C++ STL Tutorial
C++ Standard Template Library, or STL, is a powerful tool and plays a significant role in the C++ programming language. The STL library provides a collection or group of template classes and functions, giving a wide range of frequently used data structures and algorithms. The STL's major purpose is to make life easier and improve C++ programme development by offering generic, reusable, and efficient components.
The STL is based on the foundation of C++ templates, allowing developers to construct type-independent and highly flexible code. It contains many more components, such as vectors, lists, maps, iterators and basic algorithms like sorting and searching. It also has function objects like functors. These whole components are used to function in combination, which also allows the programmers to solve crucial problems, which makes it easier to design low-level data structures and algorithms.
By encouraging code reuse, readability, and maintainability, the STL has transformed C++ development. It has become an essential component of contemporary C++ development, providing a standardized and fast way to communicate with data structures and carry out critical operations. Understanding and utilizing the STL may substantially enhance your productivity and the standard of your code, whether you're an unfamiliar or seasoned C++ coder.
Key Components of C++ STL
The C++ Standard Template Library (STL) contains several key components essential to using this library. To use this library, we need to consider these key components:
1. Algorithm:
In the STL, the term "algorithm" refers to a group of predefined, reusable functions that carry out standard operations on collections of items frequently contained in containers. These methods give a standardized user interface for processing data and are made to operate with different container types (such as vectors, lists, and arrays). Using STL methods, routine data processing operations are primarily made simpler and more efficient, improving the maintainability and productivity of programs.
Common STL Algorithms: The STL has an extensive library of algorithms for many various tasks. Here are a few that are often used:
- Sorting: To organize items, use algorithms like std::sort, std::partial_sort, and std::stable_sort.
- Searching: Std::find, Std::binary_search, and Std::count algorithms help find components within a container.
- Transformation: To modify or compute data, algorithms like std::transform and std::for_each apply a defined action to each element in a range.
- Aggregation: Std::accumulate and other algorithms create aggregated values like the sum or product of components in a range.
- Set Operations: On sorted containers, algorithms like std::set_union and std::set_intersection carry out set operations, such as determining the union and intersection of sets.
2. Container:
The Standard Template Library (STL) in C++ offers a large selection of container classes that let you effectively store, manage, and work with collections of objects. The C++ STL's containers are intended to offer a variety of data structures for varied uses. They are a fundamental component of the C++ language and are vital to simplifying several programming tasks. The C++ STL's primary container types are listed below:
- Sequence Containerstd::vector: A dynamic array that may increase or contract in size. Vector access is particularly efficient because elements are kept close to one another in memory.
- std::deque (Double-Ended Queue): A double-ended queue that enables efficient insertion and deletion of entries at both ends. It is carried out via a series of memory chunks.
- std::list: A doubly-linked list with effective insertion and deletion capabilities at any location. It does not, however, offer constant-time random access.
- Associated Containers: A container that holds distinct, organized pieces is known as a set. It is implemented as a red-black tree, a self-balancing binary search tree.
- std::map: Stores key-value pairs with unique and sorted keys. It is often implemented as a red-black tree, just like a set.
- std::multiset and std::multimap: These functions are similar to set and map, except they may hold duplicate keys.
- std::unordered_set: A container that keeps distinct elements unordered and uses a hash table for quick access.
- std::unordered_map: Stores key-value pairs unordered, utilizing a hash table for quick retrieval. Compared to set and map, it is faster for huge collections.
- std::unordered_multiset and std::unordered_multimap: These functions are similar to unordered_set and unordered_map, except they can hold duplicate keys.
- std::stack: A container adapter that offers a Last-In-First-Out (LIFO) data structure. Deque or a list are frequently used in their implementation.
- std::queue: A container adapter that offers a First-In-First-Out (FIFO) data structure. Deque or a list are frequently used in their implementation.
- std::priority_queue: A container adapter that offers a priority queue data structure in which components are dequeued in descending order of priority. Vector is commonly used in its implementation.
- std::shared_ptr: A clever pointer that controls shared ownership of things that are allocated dynamically. It keeps track of ownership by reference counting.
- std::unique_ptr: An intelligent pointer that denotes exclusive control over an item and assures its deletion when no longer required.
- std::weak_ptr: An intelligent pointer that allows circular references to be destroyed in a shared ownership model.
3. Functors:
Functors, often known as "function objects," are an essential concept in the C++ Standard Template Library (STL). Functors provide a method for customized behaviour in algorithms and data structures by allowing you to treat things as functions. Functors are simply examples of classes or structs that carry out the operator() function call. They are used to express specific comparison, transformation, or operation logic in different STL algorithms and containers.
