updates for computationally calculated dependencies

.gitignore

@@ -10,3 +10,4 @@ __pycache__
 .mypy_cache
 .venv
 .vscode
+env

001-what-is-python/index.html

@@ -45,6 +45,7 @@ <h1>(Who am I?)</h1>
               <li class='fragment'>Studied numeric modelling</li>
               <li class='fragment'>Scientific programmer in industry (Dundalk)</li>
               <li class='fragment'>Web, data and infrastructure consultant</li>
+              <li class='fragment'>Open Source as a Service</li>
             </ul>
           </section>
           <section data-background="images/snake-side.png" data-background-color="black" data-state="img-right">

002-basic-control-structures/Answers.ipynb

@@ -0,0 +1,118 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "f70a0f3e",
+   "metadata": {},
+   "source": [
+    "# 002: Basic Control Structures"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "aec9a83f",
+   "metadata": {},
+   "source": [
+    "## Zipping Up"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "b5663e8e",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Set my_dictionary[ a ] to be  23\n",
+      "Set my_dictionary[ b ] to be  42\n",
+      "Set my_dictionary[ c ] to be  12\n",
+      "Set my_dictionary[ d ] to be  9\n",
+      "Set my_dictionary[ e ] to be  5\n",
+      "Set my_dictionary[ f ] to be  1\n",
+      "{'a': 23, 'b': 42, 'c': 12, 'd': 9, 'e': 5, 'f': 1}\n",
+      "Set my_dictionary[ 23 ] to be  a\n",
+      "Set my_dictionary[ 42 ] to be  b\n",
+      "Set my_dictionary[ 12 ] to be  c\n",
+      "Set my_dictionary[ 9 ] to be  d\n",
+      "Set my_dictionary[ 5 ] to be  e\n",
+      "Set my_dictionary[ 1 ] to be  f\n",
+      "{23: 'a', 42: 'b', 12: 'c', 9: 'd', 5: 'e', 1: 'f'}\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Loop through them to make a dictionary, where the first list is the keys,\n",
+    "# and the second list is the values.\n",
+    "# You might want to make this into a function where the first argument is\n",
+    "# the first list, and the second argument is the second list\n",
+    "def zip_two_lists(key_list, value_list):\n",
+    "    my_dictionary = {}\n",
+    "    for i in range(len(key_list)):\n",
+    "        my_key = key_list[i]\n",
+    "        my_value = value_list[i]\n",
+    "\n",
+    "        print('Set my_dictionary[', my_key, '] to be ', my_value)\n",
+    "        my_dictionary[my_key] = my_value\n",
+    "    return my_dictionary\n",
+    "\n",
+    "# Print out your new dictionary\n",
+    "my_list_of_keys = ['a', 'b', 'c', 'd', 'e', 'f']\n",
+    "my_list_of_values = [23, 42, 12, 9, 5, 1]\n",
+    "my_new_dictionary = zip_two_lists(my_list_of_keys, my_list_of_values)\n",
+    "print(my_new_dictionary)\n",
+    "my_new_dictionary = zip_two_lists(my_list_of_values, my_list_of_keys)\n",
+    "print(my_new_dictionary)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "e131b7ca",
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'a': 23, 'b': 42, 'c': 12, 'd': 9, 'e': 5, 'f': 1}"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "new_dct = {}\n",
+    "for key, value in zip(my_list_of_keys, my_list_of_values):\n",
+    "    new_dct[key] = value\n",
+    "new_dct"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

002-basic-control-structures/Basic control structures II.ipynb

@@ -2281,6 +2281,115 @@
     "            return False"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Decorators"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Decorators will be explored more as time permits, but to help you recognise them as we move through, a brief explanation: these are brief annotations directly above `def` (for functions and methods). They tell Python to wrap the function/method with a function-of-a-function. In another phrasing, a decorator takes a function and soups it up. This looks like:\n",
+    "\n",
+    "```python\n",
+    "@mydecorator\n",
+    "def afunction():\n",
+    "  ...\n",
+    "```  \n",
+    "\n",
+    "In this case `mydecorator` will somehow modify the function's attributes or effects - examples are `@coroutine` for marking a function as async, `@staticmethod` for marking a class's method as static, and `@timer` for timing a function when it is called. You can even make your own - decorators are usually functions with a function as an argument, so you know all the syntax you need. It might look something like this:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def val2string(f):\n",
+    "    def modified_f(val1, val2):\n",
+    "        normal_result = f(val1, val2)\n",
+    "        return str(normal_result)\n",
+    "    return modified_f"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The above creates a new function called `modified_f` (note that function definitions can live anywhere, including in a function, just like any other variable definition). It is a two-argument function, which returns the stringified version of the original function, called with the same arguments. For instance:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'4'"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "@val2string\n",
+    "def add(a, b):\n",
+    "    return a + b\n",
+    "\n",
+    "@val2string\n",
+    "def mul(a, b):\n",
+    "    return a * b\n",
+    "add(1, 3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\"['this', 'that']\""
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "add(['this'], ['that'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'12'"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "mul(6, 2)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -2348,27 +2457,6 @@
     "* comprehensions"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "hideCode": false,
-    "hidePrompt": false,
-    "slideshow": {
-     "slide_type": "notes"
-    }
-   },
-   "source": [
-    "We haven't talked about a number of structures, but a couple you may come across that we don't cover in this course, are asynchronous routines (`async`, `await`) that follow the coroutine paradigm; and decorators, which allow us to mark certain functions and methods to be wrapped by a function-of-a-function. This looks like:\n",
-    "\n",
-    "```python\n",
-    "@mydecorator\n",
-    "def afunction():\n",
-    "  ...\n",
-    "```  \n",
-    "\n",
-    "In this case `mydecorator` will somehow modify the function's attributes or effects - examples are `@coroutine` for marking a function as async, `@staticmethod` for marking a class's method as static, and `@timer` for timing a function when it is called."
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -2803,7 +2891,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.6"
+   "version": "3.7.11"
   },
   "livereveal": {
    "theme": "beige",