{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Demonstration of Pypi package OCaml for polyglot notebook\n",
    "\n",
    "TL;DR: [this Pypi `ocaml` package](https://pypi.org/project/ocaml/) allows to embed a real and complete OCaml runtime (with full standard library) in an IPython console or Jupyter notebook running IPython kernel (Python 3). OCaml functions and tiny programs can then be called directly from the IPython/Jupyter console, and results can be printed, or affected to Python variables! It even supports [Currying](https://en.wikipedia.org/wiki/Currying) multi-argument functions!\n",
    "\n",
    "See also: note, if you really want to use OCaml in a Jupyter notebook, the best solution is [OCaml-jupyter](https://github.com/akabe/ocaml-jupyter/) kernel!\n",
    "(i opened [an issue](https://github.com/akabe/ocaml-jupyter/issues/167) there to present this to the developer, just for his curiosity)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "- Author: [Lilian Besson (@Naereen)](https://github.com/Naereen/)\n",
    "- Date: 23/02/2021\n",
    "- License: [MIT License](https://lbesson.mit-license.org/)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Introduction\n",
    "\n",
    "> See [this issue](https://github.com/Naereen/notebooks/issues/28) I opened and assigned to myself."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "If you run this:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T02:31:38.720378Z",
     "start_time": "2021-02-23T02:31:38.717772Z"
    },
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "!pip3 install ocaml"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Then you can use basic OCaml expressions and standard library... from IPython or Jupyter notebook with IPython kernel, without having to install OCaml yourself on your laptop!\n",
    "It's pre-compiled. I don't know what version thought..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T04:28:17.694520Z",
     "start_time": "2021-02-23T04:28:17.691326Z"
    },
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [],
   "source": [
    "import ocaml"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T04:28:18.246375Z",
     "start_time": "2021-02-23T04:28:18.238076Z"
    }
   },
   "outputs": [],
   "source": [
    "answer_to_life = %ocaml 40 + 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T04:28:18.743192Z",
     "start_time": "2021-02-23T04:28:18.734826Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "42\n",
      "<class 'int'>\n"
     ]
    }
   ],
   "source": [
    "print(answer_to_life)\n",
    "print(type(answer_to_life))  # a real integer!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It would be a great project to show to students studying Python and C and OCaml : this tiny IPython magic makes the link between Python and OCaml (one way) using OCaml compiled as a dynamic extension to CPython 😍 !"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Reference and missing documentation of `ocaml` Pypi package\n",
    "\n",
    "This [Jupyter notebook](https://jupyter.org) uses the [ocaml v0.0.11](https://pypi.org/project/ocaml/) package from Pypi.\n",
    "\n",
    "There is no documentation, I asked the [author](https://github.com/LaurentMazare/), who works at [JaneStreet](https://www.janestreet.com/) and he redirected me to [this blog post](https://blog.janestreet.com/using-python-and-ocaml-in-the-same-jupyter-notebook/) by JaneStreet."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Apparently, being professional developers doesn't mean they restrain themselves from shipping unfinished and undocumented packages to Pypi. Okay... Why? It seems highly unprofessional! I understand being in a hurry, but then just don't publish to Pypi, and let user install it using `pip` but from a Git repository:\n",
    "```bash\n",
    "$ pip install git+https://github.com/<Username>/<Projects>\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "[Their blog post](https://blog.janestreet.com/using-python-and-ocaml-in-the-same-jupyter-notebook/) states\n",
    "> *Note that this package is not currently very well polished but it should give some ideas of what can be done through this Python-OCaml integration.*\n",
    "\n",
    "But come on, writing a short README or description in the `setup.py` is the least that they should do..."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Iframe showing the <https://pypi.org/project/ocaml/> page:\n",
    "<iframe src=\"http://pypi.org/project/ocaml/>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "I don't do that!  See my [Pypi packages](https://pypi.org/user/Naereen/) on <https://pypi.org/user/Naereen/>:\n",
    "\n",
    "> - [lempel-ziv-complexity](https://pypi.org/project/lempel-ziv-complexity) (Last released on Dec 19, 2019): *Fast implementation of the Lempel-Ziv complexity function*.\n",
    "> - [SMPyBandits](https://pypi.org/project/SMPyBandits) (Last released on Oct 25, 2019): *SMPyBandits: Open-Source Python package for Single- and Multi-Players multi-armed Bandits algorithms.*\n",
    "> - [parcoursup](https://pypi.org/project/parcoursup) (Last released on Nov 14, 2018): *ParcourSup.py : un clone en Python 3 de ParcoursSup, écrit à but didactique*.\n",
    "> - [generatewordcloud](https://pypi.org/project/generatewordcloud) (Last released on Oct 16, 2016): *A simple Python (2 or 3) script to generate a PNG word-cloud image from a bunch of text files. Based on word_cloud.*\n",
    "> - [ansicolortags](https://pypi.org/project/ansicolortags) (Last released on Jul 2, 2016): *ansicolortags brings a simple and powerful way to use colours in a terminal application with Python 2 and 3.*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Let's show the current version of the package, just for reference:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T02:23:19.621576Z",
     "start_time": "2021-02-23T02:23:19.425289Z"
    }
   },
   "outputs": [],
   "source": [
    "%load_ext watermark"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T02:23:48.476499Z",
     "start_time": "2021-02-23T02:23:48.354917Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPython 3.6.9\n",
      "IPython 7.16.1\n",
      "\n",
      "ocaml 0.0.11\n"
     ]
    }
   ],
   "source": [
    "%watermark -v -p ocaml"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## A first example\n",
    "\n",
    "As for other languages binding, we can have either a full cell, starting with `%%ocaml` :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T02:38:19.254859Z",
     "start_time": "2021-02-23T02:38:19.235065Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hello world from OCaml running in Jupyter (from IPython)!\n"
     ]
    }
   ],
   "source": [
    "%%ocaml\n",
    "print_endline \"Hello world from OCaml running in Jupyter (from IPython)!\";;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Natively, IPython/Jupyter supports [lots of \"magic commands\"](https://ipython.readthedocs.io/en/stable/interactive/magics.html), and especially `%%bash`, `%%perl`, `%%javascript` and `%%ruby` interface to famous scripting languages, and a generic `%%script` one."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T04:36:13.019507Z",
     "start_time": "2021-02-23T04:36:12.987422Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hello world from Bash running in Jupyter (from IPython)\n"
     ]
    }
   ],
   "source": [
    "%%bash\n",
    "echo \"Hello world from Bash running in Jupyter (from IPython)\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T04:36:13.576743Z",
     "start_time": "2021-02-23T04:36:13.528680Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hello world from Bash running in Jupyter (from IPython)\n"
     ]
    }
   ],
   "source": [
    "%%script bash\n",
    "echo \"Hello world from Bash running in Jupyter (from IPython)\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Not that it has been possible, since a long time, to call an OCaml toplevel like this!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T02:47:28.127172Z",
     "start_time": "2021-02-23T02:47:28.066288Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "        OCaml version 4.05.0\n",
      "\n",
      "Findlib has been successfully loaded. Additional directives:\n",
      "  #require \"package\";;      to load a package\n",
      "  #list;;                   to list the available packages\n",
      "  #camlp4o;;                to load camlp4 (standard syntax)\n",
      "  #camlp4r;;                to load camlp4 (revised syntax)\n",
      "  #predicates \"p,q,...\";;   to set these predicates\n",
      "  Topfind.reset();;         to force that packages will be reloaded\n",
      "  #thread;;                 to enable threads\n",
      "\n",
      "# Hello world from OCaml running in Jupyter (from IPython)!\n",
      "- : unit = ()\n",
      "# \n"
     ]
    }
   ],
   "source": [
    "%%script ocaml\n",
    "print_endline \"Hello world from OCaml running in Jupyter (from IPython)!\";;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "But it does nothing else than opening a sub-process, running `ocaml` command, feeding it the content of the cell, and then exiting.\n",
    "\n",
    "- Cons: It's not so pretty, as it prints all this startup messages. I thought we could silent them, like `python -q` (quiet) option... but we can't!\n",
    "- Pros: it shows the value of each line, so it can be used to quickly check something, if needed..."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## More full `%%ocaml` cells"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T02:55:00.128028Z",
     "start_time": "2021-02-23T02:54:59.757972Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "List of size 300000 had sum = 8999955009050000.\n",
      "List of size 300001 had sum = 9000045009050030.\n",
      "List of size 300002 had sum = 9000135009650061.\n",
      "List of size 300003 had sum = 9000225010850095.\n",
      "List of size 300004 had sum = 9000315012650134.\n",
      "List of size 300005 had sum = 9000405015050180.\n",
      "List of size 300006 had sum = 9000495018050235.\n",
      "List of size 300007 had sum = 9000585021650301.\n",
      "List of size 300008 had sum = 9000675025850380.\n",
      "List of size 300009 had sum = 9000765030650474.\n",
      "List of size 300010 had sum = 9000855036050585."
     ]
    }
   ],
   "source": [
    "%%ocaml\n",
    "let sum : (int list -> int) = List.fold_left (+) 0 in\n",
    "let a_list (n:int) : int list = Array.to_list (Array.init n (fun i -> i*i+30)) in\n",
    "for n = 300000 to 300010 do\n",
    "    Format.printf \"\\nList of size %2.i had sum = %4.i.%!\" n (sum (a_list n));\n",
    "done;;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "As I was saying, using `%%script ocaml` allows to quickly check things, like for instance the interface of a module!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T02:50:05.928100Z",
     "start_time": "2021-02-23T02:50:05.853498Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "        OCaml version 4.05.0\n",
      "\n",
      "Findlib has been successfully loaded. Additional directives:\n",
      "  #require \"package\";;      to load a package\n",
      "  #list;;                   to list the available packages\n",
      "  #camlp4o;;                to load camlp4 (standard syntax)\n",
      "  #camlp4r;;                to load camlp4 (revised syntax)\n",
      "  #predicates \"p,q,...\";;   to set these predicates\n",
      "  Topfind.reset();;         to force that packages will be reloaded\n",
      "  #thread;;                 to enable threads\n",
      "\n",
      "# module Array :\n",
      "  sig\n",
      "    external length : 'a array -> int = \"%array_length\"\n",
      "    external get : 'a array -> int -> 'a = \"%array_safe_get\"\n",
      "    external set : 'a array -> int -> 'a -> unit = \"%array_safe_set\"\n",
      "    external make : int -> 'a -> 'a array = \"caml_make_vect\"\n",
      "    external create : int -> 'a -> 'a array = \"caml_make_vect\"\n",
      "    external create_float : int -> float array = \"caml_make_float_vect\"\n",
      "    val make_float : int -> float array\n",
      "    val init : int -> (int -> 'a) -> 'a array\n",
      "    val make_matrix : int -> int -> 'a -> 'a array array\n",
      "    val create_matrix : int -> int -> 'a -> 'a array array\n",
      "    val append : 'a array -> 'a array -> 'a array\n",
      "    val concat : 'a array list -> 'a array\n",
      "    val sub : 'a array -> int -> int -> 'a array\n",
      "    val copy : 'a array -> 'a array\n",
      "    val fill : 'a array -> int -> int -> 'a -> unit\n",
      "    val blit : 'a array -> int -> 'a array -> int -> int -> unit\n",
      "    val to_list : 'a array -> 'a list\n",
      "    val of_list : 'a list -> 'a array\n",
      "    val iter : ('a -> unit) -> 'a array -> unit\n",
      "    val iteri : (int -> 'a -> unit) -> 'a array -> unit\n",
      "    val map : ('a -> 'b) -> 'a array -> 'b array\n",
      "    val mapi : (int -> 'a -> 'b) -> 'a array -> 'b array\n",
      "    val fold_left : ('a -> 'b -> 'a) -> 'a -> 'b array -> 'a\n",
      "    val fold_right : ('b -> 'a -> 'a) -> 'b array -> 'a -> 'a\n",
      "    val iter2 : ('a -> 'b -> unit) -> 'a array -> 'b array -> unit\n",
      "    val map2 : ('a -> 'b -> 'c) -> 'a array -> 'b array -> 'c array\n",
      "    val for_all : ('a -> bool) -> 'a array -> bool\n",
      "    val exists : ('a -> bool) -> 'a array -> bool\n",
      "    val mem : 'a -> 'a array -> bool\n",
      "    val memq : 'a -> 'a array -> bool\n",
      "    val sort : ('a -> 'a -> int) -> 'a array -> unit\n",
      "    val stable_sort : ('a -> 'a -> int) -> 'a array -> unit\n",
      "    val fast_sort : ('a -> 'a -> int) -> 'a array -> unit\n",
      "    external unsafe_get : 'a array -> int -> 'a = \"%array_unsafe_get\"\n",
      "    external unsafe_set : 'a array -> int -> 'a -> unit = \"%array_unsafe_set\"\n",
      "  end\n",
      "# \n"
     ]
    }
   ],
   "source": [
    "%%script ocaml\n",
    "#show Array;;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Using OCaml returned values from Python\n",
    "\n",
    "This package allows to use dynamically defined OCaml functions *from* Python, the same way it can be done for other languages lke Julia or R (see [this blog post](https://blog.jupyter.org/i-python-you-r-we-julia-baf064ca1fb6) if you never saw these possibilities, or [this one](https://matthiasbussonnier.com/posts/23-Cross-Language-Integration.html))."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "For instance:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T04:46:54.379207Z",
     "start_time": "2021-02-23T04:46:54.349908Z"
    },
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'bool'> True\n",
      "<class 'str'> OK ?\n",
      "<class 'int'> 2021\n",
      "<class 'float'> 2.99792458\n"
     ]
    }
   ],
   "source": [
    "b = %ocaml true\n",
    "print(type(b), b)\n",
    "\n",
    "s = %ocaml \"OK ?\"\n",
    "print(type(s), s)\n",
    "\n",
    "i = %ocaml 2021\n",
    "print(type(i), i)\n",
    "\n",
    "f = %ocaml 2.99792458\n",
    "print(type(f), f)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So booleans, strings, integers and floats get perfectly mapped from OCaml values to Python native values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T04:37:52.784857Z",
     "start_time": "2021-02-23T04:37:52.754395Z"
    },
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'list'> [(1, 3, 5)]\n",
      "<class 'list'> [2, 4, 6]\n",
      "<class 'tuple'> (23, 2, 2021)\n"
     ]
    }
   ],
   "source": [
    "l = %ocaml [1, 3, 5]\n",
    "print(type(l), l)\n",
    "\n",
    "a = %ocaml [|2; 4; 6|]\n",
    "print(type(a), a)\n",
    "\n",
    "t = %ocaml (23, 02, 2021)\n",
    "print(type(t), t)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So `'a list`, `'a array` and `'a * 'b * ..` heterogeneous tuples get perfectly mapped from OCaml values to Python native values!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "But it's not perfect, as for instance OCaml has a `char` type (similar to the one in C) but Python only has strings, so this'll fail:\n",
    "\n",
    "`ValueError: ocaml error (Failure\"unknown type char\")`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T04:37:57.025514Z",
     "start_time": "2021-02-23T04:37:56.847273Z"
    }
   },
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "ocaml error (Failure\"unknown type char\")",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-183-19c1c29bb9b1>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mget_ipython\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun_line_magic\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'ocaml'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"'C'\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py\u001b[0m in \u001b[0;36mrun_line_magic\u001b[0;34m(self, magic_name, line, _stack_depth)\u001b[0m\n\u001b[1;32m   2324\u001b[0m                 \u001b[0mkwargs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'local_ns'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msys\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getframe\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstack_depth\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mf_locals\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2325\u001b[0m             \u001b[0;32mwith\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbuiltin_trap\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2326\u001b[0;31m                 \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2327\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2328\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/ocaml/__init__.py\u001b[0m in \u001b[0;36mocaml\u001b[0;34m(line)\u001b[0m\n\u001b[1;32m     13\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mocaml\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mline\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     14\u001b[0m       \u001b[0;32mwith\u001b[0m \u001b[0msys_pipes\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 15\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mtoploop\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mline\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     16\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     17\u001b[0m     \u001b[0;32mdel\u001b[0m \u001b[0mocaml\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: ocaml error (Failure\"unknown type char\")"
     ]
    }
   ],
   "source": [
    "c = %ocaml 'C'\n",
    "print(type(c), c)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "And for functions:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T04:39:23.398954Z",
     "start_time": "2021-02-23T04:39:23.386947Z"
    }
   },
   "outputs": [],
   "source": [
    "sum_ocaml_1 = %ocaml let sum : (int list -> int) = List.fold_left (+) 0 in sum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T04:39:35.981393Z",
     "start_time": "2021-02-23T04:39:35.978005Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<built-in method anonymous_closure of PyCapsule object at 0x7ff259159120> <class 'builtin_function_or_method'>\n"
     ]
    }
   ],
   "source": [
    "print(sum_ocaml_1, type(sum_ocaml_1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T04:39:37.172737Z",
     "start_time": "2021-02-23T04:39:37.166763Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "15"
      ]
     },
     "execution_count": 189,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sum_ocaml_1 ([1, 2, 3, 4, 5])  # 15"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Or simply"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T02:57:09.743709Z",
     "start_time": "2021-02-23T02:57:09.731485Z"
    }
   },
   "outputs": [],
   "source": [
    "sum_ocaml_2 = %ocaml List.fold_left (+) 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T02:57:10.159585Z",
     "start_time": "2021-02-23T02:57:10.154765Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "15"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sum_ocaml_2 ([1, 2, 3, 4, 5])  # 15"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "What about user defined types?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T04:39:59.862267Z",
     "start_time": "2021-02-23T04:39:59.846290Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TODO"
     ]
    }
   ],
   "source": [
    "%%ocaml\n",
    "type state = TODO | DONE | Unknown of string;;\n",
    "\n",
    "let print_state (s:state) =\n",
    "    match s with\n",
    "    | TODO -> Format.printf \"TODO%!\"\n",
    "    | DONE -> Format.printf \"DONE%!\"\n",
    "    | Unknown status -> Format.printf \"%s%!\" status\n",
    ";;\n",
    "\n",
    "print_state TODO;;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "It fails:\n",
    "```\n",
    "SyntaxError: ocaml evaluation error on lines 1:11 to 1:15\n",
    "Error: \n",
    ">  1: let out = (type TODO | DONE);;\n",
    "Syntax error: operator expected.\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T04:40:28.067391Z",
     "start_time": "2021-02-23T04:40:28.057600Z"
    },
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "ename": "SyntaxError",
     "evalue": "ocaml evaluation error on lines 1:11 to 1:15\nError: \n>  1: let out = (type TODO | DONE);;\nSyntax error: operator expected.\n (<string>)",
     "output_type": "error",
     "traceback": [
      "Traceback \u001b[0;36m(most recent call last)\u001b[0m:\n",
      "  File \u001b[1;32m\"/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py\"\u001b[0m, line \u001b[1;32m3343\u001b[0m, in \u001b[1;35mrun_code\u001b[0m\n    exec(code_obj, self.user_global_ns, self.user_ns)\n",
      "  File \u001b[1;32m\"<ipython-input-191-92828381558a>\"\u001b[0m, line \u001b[1;32m1\u001b[0m, in \u001b[1;35m<module>\u001b[0m\n    t = get_ipython().run_line_magic('ocaml', 'type TODO\\xa0| DONE')\n",
      "  File \u001b[1;32m\"/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py\"\u001b[0m, line \u001b[1;32m2326\u001b[0m, in \u001b[1;35mrun_line_magic\u001b[0m\n    result = fn(*args, **kwargs)\n",
      "\u001b[0;36m  File \u001b[0;32m\"/usr/local/lib/python3.6/dist-packages/ocaml/__init__.py\"\u001b[0;36m, line \u001b[0;32m15\u001b[0;36m, in \u001b[0;35mocaml\u001b[0;36m\u001b[0m\n\u001b[0;31m    return toploop.get(line)\u001b[0m\n",
      "\u001b[0;36m  File \u001b[0;32m\"<string>\"\u001b[0;36m, line \u001b[0;32munknown\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m ocaml evaluation error on lines 1:11 to 1:15\nError: \n>  1: let out = (type TODO | DONE);;\nSyntax error: operator expected.\n\n"
     ]
    }
   ],
   "source": [
    "t = %ocaml type TODO | DONE"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Indeed the `%ocam` magic only works for *expression*, with no `;;`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## More datatypes conversions to Python?\n",
    "\n",
    "We can still explore:\n",
    "- references, `let x = ref 1`\n",
    "- polymorphic functions like `let smaller (x: 'a) (y: 'a) : true = x < y` \n",
    "- `'a option` type\n",
    "- functions with labels\n",
    "- records\n",
    "- polymorphic variants ?\n",
    "\n",
    "Fore reference, see <https://github.com/janestreet/ppx_python#conversions>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### References - fail"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T04:49:54.622648Z",
     "start_time": "2021-02-23T04:49:54.609397Z"
    }
   },
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "ocaml error (Failure\"unknown type ref\")",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-198-8acf58a91aa8>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mxref\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mget_ipython\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun_line_magic\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'ocaml'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'ref 1'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py\u001b[0m in \u001b[0;36mrun_line_magic\u001b[0;34m(self, magic_name, line, _stack_depth)\u001b[0m\n\u001b[1;32m   2324\u001b[0m                 \u001b[0mkwargs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'local_ns'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msys\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getframe\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstack_depth\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mf_locals\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2325\u001b[0m             \u001b[0;32mwith\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbuiltin_trap\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2326\u001b[0;31m                 \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2327\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2328\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/ocaml/__init__.py\u001b[0m in \u001b[0;36mocaml\u001b[0;34m(line)\u001b[0m\n\u001b[1;32m     13\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mocaml\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mline\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     14\u001b[0m       \u001b[0;32mwith\u001b[0m \u001b[0msys_pipes\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 15\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mtoploop\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mline\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     16\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     17\u001b[0m     \u001b[0;32mdel\u001b[0m \u001b[0mocaml\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: ocaml error (Failure\"unknown type ref\")"
     ]
    }
   ],
   "source": [
    "xref = %ocaml ref 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Polymorphic function - works!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 222,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T05:06:27.720251Z",
     "start_time": "2021-02-23T05:06:27.710053Z"
    },
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<built-in method anonymous_closure of PyCapsule object at 0x7ff259179f30> <class 'builtin_function_or_method'>\n"
     ]
    }
   ],
   "source": [
    "cons = %ocaml fun hd tl -> hd :: tl\n",
    "print(cons, type(cons))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T05:05:23.774460Z",
     "start_time": "2021-02-23T05:05:23.768470Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[10, 20, 30]"
      ]
     },
     "execution_count": 217,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cons(10)([20, 30])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 221,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T05:05:43.237011Z",
     "start_time": "2021-02-23T05:05:43.231596Z"
    },
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1.0, 2.0, 30]"
      ]
     },
     "execution_count": 221,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cons(1.0)([2.0, 30])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Woooo, somehow OCaml accepted a polymorphic list at some point?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T05:03:23.859310Z",
     "start_time": "2021-02-23T05:03:23.846990Z"
    },
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [],
   "source": [
    "head, tail = %ocaml List.hd, List.tl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T05:04:01.858568Z",
     "start_time": "2021-02-23T05:04:01.853220Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1, [2, 3, [1, 2, 3, [...]]])"
