u'-b html -E ' \
+ u'-t html ' \
+ u'-D version="{date}" ' \
+ u'{working_dir} ' \
+ u'{build_dir}/'
# .css file for the html format of the report
-THEME_OVERRIDES = """/* override table width restrictions */
+THEME_OVERRIDES = u"""/* override table width restrictions */
.wy-nav-content {
max-width: 1200px !important;
}
}
"""
-COLORS = ["SkyBlue", "Olive", "Purple", "Coral", "Indigo", "Pink",
- "Chocolate", "Brown", "Magenta", "Cyan", "Orange", "Black",
- "Violet", "Blue", "Yellow", "BurlyWood", "CadetBlue", "Crimson",
- "DarkBlue", "DarkCyan", "DarkGreen", "Green", "GoldenRod",
- "LightGreen", "LightSeaGreen", "LightSkyBlue", "Maroon",
- "MediumSeaGreen", "SeaGreen", "LightSlateGrey",
- "SkyBlue", "Olive", "Purple", "Coral", "Indigo", "Pink",
- "Chocolate", "Brown", "Magenta", "Cyan", "Orange", "Black",
- "Violet", "Blue", "Yellow", "BurlyWood", "CadetBlue", "Crimson",
- "DarkBlue", "DarkCyan", "DarkGreen", "Green", "GoldenRod",
- "LightGreen", "LightSeaGreen", "LightSkyBlue", "Maroon",
- "MediumSeaGreen", "SeaGreen", "LightSlateGrey"
- ]
+COLORS = [
+ u"SkyBlue", u"Olive", u"Purple", u"Coral", u"Indigo", u"Pink",
+ u"Chocolate", u"Brown", u"Magenta", u"Cyan", u"Orange", u"Black",
+ u"Violet", u"Blue", u"Yellow", u"BurlyWood", u"CadetBlue", u"Crimson",
+ u"DarkBlue", u"DarkCyan", u"DarkGreen", u"Green", u"GoldenRod",
+ u"LightGreen", u"LightSeaGreen", u"LightSkyBlue", u"Maroon",
+ u"MediumSeaGreen", u"SeaGreen", u"LightSlateGrey",
+ u"SkyBlue", u"Olive", u"Purple", u"Coral", u"Indigo", u"Pink",
+ u"Chocolate", u"Brown", u"Magenta", u"Cyan", u"Orange", u"Black",
+ u"Violet", u"Blue", u"Yellow", u"BurlyWood", u"CadetBlue", u"Crimson",
+ u"DarkBlue", u"DarkCyan", u"DarkGreen", u"Green", u"GoldenRod",
+ u"LightGreen", u"LightSeaGreen", u"LightSkyBlue", u"Maroon",
+ u"MediumSeaGreen", u"SeaGreen", u"LightSlateGrey"
+]
def generate_cpta(spec, data):
:type data: InputData
"""
- logging.info("Generating the Continuous Performance Trending and Analysis "
- "...")
+ logging.info(u"Generating the Continuous Performance Trending and Analysis "
+ u"...")
ret_code = _generate_all_charts(spec, data)
cmd = HTML_BUILDER.format(
- date=datetime.utcnow().strftime('%Y-%m-%d %H:%M UTC'),
- working_dir=spec.environment["paths"]["DIR[WORKING,SRC]"],
- build_dir=spec.environment["paths"]["DIR[BUILD,HTML]"])
+ date=datetime.utcnow().strftime(u'%Y-%m-%d %H:%M UTC'),
+ working_dir=spec.environment[u'paths'][u'DIR[WORKING,SRC]'],
+ build_dir=spec.environment[u'paths'][u'DIR[BUILD,HTML]'])
execute_command(cmd)
- with open(spec.environment["paths"]["DIR[CSS_PATCH_FILE]"], "w") as \
+ with open(spec.environment[u'paths'][u'DIR[CSS_PATCH_FILE]'], u'w') as \
css_file:
css_file.write(THEME_OVERRIDES)
- with open(spec.environment["paths"]["DIR[CSS_PATCH_FILE2]"], "w") as \
+ with open(spec.environment[u'paths'][u'DIR[CSS_PATCH_FILE2]'], u'w') as \
css_file:
css_file.write(THEME_OVERRIDES)
- if spec.configuration.get("archive-inputs", True):
+ if spec.configuration.get(u"archive-inputs", True):
archive_input_data(spec)
- logging.info("Done.")
