├── _config.yml ├── docs ├── _config.yml └── index.md ├── .gitattributes ├── Scrapers ├── emojiscraper.py └── top100scraper.py ├── top100.py ├── .gitignore ├── readme.md ├── milpy.py ├── SelenaBot.py └── emoji.py /_config.yml: -------------------------------------------------------------------------------- 1 | theme: jekyll-theme-architect -------------------------------------------------------------------------------- /docs/_config.yml: -------------------------------------------------------------------------------- 1 | theme: jekyll-theme-cayman -------------------------------------------------------------------------------- /.gitattributes: -------------------------------------------------------------------------------- 1 | # Auto detect text files and perform LF normalization 2 | * text=auto 3 | 4 | # Custom for Visual Studio 5 | *.cs diff=csharp 6 | 7 | # Standard to msysgit 8 | *.doc diff=astextplain 9 | *.DOC diff=astextplain 10 | *.docx diff=astextplain 11 | *.DOCX diff=astextplain 12 | *.dot diff=astextplain 13 | *.DOT diff=astextplain 14 | *.pdf diff=astextplain 15 | *.PDF diff=astextplain 16 | *.rtf diff=astextplain 17 | *.RTF diff=astextplain 18 | -------------------------------------------------------------------------------- /Scrapers/emojiscraper.py: -------------------------------------------------------------------------------- 1 | #! /env/bin/python3 2 | 3 | ''' 4 | Emoji scraper goes to the unicode website and makes a big long list of the emoji characters maybe 5 | ''' 6 | 7 | import requests, os, pprint 8 | from bs4 import BeautifulSoup 9 | 10 | url = 'http://unicode.org/emoji/charts/full-emoji-list.html' 11 | emoji =[] 12 | 13 | r= requests.get(url) 14 | soup = BeautifulSoup(r.text,'html.parser') 15 | emojiSoup = soup.select('.chars') 16 | for e in emojiSoup: 17 | emoji.append(e.getText()) 18 | 19 | print(str(emoji)) 20 | 21 | allEmojiFile = open('emoji.py','w') 22 | allEmojiFile.write('emoji = '+pprint.pformat(emoji)+'\n') 23 | allEmojiFile.close() -------------------------------------------------------------------------------- /Scrapers/top100scraper.py: -------------------------------------------------------------------------------- 1 | #! /env/bin/python3 2 | ''' 3 | this app scrapes an instagram tracking site for the top 100 accounts 4 | ''' 5 | 6 | import requests, os 7 | from bs4 import BeautifulSoup 8 | 9 | Archive = os.path.join('.','Archive') 10 | if os.path.exists(Archive) == False: 11 | os.makedirs(Archive) 12 | 13 | r = requests.get('https://socialblade.com/instagram/top/100/followers') #access instagram tracking site 14 | soup = BeautifulSoup(r.text, "html.parser") 15 | grams = soup.find_all('div', class_="table-cell") #scrapes the content from the table on the page 16 | 17 | top100 = [] #produces top100 list 18 | for g in grams: # populates top 100 list 19 | a = g.find("a") 20 | if a is not None: 21 | top100.append(a.get_text()) 22 | 23 | if 'justinbieber' in top100: #Cleans up "Justin Bieber bug" 24 | top100.remove('justinbieber') 25 | top100.append('justnbieber') 26 | 27 | t100file = open(os.path.join('.','Archive','top100.txt'),'w') 28 | t100file.write(str(top100)) 29 | t100file.close() 30 | -------------------------------------------------------------------------------- /top100.py: -------------------------------------------------------------------------------- 1 | top100 = [ 2 | "instagram", "selenagomez", "arianagrande", 3 | "cristiano", "beyonce", "taylorswift", 4 | "kimkardashian", "kyliejenner", "therock", 5 | "kendalljenner", "nickiminaj", "natgeo", 6 | "neymarjr", "leomessi", "nike", 7 | "mileycyrus", "khloekardashian", 8 | "jlo", "katyperry", "ddlovato", 9 | "kourtneykardash", "victoriassecret", "badgalriri", 10 | "kevinhart4real", "realmadrid", "fcbarcelona", 11 | "theellenshow", "justintimberlake", "zendaya", 12 | "vindiesel", "9gag", "shakira", 13 | "caradelevingne", "chrisbrownofficial", 14 | "davidbeckham", "emmawatson", "champagnepapi", 15 | "gigihadid", "jamesrodriguez10", "kingjames", 16 | "garethbale11", "zacefron", "adele", 17 | "nikefootball", "maluma", "iamzlatanibrahimovic", 18 | "vanessahudgens", "nasa", "ronaldinho", 19 | "ladygaga", "nba", "shawnmendes", "luissuarez9", 20 | "chanelofficial", "zayn", "danbilzerian", 21 | "hm", "brumarquezine", "adidasfootball", 22 | "anitta", "adidasoriginals", "harrystyles", 23 | "zara", "ayutingting92", "hudabeauty", 24 | "camerondallas", "letthelordbewithyou", "karimbenzema", 25 | "marcelotwelve", "zachking", "niallhoran", 26 | "marinaruybarbosa", "nickyjampr", "natgeotravel", 27 | "deepikapadukone", "raffinagita1717", "andresiniesta8", 28 | "lucyhale", "princessyahrini", "sergioramos", 29 | "leonardodicaprio", "priyankachopra", "snoopdogg", 30 | "manchesterunited", "lelepons", "louisvuitton", 31 | "jbalvin", "prillylatuconsina96", "krisjenner", 32 | "shaymitchell", "laudyacynthiabella", "onedirection", 33 | "ashleybenson", "aliaabhatt", "britneyspears", 34 | "stephencurry30", "davidluiz_4", "amandacerny", 35 | "paulpogba", "justnbieber" 36 | ] -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | build/ 12 | develop-eggs/ 13 | dist/ 14 | downloads/ 15 | eggs/ 16 | .eggs/ 17 | lib/ 18 | lib64/ 19 | parts/ 20 | sdist/ 21 | var/ 22 | wheels/ 23 | *.egg-info/ 24 | .installed.cfg 25 | *.egg 26 | 27 | # PyInstaller 28 | # Usually these files are written by a python script from a template 29 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 30 | *.manifest 31 | *.spec 32 | 33 | # Installer logs 34 | pip-log.txt 35 | pip-delete-this-directory.txt 36 | 37 | # Unit test / coverage reports 38 | htmlcov/ 39 | .tox/ 40 | .coverage 41 | .coverage.* 42 | .cache 43 | nosetests.xml 44 | coverage.xml 45 | *.cover 46 | .hypothesis/ 47 | 48 | # Translations 49 | *.mo 50 | *.pot 51 | 52 | # Django stuff: 53 | *.log 54 | local_settings.py 55 | 56 | # Flask stuff: 57 | instance/ 58 | .webassets-cache 59 | 60 | # Scrapy stuff: 61 | .scrapy 62 | 63 | # Sphinx documentation 64 | docs/_build/ 65 | 66 | # PyBuilder 67 | target/ 68 | 69 | # Jupyter Notebook 70 | .ipynb_checkpoints 71 | 72 | # pyenv 73 | .python-version 74 | 75 | # celery beat schedule file 76 | celerybeat-schedule 77 | 78 | # SageMath parsed files 79 | *.sage.py 80 | 81 | # Environments 82 | .env 83 | .venv 84 | env/ 85 | venv/ 86 | ENV/ 87 | 88 | # Spyder project settings 89 | .spyderproject 90 | .spyproject 91 | 92 | # Rope project settings 93 | .ropeproject 94 | 95 | # mkdocs documentation 96 | /site 97 | 98 | # mypy 99 | .mypy_cache/ 100 | 101 | # SelenaBot Stuff 102 | SelenaBot_Pictures/ 103 | SelenaBot_Emoji/ 104 | SelenaBot_Captions/ 105 | Archive/ 106 | test/ 107 | 108 | .jpg 109 | -------------------------------------------------------------------------------- /docs/index.md: -------------------------------------------------------------------------------- 1 | # About SelenaBot 2 | SelenaBot goes through instagram and counts the emojis used in each of the captions of the top 100 most followed accounts, before tweeting the result on [@InstaTopEmoji](https://twitter.com/InstaTopEmoji) 3 | 4 | 5 | ## The Top 100 accounts 6 | According to [this website](https://socialblade.com/instagram/top/100/followers) 7 | 8 | * instagram 9 | * selenagomez 10 | * taylorswift 