{"id":317137,"date":"2021-01-28T21:00:26","date_gmt":"2021-01-28T21:00:26","guid":{"rendered":"http:\/\/savepearlharbor.com\/?p=317137"},"modified":"-0001-11-30T00:00:00","modified_gmt":"-0001-11-29T21:00:00","slug":"","status":"publish","type":"post","link":"https:\/\/savepearlharbor.com\/?p=317137","title":{"rendered":"\u041a\u0430\u043a \u043b\u0430\u0439\u043a\u0430\u0442\u044c \u0447\u0435\u0442\u044b\u0440\u0435 \u0442\u044b\u0441\u044f\u0447\u0438 \u0434\u0435\u0432\u0443\u0448\u0435\u043a \u0432 \u0447\u0430\u0441"},"content":{"rendered":"\n<div class=\"post__text post__text_v2\" id=\"post-content-body\">\n<h4>\u0417\u0430\u0447\u0435\u043c<\/h4>\n<p>\u0423 \u043a\u0430\u0436\u0434\u043e\u0433\u043e \u043c\u043e\u043b\u043e\u0434\u043e\u0433\u043e DS \u0432 \u043a\u0430\u043a\u043e\u0439 \u0442\u043e \u043c\u043e\u043c\u0435\u043d\u0442 \u0432\u0440\u0435\u043c\u0435\u043d\u0438 \u0432\u043e\u0437\u043d\u0438\u043a\u0430\u0435\u0442 \u043f\u0440\u043e\u0431\u043b\u0435\u043c\u0430 &#8212;<s> \u043e\u0447\u0435\u043d\u044c \u0445\u043e\u0447\u0435\u0442\u0441\u044f \u0442\u044f\u043d\u043e\u0447\u043a\u0443<\/s>, \u0432\u0441\u043c\u044b\u0441\u043b\u0435 \u0441\u043f\u0430\u0440\u0441\u0438\u0442\u044c \u0442\u0438\u043d\u0434\u0435\u0440 \u0438 \u0441\u0434\u0435\u043b\u0430\u0442\u044c \u0442\u0435\u043c\u0430\u0442\u0438\u0447\u0435\u0441\u043a\u043e\u0435 \u043c\u043e\u0434\u0435\u043b\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u0435 \u043d\u0430 \u043e\u043f\u0438\u0441\u0430\u043d\u0438\u044f\u0445 \u043f\u0440\u043e\u0444\u0438\u043b\u044f.<\/p>\n<h4>\u041a\u0430\u043a<\/h4>\n<p>\u041e\u0442\u0432\u0435\u0442 \u043a\u043e\u0440\u043e\u0442\u043a\u0438\u0439 &#8212; \u043b\u0435\u0433\u043a\u043e, \u0432\u043e\u0442 \u0441\u0441\u044b\u043b\u043a\u0430 \u043d\u0430 <a href=\"https:\/\/colab.research.google.com\/drive\/1ap8pUgoYATYb5NFjiccd-1eFUIJn5ycj?usp=sharing\" rel=\"noopener noreferrer nofollow\">collab<\/a><\/p>\n<p>\u0414\u043b\u0438\u043d\u043d\u044b\u0439 \u043e\u0442\u0432\u0435\u0442 &#8212; \u0442\u0438\u043d\u0434\u0435\u0440 \u043e\u0431\u043c\u0435\u043d\u0438\u0432\u0430\u0435\u0442\u0441\u044f \u043e\u0442\u043a\u0440\u044b\u0442\u044b\u043c json \u0441  https:\/\/api.gotinder.com, \u0430 \u0432 XHR \u043b\u0435\u0436\u0438\u0442 \u043d\u0430\u0448 x auth key.  \u041e\u0441\u0442\u0430\u043b\u044c\u043d\u043e\u0435 &#8212; \u0434\u0435\u043b\u043e \u0442\u0435\u0445\u043d\u0438\u043a\u0438 \u0438 \u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a\u0438 Response. <\/p>\n<figure class=\"full-width\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/habrastorage.org\/getpro\/habr\/upload_files\/d6a\/39b\/509\/d6a39b509a9dd57d9dc31ee3a821ff56\" width=\"1084\" height=\"903\"><figcaption><\/figcaption><\/figure>\n<h4>\u041f\u0430\u0440\u0441\u0438\u043d\u0433<\/h4>\n<p>\u041a\u043e\u0434 \u0434\u043b\u044f \u043f\u0440\u043e\u0444\u0438\u043b\u044f<\/p>\n<pre><code>import datetime from geopy.geocoders import Nominatim  AuthKey = '' # \u041a\u043b\u044e\u0447 \u043f\u0438\u0445\u0443\u0435\u043c \u0441\u044e\u0434\u0430   TINDER_URL = \"https:\/\/api.gotinder.com\" geolocator = Nominatim(user_agent=\"auto-tinder\") PROF_FILE = \".