大家好,我是安果!
目前公司使用 Jira 作为项目管理工具,在每一次迭代完成后的复盘会上,我们都需要针对本次迭代的 Bug 进行数据统计,以帮助管理层能更直观的了解研发的代码质量
本篇文章将介绍如何利用统计 Jira 数据,并进行可视化
1. 准备
首先,安装 Python 依赖库
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# 安装依赖库 pip3 install jira pip3 install html - table pip3 install pyecharts pip3 install snapshot_selenium |
其中
- jira 使用 jsql 语法从在项目中获取需要的数据
- html-table 用于生成一个 HTML 格式的表格数据
- pyecharts 和 snapshot_selenium 用于数据可视化
2. 实战一下
下面我们通过 7 个步骤来实现上面的功能
2-1 登录获取客户端连接对象
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from jira import JIRA class JiraObj( object ): def __init__( self , bug_style, project_type): """ :param project_name :param sprint: 迭代号码 :param bug_style: BUG状态 """ # Jira首页地址 self .server = 'https://jira.**.team' # Jira登录账号信息 self .basic_auth = ( '用户名' , '密码' ) # 创建一个客户端连接信息 self .jiraClinet = JIRA(server = self .server, basic_auth = self .basic_auth) |
2-2 根据项目类型获取看板 id
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... # 获取boards看板 # 所有看板信息 boards = [(item. id , item.name) for item in self .jiraClinet.boards()] board_id = self .__get_board_id(boards, project_type) print ( "看板id:" , board_id) ... def __get_board_id( self , boards, project_type): """ 获取看板id :param project_type: :return: """ board_id = 1 for item in boards: if (project_type = = PROJ_TYPE.Type1 and item[ 1 ] = = 't1' ) or ( project_type = = PROJ_TYPE.Type2 and item[ 1 ] = = 't2' ): board_id = item[ 0 ] break return board_id .. |
2-3 根据看板 id 获取迭代 id 及迭代名称
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... # 获取项目Sprint,让用户进行选择 sprints = self .jiraClinet.sprints(board_id = board_id) for item in sprints: if str (sprint_no) in item.name: self .sprint_id = item. id self .sprint_name = item.name print (f "选择Sprint,id:{self.sprint_id},name:{self.sprint_name}" ) break ... |
2-4 根据项目名、Bug 类型、迭代 id 组成 jsql 语句,并查询数据
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... def get_bug_status_jsql( self , bug_status: BUG_STATUS): """ 通过bug状态,获取jsql :param bug_status: :return: """ status_jsql = '' if bug_status = = BUG_STATUS. ALL : status_jsql = ' ' elif bug_status = = BUG_STATUS.TO_VERIFY: # 待验证(已解决) status_jsql = ' AND status = 已解决 ' elif bug_status = = BUG_STATUS.TO_FIXED: # 待解决(打开、重新打开、处理中) status_jsql = ' AND status in (打开, 重新打开, 处理中) ' elif bug_status = = BUG_STATUS.CLOSED: # 关闭 status_jsql = ' AND status = Closed ' elif bug_status = = BUG_STATUS.TO_FIXED_CONTAIN_DELAY: # 待解决(打开、重新打开、处理中、延期处理) status_jsql = ' AND status in (打开, 延期处理, 重新打开, 处理中) ' return status_jsql ... jql = f 'project = {project_name} and issuetype = 故障 {self.get_bug_status_jsql(self.bug_style)} AND Sprint = {self.sprint_id} ORDER BY priority desc, updated DESC' print (jql) lists = self .get_issue_list(jql) ... |
2-5 生成本地 HTML 统计数据
需要注意的是,使用 a 标签组装的链接不能直接跳转,需要针对数据进行二次替换才能正常进行链接跳转
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from HTMLTable import ( HTMLTable ) ... def gen_html_table( self , datas): """ 初始化表单样式 :return: """ table = HTMLTable(caption = f '实时BUG统计【{self.project_name}】,一共{len(datas)}个' ) # 表头行 table.append_header_rows((( 'ID' , '状态' , '优先级' , '责任人' , '终端' , 'URL' ),)) # 添加数据 table.append_data_rows(datas) # 设置样式 table.caption.set_style({ 'font-size' : '15px' }) # 其他样式设置 ... # 替换数据,便于展示href地址 html = table.to_html().replace( "<" , "<" ).replace( ">" , ">" ).replace( """ , '"' ) with open (f "./output/{self.project_name}-bug_{current_time()}.html" , 'w' , encoding = 'utf-8' ) as file : file .write(html) ... # 生成本地文件的数据 output_tuples = tuple ([ (item.get( "key" ), item.get( "status" ), item.get( "priority" ), item.get( 'duty' ), item.get( 'end_type' ), f '<a href="{item.get(" rel="external nofollow" url")}" target="_blank">点我查看</a>' ) for item in lists]) # 生成本地HTML文件 self .gen_html_table(output_tuples) .. |
