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ScrapIn VS socketify.py

Compare ScrapIn VS socketify.py and see what are their differences

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Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

ScrapIn logo ScrapIn

LinkedIn Scraper without limit

socketify.py logo socketify.py

Maybe the fastest web framework for Python and PyPy
Not present
  • socketify.py Landing page
    Landing page //
    2023-09-24

ScrapIn features and specs

No features have been listed yet.

socketify.py features and specs

  • High Performance
    Socketify.py is designed for high scalability and performance, leveraging an efficient event loop and native extensions to handle a large number of concurrent connections efficiently.
  • WebSocket Support
    The library provides built-in support for WebSockets, making it suitable for real-time applications where persistent connections between client and server are necessary.
  • Asynchronous I/O
    Socketify.py is built on top of asynchronous I/O paradigms, allowing non-blocking operations that can improve the throughput of networked applications.
  • Ease of Use
    The library offers a clean and straightforward API with examples and documentation, which lowers the barrier to entry for developers who are new to network programming in Python.
  • Python Integration
    Being a Python library, socketify.py integrates well with existing Python applications and can be included as part of larger, multi-component systems.

Possible disadvantages of socketify.py

  • Limited Adoption
    As a relatively new or niche library, socketify.py might have a smaller user base and community compared to more established frameworks like Flask or Django, which could result in fewer community resources and third-party integrations.
  • Learning Curve
    For developers who are accustomed to synchronous programming paradigms, adapting to the asynchronous programming model of socketify.py may require an initial learning investment.
  • Documentation Depth
    While there is documentation, it might not be as extensive or comprehensive as those of more mature libraries, potentially requiring more experimentation or source code reading to fully grasp advanced features.
  • Potential Stability Issues
    Being less established, there might be undiscovered bugs or stability issues in production environments compared to long-standing Python networking libraries.
  • Ecosystem Limitations
    The library might lack some of the extensive third-party plugins or tools available in more popular frameworks, which could limit its extensibility.

Analysis of ScrapIn

Overall verdict

  • ScrapIn (scrapin.io) is a solid choice for developers and businesses needing reliable LinkedIn and company data enrichment through a straightforward API, offering real-time data retrieval with good accuracy and compliance-focused practices.

Why this product is good

  • Provides real-time LinkedIn profile and company data scraping via a simple, well-documented API
  • Delivers accurate and comprehensive enrichment data useful for lead generation and recruitment
  • Offers straightforward integration that saves developer time compared to building scrapers in-house
  • Focuses on compliant data access, reducing legal and technical risks
  • Scalable pricing suitable for both small teams and larger operations

Recommended for

  • Sales and marketing teams needing lead enrichment
  • Recruiters sourcing candidate data from LinkedIn
  • Developers building data-driven applications requiring professional profile data
  • Startups and businesses automating prospecting and CRM enrichment workflows

Analysis of socketify.py

Overall verdict

  • Socketify.py is a solid choice for developers seeking a high-performance web framework in Python, particularly for I/O-bound applications requiring speed comparable to frameworks in compiled languages, thanks to its use of uWebSockets under the hood.

Why this product is good

  • Built on uWebSockets, providing significant performance improvements over traditional Python web frameworks
  • Supports WebSockets natively, making it suitable for real-time applications
  • Lightweight and minimalistic design reduces overhead
  • Compatible with ASGI, allowing integration with existing Python async ecosystem
  • Active development and growing community support on GitHub
  • Good for building high-throughput APIs and services

Recommended for

  • Developers building real-time applications like chat apps or live notifications
  • Projects requiring high concurrency and low latency in Python
  • Teams looking to replace slower WSGI-based frameworks with something faster
  • Applications needing WebSocket support without heavy framework overhead
  • Microservices architectures where performance is critical
  • Python developers wanting an alternative to Node.js for performance-sensitive tasks

ScrapIn videos

+ Add

The Harsh Truth of Web Scraping in 2025

More videos:

  • Review - What are the best web scraping tools in 2025? | Best 3 providers reviewed
  • Tutorial - Web Scraping Is Easy Now (Browse AI Review & Tutorial)

socketify.py videos

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Category Popularity

0-100% (relative to ScrapIn and socketify.py)

ScrapIn

socketify.py

APIs
100 100%
APIs
0% 0
Python
0 0%
Python
100% 100
Data Extraction
100 100%
Data Extraction
0% 0
Websocket
0 0%
Websocket
100% 100

User comments

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Social recommendations and mentions

Based on our record, socketify.py seems to be more popular. It has been mentiond 2 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

ScrapIn mentions (0)

We have not tracked any mentions of ScrapIn yet. Tracking of ScrapIn recommendations started around Jul 2024.

socketify.py mentions (2)

  • Show HN: Python framework is faster than Golang Fiber
    These "benchmarks" are useless, they're not testing anything real world except the performance of uWebsockets. There are copy errors all over the place. And then an advertisement: https://github.com/cirospaciari/socketify.py#briefcase-comme... Is this a professional framework that produces proper, real-world benchmarks and... - Source: Hacker News / over 3 years ago
  • This is how I started the development of the fastest ASGI and WSGI Server in TechEmPower Benchmarks
    After starting the project called socketify.py at https://github.com/cirospaciari/socketify.py, I got pretty good results and reviews, but many people asked if socketify.py could be used to create a WSGI and ASGI server. WSGI and ASGI have a lot of overhead, that's is why I choose not to use them in the first place, but adding an ASGI and WSGI server allows a lot of code already written to run faster! Source: over 3 years ago

What are some alternatives?

When comparing ScrapIn and socketify.py, you can also consider the following products

Databar.ai - Databar.ai is a no-code API marketplace.

Phantombuster - A marketplace of simple to use no-code APIs

Netrows - Access professional profiles, company, and job data through our simple REST API

Apify - Apify is a web scraping and automation platform that can turn any website into an API.

Reverse Contact - Turn an email into a LinkedIn profile and +30 others datas

ScrapeNinja - Swiss army knife for high-performance web scraping

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