Python calculates expressions based on the below rules , these are generally the same as those in algebra.
Expression in Parenthesis
Parenthesis ( ) are evaluated first , any expression between the parenthesis will evaluate the value first and results will be further processed.
Exponentiation
are the second set of expression that are evaluated, if there are multiple expression then Python will evaluate each from right to left.
Multiplication , Division and Modulus
are on the same level of precedence. In case of multiple occurrence Python will evaluate each from left to right.
Addition and Substraction
are on the same level of precedence. these are evaluated last unless covered in parenthesis.In case of multiple occurrence these are evaluated from left to right.
Complete list of precedence is available at Python.org
a name identifier in memory that stores the data during the execution of the program. Python is dynamic and declaring a variable is very simple. a = 10 is simply a variable assignment statement.
Assignment operator
In Python assignment operator is simply single = sign , the value on the right get assigned to the name identifier on the left. Below are some of the example assignments a = 20 b = 40 total = a total = a + b
Arithmetic operator
In Python arithmetic operator include + - * / %
Examples : Additionc = a + b Calculates the value of a + b and assigns to c Substractionc = a - b Substracts the value of b from a and assigns to c Multiplicationc = a * b Multiplies the value of a with b and assigns to c Exponentiationc = a ** b Assigns a power b example 3 ** 2 = 9 Divisionc = a / b Divides the value of b from a and assign the new value to c Floor Divisionc = a // b Divides the value of b from a and yeild the real number of higher end and assign the new value to c Modulusc = a % b gives the remainder value as the output 9 % 2 gives remainder 1
Arithmetic plus Assignment short form
Arithmetic operator can be used along with the assignment operator to form a shorter statement
Python is one of the most popular language today , it is dynamic, general purpose programming language, it has a long history of over few decades but in recent time it has gained enormous attention specially with cloud computing.
Python is not only used for cloud application but with huge module library it is used all sort of applications such as desktop application , scripting and automation , web application , machine learning , data analysis and many more.
One of the recent projects that has raised Python value is OpenStack Cloud , this project is written in Python and utilizes libraries to integrate different part of the Cloud. This has raised the value of Python in Enterprises such as Facebook , Microsoft , Google and Amazon to name a few.
Though Python is highly in demand there are some advantages and disadvantages of using Python and it is good to understand those before considering Python for your next project.
Pro’s
Easy Python Syntax
Python was designed keeping simplicity in mind , its code is simple and easy to read as compared to other high level languages such as Java , C++ etc.
Object Oriented
Python is Object oriented , one of the main concept that makes it is a great choice is concept of objects, everything is an object including all the basic data types such as strings and integers are considered object and developer can apply methods on these objects.
Libraries
Python has a huge collection of libraries that makes the life much more easier , many of the task can be performed with very few lines of code. There are two type of libraries , Python Standard Library and 3rd Party libraries developed by Vendors for there own products.
Python is extensible
Python code can integrate with C / C++ and that makes it very extensible language , basically Python was used mainly for system integration in the past but in recent years it has developed into a more robust platform.
Portable
Languages like C and C++ the code varies from platform to platform example libraries for Windows and Linux might differ but that is not the case with Python , here you code once and you can run it anywhere. This is called write once and run anywhere.
Interpreted
Python code get executed Line by Line and thus debugging is easier and simpler
Open Source , Community support
Python is an open source language and it has a huge community support , more and more people are using Python and its support is increasing as well , many Enterprises have jumped in to adopt Python and that is increasing community greatly.
Con’s
Speed
Python as compared to low level languages like C / C++ is slow due to the structure, Python code is compiled into byte code at runtime while the C / C++ code is compiled before run-time.
Memory Utilization
for memory intensive application Python is not a good choice , the flexibility of data-types brings overhead in form of memory consumption.
Threading Issues
Multi-threading is another area where Python does not really perform as compared to other High level languages like Java , this is due to Global interpreter lock (GIL) which allows only one thread to execute at a time. As a result, single-threaded application perform better with Python.
Mobile Development
As compared to Java , Python is not greatly used for Mobile applications and thus does not have great support for Mobile devices. It is easy to use Python for mobile purposes but configuring require some extra effort.
Python is not native to mobile environment and it is seen by some programmers as a weak language for mobile computing. Android and iOS don’t support Python as an official programming language. Still, Python can be easily used for mobile purposes, but it requires some additional effort.
Conclusion
Python is ideal for creating tools , automation and applications, it is getting more and more support at both community and enterprise level , it is the most in demand language for programming jobs currently available in the market.
DevOps is a software engineering culture and practice that aims to unify software development (Dev) and software Operation (Opps). It is a culture of collaboration between development and operational people.-
It is also important to understand what is NOT DevOps.
Set of Tools There is huge list of tools used in DevOps world, the list is exhaustive but are these tools DevOps , answer is no.
DevOps is a standard answer is no it is not a standard similar to ISO standards or a framework similar to ITIL , DevOps is just a cultural movement, designed to provide delivery and stability at the same time.
DevOps is not a product , it is just a culture that is practice by an entire organization that is performing software development / operation.
DevOps as a job title , yes though it is one of in demand jobs currently there is no such title as DevOps, it is simply a culture practiced by Developers and Operation teams to collaborate and any one with the right experience and knowledge can fit into this role.
DevOps culture change
In the past the developers and operational team were working in silos and each process follow in a serial fashion, this design was very successful in the past decade considering the size of the software and the complexity it brings. SDLC (software development life cycle) models such as WaterFall were used to create and maintain. In today’s 4G world software application are mostly mobile / web-based, updates are very frequent infact some are even updated daily or weekly, and that is where the challenge to manage both development and operation collide. Teams on either end would try to push ends to perform better, this is totally in contrast to the model followed in the past decade.
To overcome this challenge Development and Operation teams were merged a change in the team culture was brought in by applying agile principals to deliver short and fast updates / rollouts to the customer keeping in mind both speed of delivery and operational stability in mind.
Goals of a DevOps culture
Fast time-to-market (TTM)
Few production failures
Immediate recovery from failures
DevOps practices and tools
DevOps performs both Operational and Developer tasks , below are the list of practices that are considered part of Devops practices.
