wbtools 3.0.11

Interface to WormBase (www.wormbase.org) curation data, including literature management and NLP functions

WBtools

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.

Installation

pip install wbtools

Usage example

Get sentences from a WormBase paper

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)

Get the latest papers (up to 50) added to WormBase or modified in the last 30 days

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()]