BioC data structures and encoder/decoder for Python
Project description
BioC XML / JSON 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.BioCXMLDocumentWriter(filename) as writer:
writer.write_collection_info(collection)
for document in collection.documents:
writer.write_document(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.BioCXMLDocumentReader(filename) as reader:
collection_info = reader.get_collection_info()
for document in reader:
# process document
...
get_collection_info can be called after the construction of the BioCXMLDocumentReader anytime.
Together with Python coroutines, this can be used to generate BioC XML in an asynchronous, non-blocking fashion.
import bioc
with bioc.BioCXMLDocumentReader(source) as reader, \
bioc.BioCXMLDocumentWriter(dest) as writer:
collection_info = reader.get_collection_info()
writer.write_collection_info(collection_info)
for document in reader:
# modify the document
...
writer.write_document(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:
from bioc.biocjson import BioCJsonIterWriter
with BioCJsonIterWriter(filename, level=bioc.PASSAGE) as writer:
for doc in collection.documents:
for passage in doc.passages:
writer.write(passage)
or
from bioc.biocjson import toJSON
import jsonlines
with jsonlines.open(filename, 'w') as writer:
for doc in collection.documents:
for passage in doc.passages:
writer.write(toJSON(passage))
Incrementally decoding the BioC Json lines file:
from bioc.biocjson import BioCJsonIterReader
with BioCJsonIterReader(filename, level=bioc.PASSAGE) as reader:
for passage in reader:
# process passage
...
or
from bioc.biocjson import fromJSON
import jsonlines
with jsonlines.open(filename) as reader:
for obj in reader:
passage = fromJSON(obj, level=bioc.PASSAGE)
...
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
If you use bioc in your research, please cite the following paper:
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.
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