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wkhtmltopdf VS NumPy

Compare wkhtmltopdf VS NumPy and see what are their differences

DocRaptor
As the only API powered by the Prince HTML-to-PDF engine, DocRaptor provides the best support for complex PDFs with powerful support for headers, page breaks, page numbers, flexbox, watermarks, accessible PDFs, and much more sponsored
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wkhtmltopdf logo wkhtmltopdf

wkhtmltopdf is an open source (LGPL) command line tools to render HTML into PDF and various image...

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • wkhtmltopdf Landing page
    Landing page //
    2021-10-21
  • NumPy Landing page
    Landing page //
    2023-05-13

wkhtmltopdf features and specs

  • HTML to PDF Conversion
    wkhtmltopdf allows for the conversion of HTML and CSS content into PDF documents, making it easier to generate reports, invoices, and other necessary documentation from web content.
  • Open Source
    As an open-source tool, wkhtmltopdf is free to use, modify, and distribute, making it accessible to developers with varying budgets.
  • Cross-Platform
    wkhtmltopdf is available on multiple operating systems, including Windows, macOS, and Linux, offering flexibility for developers working in different environments.
  • High Quality PDFs
    It utilizes the WebKit rendering engine, which ensures that the PDFs generated maintain high fidelity to the original HTML content.
  • Command Line Interface
    The tool provides a robust command-line interface that allows for scripting and automation, which can greatly enhance productivity.
  • Supports Complex Layouts
    wkhtmltopdf can handle complex layouts including CSS, JavaScript, and media queries, making it suitable for intricate designs.

Possible disadvantages of wkhtmltopdf

  • Large Files
    Generated PDF files can be quite large, especially if the HTML content includes heavy use of images and other media.
  • Resource Intensive
    wkhtmltopdf can be resource-intensive, requiring significant CPU and memory, which might be a concern for high-volume or real-time generation needs.
  • Limited Support for New Web Standards
    As an older tool, it sometimes struggles to keep up with the latest web standards and features, which may lead to partial rendering of more modern web content.
  • Steep Learning Curve
    The tool has many options and configurations, which can be overwhelming for beginners or those not familiar with command-line operations.
  • Dependency on System Libraries
    Installation and operation can be complex due to dependencies on specific system libraries, which can complicate deployment and maintenance.
  • Lack of Official Support
    Being an open-source project, it lacks professional support, which means that users may need to rely on community forums and resources for troubleshooting.

NumPy features and specs

  • Performance
    NumPy operations are executed with highly optimized C and Fortran libraries, making them significantly faster than standard Python arithmetic operations, especially for large datasets.
  • Versatility
    NumPy supports a vast range of mathematical, logical, shape manipulation, sorting, selecting, I/O, and basic linear algebra operations, making it a versatile tool for scientific and numeric computing.
  • Ease of Use
    NumPy provides an intuitive, easy-to-understand syntax that extends Python's ability to handle arrays and matrices, lowering the barrier to performing complex scientific computations.
  • Community Support
    With a large and active community, NumPy offers extensive documentation, tutorials, and support for troubleshooting issues, as well as continuous updates and enhancements.
  • Integrations
    NumPy integrates seamlessly with other libraries in Python's scientific stack like SciPy, Matplotlib, and Pandas, facilitating a streamlined workflow for data science and analysis tasks.

Possible disadvantages of NumPy

  • Memory Consumption
    NumPy arrays can consume large amounts of memory, especially when working with very large datasets, which can become a limitation on systems with limited memory capacity.
  • Learning Curve
    For users new to scientific computing or coming from different programming backgrounds, understanding the intricacies of NumPy's operations and efficient usage can take time and effort.
  • Limited GPU Support
    NumPy primarily runs on the CPU and doesn't natively support GPU acceleration, which can be a disadvantage for extremely compute-intensive tasks that could benefit from parallel processing.
  • Dependency on Python
    Since NumPy is a Python library, it depends on the Python runtime environment. This can be a limitation in environments where Python is not the primary language or isn't supported.
  • Indexing Complexity
    Although NumPy's slicing and indexing capabilities are powerful, they can sometimes be complex or unintuitive, especially for multi-dimensional arrays, leading to potential errors and confusion.

Analysis of wkhtmltopdf

Overall verdict

  • Yes, wkhtmltopdf is considered a good option for HTML to PDF conversion, especially if you need precise rendering and support for modern web standards. However, it may require some tweaking and does come with limitations on complex JavaScript and dynamic content.

Why this product is good

  • wkhtmltopdf is a popular tool for converting HTML documents into PDF format. It is favored because it uses the WebKit rendering engine, which ensures that the PDFs closely resemble the web page's appearance in a modern browser. This allows for high-quality and accurate conversions, including support for complex layouts, CSS, and JavaScript.

Recommended for

  • Developers and teams needing to generate PDFs from HTML content in web applications.
  • Organizations requiring batch processing of HTML documents into PDFs.
  • Situations where accurate reproduction of web page styling in PDF format is essential.

Analysis of NumPy

Overall verdict

  • Yes, NumPy is considered good. It is a foundational library in the Python ecosystem for numerical computing and is used globally by researchers, engineers, and data scientists.

