How To Make A Tinder Bot


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Make A Tinder Bot That Acts Like You | by Nathan Ang | Medium

Make A Tinder Bot That Acts Like You | by Nathan Ang | Medium

Our bot will automate likes on Tinder and have conversations with our matches, talking like a normal human. Then, if the person asks to hangout, we’ll get a text message with their profile and be able to setup a date with them or decline the ’s a very crude flow diagram we’re going to be basing the project around:Flow DiagramNote: Thanks to my friend Jenny for letting me use her Tinder account for testing / start, we’re going to be getting familiar with the Tinder git cloning the API and running the config files (I recommend setup via SMS) to connect our Tinder account, we should test it! from tinder_api_sms import *print(get_recommendations());Saving this in a file called and running it will successfully dump us all the data about our “recommendation deck” on Tinder:Output of get_recommendations()After we look through this data, we can isolate just what we want. In this case, I am parsing through and extracting the bio’s of our tinder_api_sms import *import pprint;printer = ettyPrinter(indent = 4);recs = get_recommendations()[“results”];for person in recs: person_id = person[“_id”]; person_bio = person[“bio”]; print(person_bio);Test Output of Bio’sBut, we don’t want to just look at this data. We’re going to automate the liking, or swiping right, on Tinder. To do this, in our for loop, we just have to add:like_person(person_id);When we run this, we can see that we already start making matches:So, we just have to run this every couple minutes or so, and automating the likes on Tinder is done! That’s alright, but this was the easy automate the conversations, we’re going to be using DialogFlow, which is Google’s machine learning have to create a new agent, and give it some training phrases and sample responses using “Intents” a new agent and add IntentsThe Intents are categories of dialog, so I added common ones such as talking about how am I are doing, what are my hobbies, talking about movies, etc. I also filled out the “Small Talk” portion of our, add the intents to the fulfillment and deploy it! DialogFlow Fulfillment and DeploymentWhen we test it on DialogFlow, such as asking our Tinder profile how it’s doing with “hyd”, it replies “good! hbu? ” which is what Jenny would say! To connect the DialogFlow to our Tinder account, I wrote this script:import dialogflowimport os from google. api_core. exceptions import InvalidArgumentDIALOGFLOW_PROJECT_ID = ‘#’DIALOGFLOW_LANGUAGE_CODE = ‘en-US’GOOGLE_APPLICATION_CREDENTIALS = ‘C:\\Users\\natha\\Documents\\TinderAPI\\Tinder\\’credential_path = “C:\\Users\\natha\\Documents\\TinderAPI\\Tinder\\”os. environ[‘GOOGLE_APPLICATION_CREDENTIALS’] = credential_pathtext_to_be_analyzed = “hyd” #this would be a message from Tindersession_client = ssionsClient()session = ssion_path(DIALOGFLOW_PROJECT_ID, SESSION_ID)text_input = (text=text_to_be_analyzed, language_code=DIALOGFLOW_LANGUAGE_CODE)query_input = (text=text_input)try: response = tect_intent(session=session, query_input=query_input)except InvalidArgument: raiseprint(“Query text:”, response. query_result. query_text)print(“Detected intent:”, )print(“Detected intent confidence:”, tent_detection_confidence)print(“Fulfillment text:”, response. fulfillment_text)So, now we have to pull the unread messages that people have sent Jenny on Tinder. To do this, we can run:from tinder_api_sms import *;from features import *;import pprintimport datetimeimport stringprinter = ettyPrinter(indent=4)#recs = get_recommendations()[“results”];count = “50”;match_dict = all_matches(count);date = str(()). replace(” “, “”);#print(date);self_dict = get_self();selfId = self_dict[‘_id’];matches = match_dict[“data”][“matches”];#find