+ logging.info(u"Done.")
return ret_code
def _generate_trending_traces(in_data, job_name, build_info,
- show_trend_line=True, name="", color=""):
+ show_trend_line=True, name=u"", color=u""):
"""Generate the trending traces:
- samples,
- outliers, regress, progress
xaxis = list()
for idx in data_x:
date = build_info[job_name][str(idx)][0]
- hover_str = ("date: {date}<br>"
- "value: {value:,}<br>"
- "{sut}-ref: {build}<br>"
- "csit-ref: mrr-{period}-build-{build_nr}<br>"
- "testbed: {testbed}")
- if "dpdk" in job_name:
+ hover_str = (u"date: {date}<br>"
+ u"value: {value:,}<br>"
+ u"{sut}-ref: {build}<br>"
+ u"csit-ref: mrr-{period}-build-{build_nr}<br>"
+ u"testbed: {testbed}")
+ if u"dpdk" in job_name:
hover_text.append(hover_str.format(
date=date,
value=int(in_data[idx]),
- sut="dpdk",
- build=build_info[job_name][str(idx)][1].rsplit('~', 1)[0],
- period="weekly",
+ sut=u"dpdk",
+ build=build_info[job_name][str(idx)][1].rsplit(u'~', 1)[0],
+ period=u"weekly",
build_nr=idx,
testbed=build_info[job_name][str(idx)][2]))
- elif "vpp" in job_name:
+ elif u"vpp" in job_name:
hover_text.append(hover_str.format(
date=date,
value=int(in_data[idx]),
- sut="vpp",
- build=build_info[job_name][str(idx)][1].rsplit('~', 1)[0],
- period="daily",
+ sut=u"vpp",
+ build=build_info[job_name][str(idx)][1].rsplit(u'~', 1)[0],
+ period=u"daily",
build_nr=idx,
testbed=build_info[job_name][str(idx)][2]))
anomalies_colors = list()
anomalies_avgs = list()
anomaly_color = {
- "regression": 0.0,
- "normal": 0.5,
- "progression": 1.0
+ u"regression": 0.0,
+ u"normal": 0.5,
+ u"progression": 1.0
}
if anomaly_classification:
- for idx, (key, value) in enumerate(data_pd.iteritems()):
+ for idx, (key, value) in enumerate(data_pd.items()):
if anomaly_classification[idx] in \
- ("outlier", "regression", "progression"):
+ (u"outlier", u"regression", u"progression"):
anomalies[key] = value
anomalies_colors.append(
anomaly_color[anomaly_classification[idx]])
trace_samples = plgo.Scatter(
x=xaxis,
- y=[y for y in data_y], # Was: y.avg
- mode='markers',
+ y=data_y,
+ mode=u"markers",
line={
- "width": 1
+ u"width": 1
},
showlegend=True,
legendgroup=name,
- name="{name}".format(name=name),
+ name=f"{name}",
marker={
- "size": 5,
- "color": color,
- "symbol": "circle",
+ u"size": 5,
+ u"color": color,
+ u"symbol": u"circle",
},
text=hover_text,
- hoverinfo="text"
+ hoverinfo=u"text"
)
traces = [trace_samples, ]
trace_trend = plgo.Scatter(
x=xaxis,
y=avgs,
- mode='lines',
+ mode=u"lines",
line={
- "shape": "linear",
- "width": 1,
- "color": color,
+ u"shape": u"linear",
+ u"width": 1,
+ u"color": color,
},
showlegend=False,
legendgroup=name,
- name='{name}'.format(name=name),
- text=["trend: {0:,}".format(int(avg)) for avg in avgs],
- hoverinfo="text+name"
+ name=f"{name}",
+ text=[f"trend: {int(avg):,}" for avg in avgs],
+ hoverinfo=u"text+name"
)
traces.append(trace_trend)
trace_anomalies = plgo.Scatter(
- x=anomalies.keys(),
+ x=list(anomalies.keys()),
y=anomalies_avgs,
- mode='markers',
- hoverinfo="none",
+ mode=u"markers",
+ hoverinfo=u"none",
showlegend=False,
legendgroup=name,
- name="{name}-anomalies".format(name=name),
+ name=f"{name}-anomalies",
marker={
- "size": 15,
- "symbol": "circle-open",
- "color": anomalies_colors,
- "colorscale": [[0.00, "red"],
- [0.33, "red"],
- [0.33, "white"],
- [0.66, "white"],
