The document is a colloquium on using grep and regular expressions. It provides an outline that introduces grep and regular expressions, explains regular expression basics like classes and quantifiers, recommends online tools for testing regular expressions, and provides examples of regular expressions including a regular expression for matching email addresses.
Regular expressions are a powerful tool for searching, matching, and parsing text patterns. They allow complex text patterns to be matched with a standardized syntax. All modern programming languages include regular expression libraries. Regular expressions can be used to search strings, replace parts of strings, split strings, and find all occurrences of a pattern in a string. They are useful for tasks like validating formats, parsing text, and finding/replacing text. This document provides examples of common regular expression patterns and methods for using regular expressions in Python.
This document provides an overview of regular expressions and how they work with patterns and matchers in Java. It defines what a regular expression is, lists common uses of regex, and describes how to create patterns, use matchers to interpret patterns and perform matches, and handle exceptions. It also covers regex syntax like metacharacters, character classes, quantifiers, boundaries, and flags. Finally, it discusses capturing groups, backreferences, index methods, study methods, and replacement methods in the Matcher class.
Regular expressions in Java allow for powerful text manipulation and extraction of parts of strings. A regular expression is a pattern that can match part or all of a string. In Java, a regular expression is compiled into a Pattern object, which is then used to create a Matcher object for a specific string. The Matcher provides methods to find matches and extract matched substrings. Mastering regular expressions requires learning a new "programming language" of punctuation symbols, but they are a useful tool for manipulating text.
This document provides an overview of using regular expressions (regex) in Java. It explains that regex allow you to describe and search for patterns in strings. The java.util.regex package includes the Pattern, Matcher, and PatternSyntaxException classes for working with regex in Java. The document then demonstrates various regex syntax like character classes, quantifiers, capturing groups, boundaries and more through code examples.
Regular expressions (regex) use metacharacters to form patterns for string matching. The basic regex structure includes character classes, quantifiers, and alternation/grouping. In Java, the Pattern class compiles a regex string into a pattern object, and Matcher finds matches in input. Matcher methods like start(), end(), and group() retrieve match details. Regex strings in Java require escaping metacharacters with a backslash to avoid compiler errors.
The document discusses regular expressions and text processing in Python. It covers various components of regular expressions like literals, escape sequences, character classes, and metacharacters. It also discusses different regular expression methods in Python like match, search, split, sub, findall, finditer, compile and groupdict. The document provides examples of using these regular expression methods to search, find, replace and extract patterns from text.
This document provides an overview of regular expressions and the grep command in Unix/Linux. It defines what regular expressions are, describes common regex patterns like characters, character classes, anchors, repetition, and groups. It also explains the differences between the grep, egrep, and fgrep commands and provides examples of using grep with regular expressions to search files.
This document provides an introduction and overview to the Haskell programming language. It discusses Haskell's core concepts like pure functions, immutable data, static typing, and lazy evaluation. It also covers common Haskell tools and libraries, how to write simple Haskell programs, and how to compile and run Haskell code. The document uses examples and interactive sessions to demonstrate Haskell syntax and show how various language features work.
Regular expressions are a powerful tool for searching, matching, and parsing text patterns. They allow complex text patterns to be matched with a standardized syntax. All modern programming languages include regular expression libraries. Regular expressions can be used to search strings, replace parts of strings, split strings, and find all occurrences of a pattern in a string. They are useful for tasks like validating formats, parsing text, and finding/replacing text. This document provides examples of common regular expression patterns and methods for using regular expressions in Python.
This document provides an overview of regular expressions and how they work with patterns and matchers in Java. It defines what a regular expression is, lists common uses of regex, and describes how to create patterns, use matchers to interpret patterns and perform matches, and handle exceptions. It also covers regex syntax like metacharacters, character classes, quantifiers, boundaries, and flags. Finally, it discusses capturing groups, backreferences, index methods, study methods, and replacement methods in the Matcher class.
Regular expressions in Java allow for powerful text manipulation and extraction of parts of strings. A regular expression is a pattern that can match part or all of a string. In Java, a regular expression is compiled into a Pattern object, which is then used to create a Matcher object for a specific string. The Matcher provides methods to find matches and extract matched substrings. Mastering regular expressions requires learning a new "programming language" of punctuation symbols, but they are a useful tool for manipulating text.
This document provides an overview of using regular expressions (regex) in Java. It explains that regex allow you to describe and search for patterns in strings. The java.util.regex package includes the Pattern, Matcher, and PatternSyntaxException classes for working with regex in Java. The document then demonstrates various regex syntax like character classes, quantifiers, capturing groups, boundaries and more through code examples.
Regular expressions (regex) use metacharacters to form patterns for string matching. The basic regex structure includes character classes, quantifiers, and alternation/grouping. In Java, the Pattern class compiles a regex string into a pattern object, and Matcher finds matches in input. Matcher methods like start(), end(), and group() retrieve match details. Regex strings in Java require escaping metacharacters with a backslash to avoid compiler errors.
The document discusses regular expressions and text processing in Python. It covers various components of regular expressions like literals, escape sequences, character classes, and metacharacters. It also discusses different regular expression methods in Python like match, search, split, sub, findall, finditer, compile and groupdict. The document provides examples of using these regular expression methods to search, find, replace and extract patterns from text.
This document provides an overview of regular expressions and the grep command in Unix/Linux. It defines what regular expressions are, describes common regex patterns like characters, character classes, anchors, repetition, and groups. It also explains the differences between the grep, egrep, and fgrep commands and provides examples of using grep with regular expressions to search files.
This document provides an introduction and overview to the Haskell programming language. It discusses Haskell's core concepts like pure functions, immutable data, static typing, and lazy evaluation. It also covers common Haskell tools and libraries, how to write simple Haskell programs, and how to compile and run Haskell code. The document uses examples and interactive sessions to demonstrate Haskell syntax and show how various language features work.
