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JavaScript VS NumPy

Compare JavaScript VS NumPy and see what are their differences

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JavaScript logo JavaScript

Lightweight, interpreted, object-oriented language with first-class functions

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • JavaScript Landing page
    Landing page //
    2023-08-05

We recommend LibHunt JavaScript for discovery and comparisons of trending JavaScript projects.

  • NumPy Landing page
    Landing page //
    2023-05-13

JavaScript features and specs

  • Wide Browser Support
    JavaScript is supported by all modern web browsers without the need for any plugins, making it highly versatile for client-side scripting.
  • Asynchronous Programming
    JavaScript supports asynchronous programming with features like callbacks, Promises, and async/await, which helps in efficiently handling tasks such as HTTP requests.
  • Rich Ecosystem and Libraries
    The JavaScript ecosystem includes a vast amount of libraries and frameworks like React, Angular, Vue, and Node.js, which streamline development processes.
  • Community Support
    JavaScript has a large and active community, providing extensive resources, documentation, and forums for troubleshooting and development advice.
  • Event-Driven
    The language is inherently event-driven, making it suitable for developing interactive web applications that react to user inputs.
  • Full-Stack Development
    With the advent of Node.js, JavaScript can be used for both client-side and server-side development, enabling full-stack development using a single language.

Possible disadvantages of JavaScript

  • Security Issues
    Being an interpreted language that runs in the browser, JavaScript code is visible to the user, making it susceptible to security risks such as Cross-Site Scripting (XSS).
  • Browser Compatibility
    While JavaScript itself is widely supported, different browsers may implement JavaScript functions and standards differently, leading to compatibility issues.
  • Performance
    JavaScript is generally slower than compiled languages such as C++ or Java. Heavy computations can lead to performance bottlenecks.
  • Single Inheritance
    JavaScript uses prototypal inheritance instead of classical inheritance, which can be confusing for developers coming from object-oriented programming backgrounds.
  • Dynamic Typing
    JavaScript's dynamic typing can lead to runtime errors that are hard to debug, as variable types are checked at runtime rather than during compilation.
  • Fragmentation
    The ecosystem has many competing libraries, frameworks, and tools, which can make it overwhelming for developers to choose the right technologies for their projects.

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.

JavaScript videos

+ Add

Learn JavaScript in 7 minutes | Create Interactive Websites | Code in 5

More videos:

  • Review - Top 10 JavaScript Interview Questions
  • Review - Learn JavaScript in 12 Minutes

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 JavaScript and NumPy)

JavaScript

NumPy

Programming Language
100 100%
Programming Language
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
OOP
100 100%
OOP
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

User comments

Share your experience with using JavaScript and NumPy. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare JavaScript and NumPy

JavaScript Reviews

Top 10 Rust Alternatives
In simple words, the main goal of JavaScript is to develop web pages and is used for authentication procedures. Some of the pros of using JavaScript as an alternative to Rust are follows.
Source: blog.back4app.com
Top 15 jQuery Alternatives To Know
ExtJS, as the name suggests, stands for Extended JavaScript. As an offering from Sencha, it depends on YahooUserInterface. ExtJS helps in creating data intensified HTML5 apps with JavaScript. It consists of a huge collection of customizable and high-performance widgets that assist in creating cross-platform mobile and web apps, for any type of modernized device.
Source: www.spec-india.com
The 10 Best Programming Languages to Learn Today
JavaScript skills are always in high demand – most of the world's top websites and apps rely on JavaScript in one way or another. Plus, JavaScript is a great springboard for learning more complex programming languages.
Source: ict.gov.ge

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 seems to be more popular. It has been mentiond 119 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.

JavaScript mentions (0)

We have not tracked any mentions of JavaScript yet. Tracking of JavaScript recommendations started around Mar 2021.

NumPy mentions (119)

  • Building an AI-powered Financial Data Analyzer with NodeJS, Python, SvelteKit, and TailwindCSS - Part 0
    The AI Service will be built using aiohttp (asynchronous Python web server) and integrates PyTorch, Hugging Face Transformers, numpy, pandas, and scikit-learn for financial data analysis. - Source: dev.to / 3 months ago
  • F1 FollowLine + HSV filter + PID Controller
    This library provides functions for working in domain of linear algebra, fourier transform, matrices and arrays. - Source: dev.to / 7 months ago
  • Intro to Ray on GKE
    The Python Library components of Ray could be considered analogous to solutions like numpy, scipy, and pandas (which is most analogous to the Ray Data library specifically). As a framework and distributed computing solution, Ray could be used in place of a tool like Apache Spark or Python Dask. It’s also worthwhile to note that Ray Clusters can be used as a distributed computing solution within Kubernetes, as... - Source: dev.to / 8 months ago
  • Streamlit 101: The fundamentals of a Python data app
    It's compatible with a wide range of data libraries, including Pandas, NumPy, and Altair. Streamlit integrates with all the latest tools in generative AI, such as any LLM, vector database, or various AI frameworks like LangChain, LlamaIndex, or Weights & Biases. Streamlit’s chat elements make it especially easy to interact with AI so you can build chatbots that “talk to your data.”. - Source: dev.to / 9 months ago
  • A simple way to extract all detected objects from image and save them as separate images using YOLOv8.2 and OpenCV
    The OpenCV image is a regular NumPy array. You can see it shape:. - Source: dev.to / 9 months ago
View more

What are some alternatives?

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

Python - Python is a clear and powerful object-oriented programming language, comparable to Perl, Ruby, Scheme, or Java.

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

Java - A concurrent, class-based, object-oriented, language specifically designed to have as few implementation dependencies as possible

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

Rust - A safe, concurrent, practical language

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

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