"""Caching of formatted files with feature-based invalidation."""

import hashlib
import os
import pickle
import sys
import tempfile
from dataclasses import dataclass, field
from pathlib import Path
from typing import Dict, Iterable, NamedTuple, Set, Tuple

from platformdirs import user_cache_dir

from _black_version import version as __version__
from black.mode import Mode

if sys.version_info >= (3, 11):
    from typing import Self
else:
    from typing_extensions import Self


class FileData(NamedTuple):
    st_mtime: float
    st_size: int
    hash: str


def get_cache_dir() -> Path:
    """Get the cache directory used by black.

    Users can customize this directory on all systems using `BLACK_CACHE_DIR`
    environment variable. By default, the cache directory is the user cache directory
    under the black application.

    This result is immediately set to a constant `black.cache.CACHE_DIR` as to avoid
    repeated calls.
    """
    # NOTE: Function mostly exists as a clean way to test getting the cache directory.
    default_cache_dir = user_cache_dir("black")
    cache_dir = Path(os.environ.get("BLACK_CACHE_DIR", default_cache_dir))
    cache_dir = cache_dir / __version__
    return cache_dir


CACHE_DIR = get_cache_dir()


def get_cache_file(mode: Mode) -> Path:
    return CACHE_DIR / f"cache.{mode.get_cache_key()}.pickle"


@dataclass
class Cache:
    mode: Mode
    cache_file: Path
    file_data: Dict[str, FileData] = field(default_factory=dict)

    @classmethod
    def read(cls, mode: Mode) -> Self:
        """Read the cache if it exists and is well formed.

        If it is not well formed, the call to write later should
        resolve the issue.
        """
        cache_file = get_cache_file(mode)
        if not cache_file.exists():
            return cls(mode, cache_file)

        with cache_file.open("rb") as fobj:
            try:
                data: Dict[str, Tuple[float, int, str]] = pickle.load(fobj)
                file_data = {k: FileData(*v) for k, v in data.items()}
            except (pickle.UnpicklingError, ValueError, IndexError):
                return cls(mode, cache_file)

        return cls(mode, cache_file, file_data)

    @staticmethod
    def hash_digest(path: Path) -> str:
        """Return hash digest for path."""

        data = path.read_bytes()
        return hashlib.sha256(data).hexdigest()

    @staticmethod
    def get_file_data(path: Path) -> FileData:
        """Return file data for path."""

        stat = path.stat()
        hash = Cache.hash_digest(path)
        return FileData(stat.st_mtime, stat.st_size, hash)

    def is_changed(self, source: Path) -> bool:
        """Check if source has changed compared to cached version."""
        res_src = source.resolve()
        old = self.file_data.get(str(res_src))
        if old is None:
            return True

        st = res_src.stat()
        if st.st_size != old.st_size:
            return True
        if int(st.st_mtime) != int(old.st_mtime):
            new_hash = Cache.hash_digest(res_src)
            if new_hash != old.hash:
                return True
        return False

    def filtered_cached(self, sources: Iterable[Path]) -> Tuple[Set[Path], Set[Path]]:
        """Split an iterable of paths in `sources` into two sets.

        The first contains paths of files that modified on disk or are not in the
        cache. The other contains paths to non-modified files.
        """
        changed: Set[Path] = set()
        done: Set[Path] = set()
        for src in sources:
            if self.is_changed(src):
                changed.add(src)
            else:
                done.add(src)
        return changed, done

    def write(self, sources: Iterable[Path]) -> None:
        """Update the cache file data and write a new cache file."""
        self.file_data.update(
            **{str(src.resolve()): Cache.get_file_data(src) for src in sources}
        )
        try:
            CACHE_DIR.mkdir(parents=True, exist_ok=True)
            with tempfile.NamedTemporaryFile(
                dir=str(self.cache_file.parent), delete=False
            ) as f:
                # We store raw tuples in the cache because pickling NamedTuples
                # doesn't work with mypyc on Python 3.8, and because it's faster.
                data: Dict[str, Tuple[float, int, str]] = {
                    k: (*v,) for k, v in self.file_data.items()
                }
                pickle.dump(data, f, protocol=4)
            os.replace(f.name, self.cache_file)
        except OSError:
            pass