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Jspreadsheet VS Scrapy

Compare Jspreadsheet VS Scrapy and see what are their differences

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Piloterr web scraping API handles headless browsers, rotates proxies for you, and offers a library featured
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Contents:
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  3. » Reviews
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Jspreadsheet logo Jspreadsheet

JavaScript Data Grid Plugin with Advanced Spreadsheet-like Controls

Scrapy logo Scrapy

Scrapy | A Fast and Powerful Scraping and Web Crawling Framework
Not present
  • Scrapy Landing page
    Landing page //
    2021-10-11

Jspreadsheet features and specs

  • User-Friendly Interface
    Jspreadsheet offers an intuitive and easy-to-use interface reminiscent of traditional spreadsheet applications like Excel, making it accessible for users familiar with spreadsheet tools.
  • Customizability
    The software is highly customizable with a comprehensive API, allowing developers to tailor the spreadsheet to their specific needs, including custom formulas, cell formatting, and more.
  • Lightweight and Fast
    Jspreadsheet is lightweight, which ensures fast loading and processing speeds, making it ideal for applications where performance is crucial.
  • Cross-Browser Compatibility
    The tool is designed to work seamlessly across different browsers, ensuring a consistent experience regardless of the user's choice of browser.
  • Integration Capabilities
    Jspreadsheet can be easily integrated with other web applications and libraries, providing flexibility in embedding and extending functionalities in various projects.

Possible disadvantages of Jspreadsheet

  • Limited Complex Features
    Compared to full-fledged spreadsheet software like Excel, Jspreadsheet might lack some advanced features necessary for complex data manipulation and analysis.
  • Learning Curve for Customization
    While it offers extensive customization options, users may encounter a learning curve when trying to implement advanced features or integrations.
  • Dependency on Developers
    Non-technical users might depend heavily on developers to customize and extend the capabilities of Jspreadsheet to meet specific requirements.
  • Mobile Experience
    Although it is possible to use Jspreadsheet on mobile devices, the experience might not be as polished or user-friendly as on desktop browsers.
  • Licensing for Full Features
    Some advanced features may be behind a paywall, requiring users to purchase a license to access the full range of capabilities offered by Jspreadsheet.

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.

Jspreadsheet 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 Jspreadsheet and Scrapy)

Jspreadsheet

Scrapy

Data Grid
100 100%
Data Grid
0% 0
Web Scraping
0 0%
Web Scraping
100% 100
Spreadsheets
100 100%
Spreadsheets
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 Jspreadsheet and Scrapy

Jspreadsheet 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 Jspreadsheet. While we know about 97 links to Scrapy, we've tracked only 1 mention of Jspreadsheet. 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.

Jspreadsheet mentions (1)

  • Js spreadsheet component
    One thing I often use is those Excel tables we use to organize data. The Jspreadsheet does something very similar, but directly in the browser. You don’t need to install anything, just open and use it. It's perfect for anyone who needs to organize information in a simple and practical way. - Source: dev.to / 9 months 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 Jspreadsheet and Scrapy, you can also consider the following products

Handsontable - JavaScript Spreadsheet

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

AG Grid - The best HTML5 datagrid in the world

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

dhtmlxSpreadsheet - dhtmlxSpreadsheet - JavaScript and PHP spreadsheet software.

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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