# Copyright (c) 2017-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the license found in the LICENSE file in
# the root directory of this source tree. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.

"""
Utilities for working with the local dataset cache.
This file is adapted from `AllenNLP <https://github.com/allenai/allennlp>`_.
and `huggingface <https://github.com/huggingface>`_.
"""

import fnmatch
from functools import wraps
from hashlib import sha256
from io import open
import json
import logging
import os
import shutil
import tarfile
import tempfile


try:
    from torch.hub import _get_torch_home
    torch_cache_home = _get_torch_home()
except ImportError:
    torch_cache_home = os.path.expanduser(
        os.getenv('TORCH_HOME', os.path.join(
            os.getenv('XDG_CACHE_HOME', '~/.cache'), 'torch')))
default_cache_path = os.path.join(torch_cache_home, 'pytorch_fairseq')

try:
    from urllib.parse import urlparse
except ImportError:
    from urlparse import urlparse

try:
    from pathlib import Path
    PYTORCH_FAIRSEQ_CACHE = Path(
        os.getenv('PYTORCH_FAIRSEQ_CACHE', default_cache_path))
except (AttributeError, ImportError):
    PYTORCH_FAIRSEQ_CACHE = os.getenv(
        'PYTORCH_FAIRSEQ_CACHE', default_cache_path)

CONFIG_NAME = "config.json"
WEIGHTS_NAME = "pytorch_model.bin"

logger = logging.getLogger(__name__)  # pylint: disable=invalid-name


def load_archive_file(archive_file):
    # redirect to the cache, if necessary
    try:
        resolved_archive_file = cached_path(archive_file, cache_dir=None)
    except EnvironmentError:
        print(
            "Archive name '{}' was not found in archive name list. "
            "We assumed '{}' was a path or URL but couldn't find any file "
            "associated to this path or URL.".format(
                archive_file,
                archive_file,
            )
        )
        return None

    if resolved_archive_file == archive_file:
        print("loading archive file {}".format(archive_file))
    else:
        print("loading archive file {} from cache at {}".format(
            archive_file, resolved_archive_file))

    # Extract archive to temp dir and replace .tar.bz2 if necessary
    tempdir = None
    if not os.path.isdir(resolved_archive_file):
        tempdir = tempfile.mkdtemp()
        print("extracting archive file {} to temp dir {}".format(
            resolved_archive_file, tempdir))
        ext = os.path.splitext(archive_file)[1][1:]
        with tarfile.open(resolved_archive_file, 'r:' + ext) as archive:
            top_dir = os.path.commonprefix(archive.getnames())
            archive.extractall(tempdir)
        os.remove(resolved_archive_file)
        shutil.move(os.path.join(tempdir, top_dir), resolved_archive_file)
        shutil.rmtree(tempdir)

    return resolved_archive_file


def url_to_filename(url, etag=None):
    """
    Convert `url` into a hashed filename in a repeatable way.
    If `etag` is specified, append its hash to the URL's, delimited
    by a period.
    """
    url_bytes = url.encode('utf-8')
    url_hash = sha256(url_bytes)
    filename = url_hash.hexdigest()

    if etag:
        etag_bytes = etag.encode('utf-8')
        etag_hash = sha256(etag_bytes)
        filename += '.' + etag_hash.hexdigest()

    return filename


def filename_to_url(filename, cache_dir=None):
    """
    Return the url and etag (which may be ``None``) stored for `filename`.
    Raise ``EnvironmentError`` if `filename` or its stored metadata do not exist.
    """
    if cache_dir is None:
        cache_dir = PYTORCH_FAIRSEQ_CACHE
    if isinstance(cache_dir, Path):
        cache_dir = str(cache_dir)

    cache_path = os.path.join(cache_dir, filename)
    if not os.path.exists(cache_path):
        raise EnvironmentError("file {} not found".format(cache_path))

    meta_path = cache_path + '.json'
    if not os.path.exists(meta_path):
        raise EnvironmentError("file {} not found".format(meta_path))

    with open(meta_path, encoding="utf-8") as meta_file:
        metadata = json.load(meta_file)
    url = metadata['url']
    etag = metadata['etag']

    return url, etag


def cached_path(url_or_filename, cache_dir=None):
    """
    Given something that might be a URL (or might be a local path),
    determine which. If it's a URL, download the file and cache it, and
    return the path to the cached file. If it's already a local path,
    make sure the file exists and then return the path.
    """
    if cache_dir is None:
        cache_dir = PYTORCH_FAIRSEQ_CACHE
    if isinstance(url_or_filename, Path):
        url_or_filename = str(url_or_filename)
    if isinstance(cache_dir, Path):
        cache_dir = str(cache_dir)

    parsed = urlparse(url_or_filename)

    if parsed.scheme in ('http', 'https', 's3'):
        # URL, so get it from the cache (downloading if necessary)
        return get_from_cache(url_or_filename, cache_dir)
    elif os.path.exists(url_or_filename):
        # File, and it exists.
        return url_or_filename
    elif parsed.scheme == '':
        # File, but it doesn't exist.
        raise EnvironmentError("file {} not found".format(url_or_filename))
    else:
        # Something unknown
        raise ValueError("unable to parse {} as a URL or as a local path".format(url_or_filename))


def split_s3_path(url):
    """Split a full s3 path into the bucket name and path."""
    parsed = urlparse(url)
    if not parsed.netloc or not parsed.path:
        raise ValueError("bad s3 path {}".format(url))
    bucket_name = parsed.netloc
    s3_path = parsed.path
    # Remove '/' at beginning of path.
    if s3_path.startswith("/"):
        s3_path = s3_path[1:]
    return bucket_name, s3_path


def s3_request(func):
    """
    Wrapper function for s3 requests in order to create more helpful error
    messages.
    """

