#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sat Apr 30 22:47:15 2022

@author: elena
"""

#import logging
import cv2
import re
import os
from copy import deepcopy
import numpy as np 
import pytesseract
from scipy import stats
from ordered_set import OrderedSet

from .loggers import LoggingMixin
from .image_processing import BBox
from .classes import noDBArticle
#from .models import ReceipeString, Market
import receipe.models as models
from .linearalignment import LinearAlignment

from django.conf import settings
from django.utils import timezone

from django.contrib.postgres.search import TrigramSimilarity

# This regular expression will try to find dates in the document at
# hand and will match the following formats:
# - XX.YY.ZZZZ with XX + YY being 1 or 2 and ZZZZ being 2 or 4 digits
# - XX/YY/ZZZZ with XX + YY being 1 or 2 and ZZZZ being 2 or 4 digits
# - XX-YY-ZZZZ with XX + YY being 1 or 2 and ZZZZ being 2 or 4 digits
# - ZZZZ.XX.YY with XX + YY being 1 or 2 and ZZZZ being 2 or 4 digits
# - ZZZZ/XX/YY with XX + YY being 1 or 2 and ZZZZ being 2 or 4 digits
# - ZZZZ-XX-YY with XX + YY being 1 or 2 and ZZZZ being 2 or 4 digits
# - XX. MONTH ZZZZ with XX being 1 or 2 and ZZZZ being 2 or 4 digits
# - MONTH ZZZZ, with ZZZZ being 4 digits
# - MONTH XX, ZZZZ with XX being 1 or 2 and ZZZZ being 4 digits

DATE_REGEX = re.compile(
    r'(\b|(?!=([_-])))([0-9]{1,2})[\.\/-]([0-9]{1,2})[\.\/-]([0-9]{4}|[0-9]{2})(\b|(?=([_-])))|'   # NOQA: E501
    r'(\b|(?!=([_-])))([0-9]{4}|[0-9]{2})[\.\/-]([0-9]{1,2})[\.\/-]([0-9]{1,2})(\b|(?=([_-])))|'   # NOQA: E501
    r'(\b|(?!=([_-])))([0-9]{1,2}[\. ]+[^ ]{3,9} ([0-9]{4}|[0-9]{2}))(\b|(?=([_-])))|'   # NOQA: E501
    r'(\b|(?!=([_-])))([^\W\d_]{3,9} [0-9]{1,2}, ([0-9]{4}))(\b|(?=([_-])))|'
    r'(\b|(?!=([_-])))([^\W\d_]{3,9} [0-9]{4})(\b|(?=([_-])))'
)

STREET_REGEX = re.compile(r'[A-Z][a-z]{1,} \d{1,3}')
ZIP_REGEX = re.compile(r'\d{5} .*')    #Valid for Germany
PHONE_REGEX = re.compile(r'\d{4,}(\/|-| \/ | - )\d*')
FLOAT_REGEX = re.compile(r'(|-|\+)\d*(,|\.)\d*')
MULTIPLE_REGEX = re.compile(r'\d{1,}(x|X){1,}')


class ReceipeParser(LoggingMixin):
    logging_name = "receipeServer.parsing"
    
    def __init__(self, logging_group, debug=False, progress_callback=None):
        super().__init__()
        self.logging_group = logging_group
        os.makedirs(settings.SCRATCH_DIR, exist_ok=True)

        self.debug = debug
        self.archive_path = None
        self.date = None
        self.market = None
        self.articles = None
        self.total = None
        self.progress_callback = progress_callback
        self.knownArticles = OrderedSet([])
        self.unknownArticles = set([])
        
    def getLine(self,boxList: list) -> list:
        """Take a list of bounding boxes (with text) and combine them to (text) lines

        Args:
            boxList (list): The list containing all bounding boxes

        Returns:
            lines (list): a list of (text) lines (one bouning box per line)
        """

        lines = []
        idx = 0
        while idx < len(boxList):   
            line = [boxList[idx]]
            
            yref1 = boxList[idx].y
            yref2 = yref1 + boxList[idx].h
            idy = idx + 1
            #Iterate over all boxes
            while idy < len(boxList):
                yval1 = boxList[idy].y 
                yval2 = boxList[idy].y + boxList[idy].h

