There has been a significant amount of AI engineering ecosystem that has popped up in the last few years which is helping to expedite the progress in this area. Tools, frameworks, and open source libraries are making boilerplate implementation ready for use by the engineering communities. The trends are so prominent that we are seeing large-scale organizations like Google, Microsoft, and Facebook open sourcing their AI tools and framework to help the engineering community build AI-based solutions. More often than not we see that most of these tools and frameworks are in Python. The use of Python for AI has become dominant in all aspects of AI engineering work like – ML, Data Engineering, Data Science, Model Development, and Deployment as well. 

This begs the question, what is AI, and why the AI Engineering community is looking at Python as a language of choice for AI-based solutions? In the subsequent sections, let us start with building a comprehensive understanding of the Artificial Intelligence domain first, some Python-based tools that are being used, and then understand the key reasons and advantages of using Python for AI.

The AI Landscape and Benefits of using Python for AI

A Brief Journey of Artificial Intelligence (AI)

Artificial Intelligence in general, means the process of making machines mimic human behavior. Founded roughly around 1956, the idea behind Artificial Intelligence was to make machines do things that are considered to be unique human capabilities, like intelligence or intuition. In the early days, the research was mostly around board games or logic experiments. 

In the early days, in some of the cases of rule-based or expert systems, Artificial Intelligence was considered to be a glorified if-else program. This means a lot of domain knowledge of the problem was coded into the system with the help of experts from that area. Checking all possible options and then optimizing the final output. On the basis of the most plausible answer was how AI was used in the initial days.

Machine Learning: The Beginning of an Era

As the research around AI progresses, we saw the dawn of a new class of the Artificial Intelligence subdomain which we affectionately called Machine Learning. The idea was to use statistical models to learn from the data of past observations to build a model which should help explain and predict future observations. The idea of using classifiers, clustering algorithms, and other statistical techniques to make sense of the data started to take shape in academics and industry. 

Python for AI – Tools for Machine Learning 

Machine Learning which uses statistical modelling and needs to train the models with a substantial amount of data generally works with Python and R Frameworks. R is an open-source language and framework for statistical workloads. However, it is majorly preferred by the academic community, and also the library support is still catching up. Python by far is the most dominant language in this space.

The open-source community in the machine learning and statistical modelling scape is very active. Tools like NumPy, Scikit-learn, Pandas, etc. are dominantly used by engineers and scientists alike. The growing community of engineers also adds to the support that a new engineer will get while venturing into this area. 

Deep Learning: Getting Closer to Humanization of ML

Deep Learning is a subset of ML. It loosely represents the way the neurons work in our brain. The neurons are structured in layers of repetitive structures. Thus, when presented with enough data they try to learn from the data with the use of mathematical optimization techniques like gradient descent and backpropagation. 

The current state of massive availability of data and frameworks makes the training of neural networks fairly easy. It has become the tool of choice in many application areas like image processing, text processing, and trading etc.

Python for AI – Tools for Deep Learning

The Deep Learning space in the last decade has seen a massive explosion of tools pouring in from major technology giants like Google, Facebook, and Microsoft. All frameworks almost invariably support Python as the de facto language of choice for training and many for inference as well. Some of the popular frameworks also support other languages too.

Frameworks like Tensorflow, Pytorch, and MXNet are very popular frameworks used for Deep Learning engineering and experimentations. Purposely, it is maintained beginner-friendly. It also works pretty well with other frameworks for Data Processing, Engineering, and Visualization. Deep Learning engineering in general is a very repetitive and experimentation-heavy engineering process. Therefore, it needs to have a language that is flexible and is very expressive in nature. 

Data Engineering: Working with the New Oil

In the age of AI, data is the new oil and data engineering is its refining process. Artificial Intelligence has a huge dependency on data and not just any data but pretty good quality data. However, it is believed that a quality model can be build with Deep Learning. It will always depend on the type of data that we feed into the training of one. So this gives rise to another set of parallel engineering domains called Data Engineering and Data Sciences.

Data Engineering comprises data collection, data processing, data cleaning, governance, analysis, reporting, and also visualization. It deals with building tools and frameworks in place to make the whole workflow seamless and usable for various modeling and reporting tasks which can lead to better decision making. 

