Google Scholar 是否有 API 可供我们在研究申请中使用?
Does Google Scholar have an API available that we can use in our research applications?
我正在从事一项具有文献搜索功能的研究出版物和合作项目。
Google Scholar 似乎可以使用,因为它是一个开源工具,但是,当我研究 Google Scholar 时,我找不到任何关于它具有 API.[=12= 的信息]
如果 API 的 Google 学者有效,请告诉我。
TIA。
快速搜索显示其他人正在尝试实现此类 API,但 Google 未提供此类 API。目前尚不清楚这是否合法,例如参见
How to get permission from Google to use Google Scholar Data, if needed?.
There's no official Google Scholar API. There are third-party solutions like free scholarly
Python package which supports profile, author, cite results but does not support organic results, or Google Scholar API from SerpApi which is a paid API with a free plan that supports organic, cite, profile, author 结果并绕过 SerpApi 后端的所有块。
使用 search_by_keyword
方法使用 scholarly
解析配置文件结果的示例代码:
import json
from scholarly import scholarly
# will paginate to the next page by default
authors = scholarly.search_keyword("biology")
for author in authors:
print(json.dumps(author, indent=2))
# part of the output:
'''
{
"container_type": "Author",
"filled": [],
"source": "SEARCH_AUTHOR_SNIPPETS",
"scholar_id": "LXVfPc8AAAAJ",
"url_picture": "https://scholar.google.com/citations?view_op=medium_photo&user=LXVfPc8AAAAJ",
"name": "Eric Lander",
"affiliation": "Broad Institute",
"email_domain": "",
"interests": [
"Biology",
"Genomics",
"Genetics",
"Bioinformatics",
"Mathematics"
],
"citedby": 552013
}
... other author results
'''
使用来自 SerpApi 的 Google Scholar Profile Results API 解析有机结果的示例代码:
import json
from serpapi import GoogleScholarSearch
# search parameters
params = {
"api_key": "Your SerpApi API key",
"engine": "google_scholar_profiles",
"hl": "en", # language
"mauthors": "biology" # search query
}
search = GoogleScholarSearch(params)
results = search.get_dict()
# only first page results
for result in results["profiles"]:
print(json.dumps(result, indent=2))
# part of the output:
'''
{
"name": "Masatoshi Nei",
"link": "https://scholar.google.com/citations?hl=en&user=VxOmZDgAAAAJ",
"serpapi_link": "https://serpapi.com/search.json?author_id=VxOmZDgAAAAJ&engine=google_scholar_author&hl=en",
"author_id": "VxOmZDgAAAAJ",
"affiliations": "Laura Carnell Professor of Biology, Temple University",
"email": "Verified email at temple.edu",
"cited_by": 384074,
"interests": [
{
"title": "Evolution",
"serpapi_link": "https://serpapi.com/search.json?engine=google_scholar_profiles&hl=en&mauthors=label%3Aevolution",
"link": "https://scholar.google.com/citations?hl=en&view_op=search_authors&mauthors=label:evolution"
},
{
"title": "Evolutionary biology",
"serpapi_link": "https://serpapi.com/search.json?engine=google_scholar_profiles&hl=en&mauthors=label%3Aevolutionary_biology",
"link": "https://scholar.google.com/citations?hl=en&view_op=search_authors&mauthors=label:evolutionary_biology"
},
{
"title": "Molecular evolution",
"serpapi_link": "https://serpapi.com/search.json?engine=google_scholar_profiles&hl=en&mauthors=label%3Amolecular_evolution",
"link": "https://scholar.google.com/citations?hl=en&view_op=search_authors&mauthors=label:molecular_evolution"
},
{
"title": "Population genetics",
"serpapi_link": "https://serpapi.com/search.json?engine=google_scholar_profiles&hl=en&mauthors=label%3Apopulation_genetics",
"link": "https://scholar.google.com/citations?hl=en&view_op=search_authors&mauthors=label:population_genetics"
},
{
"title": "Phylogenetics",
"serpapi_link": "https://serpapi.com/search.json?engine=google_scholar_profiles&hl=en&mauthors=label%3Aphylogenetics",
"link": "https://scholar.google.com/citations?hl=en&view_op=search_authors&mauthors=label:phylogenetics"
}
],
"thumbnail": "https://scholar.googleusercontent.com/citations?view_op=small_photo&user=VxOmZDgAAAAJ&citpid=3"
}
... other results
'''
我在 SerpApi 有一个专门的 Scrape historic Google Scholar results using Python 博客 post,它展示了如何抓取历史性的 2017-2021 Organic,将 Google Scholar 结果引用到 CSV,SQLite。
Disclaimer, I work for SeprApi
我正在从事一项具有文献搜索功能的研究出版物和合作项目。 Google Scholar 似乎可以使用,因为它是一个开源工具,但是,当我研究 Google Scholar 时,我找不到任何关于它具有 API.[=12= 的信息]
如果 API 的 Google 学者有效,请告诉我。
TIA。
快速搜索显示其他人正在尝试实现此类 API,但 Google 未提供此类 API。目前尚不清楚这是否合法,例如参见 How to get permission from Google to use Google Scholar Data, if needed?.