11 | * arianagrande 12 | * beyonce 13 | * kimkardashian 14 | * cristiano 15 | * kyliejenner 16 | * therock 17 | * kendalljenner 18 | * nickiminaj 19 | * nike 20 | * natgeo 21 | * neymarjr 22 | * leomessi 23 | * khloekardashian 24 | * katyperry 25 | * mileycyrus 26 | * jlo 27 | * ddlovato 28 | * kourtneykardash 29 | * victoriassecret 30 | * badgalriri 31 | * kevinhart4real 32 | * fcbarcelona 33 | * realmadrid 34 | * justintimberlake 35 | * theellenshow 36 | * zendaya 37 | * caradelevingne 38 | * 9gag 39 | * chrisbrownofficial 40 | * champagnepapi 41 | * davidbeckham 42 | * vindiesel 43 | * shakira 44 | * jamesrodriguez10 45 | * gigihadid 46 | * kingjames 47 | * garethbale11 48 | * nikefootball 49 | * zacefron 50 | * adele 51 | * vanessahudgens 52 | * emmawatson 53 | * iamzlatanibrahimovic 54 | * ladygaga 55 | * danbilzerian 56 | * nba 57 | * maluma 58 | * harrystyles 59 | * luissuarez9 60 | * ronaldinhooficial 61 | * letthelordbewithyou 62 | * nasa 63 | * adidasfootball 64 | * zayn 65 | * niallhoran 66 | * hm 67 | * brumarquezine 68 | * ayutingting92 69 | * shawnmendes 70 | * chanelofficial 71 | * camerondallas 72 | * onedirection 73 | * anitta 74 | * zachking 75 | * lucyhale 76 | * marinaruybarbosa 77 | * adidasoriginals 78 | * karimbenzema 79 | * hudabeauty 80 | * princessyahrini 81 | * krisjenner 82 | * andresiniesta8 83 | * davidluiz_4 84 | * manchesterunited 85 | * zara 86 | * itsashbenzo 87 | * nickyjampr 88 | * raffinagita1717 89 | * shaym 90 | * instagrambrasil 91 | * marcelotwelve 92 | * ciara 93 | * bellathorne 94 | * britneyspears 95 | * natgeotravel 96 | * snoopdogg 97 | * laudyacynthiabella 98 | * stephencurry30 99 | * prillylatuconsina96 100 | * louisvuitton 101 | * wizkhalifa 102 | * floydmayweather 103 | * deepikapadukone 104 | * sr4oficial 105 | * jbalvin 106 | * voguemagazine 107 | * tatawerneck 108 | -------------------------------------------------------------------------------- /readme.md: -------------------------------------------------------------------------------- 1 | # About SelenaBot 2 | SelenaBot is an script that uses BeautifulSoup and JSON to scrape instagram accounts: 3 | * It is named after [Selena Gomez](http://www.instagram.com/selenagomez), the undisputed queen of instagram. 4 | * It only requests the image files for pictures posted the previous day. **If you flood instagram/facebook for requests for all image files from an account, they stop responding to all your requests** 5 | * It outputs the files in their original JPGs with the filepaths 'username_YYYY-MM-DD_HH-MM' 6 | * Videos are currently downloaded as a JPG of the first frame. I have no need to download video files for my application so this isn't a thing I'm planning on developing. 7 | * It saves all the comments under all the images scraped in a textfile 8 | * It counts all the emojis used and outputs this as another text file 9 | 10 | The main job of SelenaBot is to generate the allPics list. Everything else in SelenaBot.py is dependent on the task you want it to do, based on the imformation in the allPics list. It is currently configured to scrape all the pictures and captions from the day before it is run, and count the frequency of each of the emojis used. 11 | 12 | 13 | 14 | ## the allPics list 15 | After crawling the page for the desired account, SelenaBot creates a list called allPics that contains 12 dictionaries, with each dictionary containing the following keys: 16 | 17 | * comments_disabled 18 | * video_views 19 | * thumbnail_src 20 | * likes 21 | * code 22 | * date 23 | * id 24 | * caption 25 | * display_src 26 | * is_video 27 | * dimensions 28 | * comments 29 | * owner 30 | 31 | These keys are fairly self explanatory. *Date* returns a unix timestamp, *display_src* & *thumbnail_src* return .jpg URLs of large and small versions of the image in question. *Likes* & *Video_Views* return integers of the respective image metrics. Important to note is these dictionary keys don't exist for images where they're irrelevant. E.g. if a picture doesn't have a caption, then the images dictionary wont have the *caption* key. 32 | 33 | ## emojiscraper.py 34 | This is a simple BeautifulSoup webscraper which scrapes the [official emoji list](unicode.org/emoji/charts/full-emoji-list.html) to produce emoji.py (see below). I plan to update this so it can automatically check if it's up-to-date. 35 | 36 | ## emoji.py 37 | A python list of all the characters that are emojis. 38 | 39 | ### how to use ### 40 | ~~~~ 41 | $ From emoji import emoji 42 | $ spam = 🍳 43 | $ spam in emoji 44 | True 45 | ~~~~ 46 | 47 | '**Skin Tone Modifiers:** Current implementation of selenabot really struggles with Skin Tone Modifiers. It counts them separately to the 'base' emoji that they're modifying. I plan on changing this in the long run, and I expect this process to be [fun](http://dwarffortresswiki.org/index.php/DF2014:Losing). 48 | 49 | ## top100gram.py 50 | SelenaBot is set up to take images posted by the top 100 most followed instagram accounts. Currently it finds this list by scraping [this website](http://socialblade.com/instagram/top/100/followers) using a BeautifulSoup scraper. This website doesn't appear to be updated very often so I might just replace this with a simple list. 51 | 52 | ## Windows 53 | I was originally developing this in windows. However windows hates emojis, making everything crash. Also IDLE hates emojis with similar results. Basically don't use windows or IDLE whenever you need python to do things where you can expect to run into lots of emojis in your strings. 54 | -------------------------------------------------------------------------------- /milpy.py: -------------------------------------------------------------------------------- 1 | #! /.env/bin/python3 2 | 3 | # M(att's) I(mage) L(ibrary) PY(thon) is a collection of my image processes that i've developed 4 | 5 | import os 6 | from PIL import Image 7 | from colorthief import ColorThief 8 | 9 | def folder_maker(directory,folder_name): 10 | folder = os.path.join(directory,folder_name) 11 | 12 | if os.path.exists(folder) == False: 13 | os.mkdir(folder) 14 | 15 | return folder 16 | 17 | def get_images_in_dir(directory , filetype): 18 | images = [os.path.join(directory,i) for i in os.listdir(directory) if os.path.isfile(os.path.join(directory,i)) and i.endswith(filetype)] 19 | 20 | return images 21 | 22 | def grid_printer(colors, size): 23 | mid = size//2 24 | grid =((0,0,mid,mid),(0,mid,mid,size),(mid,0,size,mid),(mid,mid,size,size)) 25 | 26 | im = Image.new('RGB',(size,size)) 27 | for x in range(4): 28 | im.paste(colors[x],grid[x]) 29 | 30 | return im 31 | 32 | 33 | def average_colors(image_to_average): # uses ColorThief to make a palette of the 4 most dominant colors in the image provided to it, returns a new image file of a 2x2 grid of those colors 34 | image_colors = ColorThief(image_to_average).get_palette(4) # creates a list of 4 tuples containing the RBG values of the 4 most dominant colors, see ColorThief docs for more info 35 | im_pallete = grid_printer(image_colors, 256) 36 | 37 | return im_pallete 38 | 39 | def pic_smoosher(images_to_smoosh): # combines multiple images into one big long image, currently only really works if the images provided are the