/ RESTful API

Instagram Bot - Like/Comment/Follow Automation Script

Instagram Bot - Like/Comment/Follow Automation Script

InstaPy

Automation Script for "farming" Likes, Comments and Followers on Instagram
Implemented in Python using the Selenium module.

Getting started

Video tutorials:

Setting up InstaPy for OSX

Setting up InstaPy at Digital Ocean (for Debian)

Guides:

How to Ubuntu (64-Bit)       

How to RaspberryPi       

How to Windows

Basic Installation:

1. git clone https://github.com/timgrossmann/InstaPy.git
2. cd InstaPy
3. pip install .
or
3. python setup.py install
  1. Download chromedriver for your system from here. Extract the .zip file and put it in /assets folder.

Preferred Installation:

The best way to install InstaPy is to create a virtualenv, install InstaPy there and run it from a separate file:

1. virtualenv venv
2. source venv/bin/activate
3. pip install git+https://github.com/timgrossmann/InstaPy.git

If you're not familiar with virtualenv, please read about it here and use it to your advantage.
In essence, this is be the only Python library you should install as root (e.g., with sudo). All other Python libraries should be inside a virtualenv.
Now copy/paste the quickstart.py Python code below and run your first InstaPy script. Remember to run it with Python from the virtualenv, so from venv/bin/python. To make sure which Python is used, run which python, it will tell you which Python is 'active'.
Running source venv/bin/activate will activate the correct Python to run InstaPy. To exit an activated virtualenv run `deactivate'.

Set it up yourself with this Basic Setup

Basic setup is a good way to test the tool. At project root folder open quickstart.py and update with your username and password.

from instapy import InstaPy

insta_username = ''
insta_password = ''

# if you want to run this script on a server,
# simply add nogui=True to the InstaPy() constructor
session = InstaPy(username=insta_username, password=insta_password)
session.login()

# set up all the settings
session.set_relationship_bounds(enabled=True,
				 potency_ratio=-1.21,
				  delimit_by_numbers=True,
				   max_followers=4590,
				    max_following=5555,
				     min_followers=45,
				      min_following=77)
session.set_do_comment(True, percentage=10)
session.set_comments(['aMEIzing!', 'So much fun!!', 'Nicey!'])
session.set_dont_include(['friend1', 'friend2', 'friend3'])
session.set_dont_like(['pizza', 'girl'])

# do the actual liking
session.like_by_tags(['natgeo', 'world'], amount=100)

# end the bot session
session.end()

Execute it:

$ python quickstart.py

Or use our GUI

1. Official Cross Platform GUI

3. Session scheduling with Telegram

InstaPy Available Features

Commenting

# default enabled=False, ~ every 4th image will be commented on

session.set_do_comment(enabled=True, percentage=25)
session.set_comments(['Awesome', 'Really Cool', 'I like your stuff'])

# you can also set comments for specific media types (Photo / Video)

session.set_comments(['Nice shot!'], media='Photo')
session.set_comments(['Great Video!'], media='Video')

# and you can add the username of the poster to the comment by using

session.set_comments(['Nice shot! @{}'], media='Photo')

Following

# default enabled=False, follows ~ 10% of the users from the images, times=1
# (only follows a user once (if unfollowed again))

session.set_do_follow(enabled=True, percentage=10, times=2)

Following by a list

This will follow each account from a list of instagram nicknames
follow_by_list(followlist=['samantha3', 'larry_ok'], times=1, sleep_delay=600, interact=False)

only follows a user once (if unfollowed again) would be useful for the precise targeting
sleep_delay is used to define break time after some good following (averagely ~10 follows)
For example, if one needs to get followbacks from followers of a chosen account/group of accounts.

accs = ['therock','natgeo']
session.follow_by_list(accs, times=1, sleep_delay=600, interact=False)
  • You can also interact with the followed users by enabling interact=True which will use the configuration of set_user_interact setting:
session.set_user_interact(amount=4,
				 percentage=50,
                  randomize=True,
                   media='Photo')
session.follow_by_list(followlist=['samantha3', 'larry_ok'], times=2, sleep_delay=600, interact=True)

Follow someone else's followers

# Follows the followers of each given user
# The usernames can be either a list or a string
# The amount is for each account, in this case 30 users will be followed
# If randomize is false it will pick in a top-down fashion

session.follow_user_followers(['friend1', 'friend2', 'friend3'], amount=10, randomize=False)

# default sleep_delay=600 (10min) for every 10 user following, in this case
# sleep for 60 seconds

session.follow_user_followers(['friend1', 'friend2', 'friend3'], amount=10, randomize=False, sleep_delay=60)

Note: simulation takes place while running this feature.

Follow users that someone else is following

# Follows the people that a given users are following
# The usernames can be either a list or a string
# The amount is for each account, in this case 30 users will be followed
# If randomize is false it will pick in a top-down fashion

session.follow_user_following(['friend1', 'friend2', 'friend3'], amount=10, randomize=False)

# default sleep_delay=600 (10min) for every 10 user following, in this case
# sleep for 60 seconds

session.follow_user_following(['friend1', 'friend2', 'friend3'], amount=10, randomize=False, sleep_delay=60)

Note: simulation takes place while running this feature.

Follow someone else's followers/following

# For 50% of the 30 newly followed, move to their profile
# and randomly choose 5 pictures to be liked.
# Take into account the other set options like the comment rate
# and the filtering for inappropriate words or users

session.set_user_interact(amount=5, randomize=True, percentage=50, media='Photo')
session.follow_user_followers(['friend1', 'friend2', 'friend3'], amount=10, randomize=False, interact=True)

Follow by Tags

# Follow user based on hashtags (without liking the image)

session.follow_by_tags(['tag1', 'tag2'], amount=10)

Follow the likers of photos of users

This will follow the people those liked photos of given list of users
session.follow_likers (['user1' , 'user2'], photos_grab_amount = 2, follow_likers_per_photo = 3, randomize=True, sleep_delay=600, interact=False)

in this case 2 random photos from each given user will be analyzed and 3 people who liked them will be followed, so 6 follows in total
The usernames can be any list
The photos_grab_amount is how many photos will I grat from users profile and analyze who liked it
The follow_likers_per_photo is how many people to follow per each photo
randomize=False will take photos from newes, true will take random from first 12
sleep_delay is used to define break time after some good following (averagely ~10 follows)

