用Python代码自动生成文献的IEEE引用格式的实现

今天尝试着将引用文献的格式按照IEEE的标准重新排版，感觉手动一条一条改太麻烦，而且很容易出错，所以尝试着用Python写了一个小程序用于根据BibTeX引用格式来生成IEEE引用格式。

先看代码，如下：

import re

def getIeeeJournalFormat(bibInfo):
 """
 生成期刊文献的IEEE引用格式：{作者}, "{文章标题}," {期刊名称}, vol. {卷数}, no. {编号}, pp. {页码}, {年份}.
 :return: {author}, "{title}," {journal}, vol. {volume}, no. {number}, pp. {pages}, {year}.
 """
 # 避免字典出现null值
 if "volume" not in bibInfo:
   bibInfo["volume"] = "null"
 if "number" not in bibInfo:
   bibInfo["number"] = "null"
 if "pages" not in bibInfo:
   bibInfo["pages"] = "null"

journalFormat = bibInfo["author"] + \
     ", \"" + bibInfo["title"] + \
     ",\" " + bibInfo["journal"] + \
     ", vol. " + bibInfo["volume"] + \
     ", no. " + bibInfo["number"] + \
     ", pp. " + bibInfo["pages"] + \
     ", " + bibInfo["year"] + "."

# 对格式进行调整，去掉没有的信息，调整页码格式
 journalFormatNormal = journalFormat.replace(", vol. null", "")
 journalFormatNormal = journalFormatNormal.replace(", no. null", "")
 journalFormatNormal = journalFormatNormal.replace(", pp. null", "")
 journalFormatNormal = journalFormatNormal.replace("--", "-")
 return journalFormatNormal

def getIeeeConferenceFormat(bibInfo):
 """
 生成会议文献的IEEE引用格式：{作者}, "{文章标题}, " in {会议名称}, {年份}, pp. {页码}.
 :return: {author}, "{title}, " in {booktitle}, {year}, pp. {pages}.
 """
 conferenceFormat = bibInfo["author"] + \
         ", \"" + bibInfo["title"] + ",\" " + \
         ", in " + bibInfo["booktitle"] + \
         ", " + bibInfo["year"] + \
         ", pp. " + bibInfo["pages"] + "."

# 对格式进行调整，，调整页码格式
 conferenceFormatNormal = conferenceFormat.replace("--", "-")
 return conferenceFormatNormal

def getIeeeFormat(bibInfo):
 """
 本函数用于根据文献类型调用相应函数来输出ieee文献引用格式
 :param bibInfo: 提取出的BibTeX引用信息
 :return: ieee引用格式
 """
 if "journal" in bibInfo: # 期刊论文
   return getIeeeJournalFormat(bibInfo)
 elif "booktitle" in bibInfo: # 会议论文
   return getIeeeConferenceFormat(bibInfo)

def inforDir(bibtex):
 #pattern = "[\w]+={[^{}]+}"  用正则表达式匹配符合 ...={...} 的字符串
 pattern1 = "[\w]+=" # 用正则表达式匹配符合 ...= 的字符串
 pattern2 = "{[^{}]+}" # 用正则表达式匹配符合 内层{...} 的字符串

# 找到所有的...=，并去除=号
 result1 = re.findall(pattern1, bibtex)
 for index in range(len(result1)) :
   result1[index] = re.sub('=', '', result1[index])
 # 找到所有的{...}，并去除{和}号
 result2 = re.findall(pattern2, bibtex)
 for index in range(len(result2)) :
   result2[index] = re.sub('\{', '', result2[index])
   result2[index] = re.sub('\}', '', result2[index])

# 创建BibTeX引用字典，归档所有有效信息
 infordir = {}
 for index in range(len(result1)):
   infordir[result1[index]] = result2[index]
 return infordir

def inputBibTex():
 """
 在这里输入BibTeX格式的文献引用信息
 :return:提取出的BibTeX引用信息
 """
 bibtex = []
 print("请输入BibTeX格式的文献引用：")
 i = 0
 while i < 15: # 观察可知BibTeX格式的文献引用不会多于15行
   lines = input()
   if len(lines) == 0: # 如果输入空行，则说明引用内容已经输入完毕
     break
   else:
     bibtex.append(lines)
   i += 1
 return inforDir("".join(bibtex))

if __name__ == '__main__':
 bibInfo = inputBibTex() # 获得BibTeX格式的文献引用
 print(getIeeeFormat(bibInfo)) # 输出ieee格式

