Anchors Away! More Python Regular Expressions You Wish You Knew

So you already know the basics of regular expressions, or regex, in Python. Things like how to use character sets, meta characters, quantifiers, and capture groups are the basic building blocks, but you are a power user, never satisfied with just the basics. Your text wrangling problems are more intricate than you could ever hope to solve with just those tools. Lucky for you there are more regex concepts in Python to learn. It’s anchors away for more tools for text wrangling goodness!

Not sure about the basics? Check out my piece on the building blocks of regular expressions, or regex, in Python.

(Text) Anchors Away!

Before we can set sail on the SS Regular Expressions, we need to discuss the anchor. More specifically, text anchors. A text anchor says to look for matches either at the beginning or end of a string. In Python, there are 2 types of anchors:

  • ^: Matches the following regex at the beginning of a string
  • $: Matches the preceding regex at the end of a string

As a reminder, to use regex in Python, you need to import the re module. The re.findall() function is particularly useful when experimenting with new regex topics such as anchors. It will return a list containing a vector of the actual values of the matches in the string. Make sure to load the re module before you get started.

import re

Raising the Anchor, the ^ Anchor

To set sail, we must raise the anchor at the beginning of the trip. When working with text data, you may need to match a regex pattern, but only if it appears as the first thing in the string. To do that, we also use an anchor, specifically ^.

To demonstrate, our goal is to find the word “the,” but only if it appears at the beginning of a string.

anchor = 'The ship set sail on the ocean'
anchor_n = 'Ships set sail on the ocean to go places'

Starting with anchor, when we use the ^ anchor to find “the,” we have only one instance of it returned.

anchor01 = re.findall('^[Tt]he', anchor)
print(anchor01)

['The']

We know this is the first instance because “The” at the beginning of the string is capitalized. Now with anchor_n, no results are returned. The regex would normally match “the” in the sentence, but with the ^ anchor it is only checking the beginning of the sentence.

anchor02 = re.findall('^[Tt]he', anchor_n)
print(anchor02)

[]

#data-science #python #regular-expressions #unstructured-data #text-processing

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Anchors Away! More Python Regular Expressions You Wish You Knew
Ray  Patel

Ray Patel

1619518440

top 30 Python Tips and Tricks for Beginners

Welcome to my Blog , In this article, you are going to learn the top 10 python tips and tricks.

1) swap two numbers.

2) Reversing a string in Python.

3) Create a single string from all the elements in list.

4) Chaining Of Comparison Operators.

5) Print The File Path Of Imported Modules.

6) Return Multiple Values From Functions.

7) Find The Most Frequent Value In A List.

8) Check The Memory Usage Of An Object.

#python #python hacks tricks #python learning tips #python programming tricks #python tips #python tips and tricks #python tips and tricks advanced #python tips and tricks for beginners #python tips tricks and techniques #python tutorial #tips and tricks in python #tips to learn python #top 30 python tips and tricks for beginners

Ray  Patel

Ray Patel

1619510796

Lambda, Map, Filter functions in python

Welcome to my Blog, In this article, we will learn python lambda function, Map function, and filter function.

Lambda function in python: Lambda is a one line anonymous function and lambda takes any number of arguments but can only have one expression and python lambda syntax is

Syntax: x = lambda arguments : expression

Now i will show you some python lambda function examples:

#python #anonymous function python #filter function in python #lambda #lambda python 3 #map python #python filter #python filter lambda #python lambda #python lambda examples #python map

Shardul Bhatt

Shardul Bhatt

1626775355

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.

#python development services #python development company #python app development #python development #python in web development #python software development

Mad Libs: Using regular expressions

From Tiny Python Projects by Ken Youens-Clark

Everyone loves Mad Libs! And everyone loves Python. This article shows you how to have fun with both and learn some programming skills along the way.


Take 40% off Tiny Python Projects by entering fccclark into the discount code box at checkout at manning.com.


When I was a wee lad, we used to play at Mad Libs for hours and hours. This was before computers, mind you, before televisions or radio or even paper! No, scratch that, we had paper. Anyway, the point is we only had Mad Libs to play, and we loved it! And now you must play!

We’ll write a program called mad.py  which reads a file given as a positional argument and finds all the placeholders noted in angle brackets like <verb>  or <adjective> . For each placeholder, we’ll prompt the user for the part of speech being requested like “Give me a verb” and “Give me an adjective.” (Notice that you’ll need to use the correct article.) Each value from the user replaces the placeholder in the text, and if the user says “drive” for “verb,” then <verb>  in the text replaces with drive . When all the placeholders have been replaced with inputs from the user, print out the new text.

#python #regular-expressions #python-programming #python3 #mad libs: using regular expressions #using regular expressions

Anchors Away! More Python Regular Expressions You Wish You Knew

So you already know the basics of regular expressions, or regex, in Python. Things like how to use character sets, meta characters, quantifiers, and capture groups are the basic building blocks, but you are a power user, never satisfied with just the basics. Your text wrangling problems are more intricate than you could ever hope to solve with just those tools. Lucky for you there are more regex concepts in Python to learn. It’s anchors away for more tools for text wrangling goodness!

Not sure about the basics? Check out my piece on the building blocks of regular expressions, or regex, in Python.

(Text) Anchors Away!

Before we can set sail on the SS Regular Expressions, we need to discuss the anchor. More specifically, text anchors. A text anchor says to look for matches either at the beginning or end of a string. In Python, there are 2 types of anchors:

  • ^: Matches the following regex at the beginning of a string
  • $: Matches the preceding regex at the end of a string

As a reminder, to use regex in Python, you need to import the re module. The re.findall() function is particularly useful when experimenting with new regex topics such as anchors. It will return a list containing a vector of the actual values of the matches in the string. Make sure to load the re module before you get started.

import re

Raising the Anchor, the ^ Anchor

To set sail, we must raise the anchor at the beginning of the trip. When working with text data, you may need to match a regex pattern, but only if it appears as the first thing in the string. To do that, we also use an anchor, specifically ^.

To demonstrate, our goal is to find the word “the,” but only if it appears at the beginning of a string.

anchor = 'The ship set sail on the ocean'
anchor_n = 'Ships set sail on the ocean to go places'

Starting with anchor, when we use the ^ anchor to find “the,” we have only one instance of it returned.

anchor01 = re.findall('^[Tt]he', anchor)
print(anchor01)

['The']

We know this is the first instance because “The” at the beginning of the string is capitalized. Now with anchor_n, no results are returned. The regex would normally match “the” in the sentence, but with the ^ anchor it is only checking the beginning of the sentence.

anchor02 = re.findall('^[Tt]he', anchor_n)
print(anchor02)

[]

#data-science #python #regular-expressions #unstructured-data #text-processing