Files
fixminer_source/python/javaDS.py
T
2022-05-09 00:21:02 -04:00

160 lines
5.6 KiB
Python

from datetime import date
from pandas import DataFrame
from common.commons import *
from commitCollector import *
from settings import *
from otherDatasets import markBugFixingPatches, prepareFiles
DATASET_PATH = Path(REPO_PATH)
DATASET = os.environ["dataset"]
PROJECT_LIST = os.environ["PROJECT_LIST"]
def load_commits(repo: str, git_url: str, branch: str) -> DataFrame:
"""
Load commits of a repo
:param repo: Repo name (e.g. "fuse")
:param git_url: Git clone url (e.g. "https://github.com/jboss-fuse/fuse.git")
:param branch: Git branch (e.g. "6.3.0.redhat")
:return: Commits DataFrame
"""
commits_pickle = Path(join(COMMIT_DFS, f'{repo}-fix.pickle.gz'))
# Load existing commits
if commits_pickle.is_file():
return pd.read_pickle(commits_pickle)
# Clone new commits
if not (DATASET_PATH / repo).exists():
shellCallTemplate('git config --global http.postBuffer 157286400')
shellCallTemplate(f'git -C {DATASET_PATH} clone {git_url}')
logging.info(f'Git repo cloned: {repo}')
commits = getCommitFromRepo(join(REPO_PATH, repo), join(COMMIT_DFS, repo), branch)
commits = markBugFixingPatches(commits, repo)
commits.to_pickle(commits_pickle)
return commits
def filter_commits(commits: DataFrame, end_date: date) -> DataFrame:
return commits[commits.commitDate < end_date]
def createDS(project_list: str = PROJECT_LIST):
"""
:param project_list: Comma-separated list of git project names (projects must exist in dataset.csv)
:return:
"""
pjList: list[str] = project_list.split(',')
# Ensure directories exist
DATASET_PATH.mkdir(exist_ok=True)
if not os.path.exists(COMMIT_DFS):
os.mkdir(COMMIT_DFS)
# Find project repo urls in dataset.csv
subjects: DataFrame = pd.read_csv(join(ROOT_DIR, 'data', 'dataset.csv'))
if pjList == ['ALL']:
tuples = subjects[['Repo', 'GitRepo', 'Branch']].values.tolist()
else:
tuples = subjects[subjects.Repo.isin(pjList)][['Repo', 'GitRepo', 'Branch']].values.tolist()
# Loop through repos
for repo, src, branch in tuples:
logging.info(f'Processing {repo}')
commits = load_commits(repo, src, branch)
# keep only commits that has moves
commits = commits[[any(c == 'M' for c in dic.values()) for dic in commits.files]]
# keep only commits that are changing java files (.java)
commits = commits[[all(k.endswith('.java') for k in dic) for dic in commits.files]]
# not a revert commit
# commits = commits[~commits.log.apply(lambda x: x.startswith('Revert'))]
# commits = commits[commits.files.apply(lambda x: len(x) == 1)]
# commits['cocci'] = commits.log.apply(lambda x: True if re.search('cocci|coccinelle', x) else False)
# coccis = commits[commits.cocci].commit.values.tolist()
fixes = commits[commits.fixes.str.len() != 0].commit.values.tolist()
# links = commits[commits.links.str.len()!=0].commit.values.tolist()
# bugs = set(fixes).union(links).union(coccis)
# bugs = set(fixes)#.union(coccis)
commits = commits[commits.commit.isin(fixes)]
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)