Python for AI- Tools for Data Engineering

The Data Engineering process requires frameworks and infrastructure to ingest, process, and store large quantities of data. This includes not just an infrastructure that scales vertically but also horizontally across large server farms. The workflow included data cleaning, feature engineering, and storing a large amount of data. 

The tools include Apache Spark, Kafka, Delta Lake, and many more. This area typically leverages a lot on the existing big data architecture. It also needs to have a very flexible infrastructure in place to play around with data in short iterative cycles. The proliferation of managed data and analytics frameworks is also very commonplace like data bricks.

Data Visualization: Connecting Numbers to Narratives

Journalist and Designer, David McCandless, in his TED talk said, “By visualizing information, we turn it into a landscape that you can explore with your eyes, a sort of information map. And when you’re lost in information, an information map is kind of useful.”

A picture is worth a thousand words and it is not just the numbers but the narrative behind those numbers. That need to be in place for the decision-makers to zero in on the right options. Data Visualization is quite a complex engineering piece that stands at the confluence of art and engineering.

Visualization adds narrative to the numbers and it is very meaningful when conveying the right inputs to the decision-makers in the company. It is easy to process in a condensed form. The verbose nature of the data, in general, is not very expressive to create reports and help decision-makers with the right information they are looking for. Visualization helps to bridge that gap.

Python for AI- Tools for Data Visualization

The Data Visualization tools that are available in python are Matplotlib, Seaborn, Plotly, ggplot, and Altair, etc. The visualization tools need to be simple to use APIs, cross-platform support like browser, etc. It might be helpful if it is interactive in nature. 

Why is Python the Most Preferred Language for AI?

Guido Van Rossum created Python in 1980. Since then because of its simplicity, expressiveness, and flexibility. It has been the language of choice for many general purpose applications for amateur and seasoned programmers alike. A few of the features of Python which plays out to its advantage are:

1. Simple to Learn and Use

It is simple to start and use, the developer can build expertise in this language almost effortlessly. There is a huge buffet of online tutorials that make learning Python extremely easy for beginners. Simple syntax, expressive style, and natural language semantics make it an ideal choice for developers working on AI. Further, doing quick experiments and iterations with the language is very easy because of its interpreted execution format. It can tuned to run extensively fast with the compiled version also available.

2. Mature and Supportive Community 

Python has been around for almost 30 years now and over the years it’s developer community has grown many folds. From documentation to tutorials to books there is an extensive choice of options for taking the skill levels from the beginners level to the expert in a less span of time. Getting help at the time of need builds the confidence in the programmers to dive in. It also means a lot of time saved from reinventing the wheel. 

3. Support from Large Companies 

Python among the current generation of languages possible has the biggest large-scale corporation support among its peers. With Facebook, Amazon, Google, Uber, or in-short almost the whole world is delivering their open-source frameworks and packages in Python. It is invariably becoming the default standard for developers across the globe. 

4. Versatile Open-Source Library Support

Pretty much any domain that we can think of will be very likely to have python libraries and frameworks available for the developers. It saves time, promotes reuse, and also helps to build the community of developers. 

5. Efficient, Reliable, Flexible, and Versatile

Python applications is available everywhere, whether it desktops, servers, or mobile applications. It is by far the most versatile language among the current generation of languages out there. However, the versatility of the language attracts many applications and more developers get added. Big Data, Machine Learning, and Deep Learning are some of the latest areas where Python is finding its application too.

Python has a prominent place in the Data Analytics space. The research community is in love with python and that is evident from its applications. Thousands of Machine Learning libraries are doing round and many more are getting added on a daily basis. 

6. Rapid Automation Prototyping

Python is the poster child for the automation domain. With many tools, libraries, and frameworks in place getting into automation and also mastering the art is relatively easy. In the space of Artificial Intelligence and Data Processing, a lot of automation is required largely. Due to the fact that there is a lot of data to crunch and it is just not possible to handle all this sheer volume without automation. 

Wrapping Up 

Python, with its simplicity, robustness, and expressive nature along with interpreted execution with huge open-source, corporate and community support is just the right mix of everything. Therefore, Artificial Intelligence Engineering is a highly iterative and experimentation-heavy domain. Thus Python is the perfect language to support its applications. No wonder the raging popularity of using Python for AI has only seen an upward trend and will continue to rise in the coming years as well.

We have a huge pool of expert Python Engineers with expertise in all verticals of the Artificial Intelligence domain to help your next big idea. Connect with us.

