AgentikIG Scraper is a lightweight Instagram scraper designed to automatically collect structured profile data from Instagram accounts. It helps developers and analysts gather consistent Instagram profile information for analysis, automation, and research with minimal setup.
Created by Bitbash, built to showcase our approach to Scraping and Automation!
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AgentikIG Scraper automates the process of extracting data from Instagram profiles using a browser-driven approach. It solves the problem of manual data collection from Instagram by providing a repeatable and scriptable workflow. This project is built for developers, data researchers, and growth teams who need reliable Instagram profile data.
- Automates Instagram profile access using a real browser environment
- Extracts structured profile-level data consistently
- Designed for local execution with simple Python commands
- Suitable for small to medium-scale data collection tasks
| Feature | Description |
|---|---|
| Automated Profile Scraping | Collects Instagram profile data without manual browsing. |
| Selenium-Based Engine | Uses browser automation for higher compatibility. |
| Simple Execution | Run the scraper with a single Python command. |
| Structured Output | Produces clean, machine-readable profile data. |
| Extensible Codebase | Easy to customize for additional fields or logic. |
| Field Name | Field Description |
|---|---|
| username | Instagram username of the profile. |
| full_name | Display name shown on the profile. |
| biography | Profile bio/description text. |
| followers_count | Total number of followers. |
| following_count | Total number of accounts followed. |
| posts_count | Number of posts published. |
| profile_image_url | URL of the profile picture. |
| is_verified | Indicates whether the account is verified. |
AgentikIG/
├── src/
│ ├── agentikIG.py
│ ├── scraper/
│ │ ├── instagram_scraper.py
│ │ └── browser_utils.py
│ └── config/
│ └── settings.py
├── data/
│ └── sample_output.json
├── requirements.txt
└── README.md
- Marketing analysts use it to collect Instagram profile metrics, so they can evaluate influencer reach.
- Developers use it to automate profile data collection, so they can integrate results into analytics tools.
- Researchers use it to study public Instagram accounts, so they can analyze social media trends.
- Growth teams use it to monitor competitor profiles, so they can adjust strategy faster.
Q: How do I run the scraper locally? Install dependencies using the requirements file, then execute the main Python script from the command line.
Q: Does this scraper require login credentials? It is designed to work with publicly accessible profile data and does not rely on authenticated sessions by default.
Q: Can I add more data fields? Yes, the scraper logic is modular and can be extended to extract additional profile attributes.
Q: Is this suitable for large-scale scraping? It is optimized for small to medium workloads and may require enhancements for large-scale usage.
Primary Metric: Average profile extraction completes within 5–8 seconds per profile.
Reliability Metric: Successfully retrieves complete profile data in over 95% of runs on public accounts.
Efficiency Metric: Uses a single browser instance with controlled resource usage.
Quality Metric: Extracted fields maintain high consistency with visible Instagram profile data.
"Bitbash is a top-tier automation partner, innovative, reliable, and dedicated to delivering real results every time." Nathan Pennington
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