def companiesData(period, startdate, enddate, idb, destdir):
# companies = dataFrame2Dict(vizr.GetCompaniesSCRName(startdate, enddate, idb))
companies = SCR.GetCompaniesSCRName(startdate, enddate, idb)
companies = companies['name']
companies_files = [company.replace('/', '_') for company in companies]
createJSON(companies_files, destdir + "/scr-companies.json")
# missing information from the rest of type of reviews, patches and
# number of patches waiting for reviewer and submitter
for company in companies:
company_file = company.replace("/", "_")
type_analysis = ['company', company]
# Evol
evol = {}
# data = vizr.EvolReviewsSubmitted(period, startdate, enddate, type_analysis, idb)
# evol = dict(evol.items() + completePeriodIds(dataFrame2Dict(data)).items())
data = SCR.EvolReviewsSubmitted(period, startdate, enddate,
type_analysis, idb)
evol = dict(evol.items() + completePeriodIds(data).items())
data = SCR.EvolReviewsMerged(period, startdate, enddate, type_analysis,
idb)
evol = dict(evol.items() + completePeriodIds(data).items())
data = SCR.EvolReviewsAbandoned(period, startdate, enddate,
type_analysis, idb)
evol = dict(evol.items() + completePeriodIds(data).items())
if (period == "month"):
data = SCR.EvolTimeToReviewSCR(period, startdate, enddate, idb,
type_analysis)
data['review_time_days_avg'] = checkFloatArray(
data['review_time_days_avg'])
data['review_time_days_median'] = checkFloatArray(
data['review_time_days_median'])
evol = dict(evol.items() + completePeriodIds(data).items())
createJSON(evol,
destdir + "/" + company_file + "-scr-com-evolutionary.json")
# Static
agg = {}
# data = vizr.StaticReviewsSubmitted(period, startdate, enddate, type_analysis, idb)
# agg = dict(agg.items() + dataFrame2Dict(data).items())
data = SCR.StaticReviewsSubmitted(period, startdate, enddate,
type_analysis, idb)
agg = dict(agg.items() + data.items())
data = SCR.StaticReviewsMerged(period, startdate, enddate,
type_analysis, idb)
agg = dict(agg.items() + data.items())
data = SCR.StaticReviewsAbandoned(period, startdate, enddate,
type_analysis, idb)
agg = dict(agg.items() + data.items())
data = SCR.StaticTimeToReviewSCR(startdate, enddate, idb,
type_analysis)
val = data['review_time_days_avg']
if (not val or val == 0): data['review_time_days_avg'] = 0
else: data['review_time_days_avg'] = float(val)
val = data['review_time_days_median']
if (not val or val == 0): data['review_time_days_median'] = 0
else: data['review_time_days_median'] = float(val)
agg = dict(agg.items() + data.items())
createJSON(agg, destdir + "/" + company_file + "-scr-com-static.json")
def reposData(period, startdate, enddate, idb, destdir, conf):
repos = SCR.GetReposSCRName(startdate, enddate)
repos = repos["name"]
