First stab at figuring out the number of very active mentors

README.md

@@ -141,6 +141,10 @@ This action can be configured to authenticate with GitHub App Installation or Pe
 | `HIDE_TIME_TO_CLOSE`          | False | False      | If set to `true`, the time to close will not be displayed in the generated Markdown file. |
 | `HIDE_TIME_TO_FIRST_RESPONSE` | False    | False   | If set to `true`, the time to first response will not be displayed in the generated Markdown file. |
 | `IGNORE_USERS`                | False | False      | A comma separated list of users to ignore when calculating metrics. (ie. `IGNORE_USERS: 'user1,user2'`). To ignore bots, append `[bot]` to the user (ie. `IGNORE_USERS: 'github-actions[bot]'`)  |
+| `ENABLE_MENTOR_COUNT` | False | False | If set to 'TRUE' count number of comments users left on discussions, issues and PRs and display number of active mentors |
+| `MIN_MENTOR_COMMENTS` | False | 10 | Minimum number of comments to count as a mentor |
+| `MAX_COMMENTS_EVAL` | False | 20 | Maximum number of comments per thread to evaluate for mentor stats |
+| `HEAVILY_INVOLVED_CUTOFF` | False | 3 | Cutoff after which a mentor's comments in one issue are no longer counted against their total score |
 | `LABELS_TO_MEASURE`           | False    | `""`    | A comma separated list of labels to measure how much time the label is applied. If not provided, no labels durations will be measured. Not compatible with discussions at this time. |
 | `SEARCH_QUERY`                | True     | `""`    | The query by which you can filter issues/PRs which must contain a `repo:`, `org:`, `owner:`, or a `user:` entry. For discussions, include `type:discussions` in the query. |
 

classes.py

@@ -19,9 +19,12 @@ class IssueWithMetrics:
         time_to_answer (timedelta, optional): The time it took to answer the
             discussions in the issue.
         label_metrics (dict, optional): A dictionary containing the label metrics
+        mentor_activity (dict, optional): A dictionary containing active mentors
 
     """
 
+    # pylint: disable=too-many-instance-attributes
+
     def __init__(
         self,
         title,
@@ -31,6 +34,7 @@ def __init__(
         time_to_close=None,
         time_to_answer=None,
         labels_metrics=None,
+        mentor_activity=None,
     ):
         self.title = title
         self.html_url = html_url
@@ -39,3 +43,4 @@ def __init__(
         self.time_to_close = time_to_close
         self.time_to_answer = time_to_answer
         self.label_metrics = labels_metrics
+        self.mentor_activity = mentor_activity

config.py

@@ -34,6 +34,10 @@ class EnvVars:
         hide_time_to_first_response (bool): If true, the time to first response metric is hidden in the output
         ignore_users (List[str]): List of usernames to ignore when calculating metrics
         labels_to_measure (List[str]): List of labels to measure how much time the lable is applied
+        enable_mentor_count (str): If set to TRUE, compute number of mentors
+        min_mentor_comments (str): If set, defines the minimum number of comments for mentors
+        max_comments_eval (str): If set, defines the maximum number of comments to look at for mentor evaluation
+        heavily_involved_cutoff (str): If set, defines the cutoff after which heavily involved commentors in
         search_query (str): Search query used to filter issues/prs/discussions on GitHub
     """
 
@@ -51,11 +55,16 @@ def __init__(
         hide_time_to_first_response: bool,
         ignore_user: List[str],
         labels_to_measure: List[str],
+        enable_mentor_count: str,
+        min_mentor_comments: str,
+        max_comments_eval: str,
+        heavily_involved_cutoff: str,
         search_query: str,
     ):
         self.gh_app_id = gh_app_id
         self.gh_app_installation_id = gh_app_installation_id
         self.gh_app_private_key_bytes = gh_app_private_key_bytes
+        self.search_query = search_query
         self.gh_token = gh_token
         self.ghe = ghe
         self.ignore_users = ignore_user
@@ -65,6 +74,10 @@ def __init__(
         self.hide_time_to_answer = hide_time_to_answer
         self.hide_time_to_close = hide_time_to_close
         self.hide_time_to_first_response = hide_time_to_first_response
+        self.enable_mentor_count = enable_mentor_count
+        self.min_mentor_comments = min_mentor_comments
+        self.max_comments_eval = max_comments_eval
+        self.heavily_involved_cutoff = heavily_involved_cutoff
         self.search_query = search_query
 
     def __repr__(self):
@@ -82,6 +95,10 @@ def __repr__(self):
             f"{self.hide_time_to_first_response},"
             f"{self.ignore_users},"
             f"{self.labels_to_measure},"
+            f"{self.enable_mentor_count},"
+            f"{self.min_mentor_comments},"
+            f"{self.max_comments_eval},"
+            f"{self.heavily_involved_cutoff},"
             f"{self.search_query})"
         )
 
