[workflow] added discussion stats to community report (#2572)

* [workflow] added discussion stats to community report

* polish code

.github/workflows/report_leaderboard_to_lark.yml

@@ -25,5 +25,5 @@ jobs:
       env:
         LARK_APP_ID: ${{ secrets.LARK_LEADERBOARD_APP_ID }}
         LARK_APP_SECRET: ${{ secrets.LARK_LEADERBOARD_APP_SECRET }}
-        LARK_WEBHOOK_URL: ${{ secrets.LARK_LEADERBOARD_WEBHOOK_URL }}
+        LARK_WEBHOOK_URL: ${{ secrets.LARK_NOTIFICATION_WEBHOOK_URL }}
         GITHUB_TOKEN: ${{ github.token }}

.github/workflows/scripts/generate_leaderboard_and_send_to_lark.py

 import os
 from dataclasses import dataclass
 from datetime import datetime, timedelta
+from typing import Any, Dict, List
 
 import matplotlib.pyplot as plt
 import pytz
@@ -11,16 +12,38 @@ from requests_toolbelt import MultipartEncoder
 
 @dataclass
 class Contributor:
+    """
+    Dataclass for a github contributor.
+
+    Args:
+        name (str): name of the contributor
+        num_commits_this_week (int): number of commits made within one week
+    """
     name: str
     num_commits_this_week: int
 
 
-def generate_user_engagement_leaderboard_image(github_token, output_path):
-    # request to the Github API to get the users who have replied the most in the last 7 days
-    now = datetime.utcnow()
-    start_datetime = now - timedelta(days=7)
-    start_datetime_str = start_datetime.strftime("%Y-%m-%dT%H:%M:%SZ")
+def plot_bar_chart(x: List[Any], y: List[Any], xlabel: str, ylabel: str, title: str, output_path: str) -> None:
+    """
+    This function is a utility to plot the bar charts.
+    """
+    plt.clf()
+    seaborn.color_palette()
+    fig = seaborn.barplot(x=x, y=y)
+    fig.set(xlabel=xlabel, ylabel=ylabel, title=title)
+    seaborn.despine()
+    plt.tight_layout()
+    plt.savefig(output_path, dpi=1200)
+
+
+def get_issue_pull_request_comments(github_token: str, since: str) -> Dict[str, int]:
+    """
+    Retrive the issue/PR comments made by our members in the last 7 days.
 
+    Args:
+        github_token (str): GitHub access token for API calls
+        since (str): the path parameter required by GitHub Restful APIs, in the format of YYYY-MM-DDTHH:MM:SSZ
+    """
     # prepare header
     headers = {
         'Authorization': f'Bearer {github_token}',
@@ -33,7 +56,7 @@ def generate_user_engagement_leaderboard_image(github_token, output_path):
     # do pagination to the API
     page = 1
     while True:
-        comment_api = f'https://api.github.com/repos/hpcaitech/ColossalAI/issues/comments?since={start_datetime_str}&page={page}'
+        comment_api = f'https://api.github.com/repos/hpcaitech/ColossalAI/issues/comments?since={since}&page={page}'
         comment_response = requests.get(comment_api, headers=headers).json()
 
         if len(comment_response) == 0:
@@ -61,67 +84,301 @@ def generate_user_engagement_leaderboard_image(github_token, output_path):
                     else:
                         user_engagement_count[member_name] = 1
             page += 1
+    return user_engagement_count
 
-    # plot the leaderboard
-    x = []
-    y = []
 
