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Shared parsers, emitters, and validators for the AGR ABC Markdown document format
Shared Python library for the Alliance of Genome Resources (AGR) document processing pipeline. Provides parsers, emitters, and validators for the ABC Markdown format — the canonical text representation used across all AGR services for scientific publications. Reads JATS/TEI XML articles as well as Excel (.xlsx) and Word (.docx) supplement files.
pip install agr-abc-document-parsers
For development:
pip install -e ".[dev]"
The Document class provides file-based loading methods that auto-detect
the format from the file extension (.tei.gz, .nxml.gz, .xml, .md,
.xlsx, .docx):
from agr_abc_document_parsers import Document
# Load main paper from a gzipped nXML file
doc = Document()
doc.load_main_file("paper.nxml.gz")
print(doc.title) # "Distinct DNA Binding Sites ..."
print(doc.journal) # "PLoS Genetics"
print(doc.doi) # "10.1371/journal.pgen.1004133"
print(doc.pmid) # "24516405"
print(len(doc.sections)) # 5
print(len(doc.references)) # 107
# Add supplements (each becomes a Document in doc.supplements)
doc.add_supplement_file("supp1.tei.gz")
doc.add_supplement_files(["supp2.nxml.gz", "supp3.md"])
# Office supplements: the H1 title defaults to the file name stem
doc.add_supplement_file("Table_S1.xlsx.gz", title="Supplementary Table 1")
# Method chaining
doc = (
Document()
.load_main_file("paper.nxml.gz")
.add_supplement_files(["supp1.tei.gz", "supp2.md"])
)
The load_main and add_supplement methods accept str (Markdown) or
bytes (XML or Office file, optionally gzip-compressed). Format is
auto-detected:
from agr_abc_document_parsers import Document
doc = Document()
# bytes input → auto-detects TEI vs JATS from the XML root element
doc.load_main(xml_bytes)
doc.load_main(gzipped_xml_bytes) # gz decompressed automatically
# str input → parsed as ABC-format Markdown
doc.load_main(markdown_string)
# Explicit format override
doc.load_main(xml_bytes, format="tei")
doc.load_main(xml_bytes, format="jats")
# Add supplements from mixed sources
doc.add_supplement(supplement_xml_bytes)
doc.add_supplements([s1_bytes, s2_bytes, s3_markdown_str])
# Excel / Word supplements (ZIP packages are sniffed automatically);
# pass the supplement's display name as the title
doc.add_supplement(xlsx_bytes, title="Table S1")
doc.add_supplement(docx_bytes, format="docx", title="Supplementary Methods")
from agr_abc_document_parsers import convert_xml_to_markdown
# Auto-detect TEI or JATS format; also accepts gzipped bytes
markdown = convert_xml_to_markdown(xml_bytes)
# Explicit format
markdown = convert_xml_to_markdown(xml_bytes, source_format="tei")
markdown = convert_xml_to_markdown(xml_bytes, source_format="jats")
Curators attach supplementary data as .xlsx and .docx files. Both are
read directly from their Office Open XML parts (no extra dependencies) and
go through the same Document model and emitter as JATS/TEI articles, so
the output conforms to MARKDOWN_SCHEMA.md: one H1 (the supplement's
display name), GFM tables with escaped pipes, no float/NaN quirks.
## section per non-empty worksheet (sheet name as the
heading) containing one table; the first non-empty row is the header.
Empty rows/columns are dropped, dates render as ISO (2024-03-15),
booleans as TRUE/FALSE, and cached formula results are used.Heading N paragraphs become nested sections, body text keeps
bold/italic/superscript/subscript and hyperlinks, bulleted/numbered
paragraphs become lists, Word tables become GFM tables (header rows
honoured), and footnotes/endnotes become [^n] footnotes.from agr_abc_document_parsers import convert_office_to_markdown, parse_office
# Auto-detect xlsx vs docx from the ZIP contents; gzipped bytes accepted
markdown = convert_office_to_markdown(xlsx_bytes, title="Table S1")
# Derive the title from the file name when no display name is at hand
markdown = convert_office_to_markdown(docx_bytes, filename="Methods_S1.docx.gz")
# -> "# Methods_S1"
# Explicit format, or get the Document model instead of Markdown
markdown = convert_office_to_markdown(docx_bytes, source_format="docx", title="Methods")
doc = parse_office(xlsx_bytes, title="Table S1")
convert_xml_to_markdown() and detect_format() also accept Office
packages (detect_format returns 'xlsx' / 'docx'), but
convert_office_to_markdown() is preferred because it takes the title.
