src/rewriter/gen_emoticon_rewriter_data.py

# -*- coding: utf-8 -*-
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"""Converter from emoticon data to embedded_dictionary.

Usage:
  python gen_emoticon_rewriter_data.py --input=input.tsv --output=output_header
"""

__author__ = "hidehiko"

from collections import defaultdict
import logging
import optparse
import re
import sys
from rewriter import embedded_dictionary_compiler


def ParseOptions():
  parser = optparse.OptionParser()
  parser.add_option('--input', dest='input', help='emoticon dictionary file')
  parser.add_option('--output', dest='output', help='output header file')
  return parser.parse_args()[0]


def GetDescription(key_list, key_count):
  """Generates a description from readings.

  We simply add 1) the most general reading and 2) the most specific reading.
  1) and 2) are simply approximated by checking the frequency of the readings.

  Args:
    key_list: a list of key strings.
    key_count: a dictionary of key to the number of key's occurence in the data
      file.
  Returns:
    the description string.
  """
  if len(key_list) == 1:
    return key_list[0]

  sorted_key_list = sorted(key_list, key=lambda key: (key_count[key], key))
  return '%s %s' % (sorted_key_list[-1], sorted_key_list[0])


def ReadEmoticonTsv(stream):
  """Read lines from stream to a Token dictionary for a embedded dictionary."""
  # Skip the first line (header).
  stream.next()

  data = []
  key_count = defaultdict(int)
  for line in stream:
    # The file format is:
    # value <tab> readings(space delimitered)
    field_list = line.rstrip('\n').split('\t')
    # Check the size of columns.
    if len(field_list) < 2:
      logging.critical('format error: %s', line)
      sys.exit(1)
    if len(field_list) > 3:
      logging.warning('ignore extra columns: %s', line)

    # \xE3\x80\x80 is full width space
    key_list = re.split(r'(?: |\xE3\x80\x80)+', field_list[1].strip())
    data.append((field_list[0], key_list))
    for key in key_list:
      key_count[key] += 1

  input_data = defaultdict(list)
  cost = 10
  for value, key_list in data:
    input_value = value
    if input_value == "":
      input_value = None
    description = GetDescription(key_list, key_count)
    if description == "":
      description = None

    for key in key_list:
      input_data[key].append(embedded_dictionary_compiler.Token(
          key, input_value, description, None, 0, 0, cost))
    cost += 10

  return input_data


def main():
  options = ParseOptions()
  with open(options.input, 'r') as input_stream:
    input_data = ReadEmoticonTsv(input_stream)

  with open(options.output, 'w') as output_stream:
    embedded_dictionary_compiler.Compile(
        'EmoticonData', input_data, output_stream)


if __name__ == '__main__':
  main()