def main():
start_time = datetime.datetime.now()
arguments = docopt(__doc__, version=VERSION)
insert_understand_in_path(arguments["--dllDir"])
print ("\r\n====== srcdiffplot @ https://github.com/sglebs/srccheck ==========")
print(arguments)
try:
import understand
except:
print ("Can' find the Understand DLL. Use --dllDir=...")
print ("Please set PYTHONPATH to point an Understand's C:/Program Files/SciTools/bin/pc-win64 or equivalent")
sys.exit(-1)
try:
db_before = understand.open(arguments["--before"])
except understand.UnderstandError as exc:
print ("Error opening input file: %s" % exc)
sys.exit(-2)
try:
db_after = understand.open(arguments["--after"])
except understand.UnderstandError as exc:
print ("Error opening input file: %s" % exc)
sys.exit(-2)
print("Processing %s and %s" % (db_before.name(), db_after.name()))
for plot_lambda in [plot_diff_file_metrics, plot_diff_class_metrics,plot_diff_routine_metrics]:
plot_lambda(db_before, db_after, arguments)
prj_metric_names = [metric.strip() for metric in arguments["--prjMetrics"].split(",")]
prj_metric_names = [metric for metric in prj_metric_names if len(metric)>0 ]
all_metric_names, all_metric_values_before, all_metric_values_after, all_growth_rates = collect_metric_names_with_values_and_growth(
db_after, db_before, prj_metric_names)
output_dir = arguments["--outputDir"]
file_name = os.path.split(db_before.name())[-1] + "-" + os.path.split(db_after.name())[-1] + "-diff-kiviat.png"
absolute_file_name = "%s%s%s" % (output_dir, os.sep, file_name)
if len (all_metric_names) > 0:
saved_file_name = save_kiviat_with_values_and_thresholds(all_metric_names, all_metric_values_after, all_metric_values_before, absolute_file_name, "Prj Metrics", thresholdslabel="before", valueslabel="after")
if saved_file_name is not None:
print("Saved %s" % saved_file_name)
print_growth_rates(all_metric_names, all_growth_rates)
rates_by_adjusted_metric_name = {"Prj %s growth rate" % metric_name : rate for metric_name, rate in zip (all_metric_names, all_growth_rates)}
absolute_csv_path = "%s%s%s" % (output_dir, os.sep, arguments["--outputCSV"])
csv_ok = save_csv(absolute_csv_path, rates_by_adjusted_metric_name)
if csv_ok:
print("+++ Growth ratio metrics saved to %s" % absolute_csv_path)
else:
print("\n*** Problems creating CSV file %s" % absolute_csv_path)
post_metrics_to_sonar(arguments, rates_by_adjusted_metric_name)
end_time = datetime.datetime.now()
print("\r\n--------------------------------------------------")
print("Started : %s" % str(start_time))
print("Finished: %s" % str(end_time))
print("Total: %s" % str(end_time - start_time))
print("--------------------------------------------------")
db_before.close()
db_after.close()
def main():
start_time = datetime.datetime.now()
arguments = docopt(__doc__, version=VERSION)
print(
"\r\n====== xmlkaloi @ https://github.com/sglebs/srccheck ==========")
print(arguments)
adaptive = arguments.get("--adaptive", False)
print("\r\n====== XML KALOI Metrics (%s) ==========" %
arguments.get("--maxMetrics", False))
max_metrics = load_json(arguments.get("--maxMetrics", False))
xpaths = load_json(arguments.get("--xpathForEachMetric", False))
xml = load_xml(arguments.get("--in", ""))
print(xpaths)
print("\r\n====== XML Metrics that failed the filters ===========")
[total_violation_count, current_values,
violators] = process_xml_metrics(max_metrics, xpaths, xml)
print("%s (Current values: %s)" % (violators, current_values))
if adaptive:
write_json(arguments.get("--maxMetrics", False), current_values)
output_dir = arguments["--outputDir"]
absolute_csv_path = "%s%s%s" % (output_dir, os.sep,
arguments["--outputCSV"])
csv_ok = save_csv(absolute_csv_path, current_values)
if csv_ok:
print("+++ Metrics saved to %s" % absolute_csv_path)
else:
print("\n*** Problems creating CSV file %s" % absolute_csv_path)
post_metrics_to_sonar(arguments, current_values)
end_time = datetime.datetime.now()
print("\r\n--------------------------------------------------")
print("Started : %s" % str(start_time))
print("Finished: %s" % str(end_time))
print("Total: %s" % str(end_time - start_time))
print("--------------------------------------------------")
sys.exit(total_violation_count)
def main():
start_time = datetime.datetime.now()
arguments = docopt(__doc__, version=VERSION)
sys.path.append(arguments["--dllDir"]
) # add the dir with the DLL to interop with understand
print(
"\r\n====== srccheck by Marcio Marchini: [email protected] =========="
)
print(arguments)
try:
import understand
except:
print("Can' find the Understand DLL. Use --dllDir=...")