Some of the key points are:
- Function Object Definition: Functors are user-defined classes or structures that replace the operator() function, according to the definition of a function object. Instances of the functor class can be invoked like conventional functions, thanks to this operator. Functors are more flexible than ordinary functions because they encapsulate state and behaviour.
- Custom Behaviour: With the use of functors, programmers may specify unique behaviours for various STL algorithms and containers, including sorting, searching, and transformation. This personalization may be adjusted to meet the needs of a particular application, increasing the flexibility of the code.
- Algorithm Flexibility: Functors can encapsulate additional states or context, unlike function pointers or simple functions. Algorithms can use context-sensitive information during execution by setting this state at object construction and accessing it when the functor is called.
- Code Readability: Functors can improve code readability by enclosing the logic necessary for a particular operation within a single class. More self-explanatory code and better maintenance may result from this.
- Predicates in Algorithms: Algorithms like std::sort, std::find_if, and std::remove_if frequently employ functors as predicates. Various behaviours are possible thanks to these predicates, which specify the circumstances under which items should be performed or filtered away.
- Adaptability: Functors are capable of adapting to complicated needs. A significant degree of flexibility is provided by the ability to build functors that implement different sorting criteria for sorting algorithms or filter elements based on multiple criteria.
- Stateful Functors: Functors, unlike conventional functions, may keep a state between calls. When constructing algorithms that call for context-aware judgements, the capacity to retain previous knowledge can be of great use.
- Standard Library Functors: The C++ STL includes several predefined functors, including std::less, std::greater, and std::function. These common functors streamline routine activities and act as the basis for creating unique functors.
- Functor Usage Variability: Functors may be used with containers like std::set and std::map in addition to algorithms. For the components kept in these containers, they can provide special comparison functions, enabling different ordering standards.
4. Iterators:
In C++ STL algorithms, iterators are essential for traversing and modifying components in containers without compromising the technical details of the underlying data structure. They enable the smooth integration of algorithms with different data structures and offer a standard mechanism to access items across multiple container types. Iterators in C++ STL algorithms have the following essential properties:
- Traversal Abstraction: Iterators abstract the act of moving through the contents of a container, which is known as traversal. They serve as a standardized interface that enables algorithms to operate on various container types (such as vectors, lists, and maps) without being knowledgeable about the internal structure of any individual container.
- Iterators Hierarchy: The C++ STL specifies a number of iterator types with various degrees of capability and restrictions. These consist of random access iterators for going to any element in constant time, bidirectional iterators for travelling in both directions, begin() and end() iterators for specifying a range, and more. The characteristics of the container and the needs of the algorithm determine which iterator type should be used.
- Iterator Validity: In STL algorithms, iterator validity is essential. When container items are changed (for example, by insertion or deletion), iterators may become invalid. Using algorithms carelessly can result in undefined behaviour since they reference invalidated iterators.
- Iterator Pairs: Most STL algorithms operate on a range specified by two iterators, commonly represented as [begin, end]. The beginning iterator indicates the range's initial element, and the end iterator shows its last element. The element pointed to by the end is not included in the range; only items between the beginning and end remain.
- Algorithm-Iterator Compatibility: STL algorithms are built to operate with iterators without any issues. You may use several iterators and algorithms like std::for_each, std::find, std::sort, and std::accumulate to carry out a range of activities on container items.
- Iterator Traits: The <iterator> header offers a template class named std::iterator_traits that enables access to data about the iterator type's properties by algorithms. This makes it possible for algorithms to customize their actions to the capabilities of the iterator.
- Custom Iterators: By specifying the appropriate iterator methods and attributes, developers may build custom iterators for their data structures. They may employ STL algorithms with user-defined containers, increasing code reuse.
- Iterator Adapters: The STL offers iterator adapters, such as the std::back_insert_iterator and the std::front_insert_iterator, to let algorithms insert elements into containers (such as vectors or lists) quickly. With the help of these adapters, containers may be encapsulated and made to work with algorithms that demand output iterators.
- Lambda Expressions: Iterators may now be used in algorithms more efficiently, thanks to lambda expressions in C++11 and subsequent versions. When using algorithms, programmers can provide customized behaviour inline, improving code clarity and obviating the need for additional functor classes.
- Algorithm Complexity: Analyzing an algorithm's time complexity requires knowledge about the type of iterator utilized. Depending on whether they use forward, bidirectional, or random-access iterators, algorithms have various performance characteristics.
