Software Alternatives, Accelerators & Startups

Streamlit VS ScrapeHunt

Compare Streamlit VS ScrapeHunt and see what are their differences

Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Streamlit logo Streamlit

Turn python scripts into beautiful ML tools

ScrapeHunt logo ScrapeHunt

Get a scraped database in 60 seconds
  • Streamlit Landing page
    Landing page //
    2023-10-07
  • ScrapeHunt Landing page
    Landing page //
    2021-09-22

Streamlit features and specs

  • Ease of Use
    Streamlit's API is extremely intuitive and easy to learn, which makes it accessible for developers of varying experience levels. The simplicity allows for rapid development and less time spent on complex front-end coding.
  • Interactive Widgets
    It provides a set of interactive widgets that make it simple to add complex functionalities like sliders, buttons, and file uploaders to your application with minimal code.
  • Real-time Feedback
    Streamlit supports real-time data updates, allowing users to see changes instantly. This is particularly useful for data analysis and machine learning applications where live data visualization is crucial.
  • Integration with Machine Learning Libraries
    Streamlit integrates seamlessly with popular machine learning libraries like TensorFlow, PyTorch, and scikit-learn, making it a great tool for showcasing machine learning models and results.
  • Open Source
    Being an open-source project, Streamlit is free to use and comes with the support and contributions of an active community. This means continuous improvements and a wealth of shared resources.

Possible disadvantages of Streamlit

  • Limited Customization
    Streamlit offers limited customization options compared to traditional web frameworks. This can be a hindrance if you need a highly customized UI/UX for your application.
  • Performance Issues
    For more complex or resource-intensive applications, Streamlit may suffer from performance drawbacks. It is not designed for high-performance computing out of the box.
  • Scalability
    Streamlit is not well-suited for large-scale applications requiring major backend architecture or for scenarios demanding high scalability and concurrency.
  • Limited Widget Style Options
    The styling and customization options for widgets are somewhat limited, meaning your application's look and feel might be more constrained compared to using other front-end frameworks.
  • Deployment Complexity
    While Streamlit provides some deployment options, deploying Streamlit apps in a production environment can sometimes require additional effort and knowledge, especially for those unfamiliar with web deployment practices.

ScrapeHunt features and specs

  • Ease of Use
    ScrapeHunt offers a straightforward interface and user-friendly experience, making it accessible for users with varying levels of technical expertise.
  • Pre-Built Scrapers
    The service provides a repository of pre-built scrapers for various use cases, which can save significant time compared to creating scrapers from scratch.
  • Scalability
    ScrapeHunt is designed to handle large-scale scraping tasks, making it suitable for businesses needing to extract vast amounts of data.
  • API Integration
    The platform offers robust API support, allowing easy integration with other tools and systems for seamless data flow.
  • Customer Support
    ScrapeHunt provides responsive customer support to assist users with any issues or questions that may arise while using the service.
  • Regular Updates
    The platform frequently updates its scraping technology to adapt to changes in website structures and improve performance.

Possible disadvantages of ScrapeHunt

  • Cost
    ScrapeHunt can be relatively expensive, especially for smaller businesses or individual users who may find the pricing prohibitive.
  • Limited Flexibility
    While pre-built scrapers are convenient, they may not cover all niche scraping needs, requiring custom development for specific tasks.
  • Learning Curve
    Some users might still face a learning curve when trying to fully utilize the platform's capabilities, despite its user-friendly design.
  • Data Privacy
    Using a third-party scraping service involves sharing potentially sensitive information, which could raise concerns over data privacy and security.
  • Dependency
    Relying on an external service for web scraping can create dependency issues; any downtime or service changes on ScrapeHunt's side can directly impact users' operations.

Streamlit videos

My thoughts on web frameworks in Python and R (PyWebIO vs Streamlit vs R Shiny)

More videos:

  • Review - 1/4: What is Streamlit
  • Tutorial - How to Build a Streamlit App (Beginner level Streamlit tutorial) - Part 1

ScrapeHunt videos

No ScrapeHunt videos yet. You could help us improve this page by suggesting one.

Add video

Category Popularity

0-100% (relative to Streamlit and ScrapeHunt)
Developer Tools
100 100%
0% 0
Web Scraping
0 0%
100% 100
Productivity
100 100%
0% 0
Data Extraction
0 0%
100% 100

User comments

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Social recommendations and mentions

Based on our record, Streamlit seems to be more popular. It has been mentiond 209 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.

Streamlit mentions (209)

  • Build Code-RAGent, an agent for your codebase
    The only thing left to do then was to build something that could showcase the power of code ingestion within a vector database, and it immediately clicked in my mind: "Why don't I ingest my entire codebase of solved Go exercises from Exercism?" That's how I created Code-RAGent, your friendly coding assistant based on your personal codebases and grounded in web search. It is built on top of GPT-4.1, powered by... - Source: dev.to / 22 days ago
  • How AI is Transforming Front-End Development in 2025!
    Streamlit.io: Great documentation and reusable components to integrate with your AI application for rapid python front-end AI development. - Source: dev.to / 28 days ago
  • Querying DynamoDB with Natural Language Using MCP
    The agent uses MCP to translate this into a DynamoDB query. Then, using Streamlit UI, results are returned in a structured format, making it easy to use. - Source: dev.to / 3 months ago
  • Can I run this LLM?
    It's powered by something called "Streamlit" (https://streamlit.io). > A faster way to build and share data apps Website doesn't even load for me. I don't even know what to say...welcome to web dev 2025 edition. - Source: Hacker News / 3 months ago
  • Vaadin Flow for AdminUI
    Since Vaadin is Java-focused, its major benefits are best realized within that ecosystem. If you're using .NET, Blazor might be a better fit, while in the Python world, a lightweight alternative could be Streamlit. - Source: dev.to / 3 months ago
View more

ScrapeHunt mentions (0)

We have not tracked any mentions of ScrapeHunt yet. Tracking of ScrapeHunt recommendations started around Mar 2021.

What are some alternatives?

When comparing Streamlit and ScrapeHunt, you can also consider the following products

Anvil.works - Build seriously powerful web apps with all the flexibility of Python. No web development experience required.

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

Recut - Edit silence out of videos automatically

Scrapy - Scrapy | A Fast and Powerful Scraping and Web Crawling Framework

FastAPI - FastAPI is an Open Source, modern, fast (high-performance), web framework for building APIs with Python 3.6+ based on standard Python type hints.

Portia - An open-source visual scraping tool that lets you scrape the web without coding, built by Scrapy...