                #Calculate the length of overlapp between the two boxes
                l = np.abs(np.max([yval1,yref1]) - np.min([yval2,yref2]))
                
                #If distance combared to box 1 and box 2 is more than 50% and there is some overlapp include the box
                if l/boxList[idx].h > 0.5 and l/boxList[idy].h > 0.5 and not (yval2 < yref1 or yval1 > yref2):
                    line.append(boxList[idy])
                
                    idx = idx + 1
                    idy = idy + 1
                else:
                    idy = idy + 1
            
            line.sort(key=lambda s: s.x)
            lines.append(line)
            idx = idx + 1
            
        return lines

    def grouper(self, iterable: list, interval: int = 2) -> list:
        """Group iterable into lines, within interval height. I do not understand what the code does

        Args:
            iterable (list): The list containing all (character) bounding boxes
            interval (int):  Measure to decide if boxes should be included in line

        Returns:
            group (generator): returns a generator for the lines
        """
        prev = None
        group = []
        for item in iterable:
            if not prev or abs(item[1] - prev[1]) <= interval:
                group.append(item)
            else:
                yield group
                group = [item]
            prev = item
        if group:
            yield group

    def doOCR(self,imgwidth: int, rois: list, lines: list, h: float, border: int = 10) -> list:
        """For the given rois (image parts) apply OCR and return the corresponding text

        Args:
            imgwidth (int): Width of the total image
            rois (list): List containing the image fragments
            lines (list): List with the bounding boxes
            h (float): Mean lineheigth
            border: Padding to apply around the bounding box

        Returns:
            texts (list): a list of the text of the different lines
        """
        texts = []
    
        #Tesseract
        for idy in range(0,len(rois)):
            lineroi = rois[idy]
            linebox = lines[idy]
            
            tmptext = []
            
            for idx in range(len(lineroi)):
                lineimg = np.ones((h+2*border,imgwidth), np.uint8)*255
                lineimg[border:border+h,linebox[idx].x:linebox[idx].x+linebox[idx].w][:] = cv2.resize(lineroi[idx], (linebox[idx].w,h))
                tmptext.append(pytesseract.image_to_string(lineimg,lang='deu').strip())
            
            if tmptext != '':
                texts.append(tmptext)

        print(texts) 
        return texts
    
    def parse_date(self,text: str):
        """
        Returns the date of the receipe.
        """

        def __parser(ds, date_order):
            """
            Call dateparser.parse with a particular date ordering
            """
            import dateparser

            return dateparser.parse(
                ds,
                settings={
                    "DATE_ORDER": date_order,
                    "PREFER_DAY_OF_MONTH": "first",
                    "RETURN_AS_TIMEZONE_AWARE":
                    True
                }
            )

        def __filter(date):
            if date and date.year > 1900 and \
                    date <= timezone.now(): 
                return date
            return None

        date = None

        # Iterate through all regex matches in text and try to parse the date
        for m in re.finditer(DATE_REGEX, text):
            date_string = m.group(0)

            try:
                date = __parser(date_string, settings.DATE_ORDER)
            except (TypeError, ValueError):
                # Skip all matches that do not parse to a proper date
                continue

            date = __filter(date)
            if date is not None:
                break

        return date
    
    def parse_zip_city(self,text):
        zipCode = None
        city = None
        for m in re.findall(ZIP_REGEX, text):
            stringElements = m.split(' ')
            zipCode = stringElements[0]
            if len(stringElements) > 1:
                city = stringElements[1]
            return zipCode, city
        
    def parse_street_streetNum(self,text):
        street = None
        streetNum = None
        for m in re.findall(STREET_REGEX, text):
            stringElements = m.split(' ')
            street = stringElements[0]
            if len(stringElements) > 1:
                streetNum = stringElements[1]
            return street, streetNum
    
    def parse_phone(self,text):
        for m in re.finditer(PHONE_REGEX, text):
            return m.group(0)
            
    def parse_float(self,text):
        for m in re.finditer(FLOAT_REGEX, text):
            value = m.group(0)
            value = value.replace(',','.')
            try:
                value = float(value)
            except ValueError:
                value = 0
            return value
        return 0

    def extractMarket(self,lineText,allText):
        '''Extract market detail out of the quarter of lines (allow for some artefacts from logo)
        '''
        tmpMarket = models.Market()
        for line in lineText:
            if line[0] != '':
                tmpMarket.name = line[0]
                break
        
