From 2ef02b7be555a4ef2e7d953b135d3bd5beac3faa Mon Sep 17 00:00:00 2001
From: Ben Thayer <ben@benthayer.com>
Date: Thu, 26 Sep 2019 11:23:24 -0500
Subject: [PATCH 1/5] Dates initial commit

---
 Dates/.gitignore             |   1 +
 Dates/1900s.ods              | Bin 0 -> 17680 bytes
 Dates/Dates.ipynb            | 708 +++++++++++++++++++++++++++++++++++
 Dates/Exploration.ods        | Bin 0 -> 14123 bytes
 Dates/Flashcards.ipynb       | 229 +++++++++++
 Dates/Flashcards_1.ipynb     | 250 +++++++++++++
 Dates/Personal Trainer.ipynb | 117 ++++++
 7 files changed, 1305 insertions(+)
 create mode 100644 Dates/.gitignore
 create mode 100644 Dates/1900s.ods
 create mode 100644 Dates/Dates.ipynb
 create mode 100644 Dates/Exploration.ods
 create mode 100644 Dates/Flashcards.ipynb
 create mode 100644 Dates/Flashcards_1.ipynb
 create mode 100644 Dates/Personal Trainer.ipynb

diff --git a/Dates/.gitignore b/Dates/.gitignore
new file mode 100644
index 0000000..f7fd723
--- /dev/null
+++ b/Dates/.gitignore
@@ -0,0 +1 @@
+*.apgk
diff --git a/Dates/1900s.ods b/Dates/1900s.ods
new file mode 100644
index 0000000000000000000000000000000000000000..01d0de92c0d72d4a90623d54dca4fc0a6e4cd53e
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literal 0
HcmV?d00001

diff --git a/Dates/Dates.ipynb b/Dates/Dates.ipynb
new file mode 100644
index 0000000..b4d02a1
--- /dev/null
+++ b/Dates/Dates.ipynb
@@ -0,0 +1,708 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import time\n",
+    "from datetime import datetime, date, timedelta\n",
+    "import random"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def rand_date(start=date(1400, 1, 1), end=date(2400, 1, 1)):\n",
+    "    diff = end - start\n",
+    "    return start + random.random() * diff"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def convert_to_vector(xdate):\n",
+    "    yr1 = xdate.year // 1000\n",
+    "    yr2 = (xdate.year // 100) % 10\n",
+    "    yr3 = (xdate.year // 10) % 10\n",
+    "    yr4 = (xdate.year) % 10\n",
+    "    \n",
+    "    month = xdate.month\n",
+    "    \n",
+    "    day1 = xdate.day // 10\n",
+    "    day2 = xdate.day % 10\n",
+    "    \n",
+    "    weekday = xdate.weekday()\n",
+    "    \n",
+    "    to_encode = [\n",
+    "        (yr1, 10),\n",
+    "        (yr2, 10),\n",
+    "        (yr3, 10),\n",
+    "        (yr4, 10),\n",
+    "        (month, 12),\n",
+    "        (day1, 10),\n",
+    "        (day2, 10)\n",
+    "    ]\n",
+    "    \n",
+    "    xs = []\n",
+    "    for val, num_vals in to_encode:\n",
+    "        one_hot = np.zeros(num_vals)\n",
+    "        one_hot[val-1] = 1\n",
+    "        xs.append(one_hot)\n",
+    "        \n",
+    "    x = np.concatenate(xs)\n",
+    "    \n",
+    "    y = np.zeros(7)\n",
+    "    y[weekday] = 1\n",
+    "    return x, y"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Encoding: One-hot, separate integers\n",
+    "\n",
+    "Training: Month, year, other years, other decades\n",
+    "\n",
+    "Raw\n",
+    "\n",
+    "Start small, build up\n",
+    "\n",
+    "One month, same month plus another, keep adding months until a year, then add new years\n",
+    "One month, add a month, add a year, add several month, add several years, add decades\n",
+    "Start without leap years, then include leap years\n",
+    "\n",
+    "Whole idea is to go simple and complex\n",
+    "Introduce new concepts before past concepts are solidified\n",
+    "Don't want to confuse things - easily possible\n",
+    "\n",
+    "Simplest would be a single month in non leap-year\n",
+    "When introducing leap years, do half leap years and half non-leap years\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Using TensorFlow backend.\n"
+     ]
+    }
+   ],
+   "source": [
+    "from keras.models import Sequential\n",
+    "from keras.layers import Dense\n",
+    "from keras.callbacks import Callback\n",
+    "from keras import backend as K"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model = Sequential()\n",
+    "model.add(Dense(100, input_shape=(10*6 + 12,), activation='tanh'))\n",
+    "model.add(Dense(100, activation='tanh'))\n",
+    "model.add(Dense(100, activation='tanh'))\n",
+    "model.add(Dense(7, activation='softmax'))\n",
+    "\n",
+    "model.compile('adam', 'categorical_crossentropy', metrics=['accuracy'])\n",