      ]
     },
     "execution_count": 211,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a_list = [1, 2, 3]\n",
    "a_list.append(a_list)\n",
    "head(a_list), tail(a_list)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Another example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T04:51:03.365262Z",
     "start_time": "2021-02-23T04:51:03.350071Z"
    },
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<built-in method anonymous_closure of PyCapsule object at 0x7ff25cf80a20>\n",
      "Help on built-in function anonymous_closure:\n",
      "\n",
      "anonymous_closure(...) method of builtins.PyCapsule instance\n",
      "    int -> int -> bool\n",
      "\n"
     ]
    }
   ],
   "source": [
    "smaller = %ocaml fun (x: int) (y: int) -> x < y\n",
    "print(smaller)\n",
    "help(smaller)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T04:51:11.290615Z",
     "start_time": "2021-02-23T04:51:11.279198Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<built-in method anonymous_closure of PyCapsule object at 0x7ff259179ea0>\n",
      "Help on built-in function anonymous_closure:\n",
      "\n",
      "anonymous_closure(...) method of builtins.PyCapsule instance\n",
      "    pyobject -> pyobject -> bool\n",
      "\n"
     ]
    }
   ],
   "source": [
    "smaller_poly = %ocaml fun (x: 'a) (y: 'a) -> x < y\n",
    "print(smaller_poly)\n",
    "help(smaller_poly)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Option type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 204,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T04:51:55.932941Z",
     "start_time": "2021-02-23T04:51:55.925247Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "None <class 'NoneType'>\n"
     ]
    }
   ],
   "source": [
    "none = %ocaml None\n",
    "print(none, type(none))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 205,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T04:52:18.715203Z",
     "start_time": "2021-02-23T04:52:18.702963Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "42 <class 'int'>\n"
     ]
    }
   ],
   "source": [
    "some_int = %ocaml Some 42\n",
    "print(some_int, type(some_int))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 206,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T04:52:42.025824Z",
     "start_time": "2021-02-23T04:52:42.015356Z"
    },
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "None <class 'NoneType'>\n"
     ]
    }
   ],
   "source": [
    "# instinguishable from None, so that's weird!\n",
    "some_None = %ocaml Some None\n",
    "print(some_None, type(some_None))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that this limitation was explained:\n",
    "\n",
    "> *Note that this makes the two OCaml values `[Some None]` and `[None]` indistinguishable on the Python side as both are represented using `None`.*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Functions with labels - labels get erased"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 227,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T05:07:43.917288Z",
     "start_time": "2021-02-23T05:07:43.906356Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<built-in method anonymous_closure of PyCapsule object at 0x7ff259179f00> <class 'builtin_function_or_method'>\n",
      "Help on built-in function anonymous_closure:\n",
      "\n",
      "anonymous_closure(...) method of builtins.PyCapsule instance\n",
      "    pyobject -> pyobject -> pyobject -> pyobject -> (pyobject) list -> pyobject\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# val fold_left : f:('a -> 'b -> 'a) -> init:'a -> 'b list -> 'a\n",
    "fold_left = %ocaml ListLabels.fold_left\n",
    "\n",
    "print(fold_left, type(fold_left))\n",
    "help(fold_left:)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T05:08:26.606211Z",
     "start_time": "2021-02-23T05:08:26.600049Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "15"
      ]
     },
     "execution_count": 230,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fold_left(lambda x: lambda y: x + y)(0)([1, 2, 3, 4, 5])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Record - fail"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 194,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T04:48:19.452387Z",
     "start_time": "2021-02-23T04:48:19.438480Z"
    },
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [],
   "source": [
    "%%ocaml\n",
    "type ratio = {num: int; denom: int};;\n",
    "let add_ratio r1 r2 =\n",
    "   {num = r1.num * r2.denom + r2.num * r1.denom;\n",
    "    denom = r1.denom * r2.denom};;\n",
    "add_ratio {num=1; denom=3} {num=2; denom=5};;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 197,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T04:49:06.412414Z",
     "start_time": "2021-02-23T04:49:06.396396Z"
    },
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "ocaml error (Failure\"unknown type ratio\")",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-197-077c7ab12521>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mget_ipython\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun_line_magic\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'ocaml'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'{num=1; denom=3}'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py\u001b[0m in \u001b[0;36mrun_line_magic\u001b[0;34m(self, magic_name, line, _stack_depth)\u001b[0m\n\u001b[1;32m   2324\u001b[0m                 \u001b[0mkwargs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'local_ns'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msys\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getframe\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstack_depth\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mf_locals\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2325\u001b[0m             \u001b[0;32mwith\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbuiltin_trap\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2326\u001b[0;31m                 \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2327\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2328\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/ocaml/__init__.py\u001b[0m in \u001b[0;36mocaml\u001b[0;34m(line)\u001b[0m\n\u001b[1;32m     13\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mocaml\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mline\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     14\u001b[0m       \u001b[0;32mwith\u001b[0m \u001b[0msys_pipes\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 15\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mtoploop\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mline\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     16\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     17\u001b[0m     \u001b[0;32mdel\u001b[0m \u001b[0mocaml\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: ocaml error (Failure\"unknown type ratio\")"
     ]
    }
   ],
   "source": [
    "%ocaml {num=1; denom=3}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Of course it fails!\n",
    "\n",
    "But it could be translated to Python dictionaries."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Exceptions - fail"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 207,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T05:02:32.025112Z",
     "start_time": "2021-02-23T05:02:32.018161Z"
    }
   },
   "outputs": [
    {
     "ename": "SyntaxError",
     "evalue": "ocaml evaluation error on lines 1:11 to 1:20\nError: \n>  1: let out = (exception Empty_list);;\nSyntax error: operator expected.\n (<string>)",
     "output_type": "error",
     "traceback": [
      "Traceback \u001b[0;36m(most recent call last)\u001b[0m:\n",
      "  File \u001b[1;32m\"/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py\"\u001b[0m, line \u001b[1;32m3343\u001b[0m, in \u001b[1;35mrun_code\u001b[0m\n    exec(code_obj, self.user_global_ns, self.user_ns)\n",
      "  File \u001b[1;32m\"<ipython-input-207-709df63f312a>\"\u001b[0m, line \u001b[1;32m1\u001b[0m, in \u001b[1;35m<module>\u001b[0m\n    exc = get_ipython().run_line_magic('ocaml', 'exception Empty_list')\n",
      "  File \u001b[1;32m\"/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py\"\u001b[0m, line \u001b[1;32m2326\u001b[0m, in \u001b[1;35mrun_line_magic\u001b[0m\n    result = fn(*args, **kwargs)\n",
      "\u001b[0;36m  File \u001b[0;32m\"/usr/local/lib/python3.6/dist-packages/ocaml/__init__.py\"\u001b[0;36m, line \u001b[0;32m15\u001b[0;36m, in \u001b[0;35mocaml\u001b[0;36m\u001b[0m\n\u001b[0;31m    return toploop.get(line)\u001b[0m\n",
      "\u001b[0;36m  File \u001b[0;32m\"<string>\"\u001b[0;36m, line \u001b[0;32munknown\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m ocaml evaluation error on lines 1:11 to 1:20\nError: \n>  1: let out = (exception Empty_list);;\nSyntax error: operator expected.\n\n"
     ]
    }
   ],
   "source": [
    "exc = %ocaml exception Empty_list"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T04:48:19.452387Z",
     "start_time": "2021-02-23T04:48:19.438480Z"
    },
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Polymorphic variants - fail\n",
    "See [documentation](http://caml.inria.fr/pub/docs/manual-ocaml/expr.html#sss:expr-polyvars)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 232,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T05:11:54.929252Z",
     "start_time": "2021-02-23T05:11:54.914267Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0"
     ]
    }
   ],
   "source": [
    "%%ocaml\n",
    "Format.printf \"%i%!\" (let value `float = 0 in value `float);;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 236,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T05:12:33.392009Z",
     "start_time": "2021-02-23T05:12:33.381232Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 <class 'int'>\n"
     ]
    }
   ],
   "source": [
    "zero = %ocaml let value `float = 0 in value `float\n",
    "\n",
    "print(zero, type(zero))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 237,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T05:12:34.418936Z",
     "start_time": "2021-02-23T05:12:34.410681Z"
    }
   },
   "outputs": [
    {
     "ename": "SyntaxError",
     "evalue": "unsupported type Tvariant (<string>)",
     "output_type": "error",
     "traceback": [
      "Traceback \u001b[0;36m(most recent call last)\u001b[0m:\n",
      "  File \u001b[1;32m\"/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py\"\u001b[0m, line \u001b[1;32m3343\u001b[0m, in \u001b[1;35mrun_code\u001b[0m\n    exec(code_obj, self.user_global_ns, self.user_ns)\n",
      "  File \u001b[1;32m\"<ipython-input-237-35ef86792a45>\"\u001b[0m, line \u001b[1;32m1\u001b[0m, in \u001b[1;35m<module>\u001b[0m\n    variant = get_ipython().run_line_magic('ocaml', '`float')\n",
      "  File \u001b[1;32m\"/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py\"\u001b[0m, line \u001b[1;32m2326\u001b[0m, in \u001b[1;35mrun_line_magic\u001b[0m\n    result = fn(*args, **kwargs)\n",
      "\u001b[0;36m  File \u001b[0;32m\"/usr/local/lib/python3.6/dist-packages/ocaml/__init__.py\"\u001b[0;36m, line \u001b[0;32m15\u001b[0;36m, in \u001b[0;35mocaml\u001b[0;36m\u001b[0m\n\u001b[0;31m    return toploop.get(line)\u001b[0m\n",
      "\u001b[0;36m  File \u001b[0;32m\"<string>\"\u001b[0;36m, line \u001b[0;32munknown\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m unsupported type Tvariant\n"
     ]
    }
   ],
   "source": [
    "variant = %ocaml `float\n",
    "\n",
    "print(variant, type(variant))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Optional arguments - fail\n",
    "\n",
    "It would be difficult to implement them correctly along side the (awesome) partial application closure feature..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 240,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T05:14:56.021859Z",
     "start_time": "2021-02-23T05:14:56.004570Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "42\n",
      "42"
     ]
    }
   ],
   "source": [
    "%%ocaml\n",
    "let bump ?(step = 1) x = x + step;;\n",
    "Format.printf \"\\n%i%!\" (bump 41);;\n",
    "Format.printf \"\\n%i%!\" (bump ~step:12 30);;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 241,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T05:15:02.690852Z",
     "start_time": "2021-02-23T05:15:02.676136Z"
    }
   },
   "outputs": [
    {
     "ename": "SyntaxError",
     "evalue": "optional arguments are not supported (<string>)",
     "output_type": "error",
     "traceback": [
      "Traceback \u001b[0;36m(most recent call last)\u001b[0m:\n",
      "  File \u001b[1;32m\"/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py\"\u001b[0m, line \u001b[1;32m3343\u001b[0m, in \u001b[1;35mrun_code\u001b[0m\n    exec(code_obj, self.user_global_ns, self.user_ns)\n",
      "  File \u001b[1;32m\"<ipython-input-241-9255dc0fa695>\"\u001b[0m, line \u001b[1;32m1\u001b[0m, in \u001b[1;35m<module>\u001b[0m\n    bump = get_ipython().run_line_magic('ocaml', 'let bump ?(step = 1) x = x + step in bump')\n",
      "  File \u001b[1;32m\"/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py\"\u001b[0m, line \u001b[1;32m2326\u001b[0m, in \u001b[1;35mrun_line_magic\u001b[0m\n    result = fn(*args, **kwargs)\n",
      "\u001b[0;36m  File \u001b[0;32m\"/usr/local/lib/python3.6/dist-packages/ocaml/__init__.py\"\u001b[0;36m, line \u001b[0;32m15\u001b[0;36m, in \u001b[0;35mocaml\u001b[0;36m\u001b[0m\n\u001b[0;31m    return toploop.get(line)\u001b[0m\n",
      "\u001b[0;36m  File \u001b[0;32m\"<string>\"\u001b[0;36m, line \u001b[0;32munknown\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m optional arguments are not supported\n"
     ]
    }
   ],
   "source": [
    "bump = %ocaml let bump ?(step = 1) x = x + step in bump"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Recursive list?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T05:25:31.190793Z",
     "start_time": "2021-02-23T05:25:31.130527Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 -> 1 -> 0 -> 1 ..."
     ]
    }
   ],
   "source": [
    "%%ocaml\n",
    "let rec list1 = 0 :: list2\n",
    "and list2 = 1 :: list1\n",
    "in\n",
    "Format.printf \"%i -> %i -> %i -> %i ...%!\" (List.hd list1) (List.hd list2) (List.hd (List.tl list2)) (List.hd (List.tl list1));;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T05:25:24.355622Z",
     "start_time": "2021-02-23T05:25:24.351202Z"
    }
   },
   "outputs": [],
   "source": [
    "# don't run\n",
    "if False:\n",
    "    list1, list2 = %ocaml let rec list1 = 0 :: list2 and list2 = 1 :: list1 in (list1, list2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It fails, but takes 100% CPU and freezes. But in Python we can do it:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T05:25:06.845740Z",
     "start_time": "2021-02-23T05:25:06.841831Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0, [1, [...]]]\n",
      "[1, [0, [...]]]\n"
     ]
    }
   ],
   "source": [
    "list1 = [0]\n",
    "list2 = [1]\n",
    "list1.append(list2)\n",
    "list2.append(list1)\n",
    "print(list1)\n",
    "print(list2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### From standard library"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "What about Sets, mapped to `set`?\n",
    "What about HashTbl, mapped to `dict`?\n",
    "And Stack, Queue, etc?\n",
    "\n",
    "TODO: left as an exercise for the reader."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Map - fail"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T05:29:45.020981Z",
     "start_time": "2021-02-23T05:29:44.996332Z"
    }
   },
   "outputs": [],
   "source": [
    "%%ocaml\n",
    "\n",
    "module IntPairs = struct\n",
    "    type t = int * int\n",
    "    let compare (x0,y0) (x1,y1) =\n",
    "        match Stdlib.compare x0 x1 with\n",
    "        0 -> Stdlib.compare y0 y1\n",
    "        | c -> c\n",
    "end\n",
    "\n",
    "module PairsMap = Map.Make(IntPairs)\n",
    "\n",
    "let m = PairsMap.(empty |> add (0,1) \"hello\" |> add (1,0) \"world\")\n",
    "\n",
