The document discusses regular expressions (regex) in Python. It provides examples of using regex to search for patterns in strings, extract matches, and find and group substrings. Key concepts covered include regex syntax like anchors, character classes, repetition, capturing groups, greedy/non-greedy matching, and the re module's functions like search, findall, finditer, and sub. Real-world applications mentioned include validating formats like IP addresses and parsing structured data.
Ejercicios de estilo en la programaciónSoftware Guru
El escritor francés Raymond Queneau escribió a mediados del siglo XX un libro llamado "Ejercicios de Estilo" donde mostraba una misma historia corta, redactada de 99 formas distintas.
En esta plática realizaremos el mismo ejercicio con un programa de software. Abarcaremos distintos estilos y paradigmas: programación monolítica, orientada a objetos, relacional, orientada a aspectos, monadas, map-reduce, y muchos otros, a través de los cuales podremos apreciar la riqueza del pensamiento humano aplicado a la computación.
Esto va mucho más allá de un ejercicio académico; el diseño de sistemas de gran escala se alimenta de esta variedad de estilos. También platicaremos sobre los peligros de quedar atrapado bajo un conjunto reducido de estilos a lo largo de tu carrera, y la necesidad de verdaderamente entender distintos estilos al diseñar arquitecturas de sistemas de software.
Semblanza del conferencista:
Crista Lopez es profesora en la Facultad de Ciencias Computacionales de la Universidad de California en Irvine. Su investigación se enfoca en prácticas de ingeniería de software para sistemas de gran escala. Previamente, fue miembro fundador del equipo en Xerox PARC creador del paradigma de programación orientado a aspectos (AOP). Crista es una de las desarrolladoras principales de OpenSimulator, una plataforma open source para crear mundos virtuales 3D. También es fundadora de Encitra, empresa especializada en la utilización de la realidad virtual para proyectos de desarrollo urbano sustentable. @cristalopes
The Key Difference between a List and a Tuple. The main difference between lists and a tuples is the fact that lists are mutable whereas tuples are immutable. A mutable data type means that a python object of this type can be modified. Let's create a list and assign it to a variable.
Ejercicios de estilo en la programaciónSoftware Guru
El escritor francés Raymond Queneau escribió a mediados del siglo XX un libro llamado "Ejercicios de Estilo" donde mostraba una misma historia corta, redactada de 99 formas distintas.
En esta plática realizaremos el mismo ejercicio con un programa de software. Abarcaremos distintos estilos y paradigmas: programación monolítica, orientada a objetos, relacional, orientada a aspectos, monadas, map-reduce, y muchos otros, a través de los cuales podremos apreciar la riqueza del pensamiento humano aplicado a la computación.
Esto va mucho más allá de un ejercicio académico; el diseño de sistemas de gran escala se alimenta de esta variedad de estilos. También platicaremos sobre los peligros de quedar atrapado bajo un conjunto reducido de estilos a lo largo de tu carrera, y la necesidad de verdaderamente entender distintos estilos al diseñar arquitecturas de sistemas de software.
Semblanza del conferencista:
Crista Lopez es profesora en la Facultad de Ciencias Computacionales de la Universidad de California en Irvine. Su investigación se enfoca en prácticas de ingeniería de software para sistemas de gran escala. Previamente, fue miembro fundador del equipo en Xerox PARC creador del paradigma de programación orientado a aspectos (AOP). Crista es una de las desarrolladoras principales de OpenSimulator, una plataforma open source para crear mundos virtuales 3D. También es fundadora de Encitra, empresa especializada en la utilización de la realidad virtual para proyectos de desarrollo urbano sustentable. @cristalopes
The Key Difference between a List and a Tuple. The main difference between lists and a tuples is the fact that lists are mutable whereas tuples are immutable. A mutable data type means that a python object of this type can be modified. Let's create a list and assign it to a variable.
A tour of Python: slides from presentation given in 2012.
[Some slides are not properly rendered in SlideShare: the original is still available at http://www.aleksa.org/2015/04/python-presentation_7.html.]
Beginning Haskell, Dive In, Its Not That Scary!priort
Haskell can get a bit of a reputation for being this lofty, academic, difficult to learn language. This talk aims to dispel this myth and offer an introduction to this beautiful and pragmatic language. From the point of view of someone who has been functional programming in Scala and Clojure for a while now, but who has, more recently been taking a dive into Haskell, this talk will give a basic introduction to Haskell. Hopefully it will encourage anyone who hasn't tried functional programming in Haskell to dive in too and give it a go.