  • You can also interact with the followed users by enabling interact=True which will use the configuration of set_user_interact setting:
session.set_user_interact(amount=2,
				 percentage=70,
                  randomize=True,
                   media='Photo')
session.follow_likers (['user1' , 'user2'], photos_grab_amount = 2, follow_likers_per_photo = 3, randomize=True, sleep_delay=600, interact=True)

Follow the commenters of photos of users

This will follow the people those commented on photos of given list of users
session.follow_commenters(['user1', 'user2', 'user3'], amount=100, daysold=365, max_pic = 100, sleep_delay=600, interact=False)

in this case (max 100 newest photos & maximum 365 days old) from each given user will be analyzed and 100 people who commented the most will be followed
The usernames can be any list
The amount is how many people to follow
The daysold will only take commenters from photos no older than daysold days
The max_pic will limit number of photos to analyze
sleep_delay is used to define break time after some good following (averagely ~10 follows)

  • You can also interact with the followed users by enabling interact=True which will use the configuration of set_user_interact setting:
session.set_user_interact(amount=3,
				 percentage=32,
                  randomize=True,
                   media='Video')
session.follow_commenters(['user1', 'user2', 'user3'], amount=100, daysold=365, max_pic = 100, sleep_delay=600, interact=True)

Interact with specific users

# Interact with specific users
# set_do_like, set_do_comment, set_do_follow are applicable

session.set_do_follow(enabled=False, percentage=50)
session.set_comments(["Cool", "Super!"])
session.set_do_comment(enabled=True, percentage=80)
session.set_do_like(True, percentage=70)
session.interact_by_users(['user1', 'user2', 'user3'], amount=5, randomize=True, media='Photo')

Interact with users that someone else is following

# Interact with the people that a given user is following
# set_do_comment, set_do_follow and set_do_like are applicable

session.set_user_interact(amount=5, randomize=True, percentage=50, media='Photo')
session.set_do_follow(enabled=False, percentage=70)
session.set_do_like(enabled=False, percentage=70)
session.set_comments(["Cool", "Super!"])
session.set_do_comment(enabled=True, percentage=80)
session.interact_user_following(['natgeo'], amount=10, randomize=True)

Note: simulation takes place while running this feature.

Interact with someone else's followers

# Interact with the people that a given user is following
# set_do_comment, set_do_follow and set_do_like are applicable

session.set_user_interact(amount=5, randomize=True, percentage=50, media='Photo')
session.set_do_follow(enabled=False, percentage=70)
session.set_do_like(enabled=False, percentage=70)
session.set_comments(["Cool", "Super!"])
session.set_do_comment(enabled=True, percentage=80)
session.interact_user_followers(['natgeo'], amount=10, randomize=True)

Note: simulation takes place while running this feature.

Interact on posts at given URLs

Like, comment, follow on the post in the links provided, also can interact the owner of the post
session.interact_by_URL(urls=["some/URL/1", "some/URL/2" "other/URL"], randomize=True, interact=True)

To use, define all of the interaction settings and start the feature right away!

#define interaction settings
session.set_do_like(enabled=True, percentage=94)
session.set_do_comment(enabled=True, percentage=24)
session.set_comments(["Masterful shot", "Chilling!", "Unbelievably great..."])
session.set_do_follow(enabled=True, percentage=44)
session.set_user_interact(amount=6, randomize=True, percentage=72, media='Photo')

#start the feature
session.interact_by_URL(urls=["Fv0J4AJ3Y7r/?taken-at=628416252", "Vb0D4bJgY7r" "Dj0J4VJgY7r"], randomize=True, interact=True)
Parameters:

urls:
Contains the URLs of the posts to be interacted.

  • You can provide URLs in these formats:
    full: "https://www.IG.com/p/Aj0J4bJDY7r/?taken-at=128316221"
    just post link: "https://www.IG.com/p/Aj0J4bJDY7r/"
    just post handle: "Aj0J4bJDY7r/?taken-at=128316221"
    just post ID: "Aj0J4bJDY7r"

randomize:
Shuffles the order of the URLs in the given list before starts to interact.

interact:
Use it if you like to also interact the post owner after doing interactions on the post itself.

Unfollowing

Unfollows the accounts you're following

It will unfollow ~10 accounts and sleep for ~10 minutes and then will continue to unfollow...

There are 4 Unfollow methods available to use:

|> customList |> InstapyFollowed |> nonFollowers |> allFollowing

1 - Unfollow specific users from a CUSTOM list (has 2 tracks- "all" and "nonfollowers"):
when track is "all", it will unfollow all of the users in a given list;

custom_list = ["user_1", "user_2", "user_49", "user332", "user50921", "user_n"]
session.unfollow_users(amount=84, customList=(True, custom_list, "all"), style="RANDOM", unfollow_after=55*60*60, sleep_delay=600)

if track is "nonfollowers", it will unfollow all of the users in a given list WHO are not following you back;

custom_list = ["user_1", "user_2", "user_49", "user332", "user50921", "user_n"]
session.unfollow_users(amount=84, customList=(True, custom_list, "nonfollowers"), style="RANDOM", unfollow_after=55*60*60, sleep_delay=600)
  • PRO: customList method can any kind of iterable container, such as list, tuple or set.

2 - Unfollow the users WHO was followed by InstaPy (has 2 tracks- "all" and "nonfollowers"):
again, if you like to unfollow all of the users followed by InstaPy, use the track- "all";

session.unfollow_users(amount=60, InstapyFollowed=(True, "all"), style="FIFO", unfollow_after=90*60*60, sleep_delay=501)

but if you like you unfollow only the users followed by InstaPy WHO do not follow you back, use the track- "nonfollowers";

session.unfollow_users(amount=60, InstapyFollowed=(True, "nonfollowers"), style="FIFO", unfollow_after=90*60*60, sleep_delay=501)

3 - Unfollow the users WHO do not follow you back:

session.unfollow_users(amount=126, nonFollowers=True, style="RANDOM", unfollow_after=42*60*60, sleep_delay=655)

4 - Just unfollow, regardless of a user follows you or not:

session.unfollow_users(amount=40, allFollowing=True, style="LIFO", unfollow_after=3*60*60, sleep_delay=450)

Parameters (all of these parameters apply to all of the 4 methods available):

style
You can choose unfollow style as "FIFO" (First-Input-First-Output) OR "LIFO" (Last-Input-First-Output) OR "RANDOM".

