Python port of MARC::Lint with tests
Project description
marc-lint
Python port of the Perl MARC::Lint module for validating MARC21 bibliographic records.
Now added new functionality including added leader and control validation and improved article validation based on language.
Features
- ✅ Comprehensive MARC21 validation
- ✅ Leader and control field (008) validation
- ✅ ISBN/ISSN validation using industry-standard algorithms
- ✅ Language and geographic code validation
- ✅ Article/non-filing indicator validation
- ✅ Batch processing with per-record identification
- ✅ Command-line tool with JSON output support
- ✅ Python 3.10+ support
- ✅ Type hints and comprehensive test coverage
Installation
pip install marc-lint
Or with uv:
uv pip install marc-lint
Quick Start
Command Line Interface
Lint a MARC file and display warnings:
marc-lint records.mrc
Example output:
--- Record ocm12345678 ---
020: Subfield a has bad checksum, 123456789X.
245: Must end with . (period).
--- Record ocm87654321 ---
022: Subfield a has bad checksum, 1234-5678.
============================================================
Processed 2 record(s)
Found 3 warning(s) in 2 record(s)
CLI Options
# Output as JSON (useful for automation)
marc-lint records.mrc --format json
# Quiet mode (warnings only, no summary)
marc-lint records.mrc --quiet
# Use record index as ID when 001 field is missing
marc-lint records.mrc --use-index
# Combine options
marc-lint records.mrc -f json -q
JSON Output Format
marc-lint records.mrc --format json
[
{
"record_id": "ocm12345678",
"is_valid": false,
"warnings": [
{
"field": "020",
"message": "has bad checksum, 123456789X.",
"subfield": "a",
"position": null,
"record_id": "ocm12345678"
}
]
},
{
"record_id": "ocm87654321",
"is_valid": true,
"warnings": []
}
]
Exit Codes
| Code | Meaning |
|---|---|
| 0 | No warnings found |
| 1 | Warnings found |
| 2 | Error reading file |
Use in CI/CD pipelines:
marc-lint catalog.mrc && echo "All records valid!"
Python Library - Single Record
from marc_lint import MarcLint
from pymarc import MARCReader
# Create a linter instance
linter = MarcLint()
# Process MARC records one at a time
with open('records.mrc', 'rb') as fh:
reader = MARCReader(fh)
for record in reader:
warnings = linter.check_record(record)
if warnings:
print(f"Record has {len(warnings)} warnings:")
for warning in warnings:
print(f" - {warning}")
Python Library - Batch Processing
For processing multiple records with per-record identification:
from marc_lint import MarcLint
from pymarc import MARCReader
linter = MarcLint()
with open('records.mrc', 'rb') as fh:
reader = MARCReader(fh)
records = list(reader)
# Process all records at once
results = linter.check_records(records, use_index_as_id=True)
for result in results:
if not result.is_valid:
print(f"Record {result.record_id}:")
for warning in result.warnings:
print(f" - {warning}")
# Summary statistics
total_warnings = sum(len(r.warnings) for r in results)
invalid_records = sum(1 for r in results if not r.is_valid)
print(f"Found {total_warnings} warnings in {invalid_records} of {len(results)} records")
Python Library - Structured Warnings
For automation and API integration, use structured warnings:
from marc_lint import MarcLint
from pymarc import MARCReader
linter = MarcLint()
with open('records.mrc', 'rb') as fh:
reader = MARCReader(fh)
for record in reader:
linter.check_record(record)
# Get structured warning objects
for warning in linter.warnings_structured():
print(f"Record: {warning.record_id}")
print(f"Field: {warning.field}")
print(f"Message: {warning.message}")
if warning.subfield:
print(f"Subfield: {warning.subfield}")
if warning.position is not None:
print(f"Position: {warning.position + 1}")
Python Library - JSON Output
Export warnings as JSON for APIs:
import json
from marc_lint import MarcLint
from pymarc import MARCReader
linter = MarcLint()
with open('records.mrc', 'rb') as fh:
reader = MARCReader(fh)
records = list(reader)
results = linter.check_records(records)
# Convert to JSON
output = [
{
"record_id": r.record_id,
"is_valid": r.is_valid,
"warnings": [w.to_dict() for w in r.warnings]
}
for r in results
]
print(json.dumps(output, indent=2))
Example JSON output:
[
{
"field": "020",
"message": "has bad checksum, 123456789X.",
"subfield": "a",
"position": null,
"record_id": "ocm12345678"
}
]
Python Library - Filtering Warnings
# Filter warnings by field
isbn_warnings = [
w for w in linter.warnings_structured()
if w.field == "020"
]
# Filter by subfield
subfield_a_warnings = [
w for w in linter.warnings_structured()
if w.subfield == "a"
]
# Filter by record
results = linter.check_records(records)
for result in results:
leader_warnings = [w for w in result.warnings if w.field == "LDR"]
See STRUCTURED_WARNINGS.md for detailed documentation on structured warnings.