@@ -166,6 +183,10 @@ def get_env_vars(test: bool = False) -> EnvVars:
     hide_time_to_answer = get_bool_env_var("HIDE_TIME_TO_ANSWER")
     hide_time_to_close = get_bool_env_var("HIDE_TIME_TO_CLOSE")
     hide_time_to_first_response = get_bool_env_var("HIDE_TIME_TO_FIRST_RESPONSE")
+    enable_mentor_count = os.getenv("ENABLE_MENTOR_COUNT", "FALSE")
+    min_mentor_comments = os.getenv("MIN_MENTOR_COMMENTS", "10")
+    max_comments_eval = os.getenv("MAX_COMMENTS_EVAL", "20")
+    heavily_involved_cutoff = os.getenv("HEAVILY_INVOLVED_CUTOFF", "3")
 
     return EnvVars(
         gh_app_id,
@@ -180,5 +201,9 @@ def get_env_vars(test: bool = False) -> EnvVars:
         hide_time_to_first_response,
         ignore_users_list,
         labels_to_measure_list,
+        enable_mentor_count,
+        min_mentor_comments,
+        max_comments_eval,
+        heavily_involved_cutoff,
         search_query,
     )

issue_metrics.py

@@ -31,6 +31,7 @@
 from json_writer import write_to_json
 from labels import get_label_metrics, get_stats_time_in_labels
 from markdown_writer import write_to_markdown
+from most_active_mentors import count_comments_per_user, get_mentor_count
 from time_to_answer import get_stats_time_to_answer, measure_time_to_answer
 from time_to_close import get_stats_time_to_close, measure_time_to_close
 from time_to_first_response import (
@@ -40,8 +41,6 @@
 from time_to_merge import measure_time_to_merge
 from time_to_ready_for_review import get_time_to_ready_for_review
 
-GITHUB_BASE_URL = "https://github.com"
-
 
 def search_issues(
     search_query: str, github_connection: github3.GitHub
@@ -126,6 +125,8 @@ def get_per_issue_metrics(
     discussions: bool = False,
     labels: Union[List[str], None] = None,
     ignore_users: Union[List[str], None] = None,
+    max_comments_to_eval: int = 20,
+    heavily_involved: int = 3,
 ) -> tuple[List, int, int]:
     """
     Calculate the metrics for each issue/pr/discussion in a list provided.
@@ -158,10 +159,20 @@ def get_per_issue_metrics(
                 None,
                 None,
                 None,
+                None,
             )
             issue_with_metrics.time_to_first_response = measure_time_to_first_response(
                 None, issue, ignore_users
             )
+            issue_with_metrics.mentor_activity = count_comments_per_user(
+                None,
+                issue,
+                ignore_users,
+                None,
+                None,
+                max_comments_to_eval,
+                heavily_involved,
+            )
             issue_with_metrics.time_to_answer = measure_time_to_answer(issue)
             if issue["closedAt"]:
                 issue_with_metrics.time_to_close = measure_time_to_close(None, issue)
@@ -188,6 +199,15 @@ def get_per_issue_metrics(
             issue_with_metrics.time_to_first_response = measure_time_to_first_response(
                 issue, None, pull_request, ready_for_review_at, ignore_users
             )
+            issue_with_metrics.mentor_activity = count_comments_per_user(
+                issue,
+                None,
+                pull_request,
+                ready_for_review_at,
+                ignore_users,
+                max_comments_to_eval,
+                heavily_involved,
+            )
             if labels:
                 issue_with_metrics.label_metrics = get_label_metrics(issue, labels)
             if issue.state == "closed":  # type: ignore
@@ -259,6 +279,10 @@ def main():
         token,
         env_vars.ghe,
     )
+    enable_mentor_count = env_vars.enable_mentor_count
+    min_mentor_count = int(env_vars.min_mentor_comments)
+    max_comments_eval = int(env_vars.max_comments_eval)
+    heavily_involved_cutoff = int(env_vars.heavily_involved_cutoff)
 
     # Get the repository owner and name from the search query
     owner = get_owner(search_query)
@@ -283,13 +307,13 @@ def main():
         issues = get_discussions(token, search_query)
         if len(issues) <= 0:
             print("No discussions found")
-            write_to_markdown(None, None, None, None, None, None, None)
+            write_to_markdown(None, None, None, None, None, None, None, None)
             return
     else:
         issues = search_issues(search_query, github_connection)
         if len(issues) <= 0:
             print("No issues found")
-            write_to_markdown(None, None, None, None, None, None, None)
+            write_to_markdown(None, None, None, None, None, None, None, None)
             return
 
