Question

我正在尝试从k6输出（https://docs.k6.io/docs/results-output）中提取数据：

Col_Strings       2C    GAD D2  6F  ABCDE
2C 1B D2 6F ABC    1    0   1   1   0
Act Dog House GAD  0    1   0   0   0
D2 6F Ant          0    0   1   1   0

数据采用上述格式，我试图找到一种方法来获取上面的每一行以及值。举个例子：

data_received.........: 246 kB 21 kB/s
data_sent.............: 174 kB 15 kB/s
http_req_blocked......: avg=26.24ms  min=0s      med=13.5ms  max=145.27ms p(90)=61.04ms p(95)=70.04ms 
http_req_connecting...: avg=23.96ms  min=0s      med=12ms    max=145.27ms p(90)=57.03ms p(95)=66.04ms 
http_req_duration.....: avg=197.41ms min=70.32ms med=91.56ms max=619.44ms p(90)=288.2ms p(95)=326.23ms
http_req_receiving....: avg=141.82µs min=0s      med=0s      max=1ms      p(90)=1ms     p(95)=1ms     
http_req_sending......: avg=8.15ms   min=0s      med=0s      max=334.23ms p(90)=1ms     p(95)=1ms     
http_req_waiting......: avg=189.12ms min=70.04ms med=91.06ms max=343.42ms p(90)=282.2ms p(95)=309.22ms
http_reqs.............: 190    16.054553/s
iterations............: 5      0.422488/s
vus...................: 200    min=200 max=200
vus_max...............: 200    min=200 max=200

我必须为~50-100个文件执行此操作，并希望找到一个RegEx或类似的更快的方法来执行此操作，而无需编写太多代码。有可能吗？

Answer 1

这是一个简单的Python解决方案：

import re

FIELD = re.compile(r"(\w+)\.*:(.*)", re.DOTALL)  # split the line to name:value
VALUES = re.compile(r"(?<==).*?(?=\s|$)")  # match individual values from http_req_* fields

# open the input file `k6_input.log` for reading, and k6_parsed.log` for parsing
with open("k6_input.log", "r") as f_in, open("k6_parsed.log", "w") as f_out:
    for line in f_in:  # read the input file line by line
        field = FIELD.match(line)  # first match all <field_name>...:<values> fields
        if field:
            name = field.group(1)  # get the field name from the first capture group
            f_out.write(name + ": ")  # write the field name to the output file
            value = field.group(2)  # get the field value from the second capture group
            if name[:9] == "http_req_":  # parse out only http_req_* fields
                f_out.write(", ".join(VALUES.findall(value)) + "\n")  # extract the values
            else:  # verbatim copy of other fields
                f_out.write(value)
        else:  # encountered unrecognizable field, just copy the line
            f_out.write(line)

对于包含上述内容的文件，您将获得结果：

data_received:  246 kB 21 kB/s
data_sent:  174 kB 15 kB/s
http_req_blocked: 26.24ms, 0s, 13.5ms, 145.27ms, 61.04ms, 70.04ms
http_req_connecting: 23.96ms, 0s, 12ms, 145.27ms, 57.03ms, 66.04ms
http_req_duration: 197.41ms, 70.32ms, 91.56ms, 619.44ms, 288.2ms, 326.23ms
http_req_receiving: 141.82µs, 0s, 0s, 1ms, 1ms, 1ms
http_req_sending: 8.15ms, 0s, 0s, 334.23ms, 1ms, 1ms
http_req_waiting: 189.12ms, 70.04ms, 91.06ms, 343.42ms, 282.2ms, 309.22ms
http_reqs:  190    16.054553/s
iterations:  5      0.422488/s
vus:  200    min=200 max=200
vus_max:  200    min=200 max=200

如果您必须在许多文件上运行它，我建议您调查os.glob()，os.walk()或os.listdir()以列出您需要的所有文件，然后循环他们并执行上述步骤，从而进一步自动化该过程。

从k6数据中解析输出以获取特定信息

1 个答案: