使用BioPython，如何为给定的一对搜索词而不是多行以一行（逗号分隔）打印DOI引用？

Question

首先是StackOverflow的人们，感谢您的耐心等待。我了解这是我在该主题上的第三个话题，但是由于一无所获，而且我什至不知道从哪里开始（我不知道我不知道的地方），我想我会在这里问无论如何。我正在尝试使用Biopython从PMC中提取引用，以写回CSV文件，其中包括植物名称，其治愈的相关疾病/病症/药物作用以及所引用的DOI URL给定的植物疾病对。经过许多小时的尝试去理解该怎么做，并与经验丰富的人讨论了我的代码，这才最终在Visual Studio Code中输入：

  for plant, disease in plant_disease_list:
    search_query = generate_search_query(plant, disease)
    handle1 = Entrez.esearch(db="pmc", term=search_query, retmax="10")
    record1 = Entrez.read(handle1)
    pubmed_ids = record1.get("IdList")
    if len(pubmed_ids)==0:
      print("{}, {}, None".format(plant, disease))
    else:
      for pubmed_id in pubmed_ids:
        handle2 = Entrez.esummary(db="pmc", id=pubmed_id)
        records = Entrez.read(handle2)
        for record in records:
          doi = record.get("DOI")
          if doi is None:
           print(("{}, {}".format(plant, disease)))
          else:
            doi_main = doi.split()
            string = "http://doi.org/"
            to_add = (",").join((string + x) for x in doi_main)
            print("{}, {},".format(plant, disease), to_add, sep="")

其中generate_search_query先前定义为：

def generate_search_query(plant, disease):
  search_query = '"{}" AND "{}"'.format(plant, disease)
  return search_query

这是我得到的输出：

Asystasia salicifalia, Puerperal illness, None
Asystasia salicifalia, Puerperium, None
Asystasia salicifalia, Puerperal disorder, None
Barleria strigosa, Tonic
Justicia procumbens, Lumbago, None
Justicia procumbens, Itching,http://doi.org/10.1673/031.012.0501
Strobilanthes auriculata, Malnutrition, None
Thunbergia laurifolia, Detoxificant, None
Thunbergia similis, Tonic, None
Lannea coromandelica, Dizziness,http://doi.org/10.3897/phytokeys.102.24380
Lannea coromandelica, Dizziness,http://doi.org/10.1186/s13002-016-0089-8
Lannea coromandelica, Dizziness,http://doi.org/10.1186/s13002-015-0033-3
Spondias pinnata, Flatulence,http://doi.org/10.1016/j.heliyon.2019.e02768
Spondias pinnata, Flatulence,http://doi.org/10.1186/s13002-019-0287-2
Spondias pinnata, Flatulence,http://doi.org/10.1186/s13002-018-0248-1
Spondias pinnata, Flatulence,http://doi.org/10.3897/phytokeys.102.24380
Spondias pinnata, Flatulence,http://doi.org/10.1155/2018/5382904
Spondias pinnata, Flatulence,http://doi.org/10.1186/s13002-016-0089-8
Spondias pinnata, Flatulence,http://doi.org/10.1186/s13002-015-0033-3
Spondias pinnata, Flatulence,http://doi.org/10.1186/1472-6882-13-243
Spondias pinnata, Flatulence,http://doi.org/10.1186/1472-6882-10-77
Holarrhena pubescens, Diarrhoea,http://doi.org/10.5455/javar.2019.f379
Holarrhena pubescens, Diarrhoea,http://doi.org/10.1155/2019/2321961
Holarrhena pubescens, Diarrhoea,http://doi.org/10.1186/s12906-018-2348-9
Traceback (most recent call last):
  File "scraperscript_python.py", line 33, in <module>
    handle2 = Entrez.esummary(db="pmc", id=pubmed_id)
  File "C:\Users\ASUS\AppData\Local\Programs\Python\Python37\lib\site-packages\Bio\Entrez\__init__.py", line 334, in esummary
    return _open(cgi, variables)
  File "C:\Users\ASUS\AppData\Local\Programs\Python\Python37\lib\site-packages\Bio\Entrez\__init__.py", line 569, in _open
    handle = _urlopen(cgi)
  File "C:\Users\ASUS\AppData\Local\Programs\Python\Python37\lib\urllib\request.py", line 222, in urlopen
    return opener.open(url, data, timeout)
  File "C:\Users\ASUS\AppData\Local\Programs\Python\Python37\lib\urllib\request.py", line 525, in open
    response = self._open(req, data)
  File "C:\Users\ASUS\AppData\Local\Programs\Python\Python37\lib\urllib\request.py", line 543, in _open
    '_open', req)
  File "C:\Users\ASUS\AppData\Local\Programs\Python\Python37\lib\urllib\request.py", line 503, in _call_chain
    result = func(*args)
  File "C:\Users\ASUS\AppData\Local\Programs\Python\Python37\lib\urllib\request.py", line 1362, in https_open
    context=self._context, check_hostname=self._check_hostname)
  File "C:\Users\ASUS\AppData\Local\Programs\Python\Python37\lib\urllib\request.py", line 1319, in do_open
    encode_chunked=req.has_header('Transfer-encoding'))
  File "C:\Users\ASUS\AppData\Local\Programs\Python\Python37\lib\http\client.py", line 1252, in request
    self._send_request(method, url, body, headers, encode_chunked)
  File "C:\Users\ASUS\AppData\Local\Programs\Python\Python37\lib\http\client.py", line 1298, in _send_request
    self.endheaders(body, encode_chunked=encode_chunked)
  File "C:\Users\ASUS\AppData\Local\Programs\Python\Python37\lib\http\client.py", line 1247, in endheaders
    self._send_output(message_body, encode_chunked=encode_chunked)
  File "C:\Users\ASUS\AppData\Local\Programs\Python\Python37\lib\http\client.py", line 1026, in _send_output
    self.send(msg)
  File "C:\Users\ASUS\AppData\Local\Programs\Python\Python37\lib\http\client.py", line 966, in send
    self.connect()
  File "C:\Users\ASUS\AppData\Local\Programs\Python\Python37\lib\http\client.py", line 1422, in connect
    server_hostname=server_hostname)
  File "C:\Users\ASUS\AppData\Local\Programs\Python\Python37\lib\ssl.py", line 423, in wrap_socket
    session=session
  File "C:\Users\ASUS\AppData\Local\Programs\Python\Python37\lib\ssl.py", line 870, in _create
    self.do_handshake()
  File "C:\Users\ASUS\AppData\Local\Programs\Python\Python37\lib\ssl.py", line 1139, in do_handshake
    self._sslobj.do_handshake()
KeyboardInterrupt