\/images\/unclassified\/profiles.txt\"  class Person(object):      def __init__(self, data, api):         self._api = api          self.id = data[\"_id\"]         self.name = data.get(\"name\", \"Unknown\")          self.bio = data.get(\"bio\", \"\")        \t          self.birth_date = datetime.datetime.strptime(data[\"birth_date\"], '%Y-%m-%dT%H:%M:%S.%fZ') if data.get(             \"birth_date\", False) else None         self.gender = [\"Male\", \"Female\", \"Unknown\"][data.get(\"gender\", 2)]          self.images = list(map(lambda photo: photo[\"url\"], data.get(\"photos\", [])))          self.jobs = list(             map(lambda job: {\"title\": job.get(\"title\", {}).get(\"name\"), \"company\": job.get(\"company\", {}).get(\"name\")}, data.get(\"jobs\", [])))         self.schools = list(map(lambda school: school[\"name\"], data.get(\"schools\", [])))          if data.get(\"pos\", False):             self.location = geolocator.reverse(f'{data[\"pos\"][\"lat\"]}, {data[\"pos\"][\"lon\"]}')           def __repr__(self):         return f\"{self.id}  -  {self.name} ({self.birth_date.strftime('%d.%m.%Y')})\"       def like(self):         return self._api.like(self.id)      def dislike(self):         return self._api.dislike(self.id)<\/code><\/pre>\n<p>\u041d\u0438\u0447\u0435\u0433\u043e \u0438\u043d\u0442\u0435\u0440\u0435\u0441\u043d\u043e\u0433\u043e \u0442\u0443\u0442 \u043d\u0435\u0442, \u043f\u0440\u043e\u0441\u0442\u043e \u0445\u043e\u0434\u0438\u043c \u043f\u043e html \u0438 \u0442\u044f\u043d\u0435\u043c \u0442\u043e \u0447\u0442\u043e \u043d\u0443\u0436\u043d\u043e<\/p>\n<p>\u0420\u0430\u0431\u043e\u0442\u0430 \u0441 API <\/p>\n<pre><code>import requests  TINDER_URL = \"https:\/\/api.gotinder.com\"  class tinderAPI():      def __init__(self, token):         self._token = token      def profile(self):         data = requests.get(TINDER_URL + \"\/v2\/profile?include=account%2Cuser\", headers={\"X-Auth-Token\": self._token}).json()         return Profile(data[\"data\"], self)      def matches(self, limit=10):         data = requests.get(TINDER_URL + f\"\/v2\/matches?count={limit}\", headers={\"X-Auth-Token\": self._token}).json()         return list(map(lambda match: Person(match[\"person\"], self), data[\"data\"][\"matches\"]))      def like(self, user_id):         data = requests.get(TINDER_URL + f\"\/like\/{user_id}\", headers={\"X-Auth-Token\": self._token}).json()         return {             \"is_match\": data[\"match\"],             \"liked_remaining\": data[\"likes_remaining\"]         }      def dislike(self, user_id):         requests.get(TINDER_URL + f\"\/pass\/{user_id}\", headers={\"X-Auth-Token\": self._token}).json()         return True      def nearby_persons(self):         data = requests.get(TINDER_URL + \"\/v2\/recs\/core\", headers={\"X-Auth-Token\": self._token}).json()                  return list(map(lambda user: Person(user[\"user\"], self), data[\"data\"][\"results\"]))<\/code><\/pre>\n<p>\u0422\u0443\u0442 \u043c\u044b \u043f\u043e\u043b\u0443\u0447\u0430\u0435\u043c json, \u0440\u0430\u0437\u0431\u0438\u0440\u0430\u0435\u043c \u0435\u0433\u043e \u0438 \u0442\u0430\u0449\u0438\u043c \u0432\u0441\u0435 \u0447\u0442\u043e \u043d\u0430\u043c \u043d\u0443\u0436\u043d\u043e(\u0441\u043f\u0438\u0441\u043e\u043a \u044e\u0437\u0435\u0440\u043e\u0432)<\/p>\n<h4>\u041a\u043b\u0430\u0434\u0435\u043c \u0432\u0441\u0435 \u0432 .csv<\/h4>\n<pre><code>import time import pandas as pd df = pd.DataFrame() prf = [] prsn= [] vuz = [] gender = [] job = [] if __name__ == \"__main__\":     token = AuthKey     api = tinderAPI(token)      while True:         persons = api.nearby_persons()         for person in persons:            #\u0442\u0443\u0442 \u043d\u0435\u0442 \u043b\u043e\u0433\u0438\u043a\u0438, \u043d\u0430\u043f\u0438\u0448\u0438\u0442\u0435 \u0441\u0430\u043c\u0438 \u0435\u0441\u043b\u0438 \u0437\u0430\u0445\u043e\u0442\u0438\u0442             print(person)             time.sleep(1)             person.dislike()             prf+=[person.bio]             prsn+=[person]             vuz+=[person.schools]             job+=[person.jobs]             gender+=[person.gender]             print(person.bio) df['vuz'] = vuz df['jobs'] = job df['person'] = prsn df['bio'] = prf  df['gender'] = gender df.to_csv('tinder.csv') <\/code><\/pre>\n<p>\u041a\u043e\u0433\u0434\u0430 \u043a\u043e\u043d\u0447\u0430\u044e\u0442\u0441\u044f \u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u0435\u043b\u0438 \u043e\u043d\u043e \u0432\u044b\u043b\u0435\u0442\u0430\u0435\u0442 \u0438 \u043d\u0435 \u0441\u043e\u0445\u0440\u0430\u043d\u044f\u0435\u0442, \u043f\u043e \u044d\u0442\u043e\u043c\u0443 \u043d\u0443\u0436\u043d\u043e \u0432\u044b\u0434\u0435\u043b\u044f\u0442\u044c \u043a\u043e\u0434 \u0434\u043b\u044f \u0441\u043e\u0445\u0440\u0430\u043d\u0435\u043d\u0438\u044f \u0432 \u043e\u0442\u0434\u0435\u043b\u044c\u043d\u0443\u044e \u044f\u0447\u0435\u0439\u043a\u0443 \u043a\u043e\u0434\u0430. \u0411\u043b\u0430\u0433\u043e collab \u043f\u043e\u0437\u0432\u043e\u043b\u044f\u0435\u0442 \u043d\u0435 \u0434\u0443\u043c\u0430\u0442\u044c, \u0430 \u0434\u0435\u043b\u0430\u0442\u044c. \u0411\u043e\u043b\u0435\u0435 \u043e\u043f\u044b\u0442\u043d\u044b\u0435 \u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u0435\u043b\u0438 \u043c\u043e\u0433\u0443\u0442 \u0441\u043a\u0430\u0437\u0430\u0442\u044c \u0447\u0442\u043e \u043d\u0430\u0434\u043e \u043e\u0431\u043b\u043e\u0436\u0438\u0442\u044c \u0432 try: , \u043d\u043e \u043c\u043d\u0435 \u043d\u0435 \u0445\u043e\u0447\u0435\u0442\u0441\u044f, \u0434\u0430 \u0438 \u0441\u043c\u044b\u0441\u043b\u0430 \u043d\u0435\u0442.<\/p>\n<p>\u0414\u0432\u0430 \u0447\u0430\u0441\u0430 \u0441\u043f\u0443\u0441\u0442\u044f \u043f\u043e\u043b\u0443\u0447\u0430\u0435\u043c \u0432\u0441\u0435 \u0447\u0442\u043e \u0445\u043e\u0442\u0435\u043b\u0438!!