Mastering String Methods in Python

A string is a data type in Python programming language that’s used to represent a piece of text. They are super flexible and necessary to appropriately represent text inputs in code. As a result, learning how to make the most out of them is a must.

Once the basic syntax of these data types is learnt, you can start growing your Python knowledge which will let you to more and more interesting operations with string handling. Always remember that the main goal of the learning process is to write clean and efficient code to automate routinary tasks, without memorizing any method, as you’ll completely understand them once you put them into practice.

Table of contents:

1. Introduction to Strings (3 min read).

2. Modifying Strings (2 min read).

3. Transforming Strings (2 min read).

4. Formatting Strings (1 min read).

1. Introduction to Strings

A string is a Python data type that’s used to represent a piece of text. It’s written between quotes, either double quotes or single quotes and can be as short as zero characters, or empty string, or as long as you wish.

Strings can be concatenated to build longer strings using the plus sign and also they can be multiplied by a number, which results in the continuous repetition of the string as many times as the number indicates. Also, if we want to find out the length of the string, we simply have to use the len() function as shown in the example below:

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What is GEEK

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Why use Python for Software Development

No programming language is pretty much as diverse as Python. It enables building cutting edge applications effortlessly. Developers are as yet investigating the full capability of end-to-end Python development services in various areas. 

By areas, we mean FinTech, HealthTech, InsureTech, Cybersecurity, and that's just the beginning. These are New Economy areas, and Python has the ability to serve every one of them. The vast majority of them require massive computational abilities. Python's code is dynamic and powerful - equipped for taking care of the heavy traffic and substantial algorithmic capacities. 

Programming advancement is multidimensional today. Endeavor programming requires an intelligent application with AI and ML capacities. Shopper based applications require information examination to convey a superior client experience. Netflix, Trello, and Amazon are genuine instances of such applications. Python assists with building them effortlessly. 

5 Reasons to Utilize Python for Programming Web Apps 

Python can do such numerous things that developers can't discover enough reasons to admire it. Python application development isn't restricted to web and enterprise applications. It is exceptionally adaptable and superb for a wide range of uses.

Robust frameworks 

Python is known for its tools and frameworks. There's a structure for everything. Django is helpful for building web applications, venture applications, logical applications, and mathematical processing. Flask is another web improvement framework with no conditions. 

Web2Py, CherryPy, and Falcon offer incredible capabilities to customize Python development services. A large portion of them are open-source frameworks that allow quick turn of events. 

Simple to read and compose 

Python has an improved sentence structure - one that is like the English language. New engineers for Python can undoubtedly understand where they stand in the development process. The simplicity of composing allows quick application building. 

The motivation behind building Python, as said by its maker Guido Van Rossum, was to empower even beginner engineers to comprehend the programming language. The simple coding likewise permits developers to roll out speedy improvements without getting confused by pointless subtleties. 

Utilized by the best 

Alright - Python isn't simply one more programming language. It should have something, which is the reason the business giants use it. Furthermore, that too for different purposes. Developers at Google use Python to assemble framework organization systems, parallel information pusher, code audit, testing and QA, and substantially more. Netflix utilizes Python web development services for its recommendation algorithm and media player. 

Massive community support 

Python has a steadily developing community that offers enormous help. From amateurs to specialists, there's everybody. There are a lot of instructional exercises, documentation, and guides accessible for Python web development solutions. 

Today, numerous universities start with Python, adding to the quantity of individuals in the community. Frequently, Python designers team up on various tasks and help each other with algorithmic, utilitarian, and application critical thinking. 

Progressive applications 

Python is the greatest supporter of data science, Machine Learning, and Artificial Intelligence at any enterprise software development company. Its utilization cases in cutting edge applications are the most compelling motivation for its prosperity. Python is the second most well known tool after R for data analytics.

The simplicity of getting sorted out, overseeing, and visualizing information through unique libraries makes it ideal for data based applications. TensorFlow for neural networks and OpenCV for computer vision are two of Python's most well known use cases for Machine learning applications.

Summary

Thinking about the advances in programming and innovation, Python is a YES for an assorted scope of utilizations. Game development, web application development services, GUI advancement, ML and AI improvement, Enterprise and customer applications - every one of them uses Python to its full potential. 

The disadvantages of Python web improvement arrangements are regularly disregarded by developers and organizations because of the advantages it gives. They focus on quality over speed and performance over blunders. That is the reason it's a good idea to utilize Python for building the applications of the future.

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String methods in Python

String methods:

• str.capitalize(): Returns copy of the string with its first character capitalized and rest of the letters in lowercase.

#capitalize-Only first character of string is capitalized
	s1="example of string methods"
	print (s1.capitalize()) #Output:Example of string methods
	s2="EXAMPLE OF STRING METHODS"
	print (s2.capitalize())#Output:Example of string methods

• str.title()- Returns copy of string where first character in every word is upper case.

s1="example of strings"
	print (s1.title()) #Output:Example Of Strings

• str.casefold(): Returns casefolded copy of the string. Converts string to lower case. Casefolding is similar to lowercasing but more aggressive because it is intended to remove all case distinctions in a string.

