398 lines
20 KiB
Python
398 lines
20 KiB
Python
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from pymongo import MongoClient
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from datetime import datetime
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import matplotlib.pyplot as plt
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import re
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import matplotlib
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import numpy as np
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#计算时间差值，输出为秒数
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def get_time_difference(t_old,t_new):
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time_diff_seconds = (t_new-t_old).total_seconds()
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return time_diff_seconds
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#计算列表元素时间差
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def get_time_difference_list(time_list):
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interval = list()
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for i in range(1,len(time_list)):
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interval.append(get_time_difference(time_list[i-1],time_list[i]))
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return interval
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#连接数据库
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client = MongoClient('localhost', 27017)
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db = client['numpy_db']
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collection1 = db['issue_pr']
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collection2 = db['issue_timeline_new']
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#已关闭的issue信息
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issue_data = collection1.find({"state":"closed", "pull_request": {"$exists": False}},
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{ "number": 1, "created_at": 1, "closed_at":1,"body":1,"title":1, "_id": 0 }
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).sort([("number", 1)]).batch_size(10)
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#数据初始化
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first_interval = [0]*30
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last_interval = [0]*30
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all_interval = [0]*30
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first_all = [0]*30
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last_all = [0]*30
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# count = [0]*30
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time = [0]*30
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mentioned_without_time = 0
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mentioned_without_count = 0
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assigned_without_time = 0
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assigned_without_count = 0
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cross_referenced_without_time = 0
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cross_referenced_without_count = 0
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labeled_without_time = 0
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labeled_without_count = 0
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link_without_time = 0
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link_without_count = 0
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for i in range(1,21):
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locals()['x_'+str(i)] = list()
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locals()['y_'+str(i)] = list()
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i = 0
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for issue in issue_data:
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print(issue['number'], end=' ')
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#获取五种事件类型的时间戳：@、assigned、labeled、link（cross-reference）
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mentioned_data = collection2.find(
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{ "event": "mentioned", "issue_number": issue['number']},
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{"created_at": 1, "_id": 0 }).sort([("created_at", 1)])
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mentioned_time = [datetime.strptime(event["created_at"], '%Y-%m-%dT%H:%M:%SZ') for event in mentioned_data]
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mentioned_time.sort()
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assigned_data = collection2.find(
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{ "event": "assigned", "issue_number": issue['number']},
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{"created_at": 1, "_id": 0 }).sort([("created_at", 1)])
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assigned_time = [datetime.strptime(event["created_at"], '%Y-%m-%dT%H:%M:%SZ') for event in assigned_data]
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assigned_time.sort()
