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NumPy VS Backbone.js

Compare NumPy VS Backbone.js and see what are their differences

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LibHunt tracks mentions of software libraries on relevant social networks. Based on that data, you can find the most popular projects and their alternatives. featured
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Contents:
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NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python

Backbone.js logo Backbone.js

Give your JS App some Backbone with Models, Views, Collections, and Events
  • NumPy Landing page
    Landing page //
    2023-05-13
  • Backbone.js Landing page
    Landing page //
    2018-09-30

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.

Backbone.js features and specs

  • Lightweight
    Backbone.js is minimal and lightweight, which means it has a small footprint and adds very little overhead to your project.
  • Flexibility
    Backbone.js provides a flexible structure to developers by allowing them to build their own MVC or MVP architectures using models, views, collections, and routers.
  • Ease of Integration
    Backbone.js can be easily integrated with other libraries and frameworks, such as jQuery or underscore.js, enhancing its capabilities without much difficulty.
  • Large Community
    Backbone.js has been around for a long time, resulting in a large community and a plethora of plugins and extensions that can be leveraged.
  • Detailed Documentation
    The official site offers comprehensive documentation which includes tutorials, examples, and a detailed API reference, aiding developers to understand and utilize the library efficiently.

Possible disadvantages of Backbone.js

  • Steeper Learning Curve
    New developers might find Backbone.js difficult to learn due to its non-opinionated nature and lack of enforced structure.
  • Sparse In-Built Features
    Backbone.js provides only the basic building blocks, requiring developers to write more boilerplate code or rely on external libraries for additional functionalities.
  • Outdated
    As newer frameworks and libraries (like React, Vue, and Angular) have emerged with more robust features and better performance, Backbone.js has somewhat fallen out of favor in modern development practices.
  • Event Binding Complexity
    Managing event bindings in Backbone.js can become complex and sometimes messy in large applications, which can lead to difficult maintenance and debugging.
  • Limited Two-Way Data Binding
    Backbone.js does not provide two-way data binding out-of-the-box, unlike other frameworks such as Angular, necessitating additional code to sync views and models.

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.

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

Backbone.js videos

+ Add

Introduction to Backbone.js

More videos:

  • Review - Introduction to Backbone.js
  • Review - Backbone.js Code Review w Backbone.js Mentor Jonathon

Category Popularity

0-100% (relative to NumPy and Backbone.js)

NumPy

Backbone.js

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
JavaScript Framework
0 0%
JavaScript Framework
100% 100
Data Science Tools
100 100%
Data Science Tools
0% 0
Javascript UI Libraries
0 0%
Javascript UI Libraries
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 NumPy and Backbone.js

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

Backbone.js Reviews

20 Next.js Alternatives Worth Considering
A veteran on the scene, Backbone.js is all about giving structure to your JavaScript-heavy applications. It’s standing the test of time, enabling you to keep your data logic and display logic neatly side by side, all while being lightweight.
Source: tms-outsource.com
9 Best JavaScript Frameworks to Use in 2023
Backbone.js is based on the Model View Controller (MVC) design pattern. The library supports seven components: Models, Views, Collections, Routers, Events, Sync, and Options. Backbone.js also provides an asynchronous communication layer that allows the application to communicate with a backend service.
Source: ninetailed.io
JavaScript: What Are The Most Used Frameworks For This Language?
Backbone.JS is a lightweight JavaScript library that provides a framework for developing structured and scalable web applications. It offers a set of tools for building client-side applications that interact with RESTful APIs. Backbone.JS is well-suited for developing single-page applications (SPAs) where most of the user interface is rendered in the browser, rather than...
Source: www.bocasay.com
20 Best JavaScript Frameworks For 2023
Backbone.js is a JavaScript-based framework that connects to an API via a RESTful JSON interface. Backbone.js is known for being small and light because it only requires jQuery and one JavaScript library, Underscore.js, to use the entire library.
Source: www.lambdatest.com
Top JavaScript Frameworks For Mobile App Development
Backbone JS is a JavaScript framework based on the MVP app design. As the name suggests, it acts as a strong backbone to your project. It is lightweight in nature and hence, is considered ideal for developing single-page applications. It offers a simplistic frontend and makes the best use of JavaScript functions.
Source: medium.com

Social recommendations and mentions

Based on our record, NumPy should be more popular than Backbone.js. 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.

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 / 4 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 / 9 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 / 9 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 / 10 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 / 10 months ago
View more

Backbone.js mentions (17)

  • JavaScript Views, the Hard Way – A Pattern for Writing UI
    Https://backbonejs.org/#View There is also a github repo that has examples of MVC patterns adapted to the web platform. - Source: Hacker News / about 2 months ago
  • JavaScript evolution: From Lodash and Underscore to vanilla
    Underscore was created by Jeremy Ashkenas (the creator of Backbone.js) in 2009 to provide a set of utility functions that JavaScript lacked at the time. It was also created to work with Backbone.js, but it slowly became a favorite among developers who needed utility functions that they could just call and get stuff done with without having to worry about the inner implementations and browser compatibility. - Source: dev.to / 6 months ago
  • React is 10 years old
    Got it thanks for the context. I've read the web app and it seems to me it is just https://backbonejs.org/ re-written in Typescript and allows JSX. I'm very certain Typescript and JSX will have improved the DX for Backbone like apps, but it doesn't address all of the other issues that teams had with Backbone. e.g. Cyclical event propagation, state stored in the DOM (i.e. Appendchild is error prone in large code... - Source: Hacker News / about 2 years ago
  • Just Simply – Stop saying how simple things are in our docs
    Even further nowadays, docs are created using Docusaurus. I don't have problem with it but documentation should be good (eye) friendly than easy to write. Why not be creative while writing docs such as - Backbone.js - https://backbonejs.org Or https://backbonejs.org/docs/backbone.html as code annotation. - Source: Hacker News / about 2 years ago
  • The Emperor's New Library
    What we see, a decade ago, are that many of the "popular" libraries, frameworks, and methods, not surprisingly, have gone by the wayside, a lot that have remained in current code as difficult-to-removemodernize legacy cruft (Bower, Gulp, Grunt, Backbone, Angular 1, ...), and then we have the small minority that are still here. Some that remain have had their utility lessened/questioned by platform and language... - Source: dev.to / over 2 years ago
View more

What are some alternatives?

When comparing NumPy and Backbone.js, you can also consider the following products

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

AngularJS - AngularJS lets you extend HTML vocabulary for your application. The resulting environment is extraordinarily expressive, readable, and quick to develop.

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

ExpressJS - Sinatra inspired web development framework for node.js -- insanely fast, flexible, and simple

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

ember.js - A JavaScript framework for creating ambitious web apps

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