#-----------------------------------------------------------------------------
# Copyright (c) 2012 - 2020, Anaconda, Inc., and Bokeh Contributors.
# All rights reserved.
#
# The full license is in the file LICENSE.txt, distributed with this software.
#-----------------------------------------------------------------------------
''' Helper functions for downloading and accessing sample data.

'''

#-----------------------------------------------------------------------------
# Boilerplate
#-----------------------------------------------------------------------------
import logging # isort:skip
log = logging.getLogger(__name__)

#-----------------------------------------------------------------------------
# Imports
#-----------------------------------------------------------------------------

# NOTE: since downloading sampledata is not a common occurrnce, non-stdlib
# imports are generally deferrered in this module

# Standard library imports
import hashlib
import json
from os import mkdir, remove
from os.path import abspath, dirname, exists, expanduser, isdir, isfile, join, splitext
from sys import stdout
from typing import Any, TextIO, cast
from urllib.parse import urljoin
from urllib.request import urlopen

#-----------------------------------------------------------------------------
# Globals and constants
#-----------------------------------------------------------------------------

__all__ = (
    'download',
)

DataFrame = Any

#-----------------------------------------------------------------------------
# General API
#-----------------------------------------------------------------------------

def download(progress: bool = True) -> None:
    ''' Download larger data sets for various Bokeh examples.

    '''
    data_dir = external_data_dir(create=True)
    print("Using data directory: %s" % data_dir)

    # HTTP requests are cheaper for us, and there is nothing private to protect
    s3 = 'http://sampledata.bokeh.org'
    files = json.load(open(join(dirname(__file__), "sampledata.json")))

    for filename, md5 in files:
        real_name, ext = splitext(filename)
        if ext == '.zip':
            if not splitext(real_name)[1]:
                real_name += ".csv"
        else:
            real_name += ext
        real_path = join(data_dir, real_name)

        if exists(real_path):
            local_md5 = hashlib.md5(open(real_path,'rb').read()).hexdigest()
            if local_md5 == md5:
                print(f"Skipping {filename!r} (checksum match)")
                continue
            else:
                print(f"Re-fetching {filename!r} (checksum mismatch)")

        _download_file(s3, filename, data_dir, progress=progress)

#-----------------------------------------------------------------------------
# Dev API
#-----------------------------------------------------------------------------

def external_csv(module: str, name: str, **kw: Any) -> DataFrame:
    '''

    '''
    from .dependencies import import_required
    pd = import_required('pandas', '%s sample data requires Pandas (http://pandas.pydata.org) to be installed' % module)
    return cast(Any, pd).read_csv(external_path(name), **kw)

def external_data_dir(create: bool = False) -> str:
    '''

    '''
    try:
        import yaml
    except ImportError:
        raise RuntimeError("'yaml' and 'pyyaml' are required to use bokeh.sampledata functions")

    bokeh_dir = _bokeh_dir(create=create)
    data_dir = join(bokeh_dir, "data")

    try:
        config = yaml.safe_load(open(join(bokeh_dir, 'config')))
        data_dir = expanduser(config['sampledata_dir'])
    except (IOError, TypeError):
        pass

    if not exists(data_dir):
        if not create:
            raise RuntimeError('bokeh sample data directory does not exist, please execute bokeh.sampledata.download()')
        print("Creating %s directory" % data_dir)
        try:
            mkdir(data_dir)
        except OSError:
            raise RuntimeError("could not create bokeh data directory at %s" % data_dir)
    else:
        if not isdir(data_dir):
            raise RuntimeError("%s exists but is not a directory" % data_dir)

    return data_dir

def external_path(filename: str) -> str:
    data_dir = external_data_dir()
    fn = join(data_dir, filename)
    if not exists(fn) and isfile(fn):
        raise RuntimeError('Could not locate external data file %s. Please execute bokeh.sampledata.download()' % fn)
    return fn

def package_csv(module: str, name: str, **kw: Any) -> DataFrame:
    '''

    '''
    from .dependencies import import_required
    pd = import_required('pandas', '%s sample data requires Pandas (http://pandas.pydata.org) to be installed' % module)
    return cast(Any, pd).read_csv(package_path(name), **kw)


def package_dir() -> str:
    '''

    '''
    return abspath(join(dirname(__file__), "..", "sampledata", "_data"))

def package_path(filename: str) -> str:
    '''

    '''
    return join(package_dir(), filename)

def open_csv(filename: str) -> TextIO:
    '''

    '''
    return open(filename, 'r', newline='', encoding='utf8')

#-----------------------------------------------------------------------------
# Private API
#-----------------------------------------------------------------------------

def _bokeh_dir(create: bool = False) -> str:
    '''

    '''
    bokeh_dir = join(expanduser("~"), ".bokeh")
    if not exists(bokeh_dir):
        if not create: return bokeh_dir
        print("Creating %s directory" % bokeh_dir)
        try:
            mkdir(bokeh_dir)
        except OSError:
            raise RuntimeError("could not create bokeh config directory at %s" % bokeh_dir)
    else:
        if not isdir(bokeh_dir):
            raise RuntimeError("%s exists but is not a directory" % bokeh_dir)
    return bokeh_dir

def _download_file(base_url: str, filename: str, data_dir: str, progress: bool = True) -> None:
    '''

    '''
    # These are actually somewhat expensive imports that added ~5% to overall
    # typical bokeh import times. Since downloading sampledata is not a common
    # action, we defer them to inside this function.
    from zipfile import ZipFile

    file_url = urljoin(base_url, filename)
    file_path = join(data_dir, filename)

    url = urlopen(file_url)

    with open(file_path, 'wb') as file:
        file_size = int(url.headers["Content-Length"])
        print("Downloading: %s (%d bytes)" % (filename, file_size))

        fetch_size = 0
        block_size = 16384

        while True:
            data = url.read(block_size)
            if not data:
                break

            fetch_size += len(data)
            file.write(data)

            if progress:
                status = "\r%10d [%6.2f%%]" % (fetch_size, fetch_size*100.0/file_size)
                stdout.write(status)
                stdout.flush()

    if progress:
        print()

    real_name, ext = splitext(filename)

    if ext == '.zip':
        if not splitext(real_name)[1]:
            real_name += ".csv"

        print("Unpacking: %s" % real_name)

        with ZipFile(file_path, 'r') as zip_file:
            zip_file.extract(real_name, data_dir)

        remove(file_path)

#-----------------------------------------------------------------------------
# Code
#-----------------------------------------------------------------------------
