Implementation of X/Twitter v1, v2, and GraphQL APIs.
Project description
Implementation of X/Twitter v1, v2, and GraphQL APIs.
Table of Contents
Installation
pip install twitter-api-client
Automation
from twitter.account import Account
## sign-in with credentials
email, username, password = ..., ..., ...
account = Account(email, username, password)
## or, resume session using cookies
# account = Account(cookies={"ct0": ..., "auth_token": ...})
## or, resume session using cookies (JSON file)
# account = Account(cookies='twitter.cookies')
account.tweet('test 123')
account.untweet(123456)
account.retweet(123456)
account.unretweet(123456)
account.reply('foo', tweet_id=123456)
account.quote('bar', tweet_id=123456)
account.schedule_tweet('schedule foo', 1681851240)
account.unschedule_tweet(123456)
account.tweet('hello world', media=[
{'media': 'test.jpg', 'alt': 'some alt text', 'tagged_users': [123]},
{'media': 'test.jpeg', 'alt': 'some alt text', 'tagged_users': [123]},
{'media': 'test.png', 'alt': 'some alt text', 'tagged_users': [123]},
{'media': 'test.jfif', 'alt': 'some alt text', 'tagged_users': [123]},
])
account.schedule_tweet('foo bar', '2023-04-18 15:42', media=[
{'media': 'test.gif', 'alt': 'some alt text'},
])
account.schedule_reply('hello world', '2023-04-19 15:42', tweet_id=123456, media=[
{'media': 'test.gif', 'alt': 'some alt text'},
])
account.dm('my message', [1234], media='test.jpg')
account.create_poll('test poll 123', ['hello', 'world', 'foo', 'bar'], 10080)
# tweets
account.like(123456)
account.unlike(123456)
account.bookmark(123456)
account.unbookmark(123456)
account.pin(123456)
account.unpin(123456)
# users
account.follow(1234)
account.unfollow(1234)
account.mute(1234)
account.unmute(1234)
account.enable_notifications(1234)
account.disable_notifications(1234)
account.block(1234)
account.unblock(1234)
# user profile
account.update_profile_image('test.jpg')
account.update_profile_banner('test.png')
account.update_profile_info(name='Foo Bar', description='test 123', location='Victoria, BC')
# topics
account.follow_topic(111)
account.unfollow_topic(111)
# lists
account.create_list('My List', 'description of my list', private=False)
account.update_list(222, 'My Updated List', 'some updated description', private=False)
account.update_list_banner(222, 'test.png')
account.delete_list_banner(222)
account.add_list_member(222, 1234)
account.remove_list_member(222, 1234)
account.delete_list(222)
account.pin_list(222)
account.unpin_list(222)
# refresh all pinned lists in this order
account.update_pinned_lists([222, 111, 333])
# unpin all lists
account.update_pinned_lists([])
# get timelines
timeline = account.home_timeline()
latest_timeline = account.home_latest_timeline(limit=500)
# get bookmarks
bookmarks = account.bookmarks()
# get DM inbox metadata
inbox = account.dm_inbox()
# get DMs from all conversations
dms = account.dm_history()
# get DMs from specific conversations
dms = account.dm_history(['123456-789012', '345678-901234'])
# search DMs by keyword
dms = account.dm_search('test123')
# delete entire conversation
account.dm_delete(conversation_id='123456-789012')
# delete (hide) specific DM
account.dm_delete(message_id='123456')
# get all scheduled tweets
scheduled_tweets = account.scheduled_tweets()
# delete a scheduled tweet
account.delete_scheduled_tweet(12345678)
# get all draft tweets
draft_tweets = account.draft_tweets()
# delete a draft tweet
account.delete_draft_tweet(12345678)
# delete all scheduled tweets
account.clear_scheduled_tweets()
# delete all draft tweets
account.clear_draft_tweets()
# example configuration
account.update_settings({
"address_book_live_sync_enabled": False,
"allow_ads_personalization": False,
"allow_authenticated_periscope_requests": True,
"allow_dm_groups_from": "following",
"allow_dms_from": "following",
"allow_location_history_personalization": False,
"allow_logged_out_device_personalization": False,
"allow_media_tagging": "none",
"allow_sharing_data_for_third_party_personalization": False,
"alt_text_compose_enabled": None,
"always_use_https": True,
"autoplay_disabled": False,
"country_code": "us",
"discoverable_by_email": False,
"discoverable_by_mobile_phone": False,
"display_sensitive_media": False,
"dm_quality_filter": "enabled",
"dm_receipt_setting": "all_disabled",
"geo_enabled": False,
"include_alt_text_compose": True,
"include_mention_filter": True,
"include_nsfw_admin_flag": True,
"include_nsfw_user_flag": True,
"include_ranked_timeline": True,
"language": "en",
"mention_filter": "unfiltered",
"nsfw_admin": False,
"nsfw_user": False,
"personalized_trends": True,
"protected": False,
"ranked_timeline_eligible": None,
"ranked_timeline_setting": None,
"require_password_login": False,
"requires_login_verification": False,
"sleep_time": {
"enabled": False,
"end_time": None,
"start_time": None
},
"translator_type": "none",
"universal_quality_filtering_enabled": "enabled",
"use_cookie_personalization": False,
})
# example configuration
account.update_search_settings({
"optInFiltering": True, # filter nsfw content
"optInBlocking": True, # filter blocked accounts
})
notifications = account.notifications()
account.change_password('old pwd','new pwd')
Scraping
Get all user/tweet data
Two special batch queries scraper.tweets_by_ids
and scraper.users_by_ids
should be preferred when applicable. These endpoints are more much more efficient and have higher rate limits than their unbatched counterparts. See the table below for a comparison.
