instagram automationim looking for instagram automation code to run on a pc on emulators browsers can be anything something i can use to mass dm and scrape users

This project provides a high-performance Instagram automation system built to run on PC-based emulators or browser environments. It automates messaging, scraping, and workflow tasks at scale while maintaining safe pacing and human-like behavior. By using this tool, users searching for “instagram automationim looking for instagram automation code to run on a pc on emulators browsers can be anything something i can use to mass dm and scrape users” will find a ready-to-run, extensible framework for mass DMs and targeted user data extraction.

Introduction

This automation tool streamlines repetitive Instagram workflows such as messaging, navigation, scraping, and task sequencing. It handles everything from device control to workflow scheduling so users and businesses can scale outreach with minimal manual effort.

Advanced Emulator-Driven Instagram Automation

• Automates complex UI workflows across emulators or real Android devices with Appilot-level reliability.
• Reduces repetitive manual tasks through robust scheduling and action chaining.
• Handles safe user scraping, messaging flows, and multi-profile management.
• Designed for long-running, stable sessions with comprehensive error recovery.
• Scales horizontally to handle multiple tasks and devices simultaneously.

Core Features

Feature	Description
Real Devices and Emulators	Works with physical Android devices and leading emulators (Bluestacks, Nox) with reliable UI control.
No-ADB Wireless Automation	Supports ADB-less control through Accessibility, low-level input bridges, and scrcpy-style streaming.
Mimicking Human Behavior	Implements gesture variance, subtle delays, scroll randomness, and warm-up sequences for safer behavior.
Multiple Accounts Support	Isolated containers for sessions, cookies, and profiles enable independent, configurable accounts.
Multi-Device Integration	Supports parallel execution across device farms, distributing tasks intelligently.
Exponential Growth for Your Account	Targets users based on scraping results with pacing and anti-detection logic.
Premium Support	Offers onboarding guidance, SLAs, and escalation pathways for reliability and maintenance.
Intelligent Scraping Engine	Extracts followers, interactions, and profile metadata with structured outputs.
DM Campaign Manager	Sends personalized or templated DMs at scale using safe-rate automation logic.
Workflow Scheduler	Automates daily routines with fully configurable task pipelines and retry strategies.

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How It Works

Input or Trigger — The automation is triggered through the Appilot dashboard by configuring tasks (app interactions, notifications, schedules) for an Android device or emulator. Core Logic — Appilot orchestrates UI Automator, Appium, Accessibility, or (when appropriate) ADB to perform navigation, taps/clicks, form fills, data entry, and in-app workflows. Output or Action — The bot executes the designated actions (e.g., send messages, post content, update records) and returns structured results, logs, or webhooks. Other Functionalities — Retry logic, error handling, structured logs, anti-detection pacing, and parallel processing are configurable in the Appilot dashboard. Safety Controls — Rate limits, cooldowns, randomized behavior, and proxy/device rotation to reduce risk.

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Tech Stack

Language: Kotlin, Java, JavaScript, Python Frameworks: Appium, UI Automator, Espresso, Robot Framework, Cucumber Tools: Appilot, Android Debug Bridge (ADB), Appium Inspector, Bluestacks, Nox Player, Scrcpy, Firebase Test Lab, MonkeyRunner, Accessibility Infrastructure: Dockerized device farms, Cloud emulators, Proxy networks, Parallel Device Execution, Task Queues, Real device farm

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Directory Structure

automation-bot/
├── src/
│   ├── main.py
│   ├── automation/
│   │   ├── tasks.py
│   │   ├── scheduler.py
│   │   └── utils/
│   │       ├── logger.py
│   │       ├── proxy_manager.py
│   │       └── config_loader.py
├── config/
│   ├── settings.yaml
│   ├── credentials.env
├── logs/
│   └── activity.log
├── output/
│   ├── results.json
│   └── report.csv
├── requirements.txt
└── README.md

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Use Cases

• Marketers use it to auto-send DMs to targeted audiences, so they can scale outreach without manual grind.
• E-commerce teams use it to update listings across multiple stores, so they can keep catalogs consistent.
• Community managers use it to moderate and engage faster, so they can improve response times.
• QA engineers use it to execute end-to-end device tests, so they can catch regressions pre-release.

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FAQs

How do I configure this automation for multiple accounts? Use separate profiles, per-account configuration files, and isolated device sessions to maintain independence and reduce cross-contamination.

Does it support proxy rotation or anti-detection? Yes — supports proxy pools, per-device bindings, randomized pacing, and behavioral variance to reduce detection risk.

Can I schedule it to run periodically? Yes — the scheduler uses cron-like rules, job queues, and automatic retries for reliability.

What about emulator vs real device parity? Most features work identically. Real hardware is preferred for long-running stability, while emulators provide rapid scaling.

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Performance & Reliability Benchmarks

Execution Speed: ~45–70 actions/min under typical device farm conditions. Success Rate: ~93–94% across long-running sessions with automatic retries. Scalability: Designed to orchestrate 300–1,000 devices via sharded queues and parallel workers. Resource Efficiency: ~1–1.5 CPU cores and 600–900MB RAM per active worker/device. Error Handling: Automatic retries, exponential backoff, structured logs, real-time alerts, and recovery flows.