def fetch_mem(self, lines):
"""
获取 mem 的关键数据包括: 纯物理内存使用率, 包含虚拟内存的内存使用率(无则为0)
:param lines: 带 mem 关键数据行
"""
# 解析数据错误行数
error_num = 0
mem_sum = float(0)
mem_virtual_sum = float(0)
for line in lines:
mems = line.split(",")
if len(mems) == 17:
# (Memtotal - Memfree - cached - buffers)/Memtotal * 100
mem_sum += ((float(mems[2]) - float(mems[6]) -
float(mems[11]) - float(mems[14])) /
float(mems[2]) * 100)
elif len(mems) == 8:
# (Real total - Real free)/Real total * 100
mem_sum += ((float(mems[6]) - float(mems[4])) /
float(mems[6]) * 100)
# (Real total - Real free + Virtual total - Virtual free) /(Real total + Virtual total) * 100
mem_virtual_sum += ((float(mems[6]) - float(mems[4]) +
float(mems[7]) - float(mems[5])) /
(float(mems[6]) + float(mems[7])) * 100)
else:
logger.error("解析服务器ip为 %s 的 %s 监控文件的 MEM 数据出现异常,出现异常行数据为：%s" %
(self.ip, self.name, line))
error_num += 1
continue
self.mem = (round(mem_sum / (len(lines) - error_num), 2),
round(mem_virtual_sum / (len(lines) - error_num), 2))
logger.debug("mem: 不含虚拟内存的使用率 %.2f%%, 包含虚拟内存的使用率 %.2f%%" %
(self.mem[0], self.mem[1]))
def check_dir(path):
logger.debug("检查下载路径是否存在")
if not os.path.exists(path):
logger.info("下载路径不存在,创建下载路径")
os.makedirs(path)
logger.debug("下载路径检查完成")
def start_nmon_control(self, config, filename):
"""
开启后台监控
:param config:config 对象
:param filename: nmon 文件名
:return:
"""
if not hasattr(self, "ssh"):
raise CustomError("未与服务端进行连接")
stdin, stdout, stderr = self.ssh.exec_command("ls -dl " +
self.server_name)
if stdout.channel.recv_exit_status():
stdin, stdout, stderr = self.ssh.exec_command("mkdir " +
self.server_name)
if stdout.channel.recv_exit_status():
raise CustomError(stderr.read().decode('utf-8'))
nmon_filename = filename + ".nmon"
nmon_cmd = (self.path + "/nmon -F ./" + self.server_name + "/" +
nmon_filename + " -t -s " +
config.nmon_acquisition_interval + " -c " +
config.nmon_all_time)
logger.debug("正在开启" + self.server_name + "监控,监控结果文件名为:" +
nmon_filename)
logger.debug("监控命令 %s" % nmon_cmd)
stdin, stdout, stderr = self.ssh.exec_command(nmon_cmd)
if stdout.channel.recv_exit_status():
err_msg = stderr.read().decode("utf-8")
raise CustomError(err_msg)
def download_nmon_files(self, config):
if not hasattr(self, "ssh"):
raise CustomError("未与服务端进行连接")
download_local_path = config.download_local_path + os.path.sep + self.server_name + os.path.sep + self.taskid
if not os.path.exists(download_local_path):
logger.info("正在创建文件夹" + self.server_name)
os.mkdir(download_local_path)
trans = self.ssh.get_transport()
sftp = paramiko.SFTPClient.from_transport(trans)
files = sftp.listdir_attr(self.path + "/" + self.server_name + "/" +
self.taskid)
logger.info("开始下载" + self.server_name + "监控文件")
for file in files:
logger.debug("正在下载:" + file.filename)
sftp.get(
self.path + "/" + self.server_name + "/" + self.taskid + "/" +
file.filename, download_local_path + "\\" + file.filename)
self.file_list.append(download_local_path + "\\" + file.filename)
trans.close()
# --add 20200515 报告显示顺序存在乱序的情况, 在保存完所有的文件路径后, 进行排序
self.file_list.sort()
logger.info("%s 监控文件下载完成, 文件保存在 %s" %
(self.server_name, download_local_path))
def close(self):
"""
关闭后台连接
"""
if not hasattr(self, "ssh"):
raise CustomError("未与服务端进行连接")
logger.debug("正在关闭" + self.server_name + "的连接")
self.ssh.close()
def exe_command(command):
logger.debug("正在执行命令:"+command)
result = subprocess.run(command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