In summary, iterators are the glue that enables C++ STL algorithms to operate on various container types while preserving a standardized and practical interface. By removing the specifics of data structure traversal, they make it possible to write compelling and reusable code for various applications.
5. Smart Pointer:
Smart pointers, such as std::shared_ptr and std::unique_ptr, were first introduced in C++11 and improve memory management by automating the allocation and deallocation of dynamic memory. They make resource management safer and more dependable by preventing memory leaks.
6. Allocators:
Allocators provide containers with a degree of customization in memory management. They optimize certain use cases or platforms by giving developers control over how memory is allocated and deallocated.
7. Exception Safety:
Exception safety is a significant consideration in the design of many STL components. This means that even when unexpected issues arise during data processing, they are designed to handle exceptions patiently and guarantee that resources are cleaned up appropriately.
Example Code of Vector Container:
#include<iostream>
#include<vector>
using namespace std;
int main() {
// Create a vector to store integers
vector<int> integerVector;
int value;
// Display the original size of the vector
cout << "Initial vector size = " << integerVector.size() << endl;
// Push 5 values into the vector
for(value = 0; value < 5; value++) {
integerVector.push_back(value);
}
// Display the updated size of the vector
cout << "Updated vector size = " << integerVector.size() << endl;
// Access 5 values from the vector using indexing
for(value = 0; value < 5; value++) {
cout << "Value at index " << value << " = " << integerVector[value] << endl;
}
// Use an iterator to access the values in the vector
vector<int>::iterator iter = integerVector.begin();
while (iter != integerVector.end()) {
cout << "Value using iterator = " << *iter << endl;
iter++;
}
return 0;
}
Output:
![C++ STL Tutorial](https://static.tutorialandexample.com/cpp/cpp-stl-tutorial1.png)
Explanation:
This C++ code demonstrates using vectors, a dynamic data structure like an array from the Standard Template Library (STL). The programme begins by including the required libraries, such as vectors for working with vectors and iostream for input and output operations. An empty integer-capable vector named integerVector is initialized by the main function. Furthermore, a defined integer variable called value is used to populate the vector and retrieve its elements.
The code illustrates how the size and content of the vector may be changed. The size() method is used at first to demonstrate how big the vector is and that it is currently empty. The vector is then filled with numbers from 0 to 4 using the push_back() function, which dynamically expands the vector to make room for the additional members. The program then prints the vector's adjusted size.
The code used iterators and indexing to access the vector's items. The first method uses an index-based loop to cycle through the vector and output the associated values. In the second method, iterators are used, and a vector-specific iterator is built to iterate across the vector and show each member.
Advantages of C++ STL Library
- Reusability: The reusability nature makes the algorithms and data structures ready-to-use, such as vectors, lists, queues and maps. Using this component, the developers can save time and effort without having to write or build from scratch.
- Standardization: As part of the C++ Standard Library, the C++ STL is a standardized library. It makes code more portable and minimizes compatibility difficulties by ensuring consistency across many C++ implementations and platforms.
- Efficiency: STL components frequently have excellent performance optimization. The algorithms often employ low-level optimizations and are created to be effective. Additionally, data structures with O(1) random access and effective memory management include vectors and sets.
- Standard Containers: The ability to dynamically resize STL containers, such as vectors and maps, enables them to adjust to changing data needs. They are excellent for a variety of applications due to their versatility.
- Algorithm Consistency: STL algorithms work inside the bounds of iterators' ranges, maintaining a constant user interface for various data structures. This consistency facilitates code reuse by making it simple to apply the same algorithm to different containers.
- Productivity: Using high-level methods and data structures from the STL makes coding more accessible. Development may go faster and with fewer defects if developers focus on fixing particular issues rather than minor details.
- Flexibility: The STL enables customization and offers a wide range of standard data structures and algorithms. To customize the behaviour of STL components to meet their requirements, developers can design their data structures, function objects, and iterators.
Conclusion
The C++ Standard Template Library (STL), which has significant advantages like reusable, practical and ready-to-use algorithms and data structures, is an essential tool for C++ developers. It increases productivity by minimizing low-level coding work because of components that are performance and safety-optimized.
The adaptability of STL allows for customization while preserving a constant interface for different containers. Its durability and community support guarantee dependability and offer an extensive range of resources. The C++ STL improves code reuse, effectiveness, safety, and maintainability, making it a vital tool for C++ programmers to speed up development and encourage high-quality code.