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ASP.NET vs Python: What are the differences?

ASP.NET: An open source web framework for building modern web apps and services with .NET. .NET is a developer platform made up of tools, programming languages, and libraries for building many different types of applications; Python: A clear and powerful object-oriented programming language, comparable to Perl, Ruby, Scheme, or Java. Python is a general purpose programming language created by Guido Van Rossum. Python is most praised for its elegant syntax and readable code, if you are just beginning your programming career python suits you best.

ASP.NET can be classified as a tool in the "Frameworks (Full Stack)" category, while Python is grouped under "Languages".

Python is an open source tool with 25.3K GitHub stars and 10.5K GitHub forks. Here's a link to Python's open source repository on GitHub.

Uber Technologies, Spotify, and Netflix are some of the popular companies that use Python, whereas ASP.NET is used by Performance Assessment Network (PAN), Making Waves, and Jitbit. Python has a broader approval, being mentioned in 2830 company stacks & 3639 developers stacks; compared to ASP.NET, which is listed in 76 company stacks and 76 developer stacks.

- No public GitHub repository available -

What is ASP.NET?

.NET is a developer platform made up of tools, programming languages, and libraries for building many different types of applications.

What is Python?

Python is a general purpose programming language created by Guido Van Rossum. Python is most praised for its elegant syntax and readable code, if you are just beginning your programming career python suits you best.
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      What are some alternatives to ASP.NET and Python?
      ASP.NET Core
      A free and open-source web framework, and higher performance than ASP.NET, developed by Microsoft and the community. It is a modular framework that runs on both the full .NET Framework, on Windows, and the cross-platform .NET Core.
      PHP
      Fast, flexible and pragmatic, PHP powers everything from your blog to the most popular websites in the world.
      JavaScript
      JavaScript is most known as the scripting language for Web pages, but used in many non-browser environments as well such as node.js or Apache CouchDB. It is a prototype-based, multi-paradigm scripting language that is dynamic,and supports object-oriented, imperative, and functional programming styles.
      Node.js
      Node.js uses an event-driven, non-blocking I/O model that makes it lightweight and efficient, perfect for data-intensive real-time applications that run across distributed devices.
      Java
      Java is a programming language and computing platform first released by Sun Microsystems in 1995. There are lots of applications and websites that will not work unless you have Java installed, and more are created every day. Java is fast, secure, and reliable. From laptops to datacenters, game consoles to scientific supercomputers, cell phones to the Internet, Java is everywhere!
      See all alternatives
      Decisions about ASP.NET and Python
      Amazon ElastiCache
      Amazon ElastiCache
      Amazon Elasticsearch Service
      Amazon Elasticsearch Service
      AWS Elastic Load Balancing (ELB)
      AWS Elastic Load Balancing (ELB)
      Memcached
      Memcached
      Redis
      Redis
      Python
      Python
      AWS Lambda
      AWS Lambda
      Amazon RDS
      Amazon RDS
      Microsoft SQL Server
      Microsoft SQL Server
      MariaDB
      MariaDB
      Amazon RDS for PostgreSQL
      Amazon RDS for PostgreSQL
      Rails
      Rails
      Ruby
      Ruby
      Heroku
      Heroku
      AWS Elastic Beanstalk
      AWS Elastic Beanstalk

      We initially started out with Heroku as our PaaS provider due to a desire to use it by our original developer for our Ruby on Rails application/website at the time. We were finding response times slow, it was painfully slow, sometimes taking 10 seconds to start loading the main page. Moving up to the next "compute" level was going to be very expensive.

      We moved our site over to AWS Elastic Beanstalk , not only did response times on the site practically become instant, our cloud bill for the application was cut in half.

      In database world we are currently using Amazon RDS for PostgreSQL also, we have both MariaDB and Microsoft SQL Server both hosted on Amazon RDS. The plan is to migrate to AWS Aurora Serverless for all 3 of those database systems.

      Additional services we use for our public applications: AWS Lambda, Python, Redis, Memcached, AWS Elastic Load Balancing (ELB), Amazon Elasticsearch Service, Amazon ElastiCache

      See more
      StackShare Editors
      StackShare Editors
      Kubernetes
      Kubernetes
      Go
      Go
      Python
      Python

      Following its migration from vanilla instances with autoscaling groups to Kubernetes, Postmates began facing challenges while “migrating workloads that needed to scale up very quickly.”

      The built-in Horizontal Pod Autoscaler (HPA) automatically scales the number of pods in a replication controller, deployment or replica set based on observed CPU utilization. But the challenges for Postmates is that there’s no way to configure the scale velocity of one particular cluster with an HPA.

