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ParseHub VS python xlrd

Compare ParseHub VS python xlrd and see what are their differences

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Contents:
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  2. » Videos
  3. » Reviews
  4. » Alternatives

ParseHub logo ParseHub

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

python xlrd logo python xlrd

Please use openpyxl where you can... Contribute to python-excel/xlrd development by creating an account on GitHub.
  • ParseHub Landing page
    Landing page //
    2021-09-12
  • python xlrd Landing page
    Landing page //
    2023-08-18

ParseHub features and specs

  • User-friendly Interface
    ParseHub offers a point-and-click interface that makes it easy for users to extract data from websites without needing any coding skills.
  • Advanced Features
    The tool supports complex data extraction tasks, including handling AJAX, JavaScript, infinite scroll, forms, and CAPTCHA.
  • Cross-platform Compatibility
    ParseHub is available as a web app and a desktop application, making it accessible on multiple operating systems.
  • API Integration
    ParseHub provides an API that allows for easy integration with other applications, enabling automated data extraction workflows.
  • Schedule and Automate
    Users can schedule their data extraction tasks to run at specific intervals, which is useful for keeping datasets up-to-date.
  • Cloud Storage
    Extracted data is stored in the cloud, allowing easy access and management of large datasets without consuming local storage resources.
  • Free Tier
    ParseHub offers a free tier that allows users to perform a limited number of data extraction tasks, suitable for small projects or initial testing.

Possible disadvantages of ParseHub

  • Learning Curve for Complex Tasks
    While the basic interface is user-friendly, advanced data extraction tasks may require a steep learning curve to master.
  • Monthly Limits
    The free tier and lower-tier plans have limits on the number of tasks and the amount of data that can be extracted per month, which could constrain heavy users.
  • Pricing
    Higher-tier plans can become expensive, especially for businesses that require extensive data extraction capabilities.
  • Performance Issues
    Users have reported occasional performance issues and bugs when dealing with very large or complex websites, which can affect the reliability of the data extraction processes.
  • Limited Export Formats
    While ParseHub supports common formats like CSV, JSON, and Excel, it lacks support for some specialized or less common file formats.
  • Customer Support
    Some users have reported that customer support can be slow to respond to issues, which could be problematic for time-sensitive projects.
  • Privacy Concerns
    Since the data extraction occurs on ParseHub's servers, there could be privacy concerns related to the handling of sensitive or proprietary data.

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.

ParseHub videos

+ Add

ParseHub Tutorial: Scrape Ratings and Reviews from a Website

More videos:

  • Tutorial - ParseHub Tutorial: Scraping Product Details from Amazon

python xlrd videos

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Category Popularity

0-100% (relative to ParseHub and python xlrd)

ParseHub

python xlrd

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

ParseHub Reviews

Best Data Scraping Tools
Parsehub is a fantastic tool for people who want to extract data from websites without coding. It is used widely by data analysts, journalists, data scientists, and many fields. Parse Hub is easier to use; you can click on the data that you are working on to build a web scraper, which then exports the data in excel format or JSON.
Source: pamelaewallaceu.medium.com

python xlrd Reviews

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Social recommendations and mentions

Based on our record, ParseHub should be more popular than python xlrd. It has been mentiond 3 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.

ParseHub mentions (3)

  • Home Depot price data using IMPORTXML?
    I've heard some folks have success with "parsehub.com", though I once tried it for a project and found it a bit intimidating... Source: over 3 years ago
  • Free for dev - list of software (SaaS, PaaS, IaaS, etc.)
    Parsehub.com — Extract data from dynamic sites, turn dynamic websites into APIs, 5 projects free. - Source: dev.to / almost 4 years ago
  • Turn any website into an API with no code
    Parsehub is a powerful web scraping GUI tool for efficient fetching and manipulating data from any webpage. It helps you create an API output for a given website. You can even sanitize your content by using regex or replace function. So the input is a URL and the output is a structured json file. - Source: dev.to / about 4 years ago

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

What are some alternatives?

When comparing ParseHub and python xlrd, you can also consider the following products

import.io - Import. io helps its users find the internet data they need, organize and store it, and transform it into a format that provides them with the context they need.

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

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

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

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

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.

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