+    "\n",
+    "def reset_model():\n",
+    "    global model\n",
+    "    session = K.get_session()\n",
+    "    for layer in model.layers: \n",
+    "        if hasattr(layer, 'kernel_initializer'):\n",
+    "            layer.kernel.initializer.run(session=session)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def generate_random(batch_size):\n",
+    "    dates = []\n",
+    "    xs = []\n",
+    "    ys = []\n",
+    "    for i in range(batch_size):\n",
+    "        rdate = rand_date()\n",
+    "        x, y = convert_to_vector(rdate)\n",
+    "        dates.append(rdate)\n",
+    "        xs.append(x)\n",
+    "        ys.append(y)\n",
+    "\n",
+    "    xs = np.array(xs)\n",
+    "    ys = np.array(ys)\n",
+    "    return xs, ys\n",
+    "\n",
+    "\n",
+    "def get_range_gen(start_date, end_date):\n",
+    "    def generate_range(batch_size):\n",
+    "        dates = []\n",
+    "        xs = []\n",
+    "        ys = []\n",
+    "        for i in range(batch_size):\n",
+    "            rdate = rand_date(start_date, end_date)\n",
+    "            x, y = convert_to_vector(rdate)\n",
+    "            dates.append(rdate)\n",
+    "            xs.append(x)\n",
+    "            ys.append(y)\n",
+    "\n",
+    "        xs = np.array(xs)\n",
+    "        ys = np.array(ys)\n",
+    "        return xs, ys\n",
+    "    return generate_range\n",
+    "\n",
+    "\n",
+    "def get_month_gen(year, month):\n",
+    "    start = date(year, month, 1)\n",
+    "    if month == 12:\n",
+    "        end = date(year + 1, 1, 1)\n",
+    "    else:\n",
+    "        end = date(year, month + 1, 1)\n",
+    "    return get_range_generator(start, end)\n",
+    "\n",
+    "\n",
+    "def combine_gens(generators, p=None):\n",
+    "    if p is None:\n",
+    "        p = [1/len(generators)] * len(generators)\n",
+    "    \n",
+    "    def generate(batch_size):\n",
+    "        generator = np.random.choice(generators, p=p)\n",
+    "        return generator(batch_size)\n",
+    "    \n",
+    "    return generate\n",
+    "\n",
+    "\n",
+    "def get_months_gen(year, months, p=None):\n",
+    "    gens = []\n",
+    "    for month in months:\n",
+    "        gens.append(get_month_generator(year, month))\n",
+    "    return combine_generators(gens, p)\n",
+    "\n",
+    "\n",
+    "def get_year_gen(year):\n",
+    "    return get_range_generator(date(year, 1, 1), date(year+1, 1, 1))\n",
+    "\n",
+    "\n",
+    "def get_years_gen(start_year, end_year):\n",
+    "    return get_range_generator(date(start_year, 1, 1), date(end_year + 1, 1, 1))\n",
+    "\n",
+    "\n",
+    "def get_years_gen_p(years, p=None):\n",
+    "    gens = []\n",
+    "    for year in years:\n",
+    "        gens.append(get_year_generator(year))\n",
+    "    return combine_generators(years, p)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from collections import deque"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def train_until_acc(model, data_gen, desired_acc, output=True, limit=1000000):\n",
+    "    running_acc = 0\n",
+    "    num_samples = 0\n",
+    "    batch_size = 32\n",
+    "    accs = deque(maxlen=10)\n",
+    "    accs.append(desired_acc-0.01) # so we don't get the divide by zero error\n",
+    "    \n",
+    "    batch_num = 0\n",
+    "    while sum(accs)/len(accs) < desired_acc:\n",
+    "        xs, ys = data_gen(batch_size)\n",
+    "        loss, acc = model.train_on_batch(xs, ys)\n",
+    "        accs.append(acc)\n",
+    "        num_samples += batch_size\n",
+    "        batch_num += 1\n",
+    "        if batch_num % 100 == 0:\n",
+    "            print(\"Minibatch\", batch_num, sum(accs)/len(accs))\n",
+    "        if num_samples > limit: # 1 mil by default\n",
+    "            break\n",
+    "    return num_samples\n",
+    "\n",
+    "\n",
+    "def run_schedule(schedule):\n",
+    "    reset_model()\n",
+    "    \n",
+    "    total_samples = 0\n",
+    "    for name, data_gen, accuracy in schedule:\n",
+    "        num_samples = train_until_acc(model, data_gen, accuracy)\n",
+    "        total_samples += num_samples\n",
+    "        print('Trained {} in {} samples'.format(name, num_samples))\n",
+    "    print('Training complete after {} samples'.format(total_samples))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from scipy.special import softmax\n",
