BioC data structures and encoder/decoder for Python
Project description
BioC XML format can be used to share text documents and annotations.
bioc exposes an API familiar to users of the standard library marshal and pickle modules.
Development of bioc happens on GitHub: https://github.com/yfpeng/bioc
Getting started
Installing bioc
$ pip install bioc
XML
Encoding the BioC collection object collection:
import bioc
# Serialize ``collection`` to a BioC formatted ``str``.
bioc.dumps(collection)
# Serialize ``collection`` as a BioC formatted stream to ``fp``.
with open(filename, 'w') as fp
bioc.dump(collection, fp)
Compact encoding:
import bioc
bioc.dumps(collection, pretty_print=False)
Incremental BioC serialisation:
import bioc
with bioc.iterwrite(filename, collection) as writer:
for document in collection.documents:
writer.writedocument(document)
Decoding the BioC XML file:
import bioc
# Deserialize ``s`` to a BioC collection object.
collection = bioc.loads(s)
# Deserialize ``fp`` to a BioC collection object.
with open(filename, 'r') as fp:
collection = bioc.load(fp)
Incrementally decoding the BioC XML file:
import bioc
with bioc.iterparse(filename) as parser:
collection_info = parser.get_collection_info()
for document in parser:
# process document
...
get_collection_info can be called after the construction of the iterparse anytime.
Together with Python coroutines, this can be used to generate BioC XML in an asynchronous, non-blocking fashion.
import bioc
with bioc.iterparse(filename) as parser:
with bioc.iterwrite(dst, parser.get_collection_info()) as writer:
for document in parser:
# modify the document
...
writer.writedocument(document)
Json
Encoding the BioC collection object collection:
import biocjson
# Serialize ``collection`` to a BioC Json formatted ``str``.
biocjson.dumps(collection, indent=2)
# Serialize ``collection`` as a BioC Json formatted stream to ``fp``.
with open(filename, 'w') as fp
biocjson.dump(collection, fp, indent=2)
Compact encoding:
import biocjson
biocjson.dumps(collection)
Decoding the BioC Json file:
import biocjson
# Deserialize ``s`` to a BioC collection object.
collection = biocjson.loads(s)
# Deserialize ``fp`` to a BioC collection object.
with open(filename, 'r') as fp:
collection = biocjson.load(fp)
Json Lines
Incrementally encoding the BioC structure:
with biocjson.iterparse(filename, level=bioc.PASSAGE) as reader:
for passage in reader:
# process passage
...
Incrementally decoding the BioC Json lines file:
with biocjson.iterwrite(filename, level=bioc.PASSAGE) as writer:
for doc in collection.documents:
for passage in doc.passages:
writer.write(passage)
Requirements
lxml (http://lxml.de)
jsonlines
Developers
Yifan Peng (yifan.peng@nih.gov)
Acknowledgment
Hernani Marques (https://github.com/2mh/PyBioC)
Webpage
The official BioC webpage is available with all up-to-date instructions, code, and corpora in the BioC format, and other research on, based on and related to BioC.
Reference
Comeau,D.C., Doğan,R.I., Ciccarese,P., Cohen,K.B., Krallinger,M., Leitner,F., Lu,Z., Peng,Y., Rinaldi,F., Torii,M., Valencia,V., Verspoor,K., Wiegers,T.C., Wu,C.H., Wilbur,W.J. (2013) BioC: A minimalist approach to interoperability for biomedical text processing. Database: The Journal of Biological Databases and Curation.
Peng,Y., Tudor,C., Torii,M., Wu,C.H., Vijay-Shanker,K. (2014) iSimp in BioC standard format: Enhancing the interoperability of a sentence simplification system. Database: The Journal of Biological Databases and Curation.
Marques,M., Rinaldi,F. (2012) PyBioC: a python implementation of the BioC core. In Proceedings of BioCreative IV workshop.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.