Comment

Post comment, viewing, like and unlike comments

Method	Return	Description
media_comment(media_id: str, text: str, replied_to_comment_id: Optional[int] = None)	Comment	Add a new comment to media or reply to an existing comment
media_comments(media_id: str, amount: int = 20)	List[Comment]	Get comments for media; pass amount=0 to keep paginating until exhaustion
media_comments_chunk(media_id: str, max_amount: int, min_id: str = None)	Tuple[List[Comment], str]	Get a paginated chunk of comments and the next min_id cursor
media_comments_v1(media_id: str, amount: int = 20)	List[Comment]	Get comments through the private mobile comments endpoint
media_comments_v1_chunk(media_id: str, min_id: str = “”, max_id: str = “”)	Tuple[List[Comment], str, str]	Get one private comments page and both cursors
media_stream_comments_v1_chunk(media_id: str, min_id: str = “”, max_id: str = “”)	Tuple[List[Comment], str, str]	Get one streamed comments page and both cursors
media_comments_gql(media_pk: str, amount: int = 50, max_requests: int = 0)	List[dict]	Get comments through the web GraphQL doc_id endpoint
media_comments_gql_chunk(media_pk: str, end_cursor: str = “”)	Tuple[List[dict], str]	Get one web GraphQL comments page
media_comments_threaded_gql(media_pk: str, comment_pk: str, amount: int = 0)	List[dict]	Get threaded replies through the web GraphQL doc_id endpoint
media_comments_threaded_gql_chunk(media_pk: str, comment_pk: str, end_cursor: str = “”)	Tuple[List[dict], str]	Get one threaded GraphQL comments page
media_comment_infos(media_ids: List[str])	dict	Bulk-fetch comment summaries for media ids
media_comment_replies(media_id: str, comment_id: str, amount: int = 0)	List[Comment]	Get replies for a parent media comment; pass amount=0 to keep paginating until exhaustion
media_comment_replies_chunk(media_id: str, comment_id: str, max_amount: int, min_id: str = None)	Tuple[List[Comment], str]	Get a paginated chunk of replies and the next child cursor
media_check_offensive_comment(media_id: str, text: str)	bool	Ask Instagram whether a comment text is considered offensive
media_check_offensive_comment_v2(media_id: str, comment: str)	dict	Lighter variant of media_check_offensive_comment — same endpoint without with_action_data wrapping; returns the raw payload so callers can inspect category / confidence flags beyond is_offensive
comment_like(comment_pk: int, revert: bool = False)	bool	Like a comment
comment_unlike(comment_pk: int)	bool	Unlike a comment
comment_pin(media_id: str, comment_pk: int, revert: bool = False)	bool	Pin a comment on your media
comment_unpin(media_id: str, comment_pk: int)	bool	Unpin a previously pinned comment
comment_bulk_delete(media_id: str, comment_pks: List[int])	bool	Delete one or more comments from your media
comment_likers_gql(comment_pk: str, amount: int = 0)	List[dict]	Get comment likers through public GraphQL
comment_likers_gql_chunk(comment_pk: str, end_cursor: str = “”)	Tuple[List[dict], str]	Get one public GraphQL comment-likers page

Example:

>>> from instagrapi import Client

>>> cl = Client()
>>> cl.login(USERNAME, PASSWORD)

>>> media_id = cl.media_id(cl.media_pk_from_url('https://www.instagram.com/p/ByU3LAslgWY/'))

>>> comment = cl.media_comment(media_id, "Test comment")
>>> comment.dict()
{'pk': 17926777897585108,
 'text': 'Test comment',
 'user': {'pk': 1903424587,
  'username': 'example',
  'full_name': 'Example Example',
  'profile_pic_url': HttpUrl('https://scontent-hel3-1.cdninstagram.com/v/t51.2885-19/s150x150/156689363_269505058076642_6448820957073669709_n.jpg?tp=1&_nc_ht=scontent-hel3-1.cdninstagram.com&_nc_ohc=EtzrL0pAdg8AX9pE_wN&edm=ABQSlwABAAAA&ccb=7-4&oh=e04d45b7651140e7fef61b1f67f1f408&oe=60C65AD1&_nc_sid=b2b2bd', scheme='https', host='scontent-hel3-1.cdninstagram.com', tld='com', host_type='domain', path='/v/t51.2885-19/s150x150/156689363_269505058076642_6448820957073669709_n.jpg', query='tp=1&_nc_ht=scontent-hel3-1.cdninstagram.com&_nc_ohc=EtzrL0pAdg8AX9pE_wN&edm=ABQSlwABAAAA&ccb=7-4&oh=e04d45b7651140e7fef61b1f67f1f408&oe=60C65AD1&_nc_sid=b2b2bd'),
  'stories': []},
 'created_at_utc': datetime.datetime(2021, 5, 15, 14, 50, 3, tzinfo=datetime.timezone.utc),
 'content_type': 'comment',
 'status': 'Active',
 'has_liked': None,
 'like_count': None}

