gov-doc-parser 1.0.0

Parse and extract structured data from UK government documents — GOV.UK, Hansard, ICO, FCA, BAILII, and ATRS. Research and governance analysis toolkit.

gov-doc-parser

Parse and extract structured data from UK government documents — GOV.UK, Hansard, ICO, FCA, BAILII, and ATRS. Research and governance analysis toolkit.

Install

pip install gov-doc-parser

Zero external dependencies — pure Python stdlib.

Quick start

from gov_doc_parser import GovDocParser

parser = GovDocParser()

# Parse any UK gov source
doc = parser.parse(html_text, source="ico")
print(doc.title, doc.date, doc.metadata)

# Auto-detect from URL
doc = parser.parse(html, source="auto", url="https://ico.org.uk/...")

# Extract AI references with sentiment
result = parser.parse_full(html, source="govuk")
for ref in result.ai_references:
    print(f"[{ref.sentiment}] {ref.term}: {ref.context[:100]}")
# [regulatory] algorithm: ...automated decision-making must comply with UK GDPR...
# [negative] artificial intelligence: ...AI found to be unlawful under Equality Act...

# Parse ATRS record
doc, atrs = parser.parse_atrs(atrs_html)
print(atrs.system_name, atrs.governance_score)  # 0-100 transparency score
print(atrs.dpia_completed, atrs.human_review, atrs.legal_basis)

# Batch
results = parser.batch_parse([
    {"html": govuk_html, "source": "govuk"},
    {"html": ico_html, "source": "ico"},
])

Supported sources

Source	Extracts
GOV.UK	Title, date, department, document type, sections
Hansard	Date, house, speaker, debate text, AI mentions
ICO	Enforcement type, penalty amount, decision text
FCA	Document type (Dear CEO/PS/CP), FCA reference
BAILII	Citation, court, judge, judgment text
ATRS	System name, risk tier, DPIA status, governance score

CLI

gov-doc-parser document.html --source ico
gov-doc-parser document.html --source govuk --ai-refs
gov-doc-parser atrs_record.html --atrs
gov-doc-parser document.html --json

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Linda Oraegbunam | LinkedIn | GitHub