    "(* not an expression, not usable in %ocaml magic *)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Stack (or any module using a custom type) - fail"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T05:30:11.976057Z",
     "start_time": "2021-02-23T05:30:11.956014Z"
    },
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "ocaml error (Failure\"unknown type t\")",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-10-bbd04f52cfc6>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mstack\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mget_ipython\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun_line_magic\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'ocaml'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'Stack.create()'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py\u001b[0m in \u001b[0;36mrun_line_magic\u001b[0;34m(self, magic_name, line, _stack_depth)\u001b[0m\n\u001b[1;32m   2324\u001b[0m                 \u001b[0mkwargs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'local_ns'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msys\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getframe\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstack_depth\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mf_locals\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2325\u001b[0m             \u001b[0;32mwith\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbuiltin_trap\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2326\u001b[0;31m                 \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2327\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2328\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/ocaml/__init__.py\u001b[0m in \u001b[0;36mocaml\u001b[0;34m(line)\u001b[0m\n\u001b[1;32m     13\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mocaml\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mline\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     14\u001b[0m       \u001b[0;32mwith\u001b[0m \u001b[0msys_pipes\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 15\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mtoploop\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mline\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     16\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     17\u001b[0m     \u001b[0;32mdel\u001b[0m \u001b[0mocaml\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: ocaml error (Failure\"unknown type t\")"
     ]
    }
   ],
   "source": [
    "stack = %ocaml Stack.create()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## 😮 Curryed functions!\n",
    "\n",
    "Imagine you define this function in math:\n",
    "$p : (x,y,z) \\mapsto x * y * z$, on $\\mathbb{N}^3 \\to \\mathbb{N}$.\n",
    "Then the Curryed form states that it is equivalent to\n",
    "$p' : x \\mapsto y \\mapsto z \\mapsto x * y * z$, informally defined on $\\mathbb{N} \\to \\mathbb{N} \\to \\mathbb{N} \\to \\mathbb{N}$.\n",
    "\n",
    "So for instance if $x=1$ and $y=2$, $p'(x)(y)$ is $z \\mapsto 1 * 2 * z$, which is also $z \\mapsto p(1, 2, z)$.\n",
    "\n",
    "In Python function, that would be this function:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T03:05:18.820039Z",
     "start_time": "2021-02-23T03:05:18.813277Z"
    }
   },
   "outputs": [],
   "source": [
    "def product3values(x, y, z):\n",
    "    return x * y * z"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "But you can't directly use it for partial application:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T03:08:47.843357Z",
     "start_time": "2021-02-23T03:08:47.828199Z"
    }
   },
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "product3values() missing 1 required positional argument: 'z'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-80-3ba473df199e>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0mx\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0my\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mpartial_product\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mproduct3values\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      4\u001b[0m \u001b[0mz\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m10\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"With x = {x}, y = {y}, and {partial_product} applied to z = {z}, we got {partial_product(z)}\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mTypeError\u001b[0m: product3values() missing 1 required positional argument: 'z'"
     ]
    }
   ],
   "source": [
    "x = 1\n",
    "y = 2\n",
    "partial_product = product3values(x, y)\n",
    "z = 10\n",
    "print(f\"With x = {x}, y = {y}, and {partial_product} applied to z = {z}, we got {partial_product(z)}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "With the Python standard library, it's possible to use [`functools.partial`](https://docs.python.org/3/library/functools.html#functools.partial) to obtain partially evaluated functions, which can be viewed as a limited support of Curryed function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T03:08:57.230492Z",
     "start_time": "2021-02-23T03:08:57.222604Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "With x = 1, y = 2, and functools.partial(<function product3values at 0x7ff25cda0c80>, 1, 2) applied to z = 10, we got 20\n"
     ]
    }
   ],
   "source": [
    "import functools\n",
    "\n",
    "partial_product = functools.partial(product3values, 1, 2)\n",
    "\n",
    "z = 10\n",
    "print(f\"With x = {x}, y = {y}, and {partial_product} applied to z = {z}, we got {partial_product(z)}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "But in OCaml, the conventions is to directly write functions in Curry form, rather than tuple form:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T03:11:47.257806Z",
     "start_time": "2021-02-23T03:11:47.234612Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "With x = 1, y = 2, and partial_product applied to z = 10, we got 20."
     ]
    }
   ],
   "source": [
    "%%ocaml\n",
    "(* this is advised *)\n",
    "let product_curry (x:int) (y:int) (z:int) : int = x * y * z in\n",
    "let x = 1 and y = 2 in\n",
    "let partial_product = product_curry x y in\n",
    "let z = 10 in\n",
    "Format.printf \"With x = %i, y = %i, and partial_product applied to z = %i, we got %i.\" x y z (partial_product z);;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Indeed, in most situations, the tuple form is just not \"OCaml\"esque, and tedious to use, and does not allow partial application!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T03:12:48.546640Z",
     "start_time": "2021-02-23T03:12:48.529446Z"
    }
   },
   "outputs": [
    {
     "ename": "SyntaxError",
     "evalue": "ocaml evaluation error on lines 7:165 to 7:178\nError: \n   2: let product_curry (xyz : (int * int * int)) : int =\n   3:     let x, y, z = xyz in\n   4:     x * y * z\n   5: in\n   6: let x = 1 and y = 2 in\n>  7: let partial_product = product_curry x y in\n   8: let z = 10 in\n   9: Format.printf \"With x = %i, y = %i, and partial_product applied to z = %i, we got %i.\" x y z (partial_product z);;\nThis function has type int * int * int -> int\nIt is applied to too many arguments; maybe you forgot a `;'.\n (<string>)",
     "output_type": "error",
     "traceback": [
      "Traceback \u001b[0;36m(most recent call last)\u001b[0m:\n",
      "  File \u001b[1;32m\"/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py\"\u001b[0m, line \u001b[1;32m3343\u001b[0m, in \u001b[1;35mrun_code\u001b[0m\n    exec(code_obj, self.user_global_ns, self.user_ns)\n",
      "  File \u001b[1;32m\"<ipython-input-89-a59ab8443eec>\"\u001b[0m, line \u001b[1;32m1\u001b[0m, in \u001b[1;35m<module>\u001b[0m\n    get_ipython().run_cell_magic('ocaml', '', '(* this is NOT advised *)\\nlet product_curry (xyz : (int * int * int)) : int =\\n    let x, y, z = xyz in\\n    x * y * z\\nin\\nlet x = 1 and y = 2 in\\nlet partial_product = product_curry x y in\\nlet z = 10 in\\nFormat.printf \"With x = %i, y = %i, and partial_product applied to z = %i, we got %i.\" x y z (partial_product z);;\\n')\n",
      "  File \u001b[1;32m\"/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py\"\u001b[0m, line \u001b[1;32m2371\u001b[0m, in \u001b[1;35mrun_cell_magic\u001b[0m\n    result = fn(*args, **kwargs)\n",
      "\u001b[0;36m  File \u001b[0;32m\"/usr/local/lib/python3.6/dist-packages/ocaml/__init__.py\"\u001b[0;36m, line \u001b[0;32m30\u001b[0;36m, in \u001b[0;35mocaml\u001b[0;36m\u001b[0m\n\u001b[0;31m    return toploop.eval(cell)\u001b[0m\n",
      "\u001b[0;36m  File \u001b[0;32m\"<string>\"\u001b[0;36m, line \u001b[0;32munknown\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m ocaml evaluation error on lines 7:165 to 7:178\nError: \n   2: let product_curry (xyz : (int * int * int)) : int =\n   3:     let x, y, z = xyz in\n   4:     x * y * z\n   5: in\n   6: let x = 1 and y = 2 in\n>  7: let partial_product = product_curry x y in\n   8: let z = 10 in\n   9: Format.printf \"With x = %i, y = %i, and partial_product applied to z = %i, we got %i.\" x y z (partial_product z);;\nThis function has type int * int * int -> int\nIt is applied to too many arguments; maybe you forgot a `;'.\n\n"
     ]
    }
   ],
   "source": [
    "%%ocaml\n",
    "(* this is NOT advised *)\n",
    "let product_curry (xyz : (int * int * int)) : int =\n",
    "    let x, y, z = xyz in\n",
    "    x * y * z\n",
    "in\n",
    "let x = 1 and y = 2 in\n",
    "let partial_product = product_curry x y in\n",
    "let z = 10 in\n",
    "Format.printf \"With x = %i, y = %i, and partial_product applied to z = %i, we got %i.\" x y z (partial_product z);;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Well that was some long explanation, but now comes the magic!\n",
    "If you use `%ocaml` to get in Python the values returned from OCaml, then functions are Curryed function!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T03:15:05.109399Z",
     "start_time": "2021-02-23T03:15:05.091744Z"
    }
   },
   "outputs": [],
   "source": [
    "product_curry = %ocaml let product_curry (x:int) (y:int) (z:int) : int = x * y * z in product_curry"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The only information we have on this function is the OCaml signature, in its docstring:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T03:15:14.737648Z",
     "start_time": "2021-02-23T03:15:14.728294Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on built-in function anonymous_closure:\n",
      "\n",
      "anonymous_closure(...) method of builtins.PyCapsule instance\n",
      "    int -> int -> int -> int\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(product_curry)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "So we *can't* use it as a classical 3-arguments Python function:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T03:15:40.922855Z",
     "start_time": "2021-02-23T03:15:40.910950Z"
    }
   },
   "outputs": [
    {
     "ename": "SyntaxError",
     "evalue": "(Failure \"expected int, got Tuple\") (<string>)",
     "output_type": "error",
     "traceback": [
      "Traceback \u001b[0;36m(most recent call last)\u001b[0m:\n",
      "  File \u001b[1;32m\"/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py\"\u001b[0m, line \u001b[1;32m3343\u001b[0m, in \u001b[1;35mrun_code\u001b[0m\n    exec(code_obj, self.user_global_ns, self.user_ns)\n",
      "\u001b[0;36m  File \u001b[0;32m\"<ipython-input-93-30a4c1f01ec3>\"\u001b[0;36m, line \u001b[0;32m1\u001b[0;36m, in \u001b[0;35m<module>\u001b[0;36m\u001b[0m\n\u001b[0;31m    product_curry(1, 2, 10)\u001b[0m\n",
      "\u001b[0;36m  File \u001b[0;32m\"<string>\"\u001b[0;36m, line \u001b[0;32munknown\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m (Failure \"expected int, got Tuple\")\n"
     ]
    }
   ],
   "source": [
    "product_curry(1, 2, 10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "But we CAN use it as a Curryed function!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T03:16:16.707552Z",
     "start_time": "2021-02-23T03:16:16.695731Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "20"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "product_curry(1)(2)(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Which is awesome because now we can do partial evaluation as in OCaml!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T03:17:30.462258Z",
     "start_time": "2021-02-23T03:17:30.458707Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "20"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "partial_product_1 = product_curry(1)\n",
    "partial_product_1(2)(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T03:18:12.373647Z",
     "start_time": "2021-02-23T03:18:12.367586Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(20, 20)"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "partial_product_2 = product_curry(1)(2)\n",
    "partial_product_2_too = partial_product_1(2)\n",
    "partial_product_2(10), partial_product_2_too(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "What's very cool is that these functions docstrings keep showing the signature of the underlying OCaml function, even if they were obtained from pure Python cells!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T03:19:13.969278Z",
     "start_time": "2021-02-23T03:19:13.962534Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on built-in function anonymous_closure:\n",
      "\n",
      "anonymous_closure(...) method of builtins.PyCapsule instance\n",
      "    int -> int -> int\n",
      "\n",
      "Help on built-in function anonymous_closure:\n",
      "\n",
      "anonymous_closure(...) method of builtins.PyCapsule instance\n",
      "    int -> int\n",
      "\n",
      "Help on built-in function anonymous_closure:\n",
      "\n",
      "anonymous_closure(...) method of builtins.PyCapsule instance\n",
      "    int -> int\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(partial_product_1)\n",
    "help(partial_product_2)\n",
    "help(partial_product_2_too)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "That's it for this feature, it's cool and interesting."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Some questions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Can we share variables between two consecutive full cells?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the `%ocaml` mode, nothing can be shared from the OCaml side, as it's just an expression, let's check:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T02:57:54.562848Z",
     "start_time": "2021-02-23T02:57:54.548909Z"
    },
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%ocaml let x = 1 in x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T02:58:00.063165Z",
     "start_time": "2021-02-23T02:58:00.048441Z"
    }
   },
   "outputs": [
    {
     "ename": "SyntaxError",
     "evalue": "ocaml evaluation error on lines 1:11 to 1:12\nError: \n>  1: let out = (x);;\nUnbound value x\n (<string>)",
     "output_type": "error",
     "traceback": [
      "Traceback \u001b[0;36m(most recent call last)\u001b[0m:\n",
      "  File \u001b[1;32m\"/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py\"\u001b[0m, line \u001b[1;32m3343\u001b[0m, in \u001b[1;35mrun_code\u001b[0m\n    exec(code_obj, self.user_global_ns, self.user_ns)\n",
      "  File \u001b[1;32m\"<ipython-input-67-269a4d148dbe>\"\u001b[0m, line \u001b[1;32m1\u001b[0m, in \u001b[1;35m<module>\u001b[0m\n    get_ipython().run_line_magic('ocaml', 'x')\n",
      "  File \u001b[1;32m\"/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py\"\u001b[0m, line \u001b[1;32m2326\u001b[0m, in \u001b[1;35mrun_line_magic\u001b[0m\n    result = fn(*args, **kwargs)\n",
      "\u001b[0;36m  File \u001b[0;32m\"/usr/local/lib/python3.6/dist-packages/ocaml/__init__.py\"\u001b[0;36m, line \u001b[0;32m15\u001b[0;36m, in \u001b[0;35mocaml\u001b[0;36m\u001b[0m\n\u001b[0;31m    return toploop.get(line)\u001b[0m\n",
      "\u001b[0;36m  File \u001b[0;32m\"<string>\"\u001b[0;36m, line \u001b[0;32munknown\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m ocaml evaluation error on lines 1:11 to 1:12\nError: \n>  1: let out = (x);;\nUnbound value x\n\n"
     ]
    }
   ],
   "source": [
    "%ocaml x"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "But what about full cell mode, `%%ocaml`?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T03:01:35.534980Z",