      For Postmates, which runs at least three different types of applications with distinct performance and scaling characteristics, this proved problematic.

      To overcome these challenges, the team created and open sourced the Configurable Horizontal Pod Autoscaler, which allows for fine-grained tuning on a per-HPA object basis. The result is that “you can configure critical services to scale down very slowly, while every other service could be configured to scale down instantly to reduce costs.”

      See more
      Hampton Catlin
      Hampton Catlin
      VP of Engineering at Rent The Runway · | 6 upvotes · 7.4K views
      atRent the RunwayRent the Runway
      Java
      Java
      Python
      Python
      Ruby
      Ruby

      At our company, and I've noticed a lot of other ones... application developers and dev-ops people tend to use Ruby and our statisticians and data scientists love Python . Like most companies, our stack is kind of split that way. Ruby is used as glue in most of our production systems ( Java being the main backend language), and then all of our data scientists and their various pipelines tend towards Python

      See more
      Ajit Parthan
      Ajit Parthan
      CTO at Shaw Academy · | 3 upvotes · 5.2K views
      atShaw AcademyShaw Academy
      Python
      Python
      PHP
      PHP
      #Etl

      Multiple systems means there is a requirement to cart data across them.

      Started off with Talend scripts. This was great as what we initially had were PHP/Python script - allowed for a more systematic approach to ETL.

      But ended up with a massive repository of scripts, complex crontab entries and regular failures due to memory issues.

      Using Stitch or similar services is a better approach: - no need to worry about the infrastructure needed for the ETL processes - a more formal mapping of data from source to destination as opposed to script developer doing his/her voodoo magic - lot of common sources and destination integrations are already builtin and out of the box

      etl @{etlasaservice}|topic:1323|

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      SVN (Subversion)
      SVN (Subversion)
      Git
      Git
      JSON
      JSON
      XML
      XML
      Python
      Python
      PHP
      PHP
      Java
      Java
      Swift
      Swift
      JavaScript
      JavaScript
      Linux
      Linux
      GitHub
      GitHub
      Visual Studio Code
      Visual Studio Code

      I use Visual Studio Code because at this time is a mature software and I can do practically everything using it.

      • It's free and open source: The project is hosted on GitHub and it’s free to download, fork, modify and contribute to the project.

      • Multi-platform: You can download binaries for different platforms, included Windows (x64), MacOS and Linux (.rpm and .deb packages)

      • LightWeight: It runs smoothly in different devices. It has an average memory and CPU usage. Starts almost immediately and it’s very stable.

      • Extended language support: Supports by default the majority of the most used languages and syntax like JavaScript, HTML, C#, Swift, Java, PHP, Python and others. Also, VS Code supports different file types associated to projects like .ini, .properties, XML and JSON files.

      • Integrated tools: Includes an integrated terminal, debugger, problem list and console output inspector. The project navigator sidebar is simple and powerful: you can manage your files and folders with ease. The command palette helps you find commands by text. The search widget has a powerful auto-complete feature to search and find your files.

      • Extensible and configurable: There are many extensions available for every language supported, including syntax highlighters, IntelliSense and code completion, and debuggers. There are also extension to manage application configuration and architecture like Docker and Jenkins.

      • Integrated with Git: You can visually manage your project repositories, pull, commit and push your changes, and easy conflict resolution.( there is support for SVN (Subversion) users by plugin)

      See more
      Ajit Parthan
      Ajit Parthan
      CTO at Shaw Academy · | 1 upvotes · 4K views
      atShaw AcademyShaw Academy
      Python
      Python
      PHP
      PHP

      Multiple systems means there is a requirement to cart data across them.

      Started off with Talend scripts. This was great as what we initially had were PHP/Python script - allowed for a more systematic approach to ETL.

      But ended up with a massive repository of scripts, complex crontab entries and regular failures due to memory issues.

