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ASP.NET VS NumPy

Compare ASP.NET VS NumPy and see what are their differences

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ASP.NET logo ASP.NET

ASP.NET is a free web framework for building great Web sites and Web applications using HTML, CSS and JavaScript.

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • ASP.NET Landing page
    Landing page //
    2023-04-29
  • NumPy Landing page
    Landing page //
    2023-05-13

ASP.NET features and specs

  • Performance
    ASP.NET is known for its high performance and scalability. It compiles server-side code to DLL files, which is executed on the server side, thereby speeding up the application's response time.
  • Security
    ASP.NET provides built-in security features like form authentication and Windows authentication, as well as protection against common threats such as SQL injection, cross-site scripting, and request forgery.
  • Rich Toolbox
    Visual Studio, the Integrated Development Environment (IDE) for ASP.NET, offers a rich toolbox with a plethora of controls, automatic deployment features, and other tools that significantly speed up development.
  • Cross-Platform Support
    ASP.NET Core is a cross-platform framework, which means you can run your web applications on Windows, Linux, and macOS.
  • Community and Support
    ASP.NET has a strong community and extensive documentation, making it easier to find solutions to problems and ensuring continuous improvement and support.

Possible disadvantages of ASP.NET

  • Learning Curve
    The framework can be complex for beginners, especially those without experience in C# or the .NET ecosystem.
  • Cost
    While ASP.NET Core is free and open-source, some advanced features and tools require a Visual Studio subscription, which can be expensive.
  • Hosting
    Although ASP.NET Core has improved in terms of cross-platform hosting, traditional ASP.NET applications are primarily optimized for Windows servers, limiting hosting options.
  • Resource Intensive
    ASP.NET applications can be more resource-intensive than applications built with some other frameworks, which can lead to higher infrastructure costs.
  • Complexity
    The framework offers a lot of features and functionalities, which can sometimes make it overly complex and harder to manage for smaller projects.

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.

ASP.NET videos

+ Add

Build Rating and Review System in ASP.NET MVC and Entity Framework

More videos:

  • Review - ASP.NET MVC - Review 0
  • Review - IMDeanyP Movie Review Site - ASP.NET / C# / SQL Server / MVC / Entity Framework

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 ASP.NET and NumPy)

ASP.NET

NumPy

Developer Tools
100 100%
Developer Tools
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Web Frameworks
100 100%
Web Frameworks
0% 0
Data Science Tools
0 0%
Data Science Tools
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 ASP.NET and NumPy

ASP.NET Reviews

The 20 Best Laravel Alternatives for Web Development
ASP.NET’s got that Microsoft muscle, a powerhouse of a framework for building dynamic web services and more. It lets you roll out robust websites with the smoothness that comes with deep pockets. Perfect for .NET software development teams.
Source: tms-outsource.com
Top 10 Phoenix Framework Alternatives
Moving over to the .NET platform, Asp.Net is an open-source web framework developed by Microsoft that allows developers to build dynamic web pages, apps, and services using HTML, JavaScript, and CSS.
Source: blog.back4app.com
10 Ruby on Rails Alternatives For Web Development in 2022
Last but not least, a back-end web framework created by Microsoft for the development of dynamic web pages - ASP.NET. Built on top of C# it is one the fastest frameworks available on the market. ASP.NET is capable of handling 7.01 million requests per second while Django handles only 79,266 requests. The framework is mainly used for building web applications, APIs,...
Source: www.ideamotive.co

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 should be more popular than ASP.NET. It has been mentiond 119 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.

ASP.NET mentions (22)

  • 30,656 Pages of Books About the .NET Ecosystem: C#, Blazor, ASP.NET, & T-SQL
    Most of the books teach C# and .NET, ASP.NET, Blazor, or T-SQL. I also found some .NET-specific coverage of wider topics: architecture and design, concurrency, automated tests, functional programming, and dependency injection. - Source: dev.to / about 2 months ago
  • Diversify Your Tech Stack: Uncovering Powerful Node js Alternatives
    Built by Microsoft, .NET is a high-performance application platform that uses C# for programming. .NET is cross-platform and comes with plenty of libraries and APIs covering collections, networking, and machine learning to build different types of applications. ASP.NET Core widens the .NET developer platform with libraries and tools geared towards web applications. - Source: dev.to / 9 months ago
  • C# Fundamentals
    Web Applications: ASP.NET, a powerful framework for building web applications, is primarily based on C#. Developers can create dynamic websites, web APIs, and services with ASP.NET. - Source: dev.to / 11 months ago
  • What’s New in Bold Reports 6.1 April 2024 Release
    The Bold Reporting Tools ASP.NET MVC and ASP.NET Web Forms will no longer be deployed in the embedded build. However, bug fixes are diligently transferred to our public repositories until Microsoft officially announces the end of support for these platforms. For new web application development or to stay up-to-date, Blazor or ASP.NET Core are recommended. - Source: dev.to / about 1 year ago
  • Is ASP.NET Core the next step in my career being an ASP.NET MVC developer? Or are there other technologies I should look at?
    Sorry for the possibly dumb questions. But then does .NET 5 have a "Model View Controller" workflow? I'm seeing ASP.NET still exists. But it's just "ASP.NET", no "MVC" or "Core" attached to the end. And they seem to recommend Blazor instead of C# which is something I only know the name of. Source: about 2 years ago
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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 ASP.NET and NumPy, you can also consider the following products

Ruby on Rails - Ruby on Rails is an open source full-stack web application framework for the Ruby programming...

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

Django - The Web framework for perfectionists with deadlines

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

Laravel - A PHP Framework For Web Artisans

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

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