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")