      Using Stitch or similar services is a better approach: - no need to worry about the infrastructure needed for the ETL processes - a more formal mapping of data from source to destination as opposed to script developer doing his/her voodoo magic - lot of common sources and destination integrations are already builtin and out of the box

      See more
      Eric Colson
      Eric Colson
      Chief Algorithms Officer at Stitch Fix · | 19 upvotes · 211.9K views
      atStitch FixStitch Fix
      Amazon EC2 Container Service
      Amazon EC2 Container Service
      Docker
      Docker
      PyTorch
      PyTorch
      R
      R
      Python
      Python
      Presto
      Presto
      Apache Spark
      Apache Spark
      Amazon S3
      Amazon S3
      PostgreSQL
      PostgreSQL
      Kafka
      Kafka
      #Data
      #DataStack
      #DataScience
      #ML
      #Etl
      #AWS

      The algorithms and data infrastructure at Stitch Fix is housed in #AWS. Data acquisition is split between events flowing through Kafka, and periodic snapshots of PostgreSQL DBs. We store data in an Amazon S3 based data warehouse. Apache Spark on Yarn is our tool of choice for data movement and #ETL. Because our storage layer (s3) is decoupled from our processing layer, we are able to scale our compute environment very elastically. We have several semi-permanent, autoscaling Yarn clusters running to serve our data processing needs. While the bulk of our compute infrastructure is dedicated to algorithmic processing, we also implemented Presto for adhoc queries and dashboards.

      Beyond data movement and ETL, most #ML centric jobs (e.g. model training and execution) run in a similarly elastic environment as containers running Python and R code on Amazon EC2 Container Service clusters. The execution of batch jobs on top of ECS is managed by Flotilla, a service we built in house and open sourced (see https://github.com/stitchfix/flotilla-os).

      At Stitch Fix, algorithmic integrations are pervasive across the business. We have dozens of data products actively integrated systems. That requires serving layer that is robust, agile, flexible, and allows for self-service. Models produced on Flotilla are packaged for deployment in production using Khan, another framework we've developed internally. Khan provides our data scientists the ability to quickly productionize those models they've developed with open source frameworks in Python 3 (e.g. PyTorch, sklearn), by automatically packaging them as Docker containers and deploying to Amazon ECS. This provides our data scientist a one-click method of getting from their algorithms to production. We then integrate those deployments into a service mesh, which allows us to A/B test various implementations in our product.

      For more info:

      #DataScience #DataStack #Data

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      Python
      Python
      Django
      Django
      JavaScript
      JavaScript
      Node.js
      Node.js

      Django or NodeJS? Hi, I’m thinking about which software I should use for my web-app. What about Node.js or Django for the back-end? I want to create an online preparation course for the final school exams in my country. At the beginning for maths. The course should contain tutorials and a lot of exercises of different types. E.g. multiple choice, user text/number input and drawing tasks. The exercises should change (different levels) with the learning progress. Wrong questions should asked again with different numbers. I also want a score system and statistics. So far, I have got only limited web development skills. (some HTML, CSS, Bootstrap and Wordpress). I don’t know JavaScript or Python.

      Possible pros for Python / Django: - easy syntax, easier to learn for me as a beginner - fast development, earlier release - libraries for mathematical and scientific computation

      Possible pros for JavaScript / Node.js: - great performance, better choice for real time applications: user should get the answer for a question quickly

      Which software would you use in my case? Are my arguments for Python/NodeJS right? Which kind of database would you use?

      Thank you for your answer!

      Node.js JavaScript Django Python

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      Git
      Git
      Docker
      Docker
      NATS
      NATS
      JavaScript
      JavaScript
      TypeScript
      TypeScript
      PostgreSQL
      PostgreSQL
      Python
      Python
      Go
      Go

      Go is a high performance language with simple syntax / semantics. Although it is not as expressive as some other languages, it's still a great language for backend development.

      Python is expressive and battery-included, and pre-installed in most linux distros, making it a great language for scripting.

      PostgreSQL: Rock-solid RDBMS with NoSQL support.

      TypeScript saves you from all nonsense semantics of JavaScript , LOL.

      NATS: fast message queue and easy to deploy / maintain.

      Docker makes deployment painless.

      Git essential tool for collaboration and source management.

      See more
      Omar Melendrez
      Omar Melendrez
      Front-end developer · | 3 upvotes · 4.2K views
      Python
      Python
      C#
      C#
      Node.js
      Node.js
      React
      React
      Vue.js
      Vue.js
      #Vscode
      #Fullstack

      I'm #Fullstack here and work with Vue.js, React and Node.js in some projects but also C# for other clients. Also started learning Python. And all this with just one tool!: #Vscode I have used Atom and Sublime Text in the past and they are very good too, but for me now is just vscode. I think the combination of vscode with the free available extensions that the community is creating makes a powerful tool and that's why vscode became the most popular IDE for software development. You can match it to your own needs in a couple of minutes. Did I mention you can style it your way? Amazing tool!

