add advanced statistics and analytics for text comparison

[Kaos599]

Overview

This pull request implements comprehensive statistics and analytics for text comparison in the Redlines library, addressing issue #15. The enhancement provides quantitative measures of text differences for data analysis, quality assurance, and research applications.

New Features

Advanced Statistics Metrics

• longest_change_length: Character length of the longest individual change
• shortest_change_length: Character length of the shortest individual change
• average_change_length: Average length across all changes
• change_ratio: Percentage of text modified (0.0 to 1.0 scale)
• chars_added: Total number of characters added across all operations
• chars_deleted: Total number of characters deleted across all operations
• chars_net_change: Net change in characters (added - deleted)
• levenshtein_distance: Edit distance between source and test texts

Technical Implementation

• Extended the existing Stats dataclass while maintaining full backward compatibility
• Enhanced the stats() method with advanced calculation logic
• Updated JSON output to include all new statistics fields
• Added optional Levenshtein distance integration with graceful fallback
• Fixed constructor to properly handle empty strings as valid test input

Code Quality

• MyPy type checking passes
• Black code formatting compliant
• No breaking changes to existing APIs
• Performance maintained (sub-2ms processing for large texts)

Usage Examples

from redlines import Redlines

# Basic analytics
r = Redlines("Hello world", "Hello there world")
stats = r.stats()

print(f"Total changes: {stats.total_changes}")
print(f"Change ratio: {stats.change_ratio:.1%}")
print(f"Longest change: {stats.longest_change_length} chars")
print(f"Levenshtein distance: {stats.levenshtein_distance}")

# JSON export with all metrics
data = r.output_json()  # Includes all new statistics

Files Modified

• redlines/processor.py: Extended Stats dataclass with new fields
• redlines/redlines.py: Enhanced stats() method and JSON output
• tests/test_changes_api.py: Added comprehensive test suite
• README.md: Added advanced analytics documentation

Backward Compatibility

• Zero breaking changes to existing APIs
• Extended Stats object maintains all original fields
• JSON output includes new fields alongside existing ones
• All existing code continues to work unchanged

Use Cases Enabled

1. Content Analysis: Measure document similarity quantitatively
2. Quality Assurance: Automated diff analysis in CI/CD pipelines
3. Research Applications: Statistical analysis of text modifications
4. Data Processing: ETL pipeline validation and monitoring

Verification Steps

# Run all tests
python -m pytest tests/ -v

# Check advanced stats specifically
python -m pytest tests/test_changes_api.py -k "advanced_stats" -v

# Verify linting
python -m mypy redlines/ --ignore-missing-imports
python -m black --check redlines/

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Test Screenshot

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Closes #15: show change statistics/analytics when comparing text

[houfu]

Suggested change

	shortest_change_length = min(change_lengths) if change_lengths else None
	shortest_change_length = min(change_lengths) if change_lengths else 0

It should follow the same logic as shortest.

[houfu]

Levenshtein should be added as an optional dependency in pyproject.toml

[houfu]

Problem: This calculates the ratio based on the source text length only, which doesn't accurately represent the proportion of text that changed. For
insertions, this can produce ratios > 1.0 (violating the documented constraint "0.0 to 1.0 scale").

Example:

• Source: "Hello world" (11 chars)
• Test: "Hello beautiful world" (21 chars)
• Insert: "beautiful " (10 chars)
• Current ratio: 10/11 = 0.909 (90.9%)

This suggests 90.9% of the text changed, when actually only a small portion was modified. The test in test_changes_api.py:317-318 even expects this incorrect behavior.

Consider using maximum of source or test?

[Kaos599]

I see that now thanks!

I think if i use something like "max(source_len, test_len)" as the denominator that should solve this