def chooseLike(self):
ti.like(self.id)
if (self.df.iloc[self.profileNum]['disliked'] == 1):
self.df.at[self.profileNum, 'disliked'] = 0
os.remove(f"./data/images/disliked/{self.id}.jpg")
self.df.at[self.profileNum, 'liked'] = 1
shutil.copy(f"./data/images/unlabeled/{self.id}.jpg",
f"./data/images/liked/{self.id}.jpg")
self.nextID()
def find_matches(self, results):
starting_time = util.get_time()
for idx, rec in enumerate(results):
tinder_api.like(rec['_id'])
print('Liked ' + rec['name'])
event_emitter.emit_like(rec['_id'])
if idx % 5 == 0:
matches = tinder_api.get_updates(starting_time)
print(matches)
self.socketSleep(2)
def job():
count = 0
while count < 50:
women = matches()
women = women['results']
for w in women:
tinder.like(w['_id'])
print('liked')
count += 1
api.pause()
nap_length = 3 * random.random()
time.sleep(nap_length)
def likeAPerson():
time.sleep(5)
for key, value in api.get_recommendations().items():
match = []
if (key == "results"):
for person in value:
rating = 0
person_id = ""
name = ""
for key, value in person.items():
if (key == "_id"):
person_id = value
time.sleep(5)
if key == 'photos' and value:
if len(value) >= 2:
rating += 1
if key == 'name':
name = value
if rating > 0:
print("Like on : ", name)
match = api.like(person_id)
likes_remaining = match["likes_remaining"]
if likes_remaining == 0:
print("Acabaram os likes, terminei por hoje")
quit(0)
print(match)
else:
print("Unlike: ", name)
def swipe_right(self):
LIKES_LIMIT = 45 #Tinder has a limit of 100 like per 12 hours, like 45/6 hours so we are safe.
try:
track_iterator = 0
while track_iterator <= LIKES_LIMIT:
recommendations = tinder_api.get_recs_v2()['data']['results']
for rec in recommendations:
girl_id = rec['user']['_id']
try:
like_response = tinder_api.like(girl_id)
except:
print('WHATS HAPPENING')
return
print('LIKED')
self.statistics['swipes'] += 1
track_iterator += 1
if track_iterator == LIKES_LIMIT: # Check if its time to stop liking
self.last_like_at = datetime.now()
self.fix_time_file()
self.update_statistics_file()
break
time.sleep(10)
print('DONE LIKING')
except:
print('COULD NOT FINISH LIKING')
def like_person(self):
if not self.logged_in:
self.feedback_append_line("Please login first!")
return
self.feedback_append_line("Liking: " + self.id)
resp = tinder_api.like(self.id)
if resp["match"]:
self.feedback_append_line("It seems like she likes you to! <3")
else:
self.feedback_append_line("No match ... yet!")
def swipe_right(n):
recs = api.get_recs_v2()["data"]["results"]
bound = min(len(recs), n)
for i in range(bound):
rec = recs[i]
result = api.like(rec["user"]["_id"])
dumps(result, "Swipe right...")
if i < bound - 1:
pause(.5, 3)
prop_nopes = 100.0 - prop_likes
print('likes = {} ({}%), nopes = {} ({}%)'.format(likes, prop_likes, nopes,
prop_nopes))
if __name__ == "__main__":
like_ids, dislike_ids = [], []
tinderlogin(config.username, config.password)
ti.change_preferences(age_filter_min=AGE_MIN,
age_filter_max=AGE_MAX,
distance_filter=DISTANCE)
rate_limited = 0
while True:
rec = ti.get_recs_v2()["data"]["results"]
for user in rec:
id_ = user["user"]["_id"]
url = user["user"]['photos'][0]["processedFiles"][0]["url"]
try:
if like_or_nope(url) == 1:
ti.like(id_)
like_ids.append(id_)
else:
ti.dislike(id_)
dislike_ids.append(id_)
except:
rate_limited = 1
if rate_limited == 1:
print('Limit reached.')