     "start_time": "2021-02-23T03:01:35.514162Z"
    },
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "... « The answer to life, the universe, and everything is 42 »"
     ]
    }
   ],
   "source": [
    "%%ocaml\n",
    "(* See https://en.wikipedia.org/wiki/42_(number) *)\n",
    "let answer_to_life = 42 in\n",
    "Format.printf \"\\n... « The answer to life, the universe, and everything is %i »%!\" answer_to_life;;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T03:01:43.128606Z",
     "start_time": "2021-02-23T03:01:43.118219Z"
    }
   },
   "outputs": [
    {
     "ename": "SyntaxError",
     "evalue": "ocaml evaluation error on lines 1:85 to 1:99\nError: \n>  1: Format.printf \"\\n... « The answer to life, the universe, and everything is %i »%!\" answer_to_life;;\nUnbound value answer_to_life\n (<string>)",
     "output_type": "error",
     "traceback": [
      "Traceback \u001b[0;36m(most recent call last)\u001b[0m:\n",
      "  File \u001b[1;32m\"/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py\"\u001b[0m, line \u001b[1;32m3343\u001b[0m, in \u001b[1;35mrun_code\u001b[0m\n    exec(code_obj, self.user_global_ns, self.user_ns)\n",
      "  File \u001b[1;32m\"<ipython-input-71-0d2d3c7f5c67>\"\u001b[0m, line \u001b[1;32m1\u001b[0m, in \u001b[1;35m<module>\u001b[0m\n    get_ipython().run_cell_magic('ocaml', '', 'Format.printf \"\\\\n... « The answer to life, the universe, and everything is %i »%!\" answer_to_life;;\\n')\n",
      "  File \u001b[1;32m\"/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py\"\u001b[0m, line \u001b[1;32m2371\u001b[0m, in \u001b[1;35mrun_cell_magic\u001b[0m\n    result = fn(*args, **kwargs)\n",
      "\u001b[0;36m  File \u001b[0;32m\"/usr/local/lib/python3.6/dist-packages/ocaml/__init__.py\"\u001b[0;36m, line \u001b[0;32m30\u001b[0;36m, in \u001b[0;35mocaml\u001b[0;36m\u001b[0m\n\u001b[0;31m    return toploop.eval(cell)\u001b[0m\n",
      "\u001b[0;36m  File \u001b[0;32m\"<string>\"\u001b[0;36m, line \u001b[0;32munknown\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m ocaml evaluation error on lines 1:85 to 1:99\nError: \n>  1: Format.printf \"\\n... « The answer to life, the universe, and everything is %i »%!\" answer_to_life;;\nUnbound value answer_to_life\n\n"
     ]
    }
   ],
   "source": [
    "%%ocaml\n",
    "Format.printf \"\\n... « The answer to life, the universe, and everything is %i »%!\" answer_to_life;;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "==> Answer: no, we cannot share any memory between two consecutive cells.\n",
    "Well, too bad, but it's not so important."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Is there any documentation of the magic or commands?\n",
    "\n",
    "No."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T03:02:14.011940Z",
     "start_time": "2021-02-23T03:02:14.001224Z"
    }
   },
   "outputs": [],
   "source": [
    "?%ocaml"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "    Docstring: <no docstring>\n",
    "    File:      /usr/local/lib/python3.6/dist-packages/ocaml/__init__.py"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### More remarks"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "source": [
    "Note that there blog post says that using the `opttoploop` could be used to compile the OCaml to a faster version (native code), but do not document about this.\n",
    "> Note that with the toploop module, the OCaml code is evaluated by compiling to bytecode which is not optimal, switching to the opttoploop module that generates native code should make it even faster."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T04:19:44.076307Z",
     "start_time": "2021-02-23T04:19:44.071278Z"
    },
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 164,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"opttoploop\" in dir(ocaml)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Also note that the `ocaml` module is shipped with an example of a tiny module which was written in OCaml and compiled, being made available to Python directly:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T04:21:08.068033Z",
     "start_time": "2021-02-23T04:21:08.061946Z"
    },
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<function PyCapsule.anonymous_closure>"
      ]
     },
     "execution_count": 167,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# it doesn't have a docstring, don't try help(<...>) or <...>?\n",
    "ocaml.ocaml.example_module.approx_pi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T04:21:08.795717Z",
     "start_time": "2021-02-23T04:21:08.512545Z"
    },
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.1415916986605086"
      ]
     },
     "execution_count": 168,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ocaml.ocaml.example_module.approx_pi(1000000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Final note: a tiny benchmark\n",
    "\n",
    "Let's compare the speed of naive Python and naive OCaml sum of a list/array of floats, for various input size."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T04:23:14.601650Z",
     "start_time": "2021-02-23T04:23:14.596499Z"
    }
   },
   "outputs": [],
   "source": [
    "import ocaml\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T04:23:15.186072Z",
     "start_time": "2021-02-23T04:23:15.176595Z"
    }
   },
   "outputs": [],
   "source": [
    "python_sum = sum\n",
    "ocaml_sum = %ocaml List.fold_left (+.) 0.\n",
    "numpy_sum = np.sum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T04:23:15.678415Z",
     "start_time": "2021-02-23T04:23:15.672664Z"
    },
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "15.0\n",
      "15.0\n",
      "15.0\n"
     ]
    }
   ],
   "source": [
    "print(python_sum( [1.0, 2.0, 3.0, 4.0, 5.0] ))\n",
    "print(ocaml_sum(  [1.0, 2.0, 3.0, 4.0, 5.0] ))\n",
    "print(numpy_sum(  [1.0, 2.0, 3.0, 4.0, 5.0] ))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Now for a \"large\" array, let's use IPython `%timeit` magic for very quick benchmarking.\n",
    "\n",
    "> Science is about making hypotheses, designing experiments to check them, and conclude.\n",
    "> My hypothesis here is that the OCaml version will be between 10 to 50 slower than the Python one (and Numpy version is 50-200 faster than Python)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T03:36:55.712295Z",
     "start_time": "2021-02-23T03:36:15.618508Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Comparing time of python_sum and ocaml_sun :\n",
      "\n",
      "- For size = 10000000:\n",
      "\tFor python sum: 677 ms ± 12.9 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
      "\tFor OCaml sum: 2.92 s ± 441 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n",
      "\tFor numpy.sum: 632 ms ± 4.41 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
     ]
    }
   ],
   "source": [
    "sizes = [100, 1000, 10000, 100000, 1000000, 10000000]\n",
    "print(f\"Comparing time of python_sum and ocaml_sun :\")\n",
    "for size in sizes:\n",
    "    print(f\"\\n- For size = {size}:\")\n",
    "    X = list(np.random.randn(size))\n",
    "    \n",
    "    print(\"\\tFor python sum: \", end='')\n",
    "    %timeit python_sum(X)\n",
    "    \n",
    "    assert np.isclose(python_sum(X), ocaml_sum(X))\n",
    "    print(\"\\tFor OCaml sum: \", end='')\n",
    "    %timeit ocaml_sum(X)\n",
    "\n",
    "    assert np.isclose(python_sum(X), numpy_sum(X))\n",
    "    print(\"\\tFor numpy.sum: \", end='')\n",
    "    %timeit numpy_sum(X)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Well that's better than what I expected!\n",
    "It seems that the overhead is *constant* and not increasing when the size of the input is increasing!\n",
    "\n",
    "It means that if the Python code runs in time $T_1(n)$ for inputs of size $n$, then then OCaml binding code runs in less than $T_2(n) \\leq \\alpha T_1(n) + \\beta$, with two constants $\\alpha, \\beta$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T04:24:28.370702Z",
     "start_time": "2021-02-23T04:24:27.287307Z"
    }
   },
   "outputs": [
    {
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qli++gAsugMcfT2+GY47JnEa2zTYreXPGmzCuK8x+P/G5CFVgx4uhVV+osmLDTZIkSZIkacOU1WWyEEIHoGfx0xnA3jHGKaXZI8b4anGhbDzQGDgvhPBSjPHRsp1WkiRJkiRJkiRJklQZFcUibnvrNi7936UsKVySWG7X3bsy6LBB1MqrlVimpIpj4UK44Qa46SZYktw/Tb+y7bYwZAgctbIDv5bOhncvg89HQEInOf5K472h/Qio3yr5bEmSJEmSpCyW1WUyYEDxfQR6l7ZItkyM8ZsQwiXAPUAArgEsk0mSJEmSJEmSJEmSVmvq3KmcOvZUnvvqucQyN6q1EXcfczfHbH9MYpmSKo4YYcyYzGlk336bzgw1a0KfPnDhhVCt2gpvxgjf/B3evgAW/5j8cHkNoM2NsM3pEHKSz5ckSZIkScpyWVsmCyG0BFoWP10E/H09t/w7MAyoAewUQmgZY5y8nntKkiRJkiRJkiRJkiqp/5v8f3R9oiuzF89OLPOY7Y7h7mPvZqNaGyWWKani+Phj6NkT/vvf9GY46SS4+WbYfPOVvDnvcxh/LvyQ0oBbdoLdBkF1/w2VJEmSJElalawtkwFti+8j8FWMcfH6bBZjXBRC+JLlBbW2gGUySZIkSZIkSZIkSdKvzFk8h+5PdWf0+6MTy6xZtSaDDx/MGbudQQghsVxJFcO8eTBgAAweDAUF6cyw004wdCgcdNBK3ixcAh8NhA+ugaIlic9GnRbQ7g5oenDy2ZIkSZIkSRVMNpfJmpZ4XFafMpXcp+kqV0mSJEmSJEmSJEmSNkgvf/Myncd05ts53yaWuUezPXiww4O0aNQisUxJFUOM8PDD0KsXfP99OjPUqQNXXQXdu0PVqitZ8ONLMP5smPtx4rORkwc7XQYtL4Xc6snnS5IkSZIkVUDZXCbLL74PQPMy2rPkPvmrXCVJkiRJkiRJkiRJ2qAsKVhCvxf6MfD1gURiIpm5IZe++/fliv2voEpONv/6XlIa3nsPevSAV15Jb4aTT4Ybb4SmK/vK5sUz4N1e8OX9SY+VsfHvMqeR1d0+nXxJkiRJkqQKKps/jf6uxOOGIYT9Yozr/PFYCOEAoFGJl6at82SSJEmSJEmSJEmSpEpj8vTJdBrTiXd/eDexzG0bbsvoDqPZY7M9EsuUVDHMmgX9+sHtt0NRUToztGkDw4bBPvus5M0YMwWyd3vBkpkJTwZUawy73QJbdoIQks+XJEmSJEmq4LK5TPZW8X0kczrZoBDCXjHGwtJuFEKoAty8wstvrud8kiRJkiRJkiRJkqQKrCgWMfStoVzyv0tYUrgksdwzdzuTWw6/hdp5tRPLlJT9iorgvvvg0kthxox0ZmjQAK69Fs46C3JzV7Jgzkcw/myY/nLiswGwzRnQ5kao1jCdfEmSJEmSpEoga8tkMcavQwhvAHuSKZTtDowJIfwlxrhgbfcJIdQC/l58fSx++Y0Y49dlPLIkSZIkSZIkSZIkqYL4bu53dHm0C//98r+JZTap2YS7j72bY7c/NrFMSRXD+PHQrVvmPg0hwJlnZopkjRuvZEHBIph8LXx0ExTlJz4f9VpCuztho32Tz5YkSZIkSapksrZMVuxi4BUyJ5MF4GjgkxDC1cA/YoyzV3VhCKE+8GegD7AJy084KwJ6levUkiRJkiRJkiRJkqSs9a8P/8VZj5/FrMWzEss8usXR3HPsPWxce+PEMiVlv59+gssvh3vugRjXvL487LEHDB8Ou+++igXfPwvjz4X5XyQ6FwC51aFVP9jhIsjNSz5fkiRJkiSpEsrqMlmM8Y0QwgDgSpaXwTYFbgeGhBDeBz4AZgILgZpAY6AV0BqoWnxNyY/bro4xvpHUzyBJkiRJkiRJkiRJyg5zFs+h59M9GfXeqMQya1atyS2H3cJZu59FCCGxXEnZraAARoyAPn1g9ux0ZmjSBG66CU4+GXJyVrJg0Q/w9gXwzd8Tnw2ATY6AdsOh9tbp5EuSJEmSJFVSWV0mA4gxDgghFABXs7wUFoA8oC2wsu9FKvkJ/LISWgT6xRivKcdxJUmSJEmSJEmSJElZ6JVvXqHzmM58M+ebxDLbbdqO0SeMZrtG2yWWKSn7vfIKdO8O77+fTn5ubib/yiuhfv2VLIhF8PkIePcyyJ+T8HRA9aaw+xDY4kSwhCtJkiRJklTmsr5MBhBjvC6E8CJwF7DTspdXd0nxfSi+fQR0jTG+Wm5DSpIkSZIkSZIkSZKyztLCpfR/oT83vnYjcbW/Zi47OSGHPvv1oc/+faiaWzWRTEnZb9o06N0bHnoovRkOOACGDoXWrVexYNZ7MK4rzHwr0bkyArQ4F3a5FvLqpZAvSZIkSZK0YagQZTKAGOPrIYTWwKHAacCBwEaruWQ68BJwL/BsjDGZ3wpIkiRJkiRJkiRJkrLChz99SKdHOvHOD+8klrlNg214sMOD7LX5XollSspuS5fCbbfBVVfB/PnpzLDppjBoEPzpT6s47Ct/Pky6Ej4ZDLEw4emABm2g3Qho3D75bEmSJEmSpA1MhSmTARQXwp4tvhFC2ALYCqgP1AYWALOBL2OM36YzpSRJkiRJkiRJkiQpTTFGho0bRu//9WZxweLEcs/Y9QxuPeJWaufVTixTUnb773+hZ0/4+ON08qtWhQsvhD59oPaq/mma+jhM6A4LU/hTmyq1YOerYbsekFOh/oxJkiRJkiSpwqrQn8IUF8YsjUmSJEmSJEmSJEmSAJg2bxpdHu3Cs188m1hm45qNGXnMSI7f4fjEMiVlt2++gYsugn//O70ZDjsscyLa9tuvYsHCqTChJ0wdk+hcv9jseNj9Nqi1eTr5kiRJkiRJG6gKXSaTJEmSJEmSJEmSJGmZf3/4b8564ix+XvRzYplHtTiKe469h6a1myaWKSl7LV4MN98M110HixalM8OWW8Ktt8Jxx0EIK1lQVACfDoP3+0LB/KTHg5qbQ9thsNmxyWdLkiRJkiTJMpkkSZIkSZIkSZIkqWKbu2Qu5z19Hve/e39imTWq1GDQYYM4u+3ZhJW2NSRtaJ54As47D778Mp386tXh0kuhd2+oUWMVi2aOh3FdYdY7ic4GQMiF7c+H1ldC1drJ50uSJEmSJAmwTCZJkiRJkiRJkiRJqsBe/fZVOo/pzNezv04ss+2mbRndYTTbN94+sUxJ2evzz+H88+HJJ9Ob4fjj4ZZbYKutVrFg6Rx4vw98OhyICU5WrNEe0P5OaNAm+WxJkiRJkiT9imUySZIkSZIkSZIkSVKFs7RwKVe9eBU3vHYDRbEokcyckMPl+15OvwP6UTW3aiKZkrLXggVw3XVw882wdGk6M7RoAbfdBkccsYoFMcKUf8HE82DR94nOBkDVetDmetjmLMjJTT5fkiRJkiRJv1GhymQhhNbAkcBuwOZAPaAGEEq5VYwxblPG40mSJEmSJEmSJEmSEvDxjI/p+EhH3v7+7cQyt6q/FaNPGM3em++dWKak7BQj/OtfcOGFMHVqOjPUqgV9+2ZORKtWbRWL5n8F47vB908lOdpyzf8Mu90KNZqmky9JkiRJkqSVqhBlshDC7sAwoP2Kb63jlnH9JpIkSZIkSZIkSZIkJS3GyO3jb6fXf3uxqGBRYrmntTmNwUcMpk61OollSspOH34IPXrA88+nN8Of/wwDB8Jmm61iQVE+fDQIPhgAhcn9W/mL2ltD29th08OTz5YkSZIkSdIaZX2ZLIRwCjASyGV5eSyucF+qLctiLkmSJEmSJEmSJElScr6f9z2nPXYaT3/+dGKZjWo0YuQxI+mwY4fEMiVlp7lz4aqr4LbboKAgnRlatYKhQ+HAA1ez6KfXYFxXmDM5qbGWy6kKO/aGlldAlRrJ50uSJEmSJGmtZHWZLISwD3A3mSJZLL6F4lsBMBtYkNZ8kiRJkiRJkiRJkqTyN+ajMZz5+JnMXDQzscwjtj2Ce4+9l03qbJJYpqTsEyOMHg29esGPP6YzQ926MGAAnHsuVK26ikVLfoZ3L4UvRiY62y+a7Aft74R6O6WTL0mSJEmSpLWW1WUy4GaWF8kCsBAYCvwD+CDGmNJ3PUmSJEmSJEmSJEmSytu8JfM47+nzuO/d+xLLrF6lOoMOG8Q5bc8hhJBYrqTs8+670L07vPZaejN06QLXXw8bb7yKBTHC1w/B2xfCkp8SnQ2AvIaw60DY+lQIOcnnS5IkSZIkqdSytkwWQmgO7MHyItl3wEExxs9SHUySJEmSJEmSJEmSVO5en/I6ncd05stZXyaWudsmu/HQCQ+xQ+MdEsuUlH1+/hn69oU774SionRm2G03GD4c9txzNYvmfgrjz4Ufn0tsrl/Z6pRMkax6k3TyJUmSJEmStE6ytkwG7F18H8gUyrpZJJMkSZIkSZIkSZKkyi2/MJ+rXrqK61+9nqKYTIsjJ+Rw6T6X0v/A/uTl5iWSKSn7FBbCPffA5ZfDzJnpzNCwYeYkstNPh9zcVSwqXAIf3gCTr4OipYnOB0Dd7aHdnbDxgclnS5IkSZIkab1lc5msaYnHs4HHU5pDkiRJkiRJkiRJkpSAT2Z8QqcxnZgwbUJimVvV34oHOzzIPlvsk1impOzz5pvQvTtMnJhOfghw9tlw9dXQqNFqFv74Aow7G+Z9mthsv8ipBi2vgJ16Q2615PMlSZIkSZJUJrK5TLbsU6cIfBljjGkOI0mSJEmSJEmSJEkqHzFG7pxwJxc9exGLChYllntqm1MZcsQQ6larm1impOwyfTpceincd196M+y1FwwbBrvttppFi6fD2xfD1w8mNtevND0E2t4OdVukky9JkiRJkqQyk81lsuklHmfznJIkSZIkSZIkSZKkdfTD/B84/bHT+c9n/0kss2GNhtz1+7v4w05/SCxTUnYpKIDbb4d+/WDOnHRm2HhjuOkm6NQJcnJWsSgWwRf3wru9YemsROcDoPpGsNut0PwvmePTJEmSJEmSVOFlc0lrQvF9ADZPcxBJkiRJkiRJkiRJUtkb+/FYznz8TGYsnJFY5uHbHM69x93LpnU2TSxTUnZ56SXo0QMmTUonPzcXevaE/v2hXr3VLJw9GcZ3hZ9eS2y2X9m2K7S5HvIapJMvSZIkSZKkcpG1ZbIY4/shhE+A7YEGIYR2Mcbxac8lSZIkSZIkSZIkSVo/85fO5/ynz+eed+5JLLN6leoMPHQg3dp1I3i6jrRB+u476NUL/va39Gb43e9g6FBo2XI1iwoWwgdXw0c3QyxIbLZf1G8N7UZAk72Sz5YkSZIkSVK5y9oyWbEBwEPFj/sDv09xFkmSJEmSJEmSJEnSenpjyht0HtOZL2Z9kVjmrk13ZfQJo9mpyU6JZUrKHkuXwuDBMGAALFiQzgybbQaDBsGJJ8Jq+6zTnoLx3WDBV4nN9ovcmtD6StjhfMipmny+JEmSJEmSEpGT9gCrE2P8G/AwEIAjQwj9Ux5JkiRJkiRJkiRJkrQO8gvz6fdCP/a9b9/EimSBwGX7XsabZ7xpkUzaQD3zDLRuDZdckk6RLC8PLr8cPv4YTjppNUWyhdPg1ZPgxaPSKZJtejQcPRl26mWRTJIkSZIkqZLL9pPJALqQKb39GegXQtgZuCLG+HG6Y0mSJEmSJEmSJEmS1sanMz+l0yOdGD9tfGKZzes158EOD7Jf8/0Sy5SUPb7+Gi64AMaOTW+GI4+EIUOgRYvVLCoqhM/ugPevgPy5ic32ixqbwu63weYnrOHINEmSJEmSJFUWWV0mCyH0K374MfAlsDVwPHB8CGESMAGYDiwu7d4xxgFlNKYkSZIkSZIkSZIkaSVijIyYOIKLnr2IhfkLE8s9eZeTue2I26hXvV5imZKyw6JFMHAgXH89LC71X5OUja22ypTIfv/7NfSzfn4HxnWFn5Mr2v4i5ECL7rDL1VC1bvL5kiRJkiRJSk1Wl8mAK4FY4nkEln3MtjPQej32tkwmSZIkSZIkSZIkSeXkx/k/cvpjp/PkZ08mltmgegPuOuYu/rjTHxPLlJQdYoTHHoPzz8+cSpaG6tXh8suhV6/M41XKnwfv94NPb4NYlNh8v2i4O7QfkbmXJEmSJEnSBifby2QrE9e8ZLVCGewhSZIkSZIkSZIkSVqFxz55jDMeO4OfFv6UWOahWx/KfcfdR7O6zRLLlJQdPv0UzjsPnn46vRlOOAEGDYItt1zDwiljYWIPWDg1galWUKUO7HINtOgGObnJ50uSJEmSJCkrVIQyWVjzEkmSJEmSJEmSJElS2uYvnc+Fz1zIyLdHJpZZLbcaNx16E93bdycn5CSWKyl98+fDtddmSlz5+enMsP32cNttcNhha1i44FuY0AO+eyyRuX5j8z/A7kOgpoVbSZIkSZKkDV22l8l+l/YAkiRJkiRJkiRJkqQ1e3Pqm3Qe05nPf/48scw2TdswusNoWm7UMrFMSemLEf7v/+Cii+C779KZoXZt6NcvcyJaXt5qFhYVwCdDYFJ/KFiQ2Hy/qNUc2g6HZkcnny1JkiRJkqSslNVlshjjS2nPIEmSJEmSJEmSJElatfzCfK595VquefkaCmNhIpmBQO99enPVgVdRrUq1RDIlZYcPPoAePeDFF9OboWNHuOkm2HTTNSyc8RaM6wqz30tkrl8JubDDRdC6H1SplXy+JEmSJEmSslZWl8kkSZIkSZIkSZIkSdnrs5mf0WlMJ8Z9Ny6xzC3qbcGDHR5k/+b7J5YpKX1z5sCVV8LQoVCYTG/1N3beOZO//5r++Vk6G967HD67E4gJTLaCxntB+xFQv3Xy2ZIkSZIkScp6lskkSZIkSZIkSZIkSaUSY2Tk2yO54JkLWJi/MLHczjt3ZuiRQ6lXvV5imZLSVVQEo0bBJZfA9OnpzFCvHlxzDZx9NlRZ3V/axAjf/APevgAW/5DYfL+oWh92vRG2OQNCTvL5kiRJkiRJqhAsk0mSJEmSJEmSJEmS1tr0BdM547EzePzTxxPLbFC9AXf+/k5OanlSYpmS0vf229C9O7zxRnoznH46XHcdbLTRGhbO+wLGnws/PJvIXL/R/K+w2y1QY+N08iVJkiRJklRhWCaTJEmSJEmSJEmSJK2VJz59gtMfO53pC5I7HuiQrQ/h/uPup1ndZollSkrXzJlwxRVw112Zw77S0LYtDB8O7duvYWHhUvhoIEy+BgoXJzLbr9TeFtrdDpscmny2JEmSJEmSKqQKWSYLIdQB9iy+bQE0AOoA84BZwDfAm8BbMcZ5ac0pSZIkSZIkSZIkSZXBgqULuOjZixgxcURimdVyq3HDITfQc4+e5IScxHIlpaewEEaOzBTJfv45nRkaNYIbboDTToOcNf3TM/1lGHc2zP0okdl+JScPdroUWl4GudWTz5ckSZIkSVKFVaHKZCGENsAFwElA3lpcsiSE8A9gcIzxvfKcTZIkSZIkSZIkSZIqo3HfjaPTI5347OfPEsvceeOdeeiEh2i1UavEMiWl6/XXoXt3eOeddPJzcuCcc2DAAGjYcA2Ll8yEd3rBl/clMttvbHQgtLsD6u2QTr4kSZIkSZIqtArx9W0hhCohhOuA8UAnoBoQim8rvaT4Vh04GZgQQrg2hFChynOSJEmSJEmSJEmSlJaCogIGvDSAve/ZO7EiWSDQa+9ejDtjnEUyaQPxww9w6qmwzz7pFcn23RfefhuGDVtDkSxG+PIBeGKHdIpk1RrDng/Awc9bJJMkSZIkSdI6y/pyVXEB7FHgCJaXx2KJx6sqlC1bB5ALXArsEkI4LsZYWB6zSpIkSZIkSZIkSVJl8PnPn9N5TGfenPpmYpmb192cUR1GceCWByaWKSk9+fkwfDj07w9z56YzQ9OmMHAgdOwIYXV/fQIw52MYfw5MfzGJ0X5r69Ng15ugWqN08iVJkiRJklRpZH2ZDBgBHFn8eFmJLACvA88B7wEzgAVALaAxsAtwELDPCtcdWbzfGQnNLkmSJEmSJEmSJEkVRoyRe965h/OfPp8F+QsSy+3YuiPDjhpG/er1E8uUlJ4XXoAePWDy5HTyq1SB88+Hvn2hbt01LC5cDJOvgw9vgKL8JMb7tbo7QvsRsNF+yWdLkiRJkiSpUsrqMlkIYR