same height & width 40 | images = map(Image.open, images_to_smoosh) 41 | widths, heights = zip(*(i.size for i in images)) 42 | 43 | total_width = sum(widths) 44 | max_height = max(heights) 45 | 46 | new_im = Image.new('RGB', (total_width, max_height)) 47 | 48 | images = map(Image.open, images_to_smoosh) 49 | x_offset = 0 50 | 51 | for im in images: 52 | new_im.paste(im, (x_offset,0)) 53 | x_offset += im.size[0] 54 | 55 | return new_im 56 | 57 | def bulk_picture_resizer(images_to_shrink, save_location, target_height): 58 | for count, picture in enumerate(images_to_shrink,1): 59 | img = Image.open(picture) 60 | w , h = img.size 61 | ratio = h / target_height 62 | print(count, 'of', len(images_to_shrink),'shrinking',picture) 63 | resized_img = img.resize((int(w/ratio),int(h/ratio))) 64 | resized_img.convert('RGB').save(os.path.join(save_location,'shrunk_' + os.path.basename(picture))) 65 | 66 | def multi_image_average(images_to_average): 67 | home_folder = os.path.dirname(images_to_average[0]) 68 | save_location = folder_maker(home_folder,'shrunk') 69 | combined_image_filename = os.path.join(save_location,'combined_image.jpg') 70 | average_pallete_filename = os.path.join(home_folder,'1_average_colors.jpg') 71 | 72 | print('Shrinking pictures') 73 | bulk_picture_resizer(images_to_average, save_location, 256) 74 | 75 | shrunk_images = get_images_in_dir(save_location , '.jpg') 76 | 77 | print('Combining shrunken images') 78 | combined_images = pic_smoosher(shrunk_images) 79 | combined_images.save(combined_image_filename) 80 | 81 | print('Finding average color of combined image') 82 | combined_image_palette = average_colors(combined_image_filename) 83 | combined_image_palette.save(average_pallete_filename) 84 | 85 | def directory_image_average(directory, filetype): 86 | images = get_images_in_dir(directory, filetype) 87 | multi_image_average(images) 88 | 89 | ''' 90 | shrunk_folder = folder_maker(directory) 91 | files = [os.path.join(directory,i) for i in os.listdir(directory) if os.path.isfile(os.path.join(directory,i)) and i.endswith(".jpg")] 92 | ''' -------------------------------------------------------------------------------- /SelenaBot.py: -------------------------------------------------------------------------------- 1 | #! /.env/bin/python3 2 | 3 | ''' 4 | BeautifulSoup Instagram Scraper that gets all pictures posted by celebrities yesterday (max 12 pictures per celeb) 5 | ''' 6 | 7 | import requests 8 | import json 9 | import os 10 | import pprint 11 | import sys 12 | import tweepy 13 | import milpy 14 | from collections import Counter 15 | from bs4 import BeautifulSoup 16 | from datetime import datetime, timedelta 17 | from top100 import top100 18 | from emoji import emoji 19 | 20 | #Configuration 21 | instagram = 'http://www.instagram.com/' 22 | yesterday = (datetime.today()- timedelta(days=1)).strftime('%Y-%m-%d') 23 | pictureFolder = os.path.join('.','SelenaBot_Pictures',yesterday) 24 | captionFolder = os.path.join('.','SelenaBot_Captions') 25 | emojiFolder = os.path.join('.','SelenaBot_Emoji') 26 | captionFilepath = os.path.join(captionFolder, yesterday +'_captions.txt') 27 | emojiFilepath = os.path.join(emojiFolder, yesterday +'_emoji.txt') 28 | 29 | for p in [pictureFolder, captionFolder, emojiFolder]: #makes the prequiste folders, if they don't already exits 30 | if os.path.exists(p) == False: 31 | os.makedirs(p) 32 | 33 | def make_twitter_api(profile): 34 | AUTH_FILE = sys.argv[1] 35 | with open(AUTH_FILE, "r") as auth_file: 36 | auth_data = json.load(auth_file) 37 | 38 | profile_auth_data = auth_data[profile] 39 | 40 | auth = tweepy.OAuthHandler(profile_auth_data["consumer_key"],profile_auth_data["consumer_secret"]) 41 | auth.set_access_token(profile_auth_data["access_token"],profile_auth_data["access_secret"]) 42 | 43 | return tweepy.API(auth) 44 | 45 | def DateStamp(ds): 46 | d = datetime.fromtimestamp(ds) 47 | return d.strftime('%y-%m-%d_%H-%M-%S') 48 | 49 | def picFinder(account): 50 | try: 51 | rgram = requests.get(instagram + account) #accesses the instagram account 52 | rgram.raise_for_status() 53 | except requests.exceptions.HTTPError: #this handles exceptions if accounts get deleted or suspended. Does not handle exceptions for accounts made private 54 | print('\t \t ### ACCOUNT MISSING ###') 55 | else: 56 | selenaSoup=BeautifulSoup(rgram.text,'html.parser') 57 | pageJS = selenaSoup.select('script') #selects all the JavaScript on the page 58 | for i, j in enumerate(pageJS): #Converts pageJS to list of strings so i can calculate length for below. If BS4 has a neater way of doing this, I haven't found it. 59 | pageJS[i]=str(j) 60 | picInfo= sorted(pageJS,key=len, reverse=True)[0] #finds the longest bit of JavaScript on the page, which always contains the image data 61 | allPics = json.loads(str(picInfo)[52:-10])['entry_data']['ProfilePage'][0]['user']['media']['nodes'] 62 | 63 | return allPics 64 | 65 | def captionDownloader(picture): 66 | captions = [] 67 | captionFile = open(captionFilepath,'a') 68 | if 'caption' in picture.keys(): 69 | print('\tcopying caption for picture '+DateStamp(picture['date'])) 70 | captions.append(picture['caption']) 71 | captionFile.write(str(captions)) 72 | captionFile.close() 73 | 74 | def picDownloader(account): 75 | for picture in picFinder(account): 76 | if datetime.fromtimestamp(picture['date']).strftime('%Y-%m-%d') == yesterday: #finds pictures from yesterday 77 | print('\tDownloading picture '+DateStamp(picture['date'])) 78 | picRes = requests.get(picture['display_src']) 79 | picFileName = os.path.join(pictureFolder, account+'_'+DateStamp(picture['date'])+'.jpg') 80 | picFile = open(picFileName,'wb') 81 | 82 | for chunk in picRes.iter_content(100000): 83 | picFile.write(chunk) 84 | 85 | picFile.close() 86 | captionDownloader(picture) 87 | 88 | def emojiCounter(): 89 | print('Counting the emojis...') 90 | captions = open(captionFilepath,'r').read() #opens and read the captions file 91 | emojiList = [] 92 | for c in captions: 93 | if c in emoji: 94 | emojiList.append(c) 95 | emojiCount= Counter(emojiList) 96 | topEmoji=emojiCount.most_common(1) 97 | pprint.pprint(emojiCount) #outputs the count in the terminal 98 | for i, j in topEmoji: 99 | print('##########\nthe emoji '+ i +' was used ' +str(j)+' times on instagram yesterday!') 