<\/p>\n<figure class=\"\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/habrastorage.org\/getpro\/habr\/upload_files\/524\/adb\/d58\/524adbd5857b370ec7db00cbe16bf8d7.png\" width=\"407\" height=\"272\"><figcaption><\/figcaption><\/figure>\n<p><strong>\u0421\u043f\u0430\u0441\u0438\u0431\u043e \u0437\u0430 \u043f\u0440\u043e\u0447\u0442\u0435\u043d\u0438\u0435, \u0441\u043a\u043e\u0440\u043e \u0431\u0443\u0434\u0435\u0442 \u0432\u0442\u043e\u0440\u0430\u044f \u0447\u0430\u0441\u0442\u044c \u043f\u0440\u043e \u0442\u0435\u043c\u0430\u0442\u0438\u0447\u0435\u0441\u043a\u043e\u0435 \u043c\u043e\u0434\u0435\u043b\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u0435 \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e  BERT<\/strong><\/p>\n<p>\u0411\u043e\u043b\u044c\u0448\u043e\u0435 \u0441\u043f\u0430\u0441\u0438\u0431\u043e \u044f \u0445\u043e\u0447\u0443 \u0441\u043a\u0430\u0437\u0430\u0442\u044c \u0441\u0432\u043e\u0438\u043c \u043f\u043e\u0434\u043f\u0438\u0441\u0447\u0438\u043a\u0430\u043c \u0432 <a href=\"https:\/\/t.me\/response1000000\" rel=\"noopener noreferrer nofollow\">\u0442\u0435\u043b\u0435\u0433\u0440\u0430\u043c\u043c\u0435<\/a> <\/p>\n<p>\u0422\u0430\u043a \u0436\u0435 \u0432 \u043c\u043e\u0435\u043c \u0442\u0435\u043b\u0435\u0433\u0440\u0430\u043c\u043c\u0435 \u0435\u0441\u0442\u044c \u043c\u043d\u043e\u0433\u043e \u043d\u043e\u0443\u0442\u0431\u0443\u043a\u043e\u0432 \u0438 \u0441\u0442\u0430\u0442\u0435\u0439 \u043f\u0440\u043e DS \u0438 \u043d\u0435 \u043e\u0447\u0435\u043d\u044c. \u041d\u0430\u043f\u0440\u0438\u043c\u0435\u0440 \u0440\u0435\u043d\u0434\u0435\u0440 3\u0434 \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u043d\u0430  <a href=\"https:\/\/colab.research.google.com\/\" rel=\"noopener noreferrer nofollow\">https:\/\/colab.research.google.com\/<\/a> \u0410 \u0432 \u0440\u0443\u0431\u0440\u0438\u043a\u0435 #\u0447\u0442\u0438\u0432\u043e\u043d\u0430\u043d\u043e\u0447\u044c \u044f \u0440\u0430\u0441\u0441\u043a\u0430\u0437\u044b\u0432\u0430\u044e \u043f\u0440\u043e \u0441\u0430\u043c\u043e\u0435 \u0438\u043d\u0442\u0435\u0440\u0435\u0441\u043d\u043e\u0435, \u0447\u0442\u043e  \u044f \u043d\u0430\u0448\u0435\u043b \u0437\u0430 \u043f\u043e\u0441\u043b\u0435\u0434\u043d\u0438\u0435 \u0432\u0440\u0435\u043c\u044f.<\/p>\n<p><a href=\"https:\/\/colab.research.google.com\/drive\/1ap8pUgoYATYb5NFjiccd-1eFUIJn5ycj#scrollTo=LQVYr9HM88Ph\" rel=\"noopener noreferrer nofollow\"><strong>\u041a\u043e\u0434 <\/strong><\/a><\/p>\n<\/div>\n<p> \u0441\u0441\u044b\u043b\u043a\u0430 \u043d\u0430 \u043e\u0440\u0438\u0433\u0438\u043d\u0430\u043b \u0441\u0442\u0430\u0442\u044c\u0438 <a href=\"https:\/\/habr.com\/ru\/post\/539774\/\"> https:\/\/habr.com\/ru\/post\/539774\/<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"\n<div class=\"post__text post__text_v2\" id=\"post-content-body\">\n<h4>\u0417\u0430\u0447\u0435\u043c<\/h4>\n<p>\u0423 \u043a\u0430\u0436\u0434\u043e\u0433\u043e \u043c\u043e\u043b\u043e\u0434\u043e\u0433\u043e DS \u0432 \u043a\u0430\u043a\u043e\u0439 \u0442\u043e \u043c\u043e\u043c\u0435\u043d\u0442 \u0432\u0440\u0435\u043c\u0435\u043d\u0438 \u0432\u043e\u0437\u043d\u0438\u043a\u0430\u0435\u0442 \u043f\u0440\u043e\u0431\u043b\u0435\u043c\u0430 &#8212;<s> \u043e\u0447\u0435\u043d\u044c \u0445\u043e\u0447\u0435\u0442\u0441\u044f \u0442\u044f\u043d\u043e\u0447\u043a\u0443<\/s>, \u0432\u0441\u043c\u044b\u0441\u043b\u0435 \u0441\u043f\u0430\u0440\u0441\u0438\u0442\u044c \u0442\u0438\u043d\u0434\u0435\u0440 \u0438 \u0441\u0434\u0435\u043b\u0430\u0442\u044c \u0442\u0435\u043c\u0430\u0442\u0438\u0447\u0435\u0441\u043a\u043e\u0435 \u043c\u043e\u0434\u0435\u043b\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u0435 \u043d\u0430 \u043e\u043f\u0438\u0441\u0430\u043d\u0438\u044f\u0445 \u043f\u0440\u043e\u0444\u0438\u043b\u044f.<\/p>\n<h4>\u041a\u0430\u043a<\/h4>\n<p>\u041e\u0442\u0432\u0435\u0442 \u043a\u043e\u0440\u043e\u0442\u043a\u0438\u0439 &#8212; \u043b\u0435\u0433\u043a\u043e, \u0432\u043e\u0442 \u0441\u0441\u044b\u043b\u043a\u0430 \u043d\u0430 <a href=\"https:\/\/colab.research.google.com\/drive\/1ap8pUgoYATYb5NFjiccd-1eFUIJn5ycj?usp=sharing\" rel=\"noopener noreferrer nofollow\">collab<\/a><\/p>\n<p>\u0414\u043b\u0438\u043d\u043d\u044b\u0439 \u043e\u0442\u0432\u0435\u0442 &#8212; \u0442\u0438\u043d\u0434\u0435\u0440 \u043e\u0431\u043c\u0435\u043d\u0438\u0432\u0430\u0435\u0442\u0441\u044f \u043e\u0442\u043a\u0440\u044b\u0442\u044b\u043c json \u0441  https:\/\/api.gotinder.com, \u0430 \u0432 XHR \u043b\u0435\u0436\u0438\u0442 \u043d\u0430\u0448 x auth key.  \u041e\u0441\u0442\u0430\u043b\u044c\u043d\u043e\u0435 &#8212; \u0434\u0435\u043b\u043e \u0442\u0435\u0445\u043d\u0438\u043a\u0438 \u0438 \u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a\u0438 Response. <\/p>\n<figure class=\"full-width\"><figcaption><\/figcaption><\/figure>\n<h4>\u041f\u0430\u0440\u0441\u0438\u043d\u0433<\/h4>\n<p>\u041a\u043e\u0434 \u0434\u043b\u044f \u043f\u0440\u043e\u0444\u0438\u043b\u044f<\/p>\n<pre><code>import datetime from geopy.geocoders import Nominatim  AuthKey = '' # \u041a\u043b\u044e\u0447 \u043f\u0438\u0445\u0443\u0435\u043c \u0441\u044e\u0434\u0430   TINDER_URL = \"https:\/\/api.gotinder.com\" geolocator = Nominatim(user_agent=\"auto-tinder\") PROF_FILE = \".\/images\/unclassified\/profiles.txt\"  class Person(object):      def __init__(self, data, api):         self._api = api          self.id = data[\"_id\"]         self.name = data.get(\"name\", \"Unknown\")          self.bio = data.get(\"bio\", \"\")        \t          self.birth_date = datetime.datetime.strptime(data[\"birth_date\"], '%Y-%m-%dT%H:%M:%S.