break
print(stats(len(like_ids), len(dislike_ids)))
for match in matches:
try:
match_id = matches[i]['match_id']
offer_id = 1
text = select_msg(match_id,offer_id)
api.send_msg(match_id, text)
except:
continue
rec = api.get_recommendations()
i = 0
for user in rec:
try:
if i%3=0:
api.dislike(user["person_id"])
else:
api.like(user["person_id"])
i ++
except:
continue
except:
break
# matchthread.join()
# Upon starting the program i should start a separate thread that basically begins get_matches
# so that all the data is stored locally after about a minute but behind the scenes.
# It is probably a good idea to
str(person_id) + '_' +
str(photo_no) + '_' +
str(i) + '.jpg')
img = image.img_to_array(img)
# Apply the neural network to predict face beauty.
temp = img.reshape((1, ) + img.shape)
pred = FBP_model.predict(
img.reshape((1, ) + img.shape))
print(pred)
ratings.append(pred[0][0])
i += 1
photo_no += 1
max_rating = max(ratings)
# If the maximal rating received for a profile's photo is greater than 3, like the profile.
if max_rating >= inputs.args.rating:
liker = api.like(person_id, headers)
print('\x1b[1;32;40m' + "LIKE!!" + '\x1b[0m')
if liker["match"]:
print('\x1b[6;30;42m' + "!! NEW MATCH !!" + '\x1b[0m')
liked_people += 1
if T_profile['like'] <= 0 and liker["likes_remaining"] > 0:
T_profile['like'] = 50
T_profile['like'] -= 1
liked = True
print("All: " + str(all_poeple) + " | Liked: " +
str(liked_people) + " | Likes remaining: " +
str(T_profile['like']))
F = open('log.txt', 'a')
F.write(
str(name) + ', ' + str(person_id) + ', ' +
str(max_rating) + ', ' + str(liked) + "\n")
print("Moving to {0}".format(location["label"]))
tinder_api.update_location(location["lat"], location["lon"])
location["visited"] = True
EXISTS = 5
CURRENT_LOCATION = location["label"]
break
r = tinder_api.get_recommendations()
try:
recommendations = r["results"]
except KeyError as e:
print(r)
raise e
print("Fetching {0} recommendations".format(len(recommendations)))
for recommendation in recommendations:
recommendation["t_id"] = recommendation.pop("_id")
try:
Human.objects.get(t_id=recommendation["t_id"])
except Human.DoesNotExist:
try:
human = Human(**recommendation)
except Exception as e:
raise e
human.label = CURRENT_LOCATION
human.save()
tinder_api.like(human.t_id)
print("Like {0}".format(human.name))
print("Sleeping {0} seconds...".format(LIKE_SLEEP_TIME))
time.sleep(LIKE_SLEEP_TIME)
else:
EXISTS -= 1
def _like(person_id):
res = api.like(person_id)
if 'likes_remaining' not in res:
res = api.like(person_id)
return res['likes_remaining']
def like(userId):
tinder_api.like(userId)
exit(0)
if not os.path.exists(directory):
os.makedirs(directory)
url = urls['url']
filename_path = directory + str(count_photos) + ".png"
count_photos += 1
print(url, "=>", filename_path)
wget.download(url, out=filename_path, bar=None)
filename_paths.append(filename_path)
try:
action = model.like_or_nope(filename_paths,
model_api_host=model_api_host,
model_id=model_id)
if action == 'like':
like_count += 1
print(' -> Like')
stats(like_count, nope_count)
match = ti.like(user.user_id)
if match:
print(' -> Match!')
else:
nope_count += 1
print(' -> nope')
stats(like_count, nope_count)
ti.nope(user.user_id)
except Exception as e:
print(e)
if person.get('schools'):
for school in person['schools']:
print('SCHOOL: ' + school['name'])
if person.get('bio'):
print('BIO: ' + person['bio'])
if person.get('distance_mi'):
print('DISTANCE: ' + str(person['distance_mi']) + ' miles')
for photo in person['photos']:
URL = photo['url']
with urlopen(URL) as url:
with open('temp.jpg', 'wb') as f:
f.write(url.read())
img = Image.open('temp.jpg')
img.show()
if dec:
like(rec)
print(bcolors.OKGREEN + 'LIKED' + bcolors.ENDC)
else:
dislike(rec)
print(bcolors.FAIL + 'DISLIKED' + bcolors.ENDC)
for _ in range(5):
sleep(4 * random())
print('...')
