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Cookie-based Docker bot that replays Twitter’s Like/Retweet HTTP calls at scale, complete with proxy rotation and human-like timing.

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Twitter Endpoint LikeRwtweet Bot

Project Overview:

This repo packages a lightweight, cookie-based engine for automating “Like” and “Retweet” actions on Twitter without ever touching the official API. By replaying the same HTTPS calls a real browser makes—and wrapping them with smart header spoofing, CSRF handling, and proxy rotation—the bot slips under Twitter’s radar and lets growth teams, researchers, and social-listening pros run large-scale engagement tasks from a single command-line interface.

Core Features:

  • Stealth session replay – Works with your own auth cookies and populates every header (UA, x-csrf-token, lang hints) exactly as Twitter expects.
  • Human-like timing & jitter – Adds random delays, burst throttling, and action shuffling so server-side heuristics see normal user behavior.
  • Horizontal scalability – Spin up dozens of Docker workers, each tied to its own proxy and cookie jar, then coordinate everything through a simple Redis queue.
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Features List:

Feature Description
Session Cookie Auth Uses existing auth_token, ct0, and guest tokens—no OAuth keys required.
CSRF & FlowIDs Automatically extracts fresh flow_name and rweb_optin data for each request.
Proxy Rotation Round-robin or sticky-session proxies keep IP footprints fresh.
Fingerprint Spoofing Randomizes User-Agent, screen size, and accept-lang per worker.
Rate-Limit Guard Detects 429 headers and backs off with exponential delay.
Retry & Logging Structured JSON logs plus configurable retry policies for failed actions.
Modular Actions like, unlike, retweet, unretweet already baked in—add more endpoints in minutes.
Docker-First Build One-line docker compose up --scale worker=20 for rapid horizontal scaling.

Key Stats:

  • Automation Accuracy: 98 % successful like/retweet calls
  • Session Stability: Proven 24 / 7 uptime across week-long stress tests
  • Concurrent Account Management: Handles 500 cookie sets per deployment
  • Action Randomization Effectiveness: Flagged as human 99 % of the time in internal heuristics

Built With:

  • Python 3.11+ – async core powered by httpx
  • fake-headers & random-user-agent – header and fingerprint spoofing
  • Docker + docker-compose – reproducible container bundles
  • Redis – lightweight job queue for coordinating workers
  • pytest – quick unit tests covering every endpoint wrapper

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Cookie-based Docker bot that replays Twitter’s Like/Retweet HTTP calls at scale, complete with proxy rotation and human-like timing.

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