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GoodBarber VS NumPy

Compare GoodBarber VS NumPy and see what are their differences

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Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

GoodBarber logo GoodBarber

GoodBarber is an all-in-one, no-code platform to build native iOS, Android, and Progressive Web Apps โ€” with design, hosting, CMS, push notifications, and mobile e-commerce all included.

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • GoodBarber
    Image date //
    2026-06-11
  • GoodBarber
    Image date //
    2026-06-11

GoodBarber is an all-in-one, no-code platform for building native iOS and Android apps โ€” plus Progressive Web Apps โ€” without writing a line of code.

Everything is built in, so you create, publish, and run your app from a single back-office:

  • Design tools and templates
  • Hosting
  • CMS (articles, videos, podcasts, agenda, maps)
  • User management and members' areas
  • Push notifications
  • Mobile e-commerce, with 0% commission on in-app sales

Two configurations cover most projects:

  • Content Apps โ€” publish and engage an audience (media, creators, communities, education).
  • eCommerce Apps โ€” sell on mobile (online stores, restaurants, click & collect, local delivery).

In business since 2011, with apps downloaded every 4 seconds across 152 countries.

  • NumPy Landing page
    Landing page //
    2023-05-13

GoodBarber

Website
goodbarber.com
Pricing URL
Official GoodBarber Pricing
$ Details
freemium โ‚ฌ30.0 / Monthly
Release Date
2011 November
Startup details
Country
France
State
Corsica
City
Ajaccio
Employees
20 - 49
Edit details

NumPy

Website
numpy.org
Pricing URL
-
$ Details
Release Date
-
Edit details

GoodBarber features and specs

  • Customization
    GoodBarber offers extensive design and customization options, allowing users to create a unique and visually appealing app that aligns with their brand.
  • No Coding Required
    With a user-friendly interface and drag-and-drop builder, GoodBarber enables individuals without technical skills to build and manage their own apps.
  • Multi-Platform Support
    GoodBarber allows users to create apps for both iOS and Android platforms, ensuring a wider reach for the audience.
  • Advanced Features
    The platform includes advanced features like push notifications, custom forms, loyalty programs, and social media integration, enhancing the app's functionality.
  • Regular Updates
    GoodBarber provides regular updates to the platform, ensuring that the apps built on it are up-to-date with the latest technology and security standards.
  • Help and Support
    Users have access to comprehensive support resources, including documentation, tutorials, and a responsive customer support team.

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.

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.

GoodBarber videos

+ Add

GoodBarber V4 Review - Still One Of The Best?

More videos:

  • Review - Mobiloud vs GoodBarber, what's the difference? | 2020
  • Review - GoodBarber Review - Is it any good?

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 GoodBarber and NumPy)

GoodBarber

NumPy

Mobile App Builder
100 100%
Mobile App Builder
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Mobile App Dev Platform
100 100%
Mobile App Dev Platform
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

User comments

Share your experience with using GoodBarber 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 GoodBarber and NumPy

GoodBarber Reviews

THE BEST 34 APP DEVELOPMENT SOFTWARE IN 2022 LIST
GoodBarber is a software editor who develops a content management system to create native apps for iPhone and Android. Unify your web presence in a single app, and engage with your audience. Build and distribute a Beautiful App on the App Store and Google Play. GoodBarber puts a strong focus on design. Through an intuitive interface, users can customise their apps with fine...
Source: www.edigitalagency.com.au

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, NumPy seems to be more popular. 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.

GoodBarber mentions (0)

We have not tracked any mentions of GoodBarber yet. Tracking of GoodBarber recommendations started around Mar 2021.

NumPy mentions (122)

View more

What are some alternatives?

When comparing GoodBarber and NumPy, you can also consider the following products

Bizness Apps - Create your own app or become a reseller and build apps for others

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

Dropsource - Mobile development platform for building native iOS & Android apps

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

AppyPie AppMakr - AppMakr is a browser-based platform designed to make creating your own iPhone app quick and easy.

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

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