Entrezpy: a Python library to dynamically interact with the NCBI Entrez databases

Jan P Buchmann; Edward C Holmes

doi:10.1093/bioinformatics/btz385

Entrezpy: a Python library to dynamically interact with the NCBI Entrez databases

Bioinformatics. 2019 Nov 1;35(21):4511-4514. doi: 10.1093/bioinformatics/btz385.

Authors

Jan P Buchmann¹, Edward C Holmes¹

Affiliation

¹ Marie Bashir Institute for Infectious Diseases and Biosecurity, Charles Perkins Centre, School of Life and Environmental Sciences and Sydney Medical School, The University of Sydney, Sydney, NSW 2006, Australia.

Abstract

Summary: Entrezpy is a Python library that automates the querying and downloading of data from the Entrez databases at National Center for Biotechnology Information by interacting with E-Utilities. Entrezpy implements complex queries by automatically creating E-Utility parameters from the results obtained that can then be used directly in subsequent queries. Entrezpy also allows the user to cache and retrieve results locally, implements interactions with all Entrez databases as part of an analysis pipeline and adjusts parameters within an ongoing query or using prior results. Entrezpy's modular design enables it to easily extend and adjust existing E-Utility functions.

Availability and implementation: Entrezpy is implemented in Python 3 (≥3.6) and depends only on the Python Standard Library. It is available via PyPi (https://pypi.org/project/entrezpy/) and at https://gitlab.com/ncbipy/entrezpy.git. Entrezpy is licensed under the LGPLv3 and also at http://entrezpy.readthedocs.io/.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Databases, Factual
Software*