Buch, Englisch, 257 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 424 g
Buch, Englisch, 257 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 424 g
ISBN: 978-1-4842-4004-5
Verlag: Springer
Gain an accelerated introduction to domain-specific languages in R, including coverage of regular expressions. This compact, in-depth book shows you how DSLs are programming languages specialized for a particular purpose, as opposed to general purpose programming languages. Along the way, you’ll learn to specify tasks you want to do in a precise way and achieve programming goals within a domain-specific context.
Domain-Specific Languages in R includes examples of DSLs including large data sets or matrix multiplication; pattern matching DSLs for application in computer vision; and DSLs for continuous time Markov chains and their applications in data science. After reading and using this book, you’ll understand how to write DSLs in R and have skills you can extrapolate to other programming languages.
What You'll Learn
- Program with domain-specific languages using R
- Discover the components of DSLs
- Carry out large matrix expressions and multiplications
- Implement metaprogramming with DSLs
- Parse and manipulate expressions
Who This Book Is For
Those with prior programming experience. R knowledge is helpful but not required.
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Programmierung: Methoden und Allgemeines
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Programmier- und Skriptsprachen
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken
- Mathematik | Informatik Mathematik Stochastik
- Mathematik | Informatik EDV | Informatik Informatik Mathematik für Informatiker
Weitere Infos & Material
1: Introduction
2: Matrix Expressions
3: Components of a Programming Language
4: Functions, Classes, and Operators
5: Parsing and Manipulating Expressions
6: Lambda Expressions
7: Environments and Expressions
8: Tidy Evaluation
9: List Comprehension
10: Continuous-Time Markov Chains
11: Pattern Matching
12: Dynamic Programming
13: Conclusion