  • with "FIFO", it will unfollow users in the exact order they are loaded ("FIFO" is the default style unless you change it);
  • with "LIFO" it will unfollow users in the reverse order they were loaded;
  • with "RANDOM" it will unfollow users in the shuffled order;

unfollow_after
By using this, you can unfollow users only after following them certain amount of time.
it will help to provide seamless unfollow activity without the notice of the target user
To use it, just add unfollow_after parameter with the desired time interval, e.g.,

session.unfollow_users(amount=94, InstapyFollowed=(True, "all"), style="RANDOM", unfollow_after=48*60*60, sleep_delay=600)

will unfollow users only after following them 48 hours (2 days).

  • Since unfollow_afters value is in seconds, you can simply give it unfollow_after=3600 to unfollow after 3600 seconds.
    Yeah, values kind of 1*60*60- which is also equal to 1 hour or 3600 seconds, is much more easier to use.

Sure if you like to not use it, give the value of None- unfollow_after=None.

sleep_delay
Sleep delay sets the time it will sleep after every ~10 unfollows (default delay is ~10 minutes).

NOTE: You should know that, in one RUN, unfollow_users feature can take only one method from all 4 above.
That's why, it is best to disable other 3 methods while using a one:

session.unfollow_users(amount=200, customList=(True, ["user1", "user2", "user88", "user200"], "all"), InstapyFollowed=(False, "all"), nonFollowers=False, allFollowing=False, style="FIFO", unfollow_after=22*60*60, sleep_delay=600)

here the unfollow method- customList is used
OR just keep the method you want to use and remove other 3 methods from the feature

session.unfollow_users(amount=200, allFollowing=True, style="FIFO", unfollow_after=22*60*60, sleep_delay=600)

here the unfollow method- alFollowing is used

Don't unfollow active users

# Prevents unfollow followers who have liked one of your latest 5 posts

session.set_dont_unfollow_active_users(enabled=True, posts=5)

Interactions based on the number of followers and/or following a user has

This is used to check the number of followers and/or following a user has and if these numbers either exceed the number set OR does not pass the number set OR if their ratio does not reach desired potency ratio then no further interaction happens
session.set_relationship_bounds(enabled=True,
				 potency_ratio=1.34,
				  delimit_by_numbers=True,
				   max_followers=8500,
				    max_following=4490,
				     min_followers=100,
				      min_following=56)

Use enabled=True to activate this feature, and enabled=False to deactivate it, any time
delimit_by_numbers is used to activate & deactivate the usage of max & min values
potency_ratio accepts values in 2 formats according to your style: positive & negative

  • potency_ratio with POSITIVE values can be used to route interactions to only potential (real) users WHOSE followers count is higher than following count (e.g., potency_ratio = 1.39)
    find desired potency_ratio with this formula: potency_ratio == followers count / following count (use desired counts)

e.g., target user has 5000 followers & 4000 following and you set potency_ratio=1.35.
Now it will not interact with this user, cos the user's relationship ratio is 5000/4000==1.25 and 1.25 is below desired potency_ratio of 1.35

  • potency_ratio with NEGATIVE values can be used to route interactions to only massive followers WHOSE following count is higher than followers count (e.g., potency_ratio = -1.42)
    find desired potency_ratio with this formula: potency_ratio == following count / followers count (use desired counts)

e.g., target user has 2000 followers & 3000 following and you set potency_ratio = -1.7.
Now it will not interact with this user, cos the user's relationship ratio is 3000/2000==1.5 and 1.5 is below desired potency_ratio of 1.7 (note that, negative - sign is only used to determine your style, nothing more)

There are 3 COMBINATIONS available to use:
  • 1. You can use potency_ratio or not (e.g., potency_ratio=None, delimit_by_numbers=True) - will decide only by your pre-defined max & min values regardless of the potency_ratio
session.set_relationship_bounds (enabled=True, potency_ratio=None, delimit_by_numbers=True, max_followers=22668, max_following=10200, min_followers=400, min_following=240)
  • 2. You can use only potency_ratio (e.g., potency_ratio=-1.5, delimit_by_numbers=False) - will decide per potency_ratio regardless of the pre-defined max & min values
session.set_relationship_bounds (enabled=True, potency_ratio=-1.5, delimit_by_numbers=False, max_followers=400701, max_following=90004, min_followers=963, min_following=2310)

apparently, once delimit_by_numbers gets False value, max & min values do not matter

  • 3. You can use both potency_ratio and pre-defined max & min values together (e.g., potency_ratio=2.35, delimit_by_numbers=True) - will decide per potency_ratio & your pre-defined max & min values
session.set_relationship_bounds (enabled=True, potency_ratio=2.35, delimit_by_numbers=True, max_followers=10005, max_following=24200, min_followers=77, min_following=500)

All of the 4 max & min values are able to freely operate, e.g., you may want to only delimit max_followers and min_following (e.g., max_followers=52639, max_following=None, min_followers=None, min_following=2240)

session.set_relationship_bounds (enabled=True, potency_ratio=-1.44, delimit_by_numbers=True, max_followers=52639, max_following=None, min_followers=None, min_following=2240)

Liking based on the number of existing likes a post has

This is used to check the number of existing likes a post has and if it either exceed the maximum value set OR does not pass the minimum value set then it will not like that post
session.set_delimit_liking(enabled=True, max=1005, min=20)

Use enabled=True to activate and enabled=False to deactivate it, any time
max is the maximum number of likes to compare
min is the minimum number of likes to compare

You can use both max & min values OR one of them as you desire, just put the value of None to the one you don't want to check for., e.g.,

session.set_delimit_liking(enabled=True, max=242, min=None)

at this configuration above, it will not check number of the existing likes against minimum value

  • Example:
session.set_delimit_liking(enabled=True, max=500, min=7)

Now, if a post has more existing likes than maximum value of 500, then it will not like that post,
similarly, if that post has less existing likes than the minimum value of 7, then it will not like that post...