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cross_referenced_data = collection2.find(
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{"event": "cross-referenced", "issue_number": issue['number']},
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{"created_at": 1, "_id": 0}).sort([("created_at", 1)])
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cross_referenced_time = [datetime.strptime(event["created_at"], '%Y-%m-%dT%H:%M:%SZ') for event in cross_referenced_data]
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cross_referenced_time.sort()
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labeled_data = collection2.find(
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{"event": "labeled", "issue_number": issue['number']},
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{"created_at": 1, "_id": 0}).sort([("created_at", 1)])
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labeled_time = [datetime.strptime(event["created_at"], '%Y-%m-%dT%H:%M:%SZ') for event in labeled_data]
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labeled_time.sort()
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commented_data = collection2.find(
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{"event": "commented", "issue_number": issue['number']},
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{"created_at": 1,"body":1, "_id": 0}).sort([("created_at", 1)])
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pattern = r'github.com/[a-zA-Z0-9-_.]+/[a-zA-Z0-9-_.]+/issues/[0-9]+|github.com/[a-zA-Z0-9-_.]+/[a-zA-Z0-9-_.]+/pull/[0-9]+'
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link_time = []
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for event in commented_data:
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num = len(re.findall(pattern,event['body']))
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for j in range(num):
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link_time.append(datetime.strptime(event["created_at"], '%Y-%m-%dT%H:%M:%SZ'))
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if issue['body']:
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for j in range(len(re.findall(pattern, issue['body']))):
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link_time.append(datetime.strptime(issue["created_at"], '%Y-%m-%dT%H:%M:%SZ'))
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if issue['title']:
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for j in range(len(re.findall(pattern, issue['title']))):
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link_time.append(datetime.strptime(issue["created_at"], '%Y-%m-%dT%H:%M:%SZ'))
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# link_time = [datetime.strptime(event["created_at"], '%Y-%m-%dT%H:%M:%SZ') for event in commented_data if re.findall(pattern,event['body'])]
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link_time.sort()
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#五种时间类型分别计算时间差，综合事件类型时间差
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mentioned_time.insert(0,datetime.strptime(issue["created_at"], '%Y-%m-%dT%H:%M:%SZ'))#添加issue创建、关闭的时间戳
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mentioned_time.append(datetime.strptime(issue["closed_at"], '%Y-%m-%dT%H:%M:%SZ'))
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for time in mentioned_time[0:-1]: #删除发生在issue关闭后的事件
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if get_time_difference(time,mentioned_time[-1])<0:
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mentioned_time.remove(time)
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mentioned_interval_list = get_time_difference_list(mentioned_time)
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if all(x < 10 for x in mentioned_interval_list): #删除机器人触发的事件
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continue
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assigned_time.insert(0,datetime.strptime(issue["created_at"], '%Y-%m-%dT%H:%M:%SZ')) #添加issue创建、关闭的时间戳
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assigned_time.append(datetime.strptime(issue["closed_at"], '%Y-%m-%dT%H:%M:%SZ'))
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for time in assigned_time[0:-1]: #删除发生在issue关闭后的事件
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if get_time_difference(time,assigned_time[-1])<0:
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assigned_time.remove(time)
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assigned_interval_list = get_time_difference_list(assigned_time)
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if all(x < 10 for x in assigned_interval_list): #删除机器人触发的事件
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continue
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cross_referenced_time.insert(0,datetime.strptime(issue["created_at"], '%Y-%m-%dT%H:%M:%SZ')) #添加issue创建、关闭的时间戳
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cross_referenced_time.append(datetime.strptime(issue["closed_at"], '%Y-%m-%dT%H:%M:%SZ'))
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for time in cross_referenced_time[0:-1]: #删除发生在issue关闭后的事件
