Scraping Following Lists¶

Retrieve and analyze the accounts a user follows to understand their interests, find potential connections, and build targeted outreach lists.

Overview¶

The following scraper extracts comprehensive data about accounts a user follows, including profile information, follower counts, and activity metrics. This is invaluable for competitive analysis, lead generation, and understanding network dynamics.

Use Cases¶

Competitive Analysis: See who your competitors follow for partnership insights
Lead Generation: Build lists of potential customers from relevant accounts
Network Mapping: Understand industry connections and influencer relationships
Content Discovery: Find accounts posting content your audience engages with

Basic Usage¶

import asyncio
from xeepy import Xeepy

async def scrape_following():
    async with Xeepy() as x:
        # Get accounts a user follows
        following = await x.scrape.following("elonmusk", limit=500)

        for user in following:
            print(f"@{user.username}: {user.followers_count} followers")

        # Export to CSV for analysis
        x.export.to_csv(following, "following_list.csv")

asyncio.run(scrape_following())

Advanced Options¶

async def advanced_following_scrape():
    async with Xeepy() as x:
        # Scrape with filtering options
        following = await x.scrape.following(
            username="techcrunch",
            limit=1000,
            include_protected=False,  # Skip private accounts
            min_followers=1000,       # Only accounts with 1k+ followers
            verified_only=False,      # Include non-verified accounts
            active_days=30            # Only accounts active in last 30 days
        )

        # Filter by account type
        influencers = [u for u in following if u.followers_count > 10000]
        brands = [u for u in following if u.verified and u.followers_count > 50000]

        return following

asyncio.run(advanced_following_scrape())

Batch Processing Multiple Accounts¶

async def batch_following_analysis():
    async with Xeepy() as x:
        target_accounts = ["user1", "user2", "user3"]
        all_following = {}

        for account in target_accounts:
            following = await x.scrape.following(account, limit=500)
            all_following[account] = following
            print(f"@{account} follows {len(following)} accounts")

        # Find common follows across accounts
        sets = [set(u.username for u in f) for f in all_following.values()]
        common = sets[0].intersection(*sets[1:])
        print(f"Common follows: {len(common)}")

asyncio.run(batch_following_analysis())

Configuration Options¶

Parameter	Type	Default	Description
`username`	str	required	Target username to scrape
`limit`	int	100	Maximum accounts to retrieve
`include_protected`	bool	True	Include private accounts
`min_followers`	int	0	Minimum follower count filter
`verified_only`	bool	False	Only verified accounts
`active_days`	int	None	Filter by recent activity

Rate Limiting

The scraper automatically handles rate limits. For large following lists (10k+), expect the operation to take several minutes. Use limit parameter to control batch sizes.

Private Accounts

You can only scrape following lists from public accounts or accounts that follow you back.

Best Practices¶

Start Small: Test with limit=100 before running large scrapes
Use Filters: Apply min_followers to focus on influential accounts
Schedule Off-Peak: Run large scrapes during low-traffic hours
Cache Results: Store results locally to avoid repeated scraping
Respect Privacy: Only scrape public information for legitimate purposes

Data Export¶

async def export_following_data():
    async with Xeepy() as x:
        following = await x.scrape.following("username", limit=500)

        # Multiple export formats
        x.export.to_csv(following, "following.csv")
        x.export.to_json(following, "following.json")
        x.export.to_excel(following, "following.xlsx")

asyncio.run(export_following_data())