+gC8tPGAvAU8CFMcZPVnPpI0D/EML2wCDgKJYXyrqEEO6JMb5RfpNLkiRJkiRJkiRJUsXy04KfOOPxM3jsk8cSy6xfvT53HH0Hf27158QyJaVnyhS4+GL4v/9Lb4aDD4ahQ2HHHddi8Q//g3HnwPzPy32u38itDq36wg4XQ25e8vmSJEmSJEmqtLK6TAZcWXwfyJTBrokx9lvbi4sLZ78PIVwF9GV5oexK4PAynVSSJEmSJEmSJEmSKqgnP32S0x87nR8X/JhY5kFbHcT9x93P5vU2TyxTUjqWLIFbboFrroGFC9OZYfPN4dZb4YQTIIQ1LF70I7x9IXzzcCKz/cYmh0Pb4VBnm3TyJUmSJEmSVKllbZkshFAXOIDlp5KNLU2RrKQYY/8QQiugQ/FLB4YQ6sQY55XBqJIkSZIkSZIkSZJUIS1YuoCLn72YOyfemVhmXm4eNxx8A+fteR45ISexXEnpeOopOO88+OyzdPLz8qB3b7jsMqhZcw2LYxF8PhLevRTyZycx3q9Vbwq7D4YtTlqLxpskSZIkSZK0brK2TAbsy/L5ItB/Pffrz/IyWZXi/Z9azz0lSZIkSZIkSZIkqUIa/914Oo3pxKczP00ss/VGrXnohIdovXHrxDIlpePLL+GCC+Cxx9Kb4fe/z5xGtu22a7F41vsw/myY8Ua5z/VbAVqcA7tcC3n1U8iXJEmSJEnShiSby2Sblng8Lcb4wfpsFmP8IITwHdCs+KVmq1svSZIkSZIkSZIkSZVRQVEB179yPQNeHkBBUUEimYHAhXtdyDUHXUP1KtUTyZSUjoUL4cYbM7clS9KZYZttYPDgTJlsjQoWwKSr4ONbIBaW92i/VX8XaD8CGu+RfLYkSZIkSZI2SNlcJmtcfB+BaWW05/csL5E1KqM9JUmSJEmSJEmSJKlC+OLnL+g8pjNvTE3u5J3N6m7GqONH8butfpdYpqTkxQhjx2ZOI/vmm3RmqFED+vSBCy+E6mvTW/3uCZjQHRakMHCVWtB6AGzfE3Ky+c93JEmSJEmSVNlk86dRC0o8rldGe9Yt8XhhGe0pSZIkSZIkSZIkSVktxsh9797HeU+fx/yl8xPL/UurvzD8qOE0qNEgsUxJyfvkE+jZE559Nr0ZTjwRbr4ZtthiLRYvnAoTz4Mpj5T7XCu12XGw+21Qa22GlSRJkiRJkspWNpfJphffB2DLEEL9GOPsdd0shFAf2IrMSWcl91c5CiFsCUwCahe/9E2MccvUBpIkSZIkSZIkSZI2MD8t+ImznjiLsR+PTSyzXrV63H707fy19V8Ty5SUvHnz4OqrYfBgyM9PZ4Ydd4ShQ+Hgg9dicVEhfDoM3u8DBckVa39RczPYfShsfnzy2ZIkSZIkSVKxbC6TvVN8H4GqwGnALeux32nF+yzb853VrFUZCCEE4B6WF8kkSZIkSZIkSZIkJeipz56iy6Nd+HHBj4llHrjlgTxw/ANsUc8Td6TKKkb429/g4ovh++/TmaFOHbjySujRA6pWXeNymDkBxnWFWW+X92i/FXJgu/Ng56ugap3k8yVJkiRJkqQSsrZMFmP8NITwBbA1mdPJrgoh/C/G+H5p9wohtAauIlMiC8CXMcZPy3RgrczZwEHAj8DGKc8iSZIkSZIkSZIkbTAW5i+k17O9uH3C7Yll5uXmcd1B13HBXheQE3ISy5WUrPffzxS4Xn45vRk6d4Ybb4RNNlmLxflz4b0+8NlwiEXlPttvNGwH7UdAw12Tz5YkSZIkSZJWIts/wR9BpvwVgVrAiyGE40uzQQjhWOAFoGaJve4o2zG1ohBCc+Cm4qc90pxFkiRJkiRJkiRJ2pBMmDaB3UbslmiRrNVGrRh/5ngu2vsii2RSJTV7NvTsCbvuml6RbJdd4JVXYNSotSiSxQjf/gue2BE+HZp8kaxqXWg7DA57wyKZJEmSJEmSskq2f4p/G/BV8eMI1Af+HUJ4OYRwaghhi5VdFELYovj9F4ExQMMSb38JDC2/kVXsHqA2MDbG+M+0h5EkSZIkSZIkSZIqu8KiQq59+Vr2umcvPpn5SWK5F+55IePPHM/OG++cWKak5BQVwb33wnbbwdChmedJq18fhg+HiRNh333X4oL5X8NLv4dXT4RF08p5upXY4iQ4+iPYrhvk5CafL0mSJEmSJK1GlbQHWJ0Y49Lik8VeJlMki2ROF9un+EYIYS4wE1hA5vSyRkDdEtuEEtf9DBwXY8xP6EfIWiGEbYD2wGZAHjAL+Bh4Pca4eD337gocDMwGzl2/SSVJkiRJkiRJkiStyZezvqTzmM68PuX1xDKb1WnGA8c/wMFbH5xYpqRkjR8P3bvDuHHp5IcAZ5wB114LTZqsxQVF+fDxrTDpSihcVN7j/VatraDd7bDpEclnS5IkSZIkSWspq8tkADHGySGEw4F/As3JFMMgUw4DqFd8W+nlLC+SfQ2cGGP8sPymXTchhGZkil17FN+3BeqUWPJNjHHLMso6HugL7LaKJfNDCPcDV8UYZ6zD/lsAA4uf9ooxfr8uc0qSJEmSJEmSJElasxgj9797Pz2f7sn8pfMTy/1Tyz9xx9F30KBGg8QyJSVnxgy4/HK4+26Icc3ry8Mee8CwYdC27Vpe8NPrMP5smD2pXOdaqVAFduwFrfpAlZrJ50uSJEmSJEmlkPVlMoAY44QQQmvgeqALsOyTt9V9ZBmKbwuAe4ErYozJ/fZkDUII+wAXkSmQbZpAXjXgHqDjGpbWBroDfwoh/DHG+HIpo0aSKcI9H2O8u/STSpIkSZIkSZIkSVobMxbOoOsTXXnko0cSy6xbrS63H3U7f239V0IIa75AUoVSWAgjRkCfPjBrVjozNGkCN94Ip5wCOTlrccHSWfDupfD5XeU+20o12Rfa3Qn1W6aTL0mSJEmSJJVShSiTARQXwXqEEPoAfwUOIFPE2hwo+fFhETAFeBN4CfhbjHFOwuOujXZAhySCQgg5wD+A41Z4qxD4FpgDbMWvT3hrAjwVQjgkxvjGWuacARwGLATOWt+5JUmSJEmSJEmSJK3c058/TZdHu/DD/B8Syzyg+QE8cPwDNK/fPLFMScl59VXo0QPefTed/Jwc6N4drroK6tdfiwtihK8fhncuhMXTy3u838prALsOhK27QFib1pskSZIkSZKUHSpMmWyZ4mLYHcU3AEII9cicqDU/S4tjpTWfzM9TVnrx2yLZncDVMcZp8Evh7DhgMLBF8ZqawP+FEFqt6b9rCGEzYFDx034xxi/KaHZJkiRJkiRJkiRJxRbmL+SS/17CsPHDEsusmlOVaw+6lgv3upDcnNzEciUl4/vvoXdvGD06vRn23x+GDoWdd17LC+Z+BhPOhR/+V65zrdKWnWG3m6H6RunkS5IkSZIkSeuhwpXJVqa46FRRS2TzgInAeGBc8f1WwAtlsXkIoRFwxQovXxZjvKHkCzHGImBMCGEc8CqwZfFbmwEXAv3XEDUSqEtm/sHrN7UkSZIkSZIkSZKkFb39/dt0fKQjH8/4OLHMlk1aMvqE0bRp2iaxTEnJyM+H227LnAQ2b146M2y6Kdx8M/z5zxDCWlxQuAQ+vBEmXwdFS8p9vt+osx20uwOaHpR8tiRJkiRJklRGKkWZrIJ6HHgW+Li4yPWLEMJWZZjTG6hT4vnLwI2rWhxj/C6EcAZQ8uu7Lggh3BZjnLmya0IIpwFHAPnA6THGwvUfW5IkSZIkSZIkSRJAYVEhN712E/1e7EdBUUFiuefvcT7XH3I91atUTyxTUjL+9z/o2RM++iid/KpV4YILoE8fqFNnzesB+PFFGH82zP2kPEdbuZw8aHk57HQp5FZLPl+SJEmSJEkqQ5bJUhJj/KK8M0IIOUCXFV6+MsYYV3ddjPG5EMIrwH7FL9UBTgLuWElGM+CW4qc3xhgnrd/UkiRJkiRJkiRJkpb5atZXnDz2ZF799tXEMjetsykPHP8Ah2x9SGKZkpLx7bdw0UXwr3+lN8Ohh2ZORNthh7W8YPFP8M7F8NWocp1rlTY+KHMaWd3t0smXJEmSJEmSyphlssptb6BJiedfAi+u5bX3sLxMBnA8KymTAT2BesBC4PMQwp/XsG+tEmsWxBgfX8t5JEmSJEmSJEmSpA1GjJFR742ix1M9mLd0XmK5J7U8iTuOvoOGNRomlimp/C1eDIMGwbXXwqJF6czQvDnceiscfzyEsBYXxCL48j54pzcs/bm8x/utak1gt1tgy45rObAkSZIkSZJUMWR1mSyEsC/wUomXDokxvrAO+xwE/Lf4aQT2iDFOLIMRs93RKzz/75pOJSu5doXnB4YQasUYF6zwerXi+5rA/Wuxb2Pgb8WPvwEsk0mSJEmSJEmSJEklzFw4k65PdOXfH/07scy61eoy/KjhdGzdkWBpQqpUnnwSzjsPvvginfxq1eDSS6F3b6hZcy0vmvMhjDsbfnqlXGdbpW3OhDY3QDWLtZIkSZIkSap8srpMBnQFlv2mYty6FMkAYozPhxDeAXYr3u9MYEMok7VZ4fnra3thjHFaCOFrYMvil/KAnYDxZTGYJEmSJEmSJEmSpN969otnOXXsqXw///vEMvdvvj+jjh9F8/rNE8uUVP6++ALOPx+eeCK9GY47Dm65Bbbeei0vKFgEk6+BjwZCUX65zrZS9VpB+zuhyT7JZ0uSJEmSJEkJyUl7gFUJIeQAR5E5SSwCD63nlqOK7yNw7HruVVHsuMLzD0t5/YrrV9yPGOP5McawpluJS74p8fqWpZxHkiRJkiRJkiRJqpQW5S+i51M9OXz04YkVyarmVOWGg2/g+ZOft0gmVSILFkCfPrDTTukVyVq0gP/8B8aOLUWRbNoz8J9WMPm65ItkuTUyJ5Ed+bZFMkmSJEmSJFV62XwyWWugQfHjCDy5nvs9CQwmczLZxiGE7WOMn6znnlkrhFAD2GKFl6eUcpsV12+/7hNJkiRJkiRJkiRJWpl3vn+Hjo905KMZHyWWuVOTnRjdYTS7brJrYpmSyleM8O9/w4UXwpTS/nVAGalZE/r2hQsugGrV1vKiRd/DxAvg23+U62yrtOlR0HYY1N4qnXxJkiRJkiQpYdlcJit5CtbsGOOX67NZjPGLEMJsoH7xSy2BSlsmAxqTKc4tkw9ML+Ue363wfKP1mkiSJEmSJEmSJEnSLwqLCrn59Zvp+0Jf8hM8hadn+57ccMgN1KhaI7FMSeXro4+gRw947rn0ZvjTn2DgQNh887W8oKgQPh8B710G+XPLdbaVqrEp7D4ENv8DhLDm9ZIkSZIkSVIlkc1lsqbF95HflprW1VSWl8maldGe2ar2Cs8XxhhjKfdYsIY9UxVC2AhoUsrLtimPWSRJkiRJkiRJkqTS+Hr215w85mRe+faVxDI3qb0J9x9/P4dtc1himZLK19y5MGAADBkCBQXpzNCyJQwdCr/7XSkumvUujOsKM8eV11irEWC77rDLNVC1bgr5kiRJkiRJUrqyuUxWs8TjFUtN66rkPllVjCoHK/58i9dhj0Vr2DNt5wL90x5CkiRJkiRJkiRJWlsxRka/P5pu/+nGvKXzEsv9405/5M6j76RRzUaJZUoqPzHCQw9Br17www/pzFC3Llx1FXTrBlWrruVF+fNhUn/4ZAjEwnKdb6Ua7AbtR0CjtslnS5IkSZIkSVkim8tkc0o8LqvfaDQs8XhhGe2Zraqv8HzpOuyxZIXnNdZxFmKMYV2vlSRJkiRJkiRJkiqDnxf9zNlPnM0/P/xnYpl18uow7KhhdN65MyH4KzupMnj3XejRA159Nb0ZTjkFbrgBmjYtxUVTH4UJPWDhlHKba5Wq1Iadr4HtukFONv+pjCRJkiRJklT+svkTsp+K7wOweQihRoxxxZOy1loIoSbQHIgr7F9ZrXgSWd467FFtDXtKkiRJkiRJkiRJWgv/+/J/nDL2FKbNm5ZY5r5b7Muo40exVYOtEsuUVH5+/hn69YM77oCionRm2G03GDYM9tqrFBctmAITe2TKZGnY/ATYfQjU3CydfEmSJEmSJCnLZHOZ7OMSj/OAw4D1+WTxcJYXqiLwxXrsVRHMX+H5iieVrY0VTyJbcc+03Q6U9msbt2H9/nckSZIkSZIkSZIkrbVF+Yu47LnLGPLWkMQyq+RU4erfXU2vvXuRm5ObWK6k8lFUBPfeC5ddBjNmpDNDw4Zw3XVwxhmQu7b/rBQVwCe3waR+ULCgXOdbqZpbQLvh0Oz3yWdLkiRJkiRJWSxry2QxxvdDCNOBJmROJ+vL+pWA+pApkQVgNjBufWfMcisWv2qGEEKMMa509crVWsOeqYoxTgeml+aaEEI5TSNJkiRJkiRJkiT92rs/vEvHRzry4U8fJpa5Q+MdeOiEh9htk90Sy5RUfsaNg+7dYfz4dPJDgK5d4ZproFGjUlw4YxyM7wqz3i2v0VYt5MIOF0DrK6HKin/2IEmSJEmSJCkn7QHWYCyZ8hfAriGEW9Zlk+Lrdi1+GoGxpSxVVUQzyPysy1QFNirlHs1WeF6q4pYkSZIkSZIkSZK0ISosKuSm126i/cj2iRbJurfrzsSzJlokkyqB6dPh9NNhjz3SK5LtuSdMmAB33FGKItnSOTC+Gzy7ZzpFskZ7whETYdeBFskkSZIkSZKkVcjak8mKXQucSqYIFYDzQgiNge4xxrlrujiEUBcYDvyV5aeSLQWuKa+Bs0WMcVEI4VugeYmXtwB+LMU2W6zw/OP1HkySJEmSJEmSJEmqxL6Z/Q2njD2Fl755KbHMprWbcv9x93P4tocnlimpfBQUZMpbffvCnDnpzLDRRnDTTdC5M+Ss7VcUxwjf/h9MPB8W/1Ce461c1XrQ5gbY9iwI2f69ypIkSZIkSVK6srpMFmOcEkK4HujP8jJYR+DYEMIo4D/AhBjjjGXXFJfN2gJHAZ2Buiw/3SwCN8YYv0rup0jVx/y6TLYTUJrvLNtxJftJkiRJkiRJkiRJWkGMkYcmPUS3/3Rj7pI1fi9mmTlhxxMY8fsRNK7ZOLFMSeXj5Zehe3eYNCmd/Nxc6NEDrrwS6tUrxYXzv8ycRvb90+U12uo1/wvsdgvUaJpOviRJkiRJklTBZHWZDCDGeFUIoRXwB5YXyuoC3YpvhBAisBCoyfLiGPy6RBaA/4sx9k9o9GzwLlDy6wf3Bh5YmwtDCJsAW5Z4KR/4sKwGkyRJkiRJkiRJkiqLWYtmcc6T5/CPyf9ILLN2Xm2GHjmUU3Y5hRDCmi+QlLWmTYNeveDhh9Ob4cADYehQaNWqFBcVLoWPb4YProbCxeU12qrV3gba3Q6bHJZ8tiRJkiRJklSBZX2ZrNhfgIHAeWSKYcuEEve1V7gmsrxEBjAIuLQcZ8xGTwCXlHh+SAghxBjjqi4oYcVPW1+IMc4vu9EkSZIkSZIkSZKkiu+5L5/jlLGn8N287xLL3GfzfRjVYRRbN9g6sUxJZW/pUhgyBAYMgPkp/Ta+WTMYNAhOOglK1Uud/iqM7wpzUvhO2pyqsOMl0PJyqFIj+XxJkiRJkiSpgstJe4C1EWMsiDFeABwJvEWmIFby1LEVb5RY8ypwWIyxV4yxMNHB0/c6MKPE862BA9fy2tNXeP5oWQwkSZIkSZIkSZIkVQaLCxZz4TMXcsiDhyRWJKuSU4VrD7qWl059ySKZVME9+yzsvDP07p1OkaxqVbjsMvj4Y/jTn0pRJFsyE946A/63XzpFso32hyPfg12utkgmSZIkSZIkraOKcjIZADHGZ4BnQgjtyJyctR+wDdAQqAPMA34GPgNeAZ6OMb6T0ripizEWhRDuBy4u8XL/EMKLqzudLIRwMJn/tsvMA/6vfKaUJEmSJEmSJEmSKpb3fniPTmM68cH0DxLL3L7R9jx0wkPsvunuiWVKKnvffAMXXgiPPJLeDEcckTkRbbvtSnFRjPDVg/DORbBkxprXl7VqjWDXm2GrU0p5hJokSZIkSZKkFVWoMtkyMcbxwPi056ggbgTOBmoXPz8AuAS4YWWLQwjNgLtXeHlIjDGFT4MlSZIkSZIkSZKk7FEUi7jljVu44vkrWFq4NLHcbu26cdOhN1Gzas3EMqVstnQpfPABTJyYuX3+OSxcCIsXZ97Ly4Pq1aFmTdh2W9h998ytVavMe2lYtAgGDoTrr8/MmYattoLBg+GYY0rZx5r7CYw/B358obxGW72tu0Cbm6B643TyJUmSJEmSpEqmQpbJKosQwj5AjZW8tcsKz6uHEA5ZxTbTYowfriojxjgjhHAdcF2Jl68PIWwBXBNjnFY8Sw5wLDAE2KLk/sCg1f8kkiRJkiRJkiRJUuX27ZxvOWXsKbz49YuJZTat3ZR7j72XI1scmVimlI3y8+Gxx+C//82Ux95/P1MaWxvPPbf8cV4e7Lxzplh26KFw7LFQtWr5zLxMjPD443D++fDVV+WbtSrVq8Nll0GvXlBjZX+hsCqFi2Hy9fDhDVCUXIH2F3V3gHZ3wsYHJJ8tSZIkSZIkVWIhxpj2DBusEMLXQPP13OaBGOOpa8jJAR4Ffr/CW4XAN8AcYCug/grvLwIOjTG+tp4zZo0QQkvgg2XPP/jgA1q2bJniRJIkSZIkSZIkScp2D096mHOfPJc5S+Yklnn8Dscz8piRNK7pSTzacE2dCiNHwl13wQ8/lP3+m2wCZ56ZuW22Wdnv/9lncN558NRTZb/32urQAW65BbbcspQX/vBc5jSyeZ+Vx1irl1MNWvWBHXtBbrXk8yVJkiRJkqRyNnnyZFq1alXypVYxxslJ5eckFaT0xBiLgBOBv6/wVi6wNbArvy2SzQSOqkxFMkmSJEmSJEmSJKk0Zi2axV///Vc6PtIxsSJZ7bza3HPsPTxy0iMWybRBijFzmtgf/pApQA0YUD5FMoDvv8/sv+WWmbznnsvkr68FC+Dyy6FVq/SKZNttB08/DY88Usoi2eLp8HoneP6QdIpkTQ+Foz/IlMkskkmSJEmSJEnlokraA6yLEEIgU4DaEWgI1CNTjBsVY/w6xdGyVoxxMfCXEMK/gD5Am1UsXQA8AFwVY5ye0HhlLoRwKnDqSt6qmewkkiRJkiRJkiRJqoie/+p5Thl7ClPnTk0sc6/N9uLBDg+yTcNtEsuUssknn8Dpp8NrCX/laWFhpnT1yCOwzz5w772ZMlZpxQj//CdcdFHmVLU01KoF/frB+edDXl4pLoxF8MXd8M4lkD+7nKZbjeobw263QvM/QwjJ50uSJEmSJEkbkApVJgsh7AJcBBwH1F7JkleBr1dyXW9gh+Kn38YYryynEUslxrhlCpn/Bv4dQtgW2ANoBuQBs4GPgNeKi2cV3ZbAAWkPIUmSJEmSJEmSpIplScESrnj+Cga9MSixzCo5Veh/QH8u3fdSquRUqF/hSmWisBAGD4Y+fWBxyr+tfu012GUXuPZaOO88yM1du+smT4YePeCFF8p3vtX5y19g4EBo1qyUF86eBOPOhhmvl8tcqxdg267Q5nrIq59CviRJkiRJkrThqRC/iQgh5AG3Amcve2kly+JqtvgBuKF4TQwh3L+hn2AWY/wc+DztOcrR18BLK3m9JtAu2VEkSZIkSZIkSZJUEUz6cRIdH+nIpOmTEsvcrtF2jO4wmnbN/BWWNkyffgpdusDrafSYVmHx4szpYo88suZTyubMgauugttuy5Ti0tC6NQwdCgeU9utWCxbCBwPgo0EQC8plttWqvzO0HwGN90w+W5IkSZIkSdqA5aQ9wJqEEGqSKQWdTelLZMs8DPxUfH0AOpbZgMpKMcb7Y4wHrngDuqQ9myRJkiRJkiRJkrJLUSziljduoe3ItokWyc5pew5vn/W2RTJtkGKEYcMyp4BlU5GspGWnlA0blpm3pKIiGDUKtt8ebr01nSJZvXqZEtvbb69Dkey7/8CTLeHDG5MvkuXWhF0HwhETLJJJkiRJkiRJKagIJ5P9DdiD5aWxCIwFngWmAE+saYMYY0EIYQxwVvFLRwLXlvmkkiRJkiRJkiRJkiqUKXOmcOqjp/L8V88nlrlRrY2499h7OXq7oxPLlLJJjNC7N9x8c9qTrNnixdCjB3z7Ldx4I4SQKW917w5vvJHeXKedBtdfDxttVMoLF06DiefBlH+Vy1xr1OwYaDsUajVPJ1+SJEmSJElSdpfJQgjHAMewvEj2GfCHGOMHJdbA2p1O9jiZMlkA2ocQasQYF5XtxJIkSZIkSZIkSZIqir9/8HfOefIcZi+enVjmcdsfx8hjRtKkVpPEMqVsUlgIZ58Nd9+d9iSlM3Ag/PAD1KgBI0f+9qSypOy+OwwfDnvsUcoLiwrhs9vhvSugYF65zLZaNZplSmSbHZ9p5EmSJEmSJElKTVaXyYC+xfcB+AE4MMb4/TruNb7E41xgR+Dt9ZhNkiRJkiRJkiRJUgU0e/Fsuv2nGw9PejixzFpVazHkiCGctutpy74wU9rgxFgxi2TLPPhgetmNGmVOIjvtNMjNLeXFP78N47rCzxPKZbbVCjmwXU/YeQBUrZN8viRJkiRJkqTfyNoyWQhhY2B3lp861nc9imTEGKeHEH4Cln3F3/ZYJpMkSZIkSZIkSZI2KC9+/SInjzmZKXOnJJa552Z78mCHB9m24baJZUrZJkbo3bviFsnSkpOTKeBdfTU0bFjKi/Pnwft94dOhEIvKZb7VatgW2o+Ahrslny1JkiRJkiRplbK2TAbsQ+ZEMoB84O9lsOcMlpfJGpfBfpIkSZIkSZIkSZIqgCUFS+jzfB8GvTGI+Mv3WZav3JBLvwP6cfl+l1MlJ5t/NSuVv+HD4eab056iYtl7bxg2DHbdtZQXxghTx8CEnrDou3KZbbWq1IFdroMW50BOaY9RkyRJkiRJklTesvk3Fk2L7yPweYxxQRnsObfE49plsJ8kSZIkSZIkSZKkLPfB9A/o+EhH3v/x/cQyWzRswegTRtO+WfvEMqVs9ckn0KtX2lNUHE2bwk03QadOEMKa1//Kgm9gfHeY9kS5zLZGW5wIuw2Gmpumky9JkiRJkiRpjbK5TFavxOO5q1xVOrVKPF5URntKkiRJkiRJkiRJykJFsYjb3rqNS/93KUsKlySW23X3rgw6bBC18mqtebFUyRUWwmmnweLFaU+S/apUgfPOg379oG7dUl5clA8fD4ZJV0LhwnKYbg1qbQlth0Ozo5LPliRJkiRJklQq2Vwmm1Xicb1VriqdpiUezyyjPSVJkiRJkiRJkiRlmalzp3Lq2FN57qvnEsvcqNZG3H3M3Ryz/TGJZUrZbsgQeP31tKfIfgcfDLfdBjvttA4X//QGjO8KsyeV+VxrFKrAjhdDq75QpWby+ZIkSZIkSZJKLZvLZD8W3wdgqxBCXoxx6bpuFkJoATQu8dKU9RlOkiRJkiRJkiRJUnb6v8n/R9cnujJ78ezEMo/Z7hjuPvZuNqq1UWKZUrb75BO44oq0p8hum28Ot9wCf/gDhFDKi5fOgncvg8/vAmJ5jLd6jfeG9iOgfqvksyVJkiRJkiSts2wuk00o8TgPOAh4ej3261ji8VLgzfXYS5IkSZIkSZIkSVKWmbN4Dt2f6s7o90cnllmzak0GHz6YM3Y7g1DqJohUecUIp58OixenPUl2ysuDXr3gssugVq1SXhwjfPM3ePsCWDy9XOZbrbwG0OZG2OZ0CDnJ50uSJEmSJElaL1lbJosxTgkhfAjsWPzSJaxjmSyEsAnQg+VfxfVqjNGPrCVJkiRJkiRJkqRK4qWvX+LksSfz7ZxvE8vco9kePNjhQVo0apFYplRRPP88vPZa2lNkp6OPhsGDYdtt1+HieZ/D+HPhh/+W9VhrZ8tOsNsgqO4pjJIkSZIkSVJFle1fETUSWPb1ffuHEK4o7QYhhDrAv4AGJfYaXCbTSZIkSZIkSZIkSUrVkoIlXPLfS/jdA79LrEiWG3K58oArefW0Vy2SSatw++1pT5B9tt4aHn8cnnhiHYpkhUtg0tXwZKt0imR1WsBB/4O9H7RIJkmSJEmSJFVwWXsyWbHbgfOA5mSKYANCCJsCl8cY56zp4hDC4WSKY9ux/FSy8THGJ8tnXEmSJEmSJEmSJElJmTx9Mh0f6ch7P76XWOa2DbdldIfR7LHZHollShXN1Knw6KNpT5E9atSAyy+Hiy+G6tXXYYMfX4LxZ8Pcj8t8tjXKyYOdLoOWl0LuugwvSZIkSZIkKdtkdZksxpgfQvgL8DxQnUyh7Gzg5BDC48DE4qWBTFns6BDCbsC2wEHANiXeC8DPwF8S/SEkSZIkSZIkSZIklamiWMTQt4Zyyf8uYUnhksRyz9rtLAYdPojaebUTy5QqopEjobAw7Smywx/+AIMGQfPm63Dx4hnwbi/48v6yHmvtbPw7aHcH1N0+nXxJkiRJkiRJ5SKry2QAMca3Qgh/Bv5OplAGUAv4U/FtmQCcv8JzWF4kmwP8Mcb4VbkOLEmSJEmSJEmSJKncfDf3O7o82oX/fvnfxDKb1GzC3cfezbHbH5tYplRR5efDXXelPUX6dtgBhg6FQw5Zh4tjzBTI3u0FS2aW9WhrVq0x7HYLbNkJQljzekmSJEmSJEkVStaXyQBijI+HENqTKZS1JFMQ++XtEo9LFshiidcmA3+IMX5a3rMqO4QQTgVOXclbNZOdRJIkSZIkSZIkSWXln5P/SdcnujJr8azEMo9ucTT3HHsPG9feOLFMqSJ77DH44Ye0p0hP9epwzTXQowfk5a3DBnM+gvFnw/SXy3y2tbLNGdDmRqjWMJ18SZIkSZIkSeWuQpTJAGKMk0MIbYATgfOA9iwvj61o2esfAAOBh2KMReU+pLLJlsABaQ8hSZIkSZIkSZKk9Tdn8Rx6Pt2TUe+NSiyzZtWa3HLYLZy1+1kET+aR1tp/kzs0MCudeCJcdNE6XFiwCCZfCx/dBEX5ZT7XGtVrCe3uhI32TT5bkiRJkiRJUqIqTJkMIMZYSOZ0sr+HEBoC+wI7Ao2A+sBCYAbwFfBCjHFaSqMqfV8DL63k9ZpAu2RHkSRJkiRJkiRJ0rp65ZtX6DymM9/M+SaxzHabtmP0CaPZrtF2iWVKlcXEiWlPkK6PP16Hi75/FsafC/O/KPN51ii3OrTqBztcBLnrcpSaJEmSJEmSpIqmQpXJSoox/gw8VnyTfiXGeD9w/4qvhxBakjmxTpIkSZIkSZIkSVlsaeFS+r/Qnxtfu5FITCQzJ+TQZ78+9Nm/D1VzqyaSKVUmS5fC+++nPUW63nsv898hb216WYt+gLcvgG/+Xu5zrdQmR0C74VB763TyJUmSJEmSJKWiwpbJJEmSJEmSJEmSJFVOH/70IZ0e6cQ7P7yTWOY2DbbhwQ4PstfmeyWWKVU2H3yQKVJtyJYuhcmTYdddV7MoFsHnI+DdyyB/TmKz/aJ6U9h9CGxxIoSQfL4kSZIkSZKkVFkmkyRJkiRJkiRJkpQVimIRw8cNp/f/erO4YHFiuWfsega3HnErtfNqJ5YpVUYTJ6Y9QXaYOHE1ZbJZ78G4rjDzrURnygjQ4lzY5VrIq5dCviRJkiRJkqRsUGnLZCGEqkBDYFaMcQP/7jNJkiRJkiRJkiQpu02bN40uj3bh2S+eTSyzcc3G3H3M3Ry3w3GJZUqVmWWyjAkT4IwzVngxfz5MuhI+GQyxMPmhGrSBdiOgcfvksyVJkiRJkiRllUpXJgsh/BG4CGgL5BS/9iFwFzAsxhhTHE+SJEmSJEmSJEnSCv794b8564mz+HnRz4llHtXiKO459h6a1m6aWKZUqcUifpo6k8Z10h4kfV983ojiP1fImPo4TOgOC79NfpgqtWDnq2G7HpBT6f5ERJIkSZIkSdI6yOpPCkMIJwE3Fz+NwGExxk9Ws34QcP6ypyXeagkMBv4QQjgqxriw7KeVJEmSJEmSJEmSVBpzl8yl51M9eeC9BxLLrFGlBoMOG8TZbc8mhLDmCyStnSUz+fdfN4K/pj1I+o6+ZzrQBBZOhQk9YeqYdAbZ7HjY/TaotXk6+ZIkSZIkSZKyUlaXyYBOwGbFj19bQ5Hsz8AFxU9j8S0U31P8eD9gNHBCuUwrSZIkSZIkSZIkaa28+u2rdB7Tma9nf51YZttN2zK6w2i2b7x9YpmSNjz5Swvg48Hwfl8omJ/8ADU3h7bDYLNjk8+WJEmSJEmSlPWytkwWMl8DuD/Ly2D/Ws3aKsB1xU+XlcgWAB8AjYFtSrx+XAjhyBjjU+U0uiRJkiRJkiRJkqRVWFq4lKtevIobXruBoliUSGZOyOHyfS+n3wH9qJpbNZFMSRuuoSccBm9/kHxwyIXtz4fWV0LV2snnS5IkSZIkSaoQsrZMBmwP1C1+HIFnVrP2CGBLlhfPngQ6xhjnAoQQOgB/Z/nP2xOwTCZJkiRJkiRJkiQl6KOfPqLTmE68/f3biWVu3WBrHuzwIHtvvndimZI2bNtvnEKRrFF7aD8CGrRJPluSJEmSJElShZKT9gCrsW2Jx4uBT1az9k/F9wFYCJyyrEgGEGMcA9xY/H4ADg4h1P3NLpIkSZIkSZIkSZLKXIyR4eOGs9tduyVaJDutzWm82/Vdi2SSKq+qdaHtcDj0dYtkkiRJkiRJktZKNp9MtnnxfQS+jTHG1aw9mOWnkv0rxvjzStbcBfQpfpwLtAFeLoM5JUmSJEmSJEmSJK3C9/O+57THTuPpz59OLLNRjUaMPGYkHXbskFimJCVuiz/B7rdCjU3SnkSSJEmSJElSBZLNZbLaJR7PWdWiEMJ2QFOWl8keW9m6GOPUEMI0YNPil1pgmUySJEmSJEmSJEkqN2M+GsOZj5/JzEUzE8s8YtsjuPfYe9mkjuUKSZVU7a2h7e2w6eFpTyJJkiRJkiSpAsrmMlneWq7bq/g+AEXAS6tZW7JMVn/dxpIkSZIkSZIkSZK0OvOWzOO8p8/jvnfvSyyzepXqDDpsEOe0PYcQQmK5kpSYnKqwY29oeQVUqZH2NJIkSZIkSZIqqGwuk80r8bjhatYdWHwfgY9ijD+vZm1RicfV1nEuSZIkSZIkSZIkSavw2rev0XlMZ76a/VVimbtvsjujTxjNDo13SCxTkhLVZD9ofyfU2yntSSRJkiRJkiRVcNlcJvup+D4AzUMINWKMi0ouCJmvFDyCTJEM4OU17Fm/xOOFZTGkJEmSJEmSJEmSJMgvzOeql67i+levpygWrfmCMpATcrhs38vod0A/8nLzEsmUpETlNYRdB8LWp0LISXsaSZIkSZIkSZVANpfJ3i++j2Tm/D3wzxXWHApsXGLdi2vYc5MSj39a5SpJkiRJkiRJkiRJa+2TGZ/QaUwnJkybkFjmVvW34sEOD7LPFvsklilJidrqlEyRrHqTtCeRJEmSJEmSVIlkc5nsQ+B7oCmZ08muCyE8H2OcCRBCqANcX2L9UuDZVW0WQmgB1Cnx0hdlPrEkSZIkSZIkSZK0AYkxcseEO7j42YtZVLAosdxT25zKkCOGULda3cQyJSkxdbeHdnfCxgemPYkkSZIkSZKkSihry2QxxhhCeAC4lMypY1sDk0MI/wbyyZxUttWy5cAjMcY5q9lyv5LbA5PLfmpJkiRJkiRJkiRpw/DD/B847dHTeOrzpxLLbFijISOPGckJO56QWKYkJSanGrS8AnbqDbnV0p5GkiRJkiRJUiWVtWWyYtcDp5A5nQxgI+Ds4seBTCkMMqeSXbWGvf5QfB+ByTHGeWU4p7JMCOFU4NSVvFUz2UkkSZIkSZIkSZIqn7Efj+XMx89kxsIZiWUevs3h3HvcvWxaZ9PEMiWtnSlToF9vuO+YtCepwJoeAm1vh7ot0p5EkiRJkiRJUiWX1WWyGOO8EMJRwHNAQ5aXxyh+HIAi4OwY46er2ieEsAlwSInrny+fiZVFtgQOSHsISZIkSZIkSZKkymTeknlc8MwF3PPOPYllVq9SnYGHDqRbu26EEBLLlbRm+fkweDBcdRXUyAEsk5Ve9Y1gt1uh+V/Af+MkSZIkSZIkJSCry2QAMcb3Qgg7Af3JnC62UfFbS4GXgKtjjK+uYZueQNVlWwKPl8esyipfk/nfx4pqAu2SHUWSJEmSJEmSJKnie2PKG3Qa04kvZ32ZWOauTXfloRMeYscmOyaWKWntvPIKnHMOTJ6ceV6jTrrzVEjbdoU210Neg7QnkSRJkiRJkrQByfoyGUCMcTrQDegWQqgH1ABmxBgL1nKLZ4E3SzxfWclIlUiM8X7g/hVfDyG0BD5Ieh5JkiRJkiRJkqSKKr8wn6tfvpprX7mWoliUSGYgcOm+l3LlgVeSl5uXSKaktTN9OvTuDQ88kPYkFVj91tBuBDTZK+1JJEmSJEmSJG2AKkSZrKQY4xxgTimveaGcxpEkSZIkSZIkSZIqrU9nfkqnRzoxftr4xDKb12vOgx0eZL/m+yWWKWnNCgth5Ei47DKYPTvtaSqo3JrQ+krY4XzIqZr2NJIkSZIkSZI2UBWuTCZJkiRJkiRJkiSpfMUYGTFxBBc9exEL8xcmlnvKLqdw25G3Ubda3cQyJa3ZxIlw7rkwblzak1Rgmx4NbYdB7S3TnkSSJEmSJEnSBs4ymSRJkiRJkiRJkqRf/Dj/R05/7HSe/OzJxDIbVG/AXcfcxR93+mNimZLWbPZs6NsXbr8diorSnqaCqrEp7H4bbH4ChJD2NJIkSZIkSZJU8ctkIYSmwGHLnscYR6U4jiRJkiRJkiRJklRhPfbJY5zx2Bn8tPCnxDIP3fpQ7jvuPprVbZZYpqTVixEefhguugh+/DHtaSqokAMtusMuV0NVT1uUJEmSJEmSlD0qfJkMaAncD8Ti55bJJEmSJEmSJEmSpFKYv3Q+Fz5zISPfHplYZrXcatx06E10b9+dnJCTWK6k1fvoIzj3XHjxxbQnqcDq7wx73gsNd097EkmSJEmSJEn6jcpQJlsmsLxQJkmSJEw+r4cAAQAASURBVEmSJEmSJGktvDn1TTqP6cznP3+eWGabpm0Y3WE0LTdqmVimpNVbsACuuQYGDYL8/LSnqeAOfAZqNk17CkmSJEmSJElaqcpUJpMkSZIkSZIkSZK0lvIL87n2lWu55uVrKIyFiWQGAr336c2A3w0gLzcvkUxJa/bYY9CzJ3zzTdqTVBI5uWlPIEmSJEmSJEmrZJlMkiRJkiRJkiRJ2sB8NvMzOo3pxLjvxiWWuUW9LXiww4Ps33z/xDIlrd7XX2dKZI8/nvYkkiRJkiRJkqSkWCaTJEmSJEmSJEmSNhAxRka+PZILnrmAhfkLE8vtvHNnhh45lHrV6yWWKWnVliyBQYPgmmtg0aK0p5EkSZIkSZIkJckymSRJkiRJkiRJkrQBmL5gOqc/djpPfPpEYpkNqjfgzt/fyUktT0osU9LqPf88nHsufPJJ2pNIkiRJkiRJktJgmUySJEmSJEmSJEmq5J749AlOf+x0pi+YnljmIVsfwv3H3U+zus0Sy5S0at9/DxdfDA8/nPYkkiRJkiRJkqQ0WSaTJEmSJEmSJEmSKqkFSxdw4TMXctfbdyWWWS23GjcccgM99+hJTshJLFfSyhUUwB13QJ8+MHdu2tNIkiRJkiRJktJmmUySJEmSJEmSJEmqhMZ9N45Oj3Tis58/Syxzl413YfQJo2m1UavEMiWt2ltvwTnnwDvvpD2JJEmSJEmSJClb+FWAkiRJkiRJkiRJUiVSUFTAgJcGsPc9eydWJAsEeu3di7fOeMsimZQFfv4Zzj4b9trLIpkkSZIkSZIk6dcqw8lk04AH0h5CkiRJkiRJkiRJStvnP39O5zGdeXPqm4llbl53c0Z1GMWBWx6YWKaklSsqglGjoFcvmDEj7WkkSZIkSZIkSdmowpfJYowfAV3SnkOSJEmSJEmSJElKS4yRe965h/OfPp8F+QsSy+3YuiPDjhpG/er1E8uUtHKTJsG558Krr6aTv8MO6eRKkiRJkiRJkkonJ+0BJEmSJEmSJEmSJK276Qumc/w/jufMx89MrEhWv3p9/v6HvzP6hNEWyaSUzZ+fOYls113TKZLVrAk33QTPP598tiRJkiRJkiSp9Cr8yWSSJEmSJEmSJEnShurJT5/ktMdOY/qC6YllHrTVQTxw/ANsVnezxDIl/VaM8MgjcN558N136cxwwgkweDBsvjmwOJ0ZJEmSJEmSJEmlY5lMkiRJkiRJkiRJqmAWLF3Axc9ezJ0T70wsMy83jxsOvoHz9jyPnJCTWK6k3/r8c+jRA55+Op38rbeGoUPhqKPSyZckSZIkSZIkrbsKXSYLIWwObAE0AOoA84BZwDcxxqlpziZJkiRJkiRJkiSVh/HfjafTmE58OvPTxDJbb9Sah054iNYbt04sU9JvLV4MN94I118PS5Ykn5+XB5demrnVqJF8viRJkiRJkiRp/VW4MlkI4XfAWcB+wCarWfc98BIwMsb4YjLTSZIkSZIkSZIkSeWjoKiA61+5nqteuorCWJhIZiBw0V4Xcc1B11CtSrVEMiWt3DPPQLdu8MUX6eQfcggMHw7bbZdOviRJkiRJkiSpbFSYMlkIoRXwANBm2UtruGRT4M/An0MIbwOnxhgnl9+EyiYhhFOBU1fyVs1kJ5EkSZIkSZIkSVp/X/z8BZ3HdOaNqW8klrlZ3c0YdfwofrfV7xLLlPRb330H558P//pXOvmbbAKDB8OJJ0JY02/pJUmSJEmSJElZr0KUyUIIpwB3AnlkSmSx+AYrL5XFEo8DsDswIYTQNcY4qjxnVdbYEjgg7SEkSZIkSZIkSZLWR4yRe9+5l/OfOZ/5S+cnlvuXVn9h+FHDaVCjQWKZkn4tPx+GDoX+/WF+cv/3/0VuLvTsCVdeCXXrJp8vSZIkSZIkSSofWV8mCyF0AO4GclleIltWIJsCvAfMABYAtYDGwC7A5sVrlhXLqgH3hBDmxBgfTWZ6pehr4KWVvF4TaJfsKJIkSZIkSZIkSaX304KfOOuJsxj78djEMutVq8cdR9/BX1r/JbFMSb/12mtwzjkwaVI6+XvtBXfcAbvskk6+JEmSJEmSJKn8ZHWZLITQCLiP5UWyACwChgD3xhg/X8212wCnAz2BGsXX5wL3hxC2jTHOLOfxlaIY4/3A/Su+HkJoCXyQ9DySJEmSJEmSJEml8dRnT9Hl0S78uODHxDIP3PJAHjj+Abaot0VimZJ+bcYM6N0b7rsvnfyGDeGmm6BLF8jJSWcGSZIkSZIkSVL5yvaPf/sBdVleJJsE7BRjvHx1RTKAGOMXMcbLgZbF1y07zawu0Kf8RpYkSZIkSZIkSZLWzcL8hXR7shtHPXxUYkWyvNw8bj70Zp47+TmLZFJKiopg5EjYfvv0imRnnAGffAKnn26RTJIkSZIkSZIqs6w9mSyEEIC/sLxI9i2wf4xxTmn2iTF+E0I4EHgH2KJ4r47ABWU5ryRJkiRJkiRJkrQ+JkybQKdHOvHJzE8Sy2y1USseOuEhdt5458QyJf3aO+/AOefAW2+lk7/LLnDHHbDXXuu50cIpZTKPJEmSJEmSJKl8ZfP3ibUHGpMpf0XgotIWyZaJMc4GLmb56WSNQgjty2JISZIkSZIkSZIkaX0UFBVw7cvXstc9eyVaJLtwzwsZf+Z4i2RSSubOhfPOg7Zt0ymS1a4Nt94KEyasZ5GsqAA+GgTP7ltms0mSJEmSJEmSyk/WnkwGtCjxeD7w6Hru9xgwD6hT/Hw7YNx67ilJkiRJkiRJkiStsy9nfUnnMZ15fcrriWU2q9OMB45/gIO3PjixTEnLxQj/+AdceCF8/306M/zpTzBoEDRrtp4bzRgH47vCrHfLYixJkiRJkiRJUgKyuUy2UfF9BL6OMRasz2YxxvwQwtdA6xX2lyRJkiRJkiRJkhIVY+T+d++n59M9mb90fmK5f2r5J+44+g4a1GiQWKak5T75BLp1g+eeSye/RQsYPhwOPXQ9N8qfC+/1gU+HkfmVviRJkiRJkiSposjmMlluiceFZbRnyX1yymhPSZIkSZIkSZIkaa3NWDiDsx4/izEfj0kss161egw/ajh/bf1XQgiJ5UrKWLgQrrsObroJ8vOTz69eHa64Anr1gmrV1mOjGGHqGJjQAxZNK7P5JEmSJEmSJEnJyeYy2fTi+wA0DyGEGOM6f6VZyPxWrHmJl35an+EkSZIkSZIkSZKk0nr686fp8mgXfpj/Q2KZBzQ/gFEdRrFFvS0Sy5S03BNPQI8e8PXX6eQfdRQMHQpbb72eGy34FiZ0h+8eL5O5JEmSJEmSJEnpyObTub4q8bg+cPB67ncw0GAV+0uSJEmSJEmSJEnlZmH+Qnr8pwdHPnRkYkWyqjlVuemQm3ju5Ocskkkp+OYb6NABjjkmnSLZZpvBI49kymzrVSQrKoCPboEnd7JIJkmSJEmSJEmVQDafTPYGMA+oTeZ0sptDCO1ijPml3SiEUBUYWOKl+cDrZTKlJEmSJEmSJEmStBpvf/82HR/pyMczPk4ss2WTlow+YTRtmrZJLFNSxtKlcOutMGAALFyYfH6VKnDhhdC3L9SuvZ6bzRwP486CWe+WxWiSJEmSJEmSpCyQtSeTFZfGHiNTJItAa+CxEEKpPu4OIdQExgC7LNsaGBtjLCjDcSVJkiRJkiRJkqRfKSwq5PpXrmePu/dItEh2/h7nM+GsCRbJpBS8+CK0aQOXXppOkWz//eHdd+HGG9ezSJY/Fyb0hGf2sEgmSZIkSZIkSZVMNp9MBtAXOBGoSqZUdhjwUQihH/CPGOMqP34vLpGdBAwAmpEpkQVgKdC/nOeWJEmSJEmSJEnSBuyrWV9x8tiTefXbVxPL3LTOpjxw/AMcsvUhiWVKyvjxR7j4Yhg9Op38Jk3g5puhc2cIYT02ihGmjoEJPWDRtDKbT5IkSZIkSZKUPbK6TBZj/DqEcClwC8vLYM2Au4HbQgjjgfeBGcACoBbQiMwpZO2Amiw/2Yzi+0tijF8n+GNIkiRJkiRJkiRpAxFjZNR7o+jxVA/mLZ2XWO5JLU/ijqPvoGGNhollSoLCQhgxAi6/HObMST4/BDj7bLj2WmjQYD03W/AtTOgO3z1eJrNJkiRJkiRJkrJTVpfJAGKMg0MIjYArWF4KC2SKYwcU31Zm2fetxRKPr44x3lZes0qSJEmSJEmSJGnDNXPhTLo+0ZV/f/TvxDLrVqvL8KOG07F1R8J6HUckqbTGj4dzzoGJE9PJ3313uOMOaNduPTcqKoBPboNJ/aBgQZnMJkmSJEmSJEnKXllfJgOIMfYNIYwD7gI2ZnmpbJmSvxkreQpZKL79CJwZY3yivGeVJEmSJEmSJEnShueZz5+hy6Nd+H7+94ll7t98f0YdP4rm9ZsnlikJZs2CK66AO++EuOJvrhNQr17mJLKzz4bc3PXcbOZ4GHcWzHq3LEaTJEmSJEmSJFUAFaJMBhBjfDyEsDXQGTgd2A1Y2Ufjy4plhcBE4G7goRjjokQGlSRJkiRJkiRJ0gZjUf4iLvnfJQwdNzSxzKo5VbnmoGu4aK+LyM1Z3yaJpLUVI4weDRdfDNOnpzNDp04wcCA0bbqeG+XPhff6wKfD+O13uUqSJEmSJEmSKrMKUyYDKC6E3QXcFUKoBbQFmgMNgNrAfGAW8A0wIca4IK1ZJUmSJEmSJEmSVLm98/07dHykIx/N+CixzJ2a7MToDqPZdZNdE8uUBJMnw7nnwssvp5O/445w++1w4IHruVGMMHUsTOgBi74rg8kkSZIkSZIkSRVN1pbJQgi5QK0SLy2KMeYve1JcFHsp8cEkSZIkSZIkSZK0QSssKmTg6wPp90I/8ovy13xBGenZvic3HHIDNarWSCxT2tAtWAADBsAtt0BBQfL5NWpA//5wwQWQl7eemy34NlMi++6xMplNkiRJkiRJklQxZW2ZDDgFGFni+aHA8ynNIkmSJEmSJEmSJPH17K85eczJvPLtK4llblpnU+4/7n4O3ebQxDKlDV2M8Oij0LMnTJmSzgzHHQdDhkDz5uu5UVEBfDoU3u8LBQvKZDZJkiRJkiRJUsWVzWWyjYFQ/Hh2jNEimSRJkiRJkiRJklIRY2T0+6Pp9p9uzFs6L7HcP+70R+48+k4a1WyUWKa0ofvyy0yJ7Mkn08nfcku47TY45pgy2GzmBBh3Fsx6pww2kyRJkiRJkiRVBtlcJptffB+Bb9IcRJIkSZIkSZIkSRuunxf9zNlPnM0/P/xnYpl18uow7KhhdN65MyGENV8gab0tWQIDB8K118LixcnnV60KvXvD5ZdDzZrruVn+XHivL3w2DGJRmcwnSZIkSZIkSaocsrlM9n3aA0iSJEmSJEmSJGnD9t8v/supj57KtHnTEsvcd4t9ebDDg2xZf8vEMqUN3f/+B926waefppN/0EEwfDjssMN6bhQjTB0LE3rAou/KYjRJkiRJkiRJUiWTk/YAq/FR8X0ANk9zEEmSJEmSJEmSJG1YFuUv4vynz+ew0YclViSrklOF6w++nhdPedEimZSQadPgz3+GQw9Np0jWtCk8/HCmzLbeRbIF38LLx8MrJ6RQJAuwVZeEMyVJkiRJkiRJ6yJrTyaLMU4OIUwGWgINQgh7xBjfSnsuSZIkSZIkSZIkVW7v/vAuHR/pyIc/fZhY5o6Nd2T0CaPZbZPdEsuUNmQFBZmTwPr2hXnzks/PyYHu3WHAAKhXbz03KyqAT4fC+32hYEGZzFcq9VtD+7ug9jbw1X3J50uSJEmSJEmSSiWbTyYDuKvE46tSm0KSJEmSJEmSJEmVXmFRITe9dhPtR7ZPtEjWo30PJp410SKZlJA33oC2beH889Mpku2xB0yYAEOGlEGRbOYEeKY9vH1h8kWy3BrQ5kY4YiI03jPZbEmSJEmSJEnSOsvak8mK3Q6cBOwDHBpCuDnGeHHKM0mSJEmSJEmSJKmS+Wb2N5wy9hRe+ualxDKb1m7K/cfdz+HbHp5YprQhmzkTLr0U7r47nfwGDeCGG+CMMzInk62X/LnwXl/4bBjEojKZr1Q2OQLa3Q61t1r+WrVGcML05GfJRtUapT2BJEmSJEmSJK1SVpfJYoyFIYRjgMeAfYELQgjtgX4xxhdTHU5ZLYRwKnDqSt6qmewkkiRJkiRJkiQpm8UYeWjSQ3T7TzfmLpmbWO4JO57AiN+PoHHNxollShuqoiK4/37o3TtTKEtDly5w443QpEkZbDZlDEzoAYu+K4PNSql6U9h9CGxxIoTw6/dCDlQvix9QkiRJkiRJklSesrpMFkLoV/zwJaAFsDGZU8qeCyH8CEwAvgLmAvml2TvGOKAMR1X22RI4IO0hJEmSJEmSJElS9pq1aBbnPHkO/5j8j8Qya+fVZuiRQzlll1MIKxYxJJW599+Hc86B119PJ79VK7jjDth33zLYbMEUmNgDpj5aBpuVVoAWZ8Mu10Fe/RTyJUmSJEmSJEllJavLZMCVQCzxPALLfqvWFDh6Pfa2TFa5fU2mhLiimkC7ZEeRJEmSJEmSJEnZ5rkvn+OUsafw3bzkTvbZZ/N9GNVhFFs32DqxTGlDNW8e9O8Pt90GhYXJ59eqBVddBT17QtWq67lZUQF8Ogze7wMFC8pkvlKp3xrajYAmeyWfLUmSJEmSJEkqc9leJluZuOYlqxXKYA9luRjj/cD9K74eQmgJfJD0PJIkSZIkSZIkKTssLljM5c9dzq1v3ppYZpWcKlx14FVcss8l5ObkJpYrbYhihH/+Ey64AKZNS2eGP/4Rbr0VNtusDDb7eSK8dRbMersMNiul3BrQ+krY4QLIWd9GnCRJkiRJkiQpW1SEMllY8xJJkiRJkiRJkiRp9d774T06jenEB9OT+9657Rttz0MnPMTum+6eWKa0ofrsM+jeHZ59Np38bbaBYcPgiCPKYLP8efB+X/h0KMSiMtiwlDY5AtrdDrW3Sj5bkiRJkiRJklSusr1M9ru0B5AkSZIkSZIkSVLFVhSLuOWNW7ji+StYWrg0sdxu7bpx06E3UbNqzcQypQ3RokVwww2Z29Lk/i/+i2rV4LLL4JJLoHr1MthwyliY0B0WfVcGm5VS9aaw+xDY4kQIfu+rJEmSJEmSJFVGWV0mizG+lPYMkiRJkiRJkiRJqri+nfMtp4w9hRe/fjGxzKa1m3LvsfdyZIsjE8uUNlRPPZU5jezLL9PJP/xwGDoUWrQog80WTIGJPWDqo2WwWWkFaHE27HId5NVPIV+SJEmSJEmSlJSsLpNJkiRJkiRJkiRJ6+rhSQ9z7pPnMmfJnMQyj9/heEYeM5LGNRsnliltiKZMgQsugH//O538Zs1g8GD4wx/K4ACvogL4dBi83wcKFpTFeKVTvzW0GwFN9ko+W5IkSZIkSZKUOMtkkiRJkiRJkiRJqlRmLZrFuf85l79/8PfEMmvn1WbIEUPo0qYLYb2bJZJWJT8fhgyBK6+EBSn0rnJz4fzzoX9/qFOnDDb8eSK8dRbMersMNiul3BrQuj/scCHkVE0+X5IkSZIkSZKUCstkkiRJkiRJkiRJqjSe/+p5Thl7ClPnTk0sc+/N9+bBDg+ydYOtE8uUNkSvvALnnAOTJ6eTv88+cMcd0Lp1GWyWPw/e7wufDoVYVAYbltImR0C74VDbf7ckSZIkSZIkaUNjmUySJEmSJEmSJEkV3pKCJVzx/BUMemNQYplVcqrQ/4D+XLrvpVTJ8dduUnmZPh1694YHHkgnv3FjGDgQTj4ZcnLKYMMpY2FiD1iYXOn1F9U3ht2HwBYngacoSpIkSZIkSdIGKat/qxVCqAGcWOKlN2KMn63DPtsBe5Z46W8xxvz1nU+SJEmSJEmSJEnpm/TjJDo+0pFJ0ycllrldo+0Y3WE07Zq1SyxT2tAUFsLIkXDZZTB7djoznHUWXHcdNGpUBpstmJIpkU19tAw2Wwfbng1troe8+unkS5IkSZIkSZKyQlaXyYC/AncVP14KbL2O+8wv3qdq8fN84G/rN5okSZIkSZIkSZLSVBSLGPzmYC577jKWFi5NLPectucw8NCB1MqrlVimtKF5+2045xwYNy6d/DZt4I47YM8917h0zYoK4NNh8H5fKJhfBhuWUr1W0H4ENNk7+WxJkiRJkiRJUtbJ9jLZqUAAIvCvGOP367JJjHFaCOER4M8l9rVMJkmSJEmSJEmSVEFNmTOFUx89lee/ej6xzI1rbcy9x93LUS2OSixT2tDMng19+8Ltt0NRUfL5devC/7N3n+FR1fn7x98nIfTebUhTugIK9t776m+bigoWIIAgiCBSBEVBkKJIEbvgrqu79t57AQWkiYoKCEhRegsp5/8guIv+kSIz50yS9+u6cs1kOPO5P3lgHuR4z3fw4PwiW7FE3E1f9Tl82h5WT0vAsD2UXgqa3QwNe0Baxq6vlyRJkiRJkiQVCSlbJguCoAJwJPlFMoAn9nLk4/yvTHZ8EASlwjDcvJczJUmSJEmSJEmSFLHHZz9O5ouZrNmyJrLMCxpcwH3n3Ue1MtUiy5SKkjCEf/wDrr8eli+PZ4eLL4YRI2CffRIwLHs9zBwAX98NYQytuH3OgFbjoGzd6LMlSZIkSZIkSSktZctkQHMgfdvzEHhvL+e9u21OABTfNv/jvZwpSZIkSZIkSZKkiKzZsobOL3XmH7P+EVlmmYwy3HXmXVzZ4kqCIIgsVypKvvwSOneGt9+OJ79BAxg7Fk45JUEDFz8Ln3WBTYsTNHAPlKwBh90Ftf4K/s6SJEmSJEmSJO1AKpfJDt7u+aIwDNfuzbAwDNcGQfADUGvbSw2wTCZJkiRJkiRJklQgvP3921zxzBX8sO6HyDKP3P9IJl04ifqV60eWKRUlmzbB4MFw552QnR19fsmS0L9//mloJUokYODGH+DzrrD4mQQM+wPqd4TmQ6B4xXjyJUmSJEmSJEkFQiqXySpuewyBnxI0cyX/K5NVTtBMSZIkSZIkSZIkJUlWThb93urHiI9HEBJGkpkepHPzCTfT57g+FEtL5dtpUsH13HPQtSssXBhP/rnnwt13Q506CRiWlwtf3wMz+0HOhgQM3EMVmkLre6Ha0dFnS5IkSZIkSZIKnFS++5W23fMgQTO3n5OIz5aTJEmSJEmSJElSksxeMZtLn7qUmctnRpZ5UOWDmHzRZFrv1zqyTKkoWbAgv0T2/PPx5NeqlV8iO/98CBJxF3rV5zClQ/5j1NJLQbOboWEPSMuIPl+SJEmSJEmSVCClcpnsl9PIAqBmgmbW2O756gTNlCRJkiRJkiRJUgLlhXnc9cld9HmzD1m5WZHldjisAyNOH0GZ4mUiy5SKiq1bYcQIuPVW2Lw5+vxixaBnT+jXD8ok4j/x7PUwcwB8fTeEeQkYuIf2OQNajYOydaPPliRJkiRJkiQVaKlcJlux3fN9giCoFYbhoj86LAiCWsB+QLiD+ZIkSZIkSZIkSUoBi9ctpu0zbXnz+zcjy6xepjoPnP8A5x58bmSZUlHy1lvQuTPMmxdP/oknwtix0LhxggYufhY+6wKbFido4B4oWQNajoYD/5ago9UkSZIkSZIkSUVNKpfJPuV/xS+AS4EhezGvzbbHYNvcqXsxS5IkSZIkSZIkSQn2xJwn6PBCB9ZsWRNZ5nkHn8f9599P9TLVI8uUioply/JPA3vssXjyq1fPPw3t0ksT1Lva+AN83hUWP5OAYX9A/Q7QfCgUrxhPviRJkiRJkiSpUEjZMlkYhiuCIJgFNCO/ANYrCIJHwjBcuqezgiDYD7iB/BJZAHwVhuEPCV1YkiRJkiRJkiRJf8jaLWvp8nIXJs+cHFlm6YzSjD5jNFe3vJrA032khMrNhfHjoW9fWLcu+vwggE6dYPBgqFgxAQPzcuHre2BmP8jZkICBe6hCE2g9EaodHX22JEmSJEmSJKnQSdky2TYTgXvIL4FVAF4JguDUMAxX7O6AIAhqAK9sez/bZk1M9KKSJEmSJEmSJEnac+8ueJfLn7mcRWsXRZZ5xH5HMOnCSRxU5aDIMqWiYsoU6NgRpk+PJ//ww2HCBDjssAQNXPU5TOmQ/xi19JLQ9GZo2APSi0efL0mSJEmSJEkqlNLiXmAX7gN+uXMYAk2B2UEQXBEEQcbO3hgEQUYQBG2BWUDjbe8HWAyMS866kiRJkiRJkiRJ2h1ZOVn0fr03Jz1yUmRFsvQgnYEnDOSDKz+wSCYl2KpV+SWyI4+Mp0hWsWL+aWiffJKgIln2Bvi8O7zaOp4iWc3T4Zw50ORGi2SSJEmSJEmSpIRK6ZPJwjDMDoLgYuAtoDj5hbCqwIPA8CAI3gI+A1YAG4CyQHXgcOBkoAoQbHtfAGwBLg7DcGvEP4okSZIkSZIkSZK2mbNiDpc+dSlfLP8issz6lesz+cLJHLH/EZFlSkVBGMIjj8ANN8BPP8WzwxVXwLBhUL16ggYufg4+6wKbfkjQwD1Qsga0HA0H/g2CIPp8SZIkSZIkSVKhl9JlMoAwDD8OgqAd8DCQwf+KYVWBv2z72pFf/rL+y/VZwBVhGH6U1IUlSZIkSZIkSZK0Q3lhHmM+HUPvN3qTlZsVWW77lu0ZccYIyhYvG1mmVBTMng2ZmfDBB/HkN26cfxrZ8ccnaOCmxfBZV1j8dIIG7qH6HaD5ECheKZ58SZIkSZIkSVKRkPJlMoAwDB8PguBb4AngQPILYr/Y0cexhdtdEwDfAn8Lw3BaUheVJEmSJEmSJEnSDi1Zt4R2z7bj9e9ejyyzWulq3H/+/Zzf4PzIMqWiYMMGGDQIRo2C3Nzo80uXhoED4brrICMjAQPzcuGbsfBFX8jZkICBe6hCE2h9L1Q7JvpsSZIkSZIkSVKRUyDKZABhGE4NgqAB0BboBjTayeW/FMxmAXcBk8IwzE7uhpIkSZIkSZIkSdqRJ+c8SYcXOrB6y+rIMs89+FzuP+9+apStEVmmVNiFITz1VH6Ja/HieHa46KL8ElutWgkauGoaTOkAqz5L0MA9kF4Smt4MDXtAevHo8yVJkiRJkiRJRVKBKZMBhGG4FZgITAyCYD/gOKAeUBkoB6wHVgHfAO+HYfhjXLtKkiRJkiRJkiQVdWu3rKXrK1159ItHI8ssnVGakaePpP1h7QmCYNdvkLRbvv0WunSBV16JJ79OHbjnHjj77AQNzN4AMwfA13dBmJegoXug5unQahyUqxd9tiRJkiRJkiSpSCtQZbLthWG4BHg87j0kSZIkSZIkSZL0/3t/4ftc9vRlLFy7MLLMVvu2YvJFkzm4ysGRZUqF3ZYtMGwY3H47ZGVFn1+8OPTuDX36QKlSCRq6+Dn4rAts+iFBA/dAyerQ8i448G9g4VWSJEmSJEmSFIMCWyaTJEmSJEmSJElS6tmau5Wb376ZOz68g5Awksy0II1+x/Wj3/H9yEjPiCRTKgpeew06d4b58+PJP/VUGDsWDk5UP3TTYvisKyx+OkED91D99tB8KBSvFE++JEmSJEmSJElYJpMkSZIkSZIkSVKCzF05lzZPtWH6sumRZdarVI9JF07iqAOOiixTKuyWLIHu3eHJJ+PJ32cfGD0a/vKXBB3elZcL34yFL/pCzoYEDNxDFZpA63uh2jHRZ0uSJEmSJEmS9BuWySRJkiRJkiRJkrRX8sI8xk4ZS683erElZ0tkuVe3uJpRZ46ibPGykWVKhVlODowZAwMGwIYYOldpadC1KwwaBOXLJ2joqmkwpQOs+ixBA/dAekloOgAaXg/pxaPPlyRJkiRJkiRpByyTSZIkSZIkSZIk6Q9bun4p7Z5tx2vfvhZZZtXSVbn/vPu5oOEFkWVKhd2HH0KnTjBzZjz5Rx0F48ZB8+YJGpi9AWYOgK/vgjAvQUP3QM3TodU4KFcv+mxJkiRJkiRJknYiljJZEATH//a1MAzf253rEmVHeZIkSZIkSZIkSdp9/577bzq80IFVm1dFlnn2QWfzwPkPULNszcgypcLsp5+gd2948MF48itXhmHDoF27/JPJEmLxc/BZF9j0Q4IG7oGS1aHlaDjw7xAE0edLkiRJkiRJkrQLcZ1M9g4Qbvd9yI53+e11ifJ7eSokgiBoC7TdwT+VjnYTSZIkSZIkSZIKn3VZ6+j6clce+eKRyDJLFSvFyDNG0uGwDgQWNKS9lpeXXyDr3RtWRdcH/ZWrroKhQ6Fq1QQN3LQEPu8KPzyVoIF7qH57aD4UileKJ1+SJEmSJEmSpN0Qd6Fqd+/0eUdQe6o2cELcS0iSJEmSJEmSVNh8sOgDLnv6MhasWRBZ5uH7Hs7kCyfToGqDyDKlwmzGDMjMhE8+iSf/kENg/Hg4+ugEDczLhW/GwRd9IWd9gobugQqNofVEqHZM9NmSJEmSJEmSJO2hOMtkFsmUTAuAd3fwemmgVbSrSJIkSZIkSZJU8G3N3crAdwZyx4d3kBfmRZKZFqRx07E3MeCEAWSkZ0SSKRVm69bBgAEwZkz+yWRRK1sWbr0VunSBYom6U71qOkxpD6s+S9DAPZBeEpoOgIbXQ3rx6PMlSZIkSZIkSfoD4iqTDUrwddKvhGH4MPDwb18PgqAJMDvqfSRJkiRJkiRJKsi+XPklbZ5uw7Qfp0WWWbdSXSZdOImjD0jU0UVS0RWG8K9/QY8e8OOP8ezwt7/BiBGw334JGpi9AWbdDF+NhogKrr9S8zRoNR7K1Ys+W5IkSZIkSZKkvRBLmSwMw90qie3udZIkSZIkSZIkSUq8MAwZN3UcPV/vyZacLZHlXtn8SkafOZpyJcpFlikVVl99BZ07w5tvxpNfvz6MHQunn57AoYufh886w6YfEjh0N5WsDi1Hw4F/hyCIPl+SJEmSJEmSpL0U18lkkiRJkiRJkiRJSmE/rv+RK5+7klfmvxJZZpVSVbjvvPu4sNGFkWVKhdXmzXD77TBsGGzdGn1+iRLQty/ccAOULJmgoZuWwOdd4YenEjRwD9W7BlrcAcUrxZMvSZIkSZIkSVICWCaTJEmSJEmSJEnSrzz15VO0f749P2/+ObLMM+ufyYPnP8g+5faJLFMqrF58Ea69Fr7/Pp78s86CMWOgXr0EDczLhW/GwRd9IWd9gobugQqNodW9UP3Y6LMlSZIkSZIkSUowy2SSJEmSJEmSJEkCYH3Werq90o2HZjwUWWbJYiUZcfoIMg/PJAiCyHKlwmjRIujWDZ55Jp78/feHu+6CCy+EhP3nvGo6TGkPqz5L0MA9kF4SmvaHhj0hvXj0+ZIkSZIkSZIkJYFlMkmSJEmSJEmSJPHhog+57OnL+H5NdEcZHbbPYUy+aDINqzaMLFMqjLZuhVGj4JZbYNOm6POLFYPu3WHAAChbNkFDszfArJvhq9EQ5iVo6B6oeRq0Ggfl6kefLUmSJEmSJElSElkmkyRJkiRJkiRJKsKyc7MZ9O4ghnwwhLyIChtpQRp9ju3DgBMGUNzTfqS98u670KkTzJ0bT/5xx8G4cdC0aQKHLn4ePusMm35I4NDdVLI6tBwFB16cwOPVJEmSJEmSJElKHQW2TBYEQXGgPFAK2OO/4odhuCjhS0mSJEmSJEmSJBUg836aR5un2vD5j59HllmnYh0mXTiJY2odE1mmVBgtXw433ACTJsWTX60a3HknXHZZAjtXm5bA513hh6cSNHAP1bsGmg+FEpXjyZckSZIkSZIkKQIFpkwWBEFV4BLgLKAFUG0vxoUUoJ9dkiRJkiRJkiQpkcIwZPxn4+n5Wk8252yOLLdd83aMPnM05UuUjyxTKmxyc+Hee+Gmm2Dt2ujzgwA6dIDbboPKiepc5eXCN+Pgi76Qsz5BQ/dAhcbQ6l6ofmz02ZIkSZIkSZIkRSzlC1VBEATAjUBf8k8hgz9wEpkkSZIkSZIkSZJg2YZlXPnslbw8/+XIMiuXqsx9593HRY0uiixTKow++wwyM/Mf49CyJYwfD61bJ3Do6hnwaXtYNTWBQ3dTWgloNgAa9oT04tHnS5IkSZIkSZIUg5QukwVBkA78A/gz/yuQhdu+LJRJkiRJkiRJkiTtgWfmPcM1z1/DT5t+iizzjHpn8OAFD7JvuX0jy5QKm9WroV+//CJXGEafX7483H47dOwI6ekJGpq9AWYNhK9GQ5iboKF7oOZp0GoclKsffbYkSZIkSZIkSTFK6TIZcD3wl23PfymQBcAKYDbwM7ApntUkSZIkSZIkSZIKhvVZ6+n+ancemP5AZJkli5Vk+GnD6dyqM0HgZwRKf0QYwuTJ0LMnrFgRzw5t2sDw4VCzZgKHLnkBpnaGTYsSOHQ3lagGh42GAy8GfzdJkiRJkiRJkoqglC2TBUFQAujLr0tkbwH9wjD8JM7dJEmSJEmSJEmSCoqPf/iYNk+34bvV30WW2aJmCx676DEaVWsUWaZU2MydC506wbvvxpPfsCGMGwcnnZTAoZuWwOfd4If/JHDoHqh3DTQfCiUqx5MvSZIkSZIkSVIKSNkyGXAiUI78MlkIPAX8LQzDvDiXkiRJkiRJkiRJKgiyc7O59b1bue3928iL6PZKQMCNx97IwBMHUjy9eCSZUmGzcSPceiuMGAE5OdHnlyoFAwZAjx5QPFH/Geflwjfj4YubIGd9gobugQqNodW9UP3Y6LMlSZIkSZIkSUoxqVwmq7/tMQDygG4WySRJkiRJkiRJknbt65+/ps1TbZi6dGpkmQdWOJBJF07iuAOPiyxTKkzCEJ59Frp2hR9+iGeHCy6A0aOhdu0EDl09Az5tD6ui+330X2kloGl/aHQDWHCVJEmSJEmSJAlI7TJZ+W2PIfB1GIZL41xGkiRJkiRJkiQp1YVhyL2f38v1r13PpuxNkeVecegV3H3W3ZQvUX7XF0v6/3z3XX6J7MUX48mvXRvuvhvOOy+BQ7M3wKyB8NVoCHMTOHg31TwVWo2HcvV3fa0kSZIkSZIkSUVIKpfJVm/3fF1sW0iSJEmSJEmSJBUAyzcs56rnruLFb6Jro1QuVZl7z72XPzf+c2SZUmGSlQXDh8Ntt8GWLdHnZ2TADTdA375QunQCBy95AaZ2hk2LEjh0N5WoBi1HQe1LIAiiz5ckSZIkSZIkKcWlcpls1nbPa8S2hSRJkiRJkiRJUop77qvnuPq5q1m5aWVkmafVPY2H//Qw+5bbN7JMqTB54w3o3Bm+/jqe/JNPhrFjoWHDBA7dtAQ+7wY//CeBQ/dAvauh+R1QonI8+ZIkSZIkSZIkFQCpXCb7BFgJVANqBUFQKwzDGD66TpIkSZIkSZIkKTVt2LqBHq/24L5p90WWWSK9BMNOG0aX1l1IC9Iiy5UKi6VL4frr4fHH48mvWRNGjoS//z2BB3fl5cI34+GLmyBnfYKG7oHyjaD1vVD9uOizJUmSJEmSJEkqYFK2TBaGYW4QBKOA27e9dD3QLcaVJEmSJEmSJEmSUsYniz/hsqcvY/6q+ZFlNq/ZnMkXTqZJ9SaRZUqFRU5O/klg/fvD+hj6Vmlp+Seh3XorVKiQwMGrZ8Cn7WHV1AQO3U1pJaBpf2h0A6QXjz5fkiRJkiRJkqQCKGXLZNvcCVwItAI6BUHwThiGT8e8kyRJkiRJkiRJUmyyc7O57f3bGPzeYHLD3EgyAwJ6HdOLW066heIWNqQ99sknkJkJM2bEk9+6NYwfDy1bJnBozkaYeTN8NRoi+l30KzVOgdYToFz96LMlSZIkSZIkSSrAUrpMFoZhThAEZwOvA82BfwVBMBQYHoZhDJ/XJ0mSJEmSJEmSFJ9vfv6GNk+3YcqSKZFlHljhQB698FGOP/D4yDKlwuLnn6FPH7jvvnjyK1WCoUPh6qvzTyZLmCUvwtROsGlRAofuphLVoOUoqH0JBEH0+ZIkSZIkSZIkFXApXSYDCMPw5yAIjgZGA9cAfYHrgiB4HZgGrAS2/IG5jyZyT0mSJEmSJEmSpGQJw5D7pt1H91e7syl7U2S5lx1yGWPOGkOFkhUiy5QKg7w8ePhh6NUrv1AWh7ZtYdgwqFYtgUM3LYXPu8EP/07g0D1Q72pofgeUqBxPviRJkiRJkiRJhUDKl8kAwjDcEgTBc8AJQAOgLPCnbV9/lGUySZIkSZIkSZKU8lZsXMFVz13FC1+/EFlmpZKVmHDuBP7a5K+RZUqFxcyZ0KkTfPhhPPlNm8K4cXDccQkcmpcL8yfAjD6Qsz6Bg3dT+UbQ+l6onsgfSpIkSZIkSZKkoinly2RBEFQBHgNO2/ZS+NtL9mBcuO36386QJEmSJEmSJElKOc9/9TxXPXcVKzetjCzz1Lqn8vAFD7Nf+f0iy5QKg/XrYeBAuOsuyM2NPr9MGRg0CLp2hYyMBA5ePQOmdICfpyRw6G5KKwFN+0GjXpBePPp8SZIkSZIkSZIKoZQukwVBUBF4F2jEr0tge1Ig+9XIBKwlSZIkSZIkSZKUVBu3bqTHqz2YOG1iZJkl0ktwx6l3cO0R15IWpEWWKxV0YQj//jdcdx0sXRrPDn/+M4waBfvvn8ChORth1kCYNwrCGNpxNU6BVuOh/EHRZ0uSJEmSJEmSVIildJkMGA40Jr9E9supYmuA14DZwM/ApriWkyRJkiRJkiRJSrQpS6bQ5qk2fLPqm8gyD61xKJMvmkzT6k0jy5QKg2++gS5d4LXX4smvVw/uuQfOPDPBg5e8CJ91ho0LEzx4N5SoCi1HQe1LIfCzQiVJkiRJkiRJSrSULZMFQVANuJz/lchC4GZgWBiGWXHuJkmSJEmSJEmSlGg5eTnc9t5t3PrereRGdApQQEDPo3ty60m3UqJYiUgypcJg82YYOjT/a+vW6PNLlIAbb8z/KlkygYM3LYXPu8EP/07g0D1Q7ypofgeUqBJPviRJkiRJkiRJRUDKlsmAE4EM/ncq2c1hGA6OdSNJkiRJkiRJkqQkmL9qPm2easOnSz6NLLNWhVo8+qdHOaH2CZFlSoXBK6/kn0b27bfx5J9+ev5pZAcdlMChebkwfwJ8cRNkr0vg4N1UviG0vheqHx99tiRJkiRJkiRJRUwql8lqb3sMgC3AyPhWkSRJkiRJkiRJSrwwDHlg+gNc98p1bMzeGFnupc0u5Z6z76FiyYqRZUoF3Q8/QPfu8J//xJO/334wejT83/9BECRw8OovYEp7+HlKAofuprQS0LQfNLoB0j0dUZIkSZIkSZKkKKRymSx322MIfB2G4aY4l5EkSZIkSZIkSUqkFRtXcM3z1/DcV89FllmxZEUmnDOBvzX9W2SZUkGXnQ133QUDB8LG6Dqf/5WeDtddBzffDOXKJXBwzkaYNRDmjYIwd5eXJ1yNU6DVeCifyCPWJEmSJEmSJEnSrqRymWzxds+zY9tCkiRJkiRJkiQpwV78+kWufO5KVmxcEVnmyXVO5pE/PcL+5fePLFMq6D74ADIzYfbsePKPPhrGj4dDDknw4CUvwWedYOPCBA/eDSWqQstRUPvSBB+xJkmSJEmSJEmSdkcql8nmbHsMgAPiXESSJEmSJEmSJCkRNm7dSM/XejLh8wmRZZZIL8GQU4bQ7chupAVpkeVKBdnKldCrFzz8cDz5VarA8OFwxRWQlsj/bDcthWnXwaInEzh0D9S7CprfASWqxJMvSZIkSZIkSZJSt0wWhuGcIAhmAM2BakEQtAzDcFq8W0mSJEmSJEmSJP0xU5dM5dKnLuWbVd9EltmsejMeu+gxmtVoFlmmVJDl5cF990GfPrB6dTw7tG8Pt9+eXyhLmLxcmH8vfNEHstclcPBuKt8QWt8L1Y+PPluSJEmSJEmSJP1KypbJthkJPLrt+WDg7Bh3kSRJkiRJkiRJ2mM5eTkMeX8Ig94dRG6YG0lmQMD1R13P4JMHU6JYiUgypYJu2jTIzIQpU+LJb94cxo+HI49M8ODVX8CUDvDzpwkevBvSSkDTftDoBkj3d5EkSZIkSZIkSakgpctkYRhODoLgdKANcEYQBKPCMOwe916SJEmSJEmSJEm749tV33LZ05fx8eKPI8s8oPwBPPKnRzipzkmRZUoF2dq10L8/jB2bfzJZ1MqVg8GDoVMnKJbIu7c5G2HWIJg3EiIqsv5KjZOh1QQof1D02ZIkSZIkSZIk6XeldJlsm7bAOqAT0DUIgsOBm8MwfCvWrSRJkiRJkiRJkn5HGIY8OP1Bur3SjY3ZGyPLvaTZJYw9eywVS1aMLFMqqMIQ/vlP6NEDli+PZ4eLL4YRI2CffRI8eMlL8Fkn2LgwwYN3Q4mq0HIk1G4DQRB9viRJkiRJkiRJ2qmULpMFQfDgdt8uAGoDRwOvB0GwBpgGrAS27OHoMAzDqxKwoiRJkiRJkiRJ0q+s3LiS9i+055l5z0SWWaFEBcafM56Lm10cWaZUkM2bl38S2Ntvx5N/8MEwbhycckqCB29aCtOug0VPJnjwbqp7JbQYBiWqxJMvSZIkSZIkSZJ2KaXLZOSfShZu930I/PLxdZWAk//AzGDbHMtkkiRJkiRJkiQpoV765iWufPZKlm+M7pijk2qfxMN/ephaFWpFlikVVJs2wW23wfDhkJ0dfX7JktCvH/TsCSVKJHBwXi7Mvxe+6APZ6xI4eDeVbwitJkCNE6LPliRJkiRJkiRJeyTVy2Q7Eu76EkmSJEmSJEmSpOhsyt7EDa/dwLjPxkWWWTy9OLeffDvdj+pOWpAWWa5UUD3/PFx7LSxcGE/+OefAmDFQp06CB6/+AqZ0gJ8/TfDg3ZBWApr0hca9ID2R7ThJkiRJkiRJkpQsBaFMFuz6EkmSJEmSJEmSpHh8tvQz2jzVhq9+/iqyzKbVm/LYRY9xSI1DIsuUCqoFC6BbN3juuXjya9WCu++G88+HIJF3PnM2wqxBMG8khLkJHLybapwMrcZD+YOjz5YkSZIkSZIkSX9YqpfJEv25fJIkSZIkSZIkSQmRk5fDHR/cwcB3B5KTlxNZbo8je3DbKbdRsljJyDKlgmjrVhgxAm69FTZvjj6/WDHo2RP69YMyZRI8fMlL8Fln2LggwYN3Q4mq0HIk1G6T4HacJEmSJEmSJEmKQkqXycIwXBj3DpIkSZIkSZIkSb/13ervuOzpy/joh48iy9yv3H488qdHOKXuKZFlSgXVW29B584wb148+SecAOPGQePGCR68+Uf4vBssejLBg3dT3SuhxTAoUSWefEmSJEmSJEmStNdSukwm/VFBELQF2u7gn0pHu4kkSZIkSZIkqTAJw5CHZzxM11e6smHrhshy/97074w7exyVSlWKLFMqiJYtyz8N7LHH4smvXj3/NLRLL03woV1hHsy/F2bcCNnrEjh4N5VvCK0mQI0Tos+WJEmSJEmSJEkJZZlMhVVtwLtZkiRJkiRJkqSE+WnTT7R/vj1Pz3s6sswKJSow7pxxXNLsksgypYIoNxfGj4e+fWFdDF2rIIBOnWDwYKhYMcHDV8+EKe3h508TPHg3pBWHJv2gcS9ILxF9viRJkiRJkiRJSjjLZCqsFgDv7uD10kCraFeRJEmSJEmSJBV0r8x/hXbPtmPZhmWRZZ5w4Ak8euGj1KpQK7JMqSCaMgUyM2HatHjyDz88v8h2+OEJHpyzEWbdAvNGQJib4OG7ocbJ0Go8lD84+mxJkiRJkiRJkpQ0lslUKIVh+DDw8G9fD4KgCTA76n0kSZIkSZIkSQXTpuxN9Hq9F2Onjo0sMyMtg9tOvo0eR/UgPS09slypoFm9Gvr0gYkTIQyjz69QAYYMgfbtIT3R/6kufRmmdoKNCxI8eDeUqAItRkKdy/KPXJMkSZIkSZIkSYWKZTJJkiRJkiRJkqQdmPbjNC596lLm/TQvsswm1Zrw2EWPcWjNQyPLlAqaMIRHH4UbboCVK+PZ4fLLYdgwqFEjwYM3/wifXweLnkjw4N1Utx00HwYlq8aTL0mSJEmSJEmSks4ymSRJkiRJkiRJ0nZy83IZ9uEwBrwzgJy8nMhyrzviOoacOoSSxUpGlikVNLNnQ6dO8P778eQ3bgzjxsEJJyR4cJgH8++FGTdC9roED98N5RtAq3uhRqJ/MEmSJEmSJEmSlGosk0mSJEmSJEmSJG3z/ervufyZy/lg0QeRZe5Xbj8e/tPDnFr31MgypYJmwwYYNAhGjYLc3OjzS5eGm2+G666D4sUTPHz1TJjSAX7+JMGDd0NacWjSFxr3hvQS0edLkiRJkiRJkqTIWSaTJEmSJEmSJElFXhiGPPrFo1z78rWs37o+sty/Nvkr488ZT+VSlSPLlAqSMISnn4Zu3WDx4nh2uPBCGD0aatVK8OCcjTDrFpg3AsIYGnI1ToJWE6D8wdFnS5IkSZIkSZKk2FgmkyRJkiRJkiRJRdrPm36mwwsd+M+X/4kss3yJ8ow9eyyXNruUIAgiy5UKkm+/hWuvhZdfjie/Th0YMwbOOScJw5e+DFM7wcYFSRi+CyWqQIuRUOcy8PePJEmSJEmSJElFjmUySZIkSZIkSZJUZL06/1XaPduOHzf8GFnm8Qcez6N/epQDKx4YWaZUkGzZAsOGwe23Q1ZW9PnFi0OvXtCnD5QuneDhm3+Ez6+DRU8kePBuqtsOmg+DklXjyZckSZIkSZIkSbGzTCZJkiRJkiRJkoqczdmb6f1Gb8ZMGRNZZkZaBoNPHsz1R11Pelp6ZLlSQfLaa9ClC3zzTTz5p54K99wDDRokeHCYB/PvhRk3Qva6BA/fDeUbQKsJUOPE6LMlSZIkSZIkSVJKsUwmSZIkSZIkSZKKlGk/TqPNU2348qcvI8tsXK0xky+cTIt9WkSWKRUkS5ZAjx7wREwHdu2zD4waBX/9KwRBgoevmQWftoefP0nw4N2QVhya9IXGvSG9RPT5kiRJkiRJkiQp5VgmkyRJkiRJkiRJRUJuXi7DPxrOgLcHkJ2XHVlutyO6MeSUIZTKKBVZplRQ5OTAmDEwYABs2BB9floadO0KgwZB+fIJHp6zCWbfAl+OgDAnwcN3Q42ToNX4/FPJJEmSJEmSJEmStrFMJkmSJEmSJEmSCr0FaxZw+dOX8/6i9yPL3Lfcvjx8wcOcVu+0yDKlguTDD6FTJ5g5M578o46CceOgefMkDF/6CkzNhI0LkjB8F0pUgRYjoc5lSThmTZIkSZIkSZIkFXSWySRJkiRJkiRJUqEVhiGTZk6iy0tdWL91fWS5f278ZyacM4EqpatElikVFD/9BL17w4MPxpNfuTLccQdceWX+yWQJtflH+Lw7LPpXggfvprptoflwKFk1nnxJkiRJkiRJkpTyLJNJkiRJkiRJkqRCadXmVXR8oSNPzn0yssxyxctxz9n3cNkhlxF4IpD0K3l5+QWy3r1h1ap4drjqKhg6FKomumsV5sH8iTDjRshem+Dhu6F8A2g1AWqcGH22JEmSJEmSJEkqUCyTSZIkSZIkSZKkQuf1b1+n7bNtWbp+aWSZx9Y6lkkXTqJ2xdqRZUoFxYwZkJkJn3wST/4hh8D48XD00UkYvmYWTOkAP32chOG7kFYcmtwEjW+E9BLR50uSJEmSJEmSpALHMpkkSZIkSZIkSSo0Nmdvps+bfbjr07siy8xIy+CWk27hhqNvID0tPbJcqSBYtw4GDIAxY/JPJota2bJwyy1w7bVQLNF3RnM2wexb4MsREOYkePhuqH4itJ6QfyqZJEmSJEmSJEnSbiqQZbIgCBoCBwAVgFJAsKczwjB8NNF7SZIkSZIkSZKk+MxYNoNLn7qUuSvnRpbZqGojJl80mZb7tIwsUyoIwhCeeAK6d4cff4xnh7/+FUaOhP32S8Lwpa/A1E6w8fskDN+FElWgxQioczkEe3ybVJIkSZIkSZIkFXEFpkwWBMEZQHvgdKB0AkZaJpMkSZIkSZIkqRDIzctlxMcj6PdWP7LzsiPLvbb1tdxx6h2UyigVWaZUEHz9NXTuDG+8EU9+/fowdiycfnoShm9eBp9fB4v+lYThu6FuW2g+HEpWjSdfkiRJkiRJkiQVeClfJguCoCLwMHDeLy/txbhw2/vDvdtKkiRJkiRJkiSlgoVrFnL5M5fz3sL3Isvcp+w+PHTBQ5xR/4zIMqWCYPNmuP12GDYMtm6NPr9ECbjpJujVC0qWTPDwMA/mT4QZN0L22gQP3w3lDobW90KNE6PPliRJkiRJkiRJhUpKl8mCICgNvAoczv9KYL8Uwv7QyAStJkmSJEmSJEmSYhSGIY/NeozOL3VmXda6yHIvanQRE8+dSJXSVSLLlAqCl16CLl3g++/jyT/zTLjnHqhXLwnD18yCKR3gp4+TMHwX0opDk5ug8Y2QXiL6fEmSJEmSJEmSVOikdJkM6AO04tclsi3Aa8AMYAWwMa7lJEmSJEmSJElS9FZvXk3mi5n8a86/IsssW7wsY84awxWHXkEQ+Nl10i8WLYLrroOnn44nf//94a674MILIeH/aeZsgtm3wpd3QpiT4OG7ofqJ0HoClG8QfbYkSZIkSZIkSSq0UrZMFgRBceA6fn0S2X1A7zAM18S0liRJkiRJkiRJitGb373JFc9cwZL1SyLLPOaAY3j0wkepW6luZJlSqsvOhlGjYNAg2LQp+vxixaB7dxgwAMqWTULA0ldgaifYGMNRayWqQIsRUOfyJDTkJEmSJEmSJElSUZeyZTLgWKAM/zuV7OEwDDvEu5IkSZIkSZIkSYrDlpwt3PTmTYz6ZFRkmcXSijHoxEH0PqY36WnpkeVKqe699yAzE+bOjSf/2GNh/Hho2jQJwzcvg2ndYeHjSRi+G+q2hebDoWTVePIlSZIkSZIkSVKhl8plsvrbHgMgD+gb4y6SJEmSJEmSJCkmXyz7gjZPt2H2itmRZTas2pDJF07msH0PiyxTSnXLl0OvXvDoo/HkV6sGw4fD5ck4sCvMg/n3wYzekL02wcN3Q7mDofUEqHFS9NmSJEmSJEmSJKlISeUyWZVtjyEwPwzDZXEuI0mSJEmSJEmSopUX5jHy45H0fasvW3O3RpbbuVVnhp02jNIZpSPLlFJZbi5MnAg33QRr1kSfHwTQoQPcdhtUrpyEgDWzYUp7+OnjJAzfhbTi0LgPNLkR0ktGny9JkiRJkiRJkoqcVC6Tbd7u+erYtpAkSZIkSZIkSZFbtHYRVzxzBe8seCeyzJpla/Lg+Q9y1kFnRZYppbrPPoPMzPzHOLRsCePHQ+vWSRieswlm3wpf3glhThICdqH6CdBqAlRoGH22JEmSJEmSJEkqslK5TDZ/u+dVfvcqSZIkSZIkSZJUqPxj1j/o9GIn1matjSzzwoYXMvG8iVQtXTWyTCmVrVkDffvmF7nCMPr88uXh9tuhY0dIT09CwNJXYWombPw+CcN3oUQVaHEn1Lki/9g1SZIkSZIkSZKkCKVymew9YCtQHKgTBEGlMAw9oUySJEmSJEmSpEJq9ebVdHqpE4/PfjyyzLLFy3L3mXfTtnlbAksdEmEIjz0G118PK1bEs8Oll8Kdd0LNmkkYvnkZTOsOC6P7PfMrda7IL5KVtLgqSZIkSZIkSZLikbJlsjAM1wVB8A+gLZAGXAbcHetSkiRJkiRJkiQpKd76/i2ueOYKFq9bHFnm0QcczaQLJ1G3Ut3IMqVUNncudOoE774bT37DhjBuHJx0UhKGh3kw/z6Y0Ruyozv18L/KHQytJ0CNZPxwkiRJkiRJkiRJuy8t7gV24SZg1bbn/YMgqB3jLpIkSZIkSZIkKcG25Gzh+lev55RHT4msSFYsrRi3nnQr77Z91yKZBGzcCDfeCIceGk+RrFQpGDIEvvgiSUWyNbPh9eNgasfoi2RpxaHpzXD2FxbJJEmSJEmSJElSSkjZk8kAwjBcFgTBhcDLQBXgzSAI/hyG4fSYV5MkSZIkSZIkSXtp1vJZXPrUpcxaMSuyzIOrHMxjFz3G4fseHlmmlKrCEJ59Frp1g0WL4tnh/PPhrrugdu0kDM/ZBLNvhS/vhDAnCQG7UP0EaDUBKjSMPluSJEmSJEmSJOl3pHSZDCAMw/eDIDgeeAKoC3waBMG/t33/GbAiDMOtce4oSZIkSZIkSZJ2X16Yx+hPRtPnzT5szY3uT/yZh2cy/LThlCleJrJMKVV9/z107QovvBBP/oEHwt1355fJkmLpq/BZJ9jwXZICdqJ4ZWg5AupcAUEQfb4kSZIkSZIkSdJOpHSZLAiC3N+8FJK/89+2ff1y3Z6ODsMwTOmfXZIkSZIkSZKk5796niAIOPfgc+NeJWF+WPsDbZ9ty1vfvxVZZo0yNXjwggc5+6CzI8uUUlVWFtx5JwweDFu2RJ+fkQE9e0K/flC6dBICNi+DaT1g4T+TMHw31LkCWgyHktXiyZckSZIkSZIkSdqFVC9Ubd8SC7d79CP8JEmSJEmSJEmF2satG7n25WsJgoCT65xM6YxktC6i9fjsx8l8MZM1W9ZElnlBgwu477z7qFbGYof05pvQqRN8/XU8+SedBGPHQqNGSRge5sG398P03pC9JgkBu1DuIGg1AWqeHH22JEmSJEmSJEnSHkiLe4Hd8EuJLNjua29nSZIkSZIkSZKU0ga/N5iFaxeyYM0CBr83OO519sqaLWu49KlLufg/F0dWJCuTUYb7z7ufp//2tEUyFXk//giXXAKnnhpPkaxGDXjssfwyW1KKZGtmw+vHwZQO0RfJ0jKg6QA4e6ZFMkmSJEmSJEmSVCCk+slk72EBTJIkSZIkSZJUxMxdOZc7P77zv9/f+dGdXHbIZTSqlowWRnK9/f3bXPHMFfyw7ofIMo/c/0gmXziZepXrRZYppaKcHBg3Dvr1g/Xro89PS4POneHWW6FChSQE5GyG2bfCl8MhzElCwC5UPx5a3QsVGkafLUmSJEmSJEmS9AeldJksDMMT495BkiRJkiRJkqQohWFI5ouZ5OT9rxiRnZdN5ouZvH3F2wRBEON2uy8rJ4t+b/VjxMcjCCP63Lj0IJ2bT7iZPsf1oVhaSt8CkZLuk08gMxNmzIgnv3VrGD8eWrZMUsDSV+GzTrDhuyQF7ETxytDiTqjbFgrI72RJkiRJkiRJkqRfeCdVkiRJkiRJkqQU8ugXj/Lewvf+v9ffXfguk2ZO4vJDL49hqz0za/ks2jzdhpnLZ0aWeVDlg5h80WRa79c6skwpFf38M/TpA/fdF09+pUowZAhcc03+yWQJt3k5TOsOC/+ZhOG7oc7l+UWyktXiyZckSZIkSZIkSdpLybiFI0mSJEmSJEmS/oBVm1fR8/Wev/vvPV/ryarNqyLcaM/khXmM+ngUre5rFWmRrONhHZneYbpFMhVpeXnw0EPQsGF8RbK2bWHePOjQIQlFsjAP5k+EFxrGUyQrdxCc/CYc9YhFMkmSJEmSJEmSVKB5MpkkSZIkSZIkSSmizxt9+GnTT7/77ys3reSmN29iwrkTItxq9yxet5i2z7Tlze/fjCyzepnqPHD+A5x78LmRZUqpaOZM6NQJPvwwnvymTWHcODjuuCQFrJkNUzrATx8lKWAn0jKgcR9o0gfSS0afL0mSJEmSJEmSlGCeTCZJkiRJkiRJUgr4ZPEnTJw2cZfXTfx8Ip8u/jSCjXbfv2b/i2bjm0VaJDvv4POYlTnLIpmKtPXr4frroWXLeIpkZcrAnXfCtGlJKpLlbIYZN8HLLeIpklU/Hs6aCYcMskgmSZIkSZIkSZIKDU8mkyRJkiRJkiQpZjl5OXR8oeNuXRsS0vHFjky9ZirF0uL9M//aLWvp8nIXJs+cHFlm6YzSjD5jNFe3vJogCCLLlVJJGMK//w3XXQdLl8azw//9H4waBQcckKSAH1+DqZmw4bskBexE8crQ4k6o2xb8PSNJkiRJkiRJkgoZy2SSJEmSJEmSJMXsnin38MXyL3b7+hnLZjB2yli6HdktiVvt3LsL3uXyZy5n0dpFkWUesd8RTLpwEgdVOSiyTCnVzJ8PXbrAq6/Gk1+3LtxzD5x1VpICNi+HaT1g4T+SFLALdS7PL5KVrBZPviRJkiRJkiRJUpLFUiYLguDB37wUhmF41W5clyg7zJMkSZIkSZIkKWpL1i2h/9v99/h9/d/uz1+a/IV9y+2bhK1+X1ZOFgPeHsDwj4YTEkaSmR6k0//4/vQ9vm/sp7FJcdmyBYYOzf/Kyoo+v3hx6NMHeveGUqWSEBDmwbcPwPRekL0mCQG7UO4gaDUBap4cfbYkSZIkSZIkSVKE4rrj2hb+e4c52PZ8R+Wu7a9LlJ3lSZIkSZIkSZIUqe6vdmfD1g17/L71W9fT/dXu/OvP/0rCVjs2Z8UcLn3q0j06RW1v1a9cn8kXTuaI/Y+ILFNKNa+8kn8a2bffxpN/+un5p5EdlKxDAdfMgakdYOWHSQrYibQMaNwHmvSB9JLR50uSJEmSJEmSJEUsLe4FJEmSJEmSJEkqql6d/ypPzn3yD7//iTlP8Nq3ryVwox3LC/O465O7OGziYZEWydq3bM/0DtMtkqnIWrwY/vxnOOuseIpk++4LTzyRX2ZLSpEsZzN80Rdebh5Pkaz68XDWF3DIIItkkiRJkiRJkiSpyIjrZDLIPyEskddJkiRJkiRJklRgbM7eTOeXOu/1nM4vdWZW5ixKFktOEWLJuiW0fbYtb3z3RlLm70i10tV44PwHOK/BeZFlSqkkOxvuvhtuvhk2bow+Pz0dunWDgQOhXLkkhfz4OkztCBu+S1LAThSvDC2GQ922EPjZm5IkSZIkSZIkqWiJq0xWJ8HXSZIkSZIkSZJUoAz9YCjfrt77o4bmr5rP0A+GMvDEgXu/1G88OedJOrzQgdVbVid89u859+Bzuf+8+6lRtkZkmVIq+eADyMyE2bPjyT/6aBg/Hg45JEkBm5fDtB6w8B9JCtiF2pdByxFQslo8+ZIkSZIkSZIkSTGLpUwWhuHCRF4nSZIkSZIkSVJB8vXPXzP0w6EJmzfkgyFc0uwSDq5ycELmrd2ylmtfvpZJMyclZN7uKJ1RmpGnj6T9Ye0JgiCyXClVrFwJvXvDQw/Fk1+lCgwbBm3bQloyDusK8+DbB2B6L8hek4SAXShbH1pPgJqnRJ8tSZIkSZIkSZKUQuI6mUySJEmSJEmSpCIpDEM6vdiJrblbEzZza+5WOr/UmdfavLbXRaz3F77PZU9fxsK10X3eW+v9WjPpwkkJK8NJBUleHtx/P9x4I6yO7hDAX7nmGhgyJL9QlhRr5sDUDrDywyQF7ERaBjS+EZrcBOklo8+XJEmSJEmSJElKMcn4XEFJkiRJkiRJkvQ7Hp/9OG9+/2bC577x3Rv8a86//vD7t+Zupc8bfTjh4RMiK5KlBWkMOH4AH7T7wCKZiqTp0+Goo6BDh3iKZIceCh9/DBMnJqlIlrMZvugLLzePp0hW7Tg46ws45BaLZJIkSZIkSZIkSdt4MpkkSZIkSZIkSRFZu2UtPV7rkbT53V/tzln1z6JCyQp79L65K+fS5qk2TF82PUmb/f/qVarH5Ismc+T+R0aWKaWKtWuhf38YOzb/ZLKolSsHgwdDp05QLFl3C398HaZmwoZvkxSwE8UrQYs7oW5bCPxsTUmSJEmSJEmSpO1590SSJEmSJEmSpIj0e6sfyzYsS9r8ZRuW0f/t/rt9fV6Yx5hPx3DYxMMiLZJd3eJqZnScYZFMRU4Ywj/+AQ0bwpgx8RTJ/v53mDcPunZNUpFsywr48FJ4+/R4imS1L4Nz50G9Ky2SSZIkSZIkSZIk7YAnk0mSJEmSJEmSFIHPl37OuM/GJT1n7NSxtG3elpb7tNzpdUvXL6Xds+147dvXkr7TL6qWrsr9593PBQ0viCxTShXz5kHnzvDWW/HkH3xw/klop56apIAwD759EGb0gq2rkxSyE2XrQ+sJUPOU6LMlSZIkSZIkSZIKED+OT5IkSZIkSZKkJMvNy6Xjix3JC5N/DFFemEfHFzqSm5f7u9f8e+6/aTa+WaRFsrMPOptZmbMskqnI2bQJ+vaFQw6Jp0hWsiQMHgwzZyaxSLZ2LrxxAky5JvoiWVoGNO0P58yySCZJkiRJkiRJkrQbPJlMkiRJkiRJkqQku/fze/ls6WeR5U1dOpWJn08ks1Xmr15fl7WOri935ZEvHolsl1LFSjHyjJF0OKwDQRBEliulguefh2uvhYUL48k/5xwYMwbq1ElSQM5mmHMbfDkM8rKTFLIT1Y6D1vdChUbRZ0uSJEmSJEmSJBVQlskkSZIkSZIkSUqiZRuWcdObN0We2+fNPlzU6CJqlK0BwPsL3+fyZy5nwZoFke1w+L6HM/nCyTSo2iCyTCkVLFwIXbvCc8/Fk3/AAXD33XDBBZC0DuePr8PUTNjwbZICdqJ4JWgxHOq2gyAt+nxJkiRJkiRJkqQCzLsrkiRJkiRJkiQlUc/XerI2a23kuWuz1tLz9Z5szd3KTW/exAkPnxBZkSwtSKP/8f356MqPLJKpSNm6FYYOhUaN4imSFSsGvXvDl1/Cn/6UpCLZlhXwURt4+/R4imS128C586DeVRbJJEmSJEmSJEmS/gBPJpMkSZIkSZIkKUne+v4tHpv1WGz5k2dO5tPFn/LNqm8iy6xbqS6TLpzE0QccHVmmlArefhs6dYJ58+LJP+EEGDcOGjdOUkCYB98+CDN6wdbVSQrZibL1ofV4qHlq9NmSJEmSJEmSJEmFiGUySZIkSZIkSZKSICsni8wXM+NeI9Ii2ZXNr2T0maMpV6JcZJlS3JYtg5494bGYeqPVq8Odd0KbNkk6iQxg7VyY0gFWfpCkgJ1Iy4BGvaHJTVCsVPT5kiRJkiRJkiRJhYxlMkmSJEmSJEmSkmD4R8P5+uev414jElVKVeH+8+/nTw3/FPcqUmRyc2HCBOjbF9aujT4/CCAzEwYPhkqVkhSSsxnm3AZfDoO87CSF7ES1Y6H1vVAhWcetSZIkSZIkSZIkFT2WySRJkiRJkiRJSrDvVn/Hbe/fFvcakTiz/pk8eP6D7FNun7hXkSIzZUp+kWvatHjyDz8cxo/Pf0yaZW/AlI6w4dskhvyO4pWgxXCo2w6CtOjzJUmSJEmSJEmSCjHLZCqUgiBoC7TdwT+VjnYTSZIkSZIkSUVNGIZ0eakLW3K2xL1KUpUqVoo7T7+TzMMzCYIg7nWkSKxeDTfdBPfeC2EYfX6FCjBkCLRvD+npSQrZsgKm9YAFjyUpYBdqt4GWI6Bk9XjyJUmSJEmSJEmSCjnLZCqsagMnxL2EJEmSJEmSpKLnqS+f4uX5L8e9RlIdts9hTL5oMg2rNox7FSkSYQiTJkHPnrByZTw7XHYZDB8ONWokKSDMg28fhBm9YOvqJIXsRNn60Ho81Dw1+mxJkiRJkiRJkqQixDKZCqsFwLs7eL000CraVSRJkiRJkiQVFeuz1tPtlW5xr5E0aUEafY7tw4ATBlA8vXjc60iRmD0bOnWC99+PJ79xYxg3Dk5I5kforZ0LUzrCyhh+yLQMaNQbmtwExUpFny9JkiRJkiRJklTEWCZToRSG4cPAw799PQiCJsDsqPeRJEmSJEmSVDQMfGcgS9YviXuNpKhTsQ6TLpzEMbWOiXsVKRIbNsAtt8CoUZCTE31+6dJw881w3XVQPFndzZzNMOd2+PIOyMtOUshOVDsWWt8LFRpHny1JkiRJkiRJklREFcgyWRAEAdACaARUBioAacCjYRguiHE1SZIkSZIkSVIRNXP5TO769K6410iKds3bMfrM0ZQvUT7uVaSkC0N4+mno1g0WL45nhwsvhNGjoVatJIYsewOmZMKG+UkM+R3FK0GL4VC3HQRp0edLkiRJkiRJkiQVYQWqTBYEwaHA9cAFQNkdXPIBsGAH7+sFNNz27aIwDAcmaUVJkiRJkiRJUhGUF+bR8YWO5Ia5ca+SUJVLVea+8+7jokYXxb2KFIlvv4Vrr4WXX44nv04dGDMGzjkniSFbVsC062HB5CSG7ETtS6HlSChZPZ58SZIkSZIkSZKkIq5AlMmCICgOjAI6/vLSDi4LdzJiGTB02zVhEAQPe4KZJEmSJEmSJClRHpz+IB8v/jjuNRLqjHpn8OAFD7JvuX3jXkVKuqwsGDYMbr8dtmyJPj8jA3r3hj59oHTpJIWEefDdQzD9Bti6OkkhO1G2HrQaD/ucFn22JEmSJEmSJEmS/ivly2RBEJQG3gRak18i+21pLGTH5bLt/QMYDlTb9v2lwG0JXFOSJEmSJEmSVESt3LiS3m/0jnuNhClZrCTDTxtO51adCYJd/fldKvhefx06d4Zvvokn/5RTYOxYaNAgiSFr58KUjrDy/SSG/I60DGjUC5r0hWKlos+XJEmSJEmSJEnSr6TFvcBu+CdwxHbfh8DTQCZwLrsukhGGYc629/zirEQuKEmSJEmSJEkqunq90YtVm1fFvUZCtKjZgmntp9GldReLZCr0liyBv/0NTj89niJZzZrwz3/ml9mSViTL3QJf9IeXm8dTJKt2LJw5HQ4dbJFMkiRJkiRJkiQpRaT0yWRBEJwHnMf/TiP7Bvi/MAxnb3cN/P+nle3I80B78stnrYMgKBWG4ebEbixJkiRJkiRJKkreX/g+D894OO419lpAwI3H3sjAEwdSPL143OtISZWTA2PGwIABsGFD9PlpaXDttTBoEFSokMSgZW/AlEzYMD+JIb8joyK0GA71roSgIHy2pSRJkiRJkiRJUtGR0mUyoP+2xwBYBpwYhuGPf3DW1O2epwONgGl7sZskSZIkSZIkqQjLzs0m88XMuNfYaxlpGbza5lVOqnNS3KtISffRR5CZCTNnxpN/5JEwfjw0b57EkC0rYVoPWDA5iSE7UftSaDECStWIJ1+SJEmSJEmSJEk7lbIfBRgEQQ3gMPJPHQuB/ntRJCMMwxXAyu1earB3G0qSJEmSJEmSirJRn4xizso5ca+x17Lzsvls6WdxryEl1U8/wdVXwzHHxFMkq1QJJk6EDz9MYpEszINvH4AXGsZTJCtbD056DY6ebJFMkiRJkiRJkiQphaVsmQw4hvwTyQIgB3g8ATN/2u551QTMkyRJkiRJkiQVQQvXLGTQu4PiXiNhBr47kEVrF8W9hpRweXlw//3QoAE88EA8O1x5JXz1FVxzDaQl687c2i/hjRPh06th66okhfyOtAxo0hfOngX7nBZttiRJkiRJkiRJkvZYKpfJam57DIH5YRhuTMDMdds9L5uAeZIkSZIkSZKkIqjbK93YlL0p7jUSZlP2Jrq90i3uNaSE+uILOPbY/BLXqoj7VQDNmsEHH+SX2KpVS1JI7haYOQBePhRWvp+kkJ2odgycOR0OHQzFSkWfL0mSJEmSJEmSpD2WymWyCts9X/e7V+2ZMts935ygmZIkSZIkSZKkIuT5r57n2a+ejXuNhHtm3jO88PULca8h7bV166B7d2jZEj7+OPr8smVh5EiYNg2OOSaJQcvehBebwexbIS87iUE7kFERWt8Hp74HFZtEmy1JkiRJkiRJkqS9UizuBXZi9XbPK/zuVXum5nbPf07QTEmSJEmSJElSEbFx60auffnauNdImmtfvpaT65xM6YzSca8i7bEwhCeeyC+S/fhjPDv85S/5RbL9909iyJaVMO16WDApiSE7UftSaDECStWIJ1+SJEmSJEmSJEl7JZVPJlu+7TEA6gRBUHxvhgVBcBBQdbuXftibeZIkSZIkSZKkomfwe4NZuHZh3GskzYI1Cxj83uC415D22NdfwxlnwN//Hk+RrH59eOWV/DJb0opkYQjfPggvNIynSFa2Hpz0Ghw92SKZJEmSJEmSJElSAZbKZbLPtnteHDh5L+ddut3zrcAnezlPkiRJkiRJklSEzF05lzs/vjPuNZLuzo/uZO7KuXGvIe2WzZthwABo1gxefz36/BIlYNAgmDUrv8yWNGu/hDdPhE+vgq2rkhi0A0ExaHITnD0L9jkt2mxJkiRJkiRJkiQlXLG4F/g9YRj+EATBXKDRtpd6A6/8kVlBEOwDXAuE2176IAzDLXu/pSRJkiRJkiRJhU9AEPcK0i699BJ06QLffx9P/plnwj33QL16SQzJ3QJzboe5QyEvO4lBv6PaMdDqXqjYJPpsSZIkSZIkSZIkJUUqn0wGcB/894718UEQ9N3TAUEQlAP+DVTabtbohGwnSZIkSZIkSSoyGldrTM+jesa9RtL1PLonjao12vWFUkwWLYKLLoJzzomnSLb//vCf/+SX2ZJaJFv2Jrx0CMy+NfoiWUZFaD0RTn3PIpkkSZIkSZIkSVIhk+plsnHAgm3PA+CWIAjGBkFQYXfeHATBGcAU4EjyTyULgalhGL6YhF0lSZIkSZIkSYVc/xP6c2CFA+NeI2lqV6xNv+P7xb2GtEPZ2TB8ODRqBE8/HX1+ejr07AlffplfZguSdYDflpXw0eXw1qmw/pskhezEgZfAufOg/jUQpPqtREmSJEmSJEmSJO2pYnEvsDNhGGYHQXAx8BZQkvxCWUfg8iAIngc+33ZpQH5R7JwgCFoC9YGTgXrb/VsArAIujvSHkCRJkiRJkiQVGqUzSjPmrDGc//j5ca+SFGPOGkPpjNJxryH9f957Dzp1gjlz4sk/9lgYNw6aNUtiSBjCdw/B9Btg66okBv2OsnWh1XjY5/TosyVJkiRJkiRJkhSZlC6TAYRh+GkQBH8HHie/UAZQBvjbtq9fBMB1v/ke/lckWwv8OQzD75O6sCRJkiRJkiSpUDuvwXlc0OACnv3q2bhXSag/NfwT5x58btxrSL+yYgXccAM8+mg8+VWrwp13wuWXJ/EkMoC1X8LUjrDivSSG/I6gGDTuBU36QbFS0edLkiRJkiRJkiQpUmlxL7A7wjB8HmgNzOV/J43995+3+wr4dYnsl9fmAEeEYfhORCtLkiRJkiRJkgqxu8+6u1Cd4FU6ozR3nXlX3GtI/5WbC+PHQ4MG8RTJggA6dICvvoIrrkhikSx3C8wcAC8fGk+RrNoxcNYMOPQ2i2SSJEmSJEmSJElFRIEokwGEYTgHaA5cAkzZ9nLwmy9+8/oc4Arg0DAMv45sWUmSJEmSJElSoVarQi0ubnJx3GskzMATBlKrQq2415AA+PxzOOoo6NQJ1qyJPr9FC/j4Y5gwASpXTmLQsrfgpUNg9q2Ql53EoB3IqAitJ8Kp70HFJtFmS5IkSZIkSZIkKVbF4l5gT4RhmAs8DjweBEFl4FigEVAFqAhsAn4CvgfeDsNwaUyrSpIkSZIkSZIKqTVb1nD9q9fz4IwH414lIZpWb8p1R14X9xoSa9ZAv34wbhyEYfT55cvDbbdBZiakpycxaMtKmN4Tvo/hyDWAAy+BliOhVI148iVJkiRJkiRJkhSrAlUm214YhquA57Z9SZIkSZIkSZKUdM9/9TwdX+zI0vWF57PMxp8znoz0jLjXUBEWhvDYY3D99bBiRTw7XHIJjBgBNWsmMSQM4buH84tkW1clMeh3lK0LrcbDPqdHny1JkiRJkiRJkqSUUWDLZJIkSZIkSZIkReXnTT/T9ZWu/GPWP+JeJaHaNW/HsbWOjXsNFWFffgmdOsE778ST36BB/kloJ5+c5KC182BqB1jxXpKDdiAoBo1ugKb9oVip6PMlSZIkSZIkSZKUUiyTSZIkSZIkSZK0E/+e+286v9SZFRtjOjIpSSqXqsyw04bFvYaKqI0bYfBguPNOyMmJPr9UKejfP/80tOLFkxiUuwXmDIG5QyAvO4lBv6Pq0dD6XqjYNPpsSZIkSZIkSZIkpSTLZJIkSZIkSZIk7cDyDcvp8nIX/j3333GvkhTDTh1G1dJV415DRdCzz0LXrrBoUTz5550Hd98NtWsnOWjZWzC1I6z/JslBO5BREVrcAfWuhiAt+nxJkiRJkiRJkiSlLMtkkiRJkiRJkiRtJwxD/jn7n3R9uSs/b/457nWS4ugDjqZdi3Zxr6Ei5vvvoVs3eP75ePIPPDC/RHb++UkO2rISpveE7x9NctDvOPBiaDkSStWMJ1+SJEmSJEmSJEkprUCVyYIgSAcOB1oAtYDyQCkg2MNRYRiGVyV4PUmSJEmSJElSAbdk3RIyX8zk+a9jartEID1IZ/w540nztCJFJCsLRoyAwYNh8+bo8zMyoGdP6NsXypRJYlAYwncP5xfJtq5KYtDvKFMHWo2Hfc+IPluSJEmSJEmSJEkFRoEokwVBUAHoB1wGVNvbcUAIWCaTJEmSJEmSJAH5p5E9PONhur/anbVZa+NeJ6muO/I6DqlxSNxrqIh4803o3Bm++iqe/JNOgrFjoVGjJAetnQdTO8KKd5MctANBMWh0AzTtB8VKR58vSZIkSZIkSZKkAiXly2RBEBwFPE1+iWz7E8jCeDaSJEmSJEmSJBUmi9Yu4prnr+G1b1+Le5Wk27/8/gw8cWDca6gI+PFHuP56+Oc/48mvUQNGjoSLL4Yg2PX1f1juFpgzBOYOhbytSQz6HVWPhtb3QsWm0WdLkiRJkiRJkiSpQErpMlkQBE2AV4Gy214K+V+hLJm3/iRJkiRJkiRJhVxemMfEzydyw+s3sGHrhrjXicRdZ95F2eJld32h9Afl5MC4cdC/P6xbF31+Wlr+SWi33AIVKyY5bPnbMKUjrP86yUE7kFERWtwB9a6GIC36fEmSJEmSJEmSJBVYKV0mA8aRXyT75RSyAHgNeBaYBfwMbIpnNUmSJEmSJElSQfXtqm+55vlreHvB23GvEpmzDzqbCxteGPcaKsQ+/RQyM2H69HjyW7WC8ePhsMOSHLTlJ5jeE75/JMlBv+PAi6HlSChVM558SZIkSZIkSZIkFWgpWyYLgqAecBz/O41sNfB/YRi+E+dekiRJkiRJkqSCKzcvl3um3MNNb93Epuyi81llJYuVZMxZYwiCIO5VVAitWgV9+sB990EY7vr6RKtYEYYOhauvhvT0JAaFYX6BbHpPyPo5iUG/o0wdaDUe9j0j+mxJkiRJkiRJkiQVGilbJgOO2fYYkF8o62CRTJIkSZIkSZL0R33101dc+dyVfPTDR3GvErl+x/WjbqW6ca+hQiYvDx55BHr1gp9+imeHtm3hjjugevUkB62dB1M7wop3kxy0A0ExaHQDNO0HxUpHny9JkiRJkiRJkqRCJZXLZDW3e74a+E9ci0iSJEmSJEmSCq6cvBxGfjySAW8PICs3K9LsUsVKsTlnc6SZv9WgSgN6Ht0z1h1U+MyaBZmZ8OGH8eQ3aQLjx8NxxyU5KHcLzBkKc4dA3tYkh+1A1aOh9b1QsWn02ZIkSZIkSZIkSSqUUrlMlrvtMQS+C8MwjHMZSZIkSZIkSVLBM3vFbK589kqmLp0aaW6ZjDIMO20YB1c5mNMmnRZp9m+NP2c8JYqViHUHFR7r18OgQTB6NOTm7vLyhCtTBgYOhG7dICMjyWHL34YpHWH910kO2oGMCtD8Dqh/DQRp0edLkiRJkiRJkiSp0ErlMtmi7Z6XjG0LSZIkSZIkSVKBk52bzdAPhnLre7eSnZcdafapdU/lvvPuo3bF2gBc2uxSHpv1WKQ7/KLNIW04qc5JsWSrcAlD+M9/4LrrYMmSeHb4v/+DUaPggAOSHLTlJ5jeE75/JMlBv+PAv0PLUVCqZjz5kiRJkiRJkiRJKtRSuUz2EfmnkgVA7SAIioVhmBPzTpIkSZIkSZKkFDf9x+m0e7YdXyz/ItLc8iXKM/L0kVzZ4kqCIPjv6yNOH8ELX7/A2qy1ke5TsWRF7jztzkgzVTjNnw9dusCrr8aTX7cu3HMPnHVWkoPCML9ANr0nZP2c5LAdKFMHWo2Dfc+MPluSJEmSJEmSJElFRlrcC/yeMAyXAG9s+7YMcHaM60iSJEmSJEmSUlxWThb93upHq/taRV4kO/ugs5nTaQ5XtbzqV0UygBpla3D7KbdHug/A7SffTo2yNSLPVeGxZQsMGgRNm8ZTJCteHAYMgNmzIyiSrfsK3jwJPmkXfZEsKAaNb4RzZlskkyRJkiRJkiRJUtKl8slkAL2BE8nf844gCN4Mw3BjvCtJkiRJkiRJklLNlCVTaPdsO+aunBtpbqWSlbjrzLtoc0ib/69Etr0Oh3XgoRkP8dnSzyLZq9W+rWh/WPtIslQ4vfJK/mlk334bT/7pp+efRnbQQUkOys2COUNg7hDI25rksB2oehS0vhcqNos+W5IkSZIkSZIkSUVSyp5MBhCG4Qyg07ZvDwZeCIKgenwbSZIkSZIkSZJSyebszfR6vRdHPXBU5EWyCxteyNzOc7ns0Mt2WiQDSE9LZ8I5E0gLkv9n+bQgjQnnTiA9LT3pWSp8Fi+Gv/wl/ySwOIpk++4LTzyRX2ZLepFs+Tvw0iEwe1D0RbKMCtBqApz2gUUySZIkSZIkSZIkRSqly2QAYRg+ALQBNgMnAHOCIBgYBEGzYFd35yVJkiRJkiRJhdYHiz7g0AmHMvyj4eSFeZHlVitdjSf+/AT/+et/qFm25m6/77B9D6PT4Z12feFe6tyqMy33aZn0HBUu2dkwciQ0agT//nf0+enp0L07fPllfpktqXeAtvwEH7eFN0+C9V8nMeh3HPh3OHceHNQBIiiYSpIkSZIkSZIkSdsLwjCMe4fdEgRBXeB5oBHwy9LZwCpgyx6OC8MwrJfA9VRABEHQBJj9y/ezZ8+mSZMmMW4kSZIkSZIkaU9t3LqRPm/24Z4p9xAS7d+4L256MXedeRfVylT7Q+9fu2UtDcc2ZNmGZQneLF/NsjWZ13keFUpWSMp8FU4ffACdOsGsWfHkH300jBsHhx6a5KAwhO8fhenXQ9bPSQ7bgTJ1oNU42PfM6LMlSZIkSZIkSZKUMubMmUPTpk23f6lpGIZzosovFlXQ3giC4BhgJNCQ/CLZL59HWRzY/Y99/Z+C0aCTJEmSJEmSJP3KW9+/xdXPXc33a76PNLdm2ZpMOGcCFzS8YK/mVChZgZGnj+SSpy5J0Ga/NuqMURbJtNtWroTeveGhh+LJr1IFhg2Dtm0hLdkHdK37CqZ0hBXvJDloB4Ji0KgnNO0PxUpHny9JkiRJkiRJkiRtJ9m35vZaEARdgHeAw/lfiSzciy9JkiRJkiRJUgGzLmsdHV/oyCmPnhJ5keyKQ69gbqe5e10k+8Xfm/6dU+qckpBZ2zu17qn8rcnfEj5XhU9eHkycCA0axFcku+Ya+OoruPLKJBfJcrNg1iB46ZB4imRVj4KzpkHzIRbJJEmSJEmSJEmSlBJS+mSyIAjOAe4iv0T2Sxnsl0LZVmAtsCme7SRJkiRJkiRJUXhl/iu0f749P6z7IdLc/cvvz8RzJ3LWQWcldG4QBIw7ZxzNxjdja+7WhMwsnl6csWePJQiCXV+sIm36dMjMhE8/jSf/0ENh/Hg46qgIwpa/A1M6wPqvIwj7jYwK0PwOqH8NBCn/2Y6SJEmSJEmSJEkqQlK6TAaM5n9FsgBYAYwEngO+DsMwL77VJEmSJEmSJEnJtHrzanq81oOHZzwceXaHwzow7LRhlC9RPinzD65yMDcecyO3vHdLQub1ObYPB1c5OCGzVDitXQv9+8PYsfknk0WtXDm49Vbo3BmKJfvu1JafYMYN8N3DSQ76HQf+HVqOglI148mXJEmSJEmSJEmSdiJly2RBEBwJ1CO/SAYwEzglDMOf49tKkiRJkiRJkhSF5756jo4vdOTHDT9Gmlu7Ym3uP+9+Tql7StKz+hzXh8dmPca3q7/dqzn1K9fnxmNvTNBWKmzCEB5/HHr0gGXL4tnh73+HESNg332THBSG8P2jMP16yIrhdlKZ2tBqHOyb2NMMJUmSJEmSJEmSpERKi3uBnWi57THY9ni1RTJJkiRJkiRJKtx+2vQTl/znEi54/ILIi2TXtr6WWZmzIimSAZQsVpKxZ4/d6zljzx5LyWIlE7CRCpt58+DUU+GSS+Ipkh10ELz2GvzznxEUydZ9BW+eDJ+0jb5IFhSDxr3hnDkWySRJkiRJkiRJkpTyUvZkMqDCds+XhGH4WWybSJIkSZIkSZKS7sk5T9L5pc6s3LQy0tyDKh/EA+c/wHEHHhdpLsAZ9c/gL43/wpNzn/xD7/9rk79yer3TE7yVCrpNm+C222D4cMjOjj6/ZEno2xduuAFKlEhyWG4WzB0Kc26HvK1JDtuBKkfCEROhYrPosyVJkiRJkiRJkqQ/IJXLZL/83wIhsDTORSRJkiRJkiRJybNswzK6vNSF/3z5n0hz04I0ehzZg0EnDaJ0RulIs7c36oxRvDz/ZTZs3bBH7ytXvByjzhiVpK1UUL3wAlx7LSxYEE/+2WfDmDFQt24EYcvfgakd808li1pGBWg+FOq3hyAt+nxJkiRJkiRJkiTpD0rlMtkP2z0vH9sWkiRJkiRJkqSkCMOQx2Y9RrdXurFq86pIsxtXa8yD5z/IEfsfEWnujuxXfj9uPelWur/afY/ed+tJt7JvuX2TtJUKmoULoVs3ePbZePIPOADuvhsuuACCIMlhW36CGTfAdw8nOeh31PobHDYKSu0TT74kSZIkSZIkSZK0F1L5oxI/ADYAAVAvCAILZZIkSZIkSZJUSCxZt4TzHz+fy56+LNIiWXqQTt/j+jKt/bSUKJL9okvrLjSv2Xy3r29eszmdW3dO3kIqMLZuhaFDoVGjeIpkxYpBr14wdy786U9JLpKFIXz3CLzYMJ4iWZnacOJLcOzjFskkSZIkSZIkSZJUYKVsmSwMw43Ak9u+LQZcHuM6kiRJkiRJkqQECMOQB6Y9QONxjXnh6xcizT60xqFMvWYqg08eTIliJSLN3pViacUYf854AnbdxAkImHDOBIqlFYtgM6Wyd96B5s2hTx/YvDn6/OOPhxkz4I47oGzZJIet+xreOgU+aQtZPyc57DeCdGjcG86ZA/ueFW22JEmSJEmSJEmSlGApWybbpj/wyx3BQUEQNIhzGUmSJEmSJEnSH7dwzULOmHwGVz9/Neuy1kWWm5GWwS0n3sKUa6bQYp8WkeXuqSP3P5JrWl6zy+vaH9Y+pU5VU/SWL4fLLoOTToIvv4w+v1o1ePTR/DJbkyZJDsvNglm3wEvNYPnbSQ7bgSpHwpnToPlQKFY6+nxJkiRJkiRJkiQpwVK6TBaG4VLgfGAtUAl4OwiC0+LdSpIkSZIkSZK0J/LCPMZNHUfT8U15/bvXI80+fN/DmdZhGv1P6E/x9OKRZv8RQ04dQrXS1X7336uVrsaQU4ZEuJFSSW4ujB0LDRrA5MnR5wcBdOoEX32VX2YLdn2Q3t5Z/i68fCjMuhnytiY57DcyKkCr8XD6h1DpkGizJUmSJEmSJEmSpCQqFvcCOxMEQS1gCfBXYCJQG3glCIKPgCeBz4GVwJY9nR2G4aLEbSpJkiRJkiRJ2pH5q+Zz9XNX8+7CdyPNLZFegltOuoUeR/WgWFpK/yn8VyqXqszw04bT9tm2O/z3O0+/k0qlKkW7lFLC1KmQmQmffx5P/mGHwfjx0KpVBGFZP8P0G+C7hyII24Faf4PDRkGpfeLJlyRJkiRJkiRJkpIo1e+gLwDC7b4PgQA4etvXHxWS+j+7JEmSJEmSJBVYuXm53P3p3fR9qy+bczZHmn3U/kfx4AUP0rBqw0hzE+XyQy/noRkP/X8FvBMOPIHLDrkspq0Ul9WroW9fmDABwnDX1ydahQpw++3QoQOkpyc5LAzh+0kw/XrI+inJYTtQpja0Ggf7nhV9tiRJkiRJkiRJkhSRglKoCvhfqSzc7jVJkiRJkiRJUoqZ99M8rnz2Sj5e/HGkuaWKleL2U27n2tbXkp6W7NZL8gRBwLhzxnHohEPJycsBICMtg/HnjCcI/NN4URGGMGkS9OwJK1fGs8Nll8Hw4VCjRgRh676GqR1h+dsRhP1GkA4Nr4dmN0Ox0tHnS5IkSZIkSZIkSREqKGUysDwmSZIkSZIkSSktJy+HER+N4OZ3biYrNyvS7BNrn8j9591Pvcr1Is1NlsbVGtPzqJ4M/XAoAD2P7kmjao1i3kpRmTMHOnWC996LJ79RIxg3Dk48MYKw3CyYewfMuQ3ytkYQ+BtVjoDWE6HSIdFnS5IkSZIkSZIkSTFI9TLZI3EvIEmSJEmSJEnatVnLZ9Hu2XZ8/uPnkeaWLV6W4acNp/1h7UkL0iLNTrb+J/Tnn7P/SRAE9Du+X9zrKAIbNsAtt8CoUZCTE31+6dIwYAB07w7Fi0cQuPxdmNoB1n0VQdhvZJSH5kOhfgcoZL87JEmSJEmSJEmSpJ1J6TJZGIbt4t5BkiRJkiRJkvT7tuZuZegHQxn83mCy87IjzT693ulMPHciB1Y8MNLcqJTOKM2Ys8YQBAGlM0rHvY6SKAzhmWegWzf44Yd4dvjTn2D0aDgwiv+csn6G6TfAdw9FELYDtf4Kh42GUvvEky9JkiRJkiRJkiTFKKXLZJIkSZIkSZKk1DXtx2m0e7YdM5fPjDS3QokKjDxjJO2atyMIgkizo3Zeg/PiXkFJ9t13cO218NJL8eTXrg1jxsC550YQFobw/SSYfj1k/RRB4G+UORAOHwf7nR19tiRJkiRJkiRJkpQiLJNJkiRJkiRJkvZIVk4Wt7x7C3d8eAe5YW6k2ecefC4TzpnAfuX3izRXSrSsLBg2DG6/HbZsiT4/IwN69YKbboLSURx8t+5rmJoJy9+KIOw3gnRoeD00GwDFykSfL0mSJEmSJEmSJKUQy2SSJEmSJEmSpN326eJPafdsO7786ctIcyuXqszdZ97NJc0uKfSnkanwe/116NwZvvkmnvxTToGxY6FBgwjCcrNg7jCYcxvkZUUQ+BtVjoDWE6HSIdFnS5IkSZIkSZIkSSnIMpkkSZIkSZIkaZc2ZW9iwNsDGPXJKPLCvEiz/6/R/zH27LHUKFsj0lwp0ZYuhR494F//iie/Zk0YNQr+9jeIpJO54j2Y0gHWzYsg7DcyykPzoVCvPaSlR58vSZIkSZIkSZIkpSjLZJIkSZIkSZKknXp/4ftc+dyVzF81P9LcaqWrMe6ccfy58Z8jzZUSLScH7rkHBgyA9eujz09Lgy5d4JZboEKFCAKzfobpveC7ByMI24Faf4XDRkOpfeLJlyRJkiRJkiRJklKYZTJJkiRJkiRJ0g5t2LqBPm/04Z6p90SefUmzS7jrzLuoWrpq5NlSIn38MWRmwhdfxJN/xBEwfjy0aBFBWBjCgskwrQdk/RRB4G+UORAOHwf7nR19tiRJkiRJkiRJklRAxFImC4Lgrd+8FIZheMpuXJcoO8yTJEmSJEmSJOV787s3ufr5q1mwZkGkufuU3YcJ507g/AbnR5orJdrPP8ONN8L998eTX6kS3HEHXHVV/slkSbfua5iaCcuTdWtnJ4J0aHg9NBsAxcpEny9JkiRJkiRJkiQVIHGdTHYiEG57Hmz3fGfXJcrO8iRJkiRJkiSpSFu7ZS03vH4D9027L/Lsds3bMfKMkVQsWTHybClR8vLgoYegd+/8QlkcrrwShg6FatUiCMvNgrnDYM5tkJcVQeBvVDkCWt8LlQ6NPluSJEmSJEmSJEkqgOIqk0mSJEmSJEmSUszL37xM+xfas3jd4khzDyh/APeddx9n1D8j0lwp0b74AjIz4eOP48lv1gzGj4djjokocMV7MKUDrJsXUeB2MsrDoUOgfgdIS48+X5IkSZIkSZIkSSqg4iyTBb/zfGfXSZIkSZIkSZISbNXmVXR/tTuPfvFo5NkdD+vIHafdQfkS5SPPlhJl3Tq4+WYYMwZyc6PPL1sWBg2Ca6+FjIwIArN+hum94LsHIwjbgVp/gZajofS+8eRLkiRJkiRJkiRJBVgsZbIwDNMSeZ0kSZIkSZIk6Y95Zt4zZL6YybINyyLNrVOxDveffz8n1zk50lwpkcIQnnwSuneHpUvj2eEvf4GRI2H//SMIC0NYMBmm9YCsnyII/I0yB8LhY2G/c6LPliRJkiRJkiRJkgqJOE8mIwiCAduehsCkMAwXxLiOJEmSJEmSJBUZKzeupOsrXXl89uOR5gYEdD2iK7edfBtlipeJNFtKpK+/hi5d4PXX48mvXx/uuQfOOCOiwHXfwNSOsPytiAK3E6RDwx7Q7GYo5u8NSZIkSZIkSZIkaW/EWiYDBpJfJAP4EFgQ2yaSJEmSJEmSVASEYcgTc56gy8td+GlTtCcLHVzlYB48/0GOqXVMpLlSIm3eDEOGwB13wNat0eeXKAE33QS9ekHJkhEE5mbB3GEw5zbIy4og8DeqHAGt74VKh0afLUmSJEmSJEmSJBVCcZfJAAL+VyiTJEmSJEmSJCXJsg3L6PRiJ56e93SkuWlBGj2P6snAEwdSKqNUpNlSIr38cv5pZN99F0/+GWfkn0ZWv35EgSvegykdYd2XEQVuJ6M8HDoE6neAtPTo8yVJkiRJkiRJkqRCKhXKZBbJJEmSJEmSJCmJwjBk0sxJXPfKdazesjrS7CbVmvDgBQ/Ser/WkeZKifTDD3DddfDUU/Hk77cf3HUXXHQRBEEEgVmrYEYv+PaBCMJ2oNZfoOVoKL1vPPmSJEmSJEmSJElSIZYKZTJJkiRJkiRJUpIsXreYDi904KVvXoo0Nz1Ip8+xfeh3fD9KFCsRabaUKNnZMHo0DBoEGzdGn5+eDt27w4ABUK5cBIFhCAseg2k9IGtlBIG/UeZAOHws7HdO9NmSJEmSJEmSJElSEWGZTJIkSZIkSZIKoTAMeWD6A1z/2vWsy1oXaXbzms158PwHabFPi0hzpUR67z3o1AnmzIkn/9hjYdw4aNYsosB138DUTFj+ZkSB2wnSoWEPaHYzFCsTfb4kSZIkSZIkSZJUhFgmkyRJkiRJkqRCZsGaBVz93NW8+X20pZCMtAxuPuFmeh3Ti4z0jEizpURZsQJ69YJHHoknv2pVGD4cLr8c0tIiCMzNgi+Hw+zBkJcVQeBvVGkNrSdCpUOjz5YkSZIkSZIkSZKKIMtkkiRJkiRJklRI5IV5jJ86nt5v9GZj9sZIs1vt24qHLniIJtWbRJorJUpuLtx3H/TpA2vWRJ8fBNC+Pdx+O1SuHFHoivdhSgdY92VEgdspVg6aD4H6HSEtPfp8SZIkSZIkSZIkqYiyTCZJkiRJkiRJhcD8VfO56rmreG/he5Hmlkgvwa0n3Ur3o7pTLM0/Oatg+vxzyMyEqVPjyW/RAsaPhyOOiCgwaxXM6AXfPhBR4G8c8Gc47C4ovW88+ZIkSZIkSZIkSVIR5p19SZIkSZIkSSrAcvNyuevTu+j3Vj8252yONPuYA47hgfMfoEHVBpHmSomyZg307w/jxkFeXvT55cvD4MH5RbZiUdyxCUNY8BhM6wFZKyMI/I3StaDVWNjv3OizJUmSJEmSJEmSJAGWySRJkiRJkiSpwJq7ci5XPnslny75NNLc0hmlGXLKELq07kJakBZptpQIYQj/+Adcfz0sXx7PDpdcAnfeCfvsE1Hgum9gaiYsfzOiwO0E6dCwOzQbCMXKRJ8vSZIkSZIkSZIk6b9SqUw2IgiC1RFlhWEYnhJRliRJkiRJkiQlVE5eDsM/HM7AdweyNXdrpNkn1T6J+8+/n7qV6kaaKyXKl19Cp07wzjvx5DdokH8S2sknRxSYuxW+HAazB0NeVkSh26nSGlrfC5WaR58tSZIkSZIkSZIk6f+TKmWyADgkwqwwoixJkiRJkiRJSqiZy2fS7tl2TPtxWqS55YqXY/hpw7nmsGs8jUwF0saNMHgwjBgB2dnR55cqBf37Q48eUKJERKEr3ocpHWDdlxEFbqdYOWg+BOp3hLT06PMlSZIkSZIkSZIk7VCqlMkkSZIkSZIkSTuxNXcrt79/O7e9fxs5eTmRZp9R7wwmnjeRWhVqRZorJcqzz0LXrrBoUTz5554Ld98NdepEFJi1Cmb0hm/vjyjwNw74Mxx2F5TeN558SZIkSZIkSZIkSb8rlcpkQdwLSJIkSZIkSVIq+nzp57R7th2zVsyKNLdiyYqMOmMUVxx6BUHgn3BV8CxYkF8ie/75ePJr1YIxY+D88yMKDENY8A+Y1h2yVkYUup3StaDVWNjv3OizJUmSJEmSJEmSJO2WVCmThcCdwNy4F9GeC4IgAzgLOGzbV12gClAJyAKWAp8B/wKeD8MwjGlVSZIkSZIkqUDZkrOFQe8MYvhHw8kNcyPNPr/B+Yw/Zzz7lvNkIRU8WVkwYgQMHgybN0efn5EBPXtC375QpkxEoevnw9RMWPZGRIHbCdKhYXdoNhCKRfUDS/p/7N13mNXlnf//1xl6UbE3LLH3Bmq6phijsaRusrtJNlIsCIq9994bqAhiks1m07OWGLsxURMVrNh77yLSy8zn98e4359rEAaYuc8wPB7XxeXMmXPu5xuuTP6YmffcAAAAAAAAC6O9LJMlyY1VVd1W7yFYKCsnufoTPtYlyQYf/vm3JHfXarXvVlX1eqnhAAAAAGBx9PeX/54B1wzIE+88UbS7fI/lc8kul+QHm/3AbWQslm67LRkyJHnyyfr0d9wxufTSZOONCwUbZyWPn5NMOCVpmlko+hHLb5dsNypZdqvybQAAAAAAAGCBtadlMhZv7yW5I803kD2f5I0kE5Msk2TLJIOSbJ7ks0lurdVq21RVNaNOswIAAABAuzVt9rQce9uxufAfF6ZKVbT9vU2+l0t2uSQr9165aBdaw+uvN98G9stf1qe/8srNt6H9278lxfYw3/pbcu8+yQePFwp+ROelkq3OSNbbN2noVL4PAAAAAAAALBTLZLSG15KsWFVV0yd8/I5arXZpkj8k2T3JxkkGJLm00HwAAAAAsFi444U7MvCagXl24rNFuyv1WimX7nppvrPJd4p2oTXMmZNcdlly7LHJBx+U7zc0NN+EdsopSZ8+haIz30sePCJ5dkyh4Mes8d2k34VJz9Xr0wcAAAAAAAAWmmUyFtk8lsg++pw5tVrtjDQvkyXJl2KZDAAAAACSJJNnTs5Rtx6VkfeNLN7+4RY/zIU7X5jley5fvA2L6p57kv32Sx54oD79bbdtXmTr169QsKqSF36Z3H9QMvPtQtGP6Llmsu3IZPXdyrcBAAAAAACAVmGZbAlVq9XWTbJdkr5JuiaZmOSJJHdXVTWjjbIf/Z2wS7dRAwAAAAAWKzc/e3MGXzs4L056sWh3taVWy6jdRmW3DSyFsPh5773k6KOTK65o3q8qrU+f5IwzksGDk06dCkUnP5Pct1/yxi2Fgh9R65RsODzZ/MSkS+/yfQAAAAAAAKDVWCZrB2q12uppXuza/sP/9k+y1Eee8mJVVWu3UuubSY5Lss0nPGVKrVb7aZKTqqp6pzWaH/HDj7z9RCufDQA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      "text/plain": [
       "<Figure size 4200x3000 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "µs = 1\n",
    "ms = 1000*µs\n",
    "s  = 1000*ms\n",
    "\n",
    "X = sizes\n",
    "# TODO: get this automatically?\n",
    "    \n",
    "Y_python = [ 7.27*µs, 72.1*µs, 786*µs, 7.55*ms, 68.2*ms, 677*ms ]\n",
    "Y_ocaml  = [ 16*µs, 157*µs, 1.8*ms, 24.2*ms, 286*ms, 2.92*s ]\n",
    "Y_numpy  = [ 12*µs, 67.7*µs, 615*µs, 6.25*ms, 62.6*ms, 632*ms ]\n",
    "\n",
    "fig = plt.figure(figsize=(14, 10), dpi=300)\n",
    "\n",
    "plt.loglog(X, Y_python, color=\"blue\", marker=\"o\", label=\"naive Python\", lw=4, ms=15)\n",
    "plt.loglog(X, Y_ocaml,  color=\"green\", marker=\"d\", label=\"using OCaml\", lw=4, ms=15)\n",
    "plt.loglog(X, Y_numpy,  color=\"orange\", marker=\"s\", label=\"using Numpy\", lw=4, ms=15)\n",
    "\n",
    "plt.ylabel(\"Time in micro-seconds\")\n",
    "plt.xlabel(\"Size of input list\")\n",
    "plt.legend()\n",
    "plt.title(\"Tiny benchmark comparing OCaml binding to Python\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Just to check the experimental values of $\\alpha$ and $\\beta$ in my claim above, let's use [`numpy.polyfit`](https://numpy.org/doc/stable/reference/generated/numpy.polyfit.html) function:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-02-23T03:55:04.714162Z",
     "start_time": "2021-02-23T03:55:04.701212Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([    4.31769413, -3617.94315775])"
      ]
     },
     "execution_count": 133,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.polyfit(Y_python, Y_ocaml, deg=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So the OCaml bidding code runs about 4.5 times slower than the Python one!\n",
    "\n",
    "It means that if you're doing a data analysis or some things in Python, and suddenly you think of an easy way to write an elegant and fast OCaml version, it's definitely viable to write it in OCaml, use `ocaml_function = %ocaml ...` and then use to solve your task!\n",
    "The overhead for using OCaml interpreted functions should not be too large."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Conclusion: demonstration of Pypi package OCaml for polyglot notebook\n",
    "\n",
    "This (long) notebook dived in the details of [this Pypi `ocaml` package](https://pypi.org/project/ocaml/) allows to embed a real and complete OCaml runtime (with full standard library) in an IPython console or Jupyter notebook running IPython kernel (Python 3). OCaml functions and tiny programs can then be called directly from the IPython/Jupyter console, and results can be printed, or affected to Python variables! It even supports [Currying](https://en.wikipedia.org/wiki/Currying) multi-argument functions!\n",
    "\n",
    "It's too bad that the package lack documentation, and is not open source, I would have liked to improve it a little bit!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "See also: note, if you really want to use OCaml in a Jupyter notebook, the best solution is [OCaml-jupyter](https://github.com/akabe/ocaml-jupyter/) kernel!\n",
    "(i opened [an issue](https://github.com/akabe/ocaml-jupyter/issues/167) there to present this to the developer, just for his curiosity)\n",
    "\n",
    "That's it for today!\n",
    "See [other notebooks](https://github.com/Naereen/notebooks/)"
   ]
  }
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