The post Python for AI: Tools and Key Advantages appeared first on EngineerBabu Blog.

New ideas and innovations are what make the world a dynamic place. Earth is constantly changing, science and technology being a driving force behind the rapid change in every facet of the world. Let us take for instance a boomer and a Gen z. There will always be a visible discrepancy in both generations. The development in the science and technology, Web development, and other aspects back in a Boomer’s time won’t be as robust as the developments in the Gen Zs’.

The way we code, the types of programming language, and the tools needed for those codes have changed. Nowadays, anyone can code because it’s now very easy. That shows how well web development has been modernized.

Back then when NASA wanted to explore the moon, the programming language, tools, etc. used then were a little more complicated than the modern ones, and not too many people knew about them.

For instance, in the Internet sector. We have come a long way in this particular sector. Gone are the days when we had a 2G network connection which was definitely not the fastest internet service. But slowly we moved to a 3G connection which is faster than the former. Then comes the 4G network. Now the major discussion around the world now centers around 5G connection which will be the fastest of the lots.

Impacts Of Web Development

The robust development this sector has undergone in the past years has been a joy to watch and admire. Of course, development never stops, it has no limit. So many breakthroughs, new discoveries and all that. It is safe to say that It just keeps going on and on.

Web development which is otherwise known as web programming basically involves the creation of web applications or developing a website for a private network (intranet) or the internet (which is also known as the World Wide Web).

When we talk about Web applications, we refer to social networking sites such as the popular Facebook, Twitter, YouTube, Reddit, etc, and e-commerce sites such as Jumia (a popular retailing website in West Africa), Amazon, eBay, among others.

Contrary to what everyone says, learning web development/programming is very easy. It just depends on your dedication and the availability of the right tools and guidance.

In order to build a web application, one needs to get familiar with “coding”. Coding refers to the act of writing a computer program by converting ordinary language into code.

Before the advent of python, Java, etc programmers make use of basic C code to develop a website.

Forms Of Web Development

There are two basic forms of web development. They are:

1. Front-end development that is otherwise known as Clients-side development and

2. Back-end development that is also known as Server side development.

1. Front-End Development

This refers to the construction of what the people see when they load your website or web application. This includes web designs, all the web content, and also how visitors react to the web page.

This type of web construction can be done by three basic codes and they are HTML, JavaScript, and CSS Code.

a) HTML stands for HyperText Markup Language. This code is used to write web pages. Everything you see on the website is written with HTML codes.

b) JavaScript: What this code does is to add functionality to a website. Not only this, but it also adds interactivity features to a web page. Programmers use JavaScript to develop different types of applications such as Chatbots, Web, desktops, mobile applications, machine language, amongst others.

As you will expect, this Language has numerous advantages and disadvantages.

The advantages include:

• It is very fast.
• The availability of its server is high
• It has numerous interfaces for better user experience.

The Cons of this language are:

• Bland security on the side of the client
• New features in this Language are not always supported by old browsers.

Generally, JavaScript is used to design web interfaces such as the interactive interface and the general web pages.

c) CSS code: This stands for Cascading Style Sheets. This computer code is used to design webpages. That is, the colors, fonts, scales, etc of a webpage.

2. Back-end Development

This refers to the construction of what goes on behind the web application. It makes use of a database that can be used to generate the front-end.

Codes used in building this includes:

a) PHP

b) Java

c) Nodes.js

d) Python

e) Perl

f) ASP.NET

g) Ruby on Rails, etc.

Let us briefly discuss a few out of these.

Java

Java is used by programmers to build Enterprise applications and applications of different types. Database connection, XML parsing, etc. are some of the tasks Java performs.

The pros of this Language include;

• You only need to write it once as it can run everywhere.
• High security
• It has abundant APIs

The cons include

• It is very slow and it consumes memory.
• It is not written specifically for desktop.

Ruby on Rails

Ruby on rail is an open-source programming language. It allows developers to create web applications faster.

Advantage include:

• It saves time and money.
• It works well with different Technologies.

Disadvantage include:

• It is slow
• It is not really flexible.

What is Python Programming?

Python Programming is arguably one of the best and dynamic programming languages out there. For beginners, it is always advisable that they grab the concept of Python Programming Language before any other computer language because its features are what makes it special.

Python Programming Language is not new in the coding world, it had its inception in the early 1990s. As I said earlier, Python Programming Language has been popular since the 1990s and even as at now, there are millions of people who are still learning this object-oriented programming language.

According to a survey conducted by a popular programming community known as the TIOBE INDEX, their survey shows that Python Programming Language is the third most popular programming language in the world.

Another survey shows that well over 1 million websites in the whole world are Python customers

So, what then is Python?

Python can be seen as an object-oriented and a high-level programming language that is designed in C.

In order not to confuse ourselves, what is the C Programming Language?

C programming language was developed in the 1970s. Despite this, C Programming Language is still widely known as the mother of all programming languages. This is as a result of its powerful nature to support many functionalities. And not only this, but it is also strong enough to interact with the kernel and the hardware unit.

Features of C language include

• Rich Library
• Extensible
• Recursion
• Pointers
• It is fast
• It manages memory efficiently.
• High-level language and
• Structured Language.

Now back to Python Programming Language, this programming language is useful when it comes to the creation of simple and complex operations.

Inbuilt in this computer language are modules and libraries that allow the program to support other types of programming language. Examples of these include Java, C++, C, JSON, amongst others.

Features of Python Programming

Python features are what makes it a very versatile, durable, and dynamic programming language.

When I say that Python language is dynamic, it means that we necessarily do not need to proclaim the type of variable because the python language is dynamically typed.

Let’s take for instance X=10.

The “X” in there can stand for anything such as int, String, etc.

Here are a few out of the numerous features of Python language.

1.  It is very easy to code: Python language is very easy to code, even to beginners. Unlike other languages such as Java, C++, JavaScript, etc that are somewhat hard to code, python on the other hand is very easy to code.

As an upcoming developer, it is always advisable to learn Python because it is a developer-friendly language.

If you can get access to the right tools and tutors, you would be a pro in it within a month.

2. It’s open-source code: When we call something “open source” in programming, we mean that the source code is available to the general public. Not only is it available to the public, but it is also free on their official website.

So, you can download it for personal use and you can also share it with other people.

3. It’s an object-oriented language: This particular feature is what makes Python language stand out among other programming languages. This means that it supports concepts of object encapsulation and classes.

4. Graphical User Interface (GUI) support: Graphical User Interface is a program that is supported by Python. This interface makes use of Python modules such as the PyQt5, PyQt4, TK, wxPython, etc.

By a stretch, PyQt5 is the most populous module that can be used to create a Graphical app using Python.

5. Portable Language: Python is quite a portable language. What I mean by portable is, when there is a working Python code for Windows OS, such Python code can also work on other operating systems (OS) such as Unix, Linux, Mac, Apple, etc without having to alter the code.

This shows just how versatile Python language is.

6. Python is an integration Language: Another important feature of Python language is the ability to integrate another programming language to it.

Languages such as C++, C can be integrated with a Python language.

7. Python is dynamic: Another feature of Python is how dynamic it is. Thus, Python is a dynamically-typed language. That means that variables are not determined in advance, but rather in run time. This helps to save time and rightly increase efficiency.

8. Extensibility: This feature shows that Python is a very extensive language. Python codes can be protruded into C++ or even C language. And not only this, we can as well compile those codes in C/C++ programming language.

Why Python Programming Is Ideal For Startups

Python users are growing daily, many people are beginning to see why it is one – if not the best programming language in the programming world.

For new and existing programmers, choosing Python as their new programming language shouldn’t be much of a problem because this section will expose you to why you should choose Python language.

1. Versatility
2. Excellent MVP development
3. It is ubiquitous
4. User-friendly
5. Security
6. Simplicity
7. Community Support
8. Scalable.

1. VERSATILITY

Python Programming Language is so versatile that it can be used in any web or application development. Python code works well in different development platforms such as Windows, Linus, MacOS, etc. Remarkably, it tends to reduce the cost of development while also saving time.

Python language is used in developing mobile or system games, prototyping, frameworks of web pages, Application used in graphics designing, Data Science, and most recently – in AI development, etc.

As a programmer, if you are developing an application that requires Machine Language (ML), Python Programming Language is your ideal language to use because it is a high-level simple language that makes prototyping super fast, as well as the machine learning algorithm.

2. SECURITY

From other programming languages that I have explained above, it could be deduced that most of them do not guarantee security. Over the past few years, Cybersecurity experts have used Python Programming Language to prevent Cyber attacks from Cybercriminals.  Python offers so many Cybersecurity functions such as malware Analysis, Testing tasks (testing for penetrations, etc), makes debugging very easy. For anyone new in the Cybersecurity field, it is recommended that they start with Python because it is very easy to understand.

3. USER-FRIENDLY

If there is one thing that has made developers fall in love with Python completely, that would be its cool interface and designs. Python is distinguished by its simplicity, neatness, beauty, how well structured it is, how easy to learn, and use it. For startups, learning about Python saves time and money.

4. COMMUNITY SUPPORT

One of the great things about this programming language is its popularity in the coding world. Mainstay developers as well as new developers absolutely love and support it. Python’s programmer community is arguably one of the very best in the world. This means that the Python community is very large.

Programmers in this programming community are readily available to assist you if you encounter a problem or while you are performing a complex task. The aim and object of this group are to improve Python’s functionalities and core features.

5. SCALABLE

Python language offers flexibility to a business venture. Flexibility in the sense that it can scale up and down quite easily. Apart from the fact that Python can easily be maintained, it also facilitates quick and healthy growth.

6. SIMPLICITY

Python is majorly characterized by its simplicity. Unlike other programming languages such as Java, C++, JavaScript, etc. Python is so powerful and yet so simple that even if you are new to programming, its elegant, and simple syntax will help you to quickly grasp the idea of it.

7. EXCELLENT MVP DEVELOPMENT

MVP here stands for Minimum Viable Product. Poor marketing strategies, lack of any viable business models are some of the reasons why businesses fail. Here is a quick fact, almost 70% of new Businesses always fail – is that hard to believe? I think not.  Minimum Viable Product or MVP is a kind of tool that is developed for business owners that would help in measuring customer’s behavior and responses towards a particular Product.

The feedback that the customers gave are then used to develop the final products that will in turn lead to a significant decrease in product failure. Minimum Viable Product is basically a tool for opinion polls. Usually, there are so many Tech stacks that help in developing MVP, they include Ruby on Rails, Python, PHP or Laravel, Node.js, etc. But for the purpose of this discourse, let us look at how Python helps in the development of MVP.

As we all know, Python language is a very dynamic language and it is also an interpreted language. It is useful in the development of Machine Language (ML) and also Artificial intelligence (AI), Chatbots, etc. This makes Python a wonderful tech stacks that empower MVP development.

8. IT IS UBIQUITOUS

When we say something is ubiquitous, we mean it is present everywhere, it can be found anywhere. And such is the nature of the Python language. Even if you are applying for a job, a lot of job listings require applicants to know a thing or two about Python – and that clearly shows how popular the program is.

If you are a computer science student, student of any course related to programming (data scientists, etc.) or just someone that is enthusiastic about computer programming, it is advisable that you know Python Programming Language before any other computer Language. Python is fast which thus aids development as compared to other languages such as Java, JavaScript, C, C++, etc.

Famous companies that use Python: In this section, I am going to list a few out of the numerous big companies that use Python Programming Language, and they include:

Google, Spotify, Quora, Netflix, Dropbox, Reddit, Facebook, Instagram, etc.

Conclusion

From the features and the importance of the Python language that I have explained above, it is not so hard to agree with me that Python is the best, cheapest, and fastest programming Language out there. With its dynamic nature and numerous modules and directory that would aid you in any given task. It is versatile, has a well-run community, user-friendly, scalable, and it is also stable. For new programmers and big companies, Python programming is surely a best bet.

The post Why Python Programming Is Ideal For Startups? appeared first on EngineerBabu Blog.