Regular expressions (RegEx) allow defining search patterns to match strings. RegEx use metacharacters like ^, $, *, ?, etc. to specify patterns. The re module in Python provides functions like search(), match(), sub(), split() to work with RegEx patterns. These functions take a pattern and string, and return matches or modified strings. Common tasks like finding, replacing, extracting substrings can be performed using RegEx in Python.
The document provides an introduction to the Python programming language. It covers topics such as data types in Python like integers, floats, strings, tuples, lists, and dictionaries. It also discusses operators, control flow, functions, and how to write and run Python code in the Eclipse IDE.
This document provides 15 examples of using the Linux grep command to search files for text patterns. Some key examples include searching for a string in single or multiple files, ignoring case, using regular expressions to match patterns, displaying lines before/after/around matches, inverting matches, counting matches, and highlighting matched text. The examples demonstrate many useful grep options for finding text in files.
1. This document discusses string operations and methods in Python. It covers topics like equality, numerical operations, containment, indexing, slicing, and various string methods such as capitalize(), count(), isalpha(), join(), find(), and replace().
2. Common string methods are explained including capitalize(), right/left/center justification, count(), checking string types, title case, swap case, joining strings, finding substrings, and replacing characters.
3. Examples are provided to demonstrate various string methods like capitalize(), center(), count(), isalpha(), join(), find(), and replace(). Length, indexing, and checking string types are also shown.
- Python is an interpreted, object-oriented programming language that is beginner friendly and open source. It was created in the 1990s and named after Monty Python.
- Python is very suitable for natural language processing tasks due to its built-in string and list datatypes as well as libraries like NLTK. It also has strong numeric processing capabilities useful for machine learning.
- Python code is organized using functions, classes, modules, and packages to improve structure. It is interpreted at runtime rather than requiring a separate compilation step.
This document provides an introduction and overview of strings in Python. It discusses that strings are a data type that can contain sequences of characters. The built-in string class is 'str' and strings can be defined using single, double, or triple quotes. Strings support various methods like indexing, slicing, concatenation, formatting and more. Common string methods are also described such as upper(), lower(), split(), join() which allow manipulating strings. The document also discusses comparing and slicing strings in Python.
This document provides an overview of regular expressions in Python. It discusses how regular expressions can be used to search, match, replace, and split strings. The syntax for common regular expression patterns is explained, including character classes, grouping, quantifiers, anchors, and more. Examples are given showing how to use the re module to compile patterns, search and match strings, and extract matched groups. Regular expressions in Python provide a powerful tool for manipulating text data.
This document discusses various string operations in Python including: finding the length of a string; accessing and slicing characters; the difference between strings and lists; converting case; checking character types; splitting strings; finding substrings; reading and printing strings; concatenation and repetition; iterating through strings with for loops; and common string methods like isalpha, isdigit, lower, upper, title, join, split, count, find, index. It also provides examples of problems involving anagrams, pangrams, unique characters, and removing duplicates from strings.
This document provides an introduction to the Python language and discusses Python data types. It covers how to install Python, interact with the Python interpreter through command line and IDLE modes, and learn basic Python parts like data types, operators, functions, and control structures. The document discusses numeric, string, and other data types in Python and how to manipulate them using built-in functions and operators. It also introduces Python library modules and the arcpy package for geoprocessing in ArcGIS.
This document provides an introduction to using regular expressions (REs) in the Textpad text editor. It begins with an overview of why REs are useful for searching text, then demonstrates how to write basic REs to find single characters, character ranges, word endings, and more. It also explains how to use RE features like groups, replacements, counting characters, and searching files or folders. The goal is to help uninitiated users learn the basics of writing and using REs in Textpad.
- The document discusses concurrent and parallel programming in Haskell, including the use of threads, MVars, and software transactional memory (STM).
- STM provides atomic execution of blocks of code, allowing failed transactions to automatically retry without race conditions or data corruption.
- Strategies can be used to evaluate expressions in parallel using different evaluation models like head normal form or weak head normal form.
- While functional programs may seem to have inherent parallelism, in practice extracting parallelism can be difficult due to data dependencies and irregular patterns of computation.
Regular expressions (regexes) allow complex pattern matching in text. They are used to find, extract, or replace substrings. Key regex concepts covered in the document include:
- Common regex syntax like literals, character classes, quantifiers, greedy/lazy matching, anchors, word boundaries and subpatterns.
- How a regex engine works by trying to match a pattern to a subject string and returning the earliest match.
- Uses of regex like searching text, extracting/removing/replacing strings, and validating formats.
- Terminology like regex, subject string, match, and engine.
The document introduces Python modules and importing. It discusses three formats for importing modules: import somefile, from somefile import *, and from somefile import className. It describes commonly used Python modules like sys, os, and math. It also covers defining your own modules, directories for module files, object-oriented programming in Python including defining classes, creating and deleting instances, methods and self, accessing attributes and methods, attributes, inheritance, and redefining methods.
Python Programming - XI. String Manipulation and Regular ExpressionsRanel Padon
The document discusses string manipulation and regular expressions in Python programming. It covers topics like string methods, regular expression concepts including alternatives, grouping, quantification, anchors, meta-characters and character classes. Examples are provided to demonstrate matching patterns in text using regular expressions. The re module is introduced as the core module for using regular expressions in Python.
The document discusses using regular expressions (regex) in Python to identify patterns in text, such as phone numbers. It provides examples of scripts that use regex to check if a string is a valid phone number format. The document also introduces the re module for incorporating regex into Python scripts. It describes functions like compile(), search(), and findall() that allow compiling regex patterns and searching/extracting all matches from text.
