/InfoSlicer-15/infoslicer/processing/Article_Builder.py

# Copyright (C) IBM Corporation 2008



from BeautifulSoup import Tag

from NewtifulSoup import NewtifulStoneSoup as BeautifulStoneSoup

from Article_Data import *

import re

import os

import logging



logger = logging.getLogger('infoslicer')



"""

Created by Christopher Leonard.



ID descriptions:

0 - picture

1 - heading

> 1 - anything



This class converts between DITA and article_data representation of articles. Badly in need of refactoring!

"""

def get_article_from_dita(image_path, dita):

    """

    This method takes an article in DITA format as input, parses the DITA, and outputs the corresponding article_data object

    """

    has_shortdesc = False

    input = BeautifulStoneSoup(dita)

    article_id = input.resourceid['id']

    current_section_id = ""

    current_p_id = ""

    sentence_data_list = []

    paragraph_data_list = []

    section_data_list = []

    if input.find("shortdesc") != None:

        paragraph_data=[]

        for ph in input.shortdesc.findAll("ph"):

            id = ph['id']

            source_sentence_id = id

            source_paragraph_id = "shortdesc"

            source_section_id = "shortdesc"

            source_article_id = article_id

            text = ph.renderContents().replace("\n", "").replace(" ", "").strip() + " "

            if text[0:5] == "Satur":

                logger.debug(unicode(text))

            sentence_data = Sentence_Data(id, source_article_id, source_section_id, source_paragraph_id, source_sentence_id, text)

            sentence_data_list.append(sentence_data)

        paragraph_data.append(Paragraph_Data("shortdesc", article_id, "shortdesc", "shortdesc", sentence_data_list))

        section_data = Section_Data("shortdesc", article_id, "shortdesc", paragraph_data)

        section_data_list.append(section_data)

        sentence_data_list = []

        input.shortdesc.extract()

        has_shortdesc = True

    taglist = input.findAll(re.compile("refbody|section|p|ph|image"))

    for i in xrange(len(taglist)):

        tag = taglist[len(taglist) - i - 1]

        if tag.name == "ph":

            id = tag['id']

            source_sentence_id = id

            source_paragraph_id = current_p_id

            source_section_id = current_section_id

            source_article_id = article_id

            text = tag.renderContents().replace("\n", "").replace(" ", "").strip() + " "

            sentence_data = Sentence_Data(id, source_article_id, source_section_id, source_paragraph_id, source_sentence_id, text)

            sentence_data_list.insert(0, sentence_data)

        elif tag.name == "p":

            if not tag.has_key("id"):

                id = -1

            else:

                id = tag['id']

            source_paragraph_id = id

            source_section_id = current_section_id

            source_article_id = article_id

            paragraph_data = Paragraph_Data(id, source_article_id, source_section_id, source_paragraph_id, sentence_data_list)

            paragraph_data_list.insert(0, paragraph_data)

            sentence_data_list = []

            current_p_id = id

        elif tag.name == "refbody" :

            if tag.findParent("reference").has_key("id"):

                id = "r" + tag.findParent("reference")['id']

            else:

                id = "r90000"

            source_section_id = id

            source_article_id = article_id

            section_data = Section_Data(id, source_article_id, source_section_id, paragraph_data_list)

            if has_shortdesc:

                section_data_list.insert(1,section_data)

            else:

                section_data_list.insert(0,section_data)

            if tag.findChild("title", recursive=False) != None:

                heading = tag.findChild('title').renderContents().replace("\n", "").replace(" ", "").strip()

                sen = Sentence_Data(1, source_article_id, source_section_id, 1, 1, heading)

                par = Paragraph_Data(1, source_article_id, source_section_id, 1, [sen])                    

                headingdata = Section_Data(1, source_article_id, source_section_id, [par])

                

                if has_shortdesc:

                    section_data_list.insert(1,headingdata)

                else:

                    section_data_list.insert(0,headingdata)                    

            paragraph_data_list = []

            current_section_id = tag.name[0] + id

            

        elif tag.name == "section":

            id = "s" + tag['id']

            source_section_id = id

            source_article_id = article_id



            section_data = Section_Data(id, source_article_id, source_section_id, paragraph_data_list)

            if has_shortdesc:

                section_data_list.insert(1,section_data)

            else:

                section_data_list.insert(0,section_data)

            if tag.findChild("title", recursive=False) != None:

                heading = tag.findChild('title').renderContents().replace("\n", "").replace(" ", "").strip()

                sen = Sentence_Data(1, source_article_id, source_section_id, 1, 1, heading)

                par = Paragraph_Data(1, source_article_id, source_section_id, 1, [sen])                    

                headingdata = Section_Data(1, source_article_id, source_section_id, [par])

                

                if has_shortdesc:

                    section_data_list.insert(1,headingdata)

                else:

                    section_data_list.insert(0,headingdata)

            paragraph_data_list = []

            current_section_id = id

            

        elif tag.name == "image":