-    for name, count in user_engagement_count.items():
-        x.append(count)
-        y.append(name)
-    xticks = [str(v) for v in range(1, max(x) + 1)]
-    seaborn.color_palette()
-    fig = seaborn.barplot(x=x, y=y)
-    fig.set(xlabel=f"Number of Comments made (since {start_datetime})",
-            ylabel="Member",
-            title='Active User Engagement Leaderboard')
-    seaborn.despine()
-    plt.tight_layout()
-    plt.savefig(output_path, dpi=1200)
+def get_discussion_comments(github_token, since) -> Dict[str, int]:
+    """
+    Retrive the discussion comments made by our members in the last 7 days.
+    This is only available via the GitHub GraphQL API.
+
+    Args:
+        github_token (str): GitHub access token for API calls
+        since (Datetime): the query parameter to determine whether the comment is made this week
+    """
+
+    # use graphql to get the discussions updated in the last 7 days
+    def _generate_discussion_query(num, cursor: str = None):
+        if cursor is None:
+            offset_str = ""
+        else:
+            offset_str = f", after: \"{cursor}\""
+        query = f"""
+        {{
+            repository(owner: "hpcaitech", name: "ColossalAI"){{
+                discussions(first: {num} {offset_str}){{
+                    edges {{
+                        cursor
+                        node{{
+                            title
+                            author{{
+                                login
+                            }}
+                            number
+                            authorAssociation
+                            updatedAt
+                        }}
+                    }}
+                }}
+            }}
+        }}
+        """
+        return query
+
+    def _generate_comment_reply_count_for_discussion(discussion_number, num, cursor: str = None):
+        # here we assume that each comment will not have more than 100 replies for simplicity
+        # otherwise, we have to go through pagination for both comment and reply
+        if cursor is None:
+            offset_str = ""
+        else:
+            offset_str = f", before: \"{cursor}\""
+        query = f"""
+        {{
+            repository(owner: "hpcaitech", name: "ColossalAI"){{
+                discussion(number: {discussion_number}){{
+                    title
+                    comments(last: {num} {offset_str}){{
+                        edges{{
+                            cursor
+                            node {{
+                                author{{
+                                    login
+                                }}
+                                updatedAt
+                                authorAssociation
+                                replies (last: 100) {{
+                                edges {{
+                                    node {{
+                                        author {{
+                                            login
+                                        }}
+                                        updatedAt
+                                        authorAssociation
+                                        }}
+                                    }}
+                                }}
+                            }}
+                        }}
+                    }}
+                }}
+            }}
+        }}
+        """
+        return query
+
+    # a utility function to make call to Github GraphQL API
+    def _call_graphql_api(query):
+        headers = {"Authorization": f"Bearer {github_token}"}
+        json_data = {'query': query}
+        response = requests.post('https://api.github.com/graphql', json=json_data, headers=headers)
+        data = response.json()
+        return data
+
+    # get the discussion numbers updated in the last 7 days
+    discussion_numbers = []
+    num_per_request = 10
+    cursor = None
+    while True:
+        query = _generate_discussion_query(num_per_request, cursor)
+        data = _call_graphql_api(query)
+        found_discussion_out_of_time_range = False
+
+        edges = data['data']['repository']['discussions']['edges']
+        if len(edges) == 0:
+            break
+        else:
+            # keep the discussion whose author is not a member
+            for edge in edges:
+                # print the discussion title
+                discussion = edge['node']
+
+                discussion_updated_at = datetime.strptime(discussion['updatedAt'], "%Y-%m-%dT%H:%M:%SZ")
+                # check if the updatedAt is within the last 7 days
+                # if yes, add it to dicussion_numbers
+                if discussion_updated_at > since:
+                    if discussion['authorAssociation'] != 'MEMBER':
+                        discussion_numbers.append(discussion['number'])
+                else:
+                    found_discussion_out_of_time_range = True
+
+        if found_discussion_out_of_time_range:
+            break
+        else:
+            # update cursor
+            cursor = edges[-1]['cursor']
+
+    # get the dicussion comments and replies made by our member
+    user_engagement_count = {}
+    for dicussion_number in discussion_numbers:
+        cursor = None
+        num_per_request = 10
+
+        while True:
+            query = _generate_comment_reply_count_for_discussion(dicussion_number, num_per_request, cursor)
+            data = _call_graphql_api(query)
+
+            # get the comments
+            edges = data['data']['repository']['discussion']['comments']['edges']
+
+            # update the cursor
+            if len(edges) == 0:
+                break
+            else:
+                # update cursor for pagination
+                cursor = edges[-1]['cursor']
+
+                for edge in edges:
+                    comment = edge['node']
+                    if comment['authorAssociation'] == 'MEMBER':
+                        # check if the updatedAt is within the last 7 days
+                        # if yes, add it to user_engagement_count
+                        comment_updated_at = datetime.strptime(comment['updatedAt'], "%Y-%m-%dT%H:%M:%SZ")
+                        if comment_updated_at > since:
+                            member_name = comment['author']['login']
+                            if member_name in user_engagement_count:
+                                user_engagement_count[member_name] += 1
+                            else:
+                                user_engagement_count[member_name] = 1
+
+                    # get the replies
+                    reply_edges = comment['replies']['edges']
+                    if len(reply_edges) == 0:
+                        continue
+                    else:
+                        for reply_edge in reply_edges:
+                            reply = reply_edge['node']
+                            if reply['authorAssociation'] == 'MEMBER':
+                                # check if the updatedAt is within the last 7 days
+                                # if yes, add it to dicussion_numbers
+                                reply_updated_at = datetime.strptime(reply['updatedAt'], "%Y-%m-%dT%H:%M:%SZ")
+                                if reply_updated_at > since:
+                                    member_name = reply['author']['login']
+                                    if member_name in user_engagement_count:
+                                        user_engagement_count[member_name] += 1
+                                    else:
+                                        user_engagement_count[member_name] = 1
+    return user_engagement_count
+
+
+def generate_user_engagement_leaderboard_image(github_token: str, output_path: str) -> bool:
+    """
+    Generate the user engagement leaderboard image for stats within the last 7 days
+
+    Args:
+        github_token (str): GitHub access token for API calls
+        output_path (str): the path to save the image
+    """
+
+    # request to the Github API to get the users who have replied the most in the last 7 days
+    now = datetime.utcnow()
+    start_datetime = now - timedelta(days=7)
+    start_datetime_str = start_datetime.strftime("%Y-%m-%dT%H:%M:%SZ")
 
