def test_repo(self):
repo = Repository('Jabref', 'jabref')
repo.scrape()
loader_repos = Loader('user')
i = 0
data_repos = loader_repos.load_data()
for x in data_repos:
i += 1
if i == 1:
self.assertEqual("1", x['total_pr'])
def test_repo(self):
repo = Repository('Jabref', 'jabref')
repo.scrape()
loader_repos = Loader('repo')
i = 0
data_repos = loader_repos.load_data()
for x in data_repos:
i += 1
if i == 1:
self.assertEqual("jabref", x['name'])
self.assertEqual("Jabref", x['login'])
def test_repo(self):
repo = Repository('Jabref', 'jabref')
repo.scrape()
loader_repos = Loader('repo')
i = 0
data_repos = loader_repos.load_data()
for repo in data_repos:
loader_prs = Loader('pr')
loader_prs.set_login(repo['login'])
loader_prs.set_name(repo['name'])
data_prs = loader_prs.load_data()
for data_pr in data_prs:
i += 1
if i == 1:
self.assertEqual("24", data_pr['number'])
if i == 2:
self.assertEqual("20", data_pr['number'])
if i == 3:
self.assertEqual("16", data_pr['number'])
if i == 4:
self.assertEqual("15", data_pr['number'])
def execute():
# request the system to collect data for a specific repository
if options.collect:
# scrape repository specified
repo = Repository(options.collect[0], args[0])
repo.scrape()
# scrape pull requests for this repository, including users
pr = PullRequest(options.collect[0], args[0])
pr.scrape()
return
# list all repos collected
loader_repos = Loader('repo')
data_repos = loader_repos.load_data()
if options.repos:
for data_repo in data_repos:
description = data_repo['login'] + '/' + data_repo['name'] + ': ' + data_repo['description'] + ' (' + \
data_repo['watchers'] + ' of stars)'
print(description)
# list all pull requests from a repo (or summary)
if options.pullrequest or options.summary:
# list all repos for choosing
print("Repositories: ")
for data_repo in data_repos:
description = data_repo['login'] + '/' + data_repo['name']
print(description)
# choose and list pull requests
login_chosen = input("\nUsername (login): ")
name_chosen = input("Repository Name: ")
loader_prs = Loader('pr')
loader_prs.set_login(login_chosen)
loader_prs.set_name(name_chosen)
data_prs = loader_prs.load_data()
# output the detail
if options.pullrequest:
for data_pr in data_prs:
description = 'title: ' + data_pr['title'] + ', number: ' + data_pr['number'] + ', state: ' + data_pr['state'] + ', by user: '******'user'] + ', commits: ' + data_pr['commits']
print(description)
# output summary
if options.summary:
pr_open = 0
pr_closed = 0
pr_users = []
smallest_number = 999999
oldest_date = ''
for data_pr in data_prs:
if data_pr['state'] == 'open':
pr_open += 1
if data_pr['state'] == 'closed':
pr_closed += 1
pr_users.append(data_pr['user'])
if int(data_pr['number']) < smallest_number:
smallest_number = int(data_pr['number'])
oldest_date = data_pr['created_at']
pr_users = len(set(pr_users))
print("\nRepository Summary:\n")
print("number of pull requests in 'open' state:", pr_open)
print("number of pull requests in 'closed' state:", pr_closed)
print("number of users:", pr_users)
print("date of the oldest pull request:", oldest_date)
# twitter data is located in user class
# create graphics given a repo, or create graphics considering all pull requests from all repos
if options.graph or options.allpr:
graph = Graph()
if options.graph:
graph.set_repo(options.graph[0], args[0])
graph.display()
# calculate the correlation between the data collected for a user
if options.usercorrelation:
loader_repos = Loader('user')
data_users = loader_repos.load_data()
for user in data_users:
co = np.corrcoef([int(user['followers']), int(user['following']), int(user['commit_last_year'])])
print("Correlation: ", co)
# calculate the correlation between all the numeric data in the pull requests for a repo
if options.inprcorrelation:
loader_repos = Loader('repo')
data_repos = loader_repos.load_data()
for repo in data_repos:
loader_prs = Loader('pr')
loader_prs.set_login(repo['login'])
loader_prs.set_name(repo['name'])
data_prs = loader_prs.load_data()
for data_pr in data_prs:
co = np.corrcoef([int(data_pr['number']), int(data_pr['commits']), int(data_pr['additions']), int(data_pr['deletions']), int(data_pr['changed_files'])])
print("Correlation: ", co)