def main():
credentials = json.load(open('credentials.json', 'r'))
fb_id = credentials['FB_ID']
fb_auth_token = get_access_token(credentials['FB_EMAIL_ADDRESS'],
credentials['FB_PASSWORD'])
model_api_host = str(credentials['API_HOST'])
model_id = str(credentials['MODEL_ID'])
print('Deep Learning Tinder bot')
print('----------')
print('FB_ID = {}'.format(fb_id))
print('FB_AUTH_TOKEN = {}'.format(fb_auth_token))
print('MODEL_API_HOST = {}'.format(model_api_host))
print('MODEL_ID = {}'.format(model_id))
like_count = 0
nope_count = 0
while True:
token = ti.auth_token(fb_auth_token, fb_id)
print('TINDER_TOKEN = {}'.format(token))
if not token:
print('could not get Tinder token. Program will exit.')
sys.exit(0)
print('Successfully connected to Tinder servers.')
lat = 34.7
lon = 135.5
# http://words.alx.red/tinder-api-2-profile-and-geolocation/
print(ti.change_loc(lat, lon, token))
my_profile = ti.profile(token)
print(json.dumps(my_profile, indent=4, sort_keys=True))
for user in ti.recommendations(token):
if not user:
break
count_photos = 1
filename_paths = []
for urls in user.d['photos']:
directory = "data/" + str(user.age) + "/" + str(
user.user_id) + "/"
if 'tinder_rate_limited_id' in directory:
print('Limit reached.')
exit(0)
if not os.path.exists(directory):
os.makedirs(directory)
url = urls['url']
filename_path = directory + str(count_photos) + ".png"
count_photos += 1
print(url, "=>", filename_path)
wget.download(url, out=filename_path, bar=None)
filename_paths.append(filename_path)
try:
action = model.like_or_nope(filename_paths,
model_api_host=model_api_host,
model_id=model_id)
if action == 'like':
like_count += 1
print(' -> Like')
stats(like_count, nope_count)
match = ti.like(user.user_id)
if match:
print(' -> Match!')
else:
nope_count += 1
print(' -> nope')
stats(like_count, nope_count)
ti.nope(user.user_id)
except Exception as e:
print(e)
def press(event):
global _id
global images
global like
global dislike
global txt
global fig
sys.stdout.flush()
print('you pressed {}'.format(event.key))
if event.key == 'e':
print('exit')
sys.exit()
raise SystemExit()
if event.key in ['right', 'left', 'up']:
if event.key == 'right':
# Like a user
tinder_api.like(_id)
print('you liked')
text = 'LIKED'
count = 0
for _image in images:
io.imsave(
'/home/majid/Ternow-Lovai/data/liked/profile_{}_{}.jpg'.
format(_id, count), _image)
count += 1
like += 1
#break
elif event.key == 'left':
# Dislike a user
tinder_api.dislike(_id)
print('you disliked')
text = 'DISLIKED'
count = 0
for _image in images:
io.imsave(
'/home/majid/Ternow-Lovai/data/disliked/profile_{}_{}.jpg'.
format(_id, count), _image)
count += 1
dislike += 1
#break
elif event.key == 'top':
# Superlike a user
tinder_api.superlike(_id)
print('you superliked')
text = 'SUPERLIKED'
count = 0
for _image in images:
io.imsave(
'/home/majid/Ternow-Lovai/data/liked/profile_{}_{}.jpg'.
format(_id, count), _image)
count += 1
like += 1
#break
#plt.text(5, 5, text, style='italic', bbox={'facecolor':'red', 'alpha':0.5, 'pad':10})
if text in ['LIKED', 'SUPERLIKED']:
txt = plt.text(.5,
.5,
text,
fontsize=30,
style='italic',
bbox={
'facecolor': 'green',
'alpha': 0.5,
'pad': 1
})
elif text == 'DISLIKED':
txt = plt.text(.5,
.5,
text,
fontsize=30,
style='italic',
bbox={
'facecolor': 'red',
'alpha': 0.5,
'pad': 1
})
fig.canvas.draw()
time.sleep(1)
#plt.show(block=False)
plt.close('all')
exit(0)
if not os.path.exists(directory):
os.makedirs(directory)
url = urls['url']
filename_path = directory + str(count_photos) + ".png"
count_photos += 1
print(url, "=>", filename_path)
wget.download(url, out=filename_path, bar=None)
filename_paths.append(filename_path)
try:
action = model.like_or_nope(filename_paths,
model_api_host=model_api_host,
model_id=model_id)
if action == 'like':
like_count += 1
print(' -> Like')
stats(like_count, nope_count)
match = ti.like(user.user_id)
if match:
print(' -> Match!')
else:
nope_count += 1
print(' -> nope')
stats(like_count, nope_count)
ti.nope(user.user_id)
except Exception as e:
print(e)