reelscraper 2.1.0

A convenient way to harvest Reels data without breaking a sweat—or Instagram's TOS

Reel Scraper

Scrape Instagram Reels data with ease—be it a single account or many in parallel—using Python, threading, robust logging, and optional data-saving.

Installation • Usage • Classes • Contributing • License • Acknowledgments • Disclaimer

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💻 Installation

Reel Scraper requires Python 3.9+. Install it from PyPI:

pip install reelscraper

Alternatively, clone from GitHub:

git clone https://github.com/andreaaazo/reelscraper.git
cd reelscraper
python -m pip install .

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🚀 Usage

Reel Scraper now supports additional logging and data-saving functionalities. Below are two common ways to run the scraper—either interactively or via a CLI entry point (if provided).

1. Single Account or Single-Session Scraping

Use the ReelScraper class for scraping Reels from one Instagram account at a time. Optionally, integrate a LoggerManager to get detailed logs during retries and processing.

from reelscraper import ReelScraper
from reelscraper.utils import LoggerManager

# Optionally configure the logger
logger = LoggerManager()

# Initialize with a 30-second timeout, no proxy, and logging enabled
scraper = ReelScraper(timeout=30, proxy=None, logger_manager=logger)

# Fetch up to 10 reels for username "someaccount"
reels_data = scraper.get_user_reels("someaccount", max_posts=10)
for reel in reels_data:
    print(reel)

2. Multiple Accounts with Concurrency & Data Saving

Use the ReelMultiScraper class to process multiple Instagram accounts concurrently. In addition to concurrency, you can now enable logging and automatically save the results using a DataSaver.

from reelscraper import ReelScraper, ReelMultiScraper
from reelscraper.utils import LoggerManager, DataSaver

# Configure logger and data saver
logger = LoggerManager()
data_saver = DataSaver("json")

# Initialize a single scraper instance with logging
single_scraper = ReelScraper(timeout=30, proxy=None, logger_manager=logger)

# Initialize the multi-scraper with the data saver and custom concurrency settings
multi_scraper = ReelMultiScraper(
    scraper=single_scraper,
    logger_manager=logger,
    max_workers=5,      # Number of threads
    data_saver=data_saver
)

# Provide a file with one username per line:
# accounts.txt content example:
#   user1
#   user2
#   user3
accounts_file_path = "accounts.txt"

# Start the multi-account scraping process:
# Optionally, define max_posts_per_profile and max_retries_per_profile.
all_reels = multi_scraper.scrape_accounts(
    accounts_file=accounts_file_path,
    max_posts_per_profile=20,
    max_retires_per_profile=10
)

# Display overall (aggregated) results:
print(f"Total reels scraped: {len(all_reels)}")

Note: The multi-account scraper reads usernames from your provided file (one per line) and aggregates reels across all accounts. Logging messages and progress are displayed during processing if LoggerManager is configured. The final result is saved if DataSaver is configured.

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🏗 Classes

ReelScraper

• Purpose:
  Retrieves Instagram Reels data for a single account.
• Key Components:
  • InstagramAPI: Handles HTTP requests.
  • Extractor: Formats raw data into structured reels information.
  • LoggerManager (optional): Logs retries and status events.
• Key Method:
  • get_user_reels(username, max_posts, max_retries): Fetches reels for the specified user, applying pagination, retries, and logging.

ReelMultiScraper

• Purpose:
  Scrapes multiple accounts concurrently using an underlying ReelScraper instance.
• Key Components:
  • ThreadPoolExecutor: Manages concurrent requests.
  • AccountManager: Loads accounts from a file.
  • LoggerManager (optional): Tracks start, successes, errors, and final statistics.
  • DataSaver (optional): Saves results to a file.
• Key Method:
  • scrape_accounts(accounts_file, max_posts_per_profile, max_retires_per_profile): Executes parallel scraping across the accounts listed in the provided file.

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🤝 Contributing

We welcome contributions that make this scraper smarter, faster, or more resilient to changes. To contribute:

1. Fork the project.
2. Create a new branch.
3. Commit your improvements (bonus points for clear comments and even a dash of humor).
4. Submit a pull request.

Your contributions—whether bug fixes, new features, or documentation updates—are greatly appreciated!

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📄 License

This project is licensed under the MIT License. Use, modify, or distribute the project freely (just be kind to your fellow developers and remember your caffeine intake).

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🙏 Acknowledgments

• Python Community: For enabling an accessible approach to concurrency, API integration, and packaging.
• Instagram: For providing reels that inspire both creativity and the need for efficient scraping.
• Coffee & Tea: The timeless fuels behind countless hours of problem-solving and debugging.

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⚠ Disclaimer

This project is for educational and personal use only. Always use it responsibly and in compliance with Instagram’s Terms of Service. We do not condone or endorse large-scale commercial scraping or any activity that violates policies. When in doubt, respect intellectual property and privacy the way you’d guard your grandmother’s cookie jar.

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Happy scraping and may your CPU fans stay cool!