Why this product is good

  • NumPy is widely regarded as a good library because it offers fast, flexible, and efficient array handling that is integral to scientific computing in Python. It provides tools for integrating C/C++ and Fortran code, useful linear algebra, random number capabilities, and a vast collection of mathematical functions. Its array broadcasting capabilities and versatility make complex mathematical computations straightforward.

Recommended for

  • Scientists and researchers working with large-scale scientific computations.
  • Data scientists engaged in data analysis and manipulation.
  • Engineers and developers needing performance-optimized mathematical computations.
  • Educators and students in STEM fields.

wkhtmltopdf videos

+ Add

✔️ Como instalar wkhtmltopdf ubuntu (compatible con cualquier odoo 11) Facil y rapido 2018

NumPy videos

+ Add

Learn NUMPY in 5 minutes - BEST Python Library!

More videos:

  • Review - Python for Data Analysis by Wes McKinney: Review | Learn python, numpy, pandas and jupyter notebooks
  • Review - Effective Computation in Physics: Review | Learn python, numpy, regular expressions, install python

Category Popularity

0-100% (relative to wkhtmltopdf and NumPy)

wkhtmltopdf

NumPy

HTML To PDF
100 100%
HTML To PDF
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
PDF Conversion API
100 100%
PDF Conversion API
0% 0
Data Science Tools
0 0%
Data Science Tools
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 wkhtmltopdf and NumPy

wkhtmltopdf Reviews

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NumPy Reviews

25 Python Frameworks to Master
SciPy provides a collection of algorithms and functions built on top of the NumPy. It helps to perform common scientific and engineering tasks such as optimization, signal processing, integration, linear algebra, and more.
Source: kinsta.com
Top 8 Image-Processing Python Libraries Used in Machine Learning
Scipy is used for mathematical and scientific computations but can also perform multi-dimensional image processing using the submodule scipy.ndimage. It provides functions to operate on n-dimensional Numpy arrays and at the end of the day images are just that.
Source: neptune.ai
Top Python Libraries For Image Processing In 2021
Numpy It is an open-source python library that is used for numerical analysis. It contains a matrix and multi-dimensional arrays as data structures. But NumPy can also use for image processing tasks such as image cropping, manipulating pixels, and masking of pixel values.
Source: www.analyticsvidhya.com
4 open source alternatives to MATLAB
NumPy is the main package for scientific computing with Python (as its name suggests). It can process N-dimensional arrays, complex matrix transforms, linear algebra, Fourier transforms, and can act as a gateway for C and C++ integration. It's been used in the world of game and film visual effect development, and is the fundamental data-array structure for the SciPy Stack,...
Source: opensource.com

Social recommendations and mentions

Based on our record, NumPy should be more popular than wkhtmltopdf. It has been mentiond 122 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.

wkhtmltopdf mentions (39)

  • Introducing fulgur: a blazing fast HTML-to-PDF engine in Rust — no browser required
    For years, wkhtmltopdf was the default. It's now archived, and the WebKit version it bundles has been frozen for years. Modern CSS doesn't really land there. - Source: dev.to / 4 months ago
  • DinkToPdf Alternatives: IronPDF for C# HTML to PDF
    Add the native libwkhtmltox binary to your output directory (Windows/Linux/macOS versions available from wkhtmltopdf.org). - Source: dev.to / about 1 year ago
  • Using ColdFusion and Xpdf to extract PDF metadata
    Recently when using CFPDF to personalize an existing single-page cover PDF by adding a watermark, I needed to know both the dimensions & rotation of the preexisting PDF so I could generate a PDF (using WKHTMLTOPDF) with the correct watermark placement. I decided to use Xpdf's pdfinfo.exe to extract this information primarily so that the output would be consistent regardless of which version of CFML platform is... - Source: dev.to / over 1 year ago
  • PDF Generation, Bloat and Optimization
    WKHTMLTOPDF (LGPLv3; portable) tends to be faster and generate smaller PDFs. It can also run concurrently and generate PDFs in the background without using a ColdFusion thread or impacting the Java heap memory. Download. - Source: dev.to / over 1 year ago
  • Hack WKHTMLTOPDF PDF to enable Adobe Acrobat Field Editing
    I recently integrated the auto-generation of survey results into a downloadable PDF using ColdFusion and WKHTMLTOPDF 0.12.6. Our client provided a pre-generated PDF cover page with some editable fields that we prepended to the PDF using PDFtk. Unfortunately, all auto-generated bookmarks became unusable after cover page is prepended. - Source: dev.to / almost 2 years ago
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NumPy mentions (122)

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What are some alternatives?

When comparing wkhtmltopdf and NumPy, you can also consider the following products

PDFShift - Convert any HTML documents to high-fidelity PDF using a single POST request

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

DocRaptor - As the only API powered by the Prince HTML-to-PDF engine, DocRaptor provides the best support for complex PDFs with powerful support for headers, page breaks, page numbers, flexbox, watermarks, accessible PDFs, and much more

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

WeasyPrint - WeasyPrint is a visual rendering engine for HTML and CSS that can export to PDF.

OpenCV - OpenCV is the world's biggest computer vision library

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