Regular expressions allow matching and manipulation of textual data. They were first discovered by mathematician Stephen Kleene and their search algorithm was developed by Ken Thompson in 1968 for use in tools like ed, grep, and sed. Regular expressions follow certain grammars and use meta characters to match patterns in text. They are used for tasks like validation, parsing, and data conversion.
awk is a very versatile programming language for working on text files. It is more powerful than sed but less complex than C. It is an excellent filter and report writer. In this class I will go over the elements and features of gawk, (the Free Software foundation version of awk), examples and a few one-liners.
The document discusses strings in C and common string functions. It defines a string as an array of characters terminated by a null character. It describes two ways to use strings - with a character array or string pointer. It then explains functions such as strcpy(), strcat(), strcmp() that copy, append, or compare strings. Other functions like memcpy(), memcmp() operate on a specified number of characters rather than null-terminated strings.
This document provides an introduction to regular expressions (RegEx). It explains that RegEx allows you to find, match, compare or replace text patterns. It then discusses the basic building blocks of RegEx, including characters, character classes, quantifiers, and assertions. It provides several examples of RegEx patterns to match names, words, ports numbers, and other patterns. It concludes with an overview of common RegEx match types like beginning/end of line, word boundaries, grouping, alternatives, and repetition.
The document discusses using the cut command in Unix/Linux to extract sections of text from files. It provides examples of using cut to:
1. Print characters by position or range by specifying character positions.
2. Extract fields using a delimiter like a space, and print a single field or range of fields.
3. Extract the portion of a filename after the dot when the file names are reversed line by line.
Sed is a non-interactive stream editor that was developed in 1973-1974 at Bell Labs. It performs basic text transformations on an input stream by reading from a file or standard input. Some key features of sed include searching for patterns using regular expressions, substituting strings, deleting lines, and printing/extracting parts of lines. Special characters like ^, $, ., *, and [] have special meanings when used in regular expressions with sed. Sed can manipulate line numbers to print or act on ranges of lines. Overall, sed is a powerful UNIX tool for searching, filtering, and transforming text in a non-interactive way.
Regular expressions (RegEx) allow defining search patterns to match strings. RegEx use metacharacters like ^, $, *, ?, etc. to specify patterns. The re module in Python provides functions like search(), match(), sub(), split() to work with RegEx patterns. These functions take a pattern and string, and return matches or modified strings. Common tasks like finding, replacing, extracting substrings can be performed using RegEx in Python.
The document provides an introduction to the Python programming language. It covers topics such as data types in Python like integers, floats, strings, tuples, lists, and dictionaries. It also discusses operators, control flow, functions, and how to write and run Python code in the Eclipse IDE.
This document provides 15 examples of using the Linux grep command to search files for text patterns. Some key examples include searching for a string in single or multiple files, ignoring case, using regular expressions to match patterns, displaying lines before/after/around matches, inverting matches, counting matches, and highlighting matched text. The examples demonstrate many useful grep options for finding text in files.
1. This document discusses string operations and methods in Python. It covers topics like equality, numerical operations, containment, indexing, slicing, and various string methods such as capitalize(), count(), isalpha(), join(), find(), and replace().
2. Common string methods are explained including capitalize(), right/left/center justification, count(), checking string types, title case, swap case, joining strings, finding substrings, and replacing characters.
3. Examples are provided to demonstrate various string methods like capitalize(), center(), count(), isalpha(), join(), find(), and replace(). Length, indexing, and checking string types are also shown.
- Python is an interpreted, object-oriented programming language that is beginner friendly and open source. It was created in the 1990s and named after Monty Python.
- Python is very suitable for natural language processing tasks due to its built-in string and list datatypes as well as libraries like NLTK. It also has strong numeric processing capabilities useful for machine learning.
- Python code is organized using functions, classes, modules, and packages to improve structure. It is interpreted at runtime rather than requiring a separate compilation step.
This document provides an introduction and overview of strings in Python. It discusses that strings are a data type that can contain sequences of characters. The built-in string class is 'str' and strings can be defined using single, double, or triple quotes. Strings support various methods like indexing, slicing, concatenation, formatting and more. Common string methods are also described such as upper(), lower(), split(), join() which allow manipulating strings. The document also discusses comparing and slicing strings in Python.
This document provides an overview of regular expressions in Python. It discusses how regular expressions can be used to search, match, replace, and split strings. The syntax for common regular expression patterns is explained, including character classes, grouping, quantifiers, anchors, and more. Examples are given showing how to use the re module to compile patterns, search and match strings, and extract matched groups. Regular expressions in Python provide a powerful tool for manipulating text data.
This document discusses various string operations in Python including: finding the length of a string; accessing and slicing characters; the difference between strings and lists; converting case; checking character types; splitting strings; finding substrings; reading and printing strings; concatenation and repetition; iterating through strings with for loops; and common string methods like isalpha, isdigit, lower, upper, title, join, split, count, find, index. It also provides examples of problems involving anagrams, pangrams, unique characters, and removing duplicates from strings.
This document provides an introduction to the Python language and discusses Python data types. It covers how to install Python, interact with the Python interpreter through command line and IDLE modes, and learn basic Python parts like data types, operators, functions, and control structures. The document discusses numeric, string, and other data types in Python and how to manipulate them using built-in functions and operators. It also introduces Python library modules and the arcpy package for geoprocessing in ArcGIS.
This document provides an introduction to using regular expressions (REs) in the Textpad text editor. It begins with an overview of why REs are useful for searching text, then demonstrates how to write basic REs to find single characters, character ranges, word endings, and more. It also explains how to use RE features like groups, replacements, counting characters, and searching files or folders. The goal is to help uninitiated users learn the basics of writing and using REs in Textpad.