if not result.returncode:
logger.info(result.stdout.decode("gbk"))
else:
# 调用 lr 时,会抛出一个 log4cxx 的异常, 但是脚本正常跑完,结果保存成功,此异常暂时忽略
err_msg = result.stderr.decode('gbk')
if not err_msg.find("log4cxx") >= 0:
raise CustomError(err_msg)
def fetch_cpu(self, lines):
"""
:param lines: 带 cpu 关键数据行
"""
cpu_sum = float(0)
for line in lines:
cpus = line.split(",")
# sys% datas[2] user datas[3]
# total = sys + user
cpu_sum += (float(cpus[3]) + float(cpus[2]))
self.cpu = round(cpu_sum / len(lines), 2)
logger.debug("cpu: %.2f%%" % self.cpu)
def connect(self, user, passwd):
"""
连接后台 server
:param user: 用户名
:param passwd: 密码
"""
logger.debug("正在与" + self.server_name + "建立连接")
ssh_client = paramiko.SSHClient()
ssh_client.set_missing_host_key_policy(paramiko.AutoAddPolicy())
ssh_client.connect(hostname=self.server_name,
port=self.SSH_PORT,
username=user,
password=passwd)
self.ssh = ssh_client
def get_all_script(script_path, file_extension):
"""
获取当前文件夹下所有指定后缀文件
:param script_path: 文件夹路径
:param file_extension: 文件类型
:return:返回脚本文件列表
"""
script_files = []
if not os.path.exists(script_path):
raise CustomError("路径错误,文件夹不存在")
files = os.listdir(script_path)
logger.debug("当前路径" + script_path + "下所有文件与文件夹")
logger.debug(files)
for file in files:
if not os.path.isfile(script_path + "\\" + file):
continue
if os.path.splitext(file)[1] == file_extension:
script_files.append(os.path.splitext(file)[0])
if not script_files.__len__():
raise CustomError("路径下无后缀为%s的脚本文件" % file_extension)
logger.debug("所有脚本文件")
logger.debug(script_files)
return script_files
def analyse_lr_cmd(files_path):
"""
生成lr解析命令
"""
cmd_anaylise_list = []
cmd = r'wlrun -TestPath '
# cmd_analyse = r'C:\"Program Files (x86)"\HP\LoadRunner\bin\AnalysisUI -RESULTPATH '
cmd_analyse = r'AnalysisUI -RESULTPATH '
for file_path in files_path:
command_analyse = cmd_analyse + file_path + ".lrr -TEMPLATENAME html"
cmd_anaylise_list.append(command_analyse)
logger.debug("生成的 lr 解析命令")
logger.debug(cmd_anaylise_list)
return cmd_anaylise_list
def fetch_resp_time(self, file_path, resp_avg_list, resp_min_list,
resp_max_list):
"""
提取 response time html 中 各 response time 的值
:param file_path: response time html 绝对路径
:param resp_avg_list: 保存 response time average 值
:param resp_min_list: 保存 response time min 值
:param resp_max_list: 保存 response time max 值
"""
logger.debug("%s 开始提取 response time 数据" % self.name)
with open(file_path, "r", encoding='utf8') as response_time_html_file:
response_time_str = response_time_html_file.read()
response_time_table_list = re.findall(
r'<tr class="legendRow">([\s\S]*?)</tr>', response_time_str)
if not response_time_table_list:
raise CustomError("%s 未匹配到 response time 数据" % self.name)
logger.debug("%s 共匹配到 %d 条 response time 记录" %
(self.name, len(response_time_table_list)))
for index in range(0, len(response_time_table_list)):
response_time_table_str = response_time_table_list[
index].replace("\n", "")
response_time_data_list = response_time_table_str.split(
"<td>", 6)
trasaction_name = response_time_data_list[2][:-5]
# 单位转化为 ms
response_time_average = round(
float(response_time_data_list[4][:-5]) * 1000, 2)
logger.debug(
"%s 交易 transcation %s response time average: %.2fms" %
(self.name, trasaction_name, response_time_average))
resp_avg_list.append(response_time_average)
response_time_min = round(
float(response_time_data_list[3][:-5]) * 1000, 2)