Commenting based on the number of existing comments a post has

This is used to check the number of existing comments a post has and if it either exceed the maximum value set OR does not pass the minimum value set then it will not comment on that post
session.set_delimit_commenting(enabled=True, max=32, min=0)

Use enabled=True to activate and enabled=False to deactivate it, any time
max is the maximum number of comments to compare
min is the minimum number of comments to compare

You can use both max & min values OR one of them as you desire, just put the value of None to the one you don't want to check for., e.g.,

session.set_delimit_commenting(enabled=True, max=None, min=4)

at this configuration above, it will not check number of the existing comments against maximum value

  • Example:
session.set_delimit_commenting(enabled=True, max=70, min=5)

Now, if a post has more comments than the maximum value of 70, then it will not comment on that post,
similarly, if that post has less comments than the minimum value of 5, then it will not comment on that post...

Comment by Locations

session.comment_by_locations(['224442573/salton-sea/'], amount=100)
# or
session.comment_by_locations(['224442573'], amount=100)
# or include media entities from top posts section

session.comment_by_locations(['224442573'], amount=5, skip_top_posts=False)

This method allows commenting by locations, without liking posts. To get locations follow instructions in 'Like by Locations'

Like by Locations

session.like_by_locations(['224442573/salton-sea/'], amount=100)
# or
session.like_by_locations(['224442573'], amount=100)
# or include media entities from top posts section

session.like_by_locations(['224442573'], amount=5, skip_top_posts=False)

You can find locations for the like_by_locations function by:

Example:

Like by Tags

# Like posts based on hashtags
session.like_by_tags(['natgeo', 'world'], amount=10)

Like by Tags and interact with user

# Like posts based on hashtags and like 3 posts of its poster
session.set_user_interact(amount=3, randomize=True, percentage=100, media='Photo')
session.like_by_tags(['natgeo', 'world'], amount=10, interact=True)

Like by Feeds

# This is used to perform likes on your own feeds
# amount=100  specifies how many total likes you want to perform
# randomize=True randomly skips posts to be liked on your feed
# unfollow=True unfollows the author of a post which was considered
# inappropriate interact=True visits the author's profile page of a
# certain post and likes a given number of his pictures, then returns to feed

session.like_by_feed(amount=100, randomize=True, unfollow=True, interact=True)

Blacklist Campaign

# Controls your interactions by campaigns.
# ex. this week InstaPy will like and comment interacting by campaign called
# 'soccer', next time InstaPy runs, it will not interact again with users in
# blacklist
# In general, this means that once we turn off the soccer_campaign again, InstaPy
# will have no track of the people it interacted with about soccer.
# This will help you target people only once but several times for different campaigns

session.set_blacklist(enabled=True, campaign='soccer_campaign')
session.set_do_comment(True, percentage=50)
session.set_comments(['Neymar is better than CR7', 'Soccer is cool'])
session.like_by_tags(['soccer', 'cr7', 'neymar'], amount=100, media='Photo')

Smart Hashtags

# Generate smart hashtags based on https://displaypurposes.com ranking,
# banned and spammy tags are filtered out.
# (limit) defines amount limit of generated hashtags by hashtag
# (sort) sort generated hashtag list 'top' and 'random' are available
# (log_tags) shows generated hashtags before use it
# (use_smart_hashtags) activates like_by_tag to use smart hashtags

session.set_smart_hashtags(['cycling', 'roadbike'], limit=3, sort='top', log_tags=True)
session.like_by_tags(amount=10, use_smart_hashtags=True)

Mandatory Words

session.set_mandatory_words(['#food', '#instafood'])

.set_mandatory_words searches the description and owner comments for words and
will like the image if all of those words are in there

Restricting Likes

session.set_dont_like(['#exactmatch', '[startswith', ']endswith', 'broadmatch'])

.set_dont_like searches the description and owner comments for hashtags and
won't like the image if one of those hashtags are in there

You have 4 options to exclude posts from your InstaPy session:

  • words starting with # will match only exact hashtags (e. g. #cat matches #cat, but not #catpic)
  • words starting with [ will match all hashtags starting with your word (e. g. [cat matches #catpic, #caturday and so on)
  • words starting with ] will match all hashtags ending with your word (e. g. ]cat matches #mycat, #instacat and so on)
  • words without these prefixes will match all hashtags that contain your word regardless if it is placed at the beginning, middle or end of the hashtag (e. g. cat will match #cat, #mycat, #caturday, #rainingcatsanddogs and so on)

Ignoring Users

# completely ignore liking images from certain users

session.set_ignore_users(['random_user', 'another_username'])

Ignoring Restrictions

# will ignore the don't like if the description contains
# one of the given words

session.set_ignore_if_contains(['glutenfree', 'french', 'tasty'])

Excluding friends

# will prevent commenting on and unfollowing your good friends (the images will
# still be liked)

session.set_dont_include(['friend1', 'friend2', 'friend3'])

Follow/Unfollow/exclude not working?

If you notice that one or more of the above functionalities are not working as expected - e.g. you have specified:

session.set_do_follow(enabled=True, percentage=10, times=2)

but none of the profiles are being followed - or any such functionality is misbehaving - then one thing you should check is the position/order of such methods in your script. Essentially, all the set_* methods have to be before like_by_tags or like_by_locations or unfollow. This is also implicit in all the exmples and quickstart.py

Bypass Suspicious Login Attempt

If you're having issues with the "we detected an unusual login attempt" message,
you can bypass it setting InstaPy in this way:

session = InstaPy(username=insta_username, password=insta_password, bypass_suspicious_attempt=True)

bypass_suspicious_attempt=True will send the verification code to your
email, and you will be prompted to enter the security code sent to your email.
It will login to your account, now you can set bypass_suspicious_attempt to False
bypass_suspicious_attempt=False and InstaPy will quickly login using cookies.