      See more
      Tom Klein
      Tom Klein
      CEO at Gentlent · | 4 upvotes · 24.9K views
      atGentlentGentlent
      Python
      Python
      Electron
      Electron
      Socket.IO
      Socket.IO
      Google Compute Engine
      Google Compute Engine
      TypeScript
      TypeScript
      ES6
      ES6
      Ubuntu
      Ubuntu
      PostgreSQL
      PostgreSQL
      React
      React
      nginx
      nginx
      Sass
      Sass
      HTML5
      HTML5
      PHP
      PHP
      Node.js
      Node.js
      JavaScript
      JavaScript

      Our most used programming languages are JavaScript / Node.js for it's lightweight and fast use, PHP because everyone knows it, HTML5 because you can't live without it and Sass to write great CSS. Occasionally, we use nginx as a web server and proxy, React for our UX, PostgreSQL as fast relational database, Ubuntu as server OS, ES6 and TypeScript for Node, Google Compute Engine for our infrastructure, and Socket.IO and Electron for specific use cases. We also use Python for some of our backends.

      See more
      Praveen Mooli
      Praveen Mooli
      Technical Leader at Taylor and Francis · | 11 upvotes · 97.7K views
      MongoDB Atlas
      MongoDB Atlas
      Amazon S3
      Amazon S3
      Amazon DynamoDB
      Amazon DynamoDB
      Amazon RDS
      Amazon RDS
      Serverless
      Serverless
      Docker
      Docker
      Terraform
      Terraform
      Travis CI
      Travis CI
      GitHub
      GitHub
      RxJS
      RxJS
      Angular 2
      Angular 2
      AWS Lambda
      AWS Lambda
      Amazon SQS
      Amazon SQS
      Amazon SNS
      Amazon SNS
      Amazon Kinesis Firehose
      Amazon Kinesis Firehose
      Amazon Kinesis
      Amazon Kinesis
      Flask
      Flask
      Python
      Python
      ExpressJS
      ExpressJS
      Node.js
      Node.js
      Spring Boot
      Spring Boot
      Java
      Java
      #Data
      #Devops
      #Webapps
      #Eventsourcingframework
      #Microservices
      #Backend

      We are in the process of building a modern content platform to deliver our content through various channels. We decided to go with Microservices architecture as we wanted scale. Microservice architecture style is an approach to developing an application as a suite of small independently deployable services built around specific business capabilities. You can gain modularity, extensive parallelism and cost-effective scaling by deploying services across many distributed servers. Microservices modularity facilitates independent updates/deployments, and helps to avoid single point of failure, which can help prevent large-scale outages. We also decided to use Event Driven Architecture pattern which is a popular distributed asynchronous architecture pattern used to produce highly scalable applications. The event-driven architecture is made up of highly decoupled, single-purpose event processing components that asynchronously receive and process events.

      To build our #Backend capabilities we decided to use the following: 1. #Microservices - Java with Spring Boot , Node.js with ExpressJS and Python with Flask 2. #Eventsourcingframework - Amazon Kinesis , Amazon Kinesis Firehose , Amazon SNS , Amazon SQS, AWS Lambda 3. #Data - Amazon RDS , Amazon DynamoDB , Amazon S3 , MongoDB Atlas

      To build #Webapps we decided to use Angular 2 with RxJS

      #Devops - GitHub , Travis CI , Terraform , Docker , Serverless

      See more
      PubNub
      PubNub
      asyncio
      asyncio
      JavaScript
      JavaScript
      Python
      Python

      I love Python and JavaScript . You can do the same JavaScript async operations in Python by using asyncio. This is particularly useful when you need to do socket programming in Python. With streaming sockets, data can be sent or received at any time. In case your Python program is in the middle of executing some code, other threads can handle the new socket data. Libraries like asyncio implement multiple threads, so your Python program can work in an asynchronous fashion. PubNub makes bi-directional data streaming between devices even easier.

      See more
      Helio Junior
      Helio Junior
      CSS 3
      CSS 3
      JavaScript
      JavaScript
      Python
      Python
      #Electron
      #NodeJS
      #UXdesign
      #DataScience

      Python is a excellent tool for #DataScience , but up to now is very poor in #uxdesign . To do some design I'm using JavaScript and #nodejs , #electron stack. The possibility of use CSS 3 to draw interfaces is very awesome and fast. Unfortunatelly Python don't have (yet) a good way to make a #UXdesign .

