def timezone_analysis(opts):
from vizgrimoire.analysis.timezone import Timezone
from vizgrimoire.SCM import SCM
from vizgrimoire.MLS import MLS
scm_dbcon = SCMQuery(opts.dbuser, opts.dbpassword, opts.dbcvsanaly,
opts.dbidentities, opts.dbprojects)
mls_dbcon = MLSQuery(opts.dbuser, opts.dbpassword, opts.dbmlstats,
opts.dbidentities, opts.dbprojects)
period = "month"
releases = opts.releases.split(",")[-2:]
startdate = "'" + releases[0] + "'"
enddate = "'" + releases[1] + "'"
filters = MetricFilters(period, startdate, enddate, [], 10, "", "")
tz = Timezone(scm_dbcon, filters)
dataset = tz.result(SCM)
labels = dataset["tz"]
commits = dataset["commits"]
authors = dataset["authors"]
bar_chart("Timezone git activity", labels, commits, "commits_tz", authors,
["commits", "authors"])
tz = Timezone(mls_dbcon, filters)
dataset = tz.result(MLS)
messages = dataset["messages"]
authors = dataset["authors"]
bar_chart("Timezone mailing list activity", labels, messages,
"messages_tz", authors, ["messages", "authors"])
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")
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)
data_aux = {}
data_aux["mls_usr_vol_3m"] = dataset["mls_dev_vol_3m"]
data_aux["mls_usr_subj_3m"] = dataset["mls_dev_subj_3m"]
data_aux["mls_usr_auth_3m"] = dataset["mls_dev_auth_3m"]
data_aux["mls_usr_resp_ratio_3m"] = dataset["mls_dev_resp_ratio_3m"]
data_aux["mls_usr_resp_time_med_3m"] = dataset[
"mls_dev_resp_time_med_3m"]
data.update(data_aux)
def general_info(opts, releases, people_out, affs_out):
# General info from MLS, IRC and QAForums.
scm_dbcon = SCMQuery(opts.dbuser, opts.dbpassword, opts.dbcvsanaly,
opts.dbidentities, opts.dbprojects)
# analysis currently failing
#timezone_analysis(opts)
core = []
regular = []
occasional = []
authors_month = []
emails = []
emails_senders = []
emails_senders_init = []
questions = []
answers = []
comments = []
qsenders = []
irc_sent = []
irc_senders = []
releases_data = {}
for release in releases:
startdate = "'" + release[0] + "'"
enddate = "'" + release[1] + "'"
print "General info per release: " + startdate + " - " + enddate
filters = MetricFilters("month", startdate, enddate, None,
opts.npeople, people_out, affs_out)
# SCM info
print " General info: SCM"
scm_dbcon = SCMQuery(opts.dbuser, opts.dbpassword, opts.dbcvsanaly,
opts.dbidentities, opts.dbprojects)
dataset = scm_general(scm_dbcon, filters)
core.append(dataset["core"])
regular.append(dataset["regular"])
occasional.append(dataset["occasional"])
authors_month.append(float(dataset["authorsperiod"]))
top_authors = dataset["topauthors"]
release_pos = releases.index(release)
createCSV(top_authors,
"./release/top_authors_release" + str(release_pos) + ".csv")
# MLS info
print " General info: MLS"
mls_dbcon = MLSQuery(opts.dbuser, opts.dbpassword, opts.dbmlstats,
opts.dbidentities, opts.dbprojects)
dataset = mls_report(mls_dbcon, filters)
emails.append(dataset["sent"])
emails_senders.append(dataset["senders"])
emails_senders_init.append(dataset["senders_init"])
# QAForums info
print " General info: QAForums"
qaforums_dbcon = QAForumsQuery(opts.dbuser, opts.dbpassword,
opts.dbqaforums, opts.dbidentities,
opts.dbprojects)
dataset = qaforums_report(qaforums_dbcon, filters)
questions.append(dataset["questions"])
answers.append(dataset["answers"])
comments.append(dataset["comments"])
qsenders.append(dataset["qsenders"])
# IRC info
print " General info: IRC"
irc_dbcon = IRCQuery(opts.dbuser, opts.dbpassword, opts.dbirc,
opts.dbidentities, opts.dbprojects)
dataset = irc_report(irc_dbcon, filters)
irc_sent.append(dataset["sent"])
irc_senders.append(dataset["senders"])
labels = [
"13-Q3", "13-Q4", "14-Q1", "14-Q2", "14-Q3", "14-Q4", "15-Q1", "15-Q2"
]
#labels = ["2013-Q3", "2013-Q4", "2014-Q1", "2014-Q2"]
bar_chart("Emails sent", labels, emails, "emails")
createCSV({"labels": labels, "emails": emails}, "./release/emails.csv")
bar_chart("People sending emails", labels, emails_senders,
"emails_senders")
createCSV({
"labels": labels,
"senders": emails_senders
}, "./release/emails_senders.csv")
bar_chart("People initiating threads", labels, emails_senders_init,
"emails_senders_init")
createCSV({
"labels": labels,
"senders": emails_senders_init