Endpoint | Batch Size | Rate Limit |
---|---|---|
tweets_by_ids | ~220 | 500 / 15 mins |
tweets_by_id | 1 | 50 / 15 mins |
users_by_ids | ~220 | 100 / 15 mins |
users_by_id | 1 | 500 / 15 mins |
As of Fall 2023 login by username/password is unstable. Using cookies is now recommended.
from twitter.scraper import Scraper
## sign-in with credentials
email, username, password = ..., ..., ...
scraper = Scraper(email, username, password)
## or, resume session using cookies
# scraper = Scraper(cookies={"ct0": ..., "auth_token": ...})
## or, resume session using cookies (JSON file)
# scraper = Scraper(cookies='twitter.cookies')
## or, initialize guest session (limited endpoints)
# from twitter.util import init_session
# scraper = Scraper(session=init_session())
# user data
users = scraper.users(['foo', 'bar', 'hello', 'world'])
users = scraper.users_by_ids([123, 234, 345]) # preferred
users = scraper.users_by_id([123, 234, 345])
tweets = scraper.tweets([123, 234, 345])
likes = scraper.likes([123, 234, 345])
tweets_and_replies = scraper.tweets_and_replies([123, 234, 345])
media = scraper.media([123, 234, 345])
following = scraper.following([123, 234, 345])
followers = scraper.followers([123, 234, 345])
scraper.tweet_stats([111111, 222222, 333333])
# get recommended users based on user
scraper.recommended_users()
scraper.recommended_users([123])
# tweet data
tweets = scraper.tweets_by_ids([987, 876, 754]) # preferred
tweets = scraper.tweets_by_id([987, 876, 754])
tweet_details = scraper.tweets_details([987, 876, 754])
retweeters = scraper.retweeters([987, 876, 754])
favoriters = scraper.favoriters([987, 876, 754])
scraper.download_media([
111111,
222222,
333333,
444444,
])
# trends
scraper.trends()
Resume Pagination
Pagination is already done by default, however there are circumstances where you may need to resume pagination from a specific cursor. For example, the Followers
endpoint only allows for 50 requests every 15 minutes. In this case, we can resume from where we left off by providing a specific cursor value.
from twitter.scraper import Scraper
email, username, password = ...,...,...
scraper = Scraper(email, username, password)
user_id = 44196397
cursor = '1767341853908517597|1663601806447476672' # example cursor
limit = 100 # arbitrary limit for demonstration
follower_subset, last_cursor = scraper.followers([user_id], limit=limit, cursor=cursor)
# use last_cursor to resume pagination
Search
from twitter.search import Search
email, username, password = ..., ..., ...
# default output directory is `data/search_results` if save=True
search = Search(email, username, password, save=True, debug=1)
res = search.run(
limit=37,
retries=5,
queries=[
{
'category': 'Top',
'query': 'paperswithcode -tensorflow -tf'
},
{
'category': 'Latest',
'query': 'test'
},
{
'category': 'People',
'query': 'brasil portugal -argentina'
},
{
'category': 'Photos',
'query': 'greece'
},
{
'category': 'Videos',
'query': 'italy'
},
],
)
Search Operators Reference
https://developer.twitter.com/en/docs/twitter-api/v1/rules-and-filtering/search-operators
https://developer.twitter.com/en/docs/twitter-api/tweets/search/integrate/build-a-query
Spaces
Live Audio Capture
Capture live audio for up to 500 streams per IP
from twitter.scraper import Scraper
from twitter.util import init_session
session = init_session() # initialize guest session, no login required
scraper = Scraper(session=session)
rooms = [...]
scraper.spaces_live(rooms=rooms) # capture live audio from list of rooms
Live Transcript Capture
Raw transcript chunks
from twitter.scraper import Scraper
from twitter.util import init_session
session = init_session() # initialize guest session, no login required
scraper = Scraper(session=session)
# room must be live, i.e. in "Running" state
scraper.space_live_transcript('1zqKVPlQNApJB', frequency=2) # word-level live transcript. (dirty, on-the-fly transcription before post-processing)
Processed (final) transcript chunks
from twitter.scraper import Scraper
from twitter.util import init_session
session = init_session() # initialize guest session, no login required
scraper = Scraper(session=session)
# room must be live, i.e. in "Running" state
scraper.space_live_transcript('1zqKVPlQNApJB', frequency=1) # finalized live transcript. (clean)
Search and Metadata
from twitter.scraper import Scraper
from twitter.util import init_session
from twitter.constants import SpaceCategory
session = init_session() # initialize guest session, no login required
scraper = Scraper(session=session)
# download audio and chat-log from space
spaces = scraper.spaces(rooms=['1eaJbrAPnBVJX', '1eaJbrAlZjjJX'], audio=True, chat=True)
# pull metadata only
spaces = scraper.spaces(rooms=['1eaJbrAPnBVJX', '1eaJbrAlZjjJX'])
# search for spaces in "Upcoming", "Top" and "Live" categories
spaces = scraper.spaces(search=[
{
'filter': SpaceCategory.Upcoming,
'query': 'hello'
},
{
'filter': SpaceCategory.Top,
'query': 'world'
},
{
'filter': SpaceCategory.Live,
'query': 'foo bar'
}
])
Automated Solvers
This requires installation of the proton-api-client package
To set up automated email confirmation/verification solvers, add your Proton Mail credentials below as shown.
This removes the need to manually solve email challenges via the web app. These credentials can be used
in Scraper
, Account
, and Search
constructors.
E.g.
from twitter.account import Account
from twitter.util import get_code
from proton.client import ProtonMail
proton_username, proton_password = ..., ...
proton = lambda: get_code(ProtonMail(proton_username, proton_password))
email, username, password = ..., ..., ...
account = Account(email, username, password, proton=proton)
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