- The document discusses concurrent and parallel programming in Haskell, including the use of threads, MVars, and software transactional memory (STM).
- STM provides atomic execution of blocks of code, allowing failed transactions to automatically retry without race conditions or data corruption.
- Strategies can be used to evaluate expressions in parallel using different evaluation models like head normal form or weak head normal form.
- While functional programs may seem to have inherent parallelism, in practice extracting parallelism can be difficult due to data dependencies and irregular patterns of computation.
Regular expressions (regexes) allow complex pattern matching in text. They are used to find, extract, or replace substrings. Key regex concepts covered in the document include:
- Common regex syntax like literals, character classes, quantifiers, greedy/lazy matching, anchors, word boundaries and subpatterns.
- How a regex engine works by trying to match a pattern to a subject string and returning the earliest match.
- Uses of regex like searching text, extracting/removing/replacing strings, and validating formats.
- Terminology like regex, subject string, match, and engine.
The document introduces Python modules and importing. It discusses three formats for importing modules: import somefile, from somefile import *, and from somefile import className. It describes commonly used Python modules like sys, os, and math. It also covers defining your own modules, directories for module files, object-oriented programming in Python including defining classes, creating and deleting instances, methods and self, accessing attributes and methods, attributes, inheritance, and redefining methods.
Python Programming - XI. String Manipulation and Regular ExpressionsRanel Padon
The document discusses string manipulation and regular expressions in Python programming. It covers topics like string methods, regular expression concepts including alternatives, grouping, quantification, anchors, meta-characters and character classes. Examples are provided to demonstrate matching patterns in text using regular expressions. The re module is introduced as the core module for using regular expressions in Python.
The document discusses using regular expressions (regex) in Python to identify patterns in text, such as phone numbers. It provides examples of scripts that use regex to check if a string is a valid phone number format. The document also introduces the re module for incorporating regex into Python scripts. It describes functions like compile(), search(), and findall() that allow compiling regex patterns and searching/extracting all matches from text.
Regular expressions allow matching and manipulation of textual data. They were first discovered by mathematician Stephen Kleene and their search algorithm was developed by Ken Thompson in 1968 for use in tools like ed, grep, and sed. Regular expressions follow certain grammars and use meta characters to match patterns in text. They are used for tasks like validation, parsing, and data conversion.
awk is a very versatile programming language for working on text files. It is more powerful than sed but less complex than C. It is an excellent filter and report writer. In this class I will go over the elements and features of gawk, (the Free Software foundation version of awk), examples and a few one-liners.
The document discusses strings in C and common string functions. It defines a string as an array of characters terminated by a null character. It describes two ways to use strings - with a character array or string pointer. It then explains functions such as strcpy(), strcat(), strcmp() that copy, append, or compare strings. Other functions like memcpy(), memcmp() operate on a specified number of characters rather than null-terminated strings.
This document provides an introduction to regular expressions (RegEx). It explains that RegEx allows you to find, match, compare or replace text patterns. It then discusses the basic building blocks of RegEx, including characters, character classes, quantifiers, and assertions. It provides several examples of RegEx patterns to match names, words, ports numbers, and other patterns. It concludes with an overview of common RegEx match types like beginning/end of line, word boundaries, grouping, alternatives, and repetition.
The document discusses using the cut command in Unix/Linux to extract sections of text from files. It provides examples of using cut to:
1. Print characters by position or range by specifying character positions.
2. Extract fields using a delimiter like a space, and print a single field or range of fields.
3. Extract the portion of a filename after the dot when the file names are reversed line by line.
Sed is a non-interactive stream editor that was developed in 1973-1974 at Bell Labs. It performs basic text transformations on an input stream by reading from a file or standard input. Some key features of sed include searching for patterns using regular expressions, substituting strings, deleting lines, and printing/extracting parts of lines. Special characters like ^, $, ., *, and [] have special meanings when used in regular expressions with sed. Sed can manipulate line numbers to print or act on ranges of lines. Overall, sed is a powerful UNIX tool for searching, filtering, and transforming text in a non-interactive way.
The document provides examples of how to use the grep command in Unix-based systems to search files for patterns and text. Some key examples include using grep to:
1) Search for a word like "Exception" while excluding another word like "ERROR" using grep -v.
2) Count the number of times a word appears in a file using grep -c.
3) Print lines around a matching pattern for context using grep --context.
4) Perform case-insensitive searches using grep -i or search for whole words only using grep -w.
Files saved on central Unix systems at Indiana University are stored on a Network File System (NFS) which allows users to access their files from any system by using the appropriate directory path. For example, a user logged into the Steel system who wants to access their files on the EZinfo system would use the command "cd /N/u/username/Ezinfo/". This shared file system allows users to access their files from any central Unix system but users can only use software installed on the specific system they are logged into.
Simple yet powerful keys to personal transformation. You can take charge of your life and dramatically improve the quality of your life, and shift your consciousness.
Regular expressions (regex) allow complex pattern matching in text. The document discusses regex basics like literals, character classes, quantifiers, and flags in Python. It explains how to use the re module to compile patterns into RegexObjects and search/match strings. RegexObjects provide reusable patterns while re module functions provide shortcuts but cache compiled patterns.
The document provides an introduction to Perl programming and regular expressions. It begins with simple Perl programs to print text and take user input. It then covers executing external commands, variables, operators, loops, and file operations. The document also introduces regular expressions, explaining patterns, anchors, character classes, alternation, grouping, and repetition quantifiers. It provides examples and discusses principles for matching strings with regular expressions.
