Python vs Xamarin: What are the differences?
What is 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.
What is Xamarin? Create iOS, Android and Mac apps in C#. Xamarin’s Mono-based products enable .NET developers to use their existing code, libraries and tools (including Visual Studio*), as well as skills in .NET and the C# programming language, to create mobile applications for the industry’s most widely-used mobile devices, including Android-based smartphones and tablets, iPhone, iPad and iPod Touch.
Python can be classified as a tool in the "Languages" category, while Xamarin is grouped under "Cross-Platform Mobile Development".
"Great libraries", "Readable code" and "Beautiful code" are the key factors why developers consider Python; whereas "Power of c# on mobile devices", "Native apps with native ui controls" and "Native performance" are the primary reasons why Xamarin is favored.
Python is an open source tool with 25K GitHub stars and 10.3K GitHub forks. Here's a link to Python's open source repository on GitHub.
reddit, Instacart, and Lyft are some of the popular companies that use Python, whereas Xamarin is used by Rdio, Olo, and Rumble. Python has a broader approval, being mentioned in 2789 company stacks & 3500 developers stacks; compared to Xamarin, which is listed in 74 company stacks and 65 developer stacks.
What is Python?
What is Xamarin?
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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
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:
- Our Algorithms Tour: https://algorithms-tour.stitchfix.com/
- Our blog: https://multithreaded.stitchfix.com/blog/
- Careers: https://multithreaded.stitchfix.com/careers/
#DataScience #DataStack #Data
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
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!
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.
NATS: fast message queue and easy to deploy / maintain.
Docker makes deployment painless.
Git essential tool for collaboration and source management.
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!
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
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...
I'm working as one of the engineering leads in RunaHR. As our platform is a Saas, we thought It'd be good to have an API (We chose Ruby and Rails for this) and a SPA (built with React and Redux ) connected. We started the SPA with Create React App since It's pretty easy to start.
We use Jest as the testing framework and react-testing-library to test React components. In Rails we make tests using RSpec.
Our main database is PostgreSQL, but we also use MongoDB to store some type of data. We started to use Redis for cache and other time sensitive operations.
We have a couple of extra projects: One is an Employee app built with React Native and the other is an internal back office dashboard built with Next.js for the client and Python in the backend side.
Since you said that your middleware will be accessing DB and expose API, you can go with Node.js. It will make your development fast and easy. Suppose in future you will add some business logic you can choose Java with Spring Boot or Python with Flask / Django. NOTE: Language or framework doesn't matter. Choose based on your programming knowledge.
In our company we have think a lot about languages that we're willing to use, there we have considering Java, Python and C++ . All of there languages are old and well developed at fact but that's not ideology of araclx. We've choose a edge technologies such as Node.js , Rust , Kotlin and Go as our programming languages which is some kind of fun. Node.js is one of biggest trends of 2019, same for Go. We want to grow in our company with growth of languages we have choose, and probably when we would choose Java that would be almost impossible because larger languages move on today's market slower, and cannot have big changes.
Hi Community! Trust everyone is keeping safe. I am exploring the idea of building a #Neobank (App) with end-to-end banking capabilities. In the process of exploring this space, I have come across multiple Apps (N26, Revolut, Monese, etc) and explored their stacks in detail. The confusion remains to be the Backend Tech to be used?
What would you go with considering all of the languages such as Node.js Java Rails Python are suggested by some person or the other. As a general trend, I have noticed the usage of Node with React on the front or Node with a combination of Kotlin and Swift. Please suggest what would be the right approach!
I have just started learning Python 3 week back. I want to create REST api using python. The api will be use to save form data in Oracle database. The front end is using AngularJS 8 with Angular Material. In python there are so many framework for developing REST ** I am looking for some suggestions which REST framework to choose? ** Here are some feature I am looking for * Easy integration and unit testing like in Angular we just run command. * Code packageing, like in Java maven project we can build and package. I am looking for something which I can push in artifactory and deploy whole code as package. *Support for swagger/ OpenAPI * Support for JSON Web Token * Support for testcase coverage report Framework can have feature included or can be available by extension.
I'm working in Huge company and I'm in charge to choose the cross-platform environment to develop Mobile application for all our services. I choose Xamarin but because the error i get everytime in Visual Studio, I want to leave it and recommand another solution. In fact that's why I'm here.
Weird, Install VS2017 with Xamarin on a new PC Create a new app GOT ERRORS.....!!!!!
Thank you for considering this
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.
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!