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if get_time_difference(time,cross_referenced_time[-1])<0:
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cross_referenced_time.remove(time)
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cross_referenced_interval_list = get_time_difference_list(cross_referenced_time)
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if all(x < 10 for x in cross_referenced_interval_list): #删除机器人触发的事件
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continue
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labeled_time.insert(0,datetime.strptime(issue["created_at"], '%Y-%m-%dT%H:%M:%SZ')) #添加issue创建、关闭的时间戳
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labeled_time.append(datetime.strptime(issue["closed_at"], '%Y-%m-%dT%H:%M:%SZ'))
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for time in labeled_time[0:-1]: #删除发生在issue关闭后的事件
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if get_time_difference(time,labeled_time[-1])<0:
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labeled_time.remove(time)
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labeled_interval_list = get_time_difference_list(labeled_time)
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if all(x < 10 for x in labeled_interval_list): #删除机器人触发的事件
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continue
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link_time.insert(0,datetime.strptime(issue["created_at"], '%Y-%m-%dT%H:%M:%SZ')) #添加issue创建、关闭的时间戳
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link_time.append(datetime.strptime(issue["closed_at"], '%Y-%m-%dT%H:%M:%SZ'))
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for time in link_time[0:-1]: #删除发生在issue关闭后的事件
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if get_time_difference(time,link_time[-1])<0:
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link_time.remove(time)
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link_interval_list = get_time_difference_list(link_time)
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if all(x < 10 for x in link_interval_list): #删除机器人触发的事件
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continue
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if len(mentioned_interval_list) == 1:
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mentioned_without_time += mentioned_interval_list[0]
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mentioned_without_count += 1
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elif len(mentioned_interval_list) == 2:
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locals()['x_'+str(len(mentioned_interval_list)-1)].append(mentioned_interval_list[0]/3600/24)
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locals()['y_'+str(len(mentioned_interval_list)-1)].append(get_time_difference(mentioned_time[1],mentioned_time[-1])/3600/24)
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locals()['x_'+str(len(mentioned_interval_list))].append(mentioned_interval_list[0]/3600/24)
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locals()['y_' + str(len(mentioned_interval_list))].append(
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get_time_difference(mentioned_time[0], mentioned_time[-1]) / 3600 / 24)
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elif len(mentioned_interval_list) == 3:
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locals()['x_' + str(len(mentioned_interval_list))].append(mentioned_interval_list[0] / 3600 / 24)
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locals()['y_' + str(len(mentioned_interval_list))].append(
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get_time_difference(mentioned_time[1], mentioned_time[-1]) / 3600 / 24)
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locals()['x_' + str(len(mentioned_interval_list) + 1)].append(mentioned_interval_list[0] / 3600 / 24)
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locals()['y_' + str(len(mentioned_interval_list) + 1)].append(mentioned_interval_list[-1]/3600/24)
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if len(assigned_interval_list) == 1:
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assigned_without_time += assigned_interval_list[0]
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assigned_without_count += 1
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elif len(assigned_interval_list) == 2:
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locals()['x_'+str(len(assigned_interval_list)+3)].append(assigned_interval_list[0]/3600/24)
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locals()['y_'+str(len(assigned_interval_list)+3)].append(get_time_difference(assigned_time[1],assigned_time[-1])/3600/24)
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locals()['x_'+str(len(assigned_interval_list)+4)].append(assigned_interval_list[0]/3600/24)
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locals()['y_' + str(len(assigned_interval_list) + 4)].append(
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get_time_difference(assigned_time[0], assigned_time[-1]) / 3600 / 24)
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elif len(assigned_interval_list) == 3:
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locals()['x_' + str(len(assigned_interval_list) + 4)].append(assigned_interval_list[0] / 3600 / 24)
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locals()['y_' + str(len(assigned_interval_list) + 4)].append(
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get_time_difference(assigned_time[1], assigned_time[-1]) / 3600 / 24)
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locals()['x_' + str(len(assigned_interval_list) + 5)].append(assigned_interval_list[0] / 3600 / 24)
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locals()['y_' + str(len(assigned_interval_list) + 5)].append(assigned_interval_list[-1]/3600/24)
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if len(cross_referenced_interval_list) == 1:
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cross_referenced_without_time += cross_referenced_interval_list[0]
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cross_referenced_without_count += 1
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elif len(cross_referenced_interval_list) == 2:
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locals()['x_'+str(len(cross_referenced_interval_list)+7)].append(cross_referenced_interval_list[0]/3600/24)
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locals()['y_'+str(len(cross_referenced_interval_list)+7)].append(get_time_difference(cross_referenced_time[1],cross_referenced_time[-1])/3600/24)
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locals()['x_'+str(len(cross_referenced_interval_list)+8)].append(cross_referenced_interval_list[0]/3600/24)
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locals()['y_' + str(len(cross_referenced_interval_list) + 8)].append(
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get_time_difference(cross_referenced_time[0], cross_referenced_time[-1]) / 3600 / 24)
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elif len(cross_referenced_interval_list) == 3:
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locals()['x_' + str(len(cross_referenced_interval_list) + 8)].append(
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cross_referenced_interval_list[0] / 3600 / 24)
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locals()['y_' + str(len(cross_referenced_interval_list) + 8)].append(
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get_time_difference(cross_referenced_time[1], cross_referenced_time[-1]) / 3600 / 24)
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locals()['x_' + str(len(cross_referenced_interval_list) + 9)].append(
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cross_referenced_interval_list[0] / 3600 / 24)
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locals()['y_' + str(len(cross_referenced_interval_list) + 9)].append(cross_referenced_interval_list[-1]/3600/24)
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if len(labeled_interval_list) == 1:
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labeled_without_time += labeled_interval_list[0]
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labeled_without_count += 1
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elif len(labeled_interval_list) == 2:
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locals()['x_'+str(len(labeled_interval_list)+11)].append(labeled_interval_list[0]/3600/24)
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locals()['y_'+str(len(labeled_interval_list)+11)].append(get_time_difference(labeled_time[1],labeled_time[-1])/3600/24)
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locals()['x_'+str(len(labeled_interval_list)+12)].append(labeled_interval_list[0]/3600/24)
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locals()['y_' + str(len(labeled_interval_list) + 12)].append(
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get_time_difference(labeled_time[0], labeled_time[-1]) / 3600 / 24)
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elif len(labeled_interval_list) == 3:
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locals()['x_' + str(len(labeled_interval_list) + 12)].append(labeled_interval_list[0] / 3600 / 24)
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locals()['y_' + str(len(labeled_interval_list) + 12)].append(
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get_time_difference(labeled_time[1], labeled_time[-1]) / 3600 / 24)
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locals()['x_' + str(len(labeled_interval_list) + 13)].append(labeled_interval_list[0] / 3600 / 24)
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locals()['y_' + str(len(labeled_interval_list) + 13)].append(labeled_interval_list[-1]/3600/24)
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if len(link_interval_list) == 1:
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link_without_time += link_interval_list[0]
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link_without_count += 1
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elif len(link_interval_list) == 2:
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locals()['x_'+str(len(link_interval_list)+15)].append(link_interval_list[0]/3600/24)
