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NumPy VS GoJS

Compare NumPy VS GoJS 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:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python

GoJS logo GoJS

GoJS is a JavaScript library for building interactive diagrams on HTML web pages. Build apps with flowcharts, org charts, BPMN, UML, modeling, and other visual graph types.
  • NumPy Landing page
    Landing page //
    2023-05-13
  • GoJS Landing page
    Landing page //
    2023-03-21

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.

GoJS features and specs

  • Rich Feature Set
    GoJS offers a comprehensive set of features designed for creating interactive diagrams, charts, and complex visualizations. This includes node and link modeling, custom styling, data binding, automatic layouts, and more.
  • Extensive Documentation
    The library is well-documented, providing developers with thorough guides, a detailed API reference, and numerous examples to assist in the implementation and troubleshooting of applications.
  • High Performance
    GoJS is optimized for performance, enabling the creation of responsive web applications that can handle a large number of nodes and complex interactions efficiently.
  • Flexibility and Customization
    GoJS offers great flexibility, allowing developers to customize the appearance and behavior of diagrams entirely, which makes it suitable for a wide range of use cases.
  • Active Support and Community
    The GoJS team provides active support to users through their forum and is responsive to issues and feature requests. This is complemented by a growing community of users sharing insights and solutions.

Possible disadvantages of GoJS

  • Commercial Licensing
    GoJS is a commercial product, and while it offers a free trial, a license is required for sustained use. This might be a constraint for projects with limited budgets.
  • Steep Learning Curve
    Due to its extensive capabilities and myriad of options, there can be a steep learning curve for developers new to GoJS to understand and effectively use all its features.
  • Complexity for Simple Diagrams
    While GoJS is powerful for complex diagrams, it might be considered overkill for simpler visualizations, where a lightweight library might suffice.
  • Browser Compatibility
    Although modern browsers are generally supported, there might be some compatibility issues or performance differences to manage when targeting older or less common browsers.
  • File Size
    The library's comprehensive feature set comes with a relatively large file size, which could impact loading times, particularly in environments with limited bandwidth.

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.

Analysis of GoJS

Overall verdict

  • GoJS is considered a good choice for developers needing a versatile and feature-rich library for developing complex diagramming applications. Its performance, flexibility, and extensive support make it a reliable tool for both small and large-scale projects.

Why this product is good

  • GoJS is widely regarded as a powerful JavaScript and TypeScript library for building interactive diagrams and graphs. It offers a comprehensive set of features, including customizable templates, support for a variety of diagram types, and intuitive drag-and-drop functionality. The library is optimized for performance with large datasets and provides a robust API for creating complex visual representations. It also boasts thorough documentation and a range of examples to help developers get started quickly.

Recommended for

  • Developers working on data visualization apps
  • Teams creating interactive diagrams or flowcharts
  • Projects requiring complex and scalable diagram solutions
  • Organizations needing customizable and high-performance diagram libraries

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

GoJS videos

+ Add

GoJS in 12 Minutes: JavaScript Diagramming Library Tutorial

More videos:

  • Tutorial - What's in a GoJS JavaScript Application? | GoJS Beginner Tutorial #1
  • Review - [GOJS] Design Patterns em Javascript

Category Popularity

0-100% (relative to NumPy and GoJS)

NumPy

GoJS

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Javascript UI Libraries
0 0%
Javascript UI Libraries
100% 100
Data Science Tools
100 100%
Data Science Tools
0% 0
Flowcharts
0 0%
Flowcharts
100% 100

User comments

Share your experience with using NumPy and GoJS. 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 GoJS

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

GoJS Reviews

20+ JavaScript libraries to draw your own diagrams (2022 edition)
GoJS offers many advanced features for user interactivity such as drag-and-drop, copy-and-paste, transactional state and undo management, palettes, overviews, data-bound models, event handlers, and an extensible tool system for custom operations. They provide over 150 interactive samples to help you get started with diagrams such as BPMN, flowchart, state chart, visual...
Source: modeling-languages.com

Social recommendations and mentions

Based on our record, NumPy should be more popular than GoJS. It has been mentiond 122 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 (122)

View more

GoJS mentions (13)

  • Ask HN: What do you use to create diagrams?
    Well I make https://gojs.net, so I just use the GoJS diagramming library to make diagrams :D Of course, its made for developers trying to make applications, not end users. - Source: Hacker News / over 1 year ago
  • Ask HN: What is the best software to visualize a graph with a billion nodes?
    My library (https://gojs.net) can do that easily. Give it a look, and if you think the price is acceptable for your project, contact us and we can make you a proof-of-concept. - Source: Hacker News / almost 2 years ago
  • Your 14-Day Free Trial Ain't Gonna Cut It
    If you click on their username, it takes you to their profile. https://news.ycombinator.com/user?id=simonsarris. - Source: Hacker News / about 2 years ago
  • Burning money on paid ads for a dev tool โ€“ what we've learned
    Have spent six figures yearly on ads, mostly for reach for the developer-focused diagram library GoJS (https://gojs.net) > Each experiment will need ~$500 and 2 weeks I would add a zero if you want serious data. I would also double the timescale. $5,000 over 4 weeks I second the uselessness of Google Display, it might look like conversions numbers are good but they are 100% too good to be true. As soon as you look... - Source: Hacker News / almost 3 years ago
  • Any Ideas How to Create a Graph Builder UI in React?
    Used goJS in one project and konva in another. Source: over 3 years ago
View more

What are some alternatives?

When comparing NumPy and GoJS, 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.

mxGraph - mxGraph is a fully client side JavaScript diagramming library - jgraph/mxgraph

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

jsPlumb - jsPlumb is an advanced, standards-compliant and easy to use JS library for building connectivity based applications, such as flowcharts, process flow diagrams, sequence diagrams, organisation charts, etc. More than just a diagram library.

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

Konva - Konva is 2d Canvas JavaScript framework for drawings shapes, animations, node nesting, layering, filtering, event handling, drag and drop and much more.

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