print(
"Please set PYTHONPATH to point an Understand's C:/Program Files/SciTools/bin/pc-win64/python or equivalent"
)
sys.exit(-1)
try:
db = understand.open(arguments["--in"])
except understand.UnderstandError as exc:
print("Error opening input file: %s" % exc)
sys.exit(-2)
adaptive = arguments.get("--adaptive", False)
print("\r\n====== Project Metrics (%s) (%s) ==========" %
(db.name(), db.language()[0]))
prj_metrics = project_metrics(db, arguments)
print_prj_metrics(prj_metrics)
print("")
print("\r\n====== Project Metrics that failed the filters ===========")
[total_violation_count, prj_tracked_metrics,
prj_max_metrics] = process_prj_metrics(arguments, prj_metrics)
if adaptive:
write_metrics_thresholds(arguments.get("--maxPrjMetrics", False),
prj_tracked_metrics)
print("")
print("\r\n====== File Metrics that failed the filters ===========")
[violation_count, file_tracked_metrics,
file_max_metrics] = process_file_metrics(db, arguments)
total_violation_count = total_violation_count + violation_count
if adaptive:
write_metrics_thresholds(arguments.get("--maxFileMetrics"),
file_tracked_metrics)
print("")
print("\r\n====== Class Metrics that failed the filters ==========")
[violation_count, class_tracked_metrics,
class_max_metrics] = process_class_metrics(db, arguments)
total_violation_count = total_violation_count + violation_count
if adaptive:
write_metrics_thresholds(arguments.get("--maxClassMetrics"),
class_tracked_metrics)
print("")
print("\r\n====== Routine Metrics that failed the filters ==========")
[violation_count, routine_tracked_metrics,
routine_max_metrics] = process_routine_metrics(db, arguments)
total_violation_count = total_violation_count + violation_count
if adaptive:
write_metrics_thresholds(arguments.get("--maxRoutineMetrics"),
routine_tracked_metrics)
print("")
print("\r\n====== Publishing selected metrics ===========")
tracked_metrics = {}
append_dict_with_key_prefix(tracked_metrics, prj_tracked_metrics, "Prj")
append_dict_with_key_prefix(tracked_metrics, file_tracked_metrics, "File")
append_dict_with_key_prefix(tracked_metrics, class_tracked_metrics,
"Class")
append_dict_with_key_prefix(tracked_metrics, routine_tracked_metrics,
"Routine")
max_metrics = {}
append_dict_with_key_prefix(max_metrics, prj_max_metrics, "Prj")
append_dict_with_key_prefix(max_metrics, file_max_metrics, "File")
append_dict_with_key_prefix(max_metrics, class_max_metrics, "Class")
append_dict_with_key_prefix(max_metrics, routine_max_metrics, "Routine")
file_name = save_kiviat_of_metrics(tracked_metrics, max_metrics, arguments,
os.path.split(db.name())[-1])
print("Kiviat saved to %s" % file_name)
csv_ok = save_csv(arguments["--outputCSV"], tracked_metrics)
if csv_ok:
print("+++ Metrics saved to %s" % arguments["--outputCSV"])
else:
print("\n*** Problems creating CSV file %s" % arguments["--outputCSV"])
_post_to_sonar(arguments, tracked_metrics)
print("")
end_time = datetime.datetime.now()
print("\r\n--------------------------------------------------")
print("Started : %s" % str(start_time))
print("Finished: %s" % str(end_time))
print("Total: %s" % str(end_time - start_time))
print("Violations: %i" % total_violation_count)
print("--------------------------------------------------")
db.close()
sys.exit(total_violation_count)
def main():
start_time = datetime.datetime.now()
arguments = docopt(__doc__, version=VERSION)