Relationship tools

Grab Followers of a user

Gets and returns followers of the given user in desired amount, also can save locally
popeye_followers = session.grab_followers(username="Popeye", amount="full", live_match=True, store_locally=True)
##now, `popeye_followers` variable which is a list- holds the `Followers` data of "Popeye" at requested time

Parameters:

username:
A desired username to grab its followers

  • It can be your own username OR a username of some non-private account.

amount:
Defines the desired amount of usernames to grab from the given account

  • amount="full":
    • Grabs followers entirely
  • amount=3089:
    • Grabs 3089 usernames if exist, if not, grabs available amount

live_match:
Defines the method of grabbing Followers data

Knowledge Base:
Every time you grab Followers data in "full" range of any user, it is also gonna be stored in some corner of InstaPy for that session.

  • live_match=False:
    • If the user already do have a Followers data loaded earlier in the same session, it will run a smart data-matching algorithm.
      And there, it will load only the new data from the server and then return a compact result of current data.
      The algorithm works like: load the usernames until hits the ones from the previous query at certain amount.
    • Also if the live_match is False and the user has no any sessional Followers data, then it will load live data at requested range.
    • As a result, live_match=False saves lots of precious time and server requests.
  • live_match=True:
    • It will always load live data from the server at requested range.

store_locally:
Gives the option to save the loaded Followers data in a local storage
The files will be saved into your logs folder, ~/InstaPy/logs/YourOwnUsername/relationship_data/Popeye/followers/ directory.
Sample filename 14-06-2018~full~6874.json:

  • 14-06-2018 means the time of the data acquisition.
  • "full" means the range of the data acquisition;
    If the data is requested at the range else than "full", it will write that range.
  • 6874 means the count of the usernames retrieved.
  • json is the filetype and the data is stored as a list in it.

There are several use cases of this tool for various purposes.
E.g., inside your quickstart script, you can do something like this:

#get followers of "Popeye" and "Cinderella"
popeye_followers = session.grab_followers(username="Popeye", amount="full", live_match=True, store_locally=True)
sleep(600)
cinderella_followers = session.grab_followers(username="Cinderella", amount="full", live_match=True, store_locally=True)

#find the users following "Popeye" WHO also follow "Cinderella" :D
popeye_cinderella_followers = [follower for follower in popeye_followers if follower in cinderella_followers]

PROs:

You can use this tool to take a backup of your or any other user's current followers.

Grab Following of a user

Gets and returns following of the given user in desired amount, also can save locally
lazySmurf_following = session.grab_following(username="lazy.smurf", amount="full", live_match=True, store_locally=True)
##now, `lazySmurf_following` variable which is a list- holds the `Following` data of "lazy.smurf" at requested time

Parameters:

username:
A desired username to grab its following

  • It can be your own username OR a username of some non-private account.

amount:
Defines the desired amount of usernames to grab from the given account

  • amount="full":
    • Grabs following entirely
  • amount=3089:
    • Grabs 3089 usernames if exist, if not, grabs available amount

live_match:
Defines the method of grabbing Following data

Knowledge Base:
Every time you grab Following data in "full" range of any user, it is also gonna be stored in some corner of InstaPy for that session.

  • live_match=False:
    • If the user already do have a Following data loaded earlier in the same session, it will run a smart data-matching algorithm.
      And there, it will load only the new data from the server and then return a compact result of current data.
      The algorithm works like: load the usernames until hits the ones from the previous query at certain amount.
    • Also if the live_match is False and the user has no any sessional Following data, then it will load live data at requested range.
    • As a result, live_match=False saves lots of precious time and server requests.
  • live_match=True:
    • It will always load live data from the server at requested range.

store_locally:
Gives the option to save the loaded Following data in a local storage
The files will be saved into your logs folder, ~/InstaPy/logs/YourOwnUsername/relationship_data/lazy.smurf/following/ directory.
Sample filename 15-06-2018~full~2409.json:

  • 15-06-2018 means the time of the data acquisition.
  • "full" means the range of the data acquisition;
    If the data is requested at the range else than "full", it will write that range.
  • 2409 means the count of the usernames retrieved.
  • json is the filetype and the data is stored as a list in it.

There are several use cases of this tool for various purposes.
E.g., inside your quickstart script, you can do something like this:

##as we know that all lazy Smurf care is to take some good rest, so by mistake, he can follow somebody WHOM Gargamel also follow!
#so let's find it out to save Smurfs from troubles! :D

#get following of "lazy.smurf" and "Gargamel"
lazySmurf_following = session.grab_following(username="lazy.smurf", amount="full", live_match=True, store_locally=True)
sleep(600)
gargamel_following = session.grab_following(username="Gargamel", amount="full", live_match=True, store_locally=True)

#find the users "lazy.smurf" is following WHOM "Gargamel" also follow :D
lazySmurf_gargamel_following = [following for following in lazySmurf_following if following in gargamel_following]

PROs:

You can use this tool to take a backup of your or any other user's current following.

Pick Unfollowers of a user

Compares the followers stored in a local storage against current followers and returns absent followers
all_unfollowers, active_unfollowers = session.pick_unfollowers(username="Bernard_bear", compare_by="month", compare_track="first", live_match=True, store_locally=True, print_out=True)
##now, `all_unfollowers` and `all_unfollowers` variables which are lists- hold the `Unfollowers` data of "Bernard_bear" at requested time
#`all_unfollowers` holds all of the unfollowers WHILST `active_unfollowers` holds the unfollowers WHOM "Bernard_bear" is still following

Parameters:

username:
A desired username to pick its unfollowers

  • It can be your own username OR a username of some non-private account.

compare_by:
Defines the compare point to pick unfollowers

  • Available values are:

    • "latest" chooses the very latest record from the existing records in the local folder
    • "earliest" chooses the very earliest record from the existing records in the local folder

    The compare points below needs a compare track defined, too:

    • "day" chooses from the existing records of today in the local folder
    • "month" chooses from the existing records of this month in the local folder
    • "year" chooses from the existing records of this year in the local folder

compare_track:
Defines the track to choose a file to compare for "day", "month" and "year" compare points

  • Available values are:
    • "first" selects the first record from the given day, month or year
    • "median" selects the median (the one in the middle) record from the given day, month or year
    • "last" selects the last record from the given day, month or year

live_match:
Defines the method of grabbing new Followers data to compare with existing data

Knowledge Base:
Every time you grab Followers data in "full" range of any user, it is also gonna be stored in some corner of InstaPy for that session.