其余的输出被我打断了，因为我不希望它在整个数据上运行，因为它以不正确的格式打印它。如通过Spondias pinnata和肠胃气胀的示例所看到的，您可以看到它正在不同的行中打印不同的DOI URL。问题是我不希望它那样打印，因为将它放回到原始数据中非常困难。例如，此CSV文件只有65个条目，但是有些数据集包含8000个以上的条目，这使它非常困难。例如，我希望实现的输出应如下所示（当我们考虑上述植物疾病对时）：

Spondias pinnata, Flatulence, http://doi.org/10.1016/j.heliyon.2019.e02768, http://doi.org/10.1186/s13002-019-0287-2, http://doi.org/10.1186/s13002-018-0248-1, http://doi.org/10.3897/phytokeys.102.24380, http://doi.org/10.1155/2018/5382904, http://doi.org/10.1186/s13002-016-0089-8, http://doi.org/10.1186/s13002-015-0033-3, http://doi.org/10.1186/1472-6882-13-243, http://doi.org/10.1186/1472-6882-10-77

我的家人建议我使用嵌套字典，但是我看不到如何/是否有帮助，而且我也不知道将其放置在代码中的位置，以及对已经高度嵌套的嵌套进行哪些更改循环。任何帮助，将不胜感激。谢谢。

Answer 1

以下代码：

from Bio import Entrez
import csv
Entrez.email = "[email protected]"


botanical_names = ['Asystasia salicifalia', 'Asystasia salicifalia', 'Asystasia salicifalia', 'Barleria strigosa', 'Justicia procumbens', 'Justicia procumbens', 'Strobilanthes auriculata', 'Thunbergia laurifolia', 'Thunbergia similis', 'Lannea coromandelica', 'Spondias pinnata']
diseases = ['Puerperal illness', 'Puerperium', 'Puerperal disorder', 'Tonic', 'Lumbago', 'Itching', 'Malnutrition', 'Detoxificant', 'Tonic', 'Dizziness', 'Flatulence']

assert len(botanical_names) == len(diseases)

plant_disease_list = zip(botanical_names, diseases)


with open('plant_diseases.csv', 'w', newline='') as csvfile:
    fieldnames = ['plant', 'disease', 'dois']
    writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
    writer.writeheader()

    for plant, disease in plant_disease_list:
      result = {'plant': plant,
                'disease': disease}
      search_query = '"{}" AND "{}"'.format(plant, disease)
      handle1 = Entrez.esearch(db="pmc", term=search_query, retmax="10")
      record1 = Entrez.read(handle1)
      pubmed_ids = record1.get("IdList")
      if pubmed_ids:
        handle2 = Entrez.esummary(db="pmc", id=','.join(pubmed_ids))
        records = Entrez.read(handle2)
        dois = [record.get("DOI") for record in records if record.get("DOI")  is not None]
        prefix = "http://doi.org/"
        dois = ','.join([prefix + doi for doi in dois])
        result['dois'] = dois
      writer.writerow(result)

将以下输出写入文件plant_diseases.csv：

plant,disease,dois
Asystasia salicifalia,Puerperal illness,
Asystasia salicifalia,Puerperium,
Asystasia salicifalia,Puerperal disorder,
Barleria strigosa,Tonic,
Justicia procumbens,Lumbago,
Justicia procumbens,Itching,http://doi.org/10.1673/031.012.0501
Strobilanthes auriculata,Malnutrition,
Thunbergia laurifolia,Detoxificant,
Thunbergia similis,Tonic,
Lannea coromandelica,Dizziness,"http://doi.org/10.3897/phytokeys.102.24380,http://doi.org/10.1186/s13002-016-0089-8,http://doi.org/10.1186/s13002-015-0033-3"
Spondias pinnata,Flatulence,"http://doi.org/10.1016/j.heliyon.2019.e02768,http://doi.org/10.1186/s13002-019-0287-2,http://doi.org/10.1186/s13002-018-0248-1,http://doi.org/10.3897/phytokeys.102.24380,http://doi.org/10.1155/2018/5382904,http://doi.org/10.1186/s13002-016-0089-8,http://doi.org/10.1186/s13002-015-0033-3,http://doi.org/10.1186/1472-6882-13-243,http://doi.org/10.1186/1472-6882-10-77"

注意，我已经使用csv模块来创建valid CSV文件。这包括在逗号分隔的DOI列表周围添加双qoutes，以将其与用于描述植物和疾病的逗号分隔。另外，如果您没有DOI，则无需添加“无”占位符。由于第一行包含标题，因此csv模块知道应该在每行中查找三个字段。

也请不要使用string作为变量名，因为它是a Python module in the standard library的名称。