mirror of https://github.com/hpcaitech/ColossalAI
[workflow] added discussion stats to community report (#2572)
* [workflow] added discussion stats to community report * polish codepull/2585/head
Frank Lee
GitHub
parent
b0c29d1b4c
commit
8af5a0799b
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@ -25,5 +25,5 @@ jobs:
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env:
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LARK_APP_ID: ${{ secrets.LARK_LEADERBOARD_APP_ID }}
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LARK_APP_SECRET: ${{ secrets.LARK_LEADERBOARD_APP_SECRET }}
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LARK_WEBHOOK_URL: ${{ secrets.LARK_LEADERBOARD_WEBHOOK_URL }}
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LARK_WEBHOOK_URL: ${{ secrets.LARK_NOTIFICATION_WEBHOOK_URL }}
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GITHUB_TOKEN: ${{ github.token }}
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@ -1,6 +1,7 @@
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import os
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from dataclasses import dataclass
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from datetime import datetime, timedelta
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from typing import Any, Dict, List
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import matplotlib.pyplot as plt
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import pytz
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@ -11,16 +12,38 @@ from requests_toolbelt import MultipartEncoder
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@dataclass
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class Contributor:
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"""
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Dataclass for a github contributor.
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Args:
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name (str): name of the contributor
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num_commits_this_week (int): number of commits made within one week
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"""
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name: str
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num_commits_this_week: int
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def generate_user_engagement_leaderboard_image(github_token, output_path):
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# request to the Github API to get the users who have replied the most in the last 7 days
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now = datetime.utcnow()
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start_datetime = now - timedelta(days=7)
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start_datetime_str = start_datetime.strftime("%Y-%m-%dT%H:%M:%SZ")
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def plot_bar_chart(x: List[Any], y: List[Any], xlabel: str, ylabel: str, title: str, output_path: str) -> None:
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"""
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This function is a utility to plot the bar charts.
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"""
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plt.clf()
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seaborn.color_palette()
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fig = seaborn.barplot(x=x, y=y)
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fig.set(xlabel=xlabel, ylabel=ylabel, title=title)
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seaborn.despine()
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plt.tight_layout()
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plt.savefig(output_path, dpi=1200)
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def get_issue_pull_request_comments(github_token: str, since: str) -> Dict[str, int]:
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"""
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Retrive the issue/PR comments made by our members in the last 7 days.
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Args:
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github_token (str): GitHub access token for API calls
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since (str): the path parameter required by GitHub Restful APIs, in the format of YYYY-MM-DDTHH:MM:SSZ
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"""
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# prepare header
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headers = {
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'Authorization': f'Bearer {github_token}',
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@ -33,7 +56,7 @@ def generate_user_engagement_leaderboard_image(github_token, output_path):
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# do pagination to the API
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page = 1
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while True:
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comment_api = f'https://api.github.com/repos/hpcaitech/ColossalAI/issues/comments?since={start_datetime_str}&page={page}'
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comment_api = f'https://api.github.com/repos/hpcaitech/ColossalAI/issues/comments?since={since}&page={page}'
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comment_response = requests.get(comment_api, headers=headers).json()
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if len(comment_response) == 0:
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@ -61,67 +84,301 @@ def generate_user_engagement_leaderboard_image(github_token, output_path):
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else:
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user_engagement_count[member_name] = 1
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page += 1
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return user_engagement_count
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# plot the leaderboard
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def get_discussion_comments(github_token, since) -> Dict[str, int]:
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"""
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Retrive the discussion comments made by our members in the last 7 days.
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This is only available via the GitHub GraphQL API.
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Args:
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github_token (str): GitHub access token for API calls
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since (Datetime): the query parameter to determine whether the comment is made this week
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"""
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# use graphql to get the discussions updated in the last 7 days
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def _generate_discussion_query(num, cursor: str = None):
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if cursor is None:
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offset_str = ""
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else:
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offset_str = f", after: \"{cursor}\""
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query = f"""
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{{
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repository(owner: "hpcaitech", name: "ColossalAI"){{
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discussions(first: {num} {offset_str}){{
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edges {{
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cursor
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node{{
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title
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author{{
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login
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}}
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number
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authorAssociation
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updatedAt
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}}
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}}
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}}
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}}
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}}
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"""
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return query
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def _generate_comment_reply_count_for_discussion(discussion_number, num, cursor: str = None):
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# here we assume that each comment will not have more than 100 replies for simplicity
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# otherwise, we have to go through pagination for both comment and reply
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if cursor is None:
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offset_str = ""
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else:
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offset_str = f", before: \"{cursor}\""
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query = f"""
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{{
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repository(owner: "hpcaitech", name: "ColossalAI"){{
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discussion(number: {discussion_number}){{
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title
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comments(last: {num} {offset_str}){{
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edges{{
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cursor
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node {{
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author{{
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login
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}}
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updatedAt
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authorAssociation
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replies (last: 100) {{
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edges {{
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node {{
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author {{
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login
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}}
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updatedAt
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authorAssociation
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}}
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}}
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}}
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}}
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}}
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}}
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}}
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}}
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}}
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"""
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return query
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# a utility function to make call to Github GraphQL API
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def _call_graphql_api(query):
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headers = {"Authorization": f"Bearer {github_token}"}
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json_data = {'query': query}
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response = requests.post('https://api.github.com/graphql', json=json_data, headers=headers)
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data = response.json()
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return data
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# get the discussion numbers updated in the last 7 days
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discussion_numbers = []
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num_per_request = 10
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cursor = None
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while True:
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query = _generate_discussion_query(num_per_request, cursor)
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data = _call_graphql_api(query)
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found_discussion_out_of_time_range = False
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edges = data['data']['repository']['discussions']['edges']
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if len(edges) == 0:
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break
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else:
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# keep the discussion whose author is not a member
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for edge in edges:
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# print the discussion title
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discussion = edge['node']
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discussion_updated_at = datetime.strptime(discussion['updatedAt'], "%Y-%m-%dT%H:%M:%SZ")
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# check if the updatedAt is within the last 7 days
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# if yes, add it to dicussion_numbers
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if discussion_updated_at > since:
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if discussion['authorAssociation'] != 'MEMBER':
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discussion_numbers.append(discussion['number'])
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else:
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found_discussion_out_of_time_range = True
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if found_discussion_out_of_time_range:
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break
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else:
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# update cursor
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cursor = edges[-1]['cursor']
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# get the dicussion comments and replies made by our member
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user_engagement_count = {}
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for dicussion_number in discussion_numbers:
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cursor = None
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num_per_request = 10
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while True:
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query = _generate_comment_reply_count_for_discussion(dicussion_number, num_per_request, cursor)
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data = _call_graphql_api(query)
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# get the comments
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edges = data['data']['repository']['discussion']['comments']['edges']
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# update the cursor
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if len(edges) == 0:
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break
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else:
