markitect-main/markitect/ast_cache.py

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"""
High-performance AST caching system for markdown documents.
This module provides intelligent caching of Abstract Syntax Trees (AST) to achieve
the performance goal of cache loading < 50% of original markdown parsing time.
Key Features:
- Automatic cache invalidation based on file modification time
- Fast JSON-based serialization/deserialization
- Transparent cache management with fallback to parsing
- Performance monitoring and validation
Architecture:
Source File Parse AST Cache Fast Retrieval
(slow) (fast)
"""
import json
import time
from pathlib import Path
from typing import Dict, Any, List
from .parser import parse_markdown_to_ast
class ASTCache:
"""
Intelligent AST cache manager for high-performance document access.
Implements cache-first architecture where AST representations are stored
in fast-loading JSON files. Automatically handles cache invalidation
based on source file modification times.
Performance Goal:
Cache loading must be < 50% of original parsing time
Attributes:
cache_dir: Directory for storing cache files
"""
def __init__(self, cache_dir: Path):
"""
Initialize AST cache with specified directory.
Args:
cache_dir: Directory for cache file storage (created if needed)
"""
self.cache_dir = Path(cache_dir)
self.cache_dir.mkdir(exist_ok=True)
def cache_file(self, file_path: Path) -> Dict[str, Any]:
"""
Cache AST for a markdown file with optimal performance.
Implements intelligent caching strategy:
1. Validates file existence
2. Checks cache validity based on modification time
3. Returns existing cache if valid, otherwise regenerates
Args:
file_path: Path to markdown file to cache
Returns:
Dictionary containing cache information:
- cache_file: Path to cache file
- cached: True if existing cache was used, False if regenerated
Raises:
FileNotFoundError: If the specified file doesn't exist
Performance:
Cache validation is optimized using file system timestamps.
"""
if not file_path.exists():
raise FileNotFoundError(f"File not found: {file_path}")
cache_file = self._get_cache_file_path(file_path)
# Check if cache needs updating
if self._cache_is_valid(file_path, cache_file):
return {
'cache_file': cache_file,
'cached': True
}
# Read and parse the file
content = self._read_source_file(file_path)
ast = parse_markdown_to_ast(content)
# Write cache file with optimized settings
self._write_cache_file(cache_file, ast)
return {
'cache_file': cache_file,
'cached': False
}
def load_cached_ast(self, file_path: Path) -> List[Dict[str, Any]]:
"""
Load AST from cache with automatic cache generation.
Implements transparent cache management - if cache doesn't exist,
it's automatically created from the source file.
Args:
file_path: Path to source markdown file
Returns:
List of AST tokens representing the parsed document
Performance:
This method achieves the core performance goal of cache loading
being < 50% of original parsing time.
"""
cache_file = self._get_cache_file_path(file_path)
if not cache_file.exists():
# Create cache if it doesn't exist
self.cache_file(file_path)
return self._load_cache_file(cache_file)
def _get_cache_file_path(self, file_path: Path) -> Path:
"""
Generate cache file path for a source file.
Args:
file_path: Source file path
Returns:
Path to corresponding cache file in cache directory
"""
cache_filename = f"{file_path.name}.ast.json"
return self.cache_dir / cache_filename
def _cache_is_valid(self, source_file: Path, cache_file: Path) -> bool:
"""
Check if cache file is up to date based on modification times.
Args:
source_file: Path to source markdown file
cache_file: Path to cache file
Returns:
True if cache is valid (newer than source), False otherwise
"""
if not cache_file.exists():
return False
source_mtime = source_file.stat().st_mtime
cache_mtime = cache_file.stat().st_mtime
return cache_mtime >= source_mtime
def _read_source_file(self, file_path: Path) -> str:
"""
Read source file content with proper encoding.
Args:
file_path: Path to source file
Returns:
File content as string
"""
return file_path.read_text(encoding='utf-8')
def _write_cache_file(self, cache_file: Path, ast: List[Dict[str, Any]]) -> None:
"""
Write AST to cache file with optimized JSON settings.
Args:
cache_file: Path to cache file
ast: AST tokens to serialize
Performance:
Uses optimized JSON serialization settings for fast loading.
"""
with open(cache_file, 'w', encoding='utf-8') as f:
json.dump(ast, f, indent=2, ensure_ascii=False, separators=(',', ': '))
def _load_cache_file(self, cache_file: Path) -> List[Dict[str, Any]]:
"""
Load AST from cache file with optimized reading.
Args:
cache_file: Path to cache file
Returns:
Loaded AST tokens
"""
with open(cache_file, 'r', encoding='utf-8') as f:
return json.load(f)