     # Get all the metrics
@@ -298,6 +322,8 @@ def main():
         discussions="type:discussions" in search_query,
         labels=labels,
         ignore_users=ignore_users,
+        max_comments_to_eval=max_comments_eval,
+        heavily_involved=heavily_involved_cutoff,
     )
 
     stats_time_to_first_response = get_stats_time_to_first_response(issues_with_metrics)
@@ -307,6 +333,10 @@ def main():
 
     stats_time_to_answer = get_stats_time_to_answer(issues_with_metrics)
 
+    num_mentor_count = 0
+    if enable_mentor_count == "TRUE":
+        num_mentor_count = get_mentor_count(issues_with_metrics, min_mentor_count)
+
     # Get stats describing the time in label for each label and store it in a dictionary
     # where the key is the label and the value is the average time
     stats_time_in_labels = get_stats_time_in_labels(issues_with_metrics, labels)
@@ -320,6 +350,7 @@ def main():
         stats_time_in_labels,
         num_issues_open,
         num_issues_closed,
+        num_mentor_count,
         search_query,
     )
     write_to_markdown(
@@ -330,6 +361,7 @@ def main():
         stats_time_in_labels,
         num_issues_open,
         num_issues_closed,
+        num_mentor_count,
         labels,
         search_query,
     )

json_writer.py

@@ -30,6 +30,7 @@ def write_to_json(
     stats_time_in_labels: Union[dict[str, dict[str, timedelta]], None],
     num_issues_opened: Union[int, None],
     num_issues_closed: Union[int, None],
+    num_mentor_count: Union[int, None],
     search_query: str,
 ) -> str:
     """
@@ -42,6 +43,7 @@ def write_to_json(
         "average_time_to_answer": "1 day, 0:00:00",
         "num_items_opened": 2,
         "num_items_closed": 1,
+        "num_mentor_count": 5,
         "total_item_count": 2,
         "issues": [
             {
@@ -129,6 +131,7 @@ def write_to_json(
         "90_percentile_time_in_labels": p90_time_in_labels,
         "num_items_opened": num_issues_opened,
         "num_items_closed": num_issues_closed,
+        "num_mentor_count": num_mentor_count,
         "total_item_count": len(issues_with_metrics),
     }
 

markdown_writer.py

@@ -13,6 +13,7 @@
         average_time_to_answer: timedelta,
         num_issues_opened: int,
         num_issues_closed: int,
+        num_mentor_count: int,
         file: file object = None
     ) -> None:
         Write the issues with metrics to a markdown file.
@@ -79,6 +80,7 @@ def write_to_markdown(
     average_time_in_labels: Union[dict, None],
     num_issues_opened: Union[int, None],
     num_issues_closed: Union[int, None],
+    num_mentor_count: Union[int, None],
     labels=None,
     search_query=None,
     hide_label_metrics=False,
@@ -95,7 +97,8 @@ def write_to_markdown(
         file (file object, optional): The file object to write to. If not provided,
             a file named "issue_metrics.md" will be created.
         num_issues_opened (int): The Number of items that remain opened.
-        num_issues_closed (int): The number of issues that were closed.
+        num_issues_closed (int): The number of issues that were closedi.
+        num_mentor_count (int): The number of very active commentors.
         labels (List[str]): A list of the labels that are used in the issues.
         search_query (str): The search query used to find the issues.
         hide_label_metrics (bool): Represents whether the user has chosen to hide label metrics in the output
@@ -127,6 +130,7 @@ def write_to_markdown(
             average_time_in_labels,
             num_issues_opened,
             num_issues_closed,
+            num_mentor_count,
             labels,
             columns,
             file,
@@ -184,6 +188,7 @@ def write_overall_metrics_tables(
     stats_time_in_labels,
     num_issues_opened,
     num_issues_closed,
+    num_mentor_count,
     labels,
     columns,
     file,
@@ -246,4 +251,5 @@ def write_overall_metrics_tables(
     file.write("| --- | ---: |\n")
     file.write(f"| Number of items that remain open | {num_issues_opened} |\n")
     file.write(f"| Number of items closed | {num_issues_closed} |\n")
+    file.write(f"| Number of most active mentors | {num_mentor_count} |\n")
     file.write(f"| Total number of items created | {len(issues_with_metrics)} |\n\n")