%fZ') if data.get(             \"birth_date\", False) else None         self.gender = [\"Male\", \"Female\", \"Unknown\"][data.get(\"gender\", 2)]          self.images = list(map(lambda photo: photo[\"url\"], data.get(\"photos\", [])))          self.jobs = list(             map(lambda job: {\"title\": job.get(\"title\", {}).get(\"name\"), \"company\": job.get(\"company\", {}).get(\"name\")}, data.get(\"jobs\", [])))         self.schools = list(map(lambda school: school[\"name\"], data.get(\"schools\", [])))          if data.get(\"pos\", False):             self.location = geolocator.reverse(f'{data[\"pos\"][\"lat\"]}, {data[\"pos\"][\"lon\"]}')           def __repr__(self):         return f\"{self.id}  -  {self.name} ({self.birth_date.strftime('%d.%m.%Y')})\"       def like(self):         return self._api.like(self.id)      def dislike(self):         return self._api.dislike(self.id)<\/code><\/pre>\n<p>\u041d\u0438\u0447\u0435\u0433\u043e \u0438\u043d\u0442\u0435\u0440\u0435\u0441\u043d\u043e\u0433\u043e \u0442\u0443\u0442 \u043d\u0435\u0442, \u043f\u0440\u043e\u0441\u0442\u043e \u0445\u043e\u0434\u0438\u043c \u043f\u043e html \u0438 \u0442\u044f\u043d\u0435\u043c \u0442\u043e \u0447\u0442\u043e \u043d\u0443\u0436\u043d\u043e<\/p>\n<p>\u0420\u0430\u0431\u043e\u0442\u0430 \u0441 API <\/p>\n<pre><code>import requests  TINDER_URL = \"https:\/\/api.gotinder.com\"  class tinderAPI():      def __init__(self, token):         self._token = token      def profile(self):         data = requests.get(TINDER_URL + \"\/v2\/profile?include=account%2Cuser\", headers={\"X-Auth-Token\": self._token}).json()         return Profile(data[\"data\"], self)      def matches(self, limit=10):         data = requests.get(TINDER_URL + f\"\/v2\/matches?count={limit}\", headers={\"X-Auth-Token\": self._token}).json()         return list(map(lambda match: Person(match[\"person\"], self), data[\"data\"][\"matches\"]))      def like(self, user_id):         data = requests.get(TINDER_URL + f\"\/like\/{user_id}\", headers={\"X-Auth-Token\": self._token}).json()         return {             \"is_match\": data[\"match\"],             \"liked_remaining\": data[\"likes_remaining\"]         }      def dislike(self, user_id):         requests.get(TINDER_URL + f\"\/pass\/{user_id}\", headers={\"X-Auth-Token\": self._token}).json()         return True      def nearby_persons(self):         data = requests.get(TINDER_URL + \"\/v2\/recs\/core\", headers={\"X-Auth-Token\": self._token}).json()                  return list(map(lambda user: Person(user[\"user\"], self), data[\"data\"][\"results\"]))<\/code><\/pre>\n<p>\u0422\u0443\u0442 \u043c\u044b \u043f\u043e\u043b\u0443\u0447\u0430\u0435\u043c json, \u0440\u0430\u0437\u0431\u0438\u0440\u0430\u0435\u043c \u0435\u0433\u043e \u0438 \u0442\u0430\u0449\u0438\u043c \u0432\u0441\u0435 \u0447\u0442\u043e \u043d\u0430\u043c \u043d\u0443\u0436\u043d\u043e(\u0441\u043f\u0438\u0441\u043e\u043a \u044e\u0437\u0435\u0440\u043e\u0432)<\/p>\n<h4>\u041a\u043b\u0430\u0434\u0435\u043c \u0432\u0441\u0435 \u0432 .csv<\/h4>\n<pre><code>import time import pandas as pd df = pd.DataFrame() prf = [] prsn= [] vuz = [] gender = [] job = [] if __name__ == \"__main__\":     token = AuthKey     api = tinderAPI(token)      while