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locals()['y_' + str(len(link_interval_list) + 15)].append(get_time_difference(link_time[1], link_time[-1])/3600/24)
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locals()['x_' + str(len(link_interval_list) + 16)].append(link_interval_list[0]/3600/24)
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locals()['y_' + str(len(link_interval_list) + 16)].append(get_time_difference(link_time[0],link_time[-1])/3600/24)
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elif len(link_interval_list) == 3:
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locals()['x_' + str(len(link_interval_list) + 16)].append(link_interval_list[0] / 3600 / 24)
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locals()['y_' + str(len(link_interval_list) + 16)].append(
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get_time_difference(link_time[1], link_time[-1]) / 3600 / 24)
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locals()['x_' + str(len(link_interval_list) + 17)].append(link_interval_list[0] / 3600 / 24)
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locals()['y_' + str(len(link_interval_list) + 17)].append(link_interval_list[-1]/3600/24)
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# #绘制散点图
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matplotlib.rcParams['font.family'] = 'SimHei' # 或者其他你有的中文字体
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matplotlib.rcParams['axes.unicode_minus'] = False # 正确显示负号
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fig1, ax1 = plt.subplots(2, 2)
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fig1.suptitle('mentioned')
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line1 = mentioned_without_time/mentioned_without_count/3600/24
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ax1[0,0].scatter(x_1,y_1,s=1)
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ax1[0,0].axhline(y=line1,color='red',linestyle='--')
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ax1[0,0].set_title('事件发生一次')
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ax1[0,0].set_xlabel('issue开启至事件发生时间（天）')
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ax1[0,0].set_ylabel('事件发生至issue关闭时间（天）')
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ax1[0,1].scatter(x_2,y_2,s=1)
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ax1[0,1].axhline(y=line1,color='red',linestyle='--')
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ax1[0,1].set_title('事件发生一次')
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ax1[0,1].set_xlabel('issue开启至事件发生时间（天）')
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ax1[0,1].set_ylabel('issue开启至issue关闭时间（天）')
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ax1[1,0].scatter(x_3,y_3,s=1)
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ax1[1,0].axhline(y=line1,color='red',linestyle='--')
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ax1[1,0].set_title('事件发生两次')
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ax1[1,0].set_xlabel('issue开启至第一次事件发生时间（天）')
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ax1[1,0].set_ylabel('事件第一次发生启至issue关闭时间（天）')
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ax1[1,1].scatter(x_4,y_4,s=1)
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ax1[1,1].axhline(y=line1,color='red',linestyle='--')
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ax1[1,1].set_title('事件发生两次')
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ax1[1,1].set_xlabel('issue开启至第一次事件发生时间（天）')
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ax1[1,1].set_ylabel('事件第二次发生启至issue关闭时间（天）')
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fig2, ax2 = plt.subplots(2, 2)
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fig2.suptitle('assigned')
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line2 = assigned_without_time/assigned_without_count/3600/24
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ax2[0,0].scatter(x_5,y_5,s=1)
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ax2[0,0].axhline(y=line2,color='red',linestyle='--')
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ax2[0,0].set_title('事件发生一次')
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ax2[0,0].set_xlabel('issue开启至事件发生时间（天）')
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ax2[0,0].set_ylabel('事件发生至issue关闭时间（天）')
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ax2[0,1].scatter(x_6,y_6,s=1)
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ax2[0,1].axhline(y=line2,color='red',linestyle='--')
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ax2[0,1].set_title('事件发生一次')
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ax2[0,1].set_xlabel('issue开启至事件发生时间（天）')
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ax2[0,1].set_ylabel('issue开启至issue关闭时间（天）')
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ax2[1,0].scatter(x_7,y_7,s=1)
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ax2[1,0].axhline(y=line2,color='red',linestyle='--')
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ax2[1,0].set_title('事件发生两次')
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ax2[1,0].set_xlabel('issue开启至第一次事件发生时间（天）')