last message that we didnt send for each userfor user in matches: userId = user[‘_id’]; if user[‘messages’]: lastMessage = user[‘messages’][-1]; if lastMessage[‘from’]! = selfId: message = lastMessage[‘message’]; (message);This outputs the most recent messages that people have sent to Jenny:So, now we just combine this data with DialogFlow, which will give us a reply based on our training models! On Tinder so far, it kind of works:But sometimes times it doesn’t really work:This happened because our chatbot doesn’t know what he’s talking about, and I set the default response to we need to do now is add more Intents and let our chatbot talk to more people, as it‘ll automatically grow smarter with each conversation it we let that run, we’re going to implement the “last” part, which is integrating SMS. Again, the idea is that if the person asks to hangout after talking for a while, we’ll get a text message with their profile and be able to setup a date with them or decline the do this, we’re going to be using Twilio, an API for dealing with ’s a test script that will send us a text message:from import Client# Your Account Sid and Auth Token from = ”auth_token = ”client = Client(account_sid, auth_token)message = ssages \ ( body=”Text Message”, from_=’SETUP ON TWILIO’, to=’YOUR OWN PHONE NUMBER’)print()Here we can connect it to our Tinder Bot:def twilioMsg(name, pic, message, id): message = ssages \ ( body = “After talking with \’you\’ for a bit, ” + name + ” ” + message + “\n \n if you might want to hangout, check out the interaction on tinder! \n \n if not, please reply with the ID of the person. \n \n ID: ” + id, from_=’+14082157063′, media_url = pic, to = ‘+14088911891’)print()printer = ettyPrinter(indent=4)self_dict = get_self();selfId = self_dict[‘_id’];def automated_replies(): #recs = get_recommendations()[“results”]; count = “90”; match_dict = all_matches(count);matches = match_dict[“data”][“matches”];#find last message that we didnt send for each user for user in matches:userId = user[‘_id’]; if user[‘messages’]: lastMessage = user[‘messages’][-1]; if lastMessage[‘from’]! = selfId: message = lastMessage[‘message’]; reply = MLtext(userId, message); reply = (); print(reply) if “hangout with you” in reply: name = user[‘person’][‘name’]; pic = user[‘person’][‘photos’][0][‘processedFiles’][0][‘url’]; twilioMsg(name, pic, reply, userId);elif reply: send_msg(userId, reply); (150, 1, automated_replies);Then, to register our response from our phone that goes back to Twilio, we’re going to use webhooks. To implement this, we’ll use Flask and ngrok in this script:from flask import Flask, requestfrom twilio import twimlfrom import Message, MessagingResponsefrom tinder_api_sms import *;from features import *;import datetimeimport stringimport dialogflowimport os from google. exceptions import InvalidArgumentfrom import Clientaccount_sid = ‘#’auth_token = ‘#’client = Client(account_sid, auth_token)app = Flask(__name__)(‘/sms’, methods=[‘POST’])def sms(): number = [‘From’] message_body = [‘Body’] send_msg(message_body, “my bad sorry, i can’t hangout. i hope you have a terrific day tho”);resp = MessagingResponse() ssage(‘Hello {}, you said: {}'(number, message_body)) return str(message_body)if __name__ == ‘__main__’: ()So yeah, now we’re pretty much done! We let the bot run a little bit and when someone asks to hangout, like:We get a text message:We just automated almost pretty much everything about Tinder! As some next steps, the ML chatbot could definitely be improved, and we can implement some ML facial analysis to swipe right based on some sort of objective attractiveness of each person, instead of swiping right on yeah, that’s pretty much it. You can check out all the code on my Github, and don’t hesitate hit me up if you have any questions or concerns!
Create Tinder Bot with Python - DEV Community

