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Violentmonkey VS NumPy

Compare Violentmonkey VS NumPy and see what are their differences

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Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

Violentmonkey logo Violentmonkey

Violentmonkey is a userscript manager to support running userscripts in web pages.

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • Violentmonkey Landing page
    Landing page //
    2023-10-16
  • NumPy Landing page
    Landing page //
    2023-05-13

Violentmonkey features and specs

  • Free and Open Source
    Violentmonkey is freely available to use and the source code is open for anyone to inspect, modify, and contribute to. This ensures transparency and community-driven development.
  • Active Development
    The project is actively maintained and updated, which means that bugs are fixed promptly and new features are regularly added.
  • Cross-Browser Support
    Violentmonkey is compatible with multiple browsers including Chrome, Firefox, Microsoft Edge, and Opera, providing flexibility to users regardless of their browser preference.
  • User Script Manager
    It allows users to manage and run custom scripts to enhance web pages, providing extensive customization options for a tailored browsing experience.
  • Easy Backup and Sync
    Features like backup and sync allow users to easily transfer their settings and scripts across different devices, ensuring a consistent experience.

Possible disadvantages of Violentmonkey

  • Learning Curve
    For new users, especially those not familiar with scripting, there might be a learning curve involved in understanding how to write and manage scripts effectively.
  • Security Risks
    As with any tool that runs third-party scripts, there is a potential risk for malicious scripts that can compromise user security and privacy if not properly vetted.
  • Dependency on Community Scripts
    The quality and functionality of Violentmonkey heavily rely on the availability and maintenance of user-submitted scripts, which can vary in quality.
  • Browser Performance Impact
    Running multiple or poorly optimized scripts can affect browser performance by increasing loading times and resource consumption.

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 Violentmonkey

Overall verdict

  • Yes, Violentmonkey is a reliable and efficient userscript manager that caters to the needs of users who want to customize their web browsing experience.

Why this product is good

  • Violentmonkey is considered a good choice for users looking to manage userscripts on their web browsers. It provides a clean and straightforward interface, supports a wide range of script sources, and is compatible with multiple browsers including Chrome, Firefox, and Edge. Moreover, it is open-source, allowing for community contributions and transparency.

Recommended for

  • Tech-savvy users interested in enhancing their web browser functionality through userscripts.
  • Developers who want to test userscripts in a flexible environment.
  • Users looking for an open-source alternative to other popular script managers like Greasemonkey or Tampermonkey.

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.

Violentmonkey videos

+ Add

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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 Violentmonkey and NumPy)

Violentmonkey

NumPy

Browser Extensions
100 100%
Browser Extensions
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Dark Mode
100 100%
Dark Mode
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 Violentmonkey and NumPy

Violentmonkey 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 Violentmonkey. 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.

Violentmonkey mentions (46)

  • Show HN: UserScript to manually choose model for ChatGPT website
    - GPT 4o mini, so you can save your 4o calls for more complex queries https://github.com/altbdoor/userscripts/raw/master/force-gpt3.user.js. - Source: Hacker News / almost 2 years ago
  • If your Firefox suddenly started to hang or become extremely slow today, check if you have tampermonkey 5.0. Disable it for now as it seems to be the culprit.
    Since Tampermonkey seems to be misbehaving, consider using Violentmonkey. Source: over 2 years ago
  • Current plan for the flag
    Step 1Install violentmonkey (or your favorite user script manager). Source: almost 3 years ago
  • Andrej Karpathy โ€“ State of GPT ( At MSBuild 2023)
    Sounds like a good violent monkey [0] script for you do this weekend. :) [0] https://violentmonkey.github.io/. - Source: Hacker News / about 3 years ago
  • Auto expand for reports button in modqueue
    Toolbox is great, but if that is all you really need, here's this! You can copy and paste this as a new script to use in ViolentMonkey [AMO] or whatever script manager you use. Source: about 3 years ago
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NumPy mentions (122)

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What are some alternatives?

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

Greasemonkey - Customize the way a web page displays or behaves, by using small bits of JavaScript.

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

Tampermonkey - Greasemonkey compatible script manager.

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

Greasy Fork - A site for user scripts.

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

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