from .tags.core import ndarray


class Stream(ndarray.NDArrayType):
    """
    Used to put a streamed array into the tree.

    Examples
    --------
    Save a double-precision array with 1024 columns, one row at a
    time::

         >>> from asdf import AsdfFile, Stream
         >>> import numpy as np
         >>> ff = AsdfFile()
         >>> ff.tree['streamed'] = Stream([1024], np.float64)
         >>> with open('test.asdf', 'wb') as fd:
         ...     ff.write_to(fd)
         ...     for i in range(200):
         ...         nbytes = fd.write(
         ...                      np.array([i] * 1024, np.float64).tobytes())
    """

    name = None
    types = []

    def __init__(self, shape, dtype, strides=None):
        self._shape = shape
        self._datatype, self._byteorder = ndarray.numpy_dtype_to_asdf_datatype(dtype)
        self._strides = strides
        self._array = None

    def _make_array(self):
        self._array = None

    @classmethod
    def reserve_blocks(cls, data, ctx):
        if isinstance(data, Stream):
            yield ctx.blocks.get_streamed_block()

    @classmethod
    def from_tree(cls, data, ctx):
        return ndarray.NDArrayType.from_tree(data, ctx)

    @classmethod
    def to_tree(cls, data, ctx):
        ctx.blocks.get_streamed_block()

        result = {}
        result["source"] = -1
        result["shape"] = ["*"] + data._shape
        result["datatype"] = data._datatype
        result["byteorder"] = data._byteorder
        if data._strides is not None:
            result["strides"] = data._strides
        return result

    def __repr__(self):
        return f"Stream({self._shape}, {self._datatype}, strides={self._strides})"

    def __str__(self):
        return str(self.__repr__())