  • live_match=False:
    • If the user already do have a Followers data loaded earlier in the same session, it will run a smart data-matching algorithm.
      And there, it will load only the new data from the server and then return a compact result of current data.
      The algorithm works like: load the usernames until hits the ones from the previous query at certain amount.
    • Also if the live_match is False and the user has no any sessional Followers data, then it will load live data at requested range.
    • As a result, live_match=False saves lots of precious time and server requests.
  • live_match=True:
    • It will always load live data from the server at requested range.

store_locally:
Gives the option to save the loaded Unfollowers data in a local storage
There will be 2 files saved in their own directory:

  • all_unfollowers:
    • Will store all of the unfollowers in there
    • Its files will be saved at logs folder, ~/InstaPy/logs/YourOwnUsername/relationship_data/Bernard_bear/unfollowers/all_unfollowers/ directory.
  • active_unfollowers:
    • Will store only the unfollowers WHOM you are currently following.
    • Its files will be saved at logs folder, ~/InstaPy/logs/YourOwnUsername/relationship_data/Bernard_bear/unfollowers/active_unfollowers/ directory.

Sample filename 03-06-2018~all~75.json:

  • 03-06-2018 means the time of the data acquisition.
  • "all" means that it is all of the unfollowers data;
    *"active" unfollowers files will have "active" written in there.
  • 75 means the count of the unfollowers retrieved.
  • json is the filetype and the data is stored as a list in it.

print_out:
Use this parameter if you would like the see those unfollowers printed into the console output right after finding them.

There are several use cases of this tool for various purposes.

  • You can the get the unfollowers you have had from the start of the year, or from the middle of the year or from the start of the month, etc.
    And then, e.g. do some useful analysis with that generated unfollowers data.
  • And you can also find the unfollowers to block them all.
  • Also, you can unfollow back those active unfollowers right away:
#find all of the active unfollowers of Bernard bear
all_unfollowers, active_unfollowers = session.pick_unfollowers(username="Bernard_bear", compare_by="earliest", compare_track="first", live_match=True, store_locally=True, print_out=True)
sleep(200)
#let's unfollow them immediately cos Bernard will be angry if heards about those unfollowers! :D
session.unfollow_users(amount=len(active_unfollowers), customList=(True, active_unfollowers, "all"), style="RANDOM", unfollow_after=None, sleep_delay=600)

Pick Nonfollowers of a user

Compares the Followers data against Following data of a user and returns the Nonfollowers data
scoobyDoo_nonfollowers = session.pick_nonfollowers(username="ScoobyDoo", live_match=True, store_locally=True)
#now, `scoobyDoo_nonfollowers` variable which is a list- holds the `Nonfollowers` data of "ScoobyDoo" at requested time

Parameters:

username:
A desired username to pick its nonfollowers

  • It can be your own username OR a username of some non-private account.

live_match:
Defines the method of grabbing Followers and Following data to compare with each other to find nonfollowers

Knowledge Base:
Every time you grab Followers and/or Following data in "full" range of any user, it is also gonna be stored in some corner of InstaPy for that session.

  • live_match=False:
    • If the user already do have a Followers and/or Following data loaded earlier in the same session, it will run a smart data-matching algorithm.
      And there, it will load only the new data from the server and then return a compact result of current data.
      The algorithm works like: load the usernames until hits the ones from the previous query at certain amount.
    • Also if the live_match is False and the user has no any sessional Followers and/or Following data, then it will load live data at requested range.
    • As a result, live_match=False saves lots of precious time and server requests.
  • live_match=True:
    • It will always load live data from the server at requested range.

store_locally:
Gives the option to save the loaded Nonfollowers data in a local storage
The files will be saved into your logs folder, ~/InstaPy/logs/YourOwnUsername/relationship_data/ScoobyDoo/nonfollowers/ directory.
Sample filename 01-06-2018~[5886-3575]~2465.json:

  • 01-06-2018 means the time of the data acquisition.
  • 5886 means the count of the followers retrieved.
  • 3575 means the count of the following retrieved.
  • 2465 means the count of the nonfollowers picked.
  • json is the filetype and the data is stored as a list in it.

There are several use cases of this tool for various purposes.

  • You can get the nonfollowers of several users and then do analysis.
    • e.g., in this example Scooby Do used it like this:
    ##Scooby Doo always wonders a lot and this time he wonders if there are people Shaggy is following WHO do not follow him back...
    shaggy_nonfollowers = session.pick_nonfollowers(username="Shaggy", live_match=True, store_locally=True)
    
    #now Scooby Doo will tell his friend Shaggy about this, who knows, maybe Shaggy will unfollow them all or even add to block :D
    

Pick Fans of a user

Returns Fans data- all of the accounts who do follow the user WHOM user itself do not follow back
smurfette_fans = session.pick_fans(username="Smurfette", live_match=True, store_locally=True)
#now, `smurfette_fans` variable which is a list- holds the `Fans` data of "Smurfette" at requested time

Parameters:

username:
A desired username to pick its fans

  • It can be your own username OR a username of some non-private account.

live_match:
Defines the method of grabbing Followers and Following data to compare with each other to find fans

Knowledge Base:
Every time you grab Followers and/or Following data in "full" range of any user, it is also gonna be stored in some corner of InstaPy for that session.