dllDir = arguments["--dllDir"]
sys.path.insert(0,dllDir) # add the dir with the DLLs - Qt etc
os.environ["PATH"] = dllDir + os.pathsep + os.environ["PATH"] # prepend
sys.path.insert(0,os.path.join(dllDir,"Python")) # also needed, For interop
sys.path.insert(0,os.path.join(dllDir,"python")) # also needed, For interop with older versions of Understand (which used lowercase)
#hangs!!!!! os.environ["PYTHONPATH"] = os.path.join(dllDir,"python") + os.pathsep + os.environ.get("PYTHONPATH", "") # prepend
print ("\r\n====== srcdiffplot by Marcio Marchini: [email protected] ==========")
print(arguments)
try:
import understand
except:
print ("Can' find the Understand DLL. Use --dllDir=...")
print ("Please set PYTHONPATH to point an Understand's C:/Program Files/SciTools/bin/pc-win64/python or equivalent")
sys.exit(-1)
try:
db_before = understand.open(arguments["--before"])
except understand.UnderstandError as exc:
print ("Error opening input file: %s" % exc)
sys.exit(-2)
try:
db_after = understand.open(arguments["--after"])
except understand.UnderstandError as exc:
print ("Error opening input file: %s" % exc)
sys.exit(-2)
print("Processing %s and %s" % (db_before.name(), db_after.name()))
for plot_lambda in [plot_diff_file_metrics, plot_diff_class_metrics,plot_diff_routine_metrics]:
plot_lambda(db_before, db_after, arguments)
prj_metric_names = [metric.strip() for metric in arguments["--prjMetrics"].split(",")]
prj_metric_names = [metric for metric in prj_metric_names if len(metric)>0 ]
all_metric_names, all_metric_values_before, all_metric_values_after, all_growth_rates = collect_metric_names_with_values_and_growth(
db_after, db_before, prj_metric_names)
output_dir = arguments["--outputDir"]
file_name = os.path.split(db_before.name())[-1] + "-" + os.path.split(db_after.name())[-1] + "-diff-kiviat.png"
absolute_file_name = "%s%s%s" % (output_dir, os.sep, file_name)
if len (all_metric_names) > 0:
saved_file_name = save_kiviat_with_values_and_thresholds(all_metric_names, all_metric_values_after, all_metric_values_before, absolute_file_name, "Prj Metrics", thresholdslabel="before", valueslabel="after")
if saved_file_name is not None:
print("Saved %s" % saved_file_name)
print_growth_rates(all_metric_names, all_growth_rates)
rates_by_adjusted_metric_name = {"Prj %s growth rate" % metric_name : rate for metric_name, rate in zip (all_metric_names, all_growth_rates)}
absolute_csv_path = "%s%s%s" % (output_dir, os.sep, arguments["--outputCSV"])
csv_ok = save_csv(absolute_csv_path, rates_by_adjusted_metric_name)
if csv_ok:
print("+++ Growth ratio metrics saved to %s" % absolute_csv_path)
else:
print("\n*** Problems creating CSV file %s" % absolute_csv_path)
post_metrics_to_sonar(arguments, rates_by_adjusted_metric_name)
end_time = datetime.datetime.now()
print("\r\n--------------------------------------------------")
print("Started : %s" % str(start_time))
print("Finished: %s" % str(end_time))
print("Total: %s" % str(end_time - start_time))
print("--------------------------------------------------")
db_before.close()
db_after.close()
def main():
start_time = datetime.datetime.now()
arguments = docopt(__doc__, version=VERSION)
insert_understand_in_path(arguments["--dllDir"])
print ("\r\n====== srccheck @ https://github.com/sglebs/srccheck ==========")
print(arguments)
try:
import understand
except:
print ("Can' find the Understand DLL. Use --dllDir=...")