}, "./release/emails_senders_init.csv")
bar_chart("Questions", labels, questions, "questions")
createCSV({
"labels": labels,
"questions": questions
}, "./release/questions.csv")
bar_chart("Answers", labels, answers, "answers")
createCSV({"labels": labels, "answers": answers}, "./release/answers.csv")
bar_chart("Comments", labels, comments, "comments")
createCSV({
"labels": labels,
"comments": comments
}, "./release/comments.csv")
bar_chart("People asking Questions", labels, qsenders, "question_senders")
createCSV({
"labels": labels,
"senders": qsenders
}, "./release/question_senders.csv")
bar_chart("Messages in IRC channels", labels, irc_sent, "irc_sent")
createCSV({
"labels": labels,
"messages": irc_sent
}, "./release/irc_sent.csv")
bar_chart("People in IRC channels", labels, irc_senders, "irc_senders")
createCSV({
"labels": labels,
"senders": irc_senders
}, "./release/irc_senders.csv")
bar3_chart("Community structure", labels, regular, "onion", core,
occasional, ["casual", "regular", "core"])
createCSV(
{
"labels": labels,
"core": core,
"regular": regular,
"occasional": occasional
}, "./release/onion_model.csv")
bar_chart("Developers per month", labels, authors_month, "authors_month")
createCSV({
"labels": labels,
"authormonth": authors_month
}, "./release/authors_month.csv")
# other analysis
print "Other analysis"
scm_dbcon = SCMQuery(opts.dbuser, opts.dbpassword, opts.dbcvsanaly,
opts.dbidentities)
## Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. from vizgrimoire.analysis.timezone import Timezone from vizgrimoire.SCM import SCM from vizgrimoire.MLS import MLS from vizgrimoire.metrics.query_builder import SCMQuery from vizgrimoire.metrics.query_builder import MLSQuery from vizgrimoire.metrics.metrics_filter import MetricFilters dbuser = "******" dbpassword = "" dbcvsanaly = "eclipse_source_code" dbmlstats = "eclipse_mailing_list" dbidentities = "eclipse_source_code" period = "month" startdate = "'2013-10-16'" enddate = "'2014-10-17'" scm_dbcon = SCMQuery(dbuser, dbpassword, dbcvsanaly, dbidentities) mls_dbcon = MLSQuery(dbuser, dbpassword, dbmlstats, dbidentities) filters = MetricFilters(period, startdate, enddate, [], 10, "", "") tz = Timezone(scm_dbcon, filters) dataset = tz.result(SCM) print dataset tz = Timezone(mls_dbcon, filters) dataset = tz.result(MLS) print dataset
to_date = self.__get_date_from_month(current_month + 1)
messages = self.__get_messages(from_date, to_date)
for message in messages:
message_id = message[0]
response_of = message[1]
if response_of is None:
unanswered.append(message_id)
continue
if response_of in unanswered:
unanswered.remove(response_of)
num_unanswered['month'].append(current_month)
num_unanswered['unanswered_posts'].append(len(unanswered))
return completePeriodIds(num_unanswered, self.filters.period,
self.filters.startdate, self.filters.enddate)
if __name__ == '__main__':
from vizgrimoire.metrics.query_builder import MLSQuery
filters = MetricFilters("month", "'2014-01-01'", "'2015-01-01'", None, 30)
dbcon = MLSQuery("root", "", "cp_mlstats_GrimoireLibTests",
"cp_sortinghat_GrimoireLibTests")
emailssenders = EmailsSenders(dbcon, filters)
print emailssenders.get_agg()
print emailssenders.get_list(30)
print emailssenders.get_list(365)
if opts.dbbicho is not None:
dbcon = ITSQuery(opts.dbuser, opts.dbpassword, opts.dbbicho,
opts.dbidentities)
dataset.update(its_report(dbcon, filters))
if opts.dbreview is not None:
dbcon = SCRQuery(opts.dbuser, opts.dbpassword, opts.dbreview,
opts.dbidentities)
dataset.update(scr_report(dbcon, filters))
if opts.dbirc is not None:
dbcon = IRCQuery(opts.dbuser, opts.dbpassword, opts.dbirc,
opts.dbidentities)
dataset.update(irc_report(dbcon, filters, opts.output_dir))
if opts.dbqaforums is not None:
dbcon = QAForumsQuery(opts.dbuser, opts.dbpassword,
opts.dbqaforums, opts.dbidentities)
dataset.update(qaforums_report(dbcon, filters, opts.output_dir))
if opts.dbmlstats is not None:
dbcon = MLSQuery(opts.dbuser, opts.dbpassword, opts.dbmlstats,
opts.dbidentities)
dataset.update(mls_report(dbcon, filters, opts.output_dir))
data = update_data(data, dataset)
createJSON(dataset, opts.output_dir + "/report.json")
draw(data, labels, opts.output_dir)