logger.debug("%s 交易 transcation %s response time min: %.2fms" %
(self.name, trasaction_name, response_time_min))
resp_min_list.append(response_time_min)
response_time_max = round(
float(response_time_data_list[5][:-5]) * 1000, 2)
logger.debug("%s 交易 transcation %s response time max: %.2fms" %
(self.name, trasaction_name, response_time_max))
resp_max_list.append(response_time_max)
def get_all_script_path(file_path, file_extension):
"""
获取当前文件夹下所有制定后缀文件
:param file_path: 文件夹路径
:param file_extension: 文件类型
:return:返回脚本文件全路径列表
"""
files_path = []
for root, dirs, files in os.walk(file_path):
for file in files:
logger.debug("文件名："+file)
if os.path.splitext(file)[1] == file_extension:
file_path = os.path.join(root, file)
logger.info("含有"+file_extension+"后缀的文件:"+file+",全路径为:"+file_path)
files_path.append(os.path.splitext(file_path)[0])
return files_path
def fetch_cpu(self, lines):
"""
:param lines: 带 cpu 关键数据行
"""
# 解析数据错误行数
error_num = 0
cpu_sum = float(0)
for line in lines:
cpus = line.split(",")
# sys% datas[2] user datas[3]
# total = sys + user
try:
cpu_sum += (float(cpus[3]) + float(cpus[2]))
except Exception:
logger.error("解析服务器ip为 %s 的 %s 监控文件的 cpu 数据出现异常,出现异常行数据为：%s" %
(self.ip, self.name, line))
error_num += 1
self.cpu = round(cpu_sum / (len(lines) - error_num), 2)
logger.debug("cpu: %.2f%%" % self.cpu)
def check_exe():
'''
检查jmeter是否在运行, 正在运行则退出
:return:
'''
command = "tasklist | findstr java.exe"
result = subprocess.run(command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
if result.returncode == 1:
if result.stderr:
raise CustomError(result.stderr.decode('gbk'))
elif result.returncode == 0:
command_result_str = result.stdout.decode('gbk')
logger.debug("命令 %s 执行结果 %a" % (command, command_result_str))
command_result_list = command_result_str.split(os.linesep)
logger.debug(command_result_list)
for command_result in command_result_list:
if command_result != '':
pid = command_result.split()[1]
find_jemeter = "jstack %s" % pid
result_jm = subprocess.run(find_jemeter, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
if result_jm.returncode == 0:
if "jmeter" in result_jm.stdout.decode('gbk'):
raise CustomError("jmeter 程序正在运行, 请关闭 jmeter 再开启脚本")
else:
logger.debug("jmeter不在运行运行")
else:
if result_jm.stderr:
raise CustomError(result_jm.stderr.decode('gbk'))
def fetch_tps(self, file_path, tps_list):
"""
提取 tps html 中 tps 的值
:param file_path: tps html 绝对路径
:param tps_list: 保存 tps 值的 list
"""
logger.debug("%s 开始提取 tps 数据" % self.name)
with open(file_path, "r", encoding='utf8') as tps_html_file:
tps_str = tps_html_file.read()
tps_table_list = re.findall(
r'<tr class="legendRow">([\s\S]*?)</tr>', tps_str)
if not tps_table_list:
raise CustomError("%s 未匹配到 tps 数据" % self.name)
logger.debug("%s 共匹配到 %d 条tps记录" %
(self.name, len(tps_table_list)))
for index in range(0, len(tps_table_list)):
tps_table_str = tps_table_list[index].replace("\n", "")
tps_data_list = tps_table_str.split("<td>", 5)
# 判断是否为成功记录,成功记录提取数据, 失败记录跳过
if tps_data_list[2][:-5].split(":")[1] != "Pass":
continue
logger.debug("%s 交易 transaction %s tps %s" %
(self.name, tps_data_list[2][:-5].split(":")[0],
tps_data_list[4][:-5]))
tps_list.append(tps_data_list[4][:-5])
def file_analyse(self, file):
"""
解析jmeter报告
:param file: jmeter报告所在目录
"""
try:
logger.info("开始解析%s jmeter结果文件" % os.path.basename(file))
super().file_analyse(file)