The talk will be a whistle stop tour of some functional programming fundamentals in Haskell from basic data structures, logic constructs, functional transformations, recursion to some of the basics of Haskell's type system with data declarations and type classes.
JDD2015: Functional programing and Event Sourcing - a pair made in heaven - e...PROIDEA
Contact
FUNCTIONAL PROGRAMING AND EVENT SOURCING - A PAIR MADE IN HEAVEN - EXTENDED, 2 HOURS LONG BRAINWASH
TL;DR: This is talk is a solid introduction to two (supposedly) different topics: FP & ES. I will cover both the theory and the practice. We will emerage ES+FP application starting from ES+OO one.
While reading blogs or attending conferences, you might have heard about Event Sourcing. But didn't you get this feeling, that while there is a lot of theory out there, it is really hard to see a hands-on example? And even if you find some, those are always orbiting around Object Oriented concepts?
Greg Young once said "When we talk about Event Sourcing, current state is a left-fold of previous behaviours. Nothing new to Functional Programmers". If Functional Programming is such a natural concept for event sourced systems, shouldn't they fit together on a single codebase?
In this talk we will quickly introduce Event Sourcing (but without going into details), we will introduce some functional concepts as well (like State monad). Armoured with that knowledge we will try to transform sample ES application (OO-style, tightly coupled with framework) to frameworkless, FP-style solution).
Talk is targeted for beginner and intermediate audience. Examples will be in Scala but nothing fancy - normal syntax.
This talk is an extended version of a presentation "Event Sourcing & Functional Programming - a pair made in heaven". It is enriched with content of presentations: "Monads - asking the right question" and "It's all been done before - The Hitchhiker's Guide to Time Travel".
Regular expressions are used to identify whether a pattern exists in a given sequence of characters (string) or not. They help in manipulating textual data, which is often a pre-requisite for data science projects that involve text mining. You must have come across some application of regular expressions: they are used at the server side to validate the format of email addresses or password during registration, used for parsing text data files to find, replace or delete certain string, etc.
This presentation is all about various built in
datastructures which we have in python.
List
Dictionary
Tuple
Set
and various methods present in each data structure
A tour of Python: slides from presentation given in 2012.
[Some slides are not properly rendered in SlideShare: the original is still available at http://www.aleksa.org/2015/04/python-presentation_7.html.]
Beginning Haskell, Dive In, Its Not That Scary!priort
Haskell can get a bit of a reputation for being this lofty, academic, difficult to learn language. This talk aims to dispel this myth and offer an introduction to this beautiful and pragmatic language. From the point of view of someone who has been functional programming in Scala and Clojure for a while now, but who has, more recently been taking a dive into Haskell, this talk will give a basic introduction to Haskell. Hopefully it will encourage anyone who hasn't tried functional programming in Haskell to dive in too and give it a go.
The talk will be a whistle stop tour of some functional programming fundamentals in Haskell from basic data structures, logic constructs, functional transformations, recursion to some of the basics of Haskell's type system with data declarations and type classes.
JDD2015: Functional programing and Event Sourcing - a pair made in heaven - e...PROIDEA
Contact
FUNCTIONAL PROGRAMING AND EVENT SOURCING - A PAIR MADE IN HEAVEN - EXTENDED, 2 HOURS LONG BRAINWASH
TL;DR: This is talk is a solid introduction to two (supposedly) different topics: FP & ES. I will cover both the theory and the practice. We will emerage ES+FP application starting from ES+OO one.
While reading blogs or attending conferences, you might have heard about Event Sourcing. But didn't you get this feeling, that while there is a lot of theory out there, it is really hard to see a hands-on example? And even if you find some, those are always orbiting around Object Oriented concepts?
Greg Young once said "When we talk about Event Sourcing, current state is a left-fold of previous behaviours. Nothing new to Functional Programmers". If Functional Programming is such a natural concept for event sourced systems, shouldn't they fit together on a single codebase?
In this talk we will quickly introduce Event Sourcing (but without going into details), we will introduce some functional concepts as well (like State monad). Armoured with that knowledge we will try to transform sample ES application (OO-style, tightly coupled with framework) to frameworkless, FP-style solution).
Talk is targeted for beginner and intermediate audience. Examples will be in Scala but nothing fancy - normal syntax.
This talk is an extended version of a presentation "Event Sourcing & Functional Programming - a pair made in heaven". It is enriched with content of presentations: "Monads - asking the right question" and "It's all been done before - The Hitchhiker's Guide to Time Travel".
Regular expressions are used to identify whether a pattern exists in a given sequence of characters (string) or not. They help in manipulating textual data, which is often a pre-requisite for data science projects that involve text mining. You must have come across some application of regular expressions: they are used at the server side to validate the format of email addresses or password during registration, used for parsing text data files to find, replace or delete certain string, etc.
