Parse HTML file using Python without external modu

2019-08-14 19:00发布

I am trying to Parse a html file using Python without using any external module. The reason is I am triggering a jenkins job and running into some import issues with lxml and BeautifulSoup (tried resolving it and I think somewhere I am doing over engineering to get my stuff done)

Input:

    <tr class="test">
    <td class="test">
      <a href="a.html">BA</a>
    </td>
    <td class="duration">
      0.000s
    </td>

        <td class="zero number">0</td>

        <td class="zero number">0</td>

        <td class="zero number">0</td>

    <td class="passRate">
            N/A
          </td>
  </tr>

  <tr class="test">
    <td class="test">
      <a href="o.html">Aa</a>
    </td>
    <td class="duration">
      0.000s
    </td>

        <td class="zero number">0</td>

        <td class="zero number">0</td>

        <td class="zero number">0</td>

    <td class="passRate">
            N/A
          </td>
  </tr>

  <tr class="test">
    <td class="test">
      <a href="g.html">VideoAds</a>
    </td>
    <td class="duration">
      0.390s
    </td>

        <td class="zero number">0</td>

        <td class="zero number">0</td>

        <td class="zero number">0</td>

    <td class="passRate">
            N/A
          </td>
  </tr>

  <tr class="suite">
    <td colspan="2" class="totalLabel">Total</td>

        <td class="zero number">271</td>

        <td class="zero number">0</td>

        <td class="zero number">3</td>

    <td class="passRate suite">
            98%
          </td>

  </tr>

Output:

I want to take that specific block of tr tag with the class "suite" (check at the end) and then pull the values for Zero number, Zero number, Zero number and passRate suite. Finally, print the values.

~~~~~~~~~~~~~~~~~~~~~~~~~~

Eg. Zero number = 271 ...

Pass rate = 98%

~~~~~~~~~~~~~~~~~~~~~~~~~~ Here is what I tried with lxml:

tree = parse(HTML_FILE)
tds = tree.xpath("//tr[@class='suite']//td/text()")
val = map(str.strip, tds)

This works out locally but I really want to do something without any external dependencies. Shall I use strip() or open a file using os.path.isFile(). I may not be correct but advise/walk me through what would be solution to do this.

2条回答
狗以群分
2楼-- · 2019-08-14 19:23
import re

f = open(HTML_FILE)
data = f.read()
before = '<td colspan="2" class="totalLabel">Total</td>'
after  = '%<'
start = data.find(before) + len(before)
stop  = data.find(after, start)

suite_filter = data[start:stop].strip()

RATE_PASS = re.search('suite">[ \n]+(\d+)', suite_filter).group(1)
PASS_COUNT = re.search('passed number">(\d+)', suite_filter).group(1)
SKIPPED_COUNT = re.search('zero number">(\d+)', suite_filter).group(1)

FAIL_COUNT = re.search('failed number">(\d+)', suite_filter).group(1)

TESTS_TOTAL = int(PASS_COUNT) + int(SKIPPED_COUNT) + int(FAIL_COUNT)

print RATE_PASS, PASS_COUNT, SKIPPED_COUNT, TESTS_TOTAL

Here is my solution as per the suggestions from @furas. Any improvements/suggestions are welcomed.

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聊天终结者
3楼-- · 2019-08-14 19:30

For one element you could try to use re module or even string functions.

data = '''<tr class="test">
<td class="test">
<a href="no.html">track</a></td>
<td class="duration">0.390s</td>
<td class="zero number">0</td>
<td class="zero number">0</td>
<td class="zero number">0</td>
<td class="passRate">N/A</td></tr>

<tr class="suite">
<td colspan="2" class="totalLabel">Total</td>
<td class="passed number">271</td>
<td class="zero number">0</td>
<td class="failed number">3</td>
<td class="passRate suite">98%</td>
</tr>'''

# re module

import re

print(re.search('suite">(\d+)%', data).group(1))

# string functions

before = 'passRate suite">'
after  = '%'
start = data.find(before) + len(before)
stop  = data.find(after, start)

print(data[start:stop])

EDIT: to get othere values with re

import re

print('passed:', re.search('passed number">(\d+)', data).group(1))
print('zero:', re.search('zero number">(\d+)', data).group(1))
print('failed:', re.search('zero number">(\d+)', data).group(1))
print('Rate:', re.search('suite">(\d+)', data).group(1))

passed: 271
zero: 0
failed: 0
Rate: 98
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