Blog posts tagged in Python

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Django continues to be the pick of libraries for Python developers. However, there are some not-so-well-known libraries that happened to gain traction among Python developers in 2016. In this blog, I am unveiling 7 Python libraries, excluding the established ones like Django, Flask, etc, that Python developers may find worth considering in 2017.

7 Less-Known-Yet-Helpful Python Libraries for 2017

#1 Arrow

Mobile apps are everywhere, and are often meant for global population - be it for games, social media, health monitoring and whatnot. However, the problem with the standard data/time library for Python is that it doesn’t meet the requirements of modern apps that have their target audience living in different regions and countries. Arrow is one of the libraries to battle with this problem. It comes packed with features that simplify creation, formatting, manipulation and conversion of data, time and time stamps.

The library replaces the need for datetime type that supports Python 2 or 3. With Arrow, developers can convert one time zone to another at ease. Besides, Arrow’s date, time and calendar modules open gates to hassle-free internationalization of applications.

#2 TensorFlow

TensorFlow, launched by Google in November 2015, is an open-source software library for numerical computation. It’s been just over a year since TensorFlow was launched, but the library has already witnessed considerable popularity among Python developers. As a matter of fact, TensorFlow is one of the trendiest GitHub Python repositories.

The library uses data flow graphs capable of running over GPUs and CPUs in a desktop, server, or mobile device with a single API. TensorFlow was originally developed by researchers and engineers in Google's Machine Intelligence research organization for machine learning and deep neural networks research. Although TensorFlow has created ripples in the machine learning community, it has proved to be a good fit for production applications as well.

#3 Zappa

The release of AWS Lambda brought serverless architecture to the fore. Zappa is often said to be the next evolution of application deployment for Python web applications. Rich Jones, the principal author of Zappa and the CTO of Gun.io, said in an interview, “I believe that serverless architectures - that is to say, systems without any permanent infrastructure - are the future of network applications”.


With Zappa, deployment of all Python WSGI applications on AWS Lambda + API Gateway becomes a doddle. The library rids the need of spending hundreds or even thousands of dollars on VPS services like Linode or PaaS services like Heroku. In even simpler words, we can say that Zaapa allows deployment of microservices on the cloud without any hassles of server management. Zappa is faster and scalable, too.

#4 Peewee

Peewee is a simple, expressive ORM for Python and supports SQLite, MySQL, and PostgreSQL. A database is often must for applications that use external data. However, it’s a very challenging task to get and set data from a database through ad hoc connection strings. Here comes Peewee to rescue. The library makes it possible for developers and database engineers to use a safe, programmatic approach to access database resources using a set of intuitive Python classes.

Developers who have previously created a database in SQLAlchemy would agree that it’s much easier to create a database in Peewee. Peewee is also a fit for the Flask web framework.

Click here to learn how to create a database in Peewee

#5 Sanic + uvloop

Sanic is a Flask-like, uvloop-based web framework that makes Python fast. Sanik, designed for Python 3.5, allows developers to build on async/await syntax for defining asynchronous functions. Before Sanic, Python had no way to go so fast. Another library, uvloop, serves as a blazingly fast drop-in replacement for asyncio’s default event loop.


Sanik enables developers to write async applications in Python in a way that is very similar to how they would write them in Node.js. However, going by the Sanic author’s benchmark, uvloop is well capable of handling over 33k requests/sec, which is way more than the capability of Node.js. Since Sanic is still new, more improvements and changes are highly likely to be made into it in near future. You can also contribute to its open source repository.

# 6 Bokeh

You may know that Python offers some libraries, like matplotlib and seaborn, for data visualization. However, Bokeh is a library that is specifically designed for interactive visualization that targets modern web browsers for presentation. Developers can use Bokeh for creating top-notch novel graphics in a way that is much similar to the style of D3.js. Besides, you can extend this capability with high-performance interactivity over very large or streaming datasets.

You may like to give Bokeh a try for creating interactive plots, dashboards, and data applications. Developers can also use Bokeh for transforming visualization written in other libraries, like Matplotlib, Seaborn and ggplot. Bokeh also helps in research by nicely integrating with Jupyter Notebooks.

#7 Blaze

Blaze targets database and array technologies used for analytics queries. NumPy and Pandas don’t help when it comes to running analytics over a dataset that is too big to fit in our computer’s memory. In such a case, developers often resort to PostgreSQL, MongoDB, Hadoop, Spark, out-of-disk storage systems (PyTables and BColz), etc.

However, it’s a very challenging task to understand how each system works and enters data into the proper form. Due to lack of learning about how to mix and migrate data between new technologies, it becomes very difficult to derive effective results from data analytics. Blaze ends this predicament by providing a uniform interface to a variety of database technologies and abstractions for migrating data. Blaze is a good option for expressing computations.


Although there are many other less-known-yet-effective Python libraries, like Gym + Universe, Boto3, Hug, Scrapy, Beautiful Soup and many more, I have picked only seven as the blog could go endless. Python developers can explore these libraries to see if they fit into their needs and choose accordingly.