      See more
      Greg Neumann
      Greg Neumann
      Indie, Solo, Developer · | 6 upvotes · 35.8K views
      TypeScript
      TypeScript
      Vue.js
      Vue.js
      Electron
      Electron
      Quasar Framework
      Quasar Framework
      ASP.NET
      ASP.NET
      Xamarin Forms
      Xamarin Forms
      .NET Core
      .NET Core
      Xamarin
      Xamarin

      Finding the most effective dev stack for a solo developer. Over the past year, I've been looking at many tech stacks that would be 'best' for me, as a solo, indie, developer to deliver a desktop app (Windows & Mac) plus mobile - iOS mainly. Initially, Xamarin started to stand-out. Using .NET Core as the run-time, Xamarin as the native API provider and Xamarin Forms for the UI seemed to solve all issues. But, the cracks soon started to appear. Xamarin Forms is mobile only; the Windows incarnation is different. There is no Mac UI solution (you have to code it natively in Mac OS Storyboard. I was also worried how Xamarin Forms , if I was to use it, was going to cope, in future, with Apple's new SwiftUI and Google's new Fuchsia.

      This plethora of techs for the UI-layer made me reach for the safer waters of using Web-techs for the UI. Lovely! Consistency everywhere (well, mostly). But that consistency evaporates when platform issues are addressed. There are so many web frameworks!

      But, I made a simple decision. It's just me...I am clever, but there is no army of coders here. And I have big plans for a business app. How could just 1 developer go-on to deploy a decent app to Windows, iPhone, iPad & Mac OS? I remembered earlier days when I've used Microsoft's ASP.NET to scaffold - generate - loads of Code for a web-app that I needed for several charities that I worked with. What 'generators' exist that do a lot of the platform-specific rubbish, allow the necessary customisation of such platform integration and provide a decent UI?

      I've placed my colours to the Quasar Framework mast. Oh dear, that means Electron desktop apps doesn't it? Well, Ive had enough of loads of Developers saying that "the menus won't look native" or "it uses too much RAM" and so on. I've been using non-native UI-wrapped apps for ages - the date picker in Outlook on iOS is way better than the native date-picker and I'd been using it for years without getting hot under the collar about it. Developers do get so hung-up on things that busy Users hardly notice; don't you think?. As to the RAM usage issue; that's a bit true. But Users only really notice when an app uses so much RAM that the machine starts to page-out. Electron contributes towards that horizon but does not cause it. My Users will be business-users after all. Somewhat decent machines.

      Looking forward to all that lovely Vue.js around my TypeScript and all those really, really, b e a u t I f u l UI controls of Quasar Framework . Still not sure that 1 dev can deliver all that... but I'm up for trying...

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      Interest over time
      Reviews of ASP.NET and Python
      No reviews found
      How developers use ASP.NET and Python
      Avatar of Exchange rates API
      Exchange rates API uses PythonPython

      Beautiful is better than ugly.

      Explicit is better than implicit.

      Simple is better than complex.

      Complex is better than complicated.

      Flat is better than nested.

      Sparse is better than dense.

      Readability counts.

      Special cases aren't special enough to break the rules.

      Although practicality beats purity.

      Errors should never pass silently.

      Unless explicitly silenced.

      In the face of ambiguity, refuse the temptation to guess.

      There should be one-- and preferably only one --obvious way to do it.

      Although that way may not be obvious at first unless you're Dutch.

      Now is better than never.

      Although never is often better than right now.

      If the implementation is hard to explain, it's a bad idea.

      If the implementation is easy to explain, it may be a good idea.

      Namespaces are one honking great idea -- let's do more of those!

      Avatar of Web Dreams
      Web Dreams uses PythonPython

      To me, this is by far the best programming language. Why? Because it’s the only language that really got me going after trying to get into programming with Java for a while. Python is powerful, easy to learn, and gets you to unsderstand other languages more once you understand it. Did I state I love the python language? Well, I do..

      Avatar of ttandon
      ttandon uses PythonPython

      Backend server for analysis of image samples from iPhone microscope lens. Chose this because of familiarity. The number one thing that I've learned at hackathons is that work exclusively with what you're 100% comfortable with. I use Python extensively at my day job at Wit.ai, so it was the obvious choice for the bulk of my coding.

      Avatar of papaver
      papaver uses PythonPython

      been a pythoner for around 7 years, maybe longer. quite adept at it, and love using the higher constructs like decorators. was my goto scripting language until i fell in love with clojure. python's also the goto for most vfx studios and great for the machine learning. numpy and pyqt for the win.

      Avatar of Blood Bot
      Blood Bot uses PythonPython

      Large swaths of resources built for python to achieve natural language processing. (We are in the process of deprecating the services written in python and porting them over to Javascript and node)

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