True:         persons = api.nearby_persons()         for person in persons:            #\u0442\u0443\u0442 \u043d\u0435\u0442 \u043b\u043e\u0433\u0438\u043a\u0438, \u043d\u0430\u043f\u0438\u0448\u0438\u0442\u0435 \u0441\u0430\u043c\u0438 \u0435\u0441\u043b\u0438 \u0437\u0430\u0445\u043e\u0442\u0438\u0442             print(person)             time.sleep(1)             person.dislike()             prf+=[person.bio]             prsn+=[person]             vuz+=[person.schools]             job+=[person.jobs]             gender+=[person.gender]             print(person.bio) df['vuz'] = vuz df['jobs'] = job df['person'] = prsn df['bio'] = prf  df['gender'] = gender df.to_csv('tinder.csv') <\/code><\/pre>\n<p>\u041a\u043e\u0433\u0434\u0430 \u043a\u043e\u043d\u0447\u0430\u044e\u0442\u0441\u044f \u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u0435\u043b\u0438 \u043e\u043d\u043e \u0432\u044b\u043b\u0435\u0442\u0430\u0435\u0442 \u0438 \u043d\u0435 \u0441\u043e\u0445\u0440\u0430\u043d\u044f\u0435\u0442, \u043f\u043e \u044d\u0442\u043e\u043c\u0443 \u043d\u0443\u0436\u043d\u043e \u0432\u044b\u0434\u0435\u043b\u044f\u0442\u044c \u043a\u043e\u0434 \u0434\u043b\u044f \u0441\u043e\u0445\u0440\u0430\u043d\u0435\u043d\u0438\u044f \u0432 \u043e\u0442\u0434\u0435\u043b\u044c\u043d\u0443\u044e \u044f\u0447\u0435\u0439\u043a\u0443 \u043a\u043e\u0434\u0430. \u0411\u043b\u0430\u0433\u043e collab \u043f\u043e\u0437\u0432\u043e\u043b\u044f\u0435\u0442 \u043d\u0435 \u0434\u0443\u043c\u0430\u0442\u044c, \u0430 \u0434\u0435\u043b\u0430\u0442\u044c. \u0411\u043e\u043b\u0435\u0435 \u043e\u043f\u044b\u0442\u043d\u044b\u0435 \u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u0435\u043b\u0438 \u043c\u043e\u0433\u0443\u0442 \u0441\u043a\u0430\u0437\u0430\u0442\u044c \u0447\u0442\u043e \u043d\u0430\u0434\u043e \u043e\u0431\u043b\u043e\u0436\u0438\u0442\u044c \u0432 try: , \u043d\u043e \u043c\u043d\u0435 \u043d\u0435 \u0445\u043e\u0447\u0435\u0442\u0441\u044f, \u0434\u0430 \u0438 \u0441\u043c\u044b\u0441\u043b\u0430 \u043d\u0435\u0442.<\/p>\n<p>\u0414\u0432\u0430 \u0447\u0430\u0441\u0430 \u0441\u043f\u0443\u0441\u0442\u044f \u043f\u043e\u043b\u0443\u0447\u0430\u0435\u043c \u0432\u0441\u0435 \u0447\u0442\u043e \u0445\u043e\u0442\u0435\u043b\u0438!!<\/p>\n<figure class=\"\"><figcaption><\/figcaption><\/figure>\n<p><strong>\u0421\u043f\u0430\u0441\u0438\u0431\u043e \u0437\u0430 \u043f\u0440\u043e\u0447\u0442\u0435\u043d\u0438\u0435, \u0441\u043a\u043e\u0440\u043e \u0431\u0443\u0434\u0435\u0442 \u0432\u0442\u043e\u0440\u0430\u044f \u0447\u0430\u0441\u0442\u044c \u043f\u0440\u043e \u0442\u0435\u043c\u0430\u0442\u0438\u0447\u0435\u0441\u043a\u043e\u0435 \u043c\u043e\u0434\u0435\u043b\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u0435 \u0441 \u043f\u043e\u043c\u043e\u0449\u044c\u044e  BERT<\/strong><\/p>\n<p>\u0411\u043e\u043b\u044c\u0448\u043e\u0435 \u0441\u043f\u0430\u0441\u0438\u0431\u043e \u044f \u0445\u043e\u0447\u0443 \u0441\u043a\u0430\u0437\u0430\u0442\u044c \u0441\u0432\u043e\u0438\u043c \u043f\u043e\u0434\u043f\u0438\u0441\u0447\u0438\u043a\u0430\u043c \u0432 <a href=\"https:\/\/t.me\/response1000000\" rel=\"noopener noreferrer nofollow\">\u0442\u0435\u043b\u0435\u0433\u0440\u0430\u043c\u043c\u0435<\/a> <\/p>\n<p>\u0422\u0430\u043a \u0436\u0435 \u0432 \u043c\u043e\u0435\u043c \u0442\u0435\u043b\u0435\u0433\u0440\u0430\u043c\u043c\u0435 \u0435\u0441\u0442\u044c \u043c\u043d\u043e\u0433\u043e \u043d\u043e\u0443\u0442\u0431\u0443\u043a\u043e\u0432 \u0438 \u0441\u0442\u0430\u0442\u0435\u0439 \u043f\u0440\u043e DS \u0438 \u043d\u0435 \u043e\u0447\u0435\u043d\u044c. \u041d\u0430\u043f\u0440\u0438\u043c\u0435\u0440 \u0440\u0435\u043d\u0434\u0435\u0440 3\u0434 \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u043d\u0430  <a href=\"https:\/\/colab.research.google.com\/\" rel=\"noopener noreferrer nofollow\">https:\/\/colab.research.google.com\/<\/a> \u0410 \u0432 \u0440\u0443\u0431\u0440\u0438\u043a\u0435 #\u0447\u0442\u0438\u0432\u043e\u043d\u0430\u043d\u043e\u0447\u044c \u044f \u0440\u0430\u0441\u0441\u043a\u0430\u0437\u044b\u0432\u0430\u044e \u043f\u0440\u043e \u0441\u0430\u043c\u043e\u0435 \u0438\u043d\u0442\u0435\u0440\u0435\u0441\u043d\u043e\u0435, \u0447\u0442\u043e  \u044f \u043d\u0430\u0448\u0435\u043b \u0437\u0430 \u043f\u043e\u0441\u043b\u0435\u0434\u043d\u0438\u0435 \u0432\u0440\u0435\u043c\u044f.<\/p>\n<p><a href=\"https:\/\/colab.research.google.com\/drive\/1ap8pUgoYATYb5NFjiccd-1eFUIJn5ycj#scrollTo=LQVYr9HM88Ph\" rel=\"noopener noreferrer nofollow\"><strong>\u041a\u043e\u0434 <\/strong><\/a><\/p>\n<\/div>\n<p> \u0441\u0441\u044b\u043b\u043a\u0430 \u043d\u0430 \u043e\u0440\u0438\u0433\u0438\u043d\u0430\u043b \u0441\u0442\u0430\u0442\u044c\u0438 <a href=\"https:\/\/habr.com\/ru\/post\/539774\/\"> https:\/\/habr.com\/ru\/post\/539774\/<\/a><br \/><\/br><\/br><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[],"tags":[],"class_list":["post-317137","post","type-post","status-publish","format-standard","hentry"],"_links":{"self":[{"href":"https:\/\/savepearlharbor.com\/index.php?rest_route=\/wp\/v2\/posts\/317137","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/savepearlharbor.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/savepearlharbor.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/savepearlharbor.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/savepearlharbor.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=317137"}],"version-history":[{"count":0,"href":"https:\/\/savepearlharbor.com\/index.php?rest_route=\/wp\/v2\/posts\/317137\/revisions"}],"wp:attachment":[{"href":"https:\/\/savepearlharbor.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=317137"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/savepearlharbor.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=317137"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/savepearlharbor.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=317137"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}