bconv 0.2

Convert between BioNLP formats

# bconv: Python library for converting between BioNLP formats

bconv offers format conversion and manipulation of documents with text and annotations. It supports various popular formats used in natural-language processing for biomedical texts.

## Supported formats

The following formats are currently supported:

Name | I | O | T | A | Description |

—————————- | - | - | - | - | ———– |

bioc_xml, bioc_json | ✓ | ✓ | ✓ | ✓ | BioC |

bionlp | | ✓ | | ✓ | BioNLP stand-off |

brat | | ✓ | | ✓ | brat stand-off |

conll | ✓ | ✓ | ✓ | ✓ | CoNLL |

europepmc, europepmc.zip | | ✓ | | ✓ | Europe-PMC JSON |

pubtator, pubtator_fbk | ✓ | ✓ | ✓ | ✓ | PubTator |

pubmed, pxml, pxml.gz | ✓ | | ✓ | | PubMed abstracts |

pmc, nxml | ✓ | | ✓ | | PMC full-text |

pubanno_json | | ✓ | ✓ | ✓ | PubAnnotation JSON |

tsv, text_tsv | | ✓ | ✓ | ✓ | tab-separated values |

txt | ✓ | ✓ | ✓ | | plain text |

txt_json | ✓ | | ✓ | | collection of plain-text documents |

I: input format; O: output format; T: can represent text; A: can represent annotations (entities).

## Installation

bconv is hosted on [PyPI](https://pypi.org/project/bconv/), so you can use pip to install it: `sh $ pip install bconv ` By default, pip attempts a system-level installation, which might require admin privileges. Alternatively, use pip’s –user flag for an installation owned by the current user.

## Usage

Load an annotated collection in BioC XML format: `pycon >>> import bconv >>> coll = bconv.load('bioc_xml', 'path/to/example.xml') >>> coll <Collection with 37 subelements at 0x7f1966e4b3c8> ` A Collection is a sequence of Document objects: `pycon >>> coll[0] <Document with 12 subelements at 0x7f1966e2f6d8> ` Documents contain Sections, which contain Sentences: `pycon >>> sent = coll[0][3][5] >>> sent.text 'A Live cell imaging reveals that expression of GFP‐KSHV‐TK, but not GFP induces contraction of HeLa cells.' ` Find the first annotation for this sentence: `pycon >>> e = next(sent.iter_entities()) >>> e.start, e.end, e.text (571, 578, 'KSHV‐TK') >>> e.info {'type': 'gene/protein', 'ui': 'Uniprot:F5HB62'} ` Write the whole collection to a new file in CoNLL format: `pycon >>> with open('path/to/example.conll', 'w', encoding='utf8') as f: ... bconv.dump('conll', coll, f, tagset='IOBES', include_offsets=True) `