Validation Rules
Leader Validation
Validates leader positions:
- Position 05: Record status
- Position 06: Type of record
- Position 07: Bibliographic level
- Position 08: Type of control
- Position 09: Character coding scheme
- Position 17: Encoding level
- Position 18: Descriptive cataloging form
- Position 19: Multipart resource record level
Control Field 008 Validation
Validates:
- Field length (40 characters)
- Type of date (position 06)
- Date 1 and Date 2 (positions 07-14)
- Country code (positions 15-17)
- Language code (positions 35-37)
- Modified record indicator (position 38)
- Cataloging source (position 39)
Supported Fields
- 020: ISBN validation with checksum verification
- 022: ISSN validation with checksum verification
- 041: Language codes (ISO 639-2)
- 043: Geographic area codes (MARC Geographic Areas)
- 130, 240, 630, 730, 830: Non-filing indicator validation
- 245: Comprehensive title validation (punctuation, indicators, subfield order)
- 880: Alternate graphic representation validation
- Plus general field/subfield/indicator validation for all tags
Architecture
Files
marc_lint.linter.py– mainMarcLintclass, equivalent and extension toMARC::Lint.marc_lint.code_data.py– translation of the code tables fromMARC::Lint::CodeData(language, geographic area, country codes).marc_lint.field_rules.py– equivalent to__DATA__and_read_rulesinMARC::Lint.marc_lint.warning.py–MarcWarningclass for structured warnings.marc_lint.cli.py– command-line interface.
Key behavior mirrored from the Perl module:
- Per-record checks in
MarcLint.check_record: leader validation, 1XX-count, required 245, field repeatability, indicator validity, subfield legality and repeatability, and control-field rules. - Tag-specific methods
check_020,check_022,check_041,check_043,check_245, plus_check_articlefor handling non-filing indicators. - Rules for tags are built in
_read_rulesfromRULES_DATA, which is a equivalent to__DATA__table inLint.pm.
Development
Setup
# Clone the repository
git clone https://github.com/coliin8/marclint.git
cd marclint
# Install dependencies (including dev dependencies)
uv sync --all-groups
# Activate the virtual environment (optional, uv run handles this automatically)
source .venv/bin/activate
Common Development Tasks
# Run tests
uv run pytest
# Run tests with coverage
uv run pytest --cov=src/marc_lint --cov-report=term-missing
# Run tests across all Python versions (3.10-3.14)
uv run tox
# Run linting
uv run tox -e lint
# Auto-format code
uv run tox -e format
# Run specific test file
uv run pytest tests/test_warning.py -v
# Run specific test
uv run pytest tests/test_warning.py::test_warning_basic_creation -v
# Run bump version of project
uv run bump-my-version bump patch
Code Quality
This project uses:
- pytest for testing
- pytest-cov for coverage reporting
- ruff for linting and formatting (via tox)
- tox for testing across multiple Python versions
Contributing
Contributions are welcome! Please see CONTRIBUTING.md for details.
License
MIT License - see LICENSE file for details.
This is a Python port of the original Perl MARC::Lint module.
Acknowledgments
- Bryan Baldus, Ed Summers, and Dan Lester for the original Perl MARC::Lint module (2001-2011)
- Library of Congress for MARC21 standards and documentation
Links
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