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NumPy VS AppStruct

Compare NumPy VS AppStruct and see what are their differences

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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

AppStruct logo AppStruct

AppStruct โ€” a new no-code platform built for web, mobile, desktop apps and telegram mini-apps development.
  • NumPy Landing page
    Landing page //
    2023-05-13
  • AppStruct Full Frontend Contol
    Full Frontend Contol //
    2025-06-05
  • AppStruct Build Backend Flows
    Build Backend Flows //
    2025-06-05
  • AppStruct Direct Publishing
    Direct Publishing //
    2025-06-05

Hi, Iโ€™m Boris, co-founder of AppStruct โ€” a new no-code platform built for web, mobile, and desktop apps development. Weโ€™re a team of no-code enthusiasts who set out to fix the two biggest pain points we kept running into: speed and complexity.

Weโ€™re not the first to build in the no-code space โ€” but we felt the idea has never been pushed to its full potential. So we started fresh and built AppStruct from the ground up with one goal in mind:

Combine powerful functionality with simple UX โ€” and make app creation faster than ever.

NumPy

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

AppStruct

Website
appstruct.ai
Pricing URL
Official AppStruct Pricing
$ Details
freemium $45.0 / Monthly
Release Date
2024 January
Startup details
Country
Italy
State
Florence
City
Florence
Founder(s)
Boris Markarian, Vladimir Tambovtsev, Ilia Yasir
Employees
1 - 9
Edit details

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.

AppStruct features and specs

  • ๐Ÿ–ฑ๏ธ Drag & Drop Editor
    Build your UI by dropping and stretching components on the canvas.
  • ๐Ÿ”— API Integrations
    Connect to any API service in minutes: fetch data, send updates, and power your app with external APIs. Out-of-the-box integrations with Zapier, Stripe and Excel.
  • ๐Ÿš€ One-Click Publishing
    Deploy to the App Store and Google Play in one click.
  • ๐Ÿ“ฅ APK & PWA download
    Get installable apps with shareable links.
  • ๐Ÿ“ฑ Adaptive Layouts
    Your UI automatically resizes for phones, tablets, desktops or any custom screen size.
  • ๐Ÿ—„๏ธ Built-In & External Backends
    Use our database or plug in Firebase/Supabase.
  • ๐Ÿงฉ 50+ UI Components
    Choose from a rich library of components โ€” all fully customizable to match your brand.
  • ๐Ÿ“ก WebSockets
    Real-time features like live chat and dashboards.
  • ๐Ÿ’พ Local Storage
    Store temporary or persistent data in-app.
  • ๐Ÿค– AI Component Generator
    Describe what you need, we generate the component.
  • ๐Ÿ› ๏ธ Custom Code Support
    Drop in your own React logic when needed.
  • ๐Ÿ”„ Visual Logic Builder
    Build complex conditionals and workflows with a node-based editor.
  • โž— Math Engine
    Do live calculations and metrics in the UI. Build logic based on device data, geo position, and time.
  • ๐ŸŽจ Design System
    Manage global fonts, colors, themes, and dark/light mode.
  • ๐Ÿ“ฒ Deep Links
    Create shareable URLs that open specific screens or content directly within your app.
  • ๐Ÿ” SEO Control
    Meta tags, sitemaps, and prerendering built in.
  • ๐Ÿ“ Geolocation
    Access user location data to power maps, geo-fencing, location-based content and more.
  • ๐Ÿ”” Push Notifications
    Send targeted notifications and real-time alerts. Works seamlessly with Deep Links to drive users directly to the right screen.
  • ๐Ÿ“‘ Prebuilt Templates
    E-commerce, delivery, AI chatbots, and more.
  • ๐Ÿ“ Localization
    Translate your app into multiple languages instantly.
  • ๐Ÿ“š Interactive Docs
    In-app docs and videos to help you every step of the way.

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 AppStruct

Overall verdict

  • AppStruct.ai appears to be a capable no-code/AI-powered app building platform, but its suitability depends heavily on your specific needs, technical background, and the type of application you want to create. As with any tool in this space, it's best to evaluate it through a free trial before committing.

Why this product is good

  • It aims to lower the barrier to app development by leveraging AI, allowing non-technical users to build applications without writing code
  • AI-assisted platforms can significantly speed up prototyping and reduce development costs for simple to moderately complex apps
  • No-code/low-code approaches enable faster iteration and easier maintenance for small teams and solo builders
  • It may offer templates and pre-built components that accelerate getting a functional product to market

Recommended for

  • Entrepreneurs and startups wanting to quickly build an MVP without hiring developers
  • Small business owners needing custom internal tools or simple customer-facing apps
  • Non-technical founders who want to validate an idea before investing in full development
  • Designers and product managers who want to prototype rapidly
  • Teams looking to reduce development costs for straightforward applications

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

AppStruct videos

+ Add

Welcome to AppStruct | A New Standard for No-Code

More videos:

  • Review - AppStruct & Earlybird โ€“ Live Webinar | A fresh look at no-code
  • Review - AppStruct Lifetime Deal - The Best AI-Assisted App Builder in 2025

Category Popularity

0-100% (relative to NumPy and AppStruct)

NumPy

AppStruct

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
No Code
0 0%
No Code
100% 100
Data Science Tools
100 100%
Data Science Tools
0% 0
Application Builder
0 0%
Application Builder
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare NumPy and AppStruct

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

AppStruct Reviews

We have no reviews of AppStruct yet.
Be the first one to post

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.

NumPy mentions (122)

View more

AppStruct mentions (0)

We have not tracked any mentions of AppStruct yet. Tracking of AppStruct recommendations started around Jun 2025.

What are some alternatives?

When comparing NumPy and AppStruct, 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.

Adalo - Build apps for every platform, without code โœจ

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

FlutterFlow - FlutterFlow is an online low-code platform that empowers people to build native mobile apps visually.

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

Floot - Build serious apps with AI without getting stuck

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