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# update cursor for pagination
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cursor = edges[-1]['cursor']
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for edge in edges:
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comment = edge['node']
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if comment['authorAssociation'] == 'MEMBER':
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# check if the updatedAt is within the last 7 days
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# if yes, add it to user_engagement_count
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comment_updated_at = datetime.strptime(comment['updatedAt'], "%Y-%m-%dT%H:%M:%SZ")
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if comment_updated_at > since:
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member_name = comment['author']['login']
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if member_name in user_engagement_count:
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user_engagement_count[member_name] += 1
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else:
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user_engagement_count[member_name] = 1
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# get the replies
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reply_edges = comment['replies']['edges']
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if len(reply_edges) == 0:
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continue
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else:
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for reply_edge in reply_edges:
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reply = reply_edge['node']
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if reply['authorAssociation'] == 'MEMBER':
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# check if the updatedAt is within the last 7 days
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# if yes, add it to dicussion_numbers
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reply_updated_at = datetime.strptime(reply['updatedAt'], "%Y-%m-%dT%H:%M:%SZ")
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if reply_updated_at > since:
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member_name = reply['author']['login']
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if member_name in user_engagement_count:
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user_engagement_count[member_name] += 1
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else:
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user_engagement_count[member_name] = 1
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return user_engagement_count
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def generate_user_engagement_leaderboard_image(github_token: str, output_path: str) -> bool:
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"""
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Generate the user engagement leaderboard image for stats within the last 7 days
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Args:
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github_token (str): GitHub access token for API calls
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output_path (str): the path to save the image
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"""
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# request to the Github API to get the users who have replied the most in the last 7 days
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now = datetime.utcnow()
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start_datetime = now - timedelta(days=7)
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start_datetime_str = start_datetime.strftime("%Y-%m-%dT%H:%M:%SZ")
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# get the issue/PR comments and discussion comment count
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issue_pr_engagement_count = get_issue_pull_request_comments(github_token=github_token, since=start_datetime_str)
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discussion_engagement_count = get_discussion_comments(github_token=github_token, since=start_datetime)
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total_engagement_count = {}
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# update the total engagement count
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total_engagement_count.update(issue_pr_engagement_count)
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for name, count in discussion_engagement_count.items():
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if name in total_engagement_count:
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total_engagement_count[name] += count
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else:
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total_engagement_count[name] = count
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# prepare the data for plotting
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x = []
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y = []
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for name, count in user_engagement_count.items():
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x.append(count)
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y.append(name)
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xticks = [str(v) for v in range(1, max(x) + 1)]
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seaborn.color_palette()
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fig = seaborn.barplot(x=x, y=y)
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fig.set(xlabel=f"Number of Comments made (since {start_datetime})",
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ylabel="Member",
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title='Active User Engagement Leaderboard')
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seaborn.despine()
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plt.tight_layout()
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plt.savefig(output_path, dpi=1200)
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if len(total_engagement_count) > 0:
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for name, count in total_engagement_count.items():
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x.append(count)
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y.append(name)
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# use Shanghai time to display on the image
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start_datetime_str = datetime.now(pytz.timezone('Asia/Shanghai')).strftime("%Y-%m-%dT%H:%M:%SZ")
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# plot the leaderboard
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xlabel = f"Number of Comments made (since {start_datetime_str})"
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ylabel = "Member"
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title = 'Active User Engagement Leaderboard'
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plot_bar_chart(x, y, xlabel=xlabel, ylabel=ylabel, title=title, output_path=output_path)
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return True
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else:
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return False
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def generate_contributor_leaderboard_image(github_token, output_path):
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def generate_contributor_leaderboard_image(github_token, output_path) -> bool:
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"""
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Generate the contributor leaderboard image for stats within the last 7 days
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Args:
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github_token (str): GitHub access token for API calls
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output_path (str): the path to save the image
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"""
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# request to the Github API to get the users who have contributed in the last 7 days
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URL = 'https://api.github.com/repos/hpcaitech/ColossalAI/stats/contributors'
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headers = {
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'Authorization': f'Bearer {github_token}',
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'Accept': 'application/vnd.github+json',
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'X-GitHub-Api-Version': '2022-11-28'
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}
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response = requests.get(URL, headers=headers).json()
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while True:
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response = requests.get(URL, headers=headers).json()
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if len(response) != 0:
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# sometimes the Github API returns empty response for unknown reason
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# request again if the response is empty
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break
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contributor_list = []
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# convert unix timestamp to Beijing datetime
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start_timestamp = response[0]['weeks'][-1]['w']
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start_datetime = datetime.fromtimestamp(start_timestamp, tz=pytz.timezone('Asia/Shanghai'))
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# get number of commits for each contributor
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start_timestamp = None
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for item in response:
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num_commits_this_week = item['weeks'][-1]['c']
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name = item['author']['login']
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contributor = Contributor(name=name, num_commits_this_week=num_commits_this_week)
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contributor_list.append(contributor)
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# update start_timestamp
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start_timestamp = item['weeks'][-1]['w']
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# convert unix timestamp to Beijing datetime
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start_datetime = datetime.fromtimestamp(start_timestamp, tz=pytz.timezone('Asia/Shanghai'))
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start_datetime_str = start_datetime.strftime("%Y-%m-%dT%H:%M:%SZ")
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# sort by number of commits
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contributor_list.sort(key=lambda x: x.num_commits_this_week, reverse=True)
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# remove contributors who has zero commits
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contributor_list = [x for x in contributor_list if x.num_commits_this_week > 0]
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# plot
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seaborn.color_palette()
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# prepare the data for plotting
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x = [x.num_commits_this_week for x in contributor_list]
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y = [x.name for x in contributor_list]
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fig = seaborn.barplot(x=x, y=y)
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fig.set(xlabel=f"Number of Commits (since {start_datetime})",
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ylabel="Contributor",
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title='Active Contributor Leaderboard')
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seaborn.despine()
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plt.tight_layout()
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plt.savefig(output_path, dpi=1200)
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# plot
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if len(x) > 0:
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xlabel = f"Number of Commits (since {start_datetime_str})"
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ylabel = "Contributor"
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title = 'Active Contributor Leaderboard'
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plot_bar_chart(x, y, xlabel=xlabel, ylabel=ylabel, title=title, output_path=output_path)
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return True
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else:
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return False
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def upload_image_to_lark(lark_tenant_token, image_path):
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def upload_image_to_lark(lark_tenant_token: str, image_path: str) -> str:
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"""
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Upload image to Lark and return the image key
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Args:
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lark_tenant_token (str): Lark tenant access token
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image_path (str): the path to the image to be uploaded
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"""
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url = "https://open.feishu.cn/open-apis/im/v1/images"
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form = {'image_type': 'message', 'image': (open(image_path, 'rb'))} # 需要替换具体的path
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multi_form = MultipartEncoder(form)
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@ -133,19 +390,40 @@ def upload_image_to_lark(lark_tenant_token, image_path):
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return response['data']['image_key']
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def generate_lark_tenant_access_token(app_id, app_secret):
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def generate_lark_tenant_access_token(app_id: str, app_secret: str) -> str:
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"""
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Generate Lark tenant access token.
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Args:
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app_id (str): Lark app id
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app_secret (str): Lark app secret
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"""
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url = 'https://open.feishu.cn/open-apis/auth/v3/tenant_access_token/internal'
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data = {'app_id': app_id, 'app_secret': app_secret}
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response = requests.post(url, json=data).json()
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return response['tenant_access_token']
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def send_image_to_lark(image_key, webhook_url):
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def send_image_to_lark(image_key: str, webhook_url: str) -> None:
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"""
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Send image to Lark.
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Args:
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image_key (str): the image key returned by Lark
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webhook_url (str): the webhook url to send the image
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"""
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data = {"msg_type": "image", "content": {"image_key": image_key}}
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requests.post(webhook_url, json=data)
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def send_message_to_lark(message, webhook_url):
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def send_message_to_lark(message: str, webhook_url: str):
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"""
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Send message to Lark.
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Args:
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message (str): the message to be sent
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webhook_url (str): the webhook url to send the message
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"""
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data = {"msg_type": "text", "content": {"text": message}}
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requests.post(webhook_url, json=data)
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@ -156,8 +434,8 @@ if __name__ == '__main__':
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USER_ENGAGEMENT_IMAGE_PATH = 'engagement_leaderboard.png'
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# generate images
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# generate_contributor_leaderboard_image(GITHUB_TOKEN, CONTRIBUTOR_IMAGE_PATH)
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generate_user_engagement_leaderboard_image(GITHUB_TOKEN, USER_ENGAGEMENT_IMAGE_PATH)
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contrib_success = generate_contributor_leaderboard_image(GITHUB_TOKEN, CONTRIBUTOR_IMAGE_PATH)
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engagement_success = generate_user_engagement_leaderboard_image(GITHUB_TOKEN, USER_ENGAGEMENT_IMAGE_PATH)
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# upload images
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APP_ID = os.environ['LARK_APP_ID']
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@ -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)
|
||||
|
|
|
|||
Loading…
Reference in New Issue