"""
File hash cache management systems for persistent and in-memory result storage.

This module provides abstract and concrete implementations of cache managers that
can store and retrieve FileHashResult objects to avoid redundant hash calculations.

.. versionadded:: 2.3.0
"""

from collections import OrderedDict as _OrderedDict

from .util import FileHashResult,_fs,_tt

class FileHashCacheManagerBase(_tt.abc.ABC):
    """
    Abstract base class for file hash cache management systems.

    This class defines the interface for implementing custom cache managers that can
    store and retrieve FileHashResult objects. It provides the foundation for
    building persistent or specialized caching solutions beyond the default
    in-memory cache used by FileHashCalculator.

    Implementing classes can provide various storage backends such as:
    - Database-backed caching for persistence across program runs
    - Redis or other external cache systems for distributed applications
    - File-based caching for single-machine persistence
    - Memory-mapped file caching for large datasets

    The interface is designed to be simple and focused, requiring only two
    core operations: retrieving cached results and storing new results.

    Note:
        This is an abstract base class and cannot be instantiated directly.
        Subclasses must implement the get() and set() methods to provide
        actual caching functionality.

    .. versionadded:: 2.2.4
    """

    def __init__(self) -> None:
        """
        Initialize the cache manager base class.

        This constructor performs any basic initialization needed by the base class.
        Subclasses should call super().__init__() in their constructors to ensure
        proper initialization of the base class components.

        Note:
            The base implementation is minimal and serves primarily as a placeholder
            for potential future base class functionality.
        """

    def get(self, file: "_fs.File", algorithm: str) -> _tt.Union[FileHashResult, None]:
        """
        Retrieve a cached hash result for the specified file.

        This method should look up and return any previously cached hash result
        for the given file. The implementation should handle cache validation
        logic, such as checking if the cached result is still valid based on
        file modification times or other criteria.

        Args:
            file (File): The file object to look up in the cache. The implementation
                can use any file attributes (path, modification time, size, etc.)
                as cache keys or validation criteria.

        Returns:
            FileHashResult or None: The cached hash result if found and valid,
                None if no valid cached result exists. Returning None indicates
                that a new hash calculation should be performed.

        Implementation Guidelines:
            - Use file.path as the primary cache key
            - Consider file.state.st_mtime for cache validation
            - Handle cases where cached data may be corrupted or incomplete
            - Return None for any uncertain cases to trigger recalculation
            - Optimize for fast lookup since this method may be called frequently

        Note:
            This is an abstract method that must be implemented by subclasses.
            The base class implementation raises NotImplementedError.
        """

    def set(self, file: "_fs.File", result: FileHashResult) -> None:
        """
        Store a hash result in the cache for future retrieval.

        This method should persistently store the provided hash result so it can
        be retrieved later via the get() method. The implementation should handle
        any necessary serialization, storage optimization, and error handling.

        Args:
            file (File): The file object that was hashed. This provides context
                for the cache entry, including path and metadata that may be
                useful for cache organization or validation.
            result (FileHashResult): The complete hash result to store. This
                includes the hash value, algorithm used, file path, modification
                time, and calculation timestamp.

        Implementation Guidelines:
            - Use file.path or result.path as the cache key
            - Store all relevant fields from the FileHashResult
            - Handle storage errors gracefully (logging, fallback strategies)
            - Consider implementing cache size limits or expiration policies
            - Ensure thread-safety if the cache will be used concurrently
            - Optimize for write performance since caching should not significantly
              slow down hash calculations

        Raises:
            The method should handle storage errors internally when possible,
            but may raise exceptions for critical failures that should halt
            the application (e.g., disk full, permission denied).

        Note:
            This is an abstract method that must be implemented by subclasses.
            The base class implementation raises NotImplementedError.
        """

    @_tt.overload
    def getKey(self, target: "_fs.File", algorithm: str) -> tuple[str, str]: ...

    @_tt.overload
    def getKey(self, target: "_fs.Path", algorithm: str) -> tuple[str, str]: ...

    @_tt.overload
    def getKey(self, target: FileHashResult) -> tuple[str, str]: ...

    def getKey(self, target, algorithm=None):
        """
        Generate a cache key tuple from target object and algorithm.

        This method creates a standardized cache key tuple that uniquely identifies
        a file hash entry based on the target object and algorithm. The key is used
        internally by cache managers to store and retrieve hash results efficiently.

