xtimeline 0.1.4

Lightweight X/Twitter timeline client (GraphQL via cURL or auth strategies)

X-Timeline Scraper

A Python client to scrape tweets from X (formerly Twitter) timelines using a cURL command.

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Introduction

This project provides a Python client to scrape tweets from X (formerly Twitter) timelines using a cURL command. It leverages asynchronous programming for efficient data retrieval and includes features for parsing tweet data.

Table of Contents 🗂

• Installation
• Usage
• Citation
• Contributing
• License

Installation ⚙️

To install the X-Timeline Scraper, you can use pip:

pip install xtimeline

Usage ⌨️

To use the X-Timeline Scraper, you need to provide a cURL command that accesses the desired X timeline. The instructions can be found in curl_example.txt. Then, you can use the XTimelineClient class to fetch and parse tweets.

Fetching tweets once

import asyncio
from xclient import XTimelineClient

async def main():
    async with XTimelineClient("curl.txt") as xc:
        tweets = await xc.fetch_tweets()
        for t in tweets:
            print(t.to_markdown())

asyncio.run(main())

Streaming new tweets

import asyncio
from xclient import XTimelineClient

async def main():
    async with XTimelineClient(
        "curl.txt", persist_last_id_path="state/last_id.txt"
    ) as xc:
        async for t in xc.stream(interval_s=5.0):
            print(t.to_markdown())

asyncio.run(main())

Fetch modes

Both fetch_tweets() and stream() accept a mode parameter that controls which tweets are returned:

Mode	Behaviour
"new_only" (default)	Only returns tweets newer than the last-seen cursor. The cursor advances so the same tweet is never emitted twice.
"all"	Returns every tweet in each response. Nothing is filtered. Useful when your own store (e.g. a SQLite database) handles deduplication.
"with_updates"	Returns new tweets and re-emits previously seen tweets whenever their metrics change (likes, retweets, views). Re-emitted tweets have is_update=True.

# Hand all deduplication to your own store
async for t in xc.stream(mode="all"):
    upsert_to_db(t)

# Only new tweets, cursor persisted across restarts
async with XTimelineClient(
    "curl.txt", persist_last_id_path="state/last_id.txt"
) as xc:
    async for t in xc.stream(mode="new_only"):
        process(t)

# New tweets + engagement updates
async for t in xc.stream(mode="with_updates"):
    if t.is_update:
        update_metrics_in_db(t)
    else:
        insert_new_tweet(t)

Tweet fields

Each Tweet object contains:

Field	Type	Description
id	int	Tweet ID
text	str	Full text, HTML entities unescaped, t.co links expanded, long-form tweets supported
user_name	str	Display name
user_screen_name	str	@handle (without @)
user_img	str	Profile image URL
url	str	Canonical tweet URL
created_at	str	Post time in ISO 8601 format (2026-04-01T19:15:49Z)
likes	int	Like count
retweets	int	Retweet count
replies	int	Reply count
views	int	View count
media	list[MediaItem]	Attached photos/videos
tickers	list[str]	Uppercased $TICKER symbols
hashtags	list[str]	Uppercased hashtags
title	str	Human-readable summary, e.g. "TraderSZ retweeted Jelle"
is_update	bool	True if this tweet was seen in a previous fetch this session

Citation ✍️

If you use this project in your research, please cite as follows:

@misc{project_name,
  author  = {Stephan Akkerman},
  title   = {X-Timeline Scraper},
  year    = {2025},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/StephanAkkerman/x-timeline-scraper}}
}

Contributing 🛠

Contributions are welcome! If you have a feature request, bug report, or proposal for code refactoring, please feel free to open an issue on GitHub. We appreciate your help in improving this project.

License 📜

This project is licensed under the MIT License. See the LICENSE file for details.