[-] Remove commented code

This commit is contained in:
Azalea (on HyDEV-Daisy)
2022-05-09 00:21:46 -04:00
parent ce8085b21a
commit 0b0a1e7579
2 changed files with 2 additions and 117 deletions
+2 -49
View File
@@ -31,57 +31,10 @@ def getCommitFromRepo(f: PathLike, gitrepo: str, branch: str):
shellCallTemplate(f"git -C {f} log --no-merges --pretty=format:'{form}' > {file}", enc='latin1')
# Collect commits
commits = json.loads(f'[{Path(file).read_text()}]')
content = Path(file).read_text().replace("\n", ",")
commits = json.loads(f'[{content}]')
# Convert to DataFrame
ds = pd.DataFrame.from_dict(commits)
ds['commitDate'] = pd.to_datetime(ds['commitDate'])
return ds
def caseCollect(subject):
if not os.path.exists(COMMIT_FOLDER):
os.mkdir(COMMIT_FOLDER)
if not os.path.exists(COMMIT_DFS):
os.mkdir(COMMIT_DFS)
subjects = pd.read_csv(join(DATA_PATH, 'subjects.csv'))
if subject == 'ALL':
tuples = subjects[['Repo', 'Branch']].values.tolist()
else:
# repos = subjects.query("Subject == '{0}'".format(subject)).Repo.tolist()
tuples = subjects.query("Subject == '{0}'".format(subject))[
['Repo', 'Branch']].values.tolist()
for t in tuples:
repo, branch = t
logging.info(repo)
getCommitFromRepo(join(REPO_PATH, repo), join(COMMIT_FOLDER, repo), branch)
if subject == 'ALL':
commits = listdir(COMMIT_FOLDER)
else:
commits = [i for i in listdir(COMMIT_FOLDER) if i.startswith(repo)]
for commit in commits:
logging.info(commit)
rDF = makeDF(join(COMMIT_FOLDER, commit))
repoName = commit.split('.')[0]
save_zipped_pickle(rDF, join(COMMIT_DFS, repoName + ".pickle"))
# p.dump(rDF, open(join(COMMIT_DFS, repoName + ".pickle"), "wb"))
def caseClone(subject):
if not os.path.exists(REPO_PATH):
os.mkdir(REPO_PATH)
subjects = pd.read_csv(join(DATA_PATH, 'subjects.csv'))
if subject == 'ALL':
gitrepos = subjects.GitRepo.tolist()
else:
gitrepos = subjects.query("Subject == '{0}'".format(subject)).GitRepo.tolist()
os.getcwd()
os.chdir(REPO_PATH)
for gitrepo in gitrepos:
cmd = 'git clone ' + gitrepo
out = shellCallTemplate(cmd)
-68
View File
@@ -89,71 +89,3 @@ def createDS(project_list: str = PROJECT_LIST):
print(len(commits))
# for s in a.commit.values.tolist():
parallelRun(prepareFiles, commits[['commit', 'files']].values.tolist(), repo)
# # if job == 'clone':
# for repo,src in subjects[['Repo','GitRepo']].values.tolist():
# if(pjList != ['ALL']):
# if repo in pjList:
# print(repo)
# cmd = 'git -C ' + DATASET_PATH + ' clone ' + src
# shellCallTemplate(cmd)
# logging.info(repo)
# caseClone(subject)
# caseCollect(subject)
# # elif job == 'fix':
# from filterBugFixingCommits import caseFix
#
# caseFix(subject)
# #
# # # elif job =='brDownload':
# from bugReportDownloader import caseBRDownload
#
# caseBRDownload(subject)
# # # elif job =='brParser':
# from bugReportParser import step1
#
# step1(subject)
#
# # elif job =='dataset':
#
# if not isfile(join(DATA_PATH, 'singleBR.pickle')):
#
# brs = load_zipped_pickle(join(DATA_PATH, subject + "bugReportsComplete.pickle"))
#
# subjects = pd.read_csv(join(DATA_PATH, 'subjects.csv'))
#
#
# def getCommit(x):
# bid, project = x
#
# subjects = pd.read_csv(join(DATA_PATH, 'subjects.csv'))
# repo = subjects.query("Subject == '{0}'".format(project)).Repo.tolist()[0]
# commits = load_zipped_pickle(join(DATA_PATH, COMMIT_DFS, repo + '.pickle'))
# correspondingCommit = commits.query("fix =='{0}'".format(bid)).commit.tolist()
# if len(correspondingCommit) == 1:
# return [bid, correspondingCommit[0], project]
# else:
# return None
# print('error')
#
#
# wl = brs[['bid', 'project']].values.tolist()
# dataL = parallelRunMerge(getCommit, wl)
#
# commits = pd.DataFrame(
# columns=['bid', 'commit', 'project'],
# data=list(filter(None.__ne__, dataL)))
#
# save_zipped_pickle(commits, join(DATA_PATH, 'singleBR.pickle'))
# else:
# commits = load_zipped_pickle(join(DATA_PATH, 'singleBR.pickle'))
# subjects = pd.read_csv(join(DATA_PATH, 'subjects.csv'))
# logging.info('done matching commits')
# commits['repo'] = commits.project.apply(lambda x: subjects.query("Subject == '{0}'".format(x)).Repo.tolist()[0])
#
# workList = commits[['commit', 'repo']].values.tolist()
# from dataset import prepareFiles
#
# parallelRun(prepareFiles, workList)