# For repos aggregated data. Include metrics to sort in javascript.
repos_list = {"name":[],"review_time_days_median":[],"submitted":[]}
# missing information from the rest of type of reviews, patches and
# number of patches waiting for reviewer and submitter
for repo in repos:
repo_file = repo.replace("/","_")
logging.info(repo_file)
repos_list["name"].append(repo_file)
# logging.info("Repo: " + repo_file)
type_analysis = ['repository', repo]
evol = {}
# data = vizr.EvolReviewsSubmitted(period, startdate, enddate, type_analysis)
data = SCR.EvolReviewsSubmitted(period, startdate, enddate, type_analysis)
evol = dict(evol.items() + completePeriodIds(data).items())
data = SCR.EvolReviewsMerged(period, startdate, enddate, type_analysis)
evol = dict(evol.items() + completePeriodIds(data).items())
data = SCR.EvolReviewsAbandoned(period, startdate, enddate, type_analysis)
evol = dict(evol.items() + completePeriodIds(data).items())
# data = vizr.EvolReviewsPendingChanges(period, startdate, enddate, conf, type_analysis)
# evol = dict(evol.items() + completePeriodIds(dataFrame2Dict(data)).items())
data = SCR.EvolReviewsPending(period, startdate, enddate, conf, type_analysis, idb)
evol = dict(evol.items() + completePeriodIds(data).items())
if (period == "month"):
data = SCR.EvolTimeToReviewSCR(period, startdate, enddate, idb, type_analysis)
data['review_time_days_avg'] = checkFloatArray(data['review_time_days_avg'])
data['review_time_days_median'] = checkFloatArray(data['review_time_days_median'])
evol = dict(evol.items() + completePeriodIds(data).items())
createJSON(evol, destdir+ "/"+repo_file+"-scr-rep-evolutionary.json")
# Static
agg = {}
data = SCR.StaticReviewsSubmitted(period, startdate, enddate, type_analysis)
repos_list["submitted"].append(data["submitted"])
agg = dict(agg.items() + data.items())
data = SCR.StaticReviewsMerged(period, startdate, enddate, type_analysis)
agg = dict(agg.items() + data.items())
data = SCR.StaticReviewsAbandoned(period, startdate, enddate, type_analysis)
agg = dict(agg.items() + data.items())
data = SCR.StaticReviewsPending(period, startdate, enddate, type_analysis)
agg = dict(agg.items() + data.items())
data = SCR.StaticTimeToReviewSCR(startdate, enddate, idb, type_analysis)
val = data['review_time_days_avg']
if (not val or val == 0): data['review_time_days_avg'] = 0
else: data['review_time_days_avg'] = float(val)
val = data['review_time_days_median']
if (not val or val == 0): data['review_time_days_median'] = 0
else: data['review_time_days_median'] = float(val)
agg = dict(agg.items() + data.items())
repos_list["review_time_days_median"].append(data['review_time_days_median'])
createJSON(agg, destdir + "/"+repo_file + "-scr-rep-static.json")
createJSON(repos_list, destdir+"/scr-repos.json")
def companiesData(period, startdate, enddate, idb, destdir):
# companies = dataFrame2Dict(vizr.GetCompaniesSCRName(startdate, enddate, idb))
companies = SCR.GetCompaniesSCRName(startdate, enddate, idb)
companies = companies['name']
companies_files = [company.replace('/', '_') for company in companies]
createJSON(companies_files, destdir+"/scr-companies.json")
# missing information from the rest of type of reviews, patches and
# number of patches waiting for reviewer and submitter
for company in companies:
company_file = company.replace("/","_")
type_analysis = ['company', company]
# Evol
evol = {}
# data = vizr.EvolReviewsSubmitted(period, startdate, enddate, type_analysis, idb)
# evol = dict(evol.items() + completePeriodIds(dataFrame2Dict(data)).items())
data = SCR.EvolReviewsSubmitted(period, startdate, enddate, type_analysis, idb)
evol = dict(evol.items() + completePeriodIds(data).items())
data = SCR.EvolReviewsMerged(period, startdate, enddate, type_analysis, idb)
evol = dict(evol.items() + completePeriodIds(data).items())
data = SCR.EvolReviewsAbandoned(period, startdate, enddate, type_analysis, idb)
evol = dict(evol.items() + completePeriodIds(data).items())
if (period == "month"):
data = SCR.EvolTimeToReviewSCR(period, startdate, enddate, idb, type_analysis)
data['review_time_days_avg'] = checkFloatArray(data['review_time_days_avg'])
data['review_time_days_median'] = checkFloatArray(data['review_time_days_median'])
evol = dict(evol.items() + completePeriodIds(data).items())
createJSON(evol, destdir+ "/"+company_file+"-scr-com-evolutionary.json")
# Static
agg = {}
# data = vizr.StaticReviewsSubmitted(period, startdate, enddate, type_analysis, idb)
# agg = dict(agg.items() + dataFrame2Dict(data).items())
data = SCR.StaticReviewsSubmitted(period, startdate, enddate, type_analysis, idb)
agg = dict(agg.items() + data.items())
data = SCR.StaticReviewsMerged(period, startdate, enddate, type_analysis, idb)
agg = dict(agg.items() + data.items())
data = SCR.StaticReviewsAbandoned(period, startdate, enddate, type_analysis, idb)
agg = dict(agg.items() + data.items())
data = SCR.StaticTimeToReviewSCR(startdate, enddate, idb, type_analysis)
val = data['review_time_days_avg']
if (not val or val == 0): data['review_time_days_avg'] = 0
else: data['review_time_days_avg'] = float(val)
val = data['review_time_days_median']
if (not val or val == 0): data['review_time_days_median'] = 0
else: data['review_time_days_median'] = float(val)
agg = dict(agg.items() + data.items())
createJSON(agg, destdir+"/"+company_file+"-scr-com-static.json")
def reposData(period, startdate, enddate, idb, destdir, conf):
repos = SCR.GetReposSCRName(startdate, enddate)
repos = repos["name"]
