Book Image

Hands-On Functional Programming with C++

By : Alexandru Bolboaca
Book Image

Hands-On Functional Programming with C++

By: Alexandru Bolboaca

Overview of this book

Functional programming enables you to divide your software into smaller, reusable components that are easy to write, debug, and maintain. Combined with the power of C++, you can develop scalable and functional applications for modern software requirements. This book will help you discover the functional features in C++ 17 and C++ 20 to build enterprise-level applications. Starting with the fundamental building blocks of functional programming and how to use them in C++, you’ll explore functions, currying, and lambdas. As you advance, you’ll learn how to improve cohesion and delve into test-driven development, which will enable you in designing better software. In addition to this, the book covers architectural patterns such as event sourcing to help you get to grips with the importance of immutability for data storage. You’ll even understand how to “think in functions” and implement design patterns in a functional way. By the end of this book, you’ll be able to write faster and cleaner production code in C++ with the help of functional programming.
Table of Contents (23 chapters)
Free Chapter
1
Section 1: Functional Building Blocks in C++
7
Section 2: Design with Functions
12
Section 3: Reaping the Benefits of Functional Programming
17
Section 4: The Present and Future of Functional Programming in C++

Composability and removing duplication

We have already seen an example of where we had a fair amount of duplication:

const Sums sumsWithFunctionalLoops(const vector<int>& numbers){
Sums theTotals;
vector<int> evenNumbers;
copy_if(numbers.begin(), numbers.end(), back_inserter(evenNumbers),
isEven);
theTotals.evenSum = accumulate(evenNumbers.begin(),
evenNumbers.end(), 0);

vector<int> oddNumbers;
copy_if(numbers.begin(), numbers.end(), back_inserter(oddNumbers),
isOdd);
theTotals.oddSum= accumulate(oddNumbers.begin(), oddNumbers.end(),
0);

theTotals.total = accumulate(numbers.begin(), numbers.end(), 0);

return theTotals;
}

We managed to reduce it using functions, as shown in the following code:

template<class UnaryPredicate>
const vector<int> filter(const vector<int>& input, UnaryPredicate filterFunction){
vector<int> filtered;
copy_if(input.begin(), input.end(), back_inserter(filtered),
filterFunction);
return filtered;
}

const int sum(const vector<int>& input){
return accumulate(input.begin(), input.end(), 0);
}

const Sums sumsWithFunctionalLoopsSimplified(const vector<int>& numbers){
Sums theTotals(
sum(filter(numbers, isEven)),
sum(filter(numbers, isOdd)),
sum(numbers)
);

return theTotals;
}

It's interesting to see how the functions are composed in various ways; we have sum(filter()) called twice, and sum() called once. Moreover, filter can be used with multiple predicates. Additionally, with a bit of work, we can make both filter and sum polymorphic functions:

template<class CollectionType, class UnaryPredicate>
const CollectionType filter(const CollectionType& input, UnaryPredicate filterFunction){
CollectionType filtered;
copy_if(input.begin(), input.end(), back_inserter(filtered),
filterFunction);
return filtered;
}
template<typename T, template<class> class CollectionType>
const T sum(const CollectionType<T>& input, const T& init = 0){
return accumulate(input.begin(), input.end(), init);
}

It's now easy to call filter and sum with arguments of type other than vector<int>. The implementation is not perfect, but it illustrates the point that I'm trying to make, that is, small, immutable functions can easy become polymorphic and composable. This works especially well when we can pass functions to other functions.