+    # get the issue/PR comments and discussion comment count
+    issue_pr_engagement_count = get_issue_pull_request_comments(github_token=github_token, since=start_datetime_str)
+    discussion_engagement_count = get_discussion_comments(github_token=github_token, since=start_datetime)
+    total_engagement_count = {}
 
-def generate_contributor_leaderboard_image(github_token, output_path):
+    # update the total engagement count
+    total_engagement_count.update(issue_pr_engagement_count)
+    for name, count in discussion_engagement_count.items():
+        if name in total_engagement_count:
+            total_engagement_count[name] += count
+        else:
+            total_engagement_count[name] = count
+
+    # prepare the data for plotting
+    x = []
+    y = []
+
+    if len(total_engagement_count) > 0:
+        for name, count in total_engagement_count.items():
+            x.append(count)
+            y.append(name)
+
+        # use Shanghai time to display on the image
+        start_datetime_str = datetime.now(pytz.timezone('Asia/Shanghai')).strftime("%Y-%m-%dT%H:%M:%SZ")
+
+        # plot the leaderboard
+        xlabel = f"Number of Comments made (since {start_datetime_str})"
+        ylabel = "Member"
+        title = 'Active User Engagement Leaderboard'
+        plot_bar_chart(x, y, xlabel=xlabel, ylabel=ylabel, title=title, output_path=output_path)
+        return True
+    else:
+        return False
+
+
+def generate_contributor_leaderboard_image(github_token, output_path) -> bool:
+    """
+    Generate the contributor leaderboard image for stats within the last 7 days
+
+    Args:
+        github_token (str): GitHub access token for API calls
+        output_path (str): the path to save the image
+    """
+    # request to the Github API to get the users who have contributed in the last 7 days
     URL = 'https://api.github.com/repos/hpcaitech/ColossalAI/stats/contributors'
     headers = {
         'Authorization': f'Bearer {github_token}',
         'Accept': 'application/vnd.github+json',
         'X-GitHub-Api-Version': '2022-11-28'
     }
-    response = requests.get(URL, headers=headers).json()
 
-    contributor_list = []
+    while True:
+        response = requests.get(URL, headers=headers).json()
 
-    # convert unix timestamp to Beijing datetime
-    start_timestamp = response[0]['weeks'][-1]['w']
-    start_datetime = datetime.fromtimestamp(start_timestamp, tz=pytz.timezone('Asia/Shanghai'))
+        if len(response) != 0:
+            # sometimes the Github API returns empty response for unknown reason
+            # request again if the response is empty
+            break
+
+    contributor_list = []
 
     # get number of commits for each contributor
+    start_timestamp = None
     for item in response:
         num_commits_this_week = item['weeks'][-1]['c']
         name = item['author']['login']
         contributor = Contributor(name=name, num_commits_this_week=num_commits_this_week)
         contributor_list.append(contributor)
 
+        # update start_timestamp
+        start_timestamp = item['weeks'][-1]['w']
+
+    # convert unix timestamp to Beijing datetime
+    start_datetime = datetime.fromtimestamp(start_timestamp, tz=pytz.timezone('Asia/Shanghai'))
+    start_datetime_str = start_datetime.strftime("%Y-%m-%dT%H:%M:%SZ")
+
     # sort by number of commits
     contributor_list.sort(key=lambda x: x.num_commits_this_week, reverse=True)
 
     # remove contributors who has zero commits
     contributor_list = [x for x in contributor_list if x.num_commits_this_week > 0]
 
-    # plot
-    seaborn.color_palette()
+    # prepare the data for plotting
     x = [x.num_commits_this_week for x in contributor_list]
     y = [x.name for x in contributor_list]
-    fig = seaborn.barplot(x=x, y=y)
-    fig.set(xlabel=f"Number of Commits (since {start_datetime})",
-            ylabel="Contributor",
-            title='Active Contributor Leaderboard')
-    seaborn.despine()
-    plt.tight_layout()
-    plt.savefig(output_path, dpi=1200)
 