        roi = ''
        try:
            for idx in range(0,int(len(lineText)/4)):
                roi = roi + lineText[idx][0] +'\n'
        except IndexError:
            roi = ''
    
        try:
            tmpMarket.zipCode, tmpMarket.city = self.parse_zip_city(roi)
        except TypeError:
            try:
                tmpMarket.zipCode, tmpMarket.city = self.parse_zip_city(allText)
            except TypeError:
                tmpMarket.zipCode = ''
                tmpMarket.city = ''
                
        try:
            tmpMarket.street, tmpMarket.street_number = self.parse_street_streetNum(roi)
        except TypeError:
            try:
                tmpMarket.street, tmpMarket.street_number = self.parse_street_streetNum(allText)
            except TypeError:
                tmpMarket.street = ''
                tmpMarket.street_number = 0
            
        try:
            tmpMarket.phone = self.parse_phone(roi)
        except TypeError:
            try:
                tmpMarket.phone = self.parse_phone(allText)
            except TypeError:
                tmpMarket.phone = ''
                
        #TODO: Try some fuzzy search
        #markets = Market.objects.filter( name=tmpMarket.name, street=tmpMarket.street)
        # Trigram search for name and street
        markets = models.Market.objects.annotate(similarity=TrigramSimilarity('name', tmpMarket.name)).filter(similarity__gt=0.3).order_by("-similarity")
        markets = markets.annotate(similarity=TrigramSimilarity('street', tmpMarket.street)).filter(similarity__gt=0.3).order_by("-similarity")

        if len(markets) != 0:
            return markets[0]
        else:
            return tmpMarket
       
    def progress(self, current_progress, max_progress):
        if self.progress_callback:
            self.progress_callback(current_progress, max_progress)
            
    def fixString(self,oldString):
        newString = oldString.replace('Ä','A').replace('Ö','O').replace('Ü','U').replace('ä','a').replace('ö','o').replace('ü','u').replace('#','').replace('©','o').replace('“','').replace('*','').replace('‚',',')
        return newString
            
    def get_date(self):
        return self.date
    
    def get_market(self):
        return self.market
    
    def get_articles(self):
        return [self.knownArticles, self.unknownArticles]
    
    def get_total(self):
        return self.total
 
    def lineSegmentationSimple(self, img: np.array) -> list:
        #%% Dilate in y direction to detect text lines
        kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (75,2))
        dilate = cv2.dilate(cv2.bitwise_not(img), kernel, iterations=1)

        # Find contours and filter using aspect ratio
        # Remove non-text contours by filling in the contour
        edge = cv2.Canny(dilate, 100, 250)
        cnts = cv2.findContours(edge, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

        cnts = cnts[0] if len(cnts) == 2 else cnts[1]

        xall = []
        yall = []
        wall = []
        hall = []

        textBoxes = []

        for c in cnts:
            x,y,w,h = cv2.boundingRect(c)
            xall.append(x)
            yall.append(y)
            wall.append(w)
            hall.append(h)
    
        zscoreH = stats.zscore(hall)

        for idx in range(0,len(xall)):
            #ar = w / float(h)
            #if hall[idx] > lowerHbound:# and hall[idx] < upperHbound:
            if zscoreH[idx] > 0.1 and zscoreH[idx] < 1.4 and hall[idx] < wall[idx]:  
                tmp = BBox(xall[idx],yall[idx],wall[idx],hall[idx])
                textBoxes.append(tmp)
                #cv2.drawContours(color, [cnts[idx]], -1, (0, 255, 0), 3, cv2.LINE_AA)


        lines = self.getLine(textBoxes)
        lines.reverse()

        return lines

    def lineSegmentationMSER(self, img: np.array) -> list:
        mser = cv2.MSER_create()
        regions, bboxes = mser.detectRegions(img)

        hulls = [cv2.convexHull(p.reshape(-1, 1, 2)) for p in regions]

        bboxes_list = list()
        heights = list()

        for hull in hulls:
            x, y, w, h = cv2.boundingRect(hull)
            bboxes_list.append([x, y, x + w, y + h])  # Create list of bounding boxes, with each bbox containing the left-top and right-bottom coordinates
            heights.append(h)

