Regular expressions training course description Regular expressions are an extremely powerful tool for manipulating text and data. They are now standard features in a wide range of languages and popular tools, including Python and MySQL. Regular expressions allow you to code complex and subtle text processing that you never imagined could be automated. Once you've mastered regular expressions, they'll become an invaluable part of your toolkit. You will wonder how you ever got by without them. What will you learn Use Regular Expressions. Troubleshoot Regular Expressions. Compare RE features among different versions. Explain how the regular expression engine works. Optimize REs. Match what you want, not what you don't want. Regular expressions training course details Who will benefit: Anyone looking to use regular expressions. Prerequisites: None. Duration 1 day Regular expressions training course contents Introduction to Regular Expressions Solving real problems, REs as a language, the filename analogy, language analogy, RE frame of mind, searching text files: egrep, egrep metacharacters, start and end of the line, character classes, matching any character with dot, alternation, ignoring differences in capitalization, word boundaries, optional items, other quantifiers: repetition, parentheses and backreferences, the great escape, expanding the foundation, linguistic diversification, the goal of a RE, more examples, RE nomenclature, Improving on the status quo. Extended introductory examples A short introduction to Perl, matching text with regular expressions, toward a more real-world example, side effects of a successful match, Intertwined regular expression, intermission, modifying text with regular expressions, example: form letter, example: prettifying a stock price, automated editing, a small mail utility, adding commas to a number with lookaround, text-to-HTML conversion, that doubled-word thing. Regular expression features and flavours The regex landscape, origins of REs, care and handling of REs, Integrated handling, procedural and object-oriented handling, search-and-replace example. strings character encodings and modes, strings as REs, character-encoding issues, unicode, regex modes and match modes, common metacharacters and features, character representations, character classes and class-like constructs, anchors and other 'zero-width assertions', comments and mode modifiers, grouping capturing conditionals and control. The mechanics of expression processing Two kinds of engines, new standards, regex engine types, from the department of redundancy department, testing the engine type, match basics, about the examples, rule 1: the match that begins earliest wins, engine pieces and parts, rule 2: the standard quantifiers are greedy, regex-directed versus text-directed, NFA engine: regex-directed, DFA engine: text-directed, first thoughts: NFA and DFA in comparison, backtracking, two important points on backtracking, saved states, backtracking and greediness, more about greediness and backtracking, problems of greediness, multi-character 'quotes', lazy quantifiers, greediness and laziness, laziness and backtracking, possessive quantifiers and atomic grouping, possessive quantifiers ?, +, *+, ++ and {m,n}+, the backtracking of lookaround, is alternation greedy? taking advantage of ordered alternation, NFA DFA and posix, the longest-leftmost', posix and the longest-leftmost rule, speed and efficiency. Practical regex techniques Continuation lines, matching an IP address, working with filenames, matching balanced sets of parentheses, watching out for unwanted matches, matching delimited text, knowing your data and making assumptions, stripping leading and trailing whitespace, matching and HTML tag, matching an HTML link, examining an HTTP URL, validating a hostname, plucking a hostname, plucking a URL, parsing CSV files. Crafting an efficient expression Efficiency vs. correctness, localizing greediness, global view of backtracking, more work for POSIX NFA, work required during a non-match, being more specific, alternation can be expensive, benchmarking, know what you re measuring, benchmarking with Python, common optimisations, the mechanics of regex application, pre-application optimizations, optimizations with the transmission, optimization of the regex itself, techniques for faster expressions, common sense techniques, expose literal text, expose anchors, lazy versus greedy: be specific, split into multiple REs, mimic initial-character discrimination, use atomic grouping and possessive quantifiers, lead the engine to a match, unrolling the loop, observations, using atomic grouping and possessive quantifiers, short unrolling examples, unrolling C comments, the free flowing regex, a helping hand to guide the match, a well-guided regex is a fast regex.
DevOps demystified training course description This course is an introduction to DevOps. The course emphasizes communication, collaboration , integration, and automation to improve the workflow between developers and IT operations professionals. Improved workflows lead to more opportunities to design software and services in a more agile fashion. This course is a basis for discovering the most important DevOps concepts and to understand the principles and methods behind this. The course will leave you with the inspiration to be the advocate of change. What will you learn Explain DevOps principles. Describe the relationship between Agile , Lean and IT Service Management ( ITSM). Describe methods for automation and technology factors. Describe considerations when changing. Describe challenges, risks and critical success factors. DevOps demystifieds training course details Who will benefit: Non-technical staff involved with DevOps. Prerequisites: None. Duration 1 day DevOps demystified training course contents Why DevOps? From a business perspective From an IT perspective Stereotypes of Dev and Ops: perception and reality What is DevOps? Introduction DevOps Goals DevOps Added value of DevOps Proven Results DevOps for businesses DevOps principles (The Three Ways) DevOps and other frameworks DevOps and Agile DevOps and Lean DevOps and IT Service Management DevOps culture Characteristics of a DevOps culture Organizational Considerations DevOps DevOps stakeholders DevOps roles DevOps teams DevOps organizational structures DevOps methods Continuous Integration Continuous delivery Continuous deployment Value stream mapping Kanban Theory of Constraints Improvement Kata Deming's quality circle ITSM processes DevOps and Automation Methods for DevOps automation Longevity and tools categories DevOps applications Transitioning to a DevOps culture Implementation Challenges, risks and critical success factors Measuring DevOps successes
Individuals with great leadership skills empower teams to achieve their full potential, make decisions, and stategise well to help organisations thrive. This course provides the knowledge and skills to help you hone your leadership skills.
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