file_all_path = file + r"\content\js\dashboard.js"
with open(file_all_path, "r", encoding="utf8") as jmeterfile:
text = jmeterfile.read()
static_data_match_result = re.match(
r'[\s\S]*statisticsTable"\),(.*?), function', text)
if static_data_match_result is not None:
static_json_data = static_data_match_result.group(
1).strip()
logger.debug("取到 %s 的压测结果数据为: %s" %
(os.path.basename(file), static_json_data))
static_data = json.loads(static_json_data)
logger.debug("转化成json格式:%s" % static_data)
if "items" not in static_data.keys():
raise CustomError("%s获取压测结果失败,提取到的数据中未找到item标签" %
os.path.basename(file))
static_items_data = static_data["items"]
logger.debug("提取到的数据为: %s" % static_items_data)
for static_item_data in static_items_data:
tmp_data = static_item_data['data']
# list: [Transaction, TPS, Error%, Response Time(average), Response Time(min), Response Time(max)]
tmp_list = [
tmp_data[1],
round(float(tmp_data[10]), 2), tmp_data[3],
round(float(tmp_data[4]), 2),
round(float(tmp_data[5]), 2),
round(float(tmp_data[6]), 2)
]
# dict: {name:list}
self.result_dict[tmp_data[0]] = tmp_list
logger.debug("%s 提取结果 %s" %
(os.path.basename(file), self.result_dict))
else:
raise CustomError("%s获取压测结果失败,未找到匹配数据" %
os.path.basename(file))
finally:
logger.info("%s jmeter 结果文件解析结束" % os.path.basename(file))
def fetch_mem(self, lines):
"""
获取 mem 的关键数据包括: 纯物理内存使用率, 包含虚拟内存的内存使用率(无则为0)
:param lines: 带 mem 关键数据行
"""
mem_sum = float(0)
mem_virtual_sum = float(0)
for line in lines:
mems = line.split(",")
if len(mems) == 17:
# (Memtotal - Memfree - cached - buffers)/Memtotal * 100
mem_sum += ((float(mems[2]) - float(mems[6]) - float(mems[11]) - float(mems[14])) / float(
mems[2]) * 100)
elif len(mems) == 8:
# (Real total - Real free)/Real total * 100
mem_sum += ((float(mems[6]) - float(mems[4])) / float(mems[6]) * 100)
# (Real total - Real free + Virtual total - Virtual free) /(Real total + Virtual total) * 100
mem_virtual_sum += ((float(mems[6]) - float(mems[4]) + float(mems[7]) - float(mems[5])) / (
float(mems[6]) + float(mems[7])) * 100)
else:
raise CustomError("暂不支持此内存页面数据读取")
self.mem = (round(mem_sum / len(lines), 2), round(mem_virtual_sum / len(lines), 2))
logger.debug("mem: 不含虚拟内存的使用率 %.2f%%, 包含虚拟内存的使用率 %.2f%%" % (self.mem[0], self.mem[1]))
def jmeter_cmd(script_file, path):
"""
获取路径生成执行脚本命令
"""
cmd_list = []
result_file_list = []
# cmd = r"D:\JMeter\apache-jmeter-5.1.1\bin\jmeter -n -t "
cmd = r"jmeter -n -t "
for file in script_file:
command = cmd + path + os.path.sep + file + ".jmx" + " -l " + path + os.path.sep + file + ".jtl -e -o " \
+ path + os.path.sep + file
cmd_list.append(command)
result_file_list.append(path + os.path.sep + file)
logger.debug("生成的 jmeter 命令")
logger.debug(cmd_list)
logger.debug(("jmeter结果文件保存路径"))
logger.debug(result_file_list)
return cmd_list, result_file_list
def get_all_script(script_path, file_extension):
"""
获取当前文件夹下所有指定后缀文件
:param script_path: 文件夹路径
:param file_extension: 文件类型
:return:返回脚本文件列表
:return 脚本路径
"""
# 如果是一个文件,判断后缀是否合法后,返回
if os.path.isfile(script_path):
file_and_path = os.path.split(script_path)
file = file_and_path[1]
if os.path.splitext(file)[1] == file_extension:
return [os.path.splitext(file)[0]], file_and_path[0]
else:
raise CustomError("检查到文件后缀与脚本类型不符, 预期脚本类型为: %s" % file_extension)
script_files = []
if not os.path.exists(script_path):
raise CustomError("路径错误,文件夹或者文件不存在: %s" % script_path)