        heights = sorted(heights)  # Sort heights
        median_height = heights[int(len(heights) / 2)] / 3  # Find third of the median height
        #print(median_height)

        bboxes_list = sorted(bboxes_list, key=lambda k: k[1])  # Sort the bounding boxes based on y1 coordinate ( y of the left-top coordinate )
        combined_bboxes = self.grouper(bboxes_list, median_height)  # Group the bounding boxes

        lines = []
        for group in combined_bboxes:
            x_min = min(group, key=lambda k: k[0])[0]  # Find min of x1
            x_max = max(group, key=lambda k: k[2])[2]  # Find max of x2
            y_min = min(group, key=lambda k: k[1])[1]  # Find min of y1
            y_max = max(group, key=lambda k: k[3])[3]  # Find max of y2
            if abs(y_min - y_max) < 3 * 3 * median_height and abs(y_min - y_max) > median_height and abs(x_min - x_max) > 100:
                #cv2.rectangle(img, (x_min, y_min), (x_max, y_max), (0, 255, 0), 2)
                lines.append(BBox(x_min,y_min,x_max-x_min,y_max-y_min))

        linesWithSplit = []
        for element in lines:
            edges = cv2.Canny(img[element.y:element.y+element.h,element.x:element.x+element.w],100,200)
            
            #imgplot = plt.imshow(edges)
            #Calculate projection onto x axis
            proj_v = np.sum(edges,0)
            
            #plt.plot(proj_v) 
            #plt.show()
            
            count = 0
            prev = 0
            indexend = 0
            zeroSequence = []
            gaplist = []

            #Find all gaps (projected value of 0)
            for i in range(0,len(proj_v)):
                if proj_v[i] == 0:
                    count += 1
                else:            
                    if count > prev:
                        prev = count
                        indexend = i
                        
                    if count > 70:
                        gaplist.append([prev,indexend-prev,indexend-1])
                        #indexend = 0
                    count = 0
                    prev = 0
                    indexend = 0
            
            #print("The longest sequence of 0's is "+str(prev))
            #print("index start at: "+ str(indexend-prev))
            #print("index ends at: "+ str(indexend-1))
            
            #Split the line at the borders of the gaps
            if len (gaplist) < 1:
                linesWithSplit.append([element])
            elif len (gaplist) == 1:
                tmpList = []
                tmpList.append( BBox(element.x,element.y,gaplist[0][1],element.h) )
                tmpList.append( BBox(element.x+gaplist[0][2],element.y,element.w-gaplist[0][2],element.h) )
                linesWithSplit.append(tmpList)
            else:
                tmpList = []
                for i in range(0,len(gaplist)):
                    if i == 0:
                        tmpList.append( BBox(element.x,element.y,gaplist[i][1],element.h) )
                    elif i < len(gaplist):
                        tmpList.append( BBox(element.x+gaplist[i-1][2],element.y,gaplist[i][1]-gaplist[i-1][2],element.h) )

                tmpList.append( BBox(element.x+gaplist[-1][2],element.y,element.w-gaplist[-1][2],element.h) )
                        
                linesWithSplit.append(tmpList)

        return linesWithSplit

    def parse(self,path,inputfile,source='cam'):
        self.knownArticles = set([])
        self.unknownArticles = set([])
        
        # Read image from which text needs to be extracted
        print(path)
        img = cv2.imread(path,cv2.IMREAD_GRAYSCALE)

        if source == 'cam':
            lines = self.lineSegmentationSimple(img)
        elif source == 'scanner':
            lines = self.lineSegmentationMSER(img)

        rois = []
        hsum = 0
        numh = 0

        for idx in range(0,len(lines)):
            line = lines[idx]

            tmproi = []
            for element in line:
                hsum = hsum + element.h
                numh = numh + 1
                #cv2.rectangle(color,(element.x,element.y),(element.x+element.w,element.y+element.h),(255,0,0),3)
                tmproi.append(img[element.y:element.y+element.h,element.x:element.x+element.w])

            
            rois.append(tmproi)
    
        hmean = hsum/numh
        h = int(hmean)

        #newimg = np.ones(((h+border)*len(rois)+2*border,len(img[0,:])), np.uint8)*255

        lineText = self.doOCR(len(img[0,:]), rois, lines, h)
        allText = pytesseract.image_to_string(img,lang='deu')
               
