def InstaImageScraper():
imgScraper = insta.InstagramScraper(usernames=[insta_profiles[x]],
maximum=number_last_photos,
media_metadata=True, latest=True,
media_types=['image'])
imgScraper.scrape()
print("image scraping is running, please wait 50 seconds.")
def getPostsByEnglishName():
result = {}
instagram = instagram_scraper.InstagramScraper()
user = instagram.get_user(INSTAGRAM_ACCOUNT)
posts = instagram.query_media_gen(user)
num_posts = 0
for post in posts:
caption = post['edge_media_to_caption']['edges'][0]['node']['text']
english_name = getFirstHashtag(caption)
likes = post['edge_media_preview_like']['count']
comments = post['edge_media_to_comment']['count']
thumbnail = post['thumbnail_resources'][0]
result[english_name] = {
'likes': likes,
'num_comments': comments,
'images': {
'thumbnail': {
'url': thumbnail['src'],
'width': thumbnail['config_width'],
'height': thumbnail['config_height']
}
}
}
num_posts += 1
# print('%s %d' % (getFirstHashtag(caption), likes))
print('%d instagram posts' % num_posts)
return result
def scraper():
#call('instagram-scraper ' + insta_profiles + ' -m ' + number_last_photos + ' -u 0 -p 0 -t none --media-metadata', shell=True)
imgScraper = insta.InstagramScraper(usernames=[insta_profiles[x]],
login_user="******",
login_pass="******",
maximum=number_last_photos,
media_metadata=True,
latest=True,
media_types=['image'])
imgScraper.scrape()
# Take last json image data and post in instagram images, tags and decription
with open(insta_profiles[x] + '/' + insta_profiles[x] + '.json', 'r') as j:
json_data = json.load(j)
newstr = (json_data[0]["display_url"])
imgUrl = newstr.split('?')[0].split('/')[-1]
imgTags = (json_data[0]["tags"])
# imgDescription = (json_data[0]["description"])
#Execute Instagram users with instapy. Excecute list insta_profiles
call(
'instapy -u yourusername -p yourpassword -f ./' +
insta_profiles[x] + '/' + imgUrl +
' -t "#model #models #Modeling #modelo #modellife #modelling #modelagency #Modelos #modelphotography #modelsearch #ModelStatus #modelingagency #modelfitness #ModelsWanted #modelshoot #modella #modelmanagement #modelscout #modeltest #modelindonesia #modele #modelife #modelmayhem #modelgirl #modell #modelslife #modelkids #modelcall #modelpose #ModelBehavior"',
shell=True)
time.sleep(5)
# Account number 2
call(
'instapy -u yourusername -p yourpassword -f ./' +
insta_profiles[x] + '/' + imgUrl +
' -t "#model #models #Modeling #modelo #modellife #modelling #modelagency #Modelos #modelphotography #modelsearch #ModelStatus #modelingagency #modelfitness #ModelsWanted #modelshoot #modella #modelmanagement #modelscout #modeltest #modelindonesia #modele #modelife #modelmayhem #modelgirl #modell #modelslife #modelkids #modelcall #modelpose #ModelBehavior"',
shell=True)
print(imgUrl)
print("scraped " + str(number_last_photos) + " from " + insta_profiles[x])
def start_like_followersai():
x = 0
bot.api.get_self_username_info()
profile_pic = bot.api.last_json["user"]["profile_pic_url"]
followers = bot.api.last_json["user"]["follower_count"]
following = bot.api.last_json["user"]["following_count"]
media_count = bot.api.last_json["user"]["media_count"]
number_last_photos = 1
following_username = request.form['following_username']
time_sleep = request.form['time_sleep']
user_id = bot.get_user_id_from_username(following_username)
following = bot.get_user_followers(user_id)
for user in following:
pusername = bot.get_username_from_user_id(user)
imgScraper = instagram_scraper.InstagramScraper(usernames=[pusername],
maximum=number_last_photos,
media_metadata=True,
latest=True,
media_types=['image'])
imgScraper.scrape()
# Open user json and if face is detected it will do command
try:
with open(pusername + '/' + pusername + '.json', 'r') as j:
json_data = json.load(j)
display_url = (json_data["GraphImages"][0]["display_url"])
media_id = (json_data["GraphImages"][0]["id"])
profile = (json_data["GraphImages"][0]["username"])
imgUrl = display_url.split('?')[0].split('/')[-1]
instapath = pusername + '/' + imgUrl
try:
img = cv2.imread(instapath)
detector = MTCNN()
detect = detector.detect_faces(img)
bot.logger.info("Face Detected")
except Exception as e:
bot.logger.info(e)
if not detect:
bot.logger.info("No Face Detected")
j.close()
else:
bot.api.like(media_id)
bot.logger.info("liked " + display_url + " by" + profile + "\n")
x += 1
bot.logger.info("liked " + str(x) + " images" + "\n")
bot.logger.info("Sleeping")
time_sleep = int(time_sleep)
time.sleep(time_sleep)
j.close()
except Exception as ee:
bot.logger.info(ee)
return render_template("like_followersai.html", username=username,
profile_pic=profile_pic, followers=followers,
following=following, media_count=media_count);
def InstaImageScraper():
''' Scrape image on profiles '''
imgScraper = insta.InstagramScraper(usernames=profiles,
maximum=number_last_photos,
media_metadata=True,
latest=True,
media_types=['image'])
imgScraper.scrape()
print("Images has been scraped")
def scraper():
# call('instagram-scraper ' + insta_profiles + ' -m ' + number_last_photos + ' -u 0 -p 0 -t none --media-metadata', shell=True)
imgScraper = insta.InstagramScraper(usernames=[insta_profiles[x]],
maximum=number_last_photos,
media_metadata=True,
latest=True,
media_types=['none'])
imgScraper.scrape()
print("scraped " + str(number_last_photos) + " from " + insta_profiles[x])
def start_like_followersai():
number_last_photos = 1
following_username = request.form['following_username']
time_sleep = request.form['time_sleep']
user_id = bot.get_user_id_from_username(following_username)
following = bot.get_user_followers(user_id)
for user in following:
pusername = bot.get_username_from_user_id(user)
imgScraper = instagram_scraper.InstagramScraper(
usernames=[pusername],
maximum=number_last_photos,
media_metadata=True,
latest=True,
media_types=['image'])
imgScraper.scrape()
# Open user json and if face is detected it will do command
try:
with open(pusername + '/' + pusername + '.json', 'r') as j:
json_data = json.load(j)
display_url = (json_data["GraphImages"][0]["display_url"])
media_id = (json_data["GraphImages"][0]["id"])
profile = (json_data["GraphImages"][0]["username"])
imgUrl = display_url.split('?')[0].split('/')[-1]
instapath = pusername + '/' + imgUrl
img = cv2.imread(instapath)
detector = MTCNN()
detect = detector.detect_faces(img)
if not detect:
print("no face detected")
else:
bot.api.like(media_id)
print("liked " + display_url + " by" + profile)
print("=" * 30)
time_sleep = int(time_sleep)
time.sleep(time_sleep)
except:
pass
return render_template("like_followersai.html",
username=username,
profile_pic=profile_pic,
followers=followers,
following=following,
media_count=media_count)
def scraper(profile, start, posts, username, passwd):
imgScraper = insta.InstagramScraper(usernames=[profile],
login_user=username,
login_pass=passwd,
maximum=start + posts - 1,
media_metadata=True,
latest=True,
media_types=['image'])
imgScraper.scrape()
# Take last json image data and post in instagram images, tags and decription
with open(os.path.join(profile, profile + '.json'), 'r') as j:
json_data = json.load(j)
pics = json_data[start - 1:start + posts - 1]
for pic in pics:
newstr = (pic["display_url"])
imgUrl = newstr.split('?')[0].split('/')[-1]
cap = None
try:
cap = pic["edge_media_to_caption"]["edges"][-1]["node"][
"text"] + '\n'
if caption is False:
cap = ""
else:
print("Caption: " + cap)
except:
cap = ""
print("No caption exists.")