            

            if tag.parent.name == "p":

                source_article_id = article_id

                text = image_path + '/' + tag['href']

                if not os.path.exists(text):

                    logger.info('cannot find image %s' % text)

                else:

                    picture_data = Picture_Data(source_article_id, text,

                            tag['orig_href'])

                    sentence_data_list.insert(0, picture_data)

            

    article_title = input.find("title").renderContents().replace("\n", "").strip()

    

    image_list = []

    imglist_tag = input.find(True, attrs={"id" : "imagelist"})

    if imglist_tag != None:

        for img in imglist_tag.findAll("image"):

            caption = img.findChild("alt")

            if caption != None:

                caption = caption.renderContents().replace("\n", "").strip()

            else:

                caption = ""

            if not os.path.exists(os.path.join(image_path, img['href'])):

                logger.info('cannot find image %s' % img['href'])

            else:

                image_list.append((img['href'], caption, img['orig_href']))

    

    data = Article_Data(article_id, article_id, article_title, "theme", section_data_list, image_list)                   

    

    return data





def get_dita_from_article(image_path, article):

    """

    This method takes as input an instance of the Article class.

    It calls the getData method of the article class to get the article_data representation of the article.

    It then constructs the corresponding DITA representation of the article.

    """

    article_data = article.getData()

    output = BeautifulStoneSoup("<?xml version='1.0' encoding='utf-8'?><!DOCTYPE reference PUBLIC \"-//IBM//DTD DITA IBM Reference//EN\" \"ibm-reference.dtd\"><reference><title>%s</title><prolog></prolog></reference>" % article_data.article_title)

    current_ref = output.reference            

    current_title = None



    for section in article_data.sections_data:

        #headings check

        if len(section.paragraphs_data) == 1 and len(section.paragraphs_data[0].sentences_data) == 1 and section.paragraphs_data[0].sentences_data[0].id == 1:

            paragraph = section.paragraphs_data[0]

            current_title = paragraph.sentences_data[0].text

        elif str(section.id).startswith("r"):

            reference_tag = _tag_generator(output, "reference", attrs=[("id", section.id.replace("r", ""))])

            if current_title != None:

                reference_tag.append(_tag_generator(output, "title", contents=current_title))

                current_title = None

            reference_tag.append(_tag_generator(output, "refbody"))

            for paragraph in section.paragraphs_data:

                if paragraph.id == "shortdesc":

                    paragraph_tag = _tag_generator(output, "shortdesc")

                else:

                    paragraph_tag = _tag_generator(output, "p", attrs=[("id", str(paragraph.id))])

                for sentence in paragraph.sentences_data:

                    ph_tag = _tag_generator(output, "ph", attrs=[("id", str(sentence.id))], contents = sentence.text)

                    paragraph_tag.append(ph_tag)

                reference_tag.refbody.append(paragraph_tag) 

            output.reference.append(reference_tag)

            current_ref = reference_tag.refbody

        else:

            if section.id == "shortdesc":

                section_tag = _tag_generator(output, "section", attrs=[("id", "shortdesc")])

            else:

                section_tag = _tag_generator(output, "section", attrs=[("id", str(section.id).replace("s", ""))])

            if current_title != None:

                section_tag.append(_tag_generator(output, "title", contents=current_title))

                current_title = None

            for paragraph in section.paragraphs_data:

                paragraph_tag = _tag_generator(output, "p", attrs=[("id", str(paragraph.id))])

                for sentence in paragraph.sentences_data:

                    if sentence.type == "sentence":

                        ph_tag = _tag_generator(output, "ph", attrs=[("id", str(sentence.id))], contents = sentence.text)

                        paragraph_tag.append(ph_tag)

                    elif sentence.type == "picture":

                        # switch image to relative path

                        text = sentence.text.replace(image_path, '') \

                                .lstrip('/')

                        image_tag = _tag_generator(output,

                                "image", attrs=[("href", text),

                                                ('orig_href', sentence.orig)])

                        paragraph_tag.append(image_tag)

                    else:

                        logger.ebiug(sentence.type)

                        

                section_tag.append(paragraph_tag)

            current_ref.append(section_tag)

        if current_title != None:

            current_ref.append('<section id="56756757"><p id="6875534"><ph id="65657657">%s</ph></p></section>' % current_title)

            current_title = None

    if article_data.image_list != []:

        for unnecessary_tag in output.findAll(True, attrs={"id" : "imagelist"}):

            unnecessary_tag.extract()

        image_list = _tag_generator(output, "reference", [("id", "imagelist")])

        output.reference.append(image_list)

        image_list_body = _tag_generator(output, "refbody")

        image_list.append(image_list_body)

        for image in article_data.image_list:

            image_tag = _tag_generator(output, "image", [("href", image[0]), ("orig_href", image[2])], "<alt>" + image[-1] + "</alt>")

            image_list_body.append(image_tag)

    dita = output.prettify()



    return dita

            

def _tag_generator(soup, name, attrs=[], contents=None):

    if attrs != []:

        new_tag = Tag(soup, name, attrs)

    else:

        new_tag = Tag(soup, name)

    if contents != None:

        new_tag.insert(0, contents)

    return new_tag