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StackBlitz VS NumPy

Compare StackBlitz VS NumPy and see what are their differences

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StackBlitz logo StackBlitz

Online VS Code Editor for Angular and React

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • StackBlitz Landing page
    Landing page //
    2023-09-20
  • NumPy Landing page
    Landing page //
    2023-05-13

StackBlitz features and specs

  • Speed
    StackBlitz is known for its quick load times and fast editing capabilities, making it ideal for rapid development and testing.
  • Ease of Use
    The interface is intuitive and user-friendly, allowing developers to get started quickly without a steep learning curve.
  • Zero-Setup
    Users can write, compile, and run code directly in the browser without any setup or configuration required.
  • Integrations
    StackBlitz integrates seamlessly with GitHub, allowing for easy import and export of repositories.
  • WebContainers
    StackBlitz uses WebContainers to run Node.js applications in the browser, providing a near-native development experience.
  • Collaboration
    Real-time collaboration features allow multiple users to work on the same project simultaneously, similar to Google Docs.

Possible disadvantages of StackBlitz

  • Limited Plugins
    Unlike traditional IDEs like VSCode or IntelliJ, StackBlitz has a limited ecosystem of plugins and extensions.
  • Online Dependency
    StackBlitz requires an internet connection to function, which can be a limitation for developers who need to work offline.
  • Performance
    For very large projects or those requiring extensive computational resources, performance may degrade compared to local development environments.
  • Mobile Accessibility
    While StackBlitz is accessible on mobile devices, the user experience is not as optimized as it is on desktop browsers.
  • Limited Framework Support
    Although StackBlitz supports many popular frameworks, it doesn't support all frameworks or versions, which could be limiting for some projects.
  • Storage and Persistence
    Files and data are stored in the cloud, which might raise concerns around data privacy and persistence for some users.

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.

StackBlitz videos

+ Add

StackBlitz - Online Code Editor For Angular and React - Introduction

More videos:

  • Review - Using Stackblitz for html css javascript, make websites, web development

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 StackBlitz and NumPy)

StackBlitz

NumPy

Text Editors
100 100%
Text Editors
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Programming
100 100%
Programming
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

User comments

Share your experience with using StackBlitz 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 StackBlitz and NumPy

StackBlitz Reviews

  1. Guest
    Has almost everything I need

    I've started using this as my main IDE for new projects when I'm trying things out. If it keeps getting better at the rate it has been, it'll be even better than coding locally.

    🏁 Competitors: replit
    👍 Pros:    Easy to get started and operate|Fast|Supports common extensions|Works with most npm packages
    👎 Cons:    Still not as good as local development|Can be hard to debug|Build times can be slower than local
12 Best Online IDE and Code Editors to Develop Web Applications
All applications created on StackBlitz also get deployed automatically on their servers! So, this Angular toy app I just created is hosted automatically on https://angular-yvyi2j.stackblitz.io/. Most likely, the URL is still working (will load slowly, though, as you’d expect when hosted for free)!
Source: geekflare.com
Best Online Code Editors For Web Developers
StackBlitz claims to allow you to code the future in your browser. And after trying it, I’m confident you’ll agree that this web application is extremely useful for coders.
Source: techarge.in

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

NumPy might be a bit more popular than StackBlitz. We know about 119 links to it since March 2021 and only 109 links to StackBlitz. 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.

StackBlitz mentions (109)

  • AutoView - turning your blueprint into UI components (AI Code Generator)
    In the code editor tab (powered by StackBlitz), navigate to the env.ts file and enter your OpenAI key. Run npm run generate in the terminal to see how @autoview generates TypeScript frontend code from example schemas derived from both TypeScript types and OpenAPI documents. - Source: dev.to / about 1 month ago
  • 22 Unique Developer Resources You Should Explore
    URL: https://stackblitz.com What it does: An online IDE for coding, previewing, and deploying web apps instantly. Why it's great: Rapidly spin up projects without local setups — great for experimentation. - Source: dev.to / 4 months ago
  • React Native Online Compiler: Compare the Top 5 Platforms for Your Development Needs
    StackBlitz for offline-friendly development. - Source: dev.to / 4 months ago
  • Bussin': Database as a Message Bus
    Stackblitz is our backend in this case. Here we define our services and their subscriptions and we publish relevant events. The implementation of this pattern (the how) is less important than what is accomplished:. - Source: dev.to / 5 months ago
  • Angular resources I often return to
    Stackblitz Again, not an Angular resource but this tool is used even by the Angular developers. You can set up an instant dev environment for angular. Most official Material examples have a _Stackblitz _link like the Highlighting the first autocomplete function. Besides creating a new environment, you can fork existing onces, test your costumizations and eventually implement the results in your own code. I like... - Source: dev.to / 6 months ago
View more

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 StackBlitz and NumPy, you can also consider the following products

CodePen - A front end web development playground.

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

CodeSandbox - Online playground for React

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

replit - Code, create, andlearn together. Use our free, collaborative, in-browser IDE to code in 50+ languages — without spending a second on setup.

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

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