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Create Tinder Bot with Python – DEV Community

Watched this youtube video.
The code is based on the video. I added a couple of things to it.
1. Allow a user to input username/password instead of using python file
# input email/username
email_input = (‘//*[@id=”email”]’)
username = tpass(‘please input username\n’)
# input password
password_input = (‘//*[@id=”pass”]’)
password = tpass(‘please input password\n’)
Enter fullscreen mode
Exit fullscreen mode
2. Support 2FA
Can pass the boolean to enable input and click function for 2FA
two_fa = True # if don’t need 2FA just pass False
3. Swipe randomly
The video does swipe right simply. I just make that a little bit fun lol
if rand > 0. 5:
if debug:
print(‘swipe like’)
except Exception:
print(‘swipe not like’)
4. Display action
As you can see, I added debug to show action in the Terminal.
debug = True # if pass False, prints don’t show up
5. Screenshot
If the script swipe right, it will take a screenshot and give a random string to a png file.
Get image url from the element (css background-image)
Get a webp and convert it
Save no. 2 as a png
def take_screenshot(self):
filename = self. randomString()+”
image = (
image_url = lue_of_css_property(“background-image”)
raw_url = place(‘url(“‘, ”). replace(‘”)’, ”)
# get webp
# convert webp –> png
resp = (raw_url)
im = (BytesIO(ntent)). convert(“RGB”)
(filename, “png”)
From an image, we could get a couple of things like name, age, one-line profile and Instagram username with pytesseract (OCR package)
This is not necessary since we can get them from the website directly lol
6. Terminate
As you may know, Tinder’s biz model is a subscription model, so if you don’t pay, Tinder will show you a popup that recommends you to purchase a subscription. This script is for fun and I don’t use Tinder, so I need to terminate a program instead of aborting by an error.
def not_pay(self):
popup = (
print(‘cannot swipe any more’)
print(‘will finish the program’)
If you have a Facebook account and Tinder account, you can try this simple Tinder bot.
python and pypi versions
python 3. 6. 5
selenium 3. 141. 0
requests 2. 22. 0
Pillow 6. 2. 0
Facebook account ()
how to use
install webdriver
$ brew cask install chromedriver
# check version
$ chromedriver –version
run python script
$ git clone $ cd tinder-bot
$ pip install -r
Maybe you are interested in doing something with javascript instead of using python.
Icons made by Freepik from
How to identify and report Tinder bots | NordVPN

