无法在电子商务工具库中用 scikit-learn 完全替换已弃用的 sklearn 包

Question

import pandas as pd
import re
from tqdm import tqdm
from ecommercetools import seo

Querylist1 = ['denmark, inflation',
 'denmark, immigration',
 'denmark, global warming',
 'toronto, inflation',
 'toronto, immigration',
 'toronto, global warming',
 'washington, inflation',
]

targets = []
for query in tqdm(Querylist1):
  pages_num = 5

  conditions = ['wikipedia','twitter','linkedin','facebook','news'] 
  # Step 4.3: the main body. 
  try:
    res = seo.get_serps(query, pages=pages_num)
  except:
    continue
  for c in conditions[:]:
    temp1 = res[res['link'].str.contains(c,case=False)]['title'].to_list()
    temp2 = res[res['link'].str.contains(c,case=False)]['link'].to_list()
    if len(temp1)==0:
      y = ''
    else:
      y = temp1[0]
    if len(temp2)==0:
      z = ''
      continue
    else:
      z = temp2[0]
    targets.append([y,z,c,query])

targets = pd.DataFrame(targets, columns=['title','link','link category','query keyword used'])

print(targets)

这是一个简单的脚本。但是当我运行

pip install ecommercetools

时显示以下错误：

PS C:\Users\DELL\Desktop\New folder> pip install ecommercetools
Collecting ecommercetools
  Using cached ecommercetools-0.42.9-py3-none-any.whl.metadata (54 kB)
Collecting gapandas (from ecommercetools)
  Using cached gapandas-1.0-py3-none-any.whl.metadata (4.1 kB)
Collecting httplib2>=0.15.0 (from ecommercetools)
  Using cached httplib2-0.22.0-py3-none-any.whl.metadata (2.6 kB)
Collecting lifetimes (from ecommercetools)
  Using cached Lifetimes-0.11.3-py3-none-any.whl.metadata (4.8 kB)
Requirement already satisfied: numpy in c:\users\dell\appdata\local\programs\python\python311\lib\site-packages (from ecommercetools) (1.26.3)
Requirement already satisfied: pandas in c:\users\dell\appdata\local\programs\python\python311\lib\site-packages (from ecommercetools) (2.2.0)
Collecting pycausalimpact (from ecommercetools)
  Using cached pycausalimpact-0.1.1-py2.py3-none-any.whl.metadata (8.3 kB)
Requirement already satisfied: requests in c:\users\dell\appdata\local\programs\python\python311\lib\site-packages (from ecommercetools) (2.31.0)
Requirement already satisfied: requests-html in c:\users\dell\appdata\local\programs\python\python311\lib\site-packages (from ecommercetools) (0.10.0)
Collecting sklearn (from ecommercetools)
  Using cached sklearn-0.0.post12.tar.gz (2.6 kB)
  Preparing metadata (setup.py) ... error
  error: subprocess-exited-with-error

  × python setup.py egg_info did not run successfully.
  │ exit code: 1
  ╰─> [15 lines of output]
      The 'sklearn' PyPI package is deprecated, use 'scikit-learn'
      rather than 'sklearn' for pip commands.

      Here is how to fix this error in the main use cases:
      - use 'pip install scikit-learn' rather than 'pip install sklearn'
      - replace 'sklearn' by 'scikit-learn' in your pip requirements files
        (requirements.txt, setup.py, setup.cfg, Pipfile, etc ...)
      - if the 'sklearn' package is used by one of your dependencies,
        it would be great if you take some time to track which package uses
        'sklearn' instead of 'scikit-learn' and report it to their issue tracker
      - as a last resort, set the environment variable
        SKLEARN_ALLOW_DEPRECATED_SKLEARN_PACKAGE_INSTALL=True to avoid this error

      More information is available at
      https://github.com/scikit-learn/sklearn-pypi-package
      [end of output]

  note: This error originates from a subprocess, and is likely not a problem with pip.
error: metadata-generation-failed

× Encountered error while generating package metadata.
╰─> See above for output.

note: This is an issue with the package mentioned above, not pip.
hint: See above for details.

我还安装了scikit-learn。但安装 ecommercetools 显示相同的错误。 我能看到的唯一可以理解的是：

Collecting sklearn (from ecommercetools)
  Using cached sklearn-0.0.post12.tar.gz (2.6 kB)
  Preparing metadata (setup.py) ... error

我认为当我运行

pip install ecommercetools

时，它会尝试安装默认的sklearn而不是我安装的新软件包（scikit-learn）

如有任何帮助，我们将不胜感激

如上所述

Answer 1

要用 scikit-learn 替换已弃用的 sklearn，请识别并更新依赖于过时功能的代码部分，并在需要时使用兼容的替代方案。检查更广泛的库兼容性并查看 scikit-learn 的文档以获取解决方案或解决方法。