- [0.66, "green"],
- [1.00, "green"]],
- "showscale": True,
- "line": {
- "width": 2
+ u"size": 15,
+ u"symbol": u"circle-open",
+ u"color": anomalies_colors,
+ u"colorscale": [
+ [0.00, u"red"],
+ [0.33, u"red"],
+ [0.33, u"white"],
+ [0.66, u"white"],
+ [0.66, u"green"],
+ [1.00, u"green"]
+ ],
+ u"showscale": True,
+ u"line": {
+ u"width": 2
},
- "colorbar": {
- "y": 0.5,
- "len": 0.8,
- "title": "Circles Marking Data Classification",
- "titleside": 'right',
- "titlefont": {
- "size": 14
+ u"colorbar": {
+ u"y": 0.5,
+ u"len": 0.8,
+ u"title": u"Circles Marking Data Classification",
+ u"titleside": u"right",
+ u"titlefont": {
+ u"size": 14
},
- "tickmode": 'array',
- "tickvals": [0.167, 0.500, 0.833],
- "ticktext": ["Regression", "Normal", "Progression"],
- "ticks": "",
- "ticklen": 0,
- "tickangle": -90,
- "thickness": 10
+ u"tickmode": u"array",
+ u"tickvals": [0.167, 0.500, 0.833],
+ u"ticktext": [u"Regression", u"Normal", u"Progression"],
+ u"ticks": u"",
+ u"ticklen": 0,
+ u"tickangle": -90,
+ u"thickness": 10
}
}
)
if anomaly_classification:
return traces, anomaly_classification[-1]
- else:
- return traces, None
+
+ return traces, None
def _generate_all_charts(spec, input_data):
def _generate_chart(graph):
"""Generates the chart.
+
+ :param graph: The graph to be generated
+ :type graph: dict
+ :returns: Dictionary with the job name, csv table with results and
+ list of tests classification results.
+ :rtype: dict
"""
logs = list()
- logs.append(("INFO", " Generating the chart '{0}' ...".
- format(graph.get("title", ""))))
+ logs.append(
+ (u"INFO", f" Generating the chart {graph.get(u'title', u'')} ...")
+ )
- job_name = graph["data"].keys()[0]
+ job_name = list(graph[u"data"].keys())[0]
csv_tbl = list()
res = dict()
# Transform the data
- logs.append(("INFO", " Creating the data set for the {0} '{1}'.".
- format(graph.get("type", ""), graph.get("title", ""))))
+ logs.append(
+ (u"INFO",
+ f" Creating the data set for the {graph.get(u'type', u'')} "
+ f"{graph.get(u'title', u'')}."
+ )
+ )
data = input_data.filter_data(graph, continue_on_error=True)
if data is None:
- logging.error("No data.")
- return
+ logging.error(u"No data.")
+ return dict()
chart_data = dict()
chart_tags = dict()
- for job, job_data in data.iteritems():
+ for job, job_data in data.items():
if job != job_name:
continue
for index, bld in job_data.items():
chart_data[test_name] = OrderedDict()
try:
chart_data[test_name][int(index)] = \
- test["result"]["receive-rate"]
- chart_tags[test_name] = test.get("tags", None)
+ test[u"result"][u"receive-rate"]
+ chart_tags[test_name] = test.get(u"tags", None)
except (KeyError, TypeError):
pass
for tst_name, tst_data in chart_data.items():
tst_lst = list()
for bld in builds_dict[job_name]:
- itm = tst_data.get(int(bld), '')
+ itm = tst_data.get(int(bld), u'')
# CSIT-1180: Itm will be list, compute stats.
tst_lst.append(str(itm))
- csv_tbl.append("{0},".format(tst_name) + ",".join(tst_lst) + '\n')
+ csv_tbl.append(f"{tst_name}," + u",".join(tst_lst) + u'\n')
# Generate traces:
traces = list()
index = 0
- groups = graph.get("groups", None)
+ groups = graph.get(u"groups", None)
visibility = list()
if groups:
for tag in group:
for tst_name, test_data in chart_data.items():
if not test_data:
- logs.append(("WARNING",
- "No data for the test '{0}'".
- format(tst_name)))
+ logs.append(
+ (u"WARNING", f"No data for the test {tst_name}")
+ )
continue
- if tag in chart_tags[tst_name]:
- message = "index: {index}, test: {test}".format(
- index=index, test=tst_name)
- try:
- trace, rslt = _generate_trending_traces(
- test_data,
- job_name=job_name,
- build_info=build_info,
- name='-'.join(tst_name.split('.')[-1].
- split('-')[2:-1]),
- color=COLORS[index])
- except IndexError:
- message = "Out of colors: {}".format(message)
- logs.append(("ERROR", message))
- logging.error(message)
- index += 1
- continue
- traces.extend(trace)
- visible.extend([True for _ in range(len(trace))])
- res[tst_name] = rslt
+ if tag not in chart_tags[tst_name]:
+ continue
+ message = f"index: {index}, test: {tst_name}"
+ try:
+ trace, rslt = _generate_trending_traces(
+ test_data,
+ job_name=job_name,
+ build_info=build_info,
+ name=u'-'.join(tst_name.split(u'.')[-1].
+ split(u'-')[2:-1]),
+ color=COLORS[index])
+ except IndexError:
+ logs.append(
+ (u"ERROR", f"Out of colors: {message}")
+ )
+ logging.error(f"Out of colors: {message}")
index += 1
- break
+ continue
+ traces.extend(trace)
+ visible.extend([True for _ in range(len(trace))])
+ res[tst_name] = rslt
+ index += 1
+ break
visibility.append(visible)
else:
for tst_name, test_data in chart_data.items():
if not test_data:
- logs.append(("WARNING", "No data for the test '{0}'".
- format(tst_name)))
+ logs.append(
+ (u"WARNING", f"No data for the test {tst_name}")
+ )
continue
- message = "index: {index}, test: {test}".format(
- index=index, test=tst_name)
+ message = f"index: {index}, test: {tst_name}"
try:
trace, rslt = _generate_trending_traces(
test_data,
job_name=job_name,
build_info=build_info,
- name='-'.join(tst_name.split('.')[-1].split('-')[2:-1]),
+ name=u'-'.join(
+ tst_name.split(u'.')[-1].split(u'-')[2:-1]),
color=COLORS[index])
except IndexError:
- message = "Out of colors: {}".format(message)
- logs.append(("ERROR", message))
- logging.error(message)
+ logs.append((u"ERROR", f"Out of colors: {message}"))
+ logging.error(f"Out of colors: {message}")
index += 1
continue
traces.extend(trace)
if traces:
# Generate the chart:
try:
- layout = deepcopy(graph["layout"])
+ layout = deepcopy(graph[u"layout"])
except KeyError as err:
- logging.error("Finished with error: No layout defined")
+ logging.error(u"Finished with error: No layout defined")
logging.error(repr(err))
- return
+ return dict()
if groups:
show = list()
for i in range(len(visibility)):
visible = list()
- for r in range(len(visibility)):
- for _ in range(len(visibility[r])):
- visible.append(i == r)
+ for vis_idx, _ in enumerate(visibility):
+ for _ in range(len(visibility[vis_idx])):
+ visible.append(i == vis_idx)
show.append(visible)
buttons = list()
buttons.append(dict(
- label="All",
- method="update",
- args=[{"visible": [True for _ in range(len(show[0]))]}, ]
+ label=u"All",
+ method=u"update",
+ args=[{u"visible": [True for _ in range(len(show[0]))]}, ]
))
for i in range(len(groups)):
try:
- label = graph["group-names"][i]
+ label = graph[u"group-names"][i]
except (IndexError, KeyError):
- label = "Group {num}".format(num=i + 1)
+ label = f"Group {i + 1}"
buttons.append(dict(
label=label,
- method="update",
- args=[{"visible": show[i]}, ]
+ method=u"update",
+ args=[{u"visible": show[i]}, ]
))
- layout['updatemenus'] = list([
+ layout[u"updatemenus"] = list([
dict(
active=0,
- type="dropdown",
- direction="down",
- xanchor="left",
- yanchor="bottom",
+ type=u"dropdown",
+ direction=u"down",
+ xanchor=u"left",
+ yanchor=u"bottom",
x=-0.12,
y=1.0,
buttons=buttons
)
])
- name_file = "{0}-{1}{2}".format(spec.cpta["output-file"],
- graph["output-file-name"],
- spec.cpta["output-file-type"])
+ name_file = (
+ f"{spec.cpta[u'output-file']}-{graph[u'output-file-name']}"
+ f"{spec.cpta[u'output-file-type']}")
- logs.append(("INFO", " Writing the file '{0}' ...".