Python and its Frameworks

1. Bottle: It is basically a microframework that creates a single source file for every application. This microframework of Python was initially developed for building APIs. Bottle framework has no dependencies required for crafting small web applications.
2. CherryPy: CherryPy is a popular open-source, object-oriented Python microframework that generally follows a minimalistic approach. This framework is considered as the oldest microframework as it was launched in June 2002. If you are dealing with this framework, then there is no need to add Apache Server to run the deployed apps. The developer can use any kind of technology to access or template of data.
3. Django: It is a Full-Stack framework. Django is one of the most famous and widely used web development frameworks for developing Python web applications.
   It is free to use and an open-source full-stack framework, which a good number of built-in features to make web development more manageable. It uses ORM for mapping objects to the database. As a result, it allows for less coding and programming.
4. Flask: Flask is a microframework. It is a popular Python framework that is inspired by the Sinatra Ruby framework. The microframework generally requires the Jinja2 template and the Werkzeug WSGI toolkit. All thanks to its lightweight feature and modular design, Flask is readily adaptable.
   Flask facilitates developers to build a unique and prominent web application. This microframework is perfectly suitable for Google App Engine.
5. Pyramid: The Pyramid is another leading framework ofPythons. The main aim of the open-source Python-based web development framework is to get as minimalistic complexity during the development.
   The most and the best aspect of the Pyramid is its ability to work equally well with small as well as full-scale applications with equal time investment. In addition to this, there is a multitude of resources available to extend its abilities as per the requirements.

What makes Python Language an excellent fit for enterprises?

Though Python is packed with many versatile features, there are many other reasons which Python Language a superhero of the IT industry. Just check out this:

• Made for IoT: We live in an era where we all are surrounded by the Internet and the Internet of Things. It has opened the doors for many Python programmers to embrace their skills. The device like Raspberry Pi helps developers to build their own phones, games, cameras with using Python Language. With the help of this, the Python Developers connect them with the real-world market and able to create their own gadgets at a low cost.
• Budget-Friendly: Python suits well to the enterprises with tight or any specific budget, and even it is a perfect choice for big projects as well. The majority of the entrepreneurs and businesses select Python because it enables fast development, less coding comparing to Java, PHP, C++, etc.
• Python is Free: Python is an open-source language, and that is the best part about it. All its libraries, modules, and tools are totally available at no cost, and even in the future, it will remain the same. Many of its IDEs such as; Spyder Python, PTVS Pydev with Eclipse are free for downloading. Isn’t it amazing?
• MVPs & Prototypes: With Python, the developers can create minimum viable products (MVPs), as well as prototypes. Several of tech startup owners find Python an ideal language to develop and prototype proofs-of-concept.
• Huge Productivity: Python follows OOPs (Object Oriented Programming) concept in order to provide better process, unit testing, seamless integration with the text processing capabilities. All these are essential ingredients to improve the productivity and speed of development. If you are looking to develop a sophisticated yet robust multi-protocol network, Python is a smart choice.
  

  

• Scalable: For any business or startup, it is imperative to achieve success and sustain it in the market. To ensure this, Python plays a vital role. Python helps the company to overgrow. It comfortably faces the obstacles that struggle to come on its way and ensure quality growth. With the help of Python, the business is able to survive in the market and produce a stable resultant.
• Robust: Python is the most secure and robust language of this century. Many businesses like media streaming projects or social networks are mostly web-based, and it is a complex problem to keep your content more secure, original, and unaffected. But due to Python’s property of security, all the data is secured without providing any harm.
• User-Friendly: In the software community, Python is recognized as a programming language that is easy to use and intuitive, which makes it user-friendly. Python comprises built-in dictionary data structures that are useful for building fast runtime data structures on Python development. Simultaneously, the platform enables the opportunity for high-level dynamic data typing, which eventually decreases the length of the required support code. As a result,, this tends to be the primary reason behind the liking of Python by many startups and enterprises.
• Third-party Modules: ThePython package PyPI allows us to interact with other platforms and languages swiftly. The indulgence of 3^rd party modules in the packages makes the whole development process very simple.

How are top-notch companies like Facebook, Netflix, and NASA using Python language to embrace their tech stack?

Well, there is no doubt that why Python is so attractive. Not only new startups but many established companies like; Facebook, Netflix, and NASA, are switching their deprecated tech stack to Python. Let’s see how:

Facebook

Facebook not all but a significant amount of code is written in Python language. Facebook is the #1 Social Media platform that connects 100 million people through their web applications. Facebook initially used C++ and PHP but they are so delicate to hack, the founders were looking for some robust and secured language to migrate its code. Python comes with in-built libraries that are easy to use; thus, Facebook’s production engineers do not have to write so much coding and maintenance. In this way, they focus on their real product enhancement. Using Python as a backend technology facebook made its migration cost-effective as fewer engineers require to swap the technology.

