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Scratch VS NumPy

Compare Scratch VS NumPy and see what are their differences

LibHunt
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:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Scratch logo Scratch

Scratch is the programming language & online community where young people create stories, games, & animations.

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • Scratch Landing page
    Landing page //
    2021-10-17
  • NumPy Landing page
    Landing page //
    2023-05-13

Scratch features and specs

  • Engaging Interface
    Scratch offers a visually appealing and user-friendly interface that makes it accessible for kids and beginners to learn programming concepts.
  • Community Support
    The platform has a large and active community where users can share projects, get feedback, and collaborate with others, fostering a sense of community and support.
  • Educational Value
    Scratch is designed with a strong pedagogical foundation, helping users to develop problem-solving skills, logical thinking, and creativity.
  • Drag-and-Drop Programming
    The block-based coding in Scratch eliminates syntax errors and simplifies the process of learning programming logic, making it ideal for beginners.
  • Free to Use
    Scratch is completely free to use, which makes it accessible to a wide audience without any financial barriers.
  • Portable
    Being web-based, Scratch can be accessed from any device with an internet connection, providing ease of access and flexibility.

Possible disadvantages of Scratch

  • Limited Advanced Capabilities
    Scratch is mainly designed for beginners and might not offer the depth or complexities needed for more advanced programming projects.
  • Performance Issues
    Larger projects can sometimes become slow or unresponsive, particularly on less powerful devices.
  • Simplified Programming
    The drag-and-drop nature of Scratch, while educational, might limit exposure to the syntax and intricacies of written programming languages.
  • Internet Dependency
    Scratch primarily requires an internet connection, which could be a limitation in areas with poor connectivity.
  • Age Focus
    The platform is highly targeted towards younger audiences, which might not be appealing or suitable for older learners or adults seeking beginner resources.
  • Privacy Concerns
    As with any online community, there are potential privacy and security risks, especially for younger users, which require careful monitoring and guidance.

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.

Scratch videos

+ Add

Scratch 3.0 Review: My Thoughts About Scratch 3.0

More videos:

  • Review - Numark PT01 Scratch Review
  • Review - Meguiar's scratch X 2.0 review

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 Scratch and NumPy)

Scratch

NumPy

Kids Education
100 100%
Kids Education
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Game Development
100 100%
Game Development
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

User comments

Share your experience with using Scratch 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 Scratch and NumPy

Scratch Reviews

  1. Pratham shah
    · nothing at none ·
    TOO GOOD

    It is just awesome. you can make so many things WITHOUT A TEAM! If you are starting then this is an awesome place to start at.

    🏁 Competitors: Python, Java, Code.org
    👍 Pros:    Good UI|Remix|Works perfectly|100% free|Many, many languages
Top 15 educational software to streamline the learning process
Scratch lets students create interactive stories, games, and animations. The coding projects allow students to experiment and express their ideas, developing 21st-century skills like computational thinking and creativity. Scratch introduces students to programming, STEM and digital literacy in a fun way.
Source: www.lookdigitalsignage.com
16 Scratch Alternatives
It can even permit anyone to access its junior program through which kids can learn how to make any app by taking their focus on the study related to programming. Scratch also comes with facilitating users with the permission to mix all the programming blocks so that they can create multiple characters for singing, jumping, dancing, moving, and more.
Source: www.justalternativeto.com
Coding Websites That Help Kids Learn Programming In A Fun Way in 2023
Scratch, created by MIT students, teaches coding by allowing students to create tales, games, and animations using programming blocks. There is a vibrant online community as well as a step-by-step tutorial to assist those who are just getting started. Students can also use an offline editor to revise their work. ScratchJr, a simplified version of the software, is targeted at...
Source: www.jetlearn.com
20 Best Scratch Alternatives 2023
Unlike Scratch, Snap targets not only kids but also high school and college students. The platform provides a solution for serious computer science study, while Scratch focuses on just the basics.
Source: rigorousthemes.com

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, Scratch should be more popular than NumPy. It has been mentiond 569 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.

Scratch mentions (569)

  • TikTok Is Harming Children at an Industrial Scale
    I anticipate my kid needing to live in a word with capitalism, it doesn't ncessarily mean that they need a Mastercard at 4 years old. Same with many other things: condoms, keys to a car, access to alcohol. There is a time for everything, and at the age of 4, a young human probably has not yet maxxed out on analog stimuli opportunities. I learned YouTube when it came out in 2006 and I was 21. I've got 19 years of... - Source: Hacker News / 24 days ago
  • How I Got Started in IT: My Journey to Becoming an Apprentice Support Engineer 🚀
    I've always been fascinated by the technology. I spent many hors playing video games and the first dive into the world of development was when I had to code a game on Scratch. The excercise looked pretty easy: Create a Tamagotchi-like game. Let me tell you - It wasn't easy at all for someone of a young age! There were many things that I needed to pay attention to: Things I have never heard of before! - Source: dev.to / 6 months ago
  • Principles of Educational Programming Language Design
    I would be surprised if your first program was C++? Specifically, getting a decent C++ toolchain that can produce a meaningful program is not a small thing? I'm not sure where I feel about languages made for teaching and whatnot, yet; but I would be remiss if I didn't encourage my kids to use https://scratch.mit.edu/ for their early programming. I remember early computers would boot into a BASIC prompt and I... - Source: Hacker News / 5 months ago
  • There is no such thing as a global method (in Ruby)
    I've been teaching a teenager how to code with smalltalk (Scratch): https://scratch.mit.edu/. - Source: Hacker News / 7 months ago
  • Ask HN: Platform for 11 year old to create video games?
    A good place to start with kids that age is Scratch: https://scratch.mit.edu/. - Source: Hacker News / 8 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 Scratch and NumPy, you can also consider the following products

Godot Engine - Feature-packed 2D and 3D open source game engine.

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

Code.org - Code.org is a non-profit whose goal is to expose all students to computer programming.

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

GDevelop - GDevelop is an open-source game making software designed to be used by everyone.

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

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