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Webix DataTable VS Scrapy

Compare Webix DataTable VS Scrapy and see what are their differences

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Webix DataTable logo Webix DataTable

Fast and lightweight DataTable JS widget with advanced features like rowspan and colspan, filters, sorting, sparklines, treetable, clipboard and Drag-n-drop support and much more

Scrapy logo Scrapy

Scrapy | A Fast and Powerful Scraping and Web Crawling Framework
  • Webix DataTable Landing page
    Landing page //
    2021-12-17
  • Scrapy Landing page
    Landing page //
    2021-10-11

Webix DataTable features and specs

  • Feature-rich
    Webix DataTable offers a variety of features out of the box, including sorting, filtering, paging, and editing, which can significantly speed up development time.
  • Customization
    It allows for extensive customization, enabling developers to modify the look and feel of the table, as well as its functionality to suit specific needs.
  • Performance
    The DataTable is optimized for handling large datasets efficiently, providing smooth scrolling and quick data manipulation.
  • Integration
    Webix DataTable can easily integrate with various data sources and server-side technologies, facilitating data management in complex applications.
  • Support and Documentation
    Comes with comprehensive documentation and strong support, which can help developers to effectively implement and troubleshoot the DataTable.

Possible disadvantages of Webix DataTable

  • Learning curve
    Although powerful, the extensive features and customization options can lead to a steep learning curve for new users.
  • Cost
    Webix DataTable is part of a commercial library, which may involve licensing costs that could be a consideration for small projects or startups.
  • Complexity for Simple Use-Cases
    For simple tables, using Webix DataTable can be overkill, introducing unnecessary complexity compared to simpler alternatives.
  • Dependency
    As it is a part of the Webix library, using the DataTable requires adopting the Webix framework, which may add extra weight to a project if only this component is needed.

Scrapy features and specs

  • Efficiency
    Scrapy is designed to be efficient and robust, capable of handling multiple tasks simultaneously and scraping large websites in a fast and reliable manner.
  • Built-in Tooling
    Scrapy comes with built-in tools for handling common tasks such as following links, extracting data using XPath and CSS, and exporting data in a variety of formats.
  • Customization
    Scrapy offers extensive customization options, allowing users to build complex spiders and modify their behavior through middleware and pipelines.
  • Python Integration
    Being a Python framework, Scrapy integrates seamlessly with the Python ecosystem, enabling the use of libraries like Pandas, NumPy, and others to process and analyze scraped data.
  • Community Support
    Scrapy has a large and active community, providing extensive documentation, tutorials, and third-party extensions to enhance functionality.
  • Asynchronous Processing
    Scrapy’s asynchronous processing model enhances performance by allowing multiple concurrent requests, reducing the time required for crawling sites.

Possible disadvantages of Scrapy

  • Steep Learning Curve
    For beginners, Scrapy's comprehensive feature set and the need for understanding concepts like XPath and CSS selectors can be challenging.
  • Resource Intensive
    Scrapy can be resource-intensive, potentially consuming significant memory and CPU, which can be problematic for scraping very large websites or running multiple spiders simultaneously.
  • Debugging Complexity
    Debugging Scrapy projects can be complex due to its asynchronous nature and the multiple layers of middleware and pipelines that need to be understood.
  • Overhead for Small Projects
    For simple or small-scale scraping tasks, the overhead of setting up and configuring a Scrapy project might be excessive, with simpler alternatives being more suitable.
  • Limited JavaScript Support
    Scrapy's out-of-the-box support for JavaScript-heavy websites is limited, requiring additional tools like Splash or Selenium, which can complicate the setup.
  • Dependency Management
    Managing Scrapy's dependencies and compatibility with other Python packages can sometimes be challenging, leading to potential conflicts and maintenance overhead.

Analysis of Scrapy

Overall verdict

  • Yes, Scrapy is a good option for those looking to implement web scraping projects due to its robust set of features, active community, and comprehensive documentation. It is particularly well-suited for projects that require scraping from multiple websites and processing large volumes of data efficiently.

Why this product is good

  • Scrapy is a popular open-source web crawling framework for Python that's designed for extensive, flexible, and efficient web scraping. Its built-in tools and features make it easy to extract data from websites quickly and automatically. Key advantages include its ability to handle requests asynchronously, its support for multiple protocols, its item pipeline feature that allows for data cleaning and storage, and its ease of integration with other Python libraries and databases.