print ("Please set PYTHONPATH to point an Understand's C:/Program Files/SciTools/bin/pc-win64 or equivalent")
sys.exit(-1)
try:
db = understand.open(arguments["--in"])
except understand.UnderstandError as exc:
print ("Error opening input file: %s" % exc)
sys.exit(-2)
adaptive = arguments.get("--adaptive", False)
print ("\r\n====== Project Metrics (%s) (%s) ==========" % (db.name(), db.language()[0]))
prj_metrics = project_metrics(db, arguments)
print_prj_metrics(prj_metrics)
print ("")
print ("\r\n====== Project Metrics that failed the filters ===========")
[total_violation_count , prj_tracked_metrics, prj_max_metrics ] = process_prj_metrics(arguments, prj_metrics)
if adaptive:
write_metrics_thresholds(arguments.get("--maxPrjMetrics", False), prj_tracked_metrics)
print ("")
print ("\r\n====== File Metrics that failed the filters ===========")
[violation_count, file_tracked_metrics, file_max_metrics ] = process_file_metrics(db, arguments)
total_violation_count = total_violation_count + violation_count
if adaptive:
write_metrics_thresholds(arguments.get("--maxFileMetrics"), file_tracked_metrics)
print ("")
print ("\r\n====== Class Metrics that failed the filters ==========")
[violation_count, class_tracked_metrics, class_max_metrics ] = process_class_metrics(db, arguments)
total_violation_count = total_violation_count + violation_count
if adaptive:
write_metrics_thresholds(arguments.get("--maxClassMetrics"), class_tracked_metrics)
print ("")
print ("\r\n====== Routine Metrics that failed the filters ==========")
[violation_count, routine_tracked_metrics, routine_max_metrics ] = process_routine_metrics(db, arguments)
total_violation_count = total_violation_count + violation_count
if adaptive:
write_metrics_thresholds(arguments.get("--maxRoutineMetrics"), routine_tracked_metrics)
print ("")
print ("\r\n====== Publishing selected metrics ===========")
tracked_metrics = {}
append_dict_with_key_prefix (tracked_metrics, prj_tracked_metrics, "Prj")
append_dict_with_key_prefix (tracked_metrics, file_tracked_metrics, "File")
append_dict_with_key_prefix (tracked_metrics, class_tracked_metrics, "Class")
append_dict_with_key_prefix (tracked_metrics, routine_tracked_metrics, "Routine")
max_metrics = {}
append_dict_with_key_prefix (max_metrics, prj_max_metrics, "Prj")
append_dict_with_key_prefix (max_metrics, file_max_metrics, "File")
append_dict_with_key_prefix (max_metrics, class_max_metrics, "Class")
append_dict_with_key_prefix (max_metrics, routine_max_metrics, "Routine")
output_dir = arguments["--outputDir"]
file_prefix = "%s%s%s" % (output_dir, os.sep, os.path.split(db.name())[-1])
file_name = save_kiviat_of_metrics(tracked_metrics, max_metrics, arguments, file_prefix)
print("Kiviat saved to %s"% file_name)
absolute_csv_path = "%s%s%s" % (output_dir, os.sep, arguments["--outputCSV"])
csv_ok = save_csv(absolute_csv_path, tracked_metrics)
if csv_ok:
print("+++ Metrics saved to %s" % absolute_csv_path)
else:
print ("\n*** Problems creating CSV file %s" % absolute_csv_path)
post_metrics_to_sonar(arguments, tracked_metrics)
print ("")
end_time = datetime.datetime.now()
print ("\r\n--------------------------------------------------")
print ("Started : %s" % str(start_time))
print ("Finished: %s" % str(end_time))
print ("Total: %s" % str(end_time-start_time))
print ("Violations: %i" % total_violation_count)
print ("--------------------------------------------------")
db.close()
sys.exit(total_violation_count)