What is the general format for a Try-Catch block Assume that amt l .docxajoy21
The document discusses command line arguments in C/C++ programs. It explains that command line arguments allow providing input to a program through command line instead of user input. The main() function needs to be defined as int main(int argc, char *argv[]) to access command line arguments. The argc parameter indicates number of arguments, while argv is an array containing the arguments as strings. Functions like atoi() and atof() are used to convert argument strings to int and double as arguments are received as char* by default. Examples demonstrate how to iterate through argv and access individual arguments.
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The document provides instructions for 5 programming problems as part of a weekly challenge. Problem 1 involves writing a program to convert numbers to words. Problem 2 asks to merge two sorted text files. Problem 3 is to modify an encryption program to encrypt user input while preserving non-letter characters. Problem 4 requires generating banner text from a font file and user input. Problem 5 checks for duplicates in a Sudoku puzzle given as user input.
grep is a command line utility that searches for patterns in files. It searches the given file(s) for lines containing a match to the given strings or regular expressions and outputs the matching lines. By default, grep prints the matching lines. The name "grep" derives from a similar operation using the Unix/Linux text editor ed. grep uses regular expressions to search for text patterns that can match multiple characters and patterns in text. It has many options to customize searches, such as ignoring case, counting matches, inverting matches, and more.
This document discusses regular expressions and provides examples. It introduces regular expressions and their uses for validating email addresses. It then outlines the main types of regular expressions, including simple, POSIX basic, POSIX extended, and Perl regular expressions. POSIX basic regular expressions are described as creating a standard for Unix tools.
Don't Fear the Regex - Northeast PHP 2015Sandy Smith
Have you been scared off by Klingon-looking one-liners in Perl? Do you resort to writing complicated recursive functions just to parse some HTML? Don’t!
I’ll demystify regular expressions and show you how best to do them in PHP. We’ll cover the syntax and functions that make PHP a great text-parsing language, and give you the foundation to learn more.
As a bonus, I’ll give you two cases people often use as examples for regexes that PHP gives you better native ways to accomplish.
Do you have data and lists you keep having to massage to make it useful for your project? Have you heard of regular expressions but been frightened by the Klingon-looking examples? Fear no longer!
I’ll demystify regular expressions and show you how best to do them in PHP. We’ll cover the syntax and functions that make PHP a great text-parsing language, and give you the foundation to learn more.
As a bonus, I’ll give you two cases people often use as examples for regexes that PHP gives you better native ways to accomplish.
The document describes various special characters and their meanings in regular expressions for Python. It explains the period, asterisk, plus, question mark, pipe, parentheses, square brackets, curly braces, caret, and dollar sign. It also covers escaping special characters with a backslash, as well as sequences like \w, \d, \s, \b, and more. The document provides examples and explanations of how these special characters are used in regular expressions to match patterns in text.
Python Workshop - Learn Python the Hard WayUtkarsh Sengar
This document provides an introduction to learning Python. It discusses prerequisites for Python, basic Python concepts like variables, data types, operators, conditionals and loops. It also covers functions, files, classes and exceptions handling in Python. The document demonstrates these concepts through examples and exercises learners to practice char frequency counting and Caesar cipher encoding/decoding in Python. It encourages learners to practice more to master the language and provides additional learning resources.
Scala Language Intro - Inspired by the Love GameAntony Stubbs
The document discusses Scala code for implementing a "Love Game" algorithm to calculate compatibility between names in a concise, functional way. It shows the Java implementation using loops and arrays, then demonstrates translating it to 4 lines of Scala code using functional techniques like map, zip and pattern matching. It provides background on Scala's features that enable this brevity and discusses recursion in the functional implementation.
Regular expressions (regex) are used to match patterns in text. They contain special characters called meta characters that represent expressions to match, like * for 0 or more matches and + for 1 or more matches. Regex can be used for text processing tasks like validating formats. The document discusses various regex meta characters, quantifiers, character sets, modifiers, grouping, backreferences, and lookahead/lookbehind operations. It provides examples of regex patterns for tasks like matching XML tags and validating email addresses.
Brogramming - Python, Bash for Data Processing, and GitRon Reiter
The document discusses Python coding conventions and best practices including PEP 8. It covers topics like formatting, spacing, imports, and other stylistic guidelines to make Python code more readable and consistent across projects. The Zen of Python philosophy emphasizes simple and explicit code over complex solutions. Git concepts like merge vs rebase and Git flow are also briefly mentioned.
This document provides an introduction to regular expressions (regex) in PHP. It begins with a basic explanation of what regex is for - matching patterns in strings. It then covers the basics of regex syntax, including delimiters, character classes, quantifiers, escaping special characters, and using regex in PHP functions like preg_match() and preg_replace(). It also discusses more advanced topics like character classes, subpatterns, backreferences, modifiers, and when not to use regex. The overall message is that regex is a powerful tool for text manipulation but needs to be used appropriately.
This document provides an introduction to the Ruby programming language, giving an overview of its history, features, syntax, and comparisons to other languages like Perl and Python. It discusses Ruby's object-oriented capabilities and provides examples of basic programming constructs. Resources for learning more about Ruby are also listed at the end.
This document provides an introduction to the Ruby programming language. It discusses the history and origins of Ruby, its basic syntax and features, how it compares to other languages like Perl and Python, and resources for learning more. The presenter aims to get the audience interested in and started with Ruby through a quick overview rather than an in-depth tutorial.
This document provides an introduction to the Ruby programming language. It discusses the history and origins of Ruby, its basic syntax and features, how it compares to other languages like Perl and Python, and resources for learning more. The presenter aims to get the audience interested in and started with Ruby through a quick overview rather than an in-depth tutorial.
This document provides an introduction to the Ruby programming language. It discusses the history and origins of Ruby, its basic syntax and features, how it compares to other languages like Perl and Python, and resources for learning more. The presenter aims to get the audience interested in and started with Ruby through a quick overview rather than an in-depth tutorial.
