now using the PyGithub library, so that it handles

for me the issue of too many requests in too little time

requirements.txt

@@ -3,3 +3,4 @@ tqdm
 docker
 beautifulsoup4
 unidiff
+PyGithub

stats_pull_requests.py

@@ -1,35 +1,22 @@
-import os, requests
+import os
 from datetime import datetime
 import pandas as pd
 import tqdm
+from github import Github
 
-COMMON_HEADERS = {
+# Initialize GitHub API client
-    'Accept': 'application/vnd.github+json',
+g = Github(os.environ["GITHUB_AUTH_TOKEN_CRAB"])
-    'Authorization': f'Bearer {os.environ["GITHUB_AUTH_TOKEN_CRAB"]}',
-    'X-Github-Api-Version': '2022-11-28',
-}
 
-def github_call(url, params = {}):
+def has_only_1_round_of_comments(commits, comments):
-    result = requests.get(url, headers=COMMON_HEADERS, params=params)
+    if not comments or not commits:
-    if result.status_code != 200:
-        raise Exception(f"Failed to fetch {url}: {result.status_code}, {result = }")
-    return result
-
-def get_pulls(repo_url: str) -> list[dict]:
-    response = github_call(f'{repo_url}/pulls', params={"state": "all"})
-    return response.json()
-
-def has_only_1_round_of_comments(commits: list[dict], comments: list[dict]) -> bool:
-    if len(comments) == 0 or len(commits) == 0:
         return False
     
-    # Convert timestamps to datetime objects for easy comparison
+    commit_dates = [c.commit.author.date for c in commits]
-    commit_dates = [datetime.fromisoformat(c["commit"]["author"]["date"]) for c in commits]
+    comment_dates = [c.created_at for c in comments]
-    comment_dates = [datetime.fromisoformat(c["created_at"]) for c in comments]
+    
     commit_dates.sort()
     comment_dates.sort()
     
-    # Identify the first and last comment times
     first_comment_time = comment_dates[0]
     last_comment_time = comment_dates[-1]
     
@@ -39,47 +26,43 @@ def has_only_1_round_of_comments(commits: list[dict], comments: list[dict]) -> b
     
     return True
 
-
+def process_pull(repo, pull):
-def process_pull(repo_name: str, pull_number: str) -> dict:
+    commits = list(pull.get_commits())
-    pull = github_call(f"https://api.github.com/repos/{repo_name}/pulls/{pull_number}").json()
+    comments = list(pull.get_review_comments())
-    commits = github_call(f"https://api.github.com/repos/{repo_name}/pulls/{pull_number}/commits").json()
-    comments = github_call(f"https://api.github.com/repos/{repo_name}/pulls/{pull_number}/comments").json()
     
     return {
-        "repo": repo_name,
+        "repo": repo.full_name,
-        "pr_number": pull["number"],
+        "pr_number": pull.number,
-        "additions": pull["additions"],
+        "additions": pull.additions,
-        "deletions": pull["deletions"],
+        "deletions": pull.deletions,
-        "changed_files": pull["changed_files"],
+        "changed_files": pull.changed_files,
         "has_only_1_round_of_comments": has_only_1_round_of_comments(commits, comments),
         "has_only_1_comment": len(comments) == 1,
     }
 
-def process_repo(repo_name: str) -> list[dict]:
+def process_repo(repo_name):
+    repo = g.get_repo(repo_name)
     stats = []
-    pulls = get_pulls(f"https://api.github.com/repos/{repo_name}")
+    
-    for pull in tqdm.tqdm(pulls, desc=repo_name, leave=False):
+    for pull in tqdm.tqdm(list(repo.get_pulls(state="closed")), desc=repo_name, leave=False):
-        if "merged_at" not in pull or pull["merged_at"] is None:
+        if not pull.merged_at:
             continue
         
-        stats.append(process_pull(repo_name, pull["number"]))
+        stats.append(process_pull(repo, pull))
     return stats
 
-
 def main():
     repos = pd.read_csv("results.csv")
     repos = repos[repos["good_repo_for_crab"] == True]
-    print(len(repos))
     stats = []
     
+    try:
         for _, row in tqdm.tqdm(repos.iterrows(), total=len(repos)):
             if "name" not in row or not isinstance(row["name"], str):
                 continue
-        name = row["name"]
+            stats.extend(process_repo(row["name"]))
-        stats.extend(process_repo(name))
+    finally:
-
         pd.DataFrame(stats).to_csv("pr_stats.csv", index=False)
 
-
 if __name__ == "__main__":
     main()