This presentation is all about various built in
datastructures which we have in python.
List
Dictionary
Tuple
Set
and various methods present in each data structure
A high level introduction to R statistical programming language that was presented at the Chicago Data Visualization Group's Graphing in R and ggplot2 workshop on October 8, 2012.
Regular expressions are the main way many tools matches patterns within strings.
For example, finding pieces of text within a larger doc, or finding a restriction site within a larger sequence. This slide report illustrates what a RegEx is and what you can do to find, match, compare or replace text of documents or code.
Francesca Gottschalk - How can education support child empowerment.pptxEduSkills OECD
Francesca Gottschalk from the OECD’s Centre for Educational Research and Innovation presents at the Ask an Expert Webinar: How can education support child empowerment?
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
The Roman Empire A Historical Colossus.pdfkaushalkr1407
The Roman Empire, a vast and enduring power, stands as one of history's most remarkable civilizations, leaving an indelible imprint on the world. It emerged from the Roman Republic, transitioning into an imperial powerhouse under the leadership of Augustus Caesar in 27 BCE. This transformation marked the beginning of an era defined by unprecedented territorial expansion, architectural marvels, and profound cultural influence.
The empire's roots lie in the city of Rome, founded, according to legend, by Romulus in 753 BCE. Over centuries, Rome evolved from a small settlement to a formidable republic, characterized by a complex political system with elected officials and checks on power. However, internal strife, class conflicts, and military ambitions paved the way for the end of the Republic. Julius Caesar’s dictatorship and subsequent assassination in 44 BCE created a power vacuum, leading to a civil war. Octavian, later Augustus, emerged victorious, heralding the Roman Empire’s birth.
Under Augustus, the empire experienced the Pax Romana, a 200-year period of relative peace and stability. Augustus reformed the military, established efficient administrative systems, and initiated grand construction projects. The empire's borders expanded, encompassing territories from Britain to Egypt and from Spain to the Euphrates. Roman legions, renowned for their discipline and engineering prowess, secured and maintained these vast territories, building roads, fortifications, and cities that facilitated control and integration.
The Roman Empire’s society was hierarchical, with a rigid class system. At the top were the patricians, wealthy elites who held significant political power. Below them were the plebeians, free citizens with limited political influence, and the vast numbers of slaves who formed the backbone of the economy. The family unit was central, governed by the paterfamilias, the male head who held absolute authority.
Culturally, the Romans were eclectic, absorbing and adapting elements from the civilizations they encountered, particularly the Greeks. Roman art, literature, and philosophy reflected this synthesis, creating a rich cultural tapestry. Latin, the Roman language, became the lingua franca of the Western world, influencing numerous modern languages.
Roman architecture and engineering achievements were monumental. They perfected the arch, vault, and dome, constructing enduring structures like the Colosseum, Pantheon, and aqueducts. These engineering marvels not only showcased Roman ingenuity but also served practical purposes, from public entertainment to water supply.
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdfTechSoup
In this webinar you will learn how your organization can access TechSoup's wide variety of product discount and donation programs. From hardware to software, we'll give you a tour of the tools available to help your nonprofit with productivity, collaboration, financial management, donor tracking, security, and more.
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
9. Regular Expressions
http://en.wikipedia.org/wiki/Regular_expression
In computing, a regular expression, also
referred to as "regex" or "regexp", provides a
concise and flexible means for matching
strings of text, such as particular characters,
words, or patterns of characters. A regular
expression is written in a formal language that
can be interpreted by a regular expression
processor.
Really clever "wild card" expressions for
matching and parsing strings.