下面我来详细说说这个代码怎么使用。

首先，我们需要获取到文献的BibTeX引用格式，可以在百度学术，或者谷歌学术的应用栏中找到，例如这里以谷歌学术举例：

在搜索框搜索论文：Reinforcement learning to rank in e-commerce search engine: Formalization, analysis, and application，跳转到以下页面：

点击“引用”，再点击“BibTex”

跳转到以下页面，复制所有字符串

运行我们上面给出的代码，在交互窗口把我们复制的字符串粘贴过去：

之后点击两下回车，即可得到IEEE格式的文献引用了：

这里我分了会议论文和期刊论文种格式，大家如果想要其他引用格式，可以在我的代码的基础上进行增删改，下面我放一些引用格式转换的例子：

会议论文1：

Reinforcement learning to rank in e-commerce search engine: Formalization, analysis, and application

BibTeX格式：

@inproceedings{hu2018reinforcement,
title={Reinforcement learning to rank in e-commerce search engine: Formalization, analysis, and application},
author={Hu, Yujing and Da, Qing and Zeng, Anxiang and Yu, Yang and Xu, Yinghui},
booktitle={Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining},
pages={368–377},
year={2018}
}

IEEE格式：

Hu, Yujing and Da, Qing and Zeng, Anxiang and Yu, Yang and Xu, Yinghui, “Reinforcement learning to rank in e-commerce search engine: Formalization, analysis, and application,” , in Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018, pp. 368-377.

会议论文2：

A contextual-bandit approach to personalized news article recommendation

BibTeX格式：

@inproceedings{li2010contextual,
title={A contextual-bandit approach to personalized news article recommendation},
author={Li, Lihong and Chu, Wei and Langford, John and Schapire, Robert E},
booktitle={Proceedings of the 19th international conference on World wide web},
pages={661–670},
year={2010}
}

IEEE格式：

Li, Lihong and Chu, Wei and Langford, John and Schapire, Robert E, “A contextual-bandit approach to personalized news article recommendation,” , in Proceedings of the 19th international conference on World wide web, 2010, pp. 661-670.

期刊论文1：

Infrared navigation-Part I: An assessment of feasibility

BibTeX格式：

@article{duncombe1959infrared,
title={Infrared navigation—Part I: An assessment of feasibility},
author={Duncombe, JU},
journal={IEEE Trans. Electron Devices},
volume={11},
number={1},
pages={34–39},
year={1959}
}

IEEE格式：

Duncombe, JU, “Infrared navigation—Part I: An assessment of feasibility,” IEEE Trans. Electron Devices, vol. 11, no. 1, pp. 34-39, 1959.

期刊论文2（arXiv）：

Reinforcement learning for slate-based recommender systems: A tractable decomposition and practical methodology

BibTeX格式：

@article{ie2019reinforcement,
title={Reinforcement learning for slate-based recommender systems: A tractable decomposition and practical methodology},
author={Ie, Eugene and Jain, Vihan and Wang, Jing and Narvekar, Sanmit and Agarwal, Ritesh and Wu, Rui and Cheng, Heng-Tze and Lustman, Morgane and Gatto, Vince and Covington, Paul and others},
journal={arXiv preprint arXiv:1905.12767},
year={2019}
}

IEEE格式：

Ie, Eugene and Jain, Vihan and Wang, Jing and Narvekar, Sanmit and Agarwal, Ritesh and Wu, Rui and Cheng, Heng-Tze and Lustman, Morgane and Gatto, Vince and Covington, Paul and others, “Reinforcement learning for slate-based recommender systems: A tractable decomposition and practical methodology,” arXiv preprint arXiv:1905.12767, 2019.

来源：https://blog.csdn.net/baishuiniyaonulia/article/details/114026471