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F# 4.0 Design Patterns

You're reading from   F# 4.0 Design Patterns Solve complex problems with functional thinking

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Product type Paperback
Published in Nov 2016
Publisher Packt
ISBN-13 9781785884726
Length 318 pages
Edition 1st Edition
Languages
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Author (1):
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Gene Belitski Gene Belitski
Author Profile Icon Gene Belitski
Gene Belitski
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Toc

Table of Contents (14) Chapters Close

Preface 1. Begin Thinking Functionally FREE CHAPTER 2. Dissecting F# Origins and Design 3. Basic Functions 4. Basic Pattern Matching 5. Algebraic Data Types 6. Sequences - The Core of Data Processing Patterns 7. Advanced Techniques: Functions Revisited 8. Data Crunching – Data Transformation Patterns 9. More Data Crunching 10. Type Augmentation and Generic Computations 11. F# Expert Techniques 12. F# and OOP Principles/Design Patterns 13. Troubleshooting Functional Code

Data querying

So far in the book, the sources of data collections were either collection generators or the file system. Let me move toward more realistic enterprise data sources, where data are persisted in databases. To access and transform such data, F# provides query expressions (https://msdn.microsoft.com/visualfsharpdocs/conceptual/query-expressions-%5bfsharp%5d).

Query expressions represent a concrete type of computation expressions that is embedded into the language. They allow to bring data into memory by querying external sources and transforming incoming data to the desired shape.

The F# query expressions are akin to sequence expressions: both produce data sequences. However, before the final data projection shaping the produced data sequence a query expression may apply to data a wide variety of data transformations that are similar to what we used to see in LINQ (https://en.wikipedia.org/wiki/Language_Integrated_Query). Query expressions can be considered LINQ support in F#...

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