mirror of
https://github.com/karma-riuk/crab.git
synced 2025-07-04 21:28:12 +02:00
92 lines
2.6 KiB
Python
92 lines
2.6 KiB
Python
import os, logging
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from datetime import datetime
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import pandas as pd
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import tqdm
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from github import Github
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# Set up logging
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log_file = "github_api.log"
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logging.basicConfig(
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filename=log_file,
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level=logging.WARNING, # Adjust as needed
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format="%(asctime)s - %(levelname)s - %(message)s",
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datefmt="%Y-%m-%d %H:%M:%S"
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)
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# Redirect PyGithub logging
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logging.getLogger("github.Requester").setLevel(logging.WARNING)
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# Initialize GitHub API client
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g = Github(os.environ["GITHUB_AUTH_TOKEN_CRAB"])
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def parse_date(date: str) -> datetime:
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return datetime.strptime(date, "%Y-%m-%dT%H:%M:%SZ")
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def has_only_1_round_of_comments(commits, comments):
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if not comments or not commits:
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return False
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commit_dates = [parse_date(c.commit.author.date) for c in commits]
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comment_dates = [parse_date(c.created_at) for c in comments]
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commit_dates.sort()
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comment_dates.sort()
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first_comment_time = comment_dates[0]
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last_comment_time = comment_dates[-1]
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n_before = n_after = 0
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for commit_time in commit_dates:
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if commit_time < first_comment_time:
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n_before += 1
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continue
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if commit_time > last_comment_time:
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n_after += 1
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continue
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if first_comment_time < commit_time < last_comment_time:
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return False
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return n_before >= 1 and n_after >= 1
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def process_pull(repo, pull):
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commits = list(pull.get_commits())
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comments = list(pull.get_review_comments())
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return {
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"repo": repo.full_name,
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"pr_number": pull.number,
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"additions": pull.additions,
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"deletions": pull.deletions,
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"changed_files": pull.changed_files,
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"has_only_1_round_of_comments": has_only_1_round_of_comments(commits, comments),
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"has_only_1_comment": len(comments) == 1,
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}
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def process_repo(repo_name):
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repo = g.get_repo(repo_name)
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stats = []
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for pull in tqdm.tqdm(list(repo.get_pulls(state="closed")), desc=repo_name, leave=False):
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if not pull.merged_at:
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continue
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stats.append(process_pull(repo, pull))
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return stats
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def main():
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repos = pd.read_csv("results.csv")
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repos = repos[repos["good_repo_for_crab"] == True]
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stats = []
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try:
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for _, row in tqdm.tqdm(repos.iterrows(), total=len(repos)):
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if "name" not in row or not isinstance(row["name"], str):
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continue
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stats.extend(process_repo(row["name"]))
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finally:
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pd.DataFrame(stats).to_csv("pr_stats.csv", index=False)
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if __name__ == "__main__":
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main()
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