from __future__ import absolute_import

import sys
import os
import json
import importlib

from . import backend
from .set_default_backend import set_default_backend

_enabled_apis = set()


def _gen_missing_api(api, mod_name):
    def _missing_api(*args, **kwargs):
        raise ImportError('API "%s" is not supported by backend "%s".'
                          ' You can switch to other backends by setting'
                          ' the DGLBACKEND environment.' % (api, mod_name))
    return _missing_api

def load_backend(mod_name):
    # Load backend does four things:
    # (1) Import backend framework (PyTorch, MXNet, Tensorflow, etc.)
    # (2) Import DGL C library.  DGL imports it *after* PyTorch/MXNet/Tensorflow.  Otherwise
    #     DGL will crash with errors like `munmap_chunk(): invalid pointer`.
    # (3) Sets up the tensoradapter library path.
    # (4) Import the Python wrappers of the backend framework.  DGL does this last because
    #     it already depends on both the backend framework and the DGL C library.
    if mod_name == 'pytorch':
        import torch
        mod = torch
    elif mod_name == 'mxnet':
        import mxnet
        mod = mxnet
    elif mod_name == 'tensorflow':
        import tensorflow
        mod = tensorflow
    else:
        raise NotImplementedError('Unsupported backend: %s' % mod_name)

    from .._ffi.base import load_tensor_adapter # imports DGL C library
    version = mod.__version__
    load_tensor_adapter(mod_name, version)

    print('Using backend: %s' % mod_name, file=sys.stderr)
    mod = importlib.import_module('.%s' % mod_name, __name__)
    thismod = sys.modules[__name__]
    for api in backend.__dict__.keys():
        if api.startswith('__'):
            # ignore python builtin attributes
            continue
        if api == 'data_type_dict':
            # load data type
            if api not in mod.__dict__:
                raise ImportError('API "data_type_dict" is required but missing for'
                                  ' backend "%s".' % (mod_name))
            data_type_dict = mod.__dict__[api]()
            for name, dtype in data_type_dict.items():
                setattr(thismod, name, dtype)

            # override data type dict function
            setattr(thismod, 'data_type_dict', data_type_dict)
            setattr(thismod,
                    'reverse_data_type_dict',
                    {v: k for k, v in data_type_dict.items()})
            # log backend name
            setattr(thismod, 'backend_name', mod_name)
        else:
            # load functions
            if api in mod.__dict__:
                _enabled_apis.add(api)
                setattr(thismod, api, mod.__dict__[api])
            else:
                setattr(thismod, api, _gen_missing_api(api, mod_name))

def get_preferred_backend():
    config_path = os.path.join(os.path.expanduser('~'), '.dgl', 'config.json')
    backend_name = None
    if "DGLBACKEND" in os.environ:
        backend_name = os.getenv('DGLBACKEND')
    elif os.path.exists(config_path):
        with open(config_path, "r") as config_file:
            config_dict = json.load(config_file)
            backend_name = config_dict.get('backend', '').lower()

    if (backend_name in ['tensorflow', 'mxnet', 'pytorch']):
        return backend_name
    else:
        print("DGL backend not selected or invalid.  "
              "Assuming PyTorch for now.", file=sys.stderr)
        set_default_backend('pytorch')
        return 'pytorch'


load_backend(get_preferred_backend())


def is_enabled(api):
    """Return true if the api is enabled by the current backend.

    Parameters
    ----------
    api : str
        The api name.

    Returns
    -------
    bool
        True if the API is enabled by the current backend.
    """
    return api in _enabled_apis

def to_dgl_nd(data):
    return zerocopy_to_dgl_ndarray(data)

def from_dgl_nd(data):
    return zerocopy_from_dgl_ndarray(data)