GROBID TEI can include coords attributes that identify source PDF pages.
The additive TEI-specific API returns the same canonical ABC Markdown plus
non-overlapping UTF-8 byte spans. It does not put page markers in Markdown.
from agr_abc_document_parsers import convert_tei_to_markdown_with_provenance
emission = convert_tei_to_markdown_with_provenance(tei_bytes)
markdown = emission.markdown
for span in emission.spans:
print(span.byte_start, span.byte_end, span.page_numbers, span.native_id, span.kind)
page_numbers preserves the ordered, unique positive pages reported by TEI.
It may be empty when GROBID did not provide coordinates; callers can treat
those ranges as unresolved without changing the Markdown text.
from agr_abc_document_parsers import parse_tei, parse_jats, parse_xlsx, parse_docx, emit_markdown
# Parse XML / Office files into the intermediate Document model
doc = parse_tei(tei_bytes) # also accepts gzipped bytes
doc = parse_jats(jats_bytes)
doc = parse_xlsx(xlsx_bytes, title="Table S1")
doc = parse_docx(docx_bytes, title="Supplementary Methods")
# Inspect the document
print(doc.title, doc.doi, doc.journal, doc.pmid)
for section in doc.sections:
print(section.heading)
for ref in doc.references:
print(f"{ref.index}. {ref.title} — {ref.journal}")
# Emit Markdown from Document
markdown = emit_markdown(doc)
from agr_abc_document_parsers import read_markdown, load_document_with_supplements
# Parse ABC-format Markdown → Document (round-trip capable)
doc = read_markdown(markdown_text)
# Load main paper + supplements in one call
doc = load_document_with_supplements(
main_md=main_text,
supplement_mds=[supp1_text, supp2_text],
)
from agr_abc_document_parsers import (
extract_plain_text, extract_abstract_text, extract_sentences,
)
# Full document text (title + abstract + body), no Markdown formatting
text = extract_plain_text(doc)
# Optionally include article metadata (journal, DOI, PMID, etc.)
text = extract_plain_text(doc, include_metadata=True)
# Abstract only
abstract = extract_abstract_text(doc)
# Split into sentences (handles abbreviations: Dr., Fig., et al., etc.)
sentences = extract_sentences(doc)
# Exclude supplement text
text = extract_plain_text(doc, include_supplements=False)
from agr_abc_document_parsers import validate_markdown
result = validate_markdown(markdown_text)
if result.valid:
print("Document is valid")
else:
for error in result.errors:
print(f"Line {error.line}: [{error.rule_id}] {error.message}")
from agr_abc_document_parsers import (
Document, Section, Author, Paragraph,
Figure, Table, TableCell, Reference,
Formula, ListBlock, InlineRef,
)
| Format | Parser | Input |
|---|---|---|
| GROBID TEI XML | parse_tei() | bytes (plain or gzipped) |
| PMC nXML / JATS | parse_jats() | bytes (plain or gzipped) |
Excel workbook (.xlsx, .xlsm) | parse_xlsx() | bytes (plain or gzipped) |
Word document (.docx, .docm) | parse_docx() | bytes (plain or gzipped) |
| ABC Markdown | read_markdown() | str |
All parsers produce a common Document model that can be emitted as ABC
Markdown via emit_markdown().
When using load_main_file() / add_supplement_file():
| Extension | Parser |
|---|---|
.tei, .tei.gz | TEI |
.nxml, .nxml.gz, .xml, .xml.gz | JATS |
.md | Markdown |
.gz (other) | Auto-detect from XML root element |
The validator checks 9 schema rules (S01–S09). See MARKDOWN_SCHEMA.md in the package for the full specification.
make install # install with dev dependencies
make lint # run ruff
make type-check # run mypy
make test # run pytest
make test-cov # run pytest with coverage
make build # build sdist + wheel
MIT
Download counts and popularity will appear here as the collector receives them.
| Version | Published | Direct dependencies | Open version |
|---|---|---|---|
| 1.8.0 | 5 Oct 2026 | 8 |
This describes our collected data; it is not a security assessment.
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Observed since 21 Oct, 09:25 UTC
No superseded metadata states collected. Unchanged observations do not create new revisions.
package:653b7812d4234c1202eca43e580b390c8230fa8bd9d8841cf2164bc7ceb72c42