A Python client to scrape tweets from X (formerly Twitter) timelines using a cURL command.
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.
To install the X-Timeline Scraper, you can use pip:
pip install xtimelineTo 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.
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())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():
print(t.to_markdown())
asyncio.run(main())By default, stream() now polls every ~30 seconds with built-in jitter (fuzzy interval) so requests do not follow an identical cadence.
# 30s base with +-20% jitter (default)
async for t in xc.stream():
process(t)
# Custom base interval and jitter
async for t in xc.stream(interval_s=45.0, jitter_ratio=0.15):
process(t)
# Disable jitter if you need a fixed cadence
async for t in xc.stream(interval_s=30.0, jitter_ratio=0.0):
process(t)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)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 |
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}}
}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.
This project is licensed under the MIT License. See the LICENSE file for details.