A Jupyter kernel for C++ based on the cling
C++ interpreter and the xeus
native implementation of the Jupyter protocol, xeus.
Shift + Enter
std::cout
and std::cerr
are redirected to the notebook frontend.
#include <iostream>
std::cout << "some output" << std::endl;
std::cerr << "some error" << std::endl;
#include <stdexcept>
throw std::runtime_error("Unknown exception");
Omitting the ;
in the last statement of a cell results in an output being printed
int j = 5;
j
cling
has a broad support of the features of C++. You can define functions, classes, templates, etc ...
double sqr(double a)
{
return a * a;
}
double a = 2.5;
double asqr = sqr(a);
asqr
class Foo
{
public:
virtual ~Foo() {}
virtual void print(double value) const
{
std::cout << "Foo value = " << value << std::endl;
}
};
Foo bar;
bar.print(1.2);
class Bar : public Foo
{
public:
virtual ~Bar() {}
virtual void print(double value) const
{
std::cout << "Bar value = " << 2 * value << std::endl;
}
};
Foo* bar2 = new Bar;
bar2->print(1.2);
delete bar2;
#include <typeinfo>
template <class T>
class FooT
{
public:
explicit FooT(const T& t) : m_t(t) {}
void print() const
{
std::cout << typeid(T).name() << " m_t = " << m_t << std::endl;
}
private:
T m_t;
};
template <>
class FooT<int>
{
public:
explicit FooT(const int& t) : m_t(t) {}
void print() const
{
std::cout << "m_t = " << m_t << std::endl;
}
private:
int m_t;
};
FooT<double> foot1(1.2);
foot1.print();
FooT<int> foot2(4);
foot2.print();
class Foo11
{
public:
Foo11() { std::cout << "Foo11 default constructor" << std::endl; }
Foo11(const Foo11&) { std::cout << "Foo11 copy constructor" << std::endl; }
Foo11(Foo11&&) { std::cout << "Foo11 move constructor" << std::endl; }
};
Foo11 f1;
Foo11 f2(f1);
Foo11 f3(std::move(f1));
#include <vector>
std::vector<int> v = { 1, 2, 3};
auto iter = ++v.begin();
v
*iter
... and also lambda, universal references, decltype
, etc ...
?std::vector
display_data
mechanism¶For a user-defined type T
, the rich rendering in the notebook and JupyterLab can be enabled by by implementing the function xeus::xjson mime_bundle_repr(const T& im)
, which returns the JSON mime bundle for that type.
More documentation on the rich display system of Jupyter and Xeus-cling is available at https://xeus-cling.readthedocs.io/en/latest/rich_display.html
#include <string>
#include <fstream>
#include "xtl/xbase64.hpp"
#include "xeus/xjson.hpp"
namespace im
{
struct image
{
inline image(const std::string& filename)
{
std::ifstream fin(filename, std::ios::binary);
m_buffer << fin.rdbuf();
}
std::stringstream m_buffer;
};
xeus::xjson mime_bundle_repr(const image& i)
{
auto bundle = xeus::xjson::object();
bundle["image/png"] = xtl::base64encode(i.m_buffer.str());
return bundle;
}
}
im::image marie("images/marie.png");
marie
#include <string>
#include <fstream>
#include "xtl/xbase64.hpp"
#include "xeus/xjson.hpp"
namespace au
{
struct audio
{
inline audio(const std::string& filename)
{
std::ifstream fin(filename, std::ios::binary);
m_buffer << fin.rdbuf();
}
std::stringstream m_buffer;
};
xeus::xjson mime_bundle_repr(const audio& a)
{
auto bundle = xeus::xjson::object();
bundle["text/html"] =
std::string("<audio controls=\"controls\"><source src=\"data:audio/wav;base64,")
+ xtl::base64encode(a.m_buffer.str()) +
"\" type=\"audio/wav\" /></audio>";
return bundle;
}
}
au::audio drums("audio/audio.wav");
drums
#include "xcpp/xdisplay.hpp"
xcpp::display(drums);
#include <string>
#include "xcpp/xdisplay.hpp"
namespace ht
{
struct html
{
inline html(const std::string& content)
{
m_content = content;
}
std::string m_content;
};
xeus::xjson mime_bundle_repr(const html& a)
{
auto bundle = xeus::xjson::object();
bundle["text/html"] = a.m_content;
return bundle;
}
}
// A red rectangle
ht::html rect(R"(
<div style='
width: 90px;
height: 50px;
line-height: 50px;
background-color: blue;
color: white;
text-align: center;'>
Original
</div>)");
xcpp::display(rect, "some_display_id");
// Update the rectangle to be blue
rect.m_content = R"(
<div style='
width: 90px;
height: 50px;
line-height: 50px;
background-color: red;
color: white;
text-align: center;'>
Updated
</div>)";
xcpp::display(rect, "some_display_id", true);
Magics are special commands for the kernel that are not part of the C++ language.
They are defined with the symbol %
for a line magic and %%
for a cell magic.
More documentation for magics is available at https://xeus-cling.readthedocs.io/en/latest/magics.html.
#include <algorithm>
#include <vector>
std::vector<double> to_shuffle = {1, 2, 3, 4};
%timeit std::random_shuffle(to_shuffle.begin(), to_shuffle.end());
xtensor
is a C++ library for manipulating N-D arrays with an API very similar to that of numpy.
#include <iostream>
#include "xtensor/xarray.hpp"
#include "xtensor/xio.hpp"
#include "xtensor/xview.hpp"
xt::xarray<double> arr1
{{1.0, 2.0, 3.0},
{2.0, 5.0, 7.0},
{2.0, 5.0, 7.0}};
xt::xarray<double> arr2
{5.0, 6.0, 7.0};
xt::view(arr1, 1) + arr2
Together with the C++ Jupyter kernel, xtensor
offers a similar experience as NumPy
in the Python Jupyter kernel, including broadcasting and universal functions.
#include <iostream>
#include "xtensor/xarray.hpp"
#include "xtensor/xio.hpp"
xt::xarray<int> arr
{1, 2, 3, 4, 5, 6, 7, 8, 9};
arr.reshape({3, 3});
std::cout << arr;
#include "xtensor-blas/xlinalg.hpp"
xt::xtensor<double, 2> m = {{1.5, 0.5}, {0.7, 1.0}};
std::cout << "Matrix rank: " << std::endl << xt::linalg::matrix_rank(m) << std::endl;
std::cout << "Matrix inverse: " << std::endl << xt::linalg::inv(m) << std::endl;
std::cout << "Eigen values: " << std::endl << xt::linalg::eigvals(m) << std::endl;
xt::xarray<double> arg1 = xt::arange<double>(9);
xt::xarray<double> arg2 = xt::arange<double>(18);
arg1.reshape({3, 3});
arg2.reshape({2, 3, 3});
std::cout << xt::linalg::dot(arg1, arg2) << std::endl;