>>> comment = cl.media_comment(media_id, "Test comment 2", replied_to_comment_id=comment.pk)
>>> comment.dict()
{'pk': 17926777897585109,
 'text': 'Test comment 2',
 'user': {'pk': 1903424587,
  'username': 'example',
  'full_name': 'Example Example',
  'profile_pic_url': HttpUrl('https://scontent-hel3-1.cdninstagram.com/v/t51.2885-19/s150x150/156689363_269505058076642_6448820957073669709_n.jpg?tp=1&_nc_ht=scontent-hel3-1.cdninstagram.com&_nc_ohc=EtzrL0pAdg8AX9pE_wN&edm=ABQSlwABAAAA&ccb=7-4&oh=e04d45b7651140e7fef61b1f67f1f408&oe=60C65AD1&_nc_sid=b2b2bd', scheme='https', host='scontent-hel3-1.cdninstagram.com', tld='com', host_type='domain', path='/v/t51.2885-19/s150x150/156689363_269505058076642_6448820957073669709_n.jpg', query='tp=1&_nc_ht=scontent-hel3-1.cdninstagram.com&_nc_ohc=EtzrL0pAdg8AX9pE_wN&edm=ABQSlwABAAAA&ccb=7-4&oh=e04d45b7651140e7fef61b1f67f1f408&oe=60C65AD1&_nc_sid=b2b2bd'),
  'stories': []},
 'created_at_utc': datetime.datetime(2021, 5, 15, 14, 50, 3, tzinfo=datetime.timezone.utc),
 'content_type': 'comment',
 'status': 'Active',
 'has_liked': None,
 'like_count': None}

>>> comments = cl.media_comments(media_id)
>>> comments[0].dict()
 {'pk': 17926777897585108,
 'text': 'Test comment',
 'user': {'pk': 1903424587,
  'username': 'example',
  'full_name': 'Example Example',
  'profile_pic_url': HttpUrl('https://scontent-hel3-1.cdninstagram.com/v/t51.2885-19/s150x150/156689363_269505058076642_6448820957073669709_n.jpg?tp=1&_nc_ht=scontent-hel3-1.cdninstagram.com&_nc_ohc=EtzrL0pAdg8AX9pE_wN&edm=AId3EpQBAAAA&ccb=7-4&oh=e3fbafcdb63cec3535004e85eb3397ae&oe=60C65AD1&_nc_sid=705020', scheme='https', host='scontent-hel3-1.cdninstagram.com', tld='com', host_type='domain', path='/v/t51.2885-19/s150x150/156689363_269505058076642_6448820957073669709_n.jpg', query='tp=1&_nc_ht=scontent-hel3-1.cdninstagram.com&_nc_ohc=EtzrL0pAdg8AX9pE_wN&edm=AId3EpQBAAAA&ccb=7-4&oh=e3fbafcdb63cec3535004e85eb3397ae&oe=60C65AD1&_nc_sid=705020'),
  'stories': []},
 'created_at_utc': datetime.datetime(2021, 5, 15, 14, 50, 3, tzinfo=datetime.timezone.utc),
 'content_type': 'comment',
 'status': 'Active',
 'has_liked': False,
 'like_count': 0}

>>> (comments_part1, next_min_id) = cl.media_comments_chunk(media_id, 100)
>>> next_min_id
QVFBQmZCa1dxaFB5eFpBY2luVFMwLWdmN2ZCcUV6OF9hQWlIQk12ZWZqUlctZ2pOa1J5YjJ6bFY5Q1doSGNuUmpxSS1DdXRvZ0NLemJrR1hXd2p0dS1JMg==
>>> (comments_part2, next_min_id) = cl.media_comments_chunk(media_id, 100, next_min_id)
>>> next_min_id
QVFEbHpIWmpFc3BNUkgzUFVuOGZOQlhDQ1hHeWlVWHlJSnBhb2FHbFB3YlJtNThnOUlrd01JUWdKRmRwZTRpWWU0bnZmX3VMNHlwcDBkWTJpZjQ2NE9SeQ==

>>> parent_comment = cl.media_comments(media_id)[0]
>>> replies = cl.media_comment_replies(media_id, parent_comment.pk)
>>> replies[0].dict()
{'pk': 17926777897585110,
 'text': 'Reply text',
 'user': {'pk': 1903424587,
  'username': 'example',
  'full_name': 'Example Example',
  'profile_pic_url': None},
 'created_at_utc': datetime.datetime(2021, 5, 15, 14, 51, 3, tzinfo=datetime.timezone.utc),
 'content_type': 'comment',
 'status': 'Active',
 'replied_to_comment_id': '17926777897585108',
 'has_liked': False,
 'like_count': 0}

>>> cl.media_check_offensive_comment(media_id, "Some draft text")
False

>>> cl.comment_like(17926777897585108)
True

>>> cl.comment_unlike(17926777897585108)
True

>>> cl.comment_bulk_delete(media_id, [17926777897585108])
True

Notes:

• media_comments() fetches both regular and headload comment pages until amount is reached.
• media_comments_chunk() is the better choice when you want to store and resume the server cursor manually.
• media_comment_replies() fetches inline_child_comments for a parent comment and paginates with the returned child cursor.
• comment_pin() / comment_unpin() only work on media owned by the authenticated account.
• Reply creation is supported through replied_to_comment_id; reply retrieval is supported through media_comment_replies().
• Comment creation is a write action and can still trigger Instagram spam or trust checks. Reuse saved sessions, keep volume low on new accounts, and stop when Instagram returns feedback/challenge responses.