Have you ever used any of the above seven libraries before? Do you want to add more to what’s already being discussed? Please share your views in the comment box below.
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Python developers have a big pool of frameworks to choose from for their web projects. However, Django, without a shred of doubt, has become the most popular web framework among Python developers world over. Through this blog, I am throwing light on why Python developers prefer Django to other popular Python web frameworks, such as Flask, Pyramid, Tornado, Bottle, Diesel, Pecan, Falcon, and many more.


Before jumping on to the virtues of Django, let’s understand in brief what a web framework is


A web framework is a code library that makes it easier for developers to build dynamic websites, web applications and web services. It’s a known fact that every site has a common set of functionality (like handling sessions, data validation, etc) that you need to re-write each time you create a website. This makes the task mundane and tedious. However, using a web framework ends your plight of re-writing common set of functionalities each time you create a website, resulting in faster development. In a nutshell, web frameworks ease web development life.


If you want to dive deep into web frameworks and their benefits, click here.

Why Django is the Best Web Framework for Python Developers

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Django is a high-level, MVC-style, open-source collection of libraries written in Python. Django, also called “the framework for perfectionists with deadlines," was originally designed for news sites as it allows developers to write database-driven web applications without having to start coding from scratch.


Besides faster completion of common web development tasks, Django helps keep the design clean and pragmatic. Django is the best place for new Python web developers as the official documentation and tutorials are some of the best in software development.


The tech market is flooded with a gamut of web frameworks, but Django sits nicely at the top when it comes to the most popular server-side web frameworks. The motto behind designing Django was simple: Don’t repeat yourself. Django is written in Python, therefore emphasizes efficiency improvement by minimizing the hassle of writing too much code. Cloud platform support makes Django even a more popular choice for web development.

Key Features of Django

  • Django Comes with “Batteries-Included”


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That Django is based on ”batteries-included” philosophy, you need not to use separate libraries to implement common functionalities, like authentication, URL routing, a templating system, an object-relational mapper (ORM), and database schema migrations. If you are using or have used Flask, you must have noticed that it calls for a separate library like Flask-Login to perform user authentication. Such is not the case with Django.

  • Free API


With Django, it’s easy to generate a Python API based on your models. No additional coding required as a simple command is good enough to begin generating APIs.


  • Unique Admin Interface

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Image Courtesy: Django documentation


You can have information on your site from outside contributors even before the site is completely built. Such is the power of Django. The framework empowers you to quickly and easily generate an administration site straight from an application's models.


  • Code Layout


In contrast to most web frameworks, Django makes it easier to plug new capabilities in your product by using things called applications. As a result, developers feel encouraged to write code that is self contained.


  • Django’s ORM Takes Care of Databases

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Django’s Object Relational Mapper (ORM) takes care of databases. So, no hassles of dealing with the Structured Query Language (SQL), which is mostly used to query the database for the data needed. Unlike many other Python frameworks that directly work on the database via SQL, Django developers have a unique option to manipulate the corresponding Python model object. Django works out-of-the-box with relational database management systems like PostgreSQL, MySQL, SQLite, and Oracle.


Click here to learn the basics of data management with Django and its ORM.


  • Robust Built-in Template System


Based on the inheritance system, Django’s templates allow developers to build entire, dynamic websites out of a very small amount of front-end code. Thanks to the option to replace certain elements of templates with other, context specific elements. Imagine a situation where you know that every page of your site is going to have a header and a footer. Now, you first need to write the code in the site’s base template. And then, you can alter the components between those two things dynamically, from other parts of the application.


  • Simple, Readable URLs


It’s difficult to properly read URLs developed in PHP os ASP. With Django, you can create simple and easy-to-read URLs, which is good for both human beings and search engines. You can create readable URLs with other frameworks too, but none is as easy as Django is for URL construction.


  • Enables Quick and Easy Creation of RSS and Atom feeds


With Django, you can quickly and easily create RSS and Atom feeds by creating a simple Python class.

  • Automatically Creates Tables in Database


If there is a table missing in your database, you can automatically create it by executing the migrate command in Django.



  • Easy Database Migrations


One of the most useful features of Django is database migrations. With Django’s migrations, you can change a database schema in quick time. It’s also easy to track your database schema and its associated changes. Migration names help in managing version control, and a plethora of options are available to merge versions and make modifications.


  • Security


Django is highly secured. The framework comes with default protection against XSS attacks, CSRF attacks, SQL injections, clickjacking, user management, cookies, email header injection, cryptography, directory traversal etc.



Django has a very dynamic community, with 80,000 StackOverflow issues and numerous blogs from the developers and power users. Some popular websites that use Django are Bitbucket, Pinterest, Instagram, and The Onion. Django continues to soar in popularity and is likely to remain the most popular choice of Python developers.


PHP vs Ruby vs Python: Which Language is the Best for Your Career and Prospects

 

Have you used Django for a project before? Do you really think that Django is the best framework for Python developers? As always, your views are vital for all our readers, please share them in the comment box below.

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