files = os.listdir(script_path)
logger.debug("当前路径" + script_path + "下所有文件与文件夹")
logger.debug(files)
for file in files:
if not os.path.isfile(script_path + "\\" + file):
continue
if os.path.splitext(file)[1] == file_extension:
script_files.append(os.path.splitext(file)[0])
if not script_files.__len__():
raise CustomError("路径下无后缀为%s的脚本文件" % file_extension)
logger.debug("所有脚本文件")
logger.debug(script_files)
return script_files, script_path
def _change_to_load_table(self, result_list):
"""
将压测结果转化成 html 中的 table 返回
:param result_list:需要转化的压测list
:return: str table str
"""
logger.info("开始将压测报告数据转化成 table")
html_str = """
<h1>summary</h1>
<table border="1">
<tr>
<th>script name</th>
<th>trasaction name</th>
<th>trasaction number</th>
<th>tps</th>
<th>error%</th>
<th>response time(average) ms</th>
<th>response time(min) ms</th>
<th>response time(max) ms</th>
</tr>
"""
for result in result_list:
keys_dict = result.result_dict.keys()
keys = list(keys_dict)
if len(keys) == 0:
raise CustomError("%s 脚本提取数据异常,无法获取到取样器" % result.name)
logger.debug('%s 含有 transaction %s' % (result.name, keys))
result_value_one = result.result_dict[keys[0]]
summary_html_one = """
<tr>
<td rowspan= '%d'>%s</td>
<td>%s</td>
<td>%s</td>
<td>%s</td>
<td>%s%%</td>
<td>%s</td>
<td>%s</td>
<td>%s</td>
</tr>
""" % (len(keys), result.name, keys[0], result_value_one[0],
result_value_one[1], result_value_one[2],
result_value_one[3], result_value_one[4],
result_value_one[5])
if len(keys) == 1:
html_str += summary_html_one
continue
for key_index in range(1, len(keys)):
result_value = result.result_dict[keys[key_index]]
summary_html = """
<tr>
<td>%s</td>
<td>%s</td>
<td>%s</td>
<td>%s%%</td>
<td>%s</td>
<td>%s</td>
<td>%s</td>
</tr>
""" % (keys[key_index], result_value[0], result_value[1],
result_value[2], result_value[3], result_value[4],
result_value[5])
summary_html_one += summary_html
html_str += summary_html_one
return html_str + "</table>"
def fetch_disk(self, lines):
"""
获取 disk 的关键数据包括: disk-read(KB/S),disk-write(KB/S),io(io/s),disk-busy(%)
:param lines: 带 disk 关键数据行
"""
# 累加和
diskread_sum = float(0)
diskwrite_sum = float(0)
diskio_sum = float(0)
# diskbusy 每列均值
diskbusy_avg = []
# diskbusy 最大值
diskbusy_max = float(0)
# 次数统计
diskread_num = 0
diskwrite_num = 0
diskio_num = 0
diskbusy_num = 0
for line in lines:
disks = line.split(",")
if "DISKREAD,T" in line:
# diskread
disk_read_line_sum = float(0)
# 统计每行之和
for diskread_index in range(2, len(disks)):
disk_read_line_sum += float(disks[diskread_index])
# 累加
diskread_sum += disk_read_line_sum
# 计算总行数
diskread_num += 1
elif "DISKWRITE,T" in line:
# diskwrite
disk_write_line_sum = float(0)
# 统计每行之和
for diskwrite_index in range(2, len(disks)):
disk_write_line_sum += float(disks[diskwrite_index])
# 累加
diskwrite_sum += disk_write_line_sum
# 计算总行数
diskwrite_num += 1
elif "DISKXFER,T" in line:
# 每秒 IO 操作次数
disk_io_line_sum = float(0)
# 统计每行之和
for diskio_index in range(2, len(disks)):
disk_io_line_sum += float(disks[diskio_index])
# 累加
diskio_sum += disk_io_line_sum
# 计算总行数
diskio_num += 1
elif "DISKBUSY,T" in line:
# 获取 busi 每列初始值
if len(diskbusy_avg) == 0:
for disk_busy_line_index in range(2, len(disks)):
diskbusy_avg.append(float(disks[disk_busy_line_index]))
else:
diskbusy_num += 1
# 计算 busi 每列均值
for disk_busy_line_index in range(2, len(disks)):
diskbusy_avg[disk_busy_line_index - 2] = (