A post made by Facebook in the year 2016 states that “Python is presently responsible for the multiple services in the domain of infrastructure management, consisting of the usage of TORconfig for handling networking switch setup & imaging, FBOSS for white box switch CLIs, and use of Dapper to schedule and execute maintenance work.”

• Over 21% percent of overall codebase infrastructure is covered by Python at Facebook while rest is covered by Java, C, and C++ with 9%, 15%, and 55% respectively.
• Use of Python’s framework, ‘Py3’ is increased by 5% more by May 2016.
• Since May 2016 to date, an average of 5000 codes has been modified by more than 1000 committers on. That’s a considerable amount.

Netflix

Netflix uses Python to increase its security and to solve the problem of ambiguity. Netflix engineers were free to choose the language to develop their next code, and they rely on Python. They have noticed a great list of benefits of Python and decide to shift its code. One of the leading and vital places that Python is used is in the Central Alert Gateway.

In an interview, the Netflix spokesperson stated, “We use Python through the full content lifecycle, from deciding which content to fund all the way to operating the CDN that serves the final video to 148 million members.”

When it surveyed, the  Netflix engineers point out the standard library, extremely active development community, and the wide variety of 3^rd -party libraries are available to solve nearly any given problem. In addition to this, as Python is so easy to develop, it has become a basic in many of Netflix’s other services apart from video streaming. In tracking, Netflix has seen a reduction in unexpected expirations drop from one very quarter to none since 2012 and it is considered a big achievement.

NASA

Asking about Python’s selection for NASA web development, the USA’s Senior Project Engineer Robin Friedrich says, “Python allows us to tackle the complexity of programs like the WAS without getting bogged down in the language.” Friedrich conceived of the WAS project in response to a significant gap in the way shuttle mission planning was handling data management.

In addition to this, NASA also uses Python and frameworks in Machine Learning to develop robots that behave like a human in nature. Sofia is the best example of that.

Other Companies using Python Language

Google

Python had great support from Google. The Google founders made this decision that says, “Python where we can, and C++ where we must.” Previously Google used C++ for memory control and low latency. In another way, Python is famous for its easy maintenance policy and it encouraged Google more to shift its code for the best delivery. Today, Python is among the official Google server-side languages, whereas Java, C++, and Go are others, deployed to production

Instagram

Instagram used the Django framework of Python Language to run the world’s most prominent runtime application. Taking of Instagram’s usage of Python, Instagram software engineer Min Ni says, “Initially we chose to use Python as a language owing to its reputation for practicality and simplicity, which well aligns with Instagram’s philosophy, i.e., to do simple things first. Ever since then the engineering team at Instagram has invested its time & resources to keep Python deployment viable at a massive scale they are operating at, which is 800 million monthly active users. Later in 2017, Instagram moved major of their Python codebase from Python 2.7 to Python 3.”

Quora

Quora is a famous open question and answer platform where the crowd asks any type of question. The founder of Quora had long thought about what to implement to make the product more engaging and user friendly. After so many meetings, discussions, and analyses, they zeroed in Python, C++, Java, and Scala. They did not go with C++ because it is proprietary Microsoft language and didn’t want to oblige to any future changes put out by Microsoft. While on the other hand, Java was much painful to write and time-consuming as compared to Python.

So they decided to follow Google’s footsteps and selected Python wherever they could owe the ease of writing & readability it brings. Whereas C++ is being used for performance-critical sessions.

Conclusion:

There are a few more which I haven’t discussed here like; Spotify, Reddit, DropBox, ET Cetera. So this, not the end, there are many sectors where Python is raising its flag and making the world a different place to live. It has an enormous impact on Healthcare, logistics, Space, and Aeronautics industry. Python has a massive market for the coverup. Do you want to discuss more about it, drop me an email: mayank@engineerbabu.com or for instant chat, click here.

Why hire Python developers from India uncommonly from a city like Indore?

• India is very cost-effective. If you hire a developer with $150-$200/hr USD in the USA, you can find a better developer with more skills in $25-$40/hr.
• The world’s prominent markets like North America, Australia, Singapore, UK, Eastern Europe, and South America are relatively costlier.
• Indore is a small city with a population of around 35 lakh, which provides excellent commutation with less traffic.
• A survey suggested that the export revenue of the IT industry is expected to grow 8-9 percent per year and reach 135-137 billion US dollars in the year 2019.
• The hassle-free investment in India attracts businesses to hire Python developers from India.

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Thank You

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