- format(name_file)))
+ logs.append((u"INFO", f" Writing the file {name_file} ..."))
plpl = plgo.Figure(data=traces, layout=layout)
try:
ploff.plot(plpl, show_link=False, auto_open=False,
filename=name_file)
except plerr.PlotlyEmptyDataError:
- logs.append(("WARNING", "No data for the plot. Skipped."))
+ logs.append((u"WARNING", u"No data for the plot. Skipped."))
for level, line in logs:
- if level == "INFO":
+ if level == u"INFO":
logging.info(line)
- elif level == "ERROR":
+ elif level == u"ERROR":
logging.error(line)
- elif level == "DEBUG":
+ elif level == u"DEBUG":
logging.debug(line)
- elif level == "CRITICAL":
+ elif level == u"CRITICAL":
logging.critical(line)
- elif level == "WARNING":
+ elif level == u"WARNING":
logging.warning(line)
- return {"job_name": job_name, "csv_table": csv_tbl, "results": res}
+ return {u"job_name": job_name, u"csv_table": csv_tbl, u"results": res}
builds_dict = dict()
- for job in spec.input["builds"].keys():
+ for job in spec.input[u"builds"].keys():
if builds_dict.get(job, None) is None:
builds_dict[job] = list()
- for build in spec.input["builds"][job]:
- status = build["status"]
- if status != "failed" and status != "not found" and \
- status != "removed":
- builds_dict[job].append(str(build["build"]))
+ for build in spec.input[u"builds"][job]:
+ status = build[u"status"]
+ if status not in (u"failed", u"not found", u"removed"):
+ builds_dict[job].append(str(build[u"build"]))
# Create "build ID": "date" dict:
build_info = dict()
- tb_tbl = spec.environment.get("testbeds", None)
+ tb_tbl = spec.environment.get(u"testbeds", None)
for job_name, job_data in builds_dict.items():
if build_info.get(job_name, None) is None:
build_info[job_name] = OrderedDict()
for build in job_data:
- testbed = ""
- tb_ip = input_data.metadata(job_name, build).get("testbed", "")
+ testbed = u""
+ tb_ip = input_data.metadata(job_name, build).get(u"testbed", u"")
if tb_ip and tb_tbl:
- testbed = tb_tbl.get(tb_ip, "")
+ testbed = tb_tbl.get(tb_ip, u"")
build_info[job_name][build] = (
- input_data.metadata(job_name, build).get("generated", ""),
- input_data.metadata(job_name, build).get("version", ""),
+ input_data.metadata(job_name, build).get(u"generated", u""),
+ input_data.metadata(job_name, build).get(u"version", u""),
testbed
)
# Create the header:
csv_tables = dict()
- for job_name in builds_dict.keys():
+ for job_name in builds_dict:
if csv_tables.get(job_name, None) is None:
csv_tables[job_name] = list()
- header = "Build Number:," + ",".join(builds_dict[job_name]) + '\n'
+ header = u"Build Number:," + u",".join(builds_dict[job_name]) + u'\n'
csv_tables[job_name].append(header)
build_dates = [x[0] for x in build_info[job_name].values()]
- header = "Build Date:," + ",".join(build_dates) + '\n'
+ header = u"Build Date:," + u",".join(build_dates) + u'\n'
csv_tables[job_name].append(header)
versions = [x[1] for x in build_info[job_name].values()]
- header = "Version:," + ",".join(versions) + '\n'
+ header = u"Version:," + u",".join(versions) + u'\n'
csv_tables[job_name].append(header)
- for chart in spec.cpta["plots"]:
+ for chart in spec.cpta[u"plots"]:
result = _generate_chart(chart)
+ if not result:
+ continue
- csv_tables[result["job_name"]].extend(result["csv_table"])
+ csv_tables[result[u"job_name"]].extend(result[u"csv_table"])
