def releases_info(startdate, enddate, project, opts, people_out, affs_out):
# Releases information.
data = {}
filters = MetricFilters("month", startdate, enddate,
["project", str(project)], opts.npeople,
people_out, affs_out)
# SCM report
scm_dbcon = SCMQuery(opts.dbuser, opts.dbpassword, opts.dbcvsanaly,
opts.dbidentities, opts.dbprojects)
dataset = scm_report(scm_dbcon, filters)
data["scm"] = dataset
#ITS report
its_dbcon = ITSQuery(opts.dbuser, opts.dbpassword, opts.dbbicho,
opts.dbidentities, opts.dbprojects)
dataset = its_report(its_dbcon, filters)
data["its"] = dataset
#SCR Report
scr_dbcon = SCRQuery(opts.dbuser, opts.dbpassword, opts.dbreview,
opts.dbidentities, opts.dbprojects)
dataset = scr_report(scr_dbcon, filters)
data["scr"] = dataset
return data
def data_source_increment_activity(opts, people_out, affs_out):
# Per data source, the increment or decrement of the activity is displayed
dataset = {}
data_sources = ["Gits", "Tickets", "Mailing Lists", "Gerrit", "Askbot", "IRC"]
action = ["commits", "closed tickets", "sent emails", "submitted reviews", "posted questions", "messages"]
net_values = []
rel_values = [] #percentage wrt the previous 365 days
scm_dbcon = SCMQuery(opts.dbuser, opts.dbpassword, opts.dbcvsanaly, opts.dbidentities)
its_dbcon = ITSQuery(opts.dbuser, opts.dbpassword, opts.dbbicho, opts.dbidentities)
mls_dbcon = MLSQuery(opts.dbuser, opts.dbpassword, opts.dbmlstats, opts.dbidentities)
scr_dbcon = SCRQuery(opts.dbuser, opts.dbpassword, opts.dbreview, opts.dbidentities)
qaforums_dbcon = QAForumsQuery(opts.dbuser, opts.dbpassword, opts.dbqaforums, opts.dbidentities)
irc_dbcon = IRCQuery(opts.dbuser, opts.dbpassword, opts.dbirc, opts.dbidentities)
period = "month"
type_analysis = None
releases = opts.releases.split(",")[-2:]
startdate = "'"+releases[0]+"'"
enddate = "'"+releases[1]+"'"
filters = MetricFilters(period, startdate, enddate, None, 10, people_out, affs_out)
commits = scm.Commits(scm_dbcon, filters)
closed = its.Closed(its_dbcon, filters)
emails = mls.EmailsSent(mls_dbcon, filters)
submitted = scr.Submitted(scr_dbcon, filters)
questions = qa.Questions(qaforums_dbcon, filters)
messages = irc.Sent(irc_dbcon, filters)
from vizgrimoire.ITS import ITS
ITS.set_backend("jira")
net_values.append(commits.get_trends(releases[1], 90)["commits_90"])
rel_values.append(commits.get_trends(releases[1], 90)["percentage_commits_90"])
net_values.append(closed.get_trends(releases[1], 90)["closed_90"])
rel_values.append(closed.get_trends(releases[1], 90)["percentage_closed_90"])
net_values.append(emails.get_trends(releases[1], 90)["sent_90"])
rel_values.append(emails.get_trends(releases[1], 90)["percentage_sent_90"])
net_values.append(submitted.get_trends(releases[1], 90)["submitted_90"])
rel_values.append(submitted.get_trends(releases[1], 90)["percentage_submitted_90"])
net_values.append(questions.get_trends(releases[1], 90)["qsent_90"])
rel_values.append(questions.get_trends(releases[1], 90)["percentage_qsent_90"])
net_values.append(messages.get_trends(releases[1], 90)["sent_90"])
rel_values.append(messages.get_trends(releases[1], 90)["percentage_sent_90"])
createCSV({"datasource":data_sources, "metricsnames":action, "relativevalues":rel_values, "netvalues":net_values}, "./release/data_source_evolution.csv")
def projects_efficiency(opts, people_out, affs_out):
# BMI and time to review in mean per general project
scr_dbcon = SCRQuery(opts.dbuser, opts.dbpassword, opts.dbreview, opts.dbidentities, opts.dbprojects)
scm_dbcon = SCMQuery(opts.dbuser, opts.dbpassword, opts.dbcvsanaly, opts.dbidentities, opts.dbprojects)
its_dbcon = ITSQuery(opts.dbuser, opts.dbpassword, opts.dbbicho, opts.dbidentities, opts.dbprojects)
bmi_list = []
time2review_list = []
bmi_its = []
period = "month"
releases = opts.releases.split(",")[-2:]
startdate = "'"+releases[0]+"'"
enddate = "'"+releases[1]+"'"
type_analysis = None
project_filters = MetricFilters(period, startdate, enddate, type_analysis, 10,
people_out, affs_out)
scr_bmi = scr.BMISCR(scr_dbcon, project_filters)
