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Raw data access (json)

module:hackathon.20180615 (v1.0.0)
Creation date: 2018-08-09
Source: GitHub
cID: 032630d041b4fd8a:f40e5947238264d1

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This is our attempt to share automation actions from scientific research projects as unified Python modules with a common CLI and Python API to help researchers and practitioners reuse best practices. Our on-going project is to make the onboarding process as simple as possible via this platform. Please check this CK white paper and don't hesitate to contact us if you have suggestions or feedback!


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1st Quantum Computing Hackathon, Cambridge, 15 June 2018

Installation (on Ubuntu)

Install global prerequisites, Python3 and its pip (Python2 is also supported)

$ sudo apt-get install python3 python3-pip

Install Collective Knowledge

$ sudo pip3 install ck

Installation (on MacOS)

Install Python3 and its pip (Python2 is also supported)

$ brew update
$ brew reinstall python
$ pip install ck

Non-root CK installation

You can install CK in your local user space as follows:

$ git clone http://github.com/ctuning/ck
$ export PATH=$PWD/ck/bin:$PATH

Test CK installation

$ ck version

Common part of the workflow installation

Pull CK repositories

$ ck pull repo:ck-quantum
$ ck pull repo:ck-env
$ ck pull repo:ck-rigetti
$ ck pull repo:ck-qiskit

Detect a Python interpreter (interactively choose one if there are several options)

$ ck detect soft:compiler.python

Install this CK repository with all its dependencies (other CK repos to reuse artifacts)

$ ck install package:tool-hackathon

Install pyQuil

$ ck install package:lib-pyquil-1.9.0

Run a demo program (press Enter if prompted)

$ ck run program:pyquil-demo

    * tmp-stdout.tmp

      Number of games: 10
      Q's winning average: 1.0
      Picard's flip-decision average: 0.5


$ ck run program:rigetti-vqe




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