Metadata-Version: 2.4
Name: py-tw-client
Version: 1.0.2
Summary: Implementation of X/Twitter v1, v2, and GraphQL APIs.
Home-page: https://github.com/repen/twitter-api-client
Author: Plugin.py
Author-email: 9keepa@gmail.com
License: MIT
Keywords: twitter api client async search automation bot scrape
Classifier: Environment :: Web Environment
Classifier: Intended Audience :: Developers
Classifier: Natural Language :: English
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Internet :: WWW/HTTP
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: >=3.10.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: aiofiles
Requires-Dist: nest_asyncio
Requires-Dist: httpx
Requires-Dist: tqdm
Requires-Dist: orjson
Requires-Dist: m3u8
Requires-Dist: websockets
Requires-Dist: uvloop; platform_system != "Windows"
Requires-Dist: XClientTransaction
Requires-Dist: requests
Requires-Dist: beautifulsoup4
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: keywords
Dynamic: license
Dynamic: license-file
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary



## Implementation of X/Twitter v1, v2, and GraphQL APIs.


## Table of Contents

* [Installation](#installation)
* [Automation](#automation)
* [Scraping](#scraping)
  * [Get all user/tweet data](#get-all-usertweet-data)
  * [Resume Pagination](#resume-pagination)
  * [Search](#search)
* [Spaces](#spaces)
  * [Live Audio Capture](#live-audio-capture)
  * [Live Transcript Capture](#live-transcript-capture)
  * [Search and Metadata](#search-and-metadata)
* [Automated Solvers](#automated-solvers)
* [Example API Responses](#example-api-responses)

### Installation

```bash
pip install twitter-api-client
```

### Automation

```python
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.*

```python
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.
```python
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

```python
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

```python
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**

```python
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**

```python
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
```python
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](https://pypi.org/project/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.

```python
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)
```