How to identify and report Tinder bots | NordVPN

ContentsFake Tinder profiles vs. Tinder botsBot or not? What to do if you encounter a bot What percentage of Tinder users are bots? Is Tinder safe? Bots comprise more than half of the web traffic. Not all of them are malicious, but scammers can use them to extract information or infect you with malware. Planting bots on Tinder lets scammers reach a large number of potential victims in a relatively short Tinder profiles vs. Tinder botsTinder bots are not the same as fake Tinder profiles. A bot is an account run by a computer program, while fake accounts have real people hiding behind fake identities for various reasons. Even though fake profiles might remind you of bots at first sight, it takes much longer to identify them in conversation. Some of them might even have stolen identities to back-up their ever, here are a few signs of fake tinder profiles:Avoiding live contact. If you’ve been chatting for a very long time and your match is avoiding any calls or meet-ups, they might not be who they seem;Asking for money and claiming that they’re in trouble;Asking too many personal questions;Inviting you to click on a link to play a game or check a photo. It will most likely be a malware infection or an advertising page;Immediately asking for a long-term relationship or some form of commitment to gain trust while avoiding meet-ups, calls or providing a social media profile;You can find their photos online and they turn out to be stock images or famous though some fake profiles are relatively harmless, others can facilitate serious crimes such as blackmail or robbery. They might also cause you emotional damage, especially if you only discover the scam after establishing an emotional connection. Be aware of the signs described above and never give out your info or agree to meet-up in a remote or not? Even though bots are widespread and gradually getting more advanced, they aren’t too difficult to identify on Tinder. Tinder scammers rarely have the resources to make them very sophisticated. Although you might get hooked at the first impression, further conversation will most likely show you are not talking to a real are a few ways to identify a typical bot while swiping:A profile not linked to an Instagram or Facebook account. If you see that a person’s profile is not linked to external social networks, that might be a red flag. Establishing a reliable-looking social media context around a fake profile is quite a difficult task, so scammers usually don’t bother;A profile linked to a social media account that looks fake. It’s always worth doing a quick social media search in case you have any doubts. If you notice that all the images and interests are too common and the profile lacks a personal touch, it might not be authentic;The bio looks fishy. If the bio includes lots of grammar mistakes, invitations to suspicious links, or personals details that do not make sense, you might have encountered a bot. If a simple search reveals that details from the bio are false or don’t make sense, that’s also a serious warning;The photos look too good to be true. If you notice that a person’s profile consists of professional studio images, the scammer may have lifted them from some other account. Some people like to put extra effort into their Tinder accounts, but professional or perfect photos should prompt you to take another look before you you already matched with someone, here are the red flags you should look out for when chatting to avoid a Tinder scam:Immediate response. If you get the first message unusually quickly after matching with someone, it might be a bot. Bots can reply within milliseconds, which is quite difficult for a real person;The conversation feels unnatural. A simple Tinder bot usually uses a string of messages to reply. They might answer some of your questions in a very basic way. However, they cannot maintain a natural conversational flow. Their replies might be completely unrelated to your message or they might immediately send you straightforward and provocative messages. Try asking something unexpected like “What color is the sky” or type a few random letters and see whether the responses make sense;Conversations turn into a request to click on a link to continue chatting outside of Tinder, verify your profile, or check some photos. Never click on those links. They might snatch your data, enroll you in an expensive porn subscription, infect you with malware, provide annoying ads, etc. The bot will most likely stop chatting with you if you refuse;Requests for personal details. If a person requests details such as your name, address, or credit card info, it is a sign that something is not right. Definitely don’t provide any sensitive to do if you encounter a botIf you have strong suspicions that you’ve encountered a bot, Tinder has tools to report it:1. When in chat, click on the red flag in the top right corner;2. Tap Report;3. Select the reason for reporting and click a bot or fake account before unmatching it as you won’t be able to report it after it disappears from your chat list. You can also report an account before matching by:1. Clicking on I (info) letter in the bottom right corner of the image;2. Tapping Report (username) below the profile name or reover, you should:Not provide any personal info to a person you find suspicious;Not agree to meet-up in remote or suspicious places;Always double-check photos and social media profiles, and check search engines if you have any doubts;Never open any suspicious links;If you feel unsafe or threatened, click on your profile icon and then go to Settings. Scroll down to find Show Me on Tinder option and turn it percentage of Tinder users are bots? Estimates suggest that 1 in 5 online traffic requests are generated by bad bots, designed to harm internet users. While it’s hard to tell what percentage of Tinder profiles are bots, we can assume that it isn’t more than 20%. Online scams are growing every year, however, so that number will almost certainly Tinder safe? Tinder is a relatively safe platform, but you should always take precautions. According to the Daily Mail, there have been 500 Tinder-related crimes reported during its six years of existence. Always stay alert when communicating with strangers, double-check their details in case of doubt, and instantly back-off if you notice any threatening terms of privacy, Tinder is a dating app linked with Facebook, so much of your data will be collected while using it. Thus, do not give away too much personal data, as it will be used for marketing purposes or passed to third-parties. Looking to say goodbye to online dating? Click here for a tutorial on how to delete learn more about cybersecurity, subscribe to our monthly blog newsletter below! Want to read more like this? Get the latest news and tips from ‘ve successfully subscribed to our newsletter! Email is invalidWe won’t spam and you will always be able to unsubscribe.
Paul Black
Verified author
Paul is a technology and art enthusiast who is always eager to explore the most up-to-date issues in cybersec and internet freedom. He is always in search for new and unexplored angles to share with his readers.

Frequently Asked Questions about how to make a tinder bot

How do I get a Tinder bot?

Try asking something unexpected like “What color is the sky” or type a few random letters and see whether the responses make sense; Conversations turn into a request to click on a link to continue chatting outside of Tinder, verify your profile, or check some photos. Never click on those links.Feb 3, 2021

Is Tinder filled with bots?

“Despite being one of the smoothest and easiest-to-use dating apps, Tinder is full of fake accounts and bots that can ruin the whole user experience,” warns Gonzalez. Dating-app bots can not just fool people into opening their hearts, some can fool people into opening their wallets.Jul 10, 2020

Why do people make bots on Tinder?

Why are there bots on Tinder? Tinder bots give scammers a way to obtain personal information, trick people out of money, or infect devices with malware. Experts estimate that bots make up a quarter of all web traffic, and Tinder is no exception.May 16, 2021

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