Recommended for

    Scrapy is recommended for developers, data scientists, and businesses that need to gather data from websites efficiently. It's particularly useful for projects involving data aggregation, market research, competitive analysis, and monitoring pricing changes across various platforms.

Webix DataTable videos

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Scrapy videos

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Python Scrapy Tutorial - 22 - Web Scraping Amazon

More videos:

  • Demo - Scrapy - Overview and Demo (web crawling and scraping)
  • Review - GFuel LemoNADE Taste Test & Review! | Scrapy

Category Popularity

0-100% (relative to Webix DataTable and Scrapy)

Webix DataTable

Scrapy

JavaScript Tools
100 100%
JavaScript Tools
0% 0
Web Scraping
0 0%
Web Scraping
100% 100
Data Grid
100 100%
Data Grid
0% 0
Data Extraction
0 0%
Data Extraction
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Webix DataTable and Scrapy

Webix DataTable Reviews

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Scrapy Reviews

Top 15 Best TinyTask Alternatives in 2022
The software is simply deployable via the cloud, or you can host the spiders on your server using Scrapy. Only the rules need to be written; Scrapy will take care of the rest to separate the facts. With Scrapy’s portability and ability to run on Windows, Linux, Mac, and BSD platforms, new features can be added without affecting the program’s core.
Source: www.dashtech.org

Social recommendations and mentions

Based on our record, Scrapy seems to be a lot more popular than Webix DataTable. While we know about 97 links to Scrapy, we've tracked only 2 mentions of Webix DataTable. 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.

Webix DataTable mentions (2)

  • How to Build Complex Web Widgets [Part 3]
    Let’s get down to creating the table component based on the Webix Table. And, of course, we need to pass the Pager ID to the Table configuration. Once again, we will use the getIdByRelatedView() method to generate an ID for the Pager using the Table ID. Source: about 2 years ago
  • Why using the UI components is useful for JavaScript development?
    Frameworks and UI libraries are great tools to shorten the time spent on routine and to save more resources for dealing with creative tasks. One more important detail here is that the components are rich in features. For instance, the javascript datatable widget has 21 features like drag-n-drop, sorting, filtering, data validation, clipboard support, fixed areas, advanced editors, rowspan and colspan, grid... Source: about 4 years ago

Scrapy mentions (97)

  • Current problems and mistakes of web scraping in Python and tricks to solve them!
    One might ask, what about Scrapy? I'll be honest: I don't really keep up with their updates. But I haven't heard about Zyte doing anything to bypass TLS fingerprinting. So out of the box Scrapy will also be blocked, but nothing is stopping you from using curl_cffi in your Scrapy Spider. - Source: dev.to / 10 months ago
  • Automate Spider Creation in Scrapy with Jinja2 and JSON
    Install scrapy (Offical website) either using pip or conda (Follow for detailed instructions):. - Source: dev.to / 11 months ago
  • Analyzing Svenskalag Data using DBT and DuckDB
    Using Scrapy I fetched the data needed (activities and attendance). Scrapy handled authentication using a form request in a very simple way:. - Source: dev.to / 12 months ago
  • Scrapy Vs. Crawlee
    Scrapy is an open-source Python-based web scraping framework that extracts data from websites. With Scrapy, you create spiders, which are autonomous scripts to download and process web content. The limitation of Scrapy is that it does not work very well with JavaScript rendered websites, as it was designed for static HTML pages. We will do a comparison later in the article about this. - Source: dev.to / about 1 year ago
  • What is SERP? Meaning, Use Cases and Approaches
    While there is no specific library for SERP, there are some web scraping libraries that can do the Google Search Page Ranking. One of them which is quite famous is Scrapy - It is a fast high-level web crawling and web scraping framework, used to crawl websites and extract structured data from their pages. It offers rich developer community support and has been used by more than 50+ projects. - Source: dev.to / over 1 year ago
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What are some alternatives?

When comparing Webix DataTable and Scrapy, you can also consider the following products

AG Grid - The best HTML5 datagrid in the world

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

ZingGrid - Built using web components, ZingGrid is a fully-featured, native solution for interactive, mobile-friendly JavaScript data grids and tables.

ParseHub - ParseHub is a free web scraping tool. With our advanced web scraper, extracting data is as easy as clicking the data you need.

jExcel - jExcel official website, the javascript spreadsheet. Create amazing tables with jExcel.

Octoparse - Octoparse provides easy web scraping for anyone. Our advanced web crawler, allows users to turn web pages into structured spreadsheets within clicks.

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