There's no official Google Scholar API. There are third-party solutions like free scholarly
Python package which supports profile, author, cite results but does not support organic results, or Google Scholar API from SerpApi which is a paid API with a free plan that supports organic, cite, profile, author 结果并绕过 SerpApi 后端的所有块。
使用 search_by_keyword
方法使用 scholarly
解析配置文件结果的示例代码:
import json
from scholarly import scholarly
# will paginate to the next page by default
authors = scholarly.search_keyword("biology")
for author in authors:
print(json.dumps(author, indent=2))
# part of the output:
'''
{
"container_type": "Author",
"filled": [],
"source": "SEARCH_AUTHOR_SNIPPETS",
"scholar_id": "LXVfPc8AAAAJ",
"url_picture": "https://scholar.google.com/citations?view_op=medium_photo&user=LXVfPc8AAAAJ",
"name": "Eric Lander",
"affiliation": "Broad Institute",
"email_domain": "",
"interests": [
"Biology",
"Genomics",
"Genetics",
"Bioinformatics",
"Mathematics"
],
"citedby": 552013
}
... other author results
'''
使用来自 SerpApi 的 Google Scholar Profile Results API 解析有机结果的示例代码:
import json
from serpapi import GoogleScholarSearch
# search parameters
params = {
"api_key": "Your SerpApi API key",
"engine": "google_scholar_profiles",
"hl": "en", # language
"mauthors": "biology" # search query
}
search = GoogleScholarSearch(params)
results = search.get_dict()
# only first page results
for result in results["profiles"]:
print(json.dumps(result, indent=2))
# part of the output:
'''
{
"name": "Masatoshi Nei",
"link": "https://scholar.google.com/citations?hl=en&user=VxOmZDgAAAAJ",
"serpapi_link": "https://serpapi.com/search.json?author_id=VxOmZDgAAAAJ&engine=google_scholar_author&hl=en",
"author_id": "VxOmZDgAAAAJ",
"affiliations": "Laura Carnell Professor of Biology, Temple University",
"email": "Verified email at temple.edu",
"cited_by": 384074,
"interests": [
{
"title": "Evolution",
"serpapi_link": "https://serpapi.com/search.json?engine=google_scholar_profiles&hl=en&mauthors=label%3Aevolution",
"link": "https://scholar.google.com/citations?hl=en&view_op=search_authors&mauthors=label:evolution"
},
{
"title": "Evolutionary biology",
"serpapi_link": "https://serpapi.com/search.json?engine=google_scholar_profiles&hl=en&mauthors=label%3Aevolutionary_biology",
"link": "https://scholar.google.com/citations?hl=en&view_op=search_authors&mauthors=label:evolutionary_biology"
},
{
"title": "Molecular evolution",
"serpapi_link": "https://serpapi.com/search.json?engine=google_scholar_profiles&hl=en&mauthors=label%3Amolecular_evolution",
"link": "https://scholar.google.com/citations?hl=en&view_op=search_authors&mauthors=label:molecular_evolution"
},
{
"title": "Population genetics",
"serpapi_link": "https://serpapi.com/search.json?engine=google_scholar_profiles&hl=en&mauthors=label%3Apopulation_genetics",
"link": "https://scholar.google.com/citations?hl=en&view_op=search_authors&mauthors=label:population_genetics"
},
{
"title": "Phylogenetics",
"serpapi_link": "https://serpapi.com/search.json?engine=google_scholar_profiles&hl=en&mauthors=label%3Aphylogenetics",
"link": "https://scholar.google.com/citations?hl=en&view_op=search_authors&mauthors=label:phylogenetics"
}
],
"thumbnail": "https://scholar.googleusercontent.com/citations?view_op=small_photo&user=VxOmZDgAAAAJ&citpid=3"
}
... other results
'''
我在 SerpApi 有一个专门的 Scrape historic Google Scholar results using Python 博客 post,它展示了如何抓取历史性的 2017-2021 Organic,将 Google Scholar 结果引用到 CSV,SQLite。
Disclaimer, I work for SeprApi