        #%% Extract market
        self.market = self.extractMarket(lineText,allText)
        print(self.market.name)
        print(self.market.street)
        print(self.market.street_number)
        print(self.market.zip_code)
        print(self.market.city)
        print(self.market.phone)
        
        #%% Extract date
        date = None
        
        for element in lineText:
            date = self.parse_date(' '.join(element))
            if date != None:
                break
        
        if date == None: 
            #Try again with OCR of the whole receipe
            date = self.parse_date(allText)
        
        self.date = date
        print(self.date)
        
        
        #%% Extract total
        self.total = 0
        for line in lineText:
            text = ' '.join(line)
            if 'EUR' in text or 'SUMME' in text or 'TOTAL' in text:
                value = self.parse_float(text)
                if value != 0:
                    self.total = value
                    break
        
        # If we find no result, try again with the total text
        if self.total == 0:
            for line in allText.split('\n'):
                text = line
                if 'EUR' in text or 'SUMME' in text or 'TOTAL' in text:
                    value = self.parse_float(text)
                    if value != 0:
                        self.total = value
                        break
                    
        print(self.total)            
        
        #%% Extract articles
        self.articles = []
        newArticle = noDBArticle()
        newArticle.quantity = 0
        for idx in range(5,len(lineText)):
            print(lineText[idx])
            text = ' '.join(lineText[idx])

            #The last import line of a receipe ends with the total or sum of prices, so afterwards we stop. 
            if ('EUR' in text or 'SUMME' in text or 'TOTAL' in text) and len(self.articles) > 1:
                break
            elif ('EUR' in text or 'SUMME' in text or 'TOTAL' in text) and len(self.articles) == 0:
                continue
            
            if newArticle.quantity <= 1:
                newArticle.quantity = 1
                
                #Runs only if regex found.
                for m in re.finditer(MULTIPLE_REGEX, text.replace(' ','').replace('\t','')):
                    string = m.group(0)
                    for k in re.finditer(r'\d{1,}', string):
                        newArticle.quantity = int(k.group(0))
                
                #TODO: Extract price per unit from this line
                
                #If multiple articles are found, there is no info on the article, so we skip the rest
                if newArticle.quantity > 1:
                    continue
                
            if len(lineText[idx]) > 1:
                newArticle.name = lineText[idx][0]
                newArticle.nameString = lineText[idx][0]
                newArticle.nameBBox = lines[idx][0]

            #for element in lineText[idx]:
            for idy in range(0,len(lineText[idx])):
                try:
                    newArticle.price = self.parse_float(lineText[idx][idy]) / newArticle.quantity
                except ZeroDivisionError:
                    print(newArticle.quantity)
                    newArticle.price = 0.01
                if newArticle.price != 0:
                    newArticle.priceString = lineText[idx][idy]
                    newArticle.priceBBox = lines[idx][idy]
                    break
                    
            newArticle.name = self.fixString(newArticle.name)
            copyOfNewArticle = deepcopy(newArticle)
            self.articles.append(copyOfNewArticle)
            newArticle.name=''
            newArticle.quantity = 0
            
        savedArticleMaps = models.ReceipeString.objects.all()
        
        alignmendObject = LinearAlignment(self.logging_group)
        
        for parsedArticle in self.articles:
            matches = models.Article.objects.annotate(similarity=TrigramSimilarity('name', parsedArticle.name)).filter(similarity__gt=0.3).order_by("-similarity")
            print(parsedArticle.name)
            print(matches)
            if len(matches) > 0:
                # We try to find out, if we already have added the same article
                tmpknownArticles = self.knownArticles.copy()
                sizeSet = len(tmpknownArticles)
                tmpknownArticles.add(matches[0])
                # If the size remain the same, then the article is alread in our list, so we have to increase the quantity by 1 and then add it
                if len(tmpknownArticles) == sizeSet:
                    # Elements of a set are not accessible directly, so we have to iterate over all elements
                    for element in self.knownArticles:
                        if element.name == article.name and element.id == article.id:
                            # For the comparision of two elements, the quantity does not count, so we remove it first
                            self.knownArticles.remove(matches[0])
                            article.quantity = article.quantity + 1
                            break
                        
