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python xlrd VS Scrapy

Compare python xlrd VS Scrapy and see what are their differences

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python xlrd logo python xlrd

Please use openpyxl where you can... Contribute to python-excel/xlrd development by creating an account on GitHub.

Scrapy logo Scrapy

Scrapy | A Fast and Powerful Scraping and Web Crawling Framework
  • python xlrd Landing page
    Landing page //
    2023-08-18
  • Scrapy Landing page
    Landing page //
    2021-10-11

python xlrd features and specs

  • Simplicity
    xlrd provides a straightforward and easy-to-use API for reading Excel files, making it accessible for beginners and quick implementations.
  • Widely Used
    xlrd has been a popular choice for handling Excel files in Python, which means there is a lot of available documentation and community support.
  • Efficient Reading
    It is optimized for reading data from Excel files without loading entire data into memory, which is beneficial for handling large files.

Possible disadvantages of python xlrd

  • No Write Support
    xlrd is designed solely for reading, and it does not support writing or modifying Excel files.
  • Limited to Older Excel Formats
    With version 2.0 and above, xlrd only supports the older .xls Excel file format and does not support .xlsx files.
  • Deprecated Features
    Due to changes in dependencies and updates to Excel formats, some features in xlrd have become deprecated or removed, which can limit its functionality.

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.

python xlrd videos

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Scrapy videos

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 python xlrd and Scrapy)
Development Tools
100 100%
0% 0
Web Scraping
0 0%
100% 100
Data Science And Machine Learning
Data Extraction
0 0%
100% 100

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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.

Social recommendations and mentions

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

python xlrd mentions (2)

  • I need to read multiple excel files, extract a column from each and compose a new file
    So to get this out of the way first, xlrd has less features than openpyxl and in addition only works with the old '.xls' format, not the newer '.xlsx' format. Even on the xlrd's Github repo it says: 'Please use openpyxl where you can... '. Source: about 3 years ago
  • Sending Bulk SMS using Africas Talking, Python and Excel
    There are few alternative libraries for reading and writing excel files: Pandas, Xlrd , openpyxl among others. In the end I settled for openpyxl as I had the most experience Using it and it had support for .xlsx files. - Source: dev.to / 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 / 9 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 / 10 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 / 11 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 python xlrd and Scrapy, you can also consider the following products

python docx - Create and modify Word documents with Python. Contribute to python-openxml/python-docx development by creating an account on GitHub.

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

python pillow - The friendly PIL fork (Python Imaging Library). Contribute to python-pillow/Pillow development by creating an account on GitHub.

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

bokeh python - This Python tutorial will get you up and running with Bokeh, using examples and a real-world dataset. You'll learn how to visualize your data, customize and organize your visualizations, and add interactivity.

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