OpenMetadata Community Meeting - 5th June 2024OpenMetadata
The OpenMetadata Community Meeting was held on June 5th, 2024. In this meeting, we discussed about the data quality capabilities that are integrated with the Incident Manager, providing a complete solution to handle your data observability needs. Watch the end-to-end demo of the data quality features.
* How to run your own data quality framework
* What is the performance impact of running data quality frameworks
* How to run the test cases in your own ETL pipelines
* How the Incident Manager is integrated
* Get notified with alerts when test cases fail
Watch the meeting recording here - https://www.youtube.com/watch?v=UbNOje0kf6E
WhatsApp offers simple, reliable, and private messaging and calling services for free worldwide. With end-to-end encryption, your personal messages and calls are secure, ensuring only you and the recipient can access them. Enjoy voice and video calls to stay connected with loved ones or colleagues. Express yourself using stickers, GIFs, or by sharing moments on Status. WhatsApp Business enables global customer outreach, facilitating sales growth and relationship building through showcasing products and services. Stay connected effortlessly with group chats for planning outings with friends or staying updated on family conversations.
Neo4j - Product Vision and Knowledge Graphs - GraphSummit ParisNeo4j
Dr. Jesús Barrasa, Head of Solutions Architecture for EMEA, Neo4j
Découvrez les dernières innovations de Neo4j, et notamment les dernières intégrations cloud et les améliorations produits qui font de Neo4j un choix essentiel pour les développeurs qui créent des applications avec des données interconnectées et de l’IA générative.
Graspan: A Big Data System for Big Code AnalysisAftab Hussain
We built a disk-based parallel graph system, Graspan, that uses a novel edge-pair centric computation model to compute dynamic transitive closures on very large program graphs.
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These analyses were used to augment the existing checkers; these augmented checkers found 132 new NULL pointer bugs and 1308 unnecessary NULL tests in Linux 4.4.0-rc5, PostgreSQL 8.3.9, and Apache httpd 2.2.18.
- Accepted in ASPLOS ‘17, Xi’an, China.
- Featured in the tutorial, Systemized Program Analyses: A Big Data Perspective on Static Analysis Scalability, ASPLOS ‘17.
- Invited for presentation at SoCal PLS ‘16.
- Invited for poster presentation at PLDI SRC ‘16.
Transform Your Communication with Cloud-Based IVR SolutionsTheSMSPoint
Discover the power of Cloud-Based IVR Solutions to streamline communication processes. Embrace scalability and cost-efficiency while enhancing customer experiences with features like automated call routing and voice recognition. Accessible from anywhere, these solutions integrate seamlessly with existing systems, providing real-time analytics for continuous improvement. Revolutionize your communication strategy today with Cloud-Based IVR Solutions. Learn more at: https://thesmspoint.com/channel/cloud-telephony
Software Engineering, Software Consulting, Tech Lead, Spring Boot, Spring Cloud, Spring Core, Spring JDBC, Spring Transaction, Spring MVC, OpenShift Cloud Platform, Kafka, REST, SOAP, LLD & HLD.
Zoom is a comprehensive platform designed to connect individuals and teams efficiently. With its user-friendly interface and powerful features, Zoom has become a go-to solution for virtual communication and collaboration. It offers a range of tools, including virtual meetings, team chat, VoIP phone systems, online whiteboards, and AI companions, to streamline workflows and enhance productivity.
May Marketo Masterclass, London MUG May 22 2024.pdfAdele Miller
Can't make Adobe Summit in Vegas? No sweat because the EMEA Marketo Engage Champions are coming to London to share their Summit sessions, insights and more!
This is a MUG with a twist you don't want to miss.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Microservice Teams - How the cloud changes the way we workSven Peters
A lot of technical challenges and complexity come with building a cloud-native and distributed architecture. The way we develop backend software has fundamentally changed in the last ten years. Managing a microservices architecture demands a lot of us to ensure observability and operational resiliency. But did you also change the way you run your development teams?
Sven will talk about Atlassian’s journey from a monolith to a multi-tenanted architecture and how it affected the way the engineering teams work. You will learn how we shifted to service ownership, moved to more autonomous teams (and its challenges), and established platform and enablement teams.
Introducing Crescat - Event Management Software for Venues, Festivals and Eve...Crescat
Crescat is industry-trusted event management software, built by event professionals for event professionals. Founded in 2017, we have three key products tailored for the live event industry.
Crescat Event for concert promoters and event agencies. Crescat Venue for music venues, conference centers, wedding venues, concert halls and more. And Crescat Festival for festivals, conferences and complex events.
With a wide range of popular features such as event scheduling, shift management, volunteer and crew coordination, artist booking and much more, Crescat is designed for customisation and ease-of-use.
Over 125,000 events have been planned in Crescat and with hundreds of customers of all shapes and sizes, from boutique event agencies through to international concert promoters, Crescat is rigged for success. What's more, we highly value feedback from our users and we are constantly improving our software with updates, new features and improvements.
If you plan events, run a venue or produce festivals and you're looking for ways to make your life easier, then we have a solution for you. Try our software for free or schedule a no-obligation demo with one of our product specialists today at crescat.io
Hand Rolled Applicative User ValidationCode KataPhilip Schwarz
Could you use a simple piece of Scala validation code (granted, a very simplistic one too!) that you can rewrite, now and again, to refresh your basic understanding of Applicative operators <*>, <*, *>?
The goal is not to write perfect code showcasing validation, but rather, to provide a small, rough-and ready exercise to reinforce your muscle-memory.
Despite its grandiose-sounding title, this deck consists of just three slides showing the Scala 3 code to be rewritten whenever the details of the operators begin to fade away.
