Exemple #1
0
def dataframe_to_serialized_dict(frame):
    import pandas.core.internals as _int
    block_manager = frame._data

    blocks = []
    axes = [ax for ax in block_manager.axes]

    for block in block_manager.blocks:
        values = block.values
        block_data = {}

        if isinstance(block, _int.DatetimeTZBlock):
            block_data['timezone'] = pa.lib.tzinfo_to_string(values.tz)
            if hasattr(values, 'values'):
                values = values.values
        elif isinstance(block, _int.CategoricalBlock):
            block_data.update(dictionary=values.categories,
                              ordered=values.ordered)
            values = values.codes
        block_data.update(placement=block.mgr_locs.as_array, block=values)

        # If we are dealing with an object array, pickle it instead. Note that
        # we do not use isinstance here because _int.CategoricalBlock is a
        # subclass of _int.ObjectBlock.
        if type(block) == _int.ObjectBlock:
            block_data['object'] = None
            block_data['block'] = builtin_pickle.dumps(
                values, protocol=builtin_pickle.HIGHEST_PROTOCOL)

        blocks.append(block_data)

    return {'blocks': blocks, 'axes': axes}
Exemple #2
0
def dataframe_to_serialized_dict(frame):
    import pandas.core.internals as _int
    block_manager = frame._data

    blocks = []
    axes = [ax for ax in block_manager.axes]

    for block in block_manager.blocks:
        values = block.values
        block_data = {}

        if isinstance(block, _int.DatetimeTZBlock):
            block_data['timezone'] = pa.lib.tzinfo_to_string(values.tz)
            if hasattr(values, 'values'):
                values = values.values
        elif isinstance(block, _int.CategoricalBlock):
            block_data.update(dictionary=values.categories,
                              ordered=values.ordered)
            values = values.codes
        block_data.update(
            placement=block.mgr_locs.as_array,
            block=values
        )

        # If we are dealing with an object array, pickle it instead. Note that
        # we do not use isinstance here because _int.CategoricalBlock is a
        # subclass of _int.ObjectBlock.
        if type(block) == _int.ObjectBlock:
            block_data['object'] = None
            block_data['block'] = builtin_pickle.dumps(
                values, protocol=builtin_pickle.HIGHEST_PROTOCOL)

        blocks.append(block_data)

    return {
        'blocks': blocks,
        'axes': axes
    }
Exemple #3
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def _pickle_to_buffer(x):
    pickled = builtin_pickle.dumps(x, protocol=builtin_pickle.HIGHEST_PROTOCOL)
    return py_buffer(pickled)
Exemple #4
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def _pickle_to_buffer(x):
    pickled = builtin_pickle.dumps(x, protocol=builtin_pickle.HIGHEST_PROTOCOL)
    return py_buffer(pickled)