        Args:
            target (Union[FileHashResult, FileSystemItem, Any]): The target object
                to generate a key for. Can be:
                - FileHashResult: Uses the result's path and algorithm
                - FileSystemItem (File, Path, etc.): Uses the item's path with provided algorithm
                - Any other object: Converts to string and uses with provided algorithm
            algorithm (str, optional): Hash algorithm name. Required when target is not
                a FileHashResult. Ignored when target is a FileHashResult (uses result's
                algorithm instead).

        Returns:
            Tuple[str, str]: A tuple containing (path_string, algorithm_string) that
                serves as a unique cache key. The path is always converted to string
                for consistent key generation across different path-like objects.

        Raises:
            AssertionError: If algorithm is not provided when target is not a FileHashResult.

        Note:
            This method is primarily intended for internal use by cache managers
            to maintain consistent key generation across different input types.
            The returned tuple format ensures stable dictionary keys for caching.
        """
        if isinstance(target, FileHashResult):
            return str(target.path), target.algorithm

        assert algorithm, "algorithm is required when target is not FileHashResult"

        if isinstance(target, _fs.Path):
            return str(target), algorithm
        return str(target.path), algorithm


class MemoryFileHashManager(FileHashCacheManagerBase):
    """
    Simple in-memory cache manager for file hash results.

    This implementation provides basic caching functionality using a Python dictionary
    to store hash results in memory. The cache persists for the lifetime of the
    MemoryFileHashManager instance but is not persistent across program runs.

    This is the default cache manager when caching is enabled and provides good
    performance for most use cases where memory usage is not a primary concern.

    Note:
        The cache grows without bounds, so for applications processing many files,
        consider using LfuMemoryFileHashManager instead to limit memory usage.

    .. versionadded:: 2.2.4
    """

    _cache: dict[tuple[str, str], FileHashResult]

    def __init__(self):
        self._cache = {}

    def get(self, file: "_fs.File", algorithm: str):
        return self._cache.get(self.getKey(file, algorithm))

    def set(self, file: "_fs.File", result: FileHashResult):
        self._cache[self.getKey(result)] = result


class NullFileHashManager(FileHashCacheManagerBase):
    """
    No-operation cache manager that disables caching entirely.

    This implementation provides a null object pattern for situations where
    caching is not desired. All cache operations are no-ops:
    - get() always returns None (cache miss)
    - set() discards the provided result

    Use this manager when you want to disable caching but still use the
    FileHashCalculator interface, or for testing scenarios where cache
    behavior should be eliminated.

    This manager has zero memory overhead and provides consistent performance
    characteristics since no cache lookups or storage operations are performed.

    .. versionadded:: 2.2.4
    """

    def get(self, file: "_fs.File", algorithm: str):
        return None

    def set(self, file: "_fs.File", result: FileHashResult):
        pass


class LfuMemoryFileHashManager(FileHashCacheManagerBase):
    """
    LRU (Least Recently Used) memory cache manager with size limits.

    This implementation provides memory-bounded caching using an OrderedDict to track
    access patterns. When the cache exceeds the specified maximum size, the least
    recently used entries are automatically evicted to maintain the size limit.

    The cache uses LRU eviction policy:
    - Recently accessed items are moved to the end of the cache
    - When size limit is exceeded, items from the beginning are removed
    - Both get() and set() operations update the access order

    This manager is ideal for long-running applications that process many files
    where memory usage needs to be controlled while maintaining good cache hit rates.

    Args:
        maxSize (int): Maximum number of hash results to keep in cache.
            When exceeded, least recently used entries are evicted.

    Note:
        Despite the class name "LfuMemoryFileHashManager", this implementation actually 
        uses LRU (Least Recently Used) eviction policy. The name is kept for backward 
        compatibility but may be misleading - consider it as an LRU cache manager.

    .. versionadded:: 2.2.4
    """

    _cache: "_OrderedDict[tuple[str,str], FileHashResult]"
    maxSize: int

    def __init__(self, maxSize: int):
        self._cache = _OrderedDict()
        self.maxSize = maxSize

    def get(self, file: "_fs.File", algorithm: str):
        key = self.getKey(file, algorithm)
        res = self._cache.get(key)
        if res:
            self._cache.move_to_end(key)
        return res

    def set(self, file: "_fs.File", result: FileHashResult):
        key = self.getKey(result)
        self._cache[key] = result
        self._cache.move_to_end(key)
        if len(self._cache) > self.maxSize:
            self._cache.popitem(last=False)


DefaultNoneFileHashManager = NullFileHashManager()