float(diskbusy_avg[disk_busy_line_index - 2]) *
diskbusy_num + float(disks[disk_busy_line_index])
) / (diskbusy_num + 1)
# 获取 busi 最大列的均值
for disk_busy in diskbusy_avg:
if disk_busy > diskbusy_max:
diskbusy_max = disk_busy
self.disk = (round(diskread_sum / diskread_num,
2), round(diskwrite_sum / diskwrite_num,
2), round(diskio_sum / diskio_num,
2), round(diskbusy_max, 2))
logger.debug(
"disk: diskread %.2f, diskwrite %.2f, diskio %.2f, diskbusy %.2f%%"
% (self.disk[0], self.disk[1], self.disk[2], self.disk[3]))
def fetch_net(self, lines):
"""
获取 net read(KB/s) 和 write(KB/s) 均值
:param lines:包含 net 关键数据的行
:return:
"""
# read 列索引
net_read_index = []
# write 列索引
net_write_index = []
# 所有 raad 列均值
net_read = []
# 所有 write 列均值
net_write = []
# read 列均值最大值
net_read_max = float(0)
# write 列均值最大值
net_write_max = float(0)
for line in lines:
disks = line.split(",")
if not "NET,T" in line:
for net_name_index in range(2, len(disks)):
net_name = disks[net_name_index]
# 获取 read 所在列
if "read" in net_name:
avg_read = 0
net_read_index.append(net_name_index)
# 获取 write 所在列
elif "write" in net_name:
avg_write = 0
net_write_index.append(net_name_index)
else:
# 获取每个 read 列的均值
if not len(net_read_index) == 0:
avg_read += 1
net_read_len_index = 0
for net_read_num_index in net_read_index:
if avg_read == 1:
net_read.append(float(disks[net_read_num_index]))
else:
net_read[net_read_len_index] = (
float(net_read[net_read_len_index]) *
(avg_read - 1) +
float(disks[net_read_num_index])) / avg_read
net_read_len_index += 1
# 获取每个 write 列的均值
if not len(net_write_index) == 0:
avg_write += 1
net_write_len_index = 0
for net_write_num_index in net_write_index:
if avg_write == 1:
net_write.append(float(disks[net_write_num_index]))
else:
net_write[net_write_len_index] = (
float(net_write[net_write_len_index]) *
(avg_write - 1) +
float(disks[net_write_num_index])) / avg_write
net_write_len_index += 1
for net_read_avg in net_read:
if net_read_avg > net_read_max:
net_read_max = net_read_avg
for net_write_avg in net_write:
if net_write_avg > net_write_max:
net_write_max = net_write_avg
self.net = (round(net_read_max, 2), round(net_write_max, 2))
logger.debug("net: 网络读取最大值 %.2f, 网络写入最大值 %.2f" %
(self.net[0], self.net[1]))
def lr_cmd(script_file, path):
"""
获取路径生成执行脚本命令
"""
cmd_list = []
cmd_anaylise_list = []
result_file_list = []
# cmd = r'C:\"Program Files (x86)"\HP\LoadRunner\bin\wlrun -TestPath '
cmd = r'wlrun -TestPath '
# cmd_analyse = r'C:\"Program Files (x86)"\HP\LoadRunner\bin\AnalysisUI -RESULTPATH '
cmd_analyse = r'AnalysisUI -RESULTPATH '
for file in script_file:
command = cmd + path + os.path.sep + file + ".lrs" + " -Run -ResultName " + path + os.path.sep + file
command_analyse = cmd_analyse + path + os.path.sep + file + os.path.sep + file + ".lrr -TEMPLATENAME html"
cmd_list.append(command)
cmd_anaylise_list.append(command_analyse)
result_file_list.append(path + os.path.sep + file)
logger.debug("生成的 lr 命令")
logger.debug(cmd_list)
logger.debug("生成的 lr 解析命令")
logger.debug(cmd_anaylise_list)
logger.debug("loadrunner 结果文件保存路径")
logger.debug(result_file_list)
return cmd_list, cmd_anaylise_list, result_file_list
def file_analyse(self, file):
"""
解析 Loadrunner 报告
:param file: loadrunner 报告所在路径
"""
try:
logger.info("开始解析 %s loadrunner 报告" % os.path.basename(file))
super().file_analyse(file)
tps_list = []
resp_avg_list = []
resp_min_list = []
resp_max_list = []
