Software Alternatives & Reviews

NumPy VS Webpack

Compare NumPy VS Webpack and see what are their differences

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python

Webpack logo Webpack

Webpack is a module bundler. Its main purpose is to bundle JavaScript files for usage in a browser, yet it is also capable of transforming, bundling, or packaging just about any resource or asset.
  • NumPy Landing page
    Landing page //
    2023-05-13
  • Webpack Landing page
    Landing page //
    2023-06-13

NumPy videos

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

Webpack videos

Learn Webpack - Full Tutorial for Beginners

More videos:

  • Review - Core Concepts of Webpack
  • Review - Learn Webpack Pt. 6: Cache Busting and Plugins

Category Popularity

0-100% (relative to NumPy and Webpack)
Data Science And Machine Learning
Web Application Bundler
0 0%
100% 100
Data Science Tools
100 100%
0% 0
JS Build Tools
0 0%
100% 100

User comments

Share your experience with using NumPy and Webpack. 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 NumPy and Webpack

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.
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

Webpack Reviews

Rollup v. Webpack v. Parcel
Tool Prod Build Time One Prod Build Time Two Prod Build Time Three Prod Build Time Avg Parcel 738.509 s 35.364 s 35.592 s 269.82 avg s Rollup 0.712 s 0.665 s 0.714 s 0.697 avg s Webpack 3.636 s 3.805 s 4.305 s 3.915 avg s
Source: x-team.com
If you’ve ever configured Webpack, Parcel will blow your mind!
document.body.className = document.body.className.replace(/(^|\s)is-noJs(\s|$)/, "$1is-js$2")HomepageHomepageJavascriptBecome a memberSign inGet startedIf you’ve ever configured Webpack, Parcel will blow your mind!And how to hit the ground running with Parcel.Ibrahim ButtBlockedUnblockFollowFollowingMar 16, 2018Click here to share this article on LinkedIn »Zero...
Source: medium.com
First impressions with Parcel JS
From first impressions and experience, my take currently would be as follows. Webpack is generally going to be more flexible. It also places a bit more power in the developers hands to make bundling happen exactly as desired. That isn’t to say you shouldn’t use Parcel though. Where Parcel excels is the fact you don’t configure it. You will still need to configure plugins for...
Source: codeburst.io
Parcel vs webpack - Jakob Lind
Webpack is the stable choice. You will not get fired for picking webpack. But you don’t get as much stuff for free such as optimized bundles, and code splitting.

Social recommendations and mentions

Based on our record, Webpack should be more popular than NumPy. It has been mentiond 220 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 (107)

  • Element-wise vs Matrix vs Dot multiplication
    In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication. - Source: dev.to / about 2 months ago
  • JSON in data science projects: tips & tricks
    Data science projects often use numpy. However, numpy objects are not JSON-serializable and therefore require conversion to standard python objects in order to be saved:. - Source: dev.to / about 2 months ago
  • Introducing Flama for Robust Machine Learning APIs
    Numpy: A library for scientific computing in Python. - Source: dev.to / 5 months ago
  • A Comprehensive Guide to NumPy Arrays
    Python has become a preferred language for data analysis due to its simplicity and robust library ecosystem. Among these, NumPy stands out with its efficient handling of numerical data. Let’s say you’re working with numbers for large data sets—something Python’s native data structures may find challenging. That’s where NumPy arrays come into play, making numerical computations seamless and speedy. - Source: dev.to / 6 months ago
  • Beginning Python: Project Management With PDM
    A majority of software in the modern world is built upon various third party packages. These packages help offload work that would otherwise be rather tedious. This includes interacting with cloud APIs, developing scientific applications, or even creating web applications. As you gain experience in python you'll be using more and more of these packages developed by others to power your own code. In this example... - Source: dev.to / 7 months ago
View more

Webpack mentions (220)

  • Practical and Beginner friendly guide for speeding up your web-apps
    There are various tools available that manage the size of bundled assets. We are going to use the example of a popular and widely used bundler named Webpack, and practically look at many of the optimization techniques it offers. - Source: dev.to / 3 days ago
  • JS Toolbox 2024: Essential Picks for Modern Developers Series Overview
    In part 3 We jump into the world of bundlers, comparing webpack, esbuild, vite, and parcel 2. This section aims to guide developers through each bundler, focusing on their performance, compatibility, and ease of use. - Source: dev.to / 2 months ago
  • Webpack: The Web Module Bundler
    Thats all about Webpack Basic, there are lots of feature of webpack, You can check here: https://webpack.js.org/. - Source: dev.to / 2 months ago
  • How to improve page load speed and response times: A comprehensive guide
    Many web pages use CSS and JavaScript files to handle various features and styles. Each file, however, requires a separate HTTP request, which can slow down page loading. Concatenation comes into play here. It involves combining multiple CSS or JavaScript files into a single file. As a result, pages load faster, reducing the time spent requesting individual files. Gulp, Grunt, and Webpack are some of the tools... - Source: dev.to / 2 months ago
  • Build a Vite 5 backend integration with Flask
    Once you build a simple Vite backend integration, try not to complicate Vite's configuration unless you absolutely must. Vite has become one of the most popular bundlers in the frontend space, but it wasn't the first and it certainly won't be the last. In my 7 years of building for the web, I've used Grunt, Gulp, Webpack, esbuild, and Parcel. Snowpack and Rome came-and-went before I ever had a chance to try them.... - Source: dev.to / 3 months ago
View more

What are some alternatives?

When comparing NumPy and Webpack, 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.

npm - npm is a package manager for Node.

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

rollup.js - Rollup is a module bundler for JavaScript which compiles small pieces of code into a larger piece such as application.

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

Parcel - Blazing fast, zero configuration web application bundler