Pinterest Following Scraper collects detailed profile data from the accounts a Pinterest user follows, turning scattered public information into structured, usable datasets. It helps marketers, researchers, and analysts understand networks, influence, and activity patterns with clarity and speed.
Created by Bitbash, built to showcase our approach to Scraping and Automation!
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This project extracts rich profile-level information from Pinterest following lists. Instead of manually reviewing profiles one by one, it automates the process and delivers clean, structured data ready for analysis. It’s built for analysts, growth teams, and developers who need reliable Pinterest following data at scale.
- Scans complete following lists for one or more Pinterest usernames
- Captures profile metadata, statistics, and recent activity
- Handles pagination and large following counts smoothly
- Outputs data in structured formats suitable for analytics workflows
| Feature | Description |
|---|---|
| Following list traversal | Collects all accounts followed by a target Pinterest user. |
| Rich profile metadata | Extracts usernames, IDs, full names, and profile URLs. |
| Statistics capture | Gathers pin count, board count, and follower count. |
| Media extraction | Retrieves profile images and recent pin thumbnails. |
| Activity tracking | Records last pin save timestamps when available. |
| Scalable processing | Designed to handle large datasets efficiently. |
| Field Name | Field Description |
|---|---|
| username | Pinterest handle of the followed account. |
| full_name | Display name associated with the profile. |
| id | Unique Pinterest user identifier. |
| profileUrl | Direct link to the user’s Pinterest profile. |
| pin_count | Total number of pins published by the user. |
| board_count | Number of boards created by the user. |
| follower_count | Total followers of the user. |
| image_large_url | Profile image in large resolution. |
| pin_thumbnail_urls | Thumbnails of the most recent pins. |
| last_pin_save_time | Timestamp of the latest saved pin. |
| is_private_profile | Indicates whether the profile is private. |
| is_verified_merchant | Shows merchant verification status. |
[
{
"searchUsername": "candyw8119",
"id": "922745548560406973",
"username": "thaobui75",
"full_name": "Thaobui",
"pin_count": 47,
"board_count": 7,
"follower_count": 1,
"is_private_profile": false,
"image_large_url": "https://s.pinimg.com/images/user/default_140.png",
"pin_thumbnail_urls": [
"https://i.pinimg.com/75x75/e8/7e/09/e87e096f6058f305512565cd5e823d55.jpg"
],
"last_pin_save_time": "Wed, 26 Feb 2025 21:30:01 +0000",
"profileUrl": "https://www.pinterest.com/thaobui75"
}
]
Pinterest Following Scraper/
├── src/
│ ├── main.py
│ ├── collectors/
│ │ ├── following_collector.py
│ │ └── profile_parser.py
│ ├── utils/
│ │ ├── pagination.py
│ │ └── rate_limiter.py
│ └── config/
│ └── settings.example.json
├── data/
│ ├── input.sample.json
│ └── output.sample.json
├── requirements.txt
└── README.md
- Marketing analysts use it to map competitor followings, so they can identify partnership and targeting opportunities.
- Influencer researchers use it to study creator networks, so they can spot emerging influencers early.
- Growth teams use it to analyze audience overlap, so they can refine outreach strategies.
- Data scientists use it to build Pinterest behavior models, so they can uncover trends at scale.
Can I scrape multiple Pinterest usernames at once? Yes, the input supports multiple usernames, allowing batch collection in a single run.
Does it handle large following lists? It is designed to manage large datasets efficiently, automatically handling pagination and load control.
What output formats are supported? The data is structured in JSON and can be easily converted to CSV, Excel, or other analytical formats.
Is private profile data included? Only publicly available information is collected. Private profiles are flagged but not expanded beyond visible fields.
Primary Metric: Processes an average of several hundred profiles per minute, depending on network conditions.
Reliability Metric: Maintains a high success rate with consistent data retrieval across long runs.
Efficiency Metric: Optimized request handling keeps resource usage stable during large-scale jobs.
Quality Metric: Captures complete profile records with minimal missing fields in real-world usage.
"Bitbash is a top-tier automation partner, innovative, reliable, and dedicated to delivering real results every time." Nathan Pennington
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"Bitbash delivers outstanding quality, speed, and professionalism, truly a team you can rely on." Eliza
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"Exceptional results, clear communication, and flawless delivery. Syed
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