| import pandas as pd | |
| from pyalex import Works, Authors, Sources, Institutions, Concepts, Publishers, Funders | |
| import pyalex | |
| pyalex.config.email = "theo.alvesdacosta@ekimetrics.com" | |
| class OpenAlex(): | |
| def __init__(self): | |
| pass | |
| def search(self,keywords,n_results = 100,after = None,before = None): | |
| works = Works().search(keywords).get() | |
| for page in works.paginate(per_page=n_results): | |
| break | |
| df_works = pd.DataFrame(page) | |
| return works | |
| def make_network(self): | |
| pass | |
| def get_abstract_from_inverted_index(self,index): | |
| # Determine the maximum index to know the length of the reconstructed array | |
| max_index = max([max(positions) for positions in index.values()]) | |
| # Initialize a list with placeholders for all positions | |
| reconstructed = [''] * (max_index + 1) | |
| # Iterate through the inverted index and place each token at its respective position(s) | |
| for token, positions in index.items(): | |
| for position in positions: | |
| reconstructed[position] = token | |
| # Join the tokens to form the reconstructed sentence(s) | |
| return ' '.join(reconstructed) |