from krita import *
from textblob import TextBlob
from textblob_de import TextBlobDE
import re
from html.parser import HTMLParser
import urllib.request
from wordart.svg_vorlagen import *


# define class HTML-Parser
class MyHTMLParser(HTMLParser):

    def __init__(self):
        super().__init__()
        self.data = []
        self.capture = False

    def handle_starttag(self, tag, attrs):
        if tag in ('p', 'h1'):
            self.capture = True

    def handle_endtag(self, tag):
        if tag in ('p', 'h1'):
            self.capture = False

    def handle_data(self, data):
        if self.capture:
            self.data.append(data)
            
            
# define object/class for analysis
class textforart:
    
    def __init__(self, language, sentence_lens, sentences, commas, polarity):    
       # Sprache
       self.language = language

       # Satz
       if len(sentences) == 0:
           sentences = ['Hello fellow human beeing ^.^']
       self.senctences = sentences
       
       # Sentence lengthes
       if len(sentence_lens) == 0:
           sentence_lens = [0]
       self.sentence_lens = sentence_lens       
       
       # Commas
       if len(commas) == 0:       
           commas = [0]
       self.commas = commas
            
       # Bewertung
       if len(polarity) == 0:        
           polarity = [0]
       self.polarity = polarity
       
       # Komplezität
       complexity = [0]
       self.complexity = ''

       
       # Satzlänge
       self.sentence_number = len(sentences)      
       self.min_sentence_length = min(sentence_lens)
       self.max_sentence_length = max(sentence_lens)
       self.mean_sentence_length = sum(sentence_lens) / len(sentences)  
       
       # Kommas
       self.number_commas = len(commas)
       self.min_number_commas = min(commas)
       self.max_number_commas = max(commas)
       self.mean_number_commas = len(commas)/ len(sentences)   
        
       # Bewertung
       self.sum_sentences_polarity = sum(polarity)
       self.min_sentences_polarity = min(polarity)
       self.max_sentences_polarity = max(polarity)
       self.mean_sentences_polarity = sum(polarity) / len(sentences)
        
       # Schätzer für Komplexität  
       self.max_complexity = 0
       self.min_complexity = 0
       self.mean_complexity = 0   
       
       # signatur Word -> mean purpose
       self.signatur_word = ''          
            
def add_svg(svg):
	
    clipboard = QGuiApplication.clipboard()
    mime_data = QMimeData()
    mime_data.setData('image/svg+xml', svg)
    clipboard.setMimeData(mime_data)
    Application.action('edit_paste').trigger()
    
def create_svg(svg):
    app = Krita.instance()
    # Document open?
    if app.activeDocument():
        #print("aktive document")
        doc = app.activeDocument() 
    else:
        #print("create document")
        doc = app.createDocument(800, 600, 'SVGA Test', 'RGBA', 'U8', '', 120.0)
        app.activeWindow().addView(doc)
        
    doc = app.createDocument(800, 600, 'SVGA Test', 'RGBA', 'U8', '', 120.0)
    app.activeWindow().addView(doc) 
    layer = doc.createVectorLayer('ColorSVG')
    layer.setName('ColorSVG')
    add_svg(svg)


def makeart(content, parser):

    parser.feed(urllib.request.urlopen(content).read().decode())
    linkdata = parser.data

    if linkdata is not None:
        # language
        language = ''

        # filtering parsed text
        text = ""
        for phrases in linkdata:
            phrases = phrases.rstrip("\n\r+0-9[]()+")
            # skip unwanted characters         
            text = text + phrases
         
    # create textblob
    blob = TextBlob(text)
    
    # language?
    for w in blob.words:
        if re.match(r"and", w):
            language = 'en'
        elif re.match(r"und", w):
            language = 'de'

    if language == 'de':
        blob = TextBlobDE(text)

    sentence_lens = []
    commas = []
    polarity = []

    # print polarity of sentences
    for sentence in blob.sentences:    
                # length of sentences
                sentence_lens.append(len(sentence))     
                # number of commas
                commas.append(len(re.findall(',', str(sentence))))       
                # polarity
                polarity.append(sentence.sentiment.polarity)
  
    # init new textforart object
    art = textforart(language, sentence_lens, blob.sentences, commas, polarity)   
   
    # make art out of object
    # fill color:#000000 # stroke color:#000000
    stroke = "rgb(" + str(round(125*(1/art.mean_number_commas))) + ", " + str(round(125 - art.min_sentences_polarity)) + ", " + str(round(125 - art.max_sentences_polarity)) + ")"
    fill = "rgb(" + str(round(125*(1/art.mean_number_commas))) + ", " + str(round(125 - art.min_sentences_polarity)) + ", " + str(round(125 - art.max_sentences_polarity)) + ")"

    # define with of svg
    heigh = 700- (10*art.mean_sentences_polarity)
    width = 700*art.mean_number_commas

    svg = design_svg(stroke, fill, heigh, width)
    create_svg(svg)