2-6 数据统计
首先,这里按 Bug 责任人进行分组,然后按数目进行降序排列
然后,按 Bug 优先等级进行降序排列
最后,获取每一个端的 Bug 总数
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... # 2、统计每个人(按数目) datas_by_count = {} for item in lists: datas_by_count[item.get( "duty" )] = datas_by_count.get(item.get( "duty" ), 0 ) + 1 # 降序排序 datas_by_count = sorted (datas_by_count.items(), key = lambda item: item[ 1 ], reverse = True ) # print("按Bug总数排序:", datas_by_count) # 3、统计每个人(按优先级) datas_by_priority = {} for item in datas_by_count: # 责任人 name = item[ 0 ] # 5个优先级对应的数目 counts = self .get_assignee_count(lists, name) datas_by_priority[name] = counts # 排序(按优先级多条件降序排列) datas_by_priority = sorted (datas_by_priority.items(), key = lambda item: (item[ 1 ][ 0 ], item[ 1 ][ 1 ], item[ 1 ][ 2 ], item[ 1 ][ 3 ]), reverse = True ) # print("按Bug优先级排序:", datas_by_priority) # 4、根据终端进行统计分类 keys, values = self .get_end_type_count(lists) ... |
2-7 可视化
针对上面的 3 组数据,使用 pyecharts 绘制成柱状图和饼状图
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... def draw_image( self , datas_by_count, datas_by_priority, keys, values): """ 绘制图片 :param values: :param keys: :param datas_by_count: 按bug总数排序结果 :param datas_by_priority: 按bug优先级排序结果 :return: """ # 1、按BUG总数排序绘制 bar = ( Bar().set_global_opts( title_opts = opts.TitleOpts(title = f "{self.project_name}" , subtitle = f "{self.sprint_name}" ))) bar.add_xaxis([item[ 0 ] for item in datas_by_count]) bar.add_yaxis(f "BUG总数" , [item[ 1 ] for item in datas_by_count]) # render 会生成本地 HTML 文件,默认会在当前目录生成 render.html 文件 # 也可以传入路径参数,如 bar.render("mycharts.html") # bar.render(path=f'{sprint_name}-BUG总数.html') make_snapshot(snapshot, bar.render(), "./output/1.png" ) # 2、按优先级排序绘制 bar2 = ( # Bar(init_opts=opts.InitOpts(theme=ThemeType.INFOGRAPHIC)) Bar() .add_xaxis([item[ 0 ] for item in datas_by_priority]) .add_yaxis( self .__get_priority(BUG_PRIORITY.Highest), [item[ 1 ][ 0 ] for item in datas_by_priority], color = '#6aa84f' ) .add_yaxis( self .__get_priority(BUG_PRIORITY.High), [item[ 1 ][ 1 ] for item in datas_by_priority], color = '#a2c4c9' ) .add_yaxis( self .__get_priority(BUG_PRIORITY.Medium), [item[ 1 ][ 2 ] for item in datas_by_priority], color = "#ff9900" ) .add_yaxis( self .__get_priority(BUG_PRIORITY.Low), [item[ 1 ][ 3 ] for item in datas_by_priority], color = "#ea9999" ) .add_yaxis( self .__get_priority(BUG_PRIORITY.Lowest), [item[ 1 ][ 4 ] for item in datas_by_priority], color = "#980000" ) .set_global_opts( title_opts = opts.TitleOpts(title = f "{self.project_name}" , subtitle = f "{self.sprint_name}" )) ) # bar2.render(path=f'{sprint_name}-BUG优先级.html') make_snapshot(snapshot, bar2.render(), "./output/2.png" ) # 3、根据终端来绘制饼图 if len (keys) > 0 and len (values) > 0 : c = ( Pie() .add("", [ list (z) for z in zip (keys, values)]) .set_global_opts(title_opts = opts.TitleOpts(title = "各端BUG分布" )) .set_series_opts(label_opts = opts.LabelOpts(formatter = "{b}: {c}" )) ) make_snapshot(snapshot, c.render(), f "./output/{self.project_name}_end.png" ) # 4、合并两张图片 self .concatenate_img([ './output/1.png' , './output/2.png' ], img_name = f './output/{self.sprint_name}_bug.png' , axis = 1 ) ... |
3. 总结
通过上面的操作,每次只需要输入项目类型、迭代版本号、要统计的 Bug 类型,就能统计出所需要的数据并绘制成图表
到此这篇关于利用Python统计Jira数据并可视化的文章就介绍到这了,更多相关Python统计Jira数据内容请搜索服务器之家以前的文章或继续浏览下面的相关文章希望大家以后多多支持服务器之家!
原文链接:https://mp.weixin.qq.com/s/4_N9D64IFQZqNTjJuJMqAg