10. Understanding Regular Expressions
• Very powerful and quite cryptic
• Fun once you understand them
• Regular expressions are a language
unto themselves
• A language of "marker characters" -
programming with characters
• It is kind of an "old school"
language - compact
11. Regular Expression Quick Guide
^ Matches the beginning of a line
$ Matches the end of the line
. Matches any character
s Matches whitespace
S Matches any non-whitespace character
* Repeats a character zero or more times
*? Repeats a character zero or more times (non-greedy)
+ Repeats a chracter one or more times
+? Repeats a character one or more times (non-greedy)
[aeiou] Matches a single character in the listed set
[^XYZ] Matches a single character not in the listed set
[a-z0-9] The set of characters can include a range
( Indicates where string extraction is to start
) Indicates where string extraction is to end
12. The Regular Expression Module
• Before you can use regular expressions in
your program, you must import the library
using "import re"
• You can use re.search() to see if a string
matches a regular expression similar to
using the find() method for strings
• You can use re.findall() extract portions of
a string that match your regular expression
similar to a combination of find() and
slicing: var[5:10]
13. Wild-Card Characters
• The dot character matches any
character
• If you add the asterisk character,
the character is "any number of
times"
^X.*:
Match the start of the line
Match any character
Many times
14. Matching and Extracting Data
• The re.search() returns a True/False
depending on whether the string matches
the regular expression
• If we actually want the matching strings
to be extracted, we use re.findall()
>>> import re
>>> x = 'My 2 favorite numbers are 19 and 42'
>>> y = re.findall('[0-9]+',x)
>>> print y
['2', '19', '42']
15. Warning: Greedy Matching
• The repeat characters (* and +) push outward in both directions
(greedy) to match the largest possible string
>>> import re
>>> x = 'From: Using the : character'
>>> y = re.findall('^F.+:', x)
>>> print y
['From: Using the :']
^F.+:
One or more
characters
First character in the
match is an F
Last character in the
match is a :
16. Non-Greedy Matching
• Not all regular expression repeat codes are
greedy! If you add a ? character - the + and *
chill out a bit...
>>> import re
>>> x = 'From: Using the : character'
>>> y = re.findall('^F.+?:', x)
>>> print y
['From:']
^F.+?:
One or more
characters but
not greedily
First character in the
match is an F
Last character in the
match is a :
17. Fine Tuning String Extraction
• Parenthesis are not part of the match -
but they tell where to start and stop what
string to extract
From stephen.marquard@uct.ac.za Sat Jan 5 09:14:16
2008
>>> y = re.findall('S+@S+',x)
>>> print y
['stephen.marquard@uct.ac.za']
>>> y = re.findall('^From (S+@S+)',x)
>>> print y
['stephen.marquard@uct.ac.za']
^From (S+@S+)
18. The Double Split Version
• Sometimes we split a line one way and then grab
one of the pieces of the line and split that piece
again
From stephen.marquard@uct.ac.za Sat Jan 5 09:14:16
2008
words = line.split()
email = words[1]
pieces = email.split('@')
print pieces[1]
stephen.marquard@uct.ac.za
['stephen.marquard', 'uct.ac.za']
'uct.ac.za'
19. The Regex Version
From stephen.marquard@uct.ac.za Sat Jan 5 09:14:16
2008
import re
lin = 'From stephen.marquard@uct.ac.za Sat Jan 5 09:14:1
y = re.findall('@([^ ]*)',lin)
print y['uct.ac.za']
'@([^ ]*)'
Look through the string until you find an at-sign
Match non-blank character
Match many of them
20. Escape Character
• If you want a special regular expression
character to just behave normally (most
of the time) you prefix it with ''
>>> import re
>>> x = 'We just received $10.00 for cookies.'
>>> y = re.findall('$[0-9.]+',x)
>>> print y
['$10.00']
$[0-9.]+
A digit or periodA real dollar sign
At least one
or more
21. Real world problems
• Match IP Addresses, email addresses,
URLs
• Match balanced sets of parenthesis
• Substitute words
• Tokenize
• Validate
• Count
• Delete duplicates
• Natural Language processing
22.
23.
24. RE in Python
• Unleash the power - built-in re module
• Functions
– to compile patterns
• compile
– to perform matches
• match, search, findall, finditer
– to perform operations on match object
• group, start, end, span
– to substitute
• sub, subn
• - Metacharacters
26. Examples 2
import re
dna = "ATCGCGAATTCAC"
if re.search(r"GAATTC", dna):
print("restriction site found!")
27. Examples 3
scientific_name = "Homo sapiens"
m = re.search("(.+) (.+)", scientific_name)
if m:
genus = m.group(1)
species = m.group(2)
print("genus is " + genus + ", species is " + species)
28. Examples 4
regex = r"([a-zA-Z]+) d+"
#finditer() returns an iterator that produces Match instances instead of the strings
returned by findall()
matches = re.finditer(regex, "June 24, August 9, Dec 12")
for match in matches:
print(match)
print ("Match at index:",match.group(0),match.group(1),match.start(), match.end())
29. Examples 5
text = 'abbaaabbbbaaaaa'
pattern = 'ab'
for match in re.finditer(pattern, text):
s = match.start()
e = match.end()
print ('Found "%s" at %d:%d' % (text[s:e], s, e))
30. Exercise 1
1. Which of following 4 sequences
(seq1/2/3/4)
a) contains a “Galactokinase signature”
b) How many of them?
http://us.expasy.org/prosite/