                    
                    # Then we add same again, but with changed quantity.
                    self.knownArticles.add(matches[0])
                
                # Otherwise, we just add it
                else:
                    self.knownArticles.add(matches[0])

            else:
                tmpunknownArticles = self.unknownArticles.copy()
                sizeSet = len(tmpunknownArticles)
                tmpunknownArticles.add(parsedArticle)
                # If the size remain the same, then the article is alread in our list, so we have to increase the quantity by 1 and then add it
                if len(tmpunknownArticles) == sizeSet:
                    # Elements of a set are not accessible directly, so we have to iterate over all elements
                    for element in self.unknownArticles:
                        if element.name == parsedArticle.name:
                            parsedArticle.quantity = parsedArticle.quantity + 1
                            break
                        
                    # For the comparision of to elements, the quantity does not count, so we remove it first
                    try:
                        self.unknownArticles.remove(parsedArticle)
                    except KeyError:
                        pass
                    # Then we add same again, but with changed quantity.
                    self.unknownArticles.add(parsedArticle)

                # Otherwise, we just add it
                else:
                    self.unknownArticles.add(parsedArticle)

        '''
        for parsedArticle in self.articles:
            possibleMatches = []
            possibleMatchesScore = np.array([])
            for articleMaps in savedArticleMaps:   
                #print(parsedArticle.name)
                #print(articleMaps.receipeString)
                #TODO: Add lower case letter to alignment matrix  
                alignmendObject.setStrings(parsedArticle.name.upper(), articleMaps.receipeString.upper())
                try:
                    stringScore = alignmendObject.scoring()
                except KeyError:
                    stringScore = 0

                if stringScore > 0.75:
                    print(parsedArticle.name.upper()+'  '+articleMaps.receipeString.upper()+'  Score: '+str(stringScore))
                    possibleMatches.append([parsedArticle,articleMaps])
                    possibleMatchesScore = np.append(possibleMatchesScore, stringScore)
                    if stringScore == 1:
                        break
                
            
            if len(possibleMatches) > 0:
                maxIdx = np.argmax(possibleMatchesScore)
                
                # Take the article with best matching name
                # First entry of list is the parsedArticle, then we overwrite name and id with the known one from the DB
                article = possibleMatches[maxIdx][0]
                article.name = possibleMatches[maxIdx][1].receipeString
                article.id = possibleMatches[maxIdx][1].pk
                article.articleId = possibleMatches[maxIdx][1].article
                
                # We try to find out, if we already have added the same article
                tmpknownArticles = self.knownArticles.copy()
                sizeSet = len(tmpknownArticles)
                tmpknownArticles.add(article)
                # If the size remain the same, then the article is alread in our list, so we have to increase the quantity by 1 and then add it
                if len(tmpknownArticles) == sizeSet:
                    # Elements of a set are not accessible directly, so we have to iterate over all elements
                    for element in self.knownArticles:
                        if element.name == article.name and element.id == article.id:
                            # For the comparision of two elements, the quantity does not count, so we remove it first
                            self.knownArticles.remove(article)
                            article.quantity = article.quantity + 1
                            break
                        
                    
                    # Then we add same again, but with changed quantity.
                    self.knownArticles.add(article)
                
                # Otherwise, we just add it
                else:
                    self.knownArticles.add(article)

            else:
                tmpunknownArticles = self.unknownArticles.copy()
                sizeSet = len(tmpunknownArticles)
                tmpunknownArticles.add(parsedArticle)
                # If the size remain the same, then the article is alread in our list, so we have to increase the quantity by 1 and then add it
                if len(tmpunknownArticles) == sizeSet:
                    # Elements of a set are not accessible directly, so we have to iterate over all elements
                    for element in self.unknownArticles:
                        if element.name == parsedArticle.name:
                            parsedArticle.quantity = parsedArticle.quantity + 1
                            break
                        
                    # For the comparision of to elements, the quantity does not count, so we remove it first
                    try:
                        self.unknownArticles.remove(parsedArticle)
                    except KeyError:
                        pass
                    # Then we add same again, but with changed quantity.
                    self.unknownArticles.add(parsedArticle)

                # Otherwise, we just add it
                else:
                    self.unknownArticles.add(parsedArticle)
        '''