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Bootstrap vs Python: What are the differences?

Bootstrap: Simple and flexible HTML, CSS, and JS for popular UI components and interactions. Bootstrap is the most popular HTML, CSS, and JS framework for developing responsive, mobile first projects on the web; 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.

Bootstrap and Python are primarily classified as "Front-End Frameworks" and "Languages" tools respectively.

"Responsiveness", "UI components" and "Consistent" are the key factors why developers consider Bootstrap; whereas "Great libraries", "Readable code" and "Beautiful code" are the primary reasons why Python is favored.

Bootstrap and Python are both open source tools. It seems that Bootstrap with 134K GitHub stars and 66K forks on GitHub has more adoption than Python with 25.3K GitHub stars and 10.5K GitHub forks.

According to the StackShare community, Bootstrap has a broader approval, being mentioned in 7046 company stacks & 1115 developers stacks; compared to Python, which is listed in 2827 company stacks and 3633 developer stacks.

What is Bootstrap?

Bootstrap is the most popular HTML, CSS, and JS framework for developing responsive, mobile first projects on the web.

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 Bootstrap and Python?
Semantic UI
Semantic empowers designers and developers by creating a shared vocabulary for UI.
jQuery
jQuery is a cross-platform JavaScript library designed to simplify the client-side scripting of HTML.
Material
Express your creativity with Material, an animation and graphics framework for Google's Material Design and Apple's Flat UI in Swift.
React
Lots of people use React as the V in MVC. Since React makes no assumptions about the rest of your technology stack, it's easy to try it out on a small feature in an existing project.
Foundation
Foundation is the most advanced responsive front-end framework in the world. You can quickly prototype and build sites or apps that work on any kind of device with Foundation, which includes layout constructs (like a fully responsive grid), elements and best practices.
See all alternatives
Decisions about Bootstrap and Python
Pēteris Caune
Pēteris Caune
| 9 upvotes · 58.6K views
atSIA Monkey See Monkey DoSIA Monkey See Monkey Do
jQuery
jQuery
Bootstrap
Bootstrap
PostgreSQL
PostgreSQL
Django
Django
Python
Python

Python Django PostgreSQL Bootstrap jQuery

Healthchecks.io is a SaaS cron monitoring service. I needed a tool to monitor my cron jobs. I was not happy with the existing options, so I wrote one. The initial goal was to get to a MVP state, and use it myself. The followup goals were to add functionality and polish the user interface, while keeping the UI and the under the hood stuff as simple and clean as possible.

Python and DJango were obvious choices as I was already familiar with them, and knew that many of Django's built-in features would come handy in this project: ORM, testing infrastructure, user authentication, templates, form handling.

On the UI side, instead of doing the trendy "React JS app talking to API endpoints" thing, I went with the traditional HTML forms, and full page reloads. I was aiming for the max simplicity. Paraphrasing Kevin from The Office, why waste time write lot JS when form submit do trick. The frontend does however use some JS, for example, to support live-updating dashboards.

The backend is also aiming for max simplicity, and I've tried to keep the number of components to the minimum. For example, a message broker or a key-value store could be handy, but so far I'm getting away with storing everything in the Postgres database.

The deployment and hosting setup is also rather primitive by today's standards. uWSGI runs the Django app, with a nginx reverse proxy in front. uWSGI and nginx are run as systemd services on bare metal servers. Traffic is proxied through Cloudflare Load Balancer, which allows for relatively easy rolling code upgrades. I use Fabric for automating server maintenance. I did use Ansible for a while but moved back to Fabric: my Ansible playbooks were slower, and I could not get used to mixing YAML and Jinja templating.

Healthchecks.io tech decisions in one word: KISS. Use boring tools that get the job done.

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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

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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.”

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Hampton Catlin
Hampton Catlin
VP of Engineering at Rent The Runway · | 6 upvotes · 7.3K 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

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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)

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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 · 207.5K 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.

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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!

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Tom Klein
Tom Klein
CEO at Gentlent · | 4 upvotes · 24.7K 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.

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Praveen Mooli
Praveen Mooli
Technical Leader at Taylor and Francis · | 11 upvotes · 93.6K 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

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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.

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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 .

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Interest over time
Reviews of Bootstrap and Python
Avatar of longgge
pm at 36kr
Review ofBootstrapBootstrap

我们团队一直在使用bootstrap,非常简单易用,并且有帮助。支持也很到位,很喜欢!用了4年的时间,会持续的用下去,加油!!Bootstrap!!!

Review ofBootstrapBootstrap

We have been using it for the past 3 years and have no complaints

Review ofBootstrapBootstrap

Good service with a good price, worth the money.

How developers use Bootstrap 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 StackShare
StackShare uses BootstrapBootstrap

Leanstack was on Bootstrap 2. Chose this because it is wildly popular, so it’s active, has been used a lot in production, and has a ton of features. Anything you need to do from a UI perspective, there’s likely a plugin for it already part of the library. Haven’t tried the others, but we're happy with BS.

For StackShare, we upgraded to Bootstrap 3. I don’t like that they changed the name of columns, essentially breaking the grid layout for Bootstrap 2 and below, so that was a real pain to update. I hope they don’t do that again. Once we have more bandwidth, we’re totally going to decouple our markup from Bootstrap.

Avatar of shridhardalavi
shridhardalavi uses BootstrapBootstrap

Bootstrap is a framework to help you design websites faster and easier. It includes HTML and CSS based design templates for typography, forms, buttons, tables, navigation, modals, image carousels, etc. It also gives you support for JavaScript plugins. Bootstrap's responsive CSS adjusts to phones, tablets, and desktops Bootstrap is compatible with all modern browsers (Chrome, Firefox, Internet Explorer, Safari, and Opera)

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 CloudRepo
CloudRepo uses BootstrapBootstrap

We started with a bootstrap based template and then completely rewrote it due to poor design of the template. Using boostrap properly was a great experience - once you learn it and use it properly, it's simple to use and very good at being responsive and adapting to the various screen view.

Avatar of Perljobs.Ru
Perljobs.Ru uses BootstrapBootstrap

I simply bought a "job board" template for the website, which is written using Bootstrap 2. I'm hoping to upgrade the site to Boostrap 3 when I'll have a time.

Я просто купил шаблон для доски вакансий, написанный на Boostrap 2. Когда будет время перепишу все на Bootstrap 3.

Avatar of Ujjwal Bhujel
Ujjwal Bhujel uses BootstrapBootstrap

With the advancement in CSS, Bootstrap is creating new milestones when it comes to minimising our CSS codes. So elegant and beautiful yet easy and convenient to use once you go through all the classes and its elements. In addition, its JS function is impressive too.

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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