The code is my rough and ready translation of a Haskell user-validation program found in a book called Finding Success (and Failure) in Haskell - Fall in love with applicative functors.
GraphSummit Paris - The art of the possible with Graph TechnologyNeo4j
Sudhir Hasbe, Chief Product Officer, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
Revolutionizing Visual Effects Mastering AI Face Swaps.pdfUndress Baby
The quest for the best AI face swap solution is marked by an amalgamation of technological prowess and artistic finesse, where cutting-edge algorithms seamlessly replace faces in images or videos with striking realism. Leveraging advanced deep learning techniques, the best AI face swap tools meticulously analyze facial features, lighting conditions, and expressions to execute flawless transformations, ensuring natural-looking results that blur the line between reality and illusion, captivating users with their ingenuity and sophistication.
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Need for Speed: Removing speed bumps from your Symfony projects ⚡️Łukasz Chruściel
No one wants their application to drag like a car stuck in the slow lane! Yet it’s all too common to encounter bumpy, pothole-filled solutions that slow the speed of any application. Symfony apps are not an exception.
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Looking for a reliable mobile app development company in Noida? Look no further than Drona Infotech. We specialize in creating customized apps for your business needs.
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2. Outline
1 Introduction
What does grep offer?
When should I use grep?
2 Understanding Regular Expressions
Class Basics
Quantifiers & Grouping
Online Tools
Examples
3 Using Regular Expressions With grep
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3. Outline
1 Introduction
What does grep offer?
When should I use grep?
2 Understanding Regular Expressions
Class Basics
Quantifiers & Grouping
Online Tools
Examples
3 Using Regular Expressions With grep
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4. Outline
1 Introduction
What does grep offer?
When should I use grep?
2 Understanding Regular Expressions
Class Basics
Quantifiers & Grouping
Online Tools
Examples
3 Using Regular Expressions With grep
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5. Introduction What?
What does grep offer?
grep matches regular expressions.
Your first question should be“What is a regular expression?”
A regular expression is a language pattern.
grep and REs allow us to find complex things in text.
Complex is relative and can vary from a single character to an IP
address.
Single character complex: [ajk+0-]
IP complex: (25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?).){3}
(25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)
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6. Introduction What?
What does grep offer?
grep matches regular expressions.
Your first question should be“What is a regular expression?”
A regular expression is a language pattern.
grep and REs allow us to find complex things in text.
Complex is relative and can vary from a single character to an IP
address.
Single character complex: [ajk+0-]
IP complex: (25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?).){3}
(25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)
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7. Introduction What?
What does grep offer?
grep matches regular expressions.
Your first question should be“What is a regular expression?”
A regular expression is a language pattern.
grep and REs allow us to find complex things in text.
Complex is relative and can vary from a single character to an IP
address.
Single character complex: [ajk+0-]
IP complex: (25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?).){3}
(25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)
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8. Introduction When?
When should I use grep?
Always!
Unless you find some better tool.
P.S. - grep stands for g/re/p, an ed command that means global/reg
ex/print
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9. Regular Expressions Class Basics
Class Basics
A character class is a symbol or collection of symbols that describes a
group of characters.
. (period): This matches any single character.
[...]: This matches any one character in the set.
[aeiou] matches one of the vowels.
[a-z] matches one of the lowercase alphabet.
[0-5] matches one numeral 0 through 5.
You will not remember all of these until you use them often, but
there are many special classes that can save you some typing.
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10. Regular Expressions Class Basics
Common Classes
Special Class Meaning Simple RE
d Digit characters [0-9]
D Non-digit characters [ˆ0-9]
w Word characters [a-zA-Z 0-9]
W Non-word characters [ˆa-zA-Z 0-9]
s Whitespace characters characters [fnrt]
S Non-space characters [ˆfnrt]
b Word boundary
The word boundary class is very special as it is zero length and matches
transitions between s and w and vice versa.
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11. Regular Expressions Class Basics
More Common Classes
Special Class Meaning Simple RE
[:alpha:] All alphabetic characters [a-zA-Z]
[:alnum:] All alphabetic and numeric [a-zA-Z0-9]
[:blank:] Tab and space
[:cntrl:] Control characters [x00-x1Fx7F]
[:digit:] A numeric digit [0-9]
[:graph:] Any visible character [x21-x7E]
[:lower:] Lowercase characters [a-z]
[:print:] Printables (i.e. no controls) [x20-x7E]
[:punct:] Punctuation & symbols [!”#$%&’()*+,-./:;<=>?
@[ ]ˆ ‘{|}∼]
[:space:] Space, tab, newline, etc [ trnvf]
[:upper:] Uppercase characters [A-Z]
[:word:] Word characters [a-zA-Z0-9 ]
[:xdigit:] Hex digits [A-Fa-f0-9]
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12. Regular Expressions Quantifiers & Grouping
Quantifiers & Grouping
Quantifiers are how a RE counts things.
? Exactly zero or one occurrence
* Zero or more occurrences
+ One or more occurrences
*? Zero or more occurrences non-greedy
+? One or more occurrences non-greedy
{x} Exactly x occurrences
{x,} At least x occurrences
{x,y} At least x but no more than y occurrences
Grouping is used to collect patterns together and to create
back-references. A group is simply a set of parentheses ().
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13. Regular Expressions Online Tools
Helpful Tools
The best way to understand the rest of this presentation is to see what is
being matched live. Here are some online tools that work for our needs.
RegExr - www.gskinner.com/RegExr
beware Flash, but it works well
regexpal - regexpal.com
very simple
reanimator - osteele.com/tools/reanimator
beware Flash, recommend CS 4/570 first
rubular - rubular.com
nice on-page reference
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14. Regular Expressions Examples
Your First RE
Let’s skip trivial REs and get on to something useful. These may be more
complex than you’re used to but the quicker you are able to read long,
complex REs the better. This is a nice, but not perfect, email address
matcher.