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ax2[1,0].set_ylabel('事件第一次发生启至issue关闭时间（天）')
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ax2[1,1].scatter(x_8,y_8,s=1)
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ax2[1,1].axhline(y=line2,color='red',linestyle='--')
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ax2[1,1].set_title('事件发生两次')
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ax2[1,1].set_xlabel('issue开启至第一次事件发生时间（天）')
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ax2[1,1].set_ylabel('事件第二次发生启至issue关闭时间（天）')
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fig3, ax3 = plt.subplots(2, 2)
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fig3.suptitle('cross-referenced')
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line3 = cross_referenced_without_time/cross_referenced_without_count/3600/24
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ax3[0,0].scatter(x_9,y_9,s=1)
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ax3[0,0].axhline(y=line3,color='red',linestyle='--')
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ax3[0,0].set_title('事件发生一次')
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ax3[0,0].set_xlabel('issue开启至事件发生时间（天）')
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ax3[0,0].set_ylabel('事件发生至issue关闭时间（天）')
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ax3[0,1].scatter(x_10,y_10,s=1)
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ax3[0,1].axhline(y=line3,color='red',linestyle='--')
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ax3[0,1].set_title('事件发生一次')
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ax3[0,1].set_xlabel('issue开启至事件发生时间（天）')
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ax3[0,1].set_ylabel('issue开启至issue关闭时间（天）')
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ax3[1,0].scatter(x_11,y_11,s=1)
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ax3[1,0].axhline(y=line3,color='red',linestyle='--')
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ax3[1,0].set_title('事件发生两次')
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ax3[1,0].set_xlabel('issue开启至第一次事件发生时间（天）')
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ax3[1,0].set_ylabel('事件第一次发生启至issue关闭时间（天）')
|
||
|
||
ax3[1,1].scatter(x_12,y_12,s=1)
|
||
ax3[1,1].axhline(y=line3,color='red',linestyle='--')
|
||
ax3[1,1].set_title('事件发生两次')
|
||
ax3[1,1].set_xlabel('issue开启至第一次事件发生时间（天）')
|
||
ax3[1,1].set_ylabel('事件第二次发生启至issue关闭时间（天）')
|
||
|
||
fig4, ax4 = plt.subplots(2, 2)
|
||
fig4.suptitle('labeled')
|
||
line4 = labeled_without_time/labeled_without_count/3600/24
|
||
|
||
ax4[0,0].scatter(x_13,y_13,s=1)
|
||
ax4[0,0].axhline(y=line4,color='red',linestyle='--')
|
||
ax4[0,0].set_title('事件发生一次')
|
||
ax4[0,0].set_xlabel('issue开启至事件发生时间（天）')
|
||
ax4[0,0].set_ylabel('事件发生至issue关闭时间（天）')
|
||
|
||
ax4[0,1].scatter(x_14,y_14,s=1)
|
||
ax4[0,1].axhline(y=line4,color='red',linestyle='--')
|
||
ax4[0,1].set_title('事件发生一次')
|
||
ax4[0,1].set_xlabel('issue开启至事件发生时间（天）')
|
||
ax4[0,1].set_ylabel('issue开启至issue关闭时间（天）')
|
||
|
||
ax4[1,0].scatter(x_15,y_15,s=1)
|
||
ax4[1,0].axhline(y=line4,color='red',linestyle='--')
|
||
ax4[1,0].set_title('事件发生两次')
|
||
ax4[1,0].set_xlabel('issue开启至第一次事件发生时间（天）')
|
||
ax4[1,0].set_ylabel('事件第一次发生启至issue关闭时间（天）')
|
||
|
||
ax4[1,1].scatter(x_16,y_16,s=1)
|
||
ax4[1,1].axhline(y=line4,color='red',linestyle='--')
|
||
ax4[1,1].set_title('事件发生两次')
|
||
ax4[1,1].set_xlabel('issue开启至第一次事件发生时间（天）')
|
||
ax4[1,1].set_ylabel('事件第二次发生启至issue关闭时间（天）')
|
||
|
||
fig5, ax5 = plt.subplots(2, 2)
|
||
fig5.suptitle('link')
|
||
line5 = link_without_time/link_without_count/3600/24
|
||
|
||
ax5[0,0].scatter(x_17,y_17,s=1)
|
||
ax5[0,0].axhline(y=line5,color='red',linestyle='--')
|
||
ax5[0,0].set_title('事件发生一次')
|
||
ax5[0,0].set_xlabel('issue开启至事件发生时间（天）')
|
||
ax5[0,0].set_ylabel('事件发生至issue关闭时间（天）')
|
||
|
||
ax5[0,1].scatter(x_18,y_18,s=1)
|
||
ax5[0,1].axhline(y=line5,color='red',linestyle='--')
|
||
ax5[0,1].set_title('事件发生一次')
|
||
ax5[0,1].set_xlabel('issue开启至事件发生时间（天）')
|
||
ax5[0,1].set_ylabel('issue开启至issue关闭时间（天）')
|
||
|
||
ax5[1,0].scatter(x_19,y_19,s=1)
|
||
ax5[1,0].axhline(y=line5,color='red',linestyle='--')
|
||
ax5[1,0].set_title('事件发生两次')
|
||
ax5[1,0].set_xlabel('issue开启至第一次事件发生时间（天）')
|
||
ax5[1,0].set_ylabel('事件第一次发生启至issue关闭时间（天）')
|
||
|
||
ax5[1,1].scatter(x_20,y_20,s=1)
|
||
ax5[1,1].axhline(y=line5,color='red',linestyle='--')
|
||
ax5[1,1].set_title('事件发生两次')
|
||
ax5[1,1].set_xlabel('issue开启至第一次事件发生时间（天）')
|
||
ax5[1,1].set_ylabel('事件第二次发生启至issue关闭时间（天）')
|
||
|
||
plt.tight_layout()
|
||
plt.show()
|
||
|
||
|
||
for i in range(20):
|
||
count = 0
|
||
for j in range(len(locals()['y_'+str(i+1)])):
|
||
if locals()['y_'+str(i+1)][j]< locals()['line'+str(i//4+1)]:
|
||
count += 1
|
||
|
||
print('y_'+str(i%4+1)+':')
|
||
print(count/len(locals()['y_'+str(i+1)])*100,end='%')
|
||
print('\n')
|
||
|
||
# count = 0
|
||
# for i in range(len(y_1)):
|
||
# if y_1[i]< line:
|
||
# count += 1
|
||
# print(count/len(y_1)*100,end='%')
|
||
|
||
# a = [5043, 1547, 803, 418, 274, 150, 115, 82, 61, 44, 38, 24, 27, 16, 9, 14, 14, 5, 9, 9, 1, 3, 4, 2, 2, 0, 2, 0, 1, 0]
|