  • live_match=False:
    • If the user already do have a Followers and/or Following data loaded earlier in the same session, it will run a smart data-matching algorithm.
      And there, it will load only the new data from the server and then return a compact result of current data.
      The algorithm works like: load the usernames until hits the ones from the previous query at certain amount.
    • Also if the live_match is False and the user has no any sessional Followers and/or Following data, then it will load live data at requested range.
    • As a result, live_match=False saves lots of precious time and server requests.
  • live_match=True:
    • It will always load live data from the server at requested range.

store_locally:
Gives the option to save the loaded Fans data in a local storage
The files will be saved into your logs folder, ~/InstaPy/logs/YourOwnUsername/relationship_data/Smurfette/fans/ directory.
Sample filename 05-06-2018~[4591-2575]~3477.json:

  • 05-06-2018 means the time of the data acquisition.
  • 4591 means the count of the followers retrieved.
  • 2575 means the count of the following retrieved.
  • 3477 means the count of the fans picked.
  • json is the filetype and the data is stored as a list in it.

There are several use cases of this tool for various purposes.

  • You can get the fans of several users and then do analysis.
    • e.g., in this example Smurfette used it like this:
    ##Smurfette is so famous in the place and she wonders which smurfs is following her WHOM she doesn't even know of :D
    smurfette_fans = session.pick_fans(username="Smurfette", live_match=True, store_locally=True)
    #and now, maybe she will follow back some of the smurfs whom she may know :P
    

Pick Mutual Following of a user

Returns Mutual Following data- all of the accounts who do follow the user WHOM user itself also do follow back
Winnie_mutualFollowing = session.pick_mutual_following(username="WinnieThePooh", live_match=True, store_locally=True)
#now, `Winnie_mutualFollowing` variable which is a list- holds the `Mutual Following` data of "WinnieThePooh" at requested time

Parameters:

username:
A desired username to pick its mutual following

  • It can be your own username OR a username of some non-private account.

live_match:
Defines the method of grabbing Followers and Following data to compare with each other to find mutual following

Knowledge Base:
Every time you grab Followers and/or Following data in "full" range of any user, it is also gonna be stored in some corner of InstaPy for that session.

  • live_match=False:
    • If the user already do have a Followers and/or Following data loaded earlier in the same session, it will run a smart data-matching algorithm.
      And there, it will load only the new data from the server and then return a compact result of current data.
      The algorithm works like: load the usernames until hits the ones from the previous query at certain amount.
    • Also if the live_match is False and the user has no any sessional Followers and/or Following data, then it will load live data at requested range.
    • As a result, live_match=False saves lots of precious time and server requests.
  • live_match=True:
    • It will always load live data from the server at requested range.

store_locally:
Gives the option to save the loaded Mutual Following data in a local storage
The files will be saved into your logs folder, ~/InstaPy/logs/YourOwnUsername/relationship_data/WinnieThePooh/mutual_following/ directory.
Sample filename 11-06-2018~[3872-2571]~1120.json:

  • 11-06-2018 means the time of the data acquisition.
  • 3872 means the count of the followers retrieved.
  • 2571 means the count of the following retrieved.
  • 1120 means the count of the mutual following picked.
  • json is the filetype and the data is stored as a list in it.

There are several use cases of this tool for various purposes.

  • You can get the mutual following of several users and then do analysis.
    • e.g., in this example Winnie The Pooh used it like this:
    #Winnie The Pooh is a very friendly guy and almost everybody follows him back, but he wants to be sure about it :D
    Winnie_mutual_following = session.pick_mutual_following(username="WinnieThePooh", live_match=True, store_locally=True)
    ##now, he will write a message to his mutual followers to help him get a new honey pot :>
    

Use a proxy

You can use InstaPy behind a proxy by specifying server address and port

session = InstaPy(username=insta_username, password=insta_password, proxy_address='8.8.8.8', proxy_port=8080)

To use proxy with authentication you should firstly generate proxy chrome extension (works only with Chrome and headless_browser=False).

from proxy_extension import create_proxy_extension

proxy = 'login:[email protected]:port'
proxy_chrome_extension = create_proxy_extension(proxy)

session = InstaPy(username=insta_username, password=insta_password, proxy_chrome_extension=proxy_chrome_extension, nogui=True)

Switching to Firefox

Chrome is the default browser, but InstaPy provides support for Firefox as well.

session = InstaPy(username=insta_username, password=insta_password, use_firefox=True)

Emoji Support

To use an emoji just add an u in front of the opening apostrophe:

session.set_comments([u'This post is 🔥',u'More emojis are always better 💯',u'I love your posts 😍😍😍']);
# or
session.set_comments([u'Emoji text codes are also supported :100: :thumbsup: :thumbs_up: \u2764 💯💯']);

Emoji text codes are implemented using 2 different naming codes. A complete list of emojis codes can be found on the Python Emoji Github, but you can use the alternate shorted naming scheme found for Emoji text codes here. Note: Every Emoji has not been tested. Please report any inconsistencies.

Legacy Emoji Support

You can still use Unicode strings in your comments, but there are some limitations.

  1. You can use only Unicode characters with no more than 4 characters and you have to use the unicode code (e. g. \u1234). You find a list of emoji with unicode codes on Wikipedia, but there is also a list of working emoji in /assets

  2. You have to convert your comment to Unicode. This can safely be done by adding an u in front of the opening apostrophe: u'\u1234 some comment'

Clarifai ImageAPI

Note: Head over to https://developer.clarifai.com/signup/ and create a free account, once you’re logged in go to https://developer.clarifai.com/account/applications/ and create a new application. You can find the client ID and Secret there. You get 5000 API-calls free/month.

If you want the script to get your CLARIFAI_API_KEY for your environment, you can do:

export CLARIFAI_API_KEY="<API KEY>"

Example with Imagecontent handling

session.set_do_comment(True, percentage=10)
session.set_comments(['Cool!', 'Awesome!', 'Nice!'])
session.set_use_clarifai(enabled=True)
session.clarifai_check_img_for(['nsfw'])
session.clarifai_check_img_for(['food', 'lunch', 'dinner'], comment=True, comments=['Tasty!', 'Nice!', 'Yum!'])

session.end()

Enabling Imagechecking

# default enabled=False , enables the checking with the clarifai api (image
# tagging) if secret and proj_id are not set, it will get the environment
# variables 'CLARIFAI_API_KEY'

session.set_use_clarifai(enabled=True, api_key='xxx')

Filtering inappropriate images

# uses the clarifai api to check if the image contains nsfw content
# -> won't comment if image is nsfw

session.clarifai_check_img_for(['nsfw'])

Specialized comments for images with specific content

# checks the image for keywords food and lunch, if both are found,
# comments with the given comments. If full_match is False (default), it only
# requires a single tag to match Clarifai results.

session.clarifai_check_img_for(['food', 'lunch'], comment=True, comments=['Tasty!', 'Yum!'], full_match=True)
Check out https://clarifai.com/demo to see some of the available tags.

