"""Preprocessor for merging consecutive stream outputs for easier handling."""

# Copyright (c) IPython Development Team.
# Distributed under the terms of the Modified BSD License.

import re
from IPython.utils.log import get_logger

def cell_preprocessor(function):
    """
    Wrap a function to be executed on all cells of a notebook
    
    The wrapped function should have these parameters:
    
    cell : NotebookNode cell
        Notebook cell being processed
    resources : dictionary
        Additional resources used in the conversion process.  Allows
        preprocessors to pass variables into the Jinja engine.
    index : int
        Index of the cell being processed
    """
    
    def wrappedfunc(nb, resources):
        get_logger().debug(
                "Applying preprocessor: %s", function.__name__
            )
        for index, cell in enumerate(nb.cells):
            nb.cells[index], resources = function(cell, resources, index)
        return nb, resources
    return wrappedfunc

cr_pat = re.compile(r'.*\r(?=[^\n])')

@cell_preprocessor
def coalesce_streams(cell, resources, index):
    """
    Merge consecutive sequences of stream output into single stream
    to prevent extra newlines inserted at flush calls
    
    Parameters
    ----------
    cell : NotebookNode cell
        Notebook cell being processed
    resources : dictionary
        Additional resources used in the conversion process.  Allows
        transformers to pass variables into the Jinja engine.
    index : int
        Index of the cell being processed
    """
    
    outputs = cell.get('outputs', [])
    if not outputs:
        return cell, resources
    
    last = outputs[0]
    new_outputs = [last]
    for output in outputs[1:]:
        if (output.output_type == 'stream' and
            last.output_type == 'stream' and
            last.name == output.name
        ):
            last.text += output.text

        else:
            new_outputs.append(output)
            last = output
    
    # process \r characters
    for output in new_outputs:
        if output.output_type == 'stream' and '\r' in output.text:
            output.text = cr_pat.sub('', output.text)

    cell.outputs = new_outputs
    return cell, resources