Using Q# from Python

Dockerfile

# The same image used by mybinder.org
FROM mcr.microsoft.com/quantum/iqsharp-base:0.8.1906.2007-beta

# Add metadata indicating that this image is used for the katas.
ENV IQSHARP_HOSTING_ENV=reddit

# Make sure the contents of our repo are in ${HOME}
# Required for mybinder.org
COPY . ${HOME}
USER root
RUN chown -R ${USER} ${HOME}
USER ${USER}

python-qsharp.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import qsharp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "hello = qsharp.compile(\"\"\"\n",
    "    function Hello() : Unit {\n",
    "         Message(\"Hello, world!\");\n",
    "    }\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hello, world!\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "()"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hello.simulate()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "qrng = qsharp.compile(\"\"\"\n",
    "    open Microsoft.Quantum.Measurement;\n",
    "    \n",
    "    operation NextRandomBit() : Result {\n",
    "        using (q = Qubit()) {\n",
    "            return MResetX(q);\n",
    "        }\n",
    "    }\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "key = hex(int(\"\".join([\"1\" if qrng.simulate() else \"0\" for _ in range(512)]), 2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0xcbf21e57060fccb035635ebfc0a7c01e3008ec5d34db84bb7623ccda8434b1c7fe8befe08ca81a3d0ee63939407f4b4aa43a8c25a470804352c2fd3bdf0128fe\n"
     ]
    }
   ],
   "source": [
    "print(key)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}