Installing Qiskit
A short guide on getting Qiskit Installed on your local machine
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A short guide on getting Qiskit Installed on your local machine
Last updated
Was this helpful?
Qiskit is a python library prepared for people who would like to work on quantum systems. It's a great way to integrate quantum solutions into your own work. You can use other python libraries along side it to enhance the work you do with it. Some recommended libraries would be:
- Great for visualizing results and making graphs
- A math library that includes all kinds of useful functions for preforming complex equations and operations
- A data structure library designed to make importing and handling data (especially large sets) easier
All of these, along with a bunch of other useful libraries for doing science, are included in the package, which IBM recommends you install along with qiskit.
Since this is a python library, you'll need python installed on your computer. If you already have it set-up you're good to go - just be sure that you're using python 3.5 or later. If not, you can find in the section.
We mentioned at the beginning of this guide, I'll assume you know a little python already. Python is super easy to learn and is very intuitive, especially if you already know another object oriented language like Java. You can find more in the section.
IBM recommends that you have the Anaconda suite installed - Anaconda includes a whole bunch of useful tools and it's a great option if you plan to use python for more scientific type stuff. Be careful - Anaconda will install it's own version of python along with the rest of the tools. This won't be a problem and long as you carefully follow the installation instructions. You can find some more in the section.
Once you're all set, you can find and follow the installation guide on the Qiskit website. They have several; great resources to help you out:
Both these resources are very comprehensive and should provide all the information you need to get ready to use qiskit on your local machine.
I'll be using for this tutorials. This is so that I can quickly and easily display output and show the result of the code I've written for you. You may also choose to do the same - it's a good way to learn. Jupyter will be installed with Anaconda, and you can find more in the section.
You may also want to use an IDE, like , or something similar. That's up to you - technically all this work can be done in a simple text editor, but an IDE makes for a nice experience. If you prefer simple text editors, I highly recommend - it's an excellent option.
IBM's own goes into detail about
IBM has also got an which includes a