100 | #saves the count in a text file 101 | emojiFile= open(emojiFilepath,'w') 102 | emojiFile.write(pprint.pformat(emojiCount)) 103 | emojiFile.close() 104 | 105 | 106 | return topEmoji 107 | 108 | 109 | def main(): 110 | print('downloading pictures:') 111 | for c, account in enumerate(top100,1): 112 | print(c,'Pictures from today on '+account+'\'s Instagram') 113 | picDownloader(account) 114 | print('finding dominant colour') 115 | milpy.directory_image_average(pictureFolder, '.jpg') 116 | 117 | if len(sys.argv[1]) > 2: 118 | api = make_twitter_api('InstaTopEmoji') #updates InstaTopEmoji twitterbot 119 | for i, j in emojiCounter(): 120 | api.update_status('The most popular emoji on Celebrity Instagram yesterday was: '+ i +' which was used ' +str(j)+' times') 121 | 122 | api = make_twitter_api('instaverage') #updates instaverage twitterbot 123 | tweetpic = os.path.join(pictureFolder,'1_average_colors.jpg') 124 | api.update_with_media(tweetpic, status='the dominant colours on Celebrity Instagram yesterday were...') 125 | 126 | else: 127 | print('no twitter password entered, terminating without tweeting') 128 | 129 | 130 | if __name__ == '__main__': 131 | main() -------------------------------------------------------------------------------- /emoji.py: -------------------------------------------------------------------------------- 1 | emoji = ['😀', 2 | '😁', 3 | '😂', 4 | '\U0001f923', 5 | '😃', 6 | '😄', 7 | '😅', 8 | '😆', 9 | '😉', 10 | '😊', 11 | '😋', 12 | '😎', 13 | '😍', 14 | '😘', 15 | '😗', 16 | '😙', 17 | '😚', 18 | '☺', 19 | '🙂', 20 | '🤗', 21 | '🤔', 22 | '😐', 23 | '😑', 24 | '😶', 25 | '🙄', 26 | '😏', 27 | '😣', 28 | '😥', 29 | '😮', 30 | '🤐', 31 | '😯', 32 | '😪', 33 | '😫', 34 | '😴', 35 | '😌', 36 | '🤓', 37 | '😛', 38 | '😜', 39 | '😝', 40 | '\U0001f924', 41 | '😒', 42 | '😓', 43 | '😔', 44 | '😕', 45 | '🙃', 46 | '🤑', 47 | '😲', 48 | '☹', 49 | '🙁', 50 | '😖', 51 | '😞', 52 | '😟', 53 | '😤', 54 | '😢', 55 | '😭', 56 | '😦', 57 | '😧', 58 | '😨', 59 | '😩', 60 | '😬', 61 | '😰', 62 | '😱', 63 | '😳', 64 | '😵', 65 | '😡', 66 | '😠', 67 | '😇', 68 | '\U0001f920', 69 | '\U0001f921', 70 | '\U0001f925', 71 | '😷', 72 | '🤒', 73 | '🤕', 74 | '\U0001f922', 75 | '\U0001f927', 76 | '😈', 77 | '👿', 78 | '👹', 79 | '👺', 80 | '💀', 81 | '☠', 82 | '👻', 83 | '👽', 84 | '👾', 85 | '🤖', 86 | '💩', 87 | '😺', 88 | '😸', 89 | '😹', 90 | '😻', 91 | '😼', 92 | '😽', 93 | '🙀', 94 | '😿', 95 | '😾', 96 | '🙈', 97 | '🙉', 98 | '🙊', 99 | '👦', 100 | '👦🏻', 101 | '👦🏼', 102 | '👦🏽', 103 | '👦🏾', 104 | '👦🏿', 105 | '👧', 106 | '👧🏻', 107 | '👧🏼', 108 | '👧🏽', 109 | '👧🏾', 110 | '👧🏿', 111 | '👨', 112 | '👨🏻', 113 | '👨🏼', 114 | '👨🏽', 115 | '👨🏾', 116 | '👨🏿', 117 | '👩', 118 | '👩🏻', 119 | '👩🏼', 120 | '👩🏽', 121 | '👩🏾', 122 | '👩🏿', 123 | '👴', 124 | '👴🏻', 125 | '👴🏼', 126 | '👴🏽', 127 | '👴🏾', 128 | '👴🏿', 129 | '👵', 130 | '👵🏻', 131 | '👵🏼', 132 | '👵🏽', 133 | '👵🏾', 134 | '👵🏿', 135 | '👶', 136 | '👶🏻', 137 | '👶🏼', 138 | '👶🏽', 139 | '👶🏾', 140 | '👶🏿', 141 | '👼', 142 | '👼🏻', 143 | '👼🏼', 144 | '👼🏽', 145 | '👼🏾', 146 | '👼🏿', 147 | '👨\u200d⚕️', 148 | '👨🏻\u200d⚕️', 149 | '👨🏼\u200d⚕️', 150 | '👨🏽\u200d⚕️', 151 | '👨🏾\u200d⚕️', 152 | '👨🏿\u200d⚕️', 153 | '👩\u200d⚕️', 154 | '👩🏻\u200d⚕️', 155 | '👩🏼\u200d⚕️', 156 | '👩🏽\u200d⚕️', 157 | '👩🏾\u200d⚕️', 158 | '👩🏿\u200d⚕️', 159 | '👨\u200d🎓', 160 | '👨🏻\u200d🎓', 161 | '👨🏼\u200d🎓', 162 | '👨🏽\u200d🎓', 163 | '👨🏾\u200d🎓', 164 | '👨🏿\u200d🎓', 165 | '👩\u200d🎓', 166 | '👩🏻\u200d🎓', 167 | '👩🏼\u200d🎓', 168 | '👩🏽\u200d🎓', 169 | '👩🏾\u200d🎓', 170 | '👩🏿\u200d🎓', 171 | '👨\u200d🏫', 172 | '👨🏻\u200d🏫', 173 | '👨🏼\u200d🏫', 174 | '👨🏽\u200d🏫', 175 | '👨🏾\u200d🏫', 176 | '👨🏿\u200d🏫', 177 | '👩\u200d🏫', 178 | '👩🏻\u200d🏫', 179 | '👩🏼\u200d🏫', 180 | '👩🏽\u200d🏫', 181 | '👩🏾\u200d🏫', 182 | '👩🏿\u200d🏫', 183 | '👨\u200d⚖️', 184 | '👨🏻\u200d⚖️', 185 | '👨🏼\u200d⚖️', 186 | '👨🏽\u200d⚖️', 187 | '👨🏾\u200d⚖️', 188 | '👨🏿\u200d⚖️', 189 | '👩\u200d⚖️', 190 | '👩🏻\u200d⚖️', 191 | '👩🏼\u200d⚖️', 192 | '👩🏽\u200d⚖️', 193 | '👩🏾\u200d⚖️', 194 | '👩🏿\u200d⚖️', 195 | '👨\u200d🌾', 196 | '👨🏻\u200d🌾', 197 | '👨🏼\u200d🌾', 198 | '👨🏽\u200d🌾', 199 | '👨🏾\u200d🌾', 200 | '👨🏿\u200d🌾', 201 | '👩\u200d🌾', 202 | '👩🏻\u200d🌾', 203 | '👩🏼\u200d🌾', 204 | '👩🏽\u200d🌾', 205 | '👩🏾\u200d🌾', 206 | '👩🏿\u200d🌾', 207 | '👨\u200d🍳', 208 | '👨🏻\u200d🍳', 209 | '👨🏼\u200d🍳', 210 | '👨🏽\u200d🍳', 211 | '👨🏾\u200d🍳', 212 | '👨🏿\u200d🍳', 213 | '👩\u200d🍳', 214 | '👩🏻\u200d🍳', 215 | '👩🏼\u200d🍳', 216 | '👩🏽\u200d🍳', 217 | '👩🏾\u200d🍳', 218 | '👩🏿\u200d🍳', 219 | '👨\u200d🔧', 220 | '👨🏻\u200d🔧', 221 | '👨🏼\u200d🔧', 222 | '👨🏽\u200d🔧', 223 | '👨🏾\u200d🔧', 224 | '👨🏿\u200d🔧', 225 | '👩\u200d🔧', 226 | '👩🏻\u200d🔧', 227 | '👩🏼\u200d🔧', 228 | '👩🏽\u200d🔧', 229 | '👩🏾\u200d🔧', 230 | '👩🏿\u200d🔧', 231 | '👨\u200d🏭', 232 | '👨🏻\u200d🏭', 233 | '👨🏼\u200d🏭', 234 | '👨🏽\u200d🏭', 235 | '👨🏾\u200d🏭', 236 | '👨🏿\u200d🏭', 237 | '👩\u200d🏭', 238 | '👩🏻\u200d🏭', 239 | '👩🏼\u200d🏭', 240 | '👩🏽\u200d🏭', 241 | '👩🏾\u200d🏭', 242 | '👩🏿\u200d🏭', 243 | '👨\u200d💼', 244 | '👨🏻\u200d💼', 245 | '👨🏼\u200d💼', 246 | '👨🏽\u200d💼', 247 | '👨🏾\u200d💼', 248 | '👨🏿\u200d💼', 249 | '👩\u200d💼', 250 | '👩🏻\u200d💼', 251 | '👩🏼\u200d💼', 252 | '👩🏽\u200d💼', 253 | '👩🏾\u200d💼', 254 | '👩🏿\u200d💼', 255 | '👨\u200d🔬', 256 | '👨🏻\u200d🔬', 257 | '👨🏼\u200d🔬', 258 | '👨🏽\u200d🔬', 259 | '👨🏾\u200d🔬', 260 | '👨🏿\u200d🔬', 261 | '👩\u200d🔬', 262 | '👩🏻\u200d🔬', 263 | '👩🏼\u200d🔬', 264 | '👩🏽\u200d🔬', 265 | '👩🏾\u200d🔬', 266 | '👩🏿\u200d🔬', 267 | '👨\u200d💻', 268 | '👨🏻\u200d💻', 269 | '👨🏼\u200d💻', 270 | '👨🏽\u200d💻', 271 | '👨🏾\u200d💻', 272 | '👨🏿\u200d💻', 273 | '👩\u200d💻', 274 | '👩🏻\u200d💻', 275 | '👩🏼\u200d💻', 276 | '👩🏽\u200d💻', 277 | '👩🏾\u200d💻', 278 | '👩🏿\u200d💻', 279 | '👨\u200d🎤', 280 | '👨🏻\u200d🎤', 281 | '👨🏼\u200d🎤', 282 | '👨🏽\u200d🎤', 283 | '👨🏾\u200d🎤', 284 | '👨🏿\u200d🎤', 285 | '👩\u200d🎤', 286 | '👩🏻\u200d🎤', 287 | '👩🏼\u200d🎤', 288 | '👩🏽\u200d🎤', 289 | '👩🏾\u200d🎤', 290 | '👩🏿\u200d🎤', 291 | '👨\u200d🎨', 292 | '👨🏻\u200d🎨', 293 | '👨🏼\u200d🎨', 294 | '👨🏽\u200d🎨', 295 | '👨🏾\u200d🎨', 296 | '👨🏿\u200d🎨', 297 | '👩\u200d🎨', 298 | '👩🏻\u200d🎨', 299 | '👩🏼\u200d🎨', 300 | '👩🏽\u200d🎨', 301 | '👩🏾\u200d🎨', 302 | '👩🏿\u200d🎨', 303 | '👨\u200d✈️', 304 | '👨🏻\u200d✈️', 305 | '👨🏼\u200d✈️', 306 | '👨🏽\u200d✈️', 307 | '👨🏾\u200d✈️', 308 | '👨🏿\u200d✈️', 309 | '👩\u200d✈️', 310 | '👩🏻\u200d✈️', 311 | '👩🏼\u200d✈️', 312 | '👩🏽\u200d✈️', 313 | '👩🏾\u200d✈️', 314 | '👩🏿\u200d✈️', 315 | '👨\u200d🚀', 316 | '👨🏻\u200d🚀', 317 | '👨🏼\u200d🚀', 318 | '👨🏽\u200d🚀', 319 | '👨🏾\u200d🚀', 320 | '👨🏿\u200d🚀', 321 | '👩\u200d🚀', 322 | '👩🏻\u200d🚀', 323 | '👩🏼\u200d🚀', 324 | '👩🏽\u200d🚀', 325 | '👩🏾\u200d🚀', 326 | '👩🏿\u200d🚀', 327 | '👨\u200d🚒', 328 | '👨🏻\u200d🚒', 329 | '👨🏼\u200d🚒', 330 | '👨🏽\u200d🚒', 331 | '👨🏾\u200d🚒', 332 | '👨🏿\u200d🚒', 333 | '👩\u200d🚒', 334 | '👩🏻\u200d🚒', 335 | '👩🏼\u200d🚒', 336 | '👩🏽\u200d🚒', 337 | '👩🏾\u200d🚒', 338 | '👩🏿\u200d🚒', 339 | '👮', 340 | '👮🏻', 341 | '👮🏼', 342 | '👮🏽', 343 | '👮🏾', 344 | '👮🏿', 345 | '👮\u200d♂️', 346 | '👮🏻\u200d♂️', 347 | '👮🏼\u200d♂️', 348 | '👮🏽\u200d♂️', 349 | '👮🏾\u200d♂️', 350 | '👮🏿\u200d♂️', 351 | '👮\u200d♀️', 352 | '👮🏻\u200d♀️', 353 | '👮🏼\u200d♀️', 354 | '👮🏽\u200d♀️', 355 | '👮🏾\u200d♀️', 356 | '👮🏿\u200d♀️', 357 | '🕵', 358 | '🕵🏻', 359 | '🕵🏼', 360 | '🕵🏽', 361 | '🕵🏾', 362 | '🕵🏿', 363 | '🕵️\u200d♂️', 364 | '🕵🏻\u200d♂️', 365 | '🕵🏼\u200d♂️', 366 | '🕵🏽\u200d♂️', 367 | '🕵🏾\u200d♂️', 368 | '🕵🏿\u200d♂️', 369 | '🕵️\u200d♀️', 370 | '🕵🏻\u200d♀️', 371 | '🕵🏼\u200d♀️', 372 | '🕵🏽\u200d♀️', 373 | '🕵🏾\u200d♀️', 374 | '🕵🏿\u200d♀️', 375 | '💂', 376 | '💂🏻', 377 | '💂🏼', 378 | '💂🏽', 379 | '💂🏾', 380 | '💂🏿', 381 | '💂\u200d♂️', 382 | '💂🏻\u200d♂️', 383 | '💂🏼\u200d♂️', 384 | '💂🏽\u200d♂️', 385 | '💂🏾\u200d♂️', 386 | '💂🏿\u200d♂️', 387 | '💂\u200d♀️', 388 | '💂🏻\u200d♀️', 389 | '💂🏼\u200d♀️', 390 | '💂🏽\u200d♀️', 391 | '💂🏾\u200d♀️', 392 | '💂🏿\u200d♀️', 393 | '👷', 394 | '👷🏻', 395 | '👷🏼', 396 | '👷🏽', 397 | '👷🏾', 398 | '👷🏿', 399 | '👷\u200d♂️', 400 | '👷🏻\u200d♂️', 401 | '👷🏼\u200d♂️', 402 | '👷🏽\u200d♂️', 403 | '👷🏾\u200d♂️', 404 | '👷🏿\u200d♂️', 405 | '👷\u200d♀️', 406 | '👷🏻\u200d♀️', 407 | '👷🏼\u200d♀️', 408 | '👷🏽\u200d♀️', 409 | '👷🏾\u200d♀️', 410 | '👷🏿\u200d♀️', 411 | '👳', 412 | '👳🏻', 413 | '👳🏼', 414 | '👳🏽', 415 | '👳🏾', 416 | '👳🏿', 417 | '👳\u200d♂️', 418 | '👳🏻\u200d♂️', 419 | '👳🏼\u200d♂️', 420 | '👳🏽\u200d♂️', 421 | '👳🏾\u200d♂️', 422 | '👳🏿\u200d♂️', 423 | '👳\u200d♀️', 424 | '👳🏻\u200d♀️', 425 | '👳🏼\u200d♀️', 426 | '👳🏽\u200d♀️', 427 | '👳🏾\u200d♀️', 428 | '👳🏿\u200d♀️', 429 | '👱', 430 | '👱🏻', 431 | '👱🏼', 432 | '👱🏽', 433 | '👱🏾', 434 | '👱🏿', 435 | '👱\u200d♂️', 436 | '👱🏻\u200d♂️', 437 | '👱🏼\u200d♂️', 438 | '👱🏽\u200d♂️', 439 | '👱🏾\u200d♂️', 440 | '👱🏿\u200d♂️', 441 | '👱\u200d♀️', 442 | '👱🏻\u200d♀️', 443 | '👱🏼\u200d♀️', 444 | '👱🏽\u200d♀️', 445 | '👱🏾\u200d♀️', 446 | '👱🏿\u200d♀️', 447 | '🎅', 448 | '🎅🏻', 449 | '🎅🏼', 450 | '🎅🏽', 451 | '🎅🏾', 452 | '🎅🏿', 453 | '\U0001f936', 454 | '\U0001f936🏻', 455 | '\U0001f936🏼', 456 | '\U0001f936🏽', 457 | '\U0001f936🏾', 458 | '\U0001f936🏿', 459 | '👸', 460 | '👸🏻', 461 | '👸🏼', 462 | '👸🏽', 463 | '👸🏾', 464 | '👸🏿', 465 | '\U0001f934', 466 | '\U0001f934🏻', 467 | '\U0001f934🏼', 468 | '\U0001f934🏽', 469 | '\U0001f934🏾', 470 | '\U0001f934🏿', 471 | '👰', 472 | '👰🏻', 473 | '👰🏼', 474 | '👰🏽', 475 | '👰🏾', 476 | '👰🏿', 477 | '\U0001f935', 478 | '\U0001f935🏻', 479 | '\U0001f935🏼', 480 | '\U0001f935🏽', 481 | '\U0001f935🏾', 482 | '\U0001f935🏿', 483 | '\U0001f930', 484 | '\U0001f930🏻', 485 | '\U0001f930🏼', 486 | '\U0001f930🏽', 487 | '\U0001f930🏾', 488 | '\U0001f930🏿', 489 | '👲', 490 | '👲🏻', 491 | '👲🏼', 492 | '👲🏽', 493 | '👲🏾', 494 | '👲🏿', 495 | '🙍', 496 | '🙍🏻', 497 | '🙍🏼', 498 | '🙍🏽', 499 | '🙍🏾', 500 | '🙍🏿', 501 | '🙍\u200d♂️', 502 | '🙍🏻\u200d♂️', 503 | '🙍🏼\u200d♂️', 504 | '🙍🏽\u200d♂️', 505 | '🙍🏾\u200d♂️', 506 | '🙍🏿\u200d♂️', 507 | '🙍\u200d♀️', 508 | '🙍🏻\u200d♀️', 509 | '🙍🏼\u200d♀️', 510 | '🙍🏽\u200d♀️', 511 | '🙍🏾\u200d♀️', 512 | '🙍🏿\u200d♀️', 513 | '🙎', 514 | '🙎🏻', 515 | '🙎🏼', 516 | '🙎🏽', 517 | '🙎🏾', 518 | '🙎🏿', 519 | '🙎\u200d♂️', 520 | '🙎🏻\u200d♂️', 521 | '🙎🏼\u200d♂️', 522 | '🙎🏽\u200d♂️', 523 | '🙎🏾\u200d♂️', 524 | '🙎🏿\u200d♂️', 525 | '🙎\u200d♀️', 526 | '🙎🏻\u200d♀️', 527 | '🙎🏼\u200d♀️', 528 | '🙎🏽\u200d♀️', 529 | '🙎🏾\u200d♀️', 530 | '🙎🏿\u200d♀️', 531 | '🙅', 532 | '🙅🏻', 533 | '🙅🏼', 534 | '🙅🏽', 535 | '🙅🏾', 536 | '🙅🏿', 537 | '🙅\u200d♂️', 538 | '🙅🏻\u200d♂️', 539 | '🙅🏼\u200d♂️', 540 | '🙅🏽\u200d♂️', 541 | '🙅🏾\u200d♂️', 542 | '🙅🏿\u200d♂️', 543 | '🙅\u200d♀️', 544 | '🙅🏻\u200d♀️', 545 | '🙅🏼\u200d♀️', 546 | '🙅🏽\u200d♀️', 547 | '🙅🏾\u200d♀️', 548 | '🙅🏿\u200d♀️', 549 | '🙆', 550 | '🙆🏻', 551 | '🙆🏼', 552 | '🙆🏽', 553 | '🙆🏾', 554 | '🙆🏿', 555 | '🙆\u200d♂️', 556 | '🙆🏻\u200d♂️', 557 | '🙆🏼\u200d♂️', 558 | '🙆🏽\u200d♂️', 559 | '🙆🏾\u200d♂️', 560 | '🙆🏿\u200d♂️', 561 | '🙆\u200d♀️', 562 | '🙆🏻\u200d♀️', 563 | '🙆🏼\u200d♀️', 564 | '🙆🏽\u200d♀️', 565 | '🙆🏾\u200d♀️', 566 | '🙆🏿\u200d♀️', 567 | '💁', 568 | '💁🏻', 569 | '💁🏼', 570 | '💁🏽', 571 | '💁🏾', 572 | '💁🏿', 573 | '💁\u200d♂️', 574 | '💁🏻\u200d♂️', 575 | '💁🏼\u200d♂️', 576 | '💁🏽\u200d♂️', 577 | '💁🏾\u200d♂️', 578 | '💁🏿\u200d♂️', 579 | '💁\u200d♀️', 580 | '💁🏻\u200d♀️', 581 | '💁🏼\u200d♀️', 582 | '💁🏽\u200d♀️', 583 | '💁🏾\u200d♀️', 584 | '💁🏿\u200d♀️', 585 | '🙋', 586 | '🙋🏻', 587 | '🙋🏼', 588 | '🙋🏽', 589 | '🙋🏾', 590 | '🙋🏿', 591 | '🙋\u200d♂️', 592 | '🙋🏻\u200d♂️', 593 | '🙋🏼\u200d♂️', 594 | '🙋🏽\u200d♂️', 595 | '🙋🏾\u200d♂️', 596 | '🙋🏿\u200d♂️', 597 | '🙋\u200d♀️', 598 | '🙋🏻\u200d♀️', 599 | '🙋🏼\u200d♀️', 600 | '🙋🏽\u200d♀️', 601 | '🙋🏾\u200d♀️', 602 | '🙋🏿\u200d♀️', 603 | '🙇', 604 | '🙇🏻', 605 | '🙇🏼', 606 | '🙇🏽', 607 | '🙇🏾', 608 | '🙇🏿', 609 | '🙇\u200d♂️', 610 | '🙇🏻\u200d♂️', 611 | '🙇🏼\u200d♂️', 612 | '🙇🏽\u200d♂️', 613 | '🙇🏾\u200d♂️', 614 | '🙇🏿\u200d♂️', 615 | '🙇\u200d♀️', 616 | '🙇🏻\u200d♀️', 617 | '🙇🏼\u200d♀️', 618 | '🙇🏽\u200d♀️', 619 | '🙇🏾\u200d♀️', 620 | '🙇🏿\u200d♀️', 621 | '\U0001f926', 622 | '\U0001f926🏻', 623 | '\U0001f926🏼', 624 | '\U0001f926🏽', 625 | '\U0001f926🏾', 626 | '\U0001f926🏿', 627 | '\U0001f926\u200d♂️', 628 | '\U0001f926🏻\u200d♂️', 629 | '\U0001f926🏼\u200d♂️', 630 | '\U0001f926🏽\u200d♂️', 631 | '\U0001f926🏾\u200d♂️', 632 | '\U0001f926🏿\u200d♂️', 633 | '\U0001f926\u200d♀️', 634 | '\U0001f926🏻\u200d♀️', 635 | '\U0001f926🏼\u200d♀️', 636 | '\U0001f926🏽\u200d♀️', 637 | '\U0001f926🏾\u200d♀️', 638 | '\U0001f926🏿\u200d♀️', 639 | '\U0001f937', 640 | '\U0001f937🏻', 641 | '\U0001f937🏼', 642 | '\U0001f937🏽', 643 | '\U0001f937🏾', 644 | '\U0001f937🏿', 645 | '\U0001f937\u200d♂️', 646 | '\U0001f937🏻\u200d♂️', 647 | '\U0001f937🏼\u200d♂️', 648 | '\U0001f937🏽\u200d♂️', 649 | '\U0001f937🏾\u200d♂️', 650 | '\U0001f937🏿\u200d♂️', 651 | '\U0001f937\u200d♀️', 652 | '\U0001f937🏻\u200d♀️', 653 | '\U0001f937🏼\u200d♀️', 654 | '\U0001f937🏽\u200d♀️', 655 | '\U0001f937🏾\u200d♀️', 656 | '\U0001f937🏿\u200d♀️', 657 | '💆', 658 | '💆🏻', 659 | '💆🏼', 660 | '💆🏽', 661 | '💆🏾', 662 | '💆🏿', 663 | '💆\u200d♂️', 664 | '💆🏻\u200d♂️', 665 | '💆🏼\u200d♂️', 666 | '💆🏽\u200d♂️', 667 | '💆🏾\u200d♂️', 668 | '💆🏿\u200d♂️', 669 | '💆\u200d♀️', 670 | '💆🏻\u200d♀️', 671 | '💆🏼\u200d♀️', 672 | '💆🏽\u200d♀️', 673 | '💆🏾\u200d♀️', 674 | '💆🏿\u200d♀️', 675 | '💇', 676 | '💇🏻', 677 | '💇🏼', 678 | '💇🏽', 679 | '💇🏾', 680 | '💇🏿', 681 | '💇\u200d♂️', 682 | '💇🏻\u200d♂️', 683 | '💇🏼\u200d♂️', 684 | '💇🏽\u200d♂️', 685 | '💇🏾\u200d♂️', 686 | '💇🏿\u200d♂️', 687 | '💇\u200d♀️', 688 | '💇🏻\u200d♀️', 689 | '💇🏼\u200d♀️', 690 | '💇🏽\u200d♀️', 691 | '💇🏾\u200d♀️', 692 | '💇🏿\u200d♀️', 693 | '🚶', 694 | '🚶🏻', 695 | '🚶🏼', 696 | '🚶🏽', 697 | '🚶🏾', 698 | '🚶🏿', 699 | '🚶\u200d♂️', 700 | '🚶🏻\u200d♂️', 701 | '🚶🏼\u200d♂️', 702 | '🚶🏽\u200d♂️', 703 | '🚶🏾\u200d♂️', 704 | '🚶🏿\u200d♂️', 705 | '🚶\u200d♀️', 706 | '🚶🏻\u200d♀️', 707 | '🚶🏼\u200d♀️', 708 | '🚶🏽\u200d♀️', 709 | '🚶🏾\u200d♀️', 710 | '🚶🏿\u200d♀️', 711 | '🏃', 712 | '🏃🏻', 713 | '🏃🏼', 714 | '🏃🏽', 715 | '🏃🏾', 716 | '🏃🏿', 717 | '🏃\u200d♂️', 718 | '🏃🏻\u200d♂️', 719 | '🏃🏼\u200d♂️', 720 | '🏃🏽\u200d♂️', 721 | '🏃🏾\u200d♂️', 722 | '🏃🏿\u200d♂️', 723 | '🏃\u200d♀️', 724 | '🏃🏻\u200d♀️', 725 | '🏃🏼\u200d♀️', 726 | '🏃🏽\u200d♀️', 727 | '🏃🏾\u200d♀️', 728 | '🏃🏿\u200d♀️', 729 | '💃', 730 | '💃🏻', 731 | '💃🏼', 732 | '💃🏽', 733 | '💃🏾', 734 | '💃🏿', 735 | '\U0001f57a', 736 | '\U0001f57a🏻', 737 | '\U0001f57a🏼', 738 | '\U0001f57a🏽', 739 | '\U0001f57a🏾', 740 | '\U0001f57a🏿', 741 | '👯', 742 | '👯\u200d♂️', 743 | '👯\u200d♀️', 744 | '🕴', 745 | '🕴🏻', 746 | '🕴🏼', 747 | '🕴🏽', 748 | '🕴🏾', 749 | '🕴🏿', 750 | '🗣', 751 | '👤', 752 | '👥', 753 | '\U0001f93a', 754 | '🏇', 755 | '🏇🏻', 756 | '🏇🏼', 757 | '🏇🏽', 758 | '🏇🏾', 759 | '🏇🏿', 760 | '⛷', 761 | '🏂', 762 | '🏂🏻', 763 | '🏂🏼', 764 | '🏂🏽', 765 | '🏂🏾', 766 | '🏂🏿', 767 | '🏌', 768 | '🏌🏻', 769 | '🏌🏼', 770 | '🏌🏽', 771 | '🏌🏾', 772 | '🏌🏿', 773 | '🏌️\u200d♂️', 774 | '🏌🏻\u200d♂️', 775 | '🏌🏼\u200d♂️', 776 | '🏌🏽\u200d♂️', 777 | '🏌🏾\u200d♂️', 778 | '🏌🏿\u200d♂️', 779 | '🏌️\u200d♀️', 780 | '🏌🏻\u200d♀️', 781 | '🏌🏼\u200d♀️', 782 | '🏌🏽\u200d♀️', 783 | '🏌🏾\u200d♀️', 784 | '🏌🏿\u200d♀️', 785 | '🏄', 786 | '🏄🏻', 787 | '🏄🏼', 788 | '🏄🏽', 789 | '🏄🏾', 790 | '🏄🏿', 791 | '🏄\u200d♂️', 792 | '🏄🏻\u200d♂️', 793 | '🏄🏼\u200d♂️', 794 | '🏄🏽\u200d♂️', 795 | '🏄🏾\u200d♂️', 796 | '🏄🏿\u200d♂️', 797 | '🏄\u200d♀️', 798 | '🏄🏻\u200d♀️', 799 | '🏄🏼\u200d♀️', 800 | '🏄🏽\u200d♀️', 801 | '🏄🏾\u200d♀️', 802 | '🏄🏿\u200d♀️', 803 | '🚣', 804 | '🚣🏻', 805 | '🚣🏼', 806 | '🚣🏽', 807 | '🚣🏾', 808 | '🚣🏿', 809 | '🚣\u200d♂️', 810 | '🚣🏻\u200d♂️', 811 | '🚣🏼\u200d♂️', 812 | '🚣🏽\u200d♂️', 813 | '🚣🏾\u200d♂️', 814 | '🚣🏿\u200d♂️', 815 | '🚣\u200d♀️', 816 | '🚣🏻\u200d♀️', 817 | '🚣🏼\u200d♀️', 818 | '🚣🏽\u200d♀️', 819 | '🚣🏾\u200d♀️', 820 | '🚣🏿\u200d♀️', 821 | '🏊', 822 | '🏊🏻', 823 | '🏊🏼', 824 | '🏊🏽', 825 | '🏊🏾', 826 | '🏊🏿', 827 | '🏊\u200d♂️', 828 | '🏊🏻\u200d♂️', 829 | '🏊🏼\u200d♂️', 830 | '🏊🏽\u200d♂️', 831 | '🏊🏾\u200d♂️', 832 | '🏊🏿\u200d♂️', 833 | '🏊\u200d♀️', 834 | '🏊🏻\u200d♀️', 835 | '🏊🏼\u200d♀️', 836 | '🏊🏽\u200d♀️', 837 | '🏊🏾\u200d♀️', 838 | '🏊🏿\u200d♀️', 839 | '⛹', 840 | '⛹🏻', 841 | '⛹🏼', 842 | '⛹🏽', 843 | '⛹🏾', 844 | '⛹🏿', 845 | '⛹️\u200d♂️', 846 | '⛹🏻\u200d♂️', 847 | '⛹🏼\u200d♂️', 848 | '⛹🏽\u200d♂️', 849 | '⛹🏾\u200d♂️', 850 | '⛹🏿\u200d♂️', 851 | '⛹️\u200d♀️', 852 | '⛹🏻\u200d♀️', 853 | '⛹🏼\u200d♀️', 854 | '⛹🏽\u200d♀️', 855 | '⛹🏾\u200d♀️', 856 | '⛹🏿\u200d♀️', 857 | '🏋', 858 | '🏋🏻', 859 | '🏋🏼', 860 | '🏋🏽', 861 | '🏋🏾', 862 | '🏋🏿', 863 | '🏋️\u200d♂️', 864 | '🏋🏻\u200d♂️', 865 | '🏋🏼\u200d♂️', 866 | '🏋🏽\u200d♂️', 867 | '🏋🏾\u200d♂️', 868 | '🏋🏿\u200d♂️', 869 | '🏋️\u200d♀️', 870 | '🏋🏻\u200d♀️', 871 | '🏋🏼\u200d♀️', 872 | '🏋🏽\u200d♀️', 873 | '🏋🏾\u200d♀️', 874 | '🏋🏿\u200d♀️', 875 | '🚴', 876 | '🚴🏻', 877 | '🚴🏼', 878 | '🚴🏽', 879 | '🚴🏾', 880 | '🚴🏿', 881 | '🚴\u200d♂️', 882 | '🚴🏻\u200d♂️', 883 | '🚴🏼\u200d♂️', 884 | '🚴🏽\u200d♂️', 885 | '🚴🏾\u200d♂️', 886 | '🚴🏿\u200d♂️', 887 | '🚴\u200d♀️', 888 | '🚴🏻\u200d♀️', 889 | '🚴🏼\u200d♀️', 890 | '🚴🏽\u200d♀️', 891 | '🚴🏾\u200d♀️', 892 | '🚴🏿\u200d♀️', 893 | '🚵', 894 | '🚵🏻', 895 | '🚵🏼', 896 | '🚵🏽', 897 | '🚵🏾', 898 | '🚵🏿', 899 | '🚵\u200d♂️', 900 | '🚵🏻\u200d♂️', 901 | '🚵🏼\u200d♂️', 902 | '🚵🏽\u200d♂️', 903 | '🚵🏾\u200d♂️', 904 | '🚵🏿\u200d♂️', 905 | '🚵\u200d♀️', 906 | '🚵🏻\u200d♀️', 907 | '🚵🏼\u200d♀️', 908 | '🚵🏽\u200d♀️', 909 | '🚵🏾\u200d♀️', 910 | '🚵🏿\u200d♀️', 911 | '🏎', 912 | '🏍', 913 | '\U0001f938', 914 | '\U0001f938🏻', 915 | '\U0001f938🏼', 916 | '\U0001f938🏽', 917 | '\U0001f938🏾', 918 | '\U0001f938🏿', 919 | '\U0001f938\u200d♂️', 920 | '\U0001f938🏻\u200d♂️', 921 | '\U0001f938🏼\u200d♂️', 922 | '\U0001f938🏽\u200d♂️', 923 | '\U0001f938🏾\u200d♂️', 924 | '\U0001f938🏿\u200d♂️', 925 | '\U0001f938\u200d♀️', 926 | '\U0001f938🏻\u200d♀️', 927 | '\U0001f938🏼\u200d♀️', 928 | '\U0001f938🏽\u200d♀️', 929 | '\U0001f938🏾\u200d♀️', 930 | '\U0001f938🏿\u200d♀️', 931 | '\U0001f93c', 932 | '\U0001f93c\u200d♂️', 933 | '\U0001f93c\u200d♀️', 934 | '\U0001f93d', 935 | '\U0001f93d🏻', 936 | '\U0001f93d🏼', 937 | '\U0001f93d🏽', 938 | '\U0001f93d🏾', 939 | '\U0001f93d🏿', 940 | '\U0001f93d\u200d♂️', 941 | '\U0001f93d🏻\u200d♂️', 942 | '\U0001f93d🏼\u200d♂️', 943 | '\U0001f93d🏽\u200d♂️', 944 | '\U0001f93d🏾\u200d♂️', 945 | '\U0001f93d🏿\u200d♂️', 946 | '\U0001f93d\u200d♀️', 947 | '\U0001f93d🏻\u200d♀️', 948 | '\U0001f93d🏼\u200d♀️', 949 | '\U0001f93d🏽\u200d♀️', 950 | '\U0001f93d🏾\u200d♀️', 951 | '\U0001f93d🏿\u200d♀️', 952 | '\U0001f93e', 953 | '\U0001f93e🏻', 954 | '\U0001f93e🏼', 955 | '\U0001f93e🏽', 956 | '\U0001f93e🏾', 957 | '\U0001f93e🏿', 958 | '\U0001f93e\u200d♂️', 959 | '\U0001f93e🏻\u200d♂️', 960 | '\U0001f93e🏼\u200d♂️', 961 | '\U0001f93e🏽\u200d♂️', 962 | '\U0001f93e🏾\u200d♂️', 963 | '\U0001f93e🏿\u200d♂️', 964 | '\U0001f93e\u200d♀️', 965 | '\U0001f93e🏻\u200d♀️', 966 | '\U0001f93e🏼\u200d♀️', 967 | '\U0001f93e🏽\u200d♀️', 968 | '\U0001f93e🏾\u200d♀️', 969 | '\U0001f93e🏿\u200d♀️', 970 | '\U0001f939', 971 | '\U0001f939🏻', 972 | '\U0001f939🏼', 973 | '\U0001f939🏽', 974 | '\U0001f939🏾', 975 | '\U0001f939🏿', 976 | '\U0001f939\u200d♂️', 977 | '\U0001f939🏻\u200d♂️', 978 | '\U0001f939🏼\u200d♂️', 979 | '\U0001f939🏽\u200d♂️', 980 | '\U0001f939🏾\u200d♂️', 981 | '\U0001f939🏿\u200d♂️', 982 | '\U0001f939\u200d♀️', 983 | '\U0001f939🏻\u200d♀️', 984 | '\U0001f939🏼\u200d♀️', 985 | '\U0001f939🏽\u200d♀️', 986 | '\U0001f939🏾\u200d♀️', 987 | '\U0001f939🏿\u200d♀️', 988 | '👫', 989 | '👬', 990 | '👭', 991 | '💏', 992 | '👩\u200d❤️\u200d💋\u200d👨', 993 | '👨\u200d❤️\u200d💋\u200d👨', 994 | '👩\u200d❤️\u200d💋\u200d👩', 995 | '💑', 996 | '👩\u200d❤️\u200d👨', 997 | '👨\u200d❤️\u200d👨', 998 | '👩\u200d❤️\u200d👩', 999 | '👪', 1000 | '👨\u200d👩\u200d👦', 1001 | '👨\u200d👩\u200d👧', 1002 | '👨\u200d👩\u200d👧\u200d👦', 1003 | '👨\u200d👩\u200d👦\u200d👦', 1004 | '👨\u200d👩\u200d👧\u200d👧', 1005 | '👨\u200d👨\u200d👦', 1006 | '👨\u200d👨\u200d👧', 1007 | '👨\u200d👨\u200d👧\u200d👦', 1008 | '👨\u200d👨\u200d👦\u200d👦', 1009 | '👨\u200d👨\u200d👧\u200d👧', 1010 | '👩\u200d👩\u200d👦', 1011 | '👩\u200d👩\u200d👧', 1012 | '👩\u200d👩\u200d👧\u200d👦', 1013 | '👩\u200d👩\u200d👦\u200d👦', 1014 | '👩\u200d👩\u200d👧\u200d👧', 1015 | '👨\u200d👦', 1016 | '👨\u200d👦\u200d👦', 1017 | '👨\u200d👧', 1018 | '👨\u200d👧\u200d👦', 1019 | '👨\u200d👧\u200d👧', 1020 | '👩\u200d👦', 1021 | '👩\u200d👦\u200d👦', 1022 | '👩\u200d👧', 1023 | '👩\u200d👧\u200d👦', 1024 | '👩\u200d👧\u200d👧', 1025 | '🏻', 1026 | '🏼', 1027 | '🏽', 1028 | '🏾', 1029 | '🏿', 1030 | '💪', 1031 | '💪🏻', 1032 | '💪🏼', 1033 | '💪🏽', 1034 | '💪🏾', 1035 | '💪🏿', 1036 | '\U0001f933', 1037 | '\U0001f933🏻', 1038 | '\U0001f933🏼', 1039 | '\U0001f933🏽', 1040 | '\U0001f933🏾', 1041 | '\U0001f933🏿', 1042 | '👈', 1043 | '👈🏻', 1044 | '👈🏼', 1045 | '👈🏽', 1046 | '👈🏾', 1047 | '👈🏿', 1048 | '👉', 1049 | '👉🏻', 1050 | '👉🏼', 1051 | '👉🏽', 1052 | '👉🏾', 1053 | '👉🏿', 1054 | '☝', 1055 | '☝🏻', 1056 | '☝🏼', 1057 | '☝🏽', 1058 | '☝🏾', 1059 | '☝🏿', 1060 | '👆', 1061 | '👆🏻', 1062 | '👆🏼', 1063 | '👆🏽', 1064 | '👆🏾', 1065 | '👆🏿', 1066 | '🖕', 1067 | '🖕🏻', 1068 | '🖕🏼', 1069 | '🖕🏽', 1070 | '🖕🏾', 1071 | '🖕🏿', 1072 | '👇', 1073 | '👇🏻', 1074 | '👇🏼', 1075 | '👇🏽', 1076 | '👇🏾', 1077 | '👇🏿', 1078 | '✌', 1079 | '✌🏻', 1080 | '✌🏼', 1081 | '✌🏽', 1082 | '✌🏾', 1083 | '✌🏿', 1084 | '\U0001f91e', 1085 | '\U0001f91e🏻', 1086 | '\U0001f91e🏼', 1087 | '\U0001f91e🏽', 1088 | '\U0001f91e🏾', 1089 | '\U0001f91e🏿', 1090 | '🖖', 1091 | '🖖🏻', 1092 | '🖖🏼', 1093 | '🖖🏽', 1094 | '🖖🏾', 1095 | '🖖🏿', 1096 | '🤘', 1097 | '🤘🏻', 1098 | '🤘🏼', 1099 | '🤘🏽', 1100 | '🤘🏾', 1101 | '🤘🏿', 1102 | '\U0001f919', 1103 | '\U0001f919🏻', 1104 | '\U0001f919🏼', 1105 | '\U0001f919🏽', 1106 | '\U0001f919🏾', 1107 | '\U0001f919🏿', 1108 | '🖐', 1109 | '🖐🏻', 1110 | '🖐🏼', 1111 | '🖐🏽', 1112 | '🖐🏾', 1113 | '🖐🏿', 1114 | '✋', 1115 | '✋🏻', 1116 | '✋🏼', 1117 | '✋🏽', 1118 | '✋🏾', 1119 | '✋🏿', 1120 | '👌', 1121 | '👌🏻', 1122 | '👌🏼', 1123 | '👌🏽', 1124 | '👌🏾', 1125 | '👌🏿', 1126 | '👍', 1127 | '👍🏻', 1128 | '👍🏼', 1129 | '👍🏽', 1130 | '👍🏾', 1131 | '👍🏿', 1132 | '👎', 1133 | '👎🏻', 1134 | '👎🏼', 1135 | '👎🏽', 1136 | '👎🏾', 1137 | '👎🏿', 1138 | '✊', 1139 | '✊🏻', 1140 | '✊🏼', 1141 | '✊🏽', 1142 | '✊🏾', 1143 | '✊🏿', 1144 | '👊', 1145 | '👊🏻', 1146 | '👊🏼', 1147 | '👊🏽', 1148 | '👊🏾', 1149 | '👊🏿', 1150 | '\U0001f91b', 1151 | '\U0001f91b🏻', 1152 | '\U0001f91b🏼', 1153 | '\U0001f91b🏽', 1154 | '\U0001f91b🏾', 1155 | '\U0001f91b🏿', 1156 | '\U0001f91c', 1157 | '\U0001f91c🏻', 1158 | '\U0001f91c🏼', 1159 | '\U0001f91c🏽', 1160 | '\U0001f91c🏾', 1161 | '\U0001f91c🏿', 1162 | '\U0001f91a', 1163 | '\U0001f91a🏻', 1164 | '\U0001f91a🏼', 1165 | '\U0001f91a🏽', 1166 | '\U0001f91a🏾', 1167 | '\U0001f91a🏿', 1168 | '👋', 1169 | '👋🏻', 1170 | '👋🏼', 1171 | '👋🏽', 1172 | '👋🏾', 1173 | '👋🏿', 1174 | '👏', 1175 | '👏🏻', 1176 | '👏🏼', 1177 | '👏🏽', 1178 | '👏🏾', 1179 | '👏🏿', 1180 | '✍', 1181 | '✍🏻', 1182 | '✍🏼', 1183 | '✍🏽', 1184 | '✍🏾', 1185 | '✍🏿', 1186 | '👐', 1187 | '👐🏻', 1188 | '👐🏼', 1189 | '👐🏽', 1190 | '👐🏾', 1191 | '👐🏿', 1192 | '🙌', 1193 | '🙌🏻', 1194 | '🙌🏼', 1195 | '🙌🏽', 1196 | '🙌🏾', 1197 | '🙌🏿', 1198 | '🙏', 1199 | '🙏🏻', 1200 | '🙏🏼', 1201 | '🙏🏽', 1202 | '🙏🏾', 1203 | '🙏🏿', 1204 | '\U0001f91d', 1205 | '💅', 1206 | '💅🏻', 1207 | '💅🏼', 1208 | '💅🏽', 1209 | '💅🏾', 1210 | '💅🏿', 1211 | '👂', 1212 | '👂🏻', 1213 | '👂🏼', 1214 | '👂🏽', 1215 | '👂🏾', 1216 | '👂🏿', 1217 | '👃', 1218 | '👃🏻', 1219 | '👃🏼', 1220 | '👃🏽', 1221 | '👃🏾', 1222 | '👃🏿', 1223 | '👣', 1224 | '👀', 1225 | '👁', 1226 | '👁️\u200d🗨️', 1227 | '👅', 1228 | '👄', 1229 | '💋', 1230 | '💘', 1231 | '❤', 1232 | '💓', 1233 | '💔', 1234 | '💕', 1235 | '💖', 1236 | '💗', 1237 | '💙', 1238 | '💚', 1239 | '💛', 1240 | '💜', 1241 | '\U0001f5a4', 1242 | '💝', 1243 | '💞', 1244 | '💟', 1245 | '❣', 1246 | '💌', 1247 | '💤', 1248 | '💢', 1249 | '💣', 1250 | '💥', 1251 | '💦', 1252 | '💨', 1253 | '💫', 1254 | '💬', 1255 | '🗨', 1256 | '🗯', 1257 | '💭', 1258 | '🕳', 1259 | '👓', 1260 | '🕶', 1261 | '👔', 1262 | '👕', 1263 | '👖', 1264 | '👗', 1265 | '👘', 1266 | '👙', 1267 | '👚', 1268 | '👛', 1269 | '👜', 1270 | '👝', 1271 | '🛍', 1272 | '🎒', 1273 | '👞', 1274 | '👟', 1275 | '👠', 1276 | '👡', 1277 | '👢', 1278 | '👑', 1279 | '👒', 1280 | '🎩', 1281 | '🎓', 1282 | '⛑', 1283 | '📿', 1284 | '💄', 1285 | '💍', 1286 | '💎', 1287 | '🐵', 1288 | '🐒', 1289 | '\U0001f98d', 1290 | '🐶', 1291 | '🐕', 1292 | '🐩', 1293 | '🐺', 1294 | '\U0001f98a', 1295 | '🐱', 1296 | '🐈', 1297 | '🦁', 1298 | '🐯', 1299 | '🐅', 1300 | '🐆', 1301 | '🐴', 1302 | '🐎', 1303 | '\U0001f98c', 1304 | '🦄', 1305 | '🐮', 1306 | '🐂', 1307 | '🐃', 1308 | '🐄', 1309 | '🐷', 1310 | '🐖', 1311 | '🐗', 1312 | '🐽', 1313 | '🐏', 1314 | '🐑', 1315 | '🐐', 1316 | '🐪', 1317 | '🐫', 1318 | '🐘', 1319 | '\U0001f98f', 1320 | '🐭', 1321 | '🐁', 1322 | '🐀', 1323 | '🐹', 1324 | '🐰', 1325 | '🐇', 1326 | '🐿', 1327 | '\U0001f987', 1328 | '🐻', 1329 | '🐨', 1330 | '🐼', 1331 | '🐾', 1332 | '🦃', 1333 | '🐔', 1334 | '🐓', 1335 | '🐣', 1336 | '🐤', 1337 | '🐥', 1338 | '🐦', 1339 | '🐧', 1340 | '🕊', 1341 | '\U0001f985', 1342 | '\U0001f986', 1343 | '\U0001f989', 1344 | '🐸', 1345 | '🐊', 1346 | '🐢', 1347 | '\U0001f98e', 1348 | '🐍', 1349 | '🐲', 1350 | '🐉', 1351 | '🐳', 1352 | '🐋', 1353 | '🐬', 1354 | '🐟', 1355 | '🐠', 1356 | '🐡', 1357 | '\U0001f988', 1358 | '🐙', 1359 | '🐚', 1360 | '🦀', 1361 | '\U0001f990', 1362 | '\U0001f991', 1363 | '\U0001f98b', 1364 | '🐌', 1365 | '🐛', 1366 | '🐜', 1367 | '🐝', 1368 | '🐞', 1369 | '🕷', 1370 | '🕸', 1371 | '🦂', 1372 | '💐', 1373 | '🌸', 1374 | '💮', 1375 | '🏵', 1376 | '🌹', 1377 | '\U0001f940', 1378 | '🌺', 1379 | '🌻', 1380 | '🌼', 1381 | '🌷', 1382 | '🌱', 1383 | '🌲', 1384 | '🌳', 1385 | '🌴', 1386 | '🌵', 1387 | '🌾', 1388 | '🌿', 1389 | '☘', 1390 | '🍀', 1391 | '🍁', 1392 | '🍂', 1393 | '🍃', 1394 | '🍇', 1395 | '🍈', 1396 | '🍉', 1397 | '🍊', 1398 | '🍋', 1399 | '🍌', 1400 | '🍍', 1401 | '🍎', 1402 | '🍏', 1403 | '🍐', 1404 | '🍑', 1405 | '🍒', 1406 | '🍓', 1407 | '\U0001f95d', 1408 | '🍅', 1409 | '\U0001f951', 1410 | '🍆', 1411 | '\U0001f954', 1412 | '\U0001f955', 1413 | '🌽', 1414 | '🌶', 1415 | '\U0001f952', 1416 | '🍄', 1417 | '\U0001f95c', 1418 | '🌰', 1419 | '🍞', 1420 | '\U0001f950', 1421 | '\U0001f956', 1422 | '\U0001f95e', 1423 | '🧀', 1424 | '🍖', 1425 | '🍗', 1426 | '\U0001f953', 1427 | '🍔', 1428 | '🍟', 1429 | '🍕', 1430 | '🌭', 1431 | '🌮', 1432 | '🌯', 1433 | '\U0001f959', 1434 | '\U0001f95a', 1435 | '🍳', 1436 | '\U0001f958', 1437 | '🍲', 1438 | '\U0001f957', 1439 | '🍿', 1440 | '🍱', 1441 | '🍘', 1442 | '🍙', 1443 | '🍚', 1444 | '🍛', 1445 | '🍜', 1446 | '🍝', 1447 | '🍠', 1448 | '🍢', 1449 | '🍣', 1450 | '🍤', 1451 | '🍥', 1452 | '🍡', 1453 | '🍦', 1454 | '🍧', 1455 | '🍨', 1456 | '🍩', 1457 | '🍪', 1458 | '🎂', 1459 | '🍰', 1460 | '🍫', 1461 | '🍬', 1462 | '🍭', 1463 | '🍮', 1464 | '🍯', 1465 | '🍼', 1466 | '\U0001f95b', 1467 | '☕', 1468 | '🍵', 1469 | '🍶', 1470 | '🍾', 1471 | '🍷', 1472 | '🍸', 1473 | '🍹', 1474 | '🍺', 1475 | '🍻', 1476 | '\U0001f942', 1477 | '\U0001f943', 1478 | '🍽', 1479 | '🍴', 1480 | '\U0001f944', 1481 | '🔪', 1482 | '🏺', 1483 | '🌍', 1484 | '🌎', 1485 | '🌏', 1486 | '🌐', 1487 | '🗺', 1488 | '🗾', 1489 | '🏔', 1490 | '⛰', 1491 | '🌋', 1492 | '🗻', 1493 | '🏕', 1494 | '🏖', 1495 | '🏜', 1496 | '🏝', 1497 | '🏞', 1498 | '🏟', 1499 | '🏛', 1500 | '🏗', 1501 | '🏘', 1502 | '🏙', 1503 | '🏚', 1504 | '🏠', 1505 | '🏡', 1506 | '🏢', 1507 | '🏣', 1508 | '🏤', 1509 | '🏥', 1510 | '🏦', 1511 | '🏨', 1512 | '🏩', 1513 | '🏪', 1514 | '🏫', 1515 | '🏬', 1516 | '🏭', 1517 | '🏯', 1518 | '🏰', 1519 | '💒', 1520 | '🗼', 1521 | '🗽', 1522 | '⛪', 1523 | '🕌', 1524 | '🕍', 1525 | '⛩', 1526 | '🕋', 1527 | '⛲', 1528 | '⛺', 1529 | '🌁', 1530 | '🌃', 1531 | '🌄', 1532 | '🌅', 1533 | '🌆', 1534 | '🌇', 1535 | '🌉', 1536 | '♨', 1537 | '🌌', 1538 | '🎠', 1539 | '🎡', 1540 | '🎢', 1541 | '💈', 1542 | '🎪', 1543 | '🎭', 1544 | '🖼', 1545 | '🎨', 1546 | '🎰', 1547 | '🚂', 1548 | '🚃', 1549 | '🚄', 1550 | '🚅', 1551 | '🚆', 1552 | '🚇', 1553 | '🚈', 1554 | '🚉', 1555 | '🚊', 1556 | '🚝', 1557 | '🚞', 1558 | '🚋', 1559 | '🚌', 1560 | '🚍', 1561 | '🚎', 1562 | '🚐', 1563 | '🚑', 1564 | '🚒', 1565 | '🚓', 1566 | '🚔', 1567 | '🚕', 1568 | '🚖', 1569 | '🚗', 1570 | '🚘', 1571 | '🚙', 1572 | '🚚', 1573 | '🚛', 1574 | '🚜', 1575 | '🚲', 1576 | '\U0001f6f4', 1577 | '\U0001f6f5', 1578 | '🚏', 1579 | '🛣', 1580 | '🛤', 1581 | '⛽', 1582 | '🚨', 1583 | '🚥', 1584 | '🚦', 1585 | '🚧', 1586 | '\U0001f6d1', 1587 | '⚓', 1588 | '⛵', 1589 | '\U0001f6f6', 1590 | '🚤', 1591 | '🛳', 1592 | '⛴', 1593 | '🛥', 1594 | '🚢', 1595 | '✈', 1596 | '🛩', 1597 | '🛫', 1598 | '🛬', 1599 | '💺', 1600 | '🚁', 1601 | '🚟', 1602 | '🚠', 1603 | '🚡', 1604 | '🚀', 1605 | '🛰', 1606 | '🛎', 1607 | '🚪', 1608 | '🛌', 1609 | '🛌🏻', 1610 | '🛌🏼', 1611 | '🛌🏽', 1612 | '🛌🏾', 1613 | '🛌🏿', 1614 | '🛏', 1615 | '🛋', 1616 | '🚽', 1617 | '🚿', 1618 | '🛀', 1619 | '🛀🏻', 1620 | '🛀🏼', 1621 | '🛀🏽', 1622 | '🛀🏾', 1623 | '🛀🏿', 1624 | '🛁', 1625 | '⌛', 1626 | '⏳', 1627 | '⌚', 1628 | '⏰', 1629 | '⏱', 1630 | '⏲', 1631 | '🕰', 1632 | '🕛', 1633 | '🕧', 1634 | '🕐', 1635 | '🕜', 1636 | '🕑', 1637 | '🕝', 1638 | '🕒', 1639 | '🕞', 1640 | '🕓', 1641 | '🕟', 1642 | '🕔', 1643 | '🕠', 1644 | '🕕', 1645 | '🕡', 1646 | '🕖', 1647 | '🕢', 1648 | '🕗', 1649 | '🕣', 1650 | '🕘', 1651 | '🕤', 1652 | '🕙', 1653 | '🕥', 1654 | '🕚', 1655 | '🕦', 1656 | '🌑', 1657 | '🌒', 1658 | '🌓', 1659 | '🌔', 1660 | '🌕', 1661 | '🌖', 1662 | '🌗', 1663 | '🌘', 1664 | '🌙', 1665 | '🌚', 1666 | '🌛', 1667 | '🌜', 1668 | '🌡', 1669 | '☀', 1670 | '🌝', 1671 | '🌞', 1672 | '⭐', 1673 | '🌟', 1674 | '🌠', 1675 | '☁', 1676 | '⛅', 1677 | '⛈', 1678 | '🌤', 1679 | '🌥', 1680 | '🌦', 1681 | '🌧', 1682 | '🌨', 1683 | '🌩', 1684 | '🌪', 1685 | '🌫', 1686 | '🌬', 1687 | '🌀', 1688 | '🌈', 1689 | '🌂', 1690 | '☂', 1691 | '☔', 1692 | '⛱', 1693 | '⚡', 1694 | '❄', 1695 | '☃', 1696 | '⛄', 1697 | '☄', 1698 | '🔥', 1699 | '💧', 1700 | '🌊', 1701 | '🎃', 1702 | '🎄', 1703 | '🎆', 1704 | '🎇', 1705 | '✨', 1706 | '🎈', 1707 | '🎉', 1708 | '🎊', 1709 | '🎋', 1710 | '🎍', 1711 | '🎎', 1712 | '🎏', 1713 | '🎐', 1714 | '🎑', 1715 | '🎀', 1716 | '🎁', 1717 | '🎗', 1718 | '🎟', 1719 | '🎫', 1720 | '🎖', 1721 | '🏆', 1722 | '🏅', 1723 | '\U0001f947', 1724 | '\U0001f948', 1725 | '\U0001f949', 1726 | '⚽', 1727 | '⚾', 1728 | '🏀', 1729 | '🏐', 1730 | '🏈', 1731 | '🏉', 1732 | '🎾', 1733 | '🎱', 1734 | '🎳', 1735 | '🏏', 1736 | '🏑', 1737 | '🏒', 1738 | '🏓', 1739 | '🏸', 1740 | '\U0001f94a', 1741 | '\U0001f94b', 1742 | '\U0001f945', 1743 | '🎯', 1744 | '⛳', 1745 | '⛸', 1746 | '🎣', 1747 | '🎽', 1748 | '🎿', 1749 | '🎮', 1750 | '🕹', 1751 | '🎲', 1752 | '♠', 1753 | '♥', 1754 | '♦', 1755 | '♣', 1756 | '🃏', 1757 | '🀄', 1758 | '🎴', 1759 | '🔇', 1760 | '🔈', 1761 | '🔉', 1762 | '🔊', 1763 | '📢', 1764 | '📣', 1765 | '📯', 1766 | '🔔', 1767 | '🔕', 1768 | '🎼', 1769 | '🎵', 1770 | '🎶', 1771 | '🎙', 1772 | '🎚', 1773 | '🎛', 1774 | '🎤', 1775 | '🎧', 1776 | '📻', 1777 | '🎷', 1778 | '🎸', 1779 | '🎹', 1780 | '🎺', 1781 | '🎻', 1782 | '\U0001f941', 1783 | '📱', 1784 | '📲', 1785 | '☎', 1786 | '📞', 1787 | '📟', 1788 | '📠', 1789 | '🔋', 1790 | '🔌', 1791 | '💻', 1792 | '🖥', 1793 | '🖨', 1794 | '⌨', 1795 | '🖱', 1796 | '🖲', 1797 | '💽', 1798 | '💾', 1799 | '💿', 1800 | '📀', 1801 | '🎥', 1802 | '🎞', 1803 | '📽', 1804 | '🎬', 1805 | '📺', 1806 | '📷', 1807 | '📸', 1808 | '📹', 1809 | '📼', 1810 | '🔍', 1811 | '🔎', 1812 | '🔬', 1813 | '🔭', 1814 | '📡', 1815 | '🕯', 1816 | '💡', 1817 | '🔦', 1818 | '🏮', 1819 | '📔', 1820 | '📕', 1821 | '📖', 1822 | '📗', 1823 | '📘', 1824 | '📙', 1825 | '📚', 1826 | '📓', 1827 | '📒', 1828 | '📃', 1829 | '📜', 1830 | '📄', 1831 | '📰', 1832 | '🗞', 1833 | '📑', 1834 | '🔖', 1835 | '🏷', 1836 | '💰', 1837 | '💴', 1838 | '💵', 1839 | '💶', 1840 | '💷', 1841 | '💸', 1842 | '💳', 1843 | '💹', 1844 | '💱', 1845 | '💲', 1846 | '✉', 1847 | '📧', 1848 | '📨', 1849 | '📩', 1850 | '📤', 1851 | '📥', 1852 | '📦', 1853 | '📫', 1854 | '📪', 1855 | '📬', 1856 | '📭', 1857 | '📮', 1858 | '🗳', 1859 | '✏', 1860 | '✒', 1861 | '🖋', 1862 | '🖊', 1863 | '🖌', 1864 | '🖍', 1865 | '📝', 1866 | '💼', 1867 | '📁', 1868 | '📂', 1869 | '🗂', 1870 | '📅', 1871 | '📆', 1872 | '🗒', 1873 | '🗓', 1874 | '📇', 1875 | '📈', 1876 | '📉', 1877 | '📊', 1878 | '📋', 1879 | '📌', 1880 | '📍', 1881 | '📎', 1882 | '🖇', 1883 | '📏', 1884 | '📐', 1885 | '✂', 1886 | '🗃', 1887 | '🗄', 1888 | '🗑', 1889 | '🔒', 1890 | '🔓', 1891 | '🔏', 1892 | '🔐', 1893 | '🔑', 1894 | '🗝', 1895 | '🔨', 1896 | '⛏', 1897 | '⚒', 1898 | '🛠', 1899 | '🗡', 1900 | '⚔', 1901 | '🔫', 1902 | '🏹', 1903 | '🛡', 1904 | '🔧', 1905 | '🔩', 1906 | '⚙', 1907 | '🗜', 1908 | '⚗', 1909 | '⚖', 1910 | '🔗', 1911 | '⛓', 1912 | '💉', 1913 | '💊', 1914 | '🚬', 1915 | '⚰', 1916 | '⚱', 1917 | '🗿', 1918 | '🛢', 1919 | '🔮', 1920 | '\U0001f6d2', 1921 | '🏧', 1922 | '🚮', 1923 | '🚰', 1924 | '♿', 1925 | '🚹', 1926 | '🚺', 1927 | '🚻', 1928 | '🚼', 1929 | '🚾', 1930 | '🛂', 1931 | '🛃', 1932 | '🛄', 1933 | '🛅', 1934 | '⚠', 1935 | '🚸', 1936 | '⛔', 1937 | '🚫', 1938 | '🚳', 1939 | '🚭', 1940 | '🚯', 1941 | '🚱', 1942 | '🚷', 1943 | '📵', 1944 | '🔞', 1945 | '☢', 1946 | '☣', 1947 | '⬆', 1948 | '↗', 1949 | '➡', 1950 | '↘', 1951 | '⬇', 1952 | '↙', 1953 | '⬅', 1954 | '↖', 1955 | '↕', 1956 | '↔', 1957 | '↩', 1958 | '↪', 1959 | '⤴', 1960 | '⤵', 1961 | '🔃', 1962 | '🔄', 1963 | '🔙', 1964 | '🔚', 1965 | '🔛', 1966 | '🔜', 1967 | '🔝', 1968 | '🛐', 1969 | '⚛', 1970 | '🕉', 1971 | '✡', 1972 | '☸', 1973 | '☯', 1974 | '✝', 1975 | '☦', 1976 | '☪', 1977 | '☮', 1978 | '🕎', 1979 | '🔯', 1980 | '♈', 1981 | '♉', 1982 | '♊', 1983 | '♋', 1984 | '♌', 1985 | '♍', 1986 | '♎', 1987 | '♏', 1988 | '♐', 1989 | '♑', 1990 | '♒', 1991 | '♓', 1992 | '⛎', 1993 | '🔀', 1994 | '🔁', 1995 | '🔂', 1996 | '▶', 1997 | '⏩', 1998 | '⏭', 1999 | '⏯', 2000 | '◀', 2001 | '⏪', 2002 | '⏮', 2003 | '🔼', 2004 | '⏫', 2005 | '🔽', 2006 | '⏬', 2007 | '⏸', 2008 | '⏹', 2009 | '⏺', 2010 | '⏏', 2011 | '🎦', 2012 | '🔅', 2013 | '🔆', 2014 | '📶', 2015 | '📳', 2016 | '📴', 2017 | '♻', 2018 | '📛', 2019 | '⚜', 2020 | '🔰', 2021 | '🔱', 2022 | '⭕', 2023 | '✅', 2024 | '☑', 2025 | '✔', 2026 | '✖', 2027 | '❌', 2028 | '❎', 2029 | '➕', 2030 | '♀', 2031 | '♂', 2032 | '⚕', 2033 | '➖', 2034 | '➗', 2035 | '➰', 2036 | '➿', 2037 | '〽', 2038 | '✳', 2039 | '✴', 2040 | '❇', 2041 | '‼', 2042 | '⁉', 2043 | '❓', 2044 | '❔', 2045 | '❕', 2046 | '❗', 2047 | '〰', 2048 | '©', 2049 | '®', 2050 | '™', 2051 | '#️⃣', 2052 | '*️⃣', 2053 | '0️⃣', 2054 | '1️⃣', 2055 | '2️⃣', 2056 | '3️⃣', 2057 | '4️⃣', 2058 | '5️⃣', 2059 | '6️⃣', 2060 | '7️⃣', 2061 | '8️⃣', 2062 | '9️⃣', 2063 | '🔟', 2064 | '💯', 2065 | '🔠', 2066 | '🔡', 2067 | '🔢', 2068 | '🔣', 2069 | '🔤', 2070 | '🅰', 2071 | '🆎', 2072 | '🅱', 2073 | '🆑', 2074 | '🆒', 2075 | '🆓', 2076 | 'ℹ', 2077 | '🆔', 2078 | 'Ⓜ', 2079 | '🆕', 2080 | '🆖', 2081 | '🅾', 2082 | '🆗', 2083 | '🅿', 2084 | '🆘', 2085 | '🆙', 2086 | '🆚', 2087 | '🈁', 2088 | '🈂', 2089 | '🈷', 2090 | '🈶', 2091 | '🈯', 2092 | '🉐', 2093 | '🈹', 2094 | '🈚', 2095 | '🈲', 2096 | '🉑', 2097 | '🈸', 2098 | '🈴', 2099 | '🈳', 2100 | '㊗', 2101 | '㊙', 2102 | '🈺', 2103 | '🈵', 2104 | '▪', 2105 | '▫', 2106 | '◻', 2107 | '◼', 2108 | '◽', 2109 | '◾', 2110 | '⬛', 2111 | '⬜', 2112 | '🔶', 2113 | '🔷', 2114 | '🔸', 2115 | '🔹', 2116 | '🔺', 2117 | '🔻', 2118 | '💠', 2119 | '🔘', 2120 | '🔲', 2121 | '🔳', 2122 | '⚪', 2123 | '⚫', 2124 | '🔴', 2125 | '🔵', 2126 | '🏁', 2127 | '🚩', 2128 | '🎌', 2129 | '🏴', 2130 | '🏳', 2131 | '🏳️\u200d🌈', 2132 | '🇦🇨', 2133 | '🇦🇩', 2134 | '🇦🇪', 2135 | '🇦🇫', 2136 | '🇦🇬', 2137 | '🇦🇮', 2138 | '🇦🇱', 2139 | '🇦🇲', 2140 | '🇦🇴', 2141 | '🇦🇶', 2142 | '🇦🇷', 2143 | '🇦🇸', 2144 | '🇦🇹', 2145 | '🇦🇺', 2146 | '🇦🇼', 2147 | '🇦🇽', 2148 | '🇦🇿', 2149 | '🇧🇦', 2150 | '🇧🇧', 2151 | '🇧🇩', 2152 | '🇧🇪', 2153 | '🇧🇫', 2154 | '🇧🇬', 2155 | '🇧🇭', 2156 | '🇧🇮', 2157 | '🇧🇯', 2158 | '🇧🇱', 2159 | '🇧🇲', 2160 | '🇧🇳', 2161 | '🇧🇴', 2162 | '🇧🇶', 2163 | '🇧🇷', 2164 | '🇧🇸', 2165 | '🇧🇹', 2166 | '🇧🇻', 2167 | '🇧🇼', 2168 | '🇧🇾', 2169 | '🇧🇿', 2170 | '🇨🇦', 2171 | '🇨🇨', 2172 | '🇨🇩', 2173 | '🇨🇫', 2174 | '🇨🇬', 2175 | '🇨🇭', 2176 | '🇨🇮', 2177 | '🇨🇰', 2178 | '🇨🇱', 2179 | '🇨🇲', 2180 | '🇨🇳', 2181 | '🇨🇴', 2182 | '🇨🇵', 2183 | '🇨🇷', 2184 | '🇨🇺', 2185 | '🇨🇻', 2186 | '🇨🇼', 2187 | '🇨🇽', 2188 | '🇨🇾', 2189 | '🇨🇿', 2190 | '🇩🇪', 2191 | '🇩🇬', 2192 | '🇩🇯', 2193 | '🇩🇰', 2194 | '🇩🇲', 2195 | '🇩🇴', 2196 | '🇩🇿', 2197 | '🇪🇦', 2198 | '🇪🇨', 2199 | '🇪🇪', 2200 | '🇪🇬', 2201 | '🇪🇭', 2202 | '🇪🇷', 2203 | '🇪🇸', 2204 | '🇪🇹', 2205 | '🇪🇺', 2206 | '🇫🇮', 2207 | '🇫🇯', 2208 | '🇫🇰', 2209 | '🇫🇲', 2210 | '🇫🇴', 2211 | '🇫🇷', 2212 | '🇬🇦', 2213 | '🇬🇧', 2214 | '🇬🇩', 2215 | '🇬🇪', 2216 | '🇬🇫', 2217 | '🇬🇬', 2218 | '🇬🇭', 2219 | '🇬🇮', 2220 | '🇬🇱', 2221 | '🇬🇲', 2222 | '🇬🇳', 2223 | '🇬🇵', 2224 | '🇬🇶', 2225 | '🇬🇷', 2226 | '🇬🇸', 2227 | '🇬🇹', 2228 | '🇬🇺', 2229 | '🇬🇼', 2230 | '🇬🇾', 2231 | '🇭🇰', 2232 | '🇭🇲', 2233 | '🇭🇳', 2234 | '🇭🇷', 2235 | '🇭🇹', 2236 | '🇭🇺', 2237 | '🇮🇨', 2238 | '🇮🇩', 2239 | '🇮🇪', 2240 | '🇮🇱', 2241 | '🇮🇲', 2242 | '🇮🇳', 2243 | '🇮🇴', 2244 | '🇮🇶', 2245 | '🇮🇷', 2246 | '🇮🇸', 2247 | '🇮🇹', 2248 | '🇯🇪', 2249 | '🇯🇲', 2250 | '🇯🇴', 2251 | '🇯🇵', 2252 | '🇰🇪', 2253 | '🇰🇬', 2254 | '🇰🇭', 2255 | '🇰🇮', 2256 | '🇰🇲', 2257 | '🇰🇳', 2258 | '🇰🇵', 2259 | '🇰🇷', 2260 | '🇰🇼', 2261 | '🇰🇾', 2262 | '🇰🇿', 2263 | '🇱🇦', 2264 | '🇱🇧', 2265 | '🇱🇨', 2266 | '🇱🇮', 2267 | '🇱🇰', 2268 | '🇱🇷', 2269 | '🇱🇸', 2270 | '🇱🇹', 2271 | '🇱🇺', 2272 | '🇱🇻', 2273 | '🇱🇾', 2274 | '🇲🇦', 2275 | '🇲🇨', 2276 | '🇲🇩', 2277 | '🇲🇪', 2278 | '🇲🇫', 2279 | '🇲🇬', 2280 | '🇲🇭', 2281 | '🇲🇰', 2282 | '🇲🇱', 2283 | '🇲🇲', 2284 | '🇲🇳', 2285 | '🇲🇴', 2286 | '🇲🇵', 2287 | '🇲🇶', 2288 | '🇲🇷', 2289 | '🇲🇸', 2290 | '🇲🇹', 2291 | '🇲🇺', 2292 | '🇲🇻', 2293 | '🇲🇼', 2294 | '🇲🇽', 2295 | '🇲🇾', 2296 | '🇲🇿', 2297 | '🇳🇦', 2298 | '🇳🇨', 2299 | '🇳🇪', 2300 | '🇳🇫', 2301 | '🇳🇬', 2302 | '🇳🇮', 2303 | '🇳🇱', 2304 | '🇳🇴', 2305 | '🇳🇵', 2306 | '🇳🇷', 2307 | '🇳🇺', 2308 | '🇳🇿', 2309 | '🇴🇲', 2310 | '🇵🇦', 2311 | '🇵🇪', 2312 | '🇵🇫', 2313 | '🇵🇬', 2314 | '🇵🇭', 2315 | '🇵🇰', 2316 | '🇵🇱', 2317 | '🇵🇲', 2318 | '🇵🇳', 2319 | '🇵🇷', 2320 | '🇵🇸', 2321 | '🇵🇹', 2322 | '🇵🇼', 2323 | '🇵🇾', 2324 | '🇶🇦', 2325 | '🇷🇪', 2326 | '🇷🇴', 2327 | '🇷🇸', 2328 | '🇷🇺', 2329 | '🇷🇼', 2330 | '🇸🇦', 2331 | '🇸🇧', 2332 | '🇸🇨', 2333 | '🇸🇩', 2334 | '🇸🇪', 2335 | '🇸🇬', 2336 | '🇸🇭', 2337 | '🇸🇮', 2338 | '🇸🇯', 2339 | '🇸🇰', 2340 | '🇸🇱', 2341 | '🇸🇲', 2342 | '🇸🇳', 2343 | '🇸🇴', 2344 | '🇸🇷', 2345 | '🇸🇸', 2346 | '🇸🇹', 2347 | '🇸🇻', 2348 | '🇸🇽', 2349 | '🇸🇾', 2350 | '🇸🇿', 2351 | '🇹🇦', 2352 | '🇹🇨', 2353 | '🇹🇩', 2354 | '🇹🇫', 2355 | '🇹🇬', 2356 | '🇹🇭', 2357 | '🇹🇯', 2358 | '🇹🇰', 2359 | '🇹🇱', 2360 | '🇹🇲', 2361 | '🇹🇳', 2362 | '🇹🇴', 2363 | '🇹🇷', 2364 | '🇹🇹', 2365 | '🇹🇻', 2366 | '🇹🇼', 2367 | '🇹🇿', 2368 | '🇺🇦', 2369 | '🇺🇬', 2370 | '🇺🇲', 2371 | '🇺🇳', 2372 | '🇺🇸', 2373 | '🇺🇾', 2374 | '🇺🇿', 2375 | '🇻🇦', 2376 | '🇻🇨', 2377 | '🇻🇪', 2378 | '🇻🇬', 2379 | '🇻🇮', 2380 | '🇻🇳', 2381 | '🇻🇺', 2382 | '🇼🇫', 2383 | '🇼🇸', 2384 | '🇽🇰', 2385 | '🇾🇪', 2386 | '🇾🇹', 2387 | '🇿🇦', 2388 | '🇿🇲', 2389 | '🇿🇼'] 2390 | --------------------------------------------------------------------------------