- if anomaly_classifications.get(result["job_name"], None) is None:
- anomaly_classifications[result["job_name"]] = dict()
- anomaly_classifications[result["job_name"]].update(result["results"])
+ if anomaly_classifications.get(result[u"job_name"], None) is None:
+ anomaly_classifications[result[u"job_name"]] = dict()
+ anomaly_classifications[result[u"job_name"]].update(result[u"results"])
# Write the tables:
for job_name, csv_table in csv_tables.items():
- file_name = spec.cpta["output-file"] + "-" + job_name + "-trending"
- with open("{0}.csv".format(file_name), 'w') as file_handler:
+ file_name = spec.cpta[u"output-file"] + u"-" + job_name + u"-trending"
+ with open(f"{file_name}.csv", u"w") as file_handler:
file_handler.writelines(csv_table)
txt_table = None
- with open("{0}.csv".format(file_name), 'rb') as csv_file:
- csv_content = csv.reader(csv_file, delimiter=',', quotechar='"')
+ with open(f"{file_name}.csv", u"rt") as csv_file:
+ csv_content = csv.reader(csv_file, delimiter=u',', quotechar=u'"')
line_nr = 0
for row in csv_content:
if txt_table is None:
pass
try:
txt_table.add_row(row)
+ # PrettyTable raises Exception
except Exception as err:
- logging.warning("Error occurred while generating TXT "
- "table:\n{0}".format(err))
+ logging.warning(
+ f"Error occurred while generating TXT table:\n{err}"
+ )
line_nr += 1
- txt_table.align["Build Number:"] = "l"
- with open("{0}.txt".format(file_name), "w") as txt_file:
+ txt_table.align[u"Build Number:"] = u"l"
+ with open(f"{file_name}.txt", u"w") as txt_file:
txt_file.write(str(txt_table))
# Evaluate result:
if anomaly_classifications:
- result = "PASS"
- for job_name, job_data in anomaly_classifications.iteritems():
- file_name = "{0}-regressions-{1}.txt".\
- format(spec.cpta["output-file"], job_name)
- with open(file_name, 'w') as txt_file:
- for test_name, classification in job_data.iteritems():
- if classification == "regression":
- txt_file.write(test_name + '\n')
- if classification == "regression" or \
- classification == "outlier":
- result = "FAIL"
- file_name = "{0}-progressions-{1}.txt".\
- format(spec.cpta["output-file"], job_name)
- with open(file_name, 'w') as txt_file:
- for test_name, classification in job_data.iteritems():
- if classification == "progression":
- txt_file.write(test_name + '\n')
+ result = u"PASS"
+ for job_name, job_data in anomaly_classifications.items():
+ file_name = \
+ f"{spec.cpta[u'output-file']}-regressions-{job_name}.txt"
+ with open(file_name, u'w') as txt_file:
+ for test_name, classification in job_data.items():
+ if classification == u"regression":
+ txt_file.write(test_name + u'\n')
+ if classification in (u"regression", u"outlier"):
+ result = u"FAIL"
+ file_name = \
+ f"{spec.cpta[u'output-file']}-progressions-{job_name}.txt"
+ with open(file_name, u'w') as txt_file:
+ for test_name, classification in job_data.items():
+ if classification == u"progression":
+ txt_file.write(test_name + u'\n')
else:
- result = "FAIL"
+ result = u"FAIL"
- logging.info("Partial results: {0}".format(anomaly_classifications))
- logging.info("Result: {0}".format(result))
+ logging.info(f"Partial results: {anomaly_classifications}")
+ logging.info(f"Result: {result}")
return result
Code Review / csit.git / blobdiff