# For repos aggregated data. Include metrics to sort in javascript.
repos_list = {"name": [], "review_time_days_median": [], "submitted": []}
# missing information from the rest of type of reviews, patches and
# number of patches waiting for reviewer and submitter
for repo in repos:
repo_file = repo.replace("/", "_")
logging.info(repo_file)
repos_list["name"].append(repo_file)
# logging.info("Repo: " + repo_file)
type_analysis = ['repository', repo]
evol = {}
# data = vizr.EvolReviewsSubmitted(period, startdate, enddate, type_analysis)
data = SCR.EvolReviewsSubmitted(period, startdate, enddate,
type_analysis)
evol = dict(evol.items() + completePeriodIds(data).items())
data = SCR.EvolReviewsMerged(period, startdate, enddate, type_analysis)
evol = dict(evol.items() + completePeriodIds(data).items())
data = SCR.EvolReviewsAbandoned(period, startdate, enddate,
type_analysis)
evol = dict(evol.items() + completePeriodIds(data).items())
# data = vizr.EvolReviewsPendingChanges(period, startdate, enddate, conf, type_analysis)
# evol = dict(evol.items() + completePeriodIds(dataFrame2Dict(data)).items())
data = SCR.EvolReviewsPending(period, startdate, enddate, conf,
type_analysis, idb)
evol = dict(evol.items() + completePeriodIds(data).items())
if (period == "month"):
data = SCR.EvolTimeToReviewSCR(period, startdate, enddate, idb,
type_analysis)
data['review_time_days_avg'] = checkFloatArray(
data['review_time_days_avg'])
data['review_time_days_median'] = checkFloatArray(
data['review_time_days_median'])
evol = dict(evol.items() + completePeriodIds(data).items())
createJSON(evol,
destdir + "/" + repo_file + "-scr-rep-evolutionary.json")
# Static
agg = {}
data = SCR.StaticReviewsSubmitted(period, startdate, enddate,
type_analysis)
repos_list["submitted"].append(data["submitted"])
agg = dict(agg.items() + data.items())
data = SCR.StaticReviewsMerged(period, startdate, enddate,
type_analysis)
agg = dict(agg.items() + data.items())
data = SCR.StaticReviewsAbandoned(period, startdate, enddate,
type_analysis)
agg = dict(agg.items() + data.items())
data = SCR.StaticReviewsPending(period, startdate, enddate,
type_analysis)
agg = dict(agg.items() + data.items())
data = SCR.StaticTimeToReviewSCR(startdate, enddate, idb,
type_analysis)
val = data['review_time_days_avg']
if (not val or val == 0): data['review_time_days_avg'] = 0
else: data['review_time_days_avg'] = float(val)
val = data['review_time_days_median']
if (not val or val == 0): data['review_time_days_median'] = 0
else: data['review_time_days_median'] = float(val)
agg = dict(agg.items() + data.items())
repos_list["review_time_days_median"].append(
data['review_time_days_median'])
createJSON(agg, destdir + "/" + repo_file + "-scr-rep-static.json")
createJSON(repos_list, destdir + "/scr-repos.json")
