Interface to WormBase curation database and Text Mining functions
Access WormBase paper corpus information by loading pdf files (converted to txt) and curation info from the WormBase database. The package also exposes text mining functions on papers' fulltext.
pip install wbtools
from wbtools.literature.corpus import CorpusManager
paper_id = "00050564"
cm = CorpusManager()
cm.load_from_wb_database(db_name="wb_dbname", db_user="wb_dbuser", db_password="wb_dbpasswd", db_host="wb_dbhost",
paper_ids=[paper_id], file_server_host="file_server_base_url", file_server_user="username",
file_server_passwd="password")
sentences = cm.get_paper(paper_id).get_text_docs(split_sentences=True)from wbtools.literature.corpus import CorpusManager
import datetime
one_month_ago = (datetime.datetime.now() - datetime.timedelta(days=30)).strftime("%M/%D/%Y")
cm = CorpusManager()
cm.load_from_wb_database(db_name="wb_dbname", db_user="wb_dbuser", db_password="wb_dbpasswd", db_host="wb_dbhost",
from_date=one_month_ago, max_num_papers=50,
file_server_host="file_server_base_url", file_server_user="username",
file_server_passwd="password")
paper_ids = [paper.paper_id for paper in cm.get_all_papers()]Get the latest 50 papers added to WormBase or modified that have a final pdf version and have been flagged by WB paper classification pipeline, excluding reviews and papers with temp files only (proofs)
from wbtools.literature.corpus import CorpusManager
import datetime
cm = CorpusManager()
cm.load_from_wb_database(db_name="wb_dbname", db_user="wb_dbuser", db_password="wb_dbpasswd", db_host="wb_dbhost",
max_num_papers=50, must_be_autclass_flagged=True, exclude_pap_types=['Review'],
exclude_temp_pdf=True, file_server_host="file_server_base_url",
file_server_user="username", file_server_passwd="password")
paper_ids = [paper.paper_id for paper in cm.get_all_papers()]