[[:alnum:]][[:word:].%+-]*@(?:[[:alnum:]-]+.)+[[:alpha:]]{2,4}
[[:alnum:]][[:word:].%+-]*
Match a word that doesn’t start with [.%+-].
@(?:[[:alnum:]-]+.)+
Match the @ symbol and any number of subdomains followed by
periods.
[[:alpha:]]{2,4}
Match the top level domain of 2, 3 or 4 characters.
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15. Regular Expressions Examples
Your First RE - Part 2
Let’s examine the first part.
[[:alnum:]][[:word:].%+-]*
[[:alnum:]] - Must start with an alphanumeric character.
NB: All [: ... :] classes must live in a set like [[: ... :]].
[[:word:].%+-] - Other characters maybe a ‘word’ character,
a literal space, percent symbol, plus symbol or a dash.
NB: The period must be escaped because it has special meaning.
* - repeat the previous set zero or more times.
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16. Regular Expressions Examples
Your First RE - Part 2
Let’s examine the first part.
[[:alnum:]][[:word:].%+-]*
[[:alnum:]] - Must start with an alphanumeric character.
NB: All [: ... :] classes must live in a set like [[: ... :]].
[[:word:].%+-] - Other characters maybe a ‘word’ character,
a literal space, percent symbol, plus symbol or a dash.
NB: The period must be escaped because it has special meaning.
* - repeat the previous set zero or more times.
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17. Regular Expressions Examples
Your First RE - Part 2
Let’s examine the first part.
[[:alnum:]][[:word:].%+-]*
[[:alnum:]] - Must start with an alphanumeric character.
NB: All [: ... :] classes must live in a set like [[: ... :]].
[[:word:].%+-] - Other characters maybe a ‘word’ character,
a literal space, percent symbol, plus symbol or a dash.
NB: The period must be escaped because it has special meaning.
* - repeat the previous set zero or more times.
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18. Regular Expressions Examples
Your First RE - Part 3
Now the second part, the subdomains, sub-subdomains, etc.
@(?:[[:alnum:]-]+.)+
@ - Well that literally matches the ‘at’ character.
The parenthesis denote the beginning of a group.
The ?: is a confusing notation that suppresses the creation of a
back reference. It is here so you’ll know of it, but it is rarely needed.
Again we see a special class for alphanumerics, but we’ve also
included a dash. The plus symbol tells us to look for one or more of
these characters, followed by a period.
And lastly we close the group and the plus symbol now tells us to
look for one or more of these groups.
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19. Regular Expressions Examples
Your First RE - Part 3
Now the second part, the subdomains, sub-subdomains, etc.
@(?:[[:alnum:]-]+.)+
@ - Well that literally matches the ‘at’ character.
The parenthesis denote the beginning of a group.
The ?: is a confusing notation that suppresses the creation of a
back reference. It is here so you’ll know of it, but it is rarely needed.
Again we see a special class for alphanumerics, but we’ve also
included a dash. The plus symbol tells us to look for one or more of
these characters, followed by a period.
And lastly we close the group and the plus symbol now tells us to
look for one or more of these groups.
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20. Regular Expressions Examples
Your First RE - Part 3
Now the second part, the subdomains, sub-subdomains, etc.
@(?:[[:alnum:]-]+.)+
@ - Well that literally matches the ‘at’ character.
The parenthesis denote the beginning of a group.
The ?: is a confusing notation that suppresses the creation of a
back reference. It is here so you’ll know of it, but it is rarely needed.
Again we see a special class for alphanumerics, but we’ve also
included a dash. The plus symbol tells us to look for one or more of
these characters, followed by a period.
And lastly we close the group and the plus symbol now tells us to
look for one or more of these groups.
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21. Regular Expressions Examples
Your First RE - Part 3
Now the second part, the subdomains, sub-subdomains, etc.
@(?:[[:alnum:]-]+.)+
@ - Well that literally matches the ‘at’ character.
The parenthesis denote the beginning of a group.
The ?: is a confusing notation that suppresses the creation of a
back reference. It is here so you’ll know of it, but it is rarely needed.
Again we see a special class for alphanumerics, but we’ve also
included a dash. The plus symbol tells us to look for one or more of
these characters, followed by a period.
And lastly we close the group and the plus symbol now tells us to
look for one or more of these groups.
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22. Regular Expressions Examples
Your First RE - Part 4
Finally the third part, the domain.
[[:alpha:]]{2,4}
We’ll now this part is easy. Just match 2, 3 or 4 alphabetical
characters.
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23. Regular Expressions Examples
Your Second RE
Now we’ll look at a RE that can help use build a header file for a c
program file, given that some neglectful programmer has failed to design
his/her c program properly. This will be a quicker example.
ˆ[ws]*([ws*&,]*)s*{
ˆ[ws]*(
At the beginning of a line match some keywords and types and
the function name and then literal parenthesis.
[ws*&,]*
Match some more words, keywords, variable modifiers and commas.
)s*{
Finally match the closing parenthesis, some whitespace and the
left curly brace, denoting the start of the function body.
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24. Regular Expressions Examples
Your Second RE - Fine Details
ˆ[ws]*([ws*&,]*)s*{
In general, most RE parsers will not match across multiple lines, even
though the s class matches the newline character. This is very
bothersome but is easily overcome by using pcregrep. pcre is Perl
Compatible Regular Expression. This is all I will ever say about Perl.
Notice that the literal * must be escaped like so, *.
As must the parentheses due to their special RE meaning.
Escaping so many characters is very annoying, but unfortunately it is
necessary.
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