    @wraps(func)
    def wrapper(url, *args, **kwargs):
        from botocore.exceptions import ClientError
        try:
            return func(url, *args, **kwargs)
        except ClientError as exc:
            if int(exc.response["Error"]["Code"]) == 404:
                raise EnvironmentError("file {} not found".format(url))
            else:
                raise

    return wrapper


@s3_request
def s3_etag(url):
    """Check ETag on S3 object."""
    import boto3
    s3_resource = boto3.resource("s3")
    bucket_name, s3_path = split_s3_path(url)
    s3_object = s3_resource.Object(bucket_name, s3_path)
    return s3_object.e_tag


@s3_request
def s3_get(url, temp_file):
    """Pull a file directly from S3."""
    import boto3
    s3_resource = boto3.resource("s3")
    bucket_name, s3_path = split_s3_path(url)
    s3_resource.Bucket(bucket_name).download_fileobj(s3_path, temp_file)


def http_get(url, temp_file):
    import requests
    from tqdm import tqdm
    req = requests.get(url, stream=True)
    content_length = req.headers.get('Content-Length')
    total = int(content_length) if content_length is not None else None
    progress = tqdm(unit="B", total=total)
    for chunk in req.iter_content(chunk_size=1024):
        if chunk:  # filter out keep-alive new chunks
            progress.update(len(chunk))
            temp_file.write(chunk)
    progress.close()


def get_from_cache(url, cache_dir=None):
    """
    Given a URL, look for the corresponding dataset in the local cache.
    If it's not there, download it. Then return the path to the cached file.
    """
    if cache_dir is None:
        cache_dir = PYTORCH_FAIRSEQ_CACHE
    if isinstance(cache_dir, Path):
        cache_dir = str(cache_dir)

    if not os.path.exists(cache_dir):
        os.makedirs(cache_dir)

    # Get eTag to add to filename, if it exists.
    if url.startswith("s3://"):
        etag = s3_etag(url)
    else:
        try:
            import requests
            response = requests.head(url, allow_redirects=True)
            if response.status_code != 200:
                etag = None
            else:
                etag = response.headers.get("ETag")
        except EnvironmentError:
            etag = None

    filename = url_to_filename(url, etag)

    # get cache path to put the file
    cache_path = os.path.join(cache_dir, filename)

    # If we don't have a connection (etag is None) and can't identify the file
    # try to get the last downloaded one
    if not os.path.exists(cache_path) and etag is None:
        matching_files = fnmatch.filter(os.listdir(cache_dir), filename + '.*')
        matching_files = list(filter(lambda s: not s.endswith('.json'), matching_files))
        if matching_files:
            cache_path = os.path.join(cache_dir, matching_files[-1])

    if not os.path.exists(cache_path):
        # Download to temporary file, then copy to cache dir once finished.
        # Otherwise you get corrupt cache entries if the download gets interrupted.
        with tempfile.NamedTemporaryFile() as temp_file:
            logger.info("%s not found in cache, downloading to %s", url, temp_file.name)

            # GET file object
            if url.startswith("s3://"):
                s3_get(url, temp_file)
            else:
                http_get(url, temp_file)

            # we are copying the file before closing it, so flush to avoid truncation
            temp_file.flush()
            # shutil.copyfileobj() starts at the current position, so go to the start
            temp_file.seek(0)

            logger.info("copying %s to cache at %s", temp_file.name, cache_path)
            with open(cache_path, 'wb') as cache_file:
                shutil.copyfileobj(temp_file, cache_file)

            logger.info("creating metadata file for %s", cache_path)
            meta = {'url': url, 'etag': etag}
            meta_path = cache_path + '.json'
            with open(meta_path, 'w') as meta_file:
                output_string = json.dumps(meta)
                meta_file.write(output_string)

            logger.info("removing temp file %s", temp_file.name)

    return cache_path


def read_set_from_file(filename):
    '''
    Extract a de-duped collection (set) of text from a file.
    Expected file format is one item per line.
    '''
    collection = set()
    with open(filename, 'r', encoding='utf-8') as file_:
        for line in file_:
            collection.add(line.rstrip())
    return collection


def get_file_extension(path, dot=True, lower=True):
    ext = os.path.splitext(path)[1]
    ext = ext if dot else ext[1:]
    return ext.lower() if lower else ext