time2review = scr.TimeToReview(scr_dbcon, project_filters)
# ITS BMI index
from vizgrimoire.ITS import ITS
ITS.set_backend("jira")
opened = its.Opened(its_dbcon, project_filters)
closed = its.Closed(its_dbcon, project_filters)
tickets_opened = opened.get_agg()["opened"]
tickets_closed = closed.get_agg()["closed"]
its_bmi = 0
if tickets_closed > 0:
its_bmi = round(float(tickets_closed)/float(tickets_opened), 2)
bmi_list.append(round(scr_bmi.get_agg()["bmiscr"], 2))
time2review_list.append(round(time2review.get_agg()["review_time_days_median"], 2))
bmi_its.append(its_bmi)
createCSV({"projects":"general", "bmi":bmi_list, "timereview":time2review_list, "bmiits":bmi_its}, "./release/integrated_projects_efficiency.csv")
project_sloc = float(sonar_metrics["ncloc"])
print "Project: " + str(project)
print "NCLOC: " + str(project_sloc)
filters = MetricFilters("month", startdate, enddate,
["project", "'" + project + "'"], opts.npeople,
people_out, affs_out)
#SCM report
scm_dbcon = SCMQuery(opts.dbuser, opts.dbpassword, opts.dbcvsanaly,
opts.dbidentities)
data.update(scm_report(scm_dbcon, filters, project_sloc))
#ITS report
ITS.set_backend("bg")
its_dbcon = ITSQuery(opts.dbuser, opts.dbpassword, opts.dbbicho,
opts.dbidentities)
data.update(its_report(its_dbcon, filters, project_sloc))
#SCR Report
#scr_dbcon = SCRQuery(opts.dbuser, opts.dbpassword, opts.dbreview, opts.dbidentities)
#data["scr"] = scr_report(scr_dbcon, filters)
#MLS Report
mls_dbcon = MLSQuery(opts.dbuser, opts.dbpassword, opts.dbmlstats,
opts.dbidentities)
data.update(mls_report(mls_dbcon, filters, project_sloc))
#FUDFORUMS Report
fudforums_dbcon = MLSQuery(opts.dbuser, opts.dbpassword,
opts.dbfudforums, opts.dbidentities)
dataset = mls_report(fudforums_dbcon, filters, project_sloc)
def projects_efficiency(opts, people_out, affs_out):
# BMI and time to review in mean per general project
scr_dbcon = SCRQuery(opts.dbuser, opts.dbpassword, opts.dbreview,
opts.dbidentities, opts.dbprojects)
scm_dbcon = SCMQuery(opts.dbuser, opts.dbpassword, opts.dbcvsanaly,
opts.dbidentities, opts.dbprojects)
its_dbcon = ITSQuery(opts.dbuser, opts.dbpassword, opts.dbbicho,
opts.dbidentities, opts.dbprojects)
projects = integrated_projects(scm_dbcon)
projects_ids = projects["subproject_id"]
projects_list = []
bmi_list = []
time2review_list = []
bmi_its = []
period = "month"
releases = opts.releases.split(",")[-2:]
startdate = "'" + releases[0] + "'"
enddate = "'" + releases[1] + "'"
for project_id in projects_ids:
project_title = "'" + project_id + "'"
type_analysis = ["project", project_id]
project_filters = MetricFilters(period, startdate, enddate,
type_analysis, 10, people_out,
affs_out)
scr_bmi = scr.BMISCR(scr_dbcon, project_filters)
time2review = scr.TimeToReview(scr_dbcon, project_filters)
# ITS BMI index
from vizgrimoire.ITS import ITS
ITS.set_backend("launchpad")
if project_id == 'Documentation':
ITS._get_backend(
).closed_condition = "(new_value='Fix Committed' or new_value='Fix Released')"
else:
ITS.closed_condition = "(new_value='Fix Committed')"
opened = its.Opened(its_dbcon, project_filters)
closed = its.Closed(its_dbcon, project_filters)
tickets_opened = opened.get_agg()["opened"]
tickets_closed = closed.get_agg()["closed"]
its_bmi = 0
if tickets_closed > 0:
its_bmi = round(float(tickets_closed) / float(tickets_opened), 2)
projects_list.append(project_id)
bmi_list.append(round(scr_bmi.get_agg()["bmiscr"], 2))
time2review_list.append(
round(time2review.get_agg()["review_time_days_median"], 2))
bmi_its.append(its_bmi)
createCSV(
{
"projects": projects_list,
"bmi": bmi_list,
"timereview": time2review_list,
"bmiits": bmi_its
}, "./release/integrated_projects_efficiency.csv")
def get_top_data(cls, startdate, enddate, identities_db, filter_, npeople):
bots = cls.get_bots()
closed_condition = cls._get_closed_condition()
# TODO: It should be configurable from Automator
top_issues_on = False
top = None
mopeners = DataSource.get_metrics("openers", cls)
mclosers = DataSource.get_metrics("closers", cls)