summary_html_path = file + r'\An_Report1\summary.html'
content_html_path = file + r'\An_Report1\contents.html'
with open(summary_html_path, "r",
encoding='utf8') as summary_html_file:
summary_str = summary_html_file.read()
transaction_name_list = re.findall(
r'headers="LraTransaction Name".*?8">(.*?)</td>',
summary_str)
logger.debug(
"trasaction_name_list is None: %s" %
str(False if
(transaction_name_list is not None) else True))
pass_list = re.findall(r'headers="LraPass".*?8">(.*?)</td>',
summary_str)
logger.debug("pass_list is None: %s" %
str(False if (pass_list is not None) else True))
fail_list = re.findall(r'headers="LraFail".*?8">(.*?)</td>',
summary_str)
logger.debug("fail_list is None: %s" %
str(False if (fail_list is not None) else True))
if not pass_list or not fail_list or not transaction_name_list:
raise CustomError("%s 有未匹配到的数据" % self.name)
# TPS 从 TPS html 页面中获取, 先从 contents.html 获取到 TPS html 名称
# Respnse Time 从 Response Time html 页面中获取,先从 contents.html 获取到 Response Time html 名称
with open(content_html_path, "r",
encoding='utf8') as content_html_file:
content_str = content_html_file.read()
tps_html_name_match = re.match(
r'[\s\S]*href="(.*?)" Target.*?>Transactions per Second',
content_str)
response_time_html_name_match = re.match(
r'[\s\S]*href="(.*?)" Target.*?>Average Transaction Response Time',
content_str)
if tps_html_name_match is None:
raise CustomError("%s 未找到 tps html 报告" % self.name)
elif response_time_html_name_match is None:
raise CustomError("%s 未找到 Respnse Time html 报告" %
self.name)
tps_html_name = tps_html_name_match.group(1)
logger.debug("%s tps html name %s " %
(os.path.basename(file), tps_html_name))
tps_html_path = file + r'\An_Report1' + os.path.sep + tps_html_name
logger.debug("%s tps html path %s " %
(os.path.basename(file), tps_html_path))
response_time_html_name = response_time_html_name_match.group(
1)
logger.debug("%s response time html name %s" %
(os.path.basename(file), response_time_html_name))
response_time_html_path = file + r'\An_Report1' + os.path.sep + response_time_html_name
logger.debug("%s response time html path %s" %
(os.path.basename(file), response_time_html_path))
self.fetch_tps(tps_html_path, tps_list)
self.fetch_resp_time(response_time_html_path, resp_avg_list,
resp_min_list, resp_max_list)
# 长整数取到的数字带有逗号,例如1024是1,024,在取数字时,先将逗号去掉
for index in range(0, len(transaction_name_list)):
transaction_name = transaction_name_list[index]
logger.debug("transaction name %s" % transaction_name)
tps = tps_list[index]
logger.debug("tps %s" % tps)
pass_tsc = pass_list[index].replace(",", "")
logger.debug("pass transaction: %s" % pass_tsc)
fail_tsc = fail_list[index].replace(",", "")
logger.debug("fail transaction: %s" % fail_tsc)
# 时间转化成 ms 单位
resp_avg = resp_avg_list[index]
logger.debug("resp average time : %sms" % resp_avg)
resp_max = resp_max_list[index]
logger.debug("resp max time: %sms" % resp_max)
resp_min = resp_min_list[index]
logger.debug("resp min time: %sms" % resp_min)
all_tsc = str(int(fail_tsc) + int(pass_tsc))
error = round(int(fail_tsc) / int(all_tsc) * 100, 2)
# list: [Transaction, TPS, Error%, Response Time(average), Response Time(min), Response Time(max)]
data_list = [all_tsc, tps, error, resp_avg, resp_min, resp_max]
# dict:{transaction name:list}
self.result_dict[transaction_name] = data_list
finally:
logger.info("%s loadrunner 报告解析结束" % os.path.basename(file))