-
-def upload_image_to_lark(lark_tenant_token, image_path):
+    # plot
+    if len(x) > 0:
+        xlabel = f"Number of Commits (since {start_datetime_str})"
+        ylabel = "Contributor"
+        title = 'Active Contributor Leaderboard'
+        plot_bar_chart(x, y, xlabel=xlabel, ylabel=ylabel, title=title, output_path=output_path)
+        return True
+    else:
+        return False
+
+
+def upload_image_to_lark(lark_tenant_token: str, image_path: str) -> str:
+    """
+    Upload image to Lark and return the image key
+
+    Args:
+        lark_tenant_token (str): Lark tenant access token
+        image_path (str): the path to the image to be uploaded
+    """
     url = "https://open.feishu.cn/open-apis/im/v1/images"
     form = {'image_type': 'message', 'image': (open(image_path, 'rb'))}    # 需要替换具体的path
     multi_form = MultipartEncoder(form)
@@ -133,19 +390,40 @@ def upload_image_to_lark(lark_tenant_token, image_path):
     return response['data']['image_key']
 
 
-def generate_lark_tenant_access_token(app_id, app_secret):
+def generate_lark_tenant_access_token(app_id: str, app_secret: str) -> str:
+    """
+    Generate Lark tenant access token.
+
+    Args:
+        app_id (str): Lark app id
+        app_secret (str): Lark app secret
+    """
     url = 'https://open.feishu.cn/open-apis/auth/v3/tenant_access_token/internal'
     data = {'app_id': app_id, 'app_secret': app_secret}
     response = requests.post(url, json=data).json()
     return response['tenant_access_token']
 
 
-def send_image_to_lark(image_key, webhook_url):
+def send_image_to_lark(image_key: str, webhook_url: str) -> None:
+    """
+    Send image to Lark.
+
+    Args:
+        image_key (str): the image key returned by Lark
+        webhook_url (str): the webhook url to send the image
+    """
     data = {"msg_type": "image", "content": {"image_key": image_key}}
     requests.post(webhook_url, json=data)
 
 
-def send_message_to_lark(message, webhook_url):
+def send_message_to_lark(message: str, webhook_url: str):
+    """
+    Send message to Lark.
+
+    Args:
+        message (str): the message to be sent
+        webhook_url (str): the webhook url to send the message
+    """
     data = {"msg_type": "text", "content": {"text": message}}
     requests.post(webhook_url, json=data)
 
@@ -156,8 +434,8 @@ if __name__ == '__main__':
     USER_ENGAGEMENT_IMAGE_PATH = 'engagement_leaderboard.png'
 
     # generate images
-    # generate_contributor_leaderboard_image(GITHUB_TOKEN, CONTRIBUTOR_IMAGE_PATH)
-    generate_user_engagement_leaderboard_image(GITHUB_TOKEN, USER_ENGAGEMENT_IMAGE_PATH)
+    contrib_success = generate_contributor_leaderboard_image(GITHUB_TOKEN, CONTRIBUTOR_IMAGE_PATH)
+    engagement_success = generate_user_engagement_leaderboard_image(GITHUB_TOKEN, USER_ENGAGEMENT_IMAGE_PATH)
 
     # upload images
     APP_ID = os.environ['LARK_APP_ID']
@@ -166,11 +444,27 @@ if __name__ == '__main__':
     contributor_image_key = upload_image_to_lark(LARK_TENANT_TOKEN, CONTRIBUTOR_IMAGE_PATH)
     user_engagement_image_key = upload_image_to_lark(LARK_TENANT_TOKEN, USER_ENGAGEMENT_IMAGE_PATH)
 
-    # send contributor image to lark
+    # send message to lark
     LARK_WEBHOOK_URL = os.environ['LARK_WEBHOOK_URL']
-    send_message_to_lark("本周的开发者贡献榜单出炉啦！", LARK_WEBHOOK_URL)
-    send_image_to_lark(contributor_image_key, LARK_WEBHOOK_URL)
+    message = """本周的社区榜单出炉啦！
+1. 开发贡献者榜单
+2. 用户互动榜单
+
+注：
+- 开发贡献者测评标准为：本周由公司成员提交的commit次数
+- 用户互动榜单测评标准为：本周由公司成员在非成员创建的issue/PR/discussion中回复的次数
+"""
+
+    send_message_to_lark(message, LARK_WEBHOOK_URL)
+
+    # send contributor image to lark
+    if contrib_success:
+        send_image_to_lark(contributor_image_key, LARK_WEBHOOK_URL)
+    else:
+        send_message_to_lark("本周没有成员贡献commit，无榜单图片生成。", LARK_WEBHOOK_URL)
 
     # send user engagement image to lark
-    send_message_to_lark("本周的开源社区互动榜单出炉啦！", LARK_WEBHOOK_URL)
-    send_image_to_lark(user_engagement_image_key, LARK_WEBHOOK_URL)
+    if engagement_success:
+        send_image_to_lark(user_engagement_image_key, LARK_WEBHOOK_URL)
+    else:
+        send_message_to_lark("本周没有成员互动，无榜单图片生成。", LARK_WEBHOOK_URL)