In a previous article I explained how to create a Conan package. In this article I’m going to show the steps needed to publish it, so it can be used by anyone.

After we have our Conan package ready, we need to create a JFrog Bintray account.

In the past I wrote an article that explains how to consume packages using Conan. In this article I’m going to explain how we can create our own packages with Conan.

I’m going to create a simple cpp library and make a conan package out of it.

Sample package

The first step is to create a folder for the library:

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mkdir MyLib
cd MyLib

A variadic function is a function that can take a variable number of arguments.

I have used variadic functions in previous posts, but I have not explained how they work. This post will cover that.

C-style variadic functions

C++ supports the C-like syntax for writing variadic fuctions.

Let’s say we want to write a function that adds numbers together. If we wanted to write a function that adds two numbers, we could do it easily:

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int add(int a, int b) {
  return a + b;
}

Using functions that take functions

There are times, when it is convenient to have a function receive a function as an argument. This technique can be seen in the standard C++ library. As an example, std::transform can be used to create a series of values based on other values:

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#include <vector>
#include <algorithm>
#include <iostream>

int makeNumbersBig(int small) {
  return small * 10;
}

int main() {
  std::vector<int> numbers{1, 2, 3}; // numbers has 3 values: 1, 2, 3
  std::vector<int> bigNumbers(3); // bigNumbers has 3 values, default
                                  // initialized: 0, 0, 0

  // Starting at numbers.begin() and until numbers.end(), execute
  // makeNumbersBig and store the result in bigNumbers
  std::transform(
    numbers.begin(),
    numbers.end(),
    bigNumbers.begin(),
    makeNumbersBig
  );

  // Print the values of bigNumbers
  for (const auto big : bigNumbers) {
    std::cout << big << std::endl;
  }
}

A while ago I discovered generics in Java. Today, I’m going to explore how to do the same with C++.

Generics in C++ are known as templates. We use the keyword template to tell the compiler that we are about to define one:

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template <typename T>
class Hello {};

In the example above, you can also see that typename is used to define the type. You might also see the keyword class used interchangeably (There are some scenarios where they are not interchangeable, but I’m not going to cover those in this article):

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template <class T>
class Hello {};

In previous articles, I explored how to write concurrent code using threads, how to communicate between threads using futures, async, packaged tasks and promises, how to avoid race conditions using mutexes, and other related topics. This article is going to go a little higher level and explore some things to consider when designing a concurrent system.

Why use concurrency?

Before I started working with C++, I used to write software in PHP, JavaScript, Ruby, etc. When I wrote software on those languages, I didn’t need to worry about concurrency, why do I need to worry now?

When I was writing web applications in PHP, I didn’t have to worry about threads or mutexes. I received a request, maybe got some data from a database, did some calculations and returned a result. Why can’t life continue to be that easy?

In this article, I’m going to explain how to create a very simple server with C++. The server will receive a single message, send a response and then quit. For network programming in C++, we need to use some low level C functions that translate directly to syscalls.

Let’s explore the syscalls we’ll need.

socket

We’ll use the socket function to create a socket. A socket can be seeen as a file descriptor that can be used for communication.

This is the signature of the function:

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int socket(int domain, int type, int protocol);

An operation on data is said to be atomic if it is impossible to find the operation half-way done. It’s very easy to see when an operation is not atomic when used in a struct:

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struct Type {
  int a;
  int b;
}

Type data;

void fillType(int a, int b) {
  data.a = a;
  data.b = b;
}

In a previous article, I showed how to use mutexes to prevent race conditions. Condition Variables use mutexes to allow exclusive access to data, but also allow threads to wait for something to happen before they start to do work.

Understanding when Condition Variables are useful is easier with an example. Let’s say we are building a queue system. To keep it simple we will start with 1 producer and 1 consumer. We can make this system safe with a mutex:

I consider dependency management a very important part of a maintainable software project. Once you start writing software that depends on other code, it can quickly become unpractical to do dependency management by hand, so a good system is necessary to make it easy to work on such projects.

Since C++ has been out for a while, I expected to find a very mature ecosystem in this regard. Looking around and reading a little, I found that there is no community agreed way of solving the problem of managing dependencies. One reason for this seems to be that it’s not easy to build a system that helps you do dependency management when there are many ways to build a package.