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Boosting data processing in Deepnote: A guide to setting Up C++ kernels

By Filip Žitný

Updated on March 6, 2024

The advantage of C++ in Deepnote can come in handy when you want faster data processing. If this is your goal, then this guide is for you.

For users looking to work with C++, We've prepared a setup for a C++ kernel in Deepnote using a custom environment. We will provide detailed instructions on setting up and running a C++ kernel in Deepnote, along with tips for troubleshooting common issues.

Setting up the C++ kernel

FROM deepnote/python:3.9

RUN apt-get update && \\
    apt-get install -y g++ libtinfo5
RUN pip install jupyter-console
RUN wget <> && \\
    tar -xf cling_2020-11-05_ROOT-ubuntu18.04.tar.bz2 && \\
    cd cling_2020-11-05_ROOT-ubuntu18.04/share/cling/Jupyter/kernel && \\
    pip install -e . && \\
    jupyter-kernelspec install --user cling-cpp17
ENV PATH="cling_2020-11-05_ROOT-ubuntu18.04/bin:$PATH"
RUN jupyter console --kernel cling-cpp17

Example: Running C++ code

#include <bits/stdc++.h>
using namespace std; //this line is only for noobs xD
short countBits(unsigned int x){
	short numBits = 0;
	while (x) {
		numBits += x& 1;
		x >>= 1;
	return numBits
count << countBits(4) <<endl;
// result 1

Please note, in the current version of the kernel, there are some limitations like the inability to define more than one function in a block. However, these are expected to be corrected in future versions of this kernel.

So if you think C++ can be your game-changer, deep dive into Deepnote and start the process.

If you encounter further issues, please get in touch with our support. Happy coding in Deepnote!

Filip Žitný

Data Scientist

Follow Filip on Twitter, LinkedIn and GitHub

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