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Python Documentation Translation Dictionary

This document describes the terminology dictionaries for maintaining translation consistency across the Python documentation project.

Overview

The translation dictionary project provides curated key terms and their translations to help translators maintain consistent terminology usage across different documents. The dictionaries are maintained using LLM knowledge to identify and categorize important Python terminology.

Generated Files

terminology_dictionary.csv

The complete terminology dictionary containing important terms identified from Python documentation. Contains:

  • source_term: The original English term
  • translated_term: The corresponding Chinese (Traditional) translation
  • frequency: Number of occurrences across all files
  • files_count: Number of different files containing this term
  • source_file: Example file where this term was found
  • directory: Directory of the source file
  • example_files: List of up to 5 files containing this term

Total entries: ~14,700 unique terms

focused_terminology_dictionary.csv

A curated subset of ~2,900 terms focusing on the most important Python terminology. Includes additional columns:

  • priority: High/Medium priority classification
  • category: Term classification

Categories:

  • Core Concepts (7 terms): class, function, method, module, package, object, type
  • Built-in Types (9 terms): int, str, list, dict, tuple, set, float, bool, complex
  • Keywords/Constants (8 terms): None, True, False, return, import, def, async, await
  • Exceptions (690 terms): All *Error and *Exception terms
  • Code Elements (825 terms): Terms in backticks, magic methods
  • Common Terms (1,365 terms): Frequently used technical terms

Maintenance

The terminology dictionaries are maintained using LLM knowledge to identify important Python terms and their translations. The dictionaries can be updated as needed to reflect new terminology or improved translations.

Integration with Translation Workflow

For New Translators

  1. Start with focused_terminology_dictionary.csv
  2. Learn standard translations for core Python concepts
  3. Reference high-frequency terms for consistency

For Translation Review

  1. Check new translations against the dictionary
  2. Verify consistent terminology usage
  3. Update dictionary when establishing new standard translations

For Project Management

  1. Track translation progress for key technical terms
  2. Identify terminology needing standardization
  3. Prioritize translation efforts using frequency data

Output Format

CSV files use UTF-8 encoding to properly handle Chinese characters. Compatible with Excel, Google Sheets, and other spreadsheet applications.

Maintenance

Adding New Patterns

To extend pattern recognition, modify extract_key_terms() function in extract_terminology.py:

# Add new technical patterns
tech_patterns = [
    r'\b(?:new_pattern_here)\b',
    # existing patterns...
]

Adjusting Filters

Modify filtering criteria in is_significant_term() and create_focused_dictionary() functions.

Performance Optimization

  • Current processing: ~509 files in 2-3 minutes
  • Memory usage: ~50MB peak
  • Scalable to larger repositories

This documentation provides comprehensive guidance for maintaining and using the translation dictionary system to ensure consistent, high-quality Python documentation translation.