# We should check this metric is ON
stories_openers = DataSource.get_metrics("stories_openers", cls)
if mopeners is None or mclosers is None: return None
period = None
type_analysis = None
if filter_ is not None:
type_analysis = filter_.get_type_analysis()
mfilter = MetricFilters(period, startdate, enddate, type_analysis,
npeople)
if mclosers.filters.closed_condition is not None:
mfilter.closed_condition = mclosers.filters.closed_condition
if filter_ is None:
top_closers_data = {}
top_closers_data['closers.'] = mclosers.get_list(mfilter, 0)
top_closers_data['closers.last month'] = mclosers.get_list(
mfilter, 31)
top_closers_data['closers.last year'] = mclosers.get_list(
mfilter, 365)
top_openers_data = {}
top_openers_data['openers.'] = mopeners.get_list(mfilter, 0)
top_openers_data['openers.last month'] = mopeners.get_list(
mfilter, 31)
top_openers_data['openers.last year'] = mopeners.get_list(
mfilter, 365)
top = dict(top_closers_data.items() + top_openers_data.items())
if top_issues_on:
from vizgrimoire.analysis.top_issues import TopIssues
from vizgrimoire.report import Report
db_identities = Report.get_config()['generic']['db_identities']
dbuser = Report.get_config()['generic']['db_user']
dbpass = Report.get_config()['generic']['db_password']
dbname = Report.get_config()['generic'][cls.get_db_name()]
dbcon = ITSQuery(dbuser, dbpass, dbname, db_identities)
metric_filters = MetricFilters(None, startdate, enddate, [])
top_issues_data = TopIssues(dbcon, metric_filters).result(cls)
top = dict(top.items() + top_issues_data.items())
if False and stories_openers is not None:
top_sopeners_data = {}
top_sopeners_data[
'stories_openers.'] = stories_openers.get_list(mfilter, 0)
top_sopeners_data[
'stories_openers.last month'] = stories_openers.get_list(
mfilter, 31)
top_sopeners_data[
'stories_openers.last year'] = stories_openers.get_list(
mfilter, 365)
top = dict(top.items() + top_sopeners_data.items())
else:
filter_name = filter_.get_name()
if filter_name in ["company", "domain", "repository"]:
if filter_name in ["company", "domain", "repository"]:
top = {}
top['closers.'] = mclosers.get_list(mfilter, 0)
top['closers.last month'] = mclosers.get_list(mfilter, 31)
top['closers.last year'] = mclosers.get_list(mfilter, 365)
else:
# Remove filters above if there are performance issues
top = mclosers.get_list(mfilter)
else:
top = None
return top
if not data:
data = state_data
data[state] = data["changes"]
data.pop("changes") # remove not needed data
else:
data[state] = state_data["changes"]
# TODO: Hardcoded creation of file
createJSON(data, "../../../../json/its-changes.json")
return data
def get_today_date():
import datetime
return str(datetime.date.today())
if __name__ == '__main__':
today_date = "'" + get_today_date() + "'"
filters = MetricFilters("month", "'2010-01-01'", today_date, [])
dbcon = ITSQuery("root", "", "cp_bicho_cloudera", "cp_sortinghat_cloudera")
all_people_changing = StatusChangers(dbcon, filters)
print all_people_changing.result()
all_changes = StatusChanges(dbcon, filters)
print all_changes.result()
trackers.get_trends(enddate, i).items())
if filters.type_analysis == []:
createJSON(data, "scr-static.json")
else:
tracker = filters.type_analysis[1]
tracker = tracker.replace("'", "")
name = tracker.split("/")[-1:][0]
createJSON(data, name + "-scr-static.json")
if __name__ == '__main__':
# PYTHONPATH=./:../../:../analysis/:../ python scr_jira_metrics.py
filters = MetricFilters("month", "'2008-10-20'", "'2014-10-01'", [])
dbcon = ITSQuery("root", "", "lcanas_bicho_gerrit_liferay_4444",
"lcanas_cvsanaly_liferay_4444")
create_json(dbcon, filters)
ITS.set_backend("jira")
ITS._get_backend().closed_condition = " i.status = 'Closed' "
#per tracker data
trackers = Trackers(dbcon, filters)
trackers_list = trackers.get_list()
trackers_names = []
for tracker in trackers_list["name"]:
tracker_name = tracker.split("/")[-1:][0]
trackers_names.append(tracker_name)
tracker_str = "'" + tracker + "'"
filters = MetricFilters("month", "'2008-10-20'", "'2014-10-01'",
['repository', tracker_str])