"""Module providing access to all known dataset definitions."""

from __future__ import annotations

import hashlib
import os
import textwrap
from pathlib import Path
from typing import Any

import importlib_resources
import yaml

_hashinfo_formatversion = 1

definition: dict[str, Any]
fileinfo_dirty: set[str]


def _load_yml_definitions() -> None:
    """
    Read dataset .yml files from definitions/ and hashinfo/ directories.
    This is done once during the module import stage.
    """
    global definition, fileinfo_dirty
    definition = {}
    fileinfo_dirty = set()
    base_directory = importlib_resources.files("dials_data") / "definitions"
    hash_directory = importlib_resources.files("dials_data") / "hashinfo"
    for definition_file in base_directory.glob("*.yml"):
        dataset_definition = definition_file.read_bytes()
        dataset_name = definition_file.stem
        definition[dataset_name] = yaml.safe_load(dataset_definition)
        dhash = hashlib.sha256()
        dhash.update(dataset_definition)
        definition[dataset_name]["hash"] = dhash.hexdigest()

        h_file = hash_directory / definition_file.name
        if not h_file.exists():
            fileinfo_dirty.add(dataset_name)
            continue
        hashinfo = yaml.safe_load(h_file.read_bytes())
        if (
            hashinfo["definition"] == definition[dataset_name]["hash"]
            and hashinfo["formatversion"] == _hashinfo_formatversion
        ):
            definition[dataset_name]["hashinfo"] = hashinfo
        else:
            fileinfo_dirty.add(dataset_name)


_load_yml_definitions()


def create_integrity_record(dataset_name) -> dict[str, Any]:
    """
    Generate a dictionary for the integrity information of a specific dataset.
    """
    return {
        "definition": definition[dataset_name]["hash"],
        "formatversion": _hashinfo_formatversion,
    }


def repository_location() -> Path:
    """
    Returns an appropriate location where the downloaded regression data should
    be stored.

    In order of evaluation:
    * If the environment variable DIALS_DATA is set and exists or can be
      created then use that location
    * If a Diamond Light Source specific path exists then use that location
    * If the environment variable LIBTBX_BUILD is set and the directory
      'dials_data' exists or can be created underneath that location then
      use that.
    * Use ~/.cache/dials_data if it exists or can be created
    * Otherwise fail with a RuntimeError
    """
    if os.getenv("DIALS_DATA"):
        try:
            repository = Path(os.environ["DIALS_DATA"])
            repository.mkdir(parents=True, exist_ok=True)
            return repository
        except (KeyError, TypeError, OSError):
            pass
    try:
        repository = Path("/dls/science/groups/scisoft/DIALS/dials_data")
        if repository.is_dir():
            return repository
    except OSError:
        pass
    if os.getenv("LIBTBX_BUILD"):
        try:
            repository = Path(os.environ["LIBTBX_BUILD"]) / "dials_data"
            repository.mkdir(parents=True, exist_ok=True)
            return repository
        except (KeyError, TypeError, OSError):
            pass
    try:
        repository = Path.home() / ".cache" / "dials_data"
        repository.mkdir(parents=True, exist_ok=True)
        return repository
    except (TypeError, OSError):
        raise RuntimeError(
            "Could not determine regression data location. Use environment variable DIALS_DATA"
        )


def get_resident_size(ds) -> int:
    if ds in fileinfo_dirty:
        return 0
    return sum(item["size"] for item in definition[ds]["hashinfo"]["verify"])


def _human_readable(num: float, suffix: str = "B") -> str:
    for unit in ("", "k", "M", "G"):
        if num < 10:
            return f"{num:.1f}{unit}{suffix}"
        if num < 1024:
            return f"{num:.0f}{unit}{suffix}"
        num /= 1024.0
    return f"{num:.0f}T{suffix}"


def list_known_definitions(ds_list, quiet=False) -> None:
    indent = " " * 4
    for shortname in sorted(ds_list):
        if quiet:
            print(shortname)
            continue
        dataset = definition[shortname]
        if shortname in fileinfo_dirty:
            size_information = "unverified dataset"
        else:
            size_information = _human_readable(get_resident_size(shortname))
        print(
            "{shortname}: {dataset[name]} ({size_information})".format(
                shortname=shortname, dataset=dataset, size_information=size_information
            )
        )
        print(
            "{indent}{author} ({license})".format(
                author=dataset.get("author", "unknown author"),
                indent=indent,
                license=dataset.get("license", "unknown license"),
            )
        )
        if dataset.get("url"):
            print("{indent}{dataset[url]}".format(indent=indent, dataset=dataset))
        print(
            "\n{}\n".format(
                textwrap.fill(
                    dataset["description"],
                    initial_indent=indent,
                    subsequent_indent=indent,
                )
            )
        )