Python's Scholarly Package revolutionized academic research, providing easy access to a wealth of Google Scholar profile data. However, its potential has been hampered by the infamous StopIteration error interrupting data extraction. This error stems from misuse of the next() function, hindering a comprehensive collection of data and limiting academic progress.
Yet, the StopIteration error is solvable. Firstly, avoiding the use of next() and iterating directly through search_query stops error emergence – it enables systematic data retrieval without prematurely facing the error. Secondly, using nested loops to sift through search results, ensures complete access to all data in the professor_list and avoids the error.
These corrections allow the Python scholarly package to fully realise its potential, paving the way for richer academic insights and pushing academic research into a new era of comprehensive scholarship, freeing it from the limitations of the StopIteration error.
Full article here: https://medium.com/@lawsuithelpdesk/unveiling-the-secrets-of-google-scholars-python-package-overcoming-stopiteration-errors-for-24a8af1fd5c0