Running on a Server

Use the nogui parameter to interact with virtual display

session = InstaPy(username='test', password='test', nogui=True)

Running on a Headless Browser

Note: Chrome only! Must use chromedriver v2.9+

Use headless_browser parameter to run the bot via the CLI. Works great if running the scripts locally, or to deploy on a server. No GUI, less CPU intensive. Example

session = InstaPy(username='test', password='test', headless_browser=True)

Running Multiple Accounts

Use the multi_logs parameter if you are going to use multiple accounts and want the log files stored per account.

session = InstaPy(username='test', password='test', multi_logs=True)

Running with Docker microservices manual

Docker allows very easy and fast run of the instapy bot without any pain and tears.

0. Preparations

Install docker from the official website https://www.docker.com/

Install VNC viewer if you do not have one. For windows, a good program is http://www.tightvnc.com/

1. Set your instagram login and password

Open docker_quickstart.py and fill the quotes after insta_username and insta_password with your credentials.

Don't forget to make other changes for the file as you want to. Read the documentation above for info.

2. Run and build containers with docker-compose

First you need to open your terminal, move to the root folder (usually with the cd command) of instapy project and then type:

docker-compose up -d --build

That's all! At this step, you are already successfully running your personal bot!

3. See what your bot can do right now

Run your VNC viewer, and type address and port localhost:5900. The password is secret.

4. Stop your instapy bot

Use your terminal again, type in the same window:

docker-compose down

Your bot is stopped!

5. Further steps

Those are just basic steps to run instapy bot on your PC with docker. There are other docker-compose settings file in the root of project.

Development environment to run, test and debug by SSH

Use it to help us with development and test instapy! docker-dev.yml file.

docker-compose -f docker-dev.yml up -d

After striking this command, you can access your bot by VNC on the adress localhost:5901, the password is secret.

But there is more! There is a fully accessible bash console with all code mounted at the path /code. When you hack some files they are dynamically updated inside your container.

To access yor container console to run bot type localhost:22 in your favorite ssh client. The User is root and the password is root also.

Run in production without opened VNC port

Suitable to run in a remote server. Attention! You can not view what happened through VNC on this configuration docker-prod.yml file.

docker-compose -f docker-prod.yml up -d

Running all-in-one with Docker (obsolete)

1. Build the Image

First you need to build the image by running this in the Terminal:

docker build -t instapy ./docker_conf/all_in_one

Make sure to use the nogui feature:

# you can use the nogui parameter to use a virtual display

session = InstaPy(username='test', password='test', nogui=True)

2. Run in a Container

After the build succeeds, you can simply run the container with:

docker run --name=instapy -e INSTA_USER=<your-user> -e INSTA_PW=<your-pw> -d --rm instapy

Automate InstaPy

Windows Task Scheduler

You can use Window's built in Task Scheduler to automate InstaPy, using a variety of trigger types: time, login, computer idles, etc. To schedule a simple daily run of an Instapy script follow the below directions

  1. Open Windows Task Scheduler
  2. Select "Create Basic Task"
  3. Fill out "Name" and "Description" as desired, click "Next"
  4. On "Trigger" screen select how frequently to run, click "Next" (Frequency can be modified later)
  5. On "Daily" screen, hit "Next"
  6. "Action Screen" select "Start a program" and then click "Next"
  7. "Program/script" enter the path, or browse to select the path to python. (How to find python path on Windows)
  8. "Add arguments" input the InstaPy script path you wish to run. (Example: C:\Users\USER_NAME\Documents\GitHub\InstaPy\craigquick.py)
  9. "Start in" input Instapy install location (Example: C:\Users\USER_NAME\Documents\GitHub\InstaPy). Click "Next"
  10. To finish the process, hit "Finish"

cron

You can add InstaPy to your crontab, so that the script will be executed regularly. This is especially useful for servers, but be sure not to break Instagrams follow and like limits.

# Edit or create a crontab
crontab -e
# Add information to execute your InstaPy regularly.
# With cd you navigate to your InstaPy folder, with the part after &&
# you execute your quickstart.py with python. Make sure that those paths match
# your environment.
45 */4 * * * cd /home/user/InstaPy && /usr/bin/python ./quickstart.py

Schedule

Schedule is an in-process scheduler for periodic jobs that uses the builder pattern for configuration. Schedule lets you run Python functions periodically at pre-determined intervals using a simple, human-friendly syntax.

pip install schedule
from instapy import InstaPy
import schedule
import time

def job():
    try:
        session = InstaPy(selenium_local_session=False) # Assuming running in Compose
        session.set_selenium_remote_session(selenium_url='http://selenium:4444/wd/hub')
        session.login()
        session.set_do_comment(enabled=True, percentage=20)
        session.set_comments(['Well done!'])
        session.set_do_follow(enabled=True, percentage=5, times=2)
        session.like_by_tags(['love'], amount=100, media='Photo')
        session.end()
    except:
        import traceback
        print(traceback.format_exc())

schedule.every().day.at("6:35").do(job)
schedule.every().day.at("16:22").do(job)

while True:
    schedule.run_pending()
    time.sleep(1)

Extra Information

How not to be banned?

Built-in delays prevent your account from getting banned. (Just make sure you don't like 1000s of post/day)

Chrome Browser

64-bit system is a requirement for current versions of chrome browser.

Simulation

During indirect data retrieval, simulation happens to provide a genuine activity flow triggered by a wise algorithm.

To turn off simulation or to decrease its occurrence frequency, use set_simulation setting:

#use the value of `False` to permanently turn it off
session.set_simulation(enabled=False)

#use a desired occurrence percentage
session.set_simulation(enabled=True, percentage=66)

GitHub