![]() ![]() "email": "Verified email at informatik.uni-freiburg. Print(json.dumps(profile_results_data, indent=2)) Search.params_dict.update(dict(parse_qsl(urlsplit(profile_results.get("pagination").get("next")).query))) # splits URL in parts as a dict() and update search "params" variable to a new page that will be passed to GoogleSearch() If "next" in profile_results.get("pagination", ): Profile_results = search.get_dict() # JSON -> Python dictionaryįor profile in profile_results: Search = GoogleSearch(params) # where extraction happens on SerpApi backend de + "University of Freiburg"' # search query "engine": "google_scholar_profiles", # profile results search engine "api_key": os.getenv("API_KEY"), # SerpApi API key # Iterates over all pages and extracts profile results.įrom urllib.parse import urlsplit, parse_qsl It's a paid API with a free plan which differs by providing a complete solution without the need to figure out how to extract the data and maintain it over time. "profile_city_by_count": "Cited by 94818",Īlternatively, you can achieve it using Google Scholar Profile Results API from SerpApi. "profile_affiliations": "Professor of Computer Science, University of Freiburg", Print(json.dumps(profile_results, indent=2)) If selector.css("button.gs_btnPR::attr(onclick)").get(): ![]() # check if next page token is present -> update next page token and increment 10 to get the next page Interests = profile.css(".gs_ai_one_int::text").getall() Advanced Search should be the second to last option in the newly-opened menu. In the upper left corner of the page, press the button made of three horizontal lines to open a new menu. To pull up the Advanced Scholar Search menu, go to the regular Google Scholar search page. Print(f"extracting authors at page #'Īffiliations = profile.css(".gs_ai_aff").xpath("normalize-space()").get()Įmail = profile.css(".gs_ai_eml").xpath("normalize-space()").get()Ĭited_by = profile.css(".gs_ai_cby *::text").get() Accessing the Advanced Scholar Search Menu. # pass response to HTML/XML processing library Html = requests.get("", params=params, headers=headers, timeout=30) de + "University of Freiburg"', # search query "view_op": "search_authors", # author results Additionally, you can add functionality to save those results to CSV/Excel or to DB.Ĭode and full example in the online IDE to test out extraction part: # Iterates over all pages and extracts profile results. A complimentary answer to CephBirk if you want to do it programmatically via Python. ![]()
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