random.shuffle(tags)
#Execute Instagram users with instapy. Excecute list insta_profiles
tagString = "#" + " #".join(tags[:min(30, len(tags)) - 1])
call('instapy -u ' + username + ' -p ' + passwd + ' -f ./' +
profile + '/' + imgUrl + ' -t "' + cap + tagString + '"',
shell=True)
print(imgUrl)
time.sleep(delay)
print("Scraped " + str(posts) + "(Post no. " + str(start) + ", Post no. " +
str(start + posts - 1) + ") posts from " + profile)
"Make sure you have all arguments: username, password, and tag genre. "
)
print("Example command: `python selenium_driver.py username password tag`")
username = input("username: "******"password: "******"tag genre: ")
else:
username = str(sys.argv[1])
password = str(sys.argv[2])
try:
tag_genre = str(sys.argv[3])
except:
tag_genre = ""
# set up scraper
scraper = instagram_scraper.InstagramScraper()
scraper.setUp()
scraper.login(username, password)
tag = tag_dict.get(tag_genre, ["instagram"])
if tag_genre == "ad":
insta_users = scraper.related_tags_search_paid_promo("ad")
scraper.write_arr_to_file("ad", insta_users)
elif tag_genre == "emails":
dirname = input("directory name: ")
scraper.get_insta_profile_emails(dirname)
else:
for tt in tag:
insta_users = scraper.related_tags_search_by_likes(tt)
def instascraper(bot, new_media_id, path=POSTED_MEDIAS):
global x
while x < len(insta_profiles):
imgScraper = insta.InstagramScraper(usernames=[insta_profiles[x]],
maximum=number_last_photos,
media_metadata=True,
latest=True,
media_types=['image'])
imgScraper.scrape()
print("image scraping is running or not")
try:
# Open insta_profiles[x] and it's scraped json file at take first image location
with open(insta_profiles[x] + '/' + insta_profiles[x] + '.json',
'r') as j:
json_data = json.load(j)
newstr = (json_data[0]["display_url"])
imgUrl = newstr.split('?')[0].split('/')[-1]
global instapath
instapath = insta_profiles[x] + '/' + imgUrl
# Locate Face On image scraped
image = face_recognition.load_image_file(instapath)
face_locations = face_recognition.face_locations(image)
# If no face located scrape the next profile
if not face_locations:
print("There is no Face Detected scraping next profile")
x += 1
instascraper()
else:
print(
"There is a Face Detected scraping and posting this image"
)
print(face_locations)
print(instapath)
# Append username info to csv file
try:
f = open(f"{username}.tsv", "a+")
f.write(str(saveStats))
f.close
f = open(f"{username}.tsv", "r")
last_line = f.readlines()[-2].replace("False", "")
print("Date - Time - Followers - Following - Posts")
print(last_line)
f.close
# Write username tsv file if it does not exist
except:
f = open(f"{username}.tsv", "w+")
f.write(str(saveStats))
f.close
f = open(f"{username}.tsv", "r")
last_line = f.readlines()[-1]
print("Date - Time - Followers - Following - Posts")
print(last_line)
f.close
time.sleep(2)
time.sleep(2)
repost_best_photos(bot, users, args.amount)
print("Posting Instagram")
os.remove("posted_medias.txt")
time.sleep(900)
except:
print("User is set to Private scraping next user")
x += 1
import instagram_scraper as insta
scraper = insta.InstagramScraper(hashtag='bangaloreairport',
maximum=200,
quiet=False,
tag=True)
a = scraper.scrape_hashtag()
print(a)
parser.add_argument('users', type=str, nargs='*', help='users')
args = parser.parse_args()
bot = Bot()
bot.login()
users = None
if args.users:
users = args.users
elif args.file:
users = utils.file(args.file).list
while x < len(insta_profiles):
imgScraper = insta.InstagramScraper(usernames=[insta_profiles[x]],
maximum=number_last_photos,
media_metadata=True,
latest=True,
media_types=['image'])
imgScraper.scrape()
print("image scraping is running or not")
try:
with open(insta_profiles[x] + '/' + insta_profiles[x] + '.json',
'r') as j:
json_data = json.load(j)
newstr = (json_data[0]["display_url"])
imgUrl = newstr.split('?')[0].split('/')[-1]
instapath = insta_profiles[x] + '/' + imgUrl
print(instapath)
repost_best_photos(bot, users, args.amount)
time.sleep(600)
def instagram(update, context):
scraper = instagram_scraper.InstagramScraper()
insta_post = scraper.get_latest_instagram_post()
context.bot.send_message(chat_id=update.message.chat_id,
text=insta_post)
