https://github.com/mostafahima/insta-data-scraper
An automated tool for scraping Instagram account data, collecting post URLs, comments, and organizing the data into Excel files for easy analysis.
https://github.com/mostafahima/insta-data-scraper
scraping-python
Last synced: 3 months ago
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An automated tool for scraping Instagram account data, collecting post URLs, comments, and organizing the data into Excel files for easy analysis.
- Host: GitHub
- URL: https://github.com/mostafahima/insta-data-scraper
- Owner: MostafaHima
- License: gpl-3.0
- Created: 2024-12-03T01:08:09.000Z (6 months ago)
- Default Branch: main
- Last Pushed: 2024-12-03T04:00:56.000Z (6 months ago)
- Last Synced: 2024-12-28T16:50:03.552Z (5 months ago)
- Topics: scraping-python
- Language: Python
- Homepage:
- Size: 327 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Instagram Data Scraping Automation Script
## Overview
This script is a powerful and efficient automation tool designed to scrape data from Instagram profiles. By leveraging Selenium WebDriver, the script automates the entire process, including logging into an Instagram account, navigating through posts, collecting valuable data (such as post URLs, details, and comments), and then organizing the data into a structured Excel file for further analysis or use.
## Key Features:
### 1. **Automated Instagram Login:**
- The script begins by logging into the target Instagram account using provided credentials, ensuring a seamless login process.
### 2. **Profile Data Collection:**
- It gathers essential profile information, including follower count, following count, and the number of posts, offering an insightful overview of the account’s performance.
### 3. **Post URL Extraction:**
- It automatically extracts URLs from all the posts on the profile, enabling quick access to specific content.
### 4. **Comments Scraping:**
- The script digs deeper by scraping all the comments under each post, storing the valuable insights for further analysis.
### 5. **Data Organization and Upload:**
- All collected data (post details, comment counts, and comments) are neatly organized and uploaded to an Excel file, making it easy to analyze, store, or share.
### 6. **Advanced Error Handling and Automation:**
- The script is designed to handle errors gracefully and allows for continuous scrolling and data collection from Instagram pages, ensuring no data is left behind.
### 7. **Easy-to-Use Interface:**
- Simply input the Instagram profile URL and the script does the rest, navigating to the target page, scraping data, and generating a report automatically.
## Benefits:
- **Efficiency:** It automates time-consuming tasks like manual scraping and data entry, saving significant time and effort.
- **Customization:** Users can customize the profile URL and login credentials, making the script flexible for various use cases.
- **Comprehensive Data:** By collecting both post URLs and comments, it offers a holistic view of Instagram profiles.
- **Ready for Analysis:** Data is exported to an Excel file, making it ready for any further analysis or reporting.
## Data Collected
The script collects the following data for each post:
1. **Replies**: All replies under each comment (if available).
2. **Likes**: The number of likes each comment has received.
3. **Comment Text**: The content of each comment.
4. **Name of Commenter**: The username of the person who made the comment.
5. **Commenter's URL**: The URL to the commenter's profile.
## Applications:
- Social media analysis
- Marketing and influencer research
- Competitor analysis
- Data-driven decision making
## Conclusion:
This Instagram scraping automation script is an ideal tool for marketers, researchers, and data analysts looking to gather insights from Instagram profiles quickly and efficiently. With its ease of use, customization options, and reliable data collection capabilities, it empowers users to access valuable social media data in a structured and actionable format.
## How to Use
### Prerequisites
1. Ensure you have Python installed on your machine. You can download it from the [official website](https://www.python.org/downloads/).
```bash
git clone https://github.com/MostafaHima/your-repository.git
```
```bash
pip install -r requirements.txt
```
```bash
python main.py
```