#casefold- converts all character to lower case
	s1="Example Of String Methods"
	print (s1.casefold()) #Output:example of string methods

	s2="ß-Beta"
	#ß-lowercase is equivalent to ss. casefold converts it to ss. But lower doesn't do that.
	print (s2.casefold()) #Output: ss-beta
	print (s2.lower())#Output: ß-beta

• str.swapcase():Returns copy of string with uppercase characters converted to lowercase and vice versa.

s1="example of strings"
	print (s1.swapcase()) #Output:EXAMPLE OF STRINGS

	s2="EXAMPLE OF STRINGS"
	print (s2.swapcase()) #Output:example of strings

	s3="Example Of Strings"
	print (s3.swapcase()) #Output:eXAMPLE oF sTRINGS

• str.lower()-Returns copy of string in lowercase.Symbols and numbers are ignored.

s1="Example Of Strings"
	print (s1.lower()) #Output:example of strings

	s2="EXAMPLE OF STRINGS??"
	print (s2.lower())#Output:example of strings??

	s3="1.example of strings?"
	print (s3.lower()) #Output:1.example of strings?

• str.upper()-Returns copy of string in uppercase.Symbols and numbers are ignored.

s1="Example Of Strings"
	print (s1.upper())#Output:EXAMPLE OF STRINGS

	s2="EXAMPLE OF STRINGS??"
	print (s2.upper())#Output:EXAMPLE OF STRINGS??

	s3="1.example of strings?"
	print (s3.upper()) #Output:1.EXAMPLE OF STRINGS?

• str.encode():Returns an encoded version of the string in byte format.

str.encode(encoding=”encoding”,errors=”errors”)

encoding(Optional):Default encoding is “utf-8”

errors(Optional):Default errors is “strict”.Raise unicode error.

s1= "example öf strings"
	print (s1) #Output:example öf strings

	#Use backslash for the character that can't be encoded
	print(s1.encode(encoding="ascii",errors="backslashreplace")) #Output:b'example \\xf6f strings'

	#ignores the character that can't be encoded
	print(s1.encode(encoding="ascii",errors="ignore"))#Output:b'example f strings'

	#replace the character that can't be encoded with the text explanining the character. 
	print(s1.encode(encoding="ascii",errors="namereplace"))#Output:b'example \\N{LATIN SMALL LETTER O WITH DIAERESIS}f strings'

	#Replace the character that can't be encoded with the question mark
	print(s1.encode(encoding="ascii",errors="replace"))#Output:b'example ?f strings'

	#Replace the character that can't be encoded with xml character.
	print(s1.encode(encoding="ascii",errors="xmlcharrefreplace"))#Output:b'example öf strings'

	#strict-Raise Unicode Error
	print(s1.encode(encoding="ascii",errors="strict"))
	#Output:UnicodeEncodeError: 'ascii' codec can't encode character '\xf6' in position 8: ordinal not in range(128)

	#errors are not mentioned.Default is strict-Raise Unicode Error.
	print(s1.encode(encoding="ascii"))
	#Output:UnicodeEncodeError: 'ascii' codec can't encode character '\xf6' in position 8: ordinal not in range(128)

• str.startswith()- Returns True, if the string starts with specified value, otherwise returns False.

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How To Compare Tesla and Ford Company By Using Magic Methods in Python

Magic Methods are the special methods which gives us the ability to access built in syntactical features such as ‘<’, ‘>’, ‘==’, ‘+’ etc…

You must have worked with such methods without knowing them to be as magic methods. Magic methods can be identified with their names which start with __ and ends with __ like init, call, str etc. These methods are also called Dunder Methods, because of their name starting and ending with Double Underscore (Dunder).

Now there are a number of such special methods, which you might have come across too, in Python. We will just be taking an example of a few of them to understand how they work and how we can use them.

1. init

class AnyClass:
    def __init__():
        print("Init called on its own")
obj = AnyClass()

The first example is _init, _and as the name suggests, it is used for initializing objects. Init method is called on its own, ie. whenever an object is created for the class, the init method is called on its own.

The output of the above code will be given below. Note how we did not call the init method and it got invoked as we created an object for class AnyClass.

Init called on its own

2. add

Let’s move to some other example, add gives us the ability to access the built in syntax feature of the character +. Let’s see how,

class AnyClass:
    def __init__(self, var):
        self.some_var = var
    def __add__(self, other_obj):
        print("Calling the add method")
        return self.some_var + other_obj.some_var
obj1 = AnyClass(5)
obj2 = AnyClass(6)
obj1 + obj2

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How to Master Python for Data Science

Here’s the Essential Python you Need for Data Science

you’re embarking on your journey into data science and everyone recommends that you start with learning how to code. You decided on Python and are now paralyzed by the large piles of learning resources that are at your disposal. Perhaps you are overwhelmed and owing to analysis paralysis, you are procrastinating your first steps in learning how to code in Python.

In this article, I’ll be your guide and take you on a journey of exploring the essential bare minimal knowledge that you need in order to master Python for getting started in data science. I will assume that you have no prior coding experience or that you may come from a non-technical background. However, if you are coming from a technical or computer science background and have knowledge of a prior programming language and would like to transition to Python, you can use this article as a high-level overview to get acquainted with the gist of the Python language. Either way, it is the aim of this article to navigate you through the landscape of the Python language at their intersection with data science, which will help you get started in no time.

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Python Tricks Every Developer Should Know

Python is awesome, it’s one of the easiest languages with simple and intuitive syntax but wait, have you ever thought that there might ways to write your python code simpler?

In this tutorial, you’re going to learn a variety of Python tricks that you can use to write your Python code in a more readable and efficient way like a pro.

Let’s get started

Swapping value in Python

Instead of creating a temporary variable to hold the value of the one while swapping, you can do this instead

>>> FirstName = "kalebu"
>>> LastName = "Jordan"
>>> FirstName, LastName = LastName, FirstName 
>>> print(FirstName, LastName)
('Jordan', 'kalebu')

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