markitect-main/markitect/matter_frontmatter/parser.py

"""
Frontmatter parser for extracting and manipulating YAML/JSON/TOML frontmatter.
"""

import re
import yaml
import json
from typing import Dict, Any, List, Optional
from .stats import FrontmatterStats


class FrontmatterParser:
    """Parser for frontmatter in MarkdownMatters documents."""

    def extract_frontmatter(self, text: str) -> Dict[str, Any]:
        """
        Extract frontmatter from markdown text.

        Args:
            text: Full markdown document text

        Returns:
            Dictionary containing frontmatter data
        """
        frontmatter_content = self._extract_frontmatter_content(text)

        if not frontmatter_content:
            return {}

        # Try to parse as YAML first (most common)
        try:
            return yaml.safe_load(frontmatter_content) or {}
        except yaml.YAMLError:
            pass

        # Try to parse as JSON
        try:
            return json.loads(frontmatter_content)
        except json.JSONDecodeError:
            pass

        # TODO: Add TOML support in future iterations

        return {}

    def set_frontmatter_value(self, text: str, key: str, value: Any) -> str:
        """
        Set a frontmatter value in the document.

        Args:
            text: Full markdown document text
            key: Frontmatter key (supports dot notation for nested)
            value: Value to set

        Returns:
            Updated document text
        """
        frontmatter = self.extract_frontmatter(text)

        # Handle nested keys with dot notation
        if '.' in key:
            self._set_nested_value(frontmatter, key, value)
        else:
            frontmatter[key] = value

        # Replace or add frontmatter block
        return self._update_frontmatter_in_text(text, frontmatter)

    def get_frontmatter_keys(self, text: str, include_nested: bool = False) -> List[str]:
        """
        Get list of frontmatter keys.

        Args:
            text: Full markdown document text
            include_nested: Include nested keys with dot notation

        Returns:
            List of frontmatter keys
        """
        frontmatter = self.extract_frontmatter(text)

        if not include_nested:
            return list(frontmatter.keys())

        return self._get_all_keys_recursive(frontmatter)

    def get_nested_value(self, frontmatter: Dict[str, Any], key: str) -> Any:
        """
        Get nested value using dot notation.

        Args:
            frontmatter: Frontmatter dictionary
            key: Key with dot notation (e.g., "nested.category")

        Returns:
            Value or None if not found
        """
        keys = key.split('.')
        current = frontmatter

        for k in keys:
            if isinstance(current, dict) and k in current:
                current = current[k]
            else:
                return None

        return current

    def calculate_frontmatter_stats(self, text: str) -> FrontmatterStats:
        """
        Calculate statistics for frontmatter.

        Args:
            text: Full markdown document text

        Returns:
            FrontmatterStats object
        """
        frontmatter = self.extract_frontmatter(text)

        if not frontmatter:
            return FrontmatterStats(
                has_frontmatter=False,
                total_fields=0,
                nested_fields=0,
                format=None,
                field_types={}
            )

        # Detect format
        format_type = self._detect_frontmatter_format(text)

        # Count fields
        total_fields = len(frontmatter)
        nested_fields = self._count_nested_fields(frontmatter)

        # Analyze field types
        field_types = self._analyze_field_types(frontmatter)

        return FrontmatterStats(
            has_frontmatter=True,
            total_fields=total_fields,
            nested_fields=nested_fields,
            format=format_type,
            field_types=field_types
        )

    def _extract_frontmatter_content(self, text: str) -> Optional[str]:
        """Extract the raw frontmatter content between delimiters."""
        # Pattern for YAML frontmatter (---...---)
        yaml_pattern = r'^---\s*\n(.*?)\n---\s*\n'

        match = re.search(yaml_pattern, text, flags=re.DOTALL | re.MULTILINE)
        if match:
            return match.group(1).strip()

        return None

    def _detect_frontmatter_format(self, text: str) -> Optional[str]:
        """Detect the format of frontmatter (yaml, json, toml)."""
        content = self._extract_frontmatter_content(text)
        if not content:
            return None

        # Simple heuristics for format detection
        content = content.strip()
        if content.startswith('{') and content.endswith('}'):
            return "json"
        else:
            # Default to YAML for now
            return "yaml"

    def _set_nested_value(self, data: Dict[str, Any], key: str, value: Any) -> None:
        """Set nested value using dot notation."""
        keys = key.split('.')
        current = data

        # Navigate to the parent of the final key
        for k in keys[:-1]:
            if k not in current:
                current[k] = {}
            current = current[k]

        # Set the final value
        current[keys[-1]] = value

    def _get_all_keys_recursive(self, data: Dict[str, Any], prefix: str = "") -> List[str]:
        """Get all keys recursively with dot notation."""
        keys = []

        for key, value in data.items():
            full_key = f"{prefix}.{key}" if prefix else key
            keys.append(full_key)

            if isinstance(value, dict):
                keys.extend(self._get_all_keys_recursive(value, full_key))

        return keys

    def _count_nested_fields(self, data: Dict[str, Any]) -> int:
        """Count nested fields recursively."""
        count = 0

        for value in data.values():
            if isinstance(value, dict):
                count += len(value)
                count += self._count_nested_fields(value)

        return count

    def _analyze_field_types(self, data: Dict[str, Any]) -> Dict[str, int]:
        """Analyze field types in frontmatter."""
        type_counts = {}

        def count_types(obj):
            if isinstance(obj, dict):
                type_counts["object"] = type_counts.get("object", 0) + 1
                for v in obj.values():
                    count_types(v)
            elif isinstance(obj, list):
                type_counts["array"] = type_counts.get("array", 0) + 1
                for item in obj:
                    count_types(item)
            elif isinstance(obj, bool):
                type_counts["boolean"] = type_counts.get("boolean", 0) + 1
            elif isinstance(obj, (int, float)):
                type_counts["number"] = type_counts.get("number", 0) + 1
            elif isinstance(obj, str):
                type_counts["string"] = type_counts.get("string", 0) + 1

        # Count top-level fields only for now
        for value in data.values():
            count_types(value)

        return type_counts

    def _update_frontmatter_in_text(self, text: str, frontmatter: Dict[str, Any]) -> str:
        """Update or add frontmatter block in text."""
        # Convert frontmatter to YAML
        frontmatter_yaml = yaml.dump(frontmatter, default_flow_style=False)

        # Check if text already has frontmatter
        yaml_pattern = r'^---\s*\n.*?\n---\s*\n'

        if re.search(yaml_pattern, text, flags=re.DOTALL | re.MULTILINE):
            # Replace existing frontmatter
            new_frontmatter = f"---\n{frontmatter_yaml}---\n"
            return re.sub(yaml_pattern, new_frontmatter, text, flags=re.DOTALL | re.MULTILINE)
        else:
            # Add frontmatter to beginning
            new_frontmatter = f"---\n{frontmatter_yaml}---\n\n"
            return new_frontmatter + text