From f0554a8e69c54386935050ecce9838ba8898035a Mon Sep 17 00:00:00 2001
From: "Davide Gessa (dakk)" <gessadavide@gmail.com>
Date: Fri, 24 Nov 2023 11:38:04 +0100
Subject: [PATCH] add quickstart.ipynb to docs

---
 CONTRIBUTING.md                      |   2 +-
 docs/source/conf.py                  |   1 +
 docs/source/index.rst                |  10 +-
 docs/source/quickstart.ipynb         | 171 +++++++++++++++++++++++++++
 docs/source/supported.rst            |   1 +
 qlasskit/qcircuit/qcircuitwrapper.py |   2 +-
 6 files changed, 182 insertions(+), 5 deletions(-)
 create mode 100644 docs/source/quickstart.ipynb

diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
index 1328cdea..c2024754 100644
--- a/CONTRIBUTING.md
+++ b/CONTRIBUTING.md
@@ -18,7 +18,7 @@ tox
 ## Make docs
 
 ```
-pip install sphinx sphinx_rtd_theme
+pip install sphinx sphinx_rtd_theme myst_parser
 cd docs
 make html
 ```
\ No newline at end of file
diff --git a/docs/source/conf.py b/docs/source/conf.py
index 4bdf881e..b74e6cdb 100644
--- a/docs/source/conf.py
+++ b/docs/source/conf.py
@@ -22,6 +22,7 @@
     "sphinx.ext.coverage",
     "sphinx.ext.napoleon",
     "sphinx_rtd_theme",
+    "myst_nb"
 ]
 
 templates_path = ["_templates"]
diff --git a/docs/source/index.rst b/docs/source/index.rst
index fa5076de..41eb9a01 100644
--- a/docs/source/index.rst
+++ b/docs/source/index.rst
@@ -4,16 +4,20 @@ Qlasskit
 Qlasskit is a Python library that allows quantum developers to write classical algorithms in pure 
 Python and translate them into unitary operators (gates) for use in quantum circuits.
 
-
-
 .. toctree::
    :maxdepth: 2
-   
+   :caption: Qlasskit
+
+   quickstart.ipynb   
    howitworks
    supported
    algorithms
    api
 
+.. toctree::
+   :maxdepth: 2
+   :caption: Examples
+
 
 Indices and tables
 ==================
diff --git a/docs/source/quickstart.ipynb b/docs/source/quickstart.ipynb
new file mode 100644
index 00000000..644bb187
--- /dev/null
+++ b/docs/source/quickstart.ipynb
@@ -0,0 +1,171 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Quickstart\n",
+    "\n",
+    "First, install the qlasskit library using pip:\n",
+    "\n",
+    "```\n",
+    "pip install qlasskit\n",
+    "```\n",
+    "\n",
+    "We now define a function named `and_all` that returns `True` iff all the element of an input list `a_list` are `True`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from qlasskit import qlassf, Qlist, Qint2\n",
+    "\n",
+    "@qlassf\n",
+    "def and_all(a_list: Qlist[bool, 4]) -> bool:\n",
+    "    r = True\n",
+    "    for i in a_list:\n",
+    "        r = r and i\n",
+    "    return r           "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The qlasskit compiler will produce an optimized quantum circuit performing the given function."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 203.885x451.5 with 1 Axes>"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "and_all.export('qiskit').draw('mpl')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We now can use our quantum function as an oracle for a Grover search. For instance, we want to find the input value that yeld to a `True` value of the function:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from qlasskit.algorithms import Grover\n",
+    "\n",
+    "q_algo = Grover(and_all, True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Qlasskit prepares the quantum circuit for the Grover search:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 2210.55x1120.39 with 1 Axes>"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "qc = q_algo.export('qiskit')\n",
+    "qc.draw('mpl')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now we can use our prefered framework and simulator for sampling the result; this is an example using `qiskit` with `aer_simulator`.\n",
+    "\n",
+    "The `Grover` class, along with all circuit wrappers in qlasskit, provides utilities to encode inputs and decode outputs from a quantum circuit using the high level type definition. In the output histogram, it's now evident that the input leading to a `True` result in the `and_all` function is a list where all elements are set to `True`, aligning with our expectations.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 700x500 with 1 Axes>"
+      ]
+     },
+     "execution_count": 35,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from qiskit import Aer, QuantumCircuit, transpile\n",
+    "from qiskit.visualization import plot_histogram\n",
+    "\n",
+    "qc.measure_all()\n",
+    "simulator = Aer.get_backend(\"aer_simulator\")\n",
+    "circ = transpile(qc, simulator)\n",
+    "result = simulator.run(circ).result()\n",
+    "counts = result.get_counts(circ)\n",
+    "\n",
+    "counts_readable = q_algo.decode_counts(counts)\n",
+    "plot_histogram(counts_readable)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "qlasskit_310-env",
+   "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": "3.10.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/docs/source/supported.rst b/docs/source/supported.rst
index a396e9fc..3fb89e2b 100644
--- a/docs/source/supported.rst
+++ b/docs/source/supported.rst
@@ -73,6 +73,7 @@ List (fixed size)
 ^^^^^^^^^^^^^^^^^
 
 .. code-block:: python
+   
    [a, b]
 
 
diff --git a/qlasskit/qcircuit/qcircuitwrapper.py b/qlasskit/qcircuit/qcircuitwrapper.py
index c3fe0109..003de79b 100644
--- a/qlasskit/qcircuit/qcircuitwrapper.py
+++ b/qlasskit/qcircuit/qcircuitwrapper.py
@@ -86,4 +86,4 @@ def export(self, framework: SupportedFramework = "qiskit") -> Any:
         return self._qcircuit.export(mode="circuit", framework=framework)
 
     def draw(self):
-        print(self._qcircuit.draw())
+        return self._qcircuit.draw()