+    "\n",
+    "def get_schedule_generator(x):\n",
+    "    class P:\n",
+    "        def __init__(self, x):\n",
+    "            self.x = x\n",
+    "        def __getitem__(self, key):\n",
+    "            x.add_constraints()\n",
+    "            return softmax(x[key])\n",
+    "    \n",
+    "    x = X(x)\n",
+    "    p = P(x)\n",
+    "    \n",
+    "    schedule = [\n",
+    "        ('Aug', get_month_generator(2019, 8), 0.99)\n",
+    "    ]\n",
+    "    class StagedValue:\n",
+    "        def __init__(self, num):\n",
+    "            self.num = num\n",
+    "    class Stager:\n",
+    "        def __init__(self):\n",
+    "            self.total = 0\n",
+    "            self.constraints = []\n",
+    "        def __getitem__(self, key):\n",
+    "            self.total += key\n",
+    "            new_constraints = None # TODO Implement new constraints\n",
+    "            self.constraints.append(new_constraints)\n",
+    "            return StagedValue(key)\n",
+    "    \n",
+    "    # TODO How do I get this for multiple situations\n",
+    "    schedule = [ # Have a schedule generator. Maybe iterate through after staging to activate\n",
+    "        ('Aug', get_month_generator(2019, 8), 0.99),\n",
+    "        ('Sep', get_months_generator(2019, [8, 9], p=p[2]), 0.99),\n",
+    "        ('All', get_month_generator(2019, [8, 9]), 0.99)\n",
+    "    ]\n",
+    "    \n",
+    "    # need to create function that accepts the right number of parameters and stuff\n",
+    "    # use sparse matrix to represent constraints\n",
+    "    class X:\n",
+    "        def __init__(self, x):\n",
+    "            self.x = x\n",
+    "            self.current = 0\n",
+    "        def __getitem__(self, key):\n",
+    "            values = self.x[self.current: self.current+key]\n",
+    "            self.current += key\n",
+    "            return values\n",
+    "        def __len__(self):\n",
+    "            return self.current\n",
+    "        \n",
+    "    def get_schedule(x):\n",
+    "        x = X(x)\n",
+    "        processed_schedule = []\n",
+    "        for name, func, params, probability in schedule:\n",
+    "            # process into actual schedule\n",
+    "            new_params = []\n",
+    "            for param in params:\n",
+    "                if type(param) is StagedValue:\n",
+    "                    new_params.append(x[param.num])\n",
+    "                else:\n",
+    "                    new_params.append(param)\n",
+    "            schedule_item = (name, func(*params), probability)\n",
+    "            processed_schedule.append(schedule_item)\n",
+    "        return processed_schedule\n",
+    "    \n",
+    "    return get_schedule, constraints, x0\n",
+    "    \n",
+    "    \n",
+    "    \n",
+    "    schedule = [ # Have a schedule generator. Maybe iterate through after staging to activate\n",
+    "        ('Aug', get_month_generator(2019, 8), 0.99),\n",
+    "        ('Sep', get_months_generator(2019, [8, 9], p=p[2]), x[1]),\n",
+    "        ('Oct', get_month_generator(2019, [8, 9, 10], p=p[3]), x[1]),\n",
+    "        ('Oct', get_month_generator(2019, [8, 9, 10]), 0.99)\n",
+    "    ]\n",
+    "    \n",
+    "    schedule = [\n",
+    "        ('2019-1', get_months_gen(2019, range(1, 13), p=x[12]), x[1]),\n",
+    "        ('2019-2', get_months_gen(2019, range(1, 13), p=x[12]), x[1]),\n",
+    "        ('2019-3', get_months_gen(2019, range(1, 13), p=x[12]), x[1]),\n",
+    "        ('2019-4', get_months_gen(2019, range(1, 13), p=x[12]), x[1]),\n",
+    "        ('2019-5', get_months_gen(2019, range(1, 13), p=x[12]), x[1]),\n",
+    "        ('2019-6', get_months_gen(2019, range(1, 13), p=x[12]), x[1]),\n",
+    "        ('2019-7', get_months_gen(2019, range(1, 13), p=x[12]), x[1]),\n",
+    "        ('2019-8', get_months_gen(2019, range(1, 13), p=x[12]), x[1]),\n",
+    "        ('2019-9', get_months_gen(2019, range(1, 13), p=x[12]), x[1]),\n",
+    "        ('2019-10', get_months_gen(2019, range(1, 13), p=x[12]), x[1]),\n",
+    "        ('2019-11', get_months_gen(2019, range(1, 13), p=x[12]), x[1]),\n",
+    "        ('2019-12', get_months_gen(2019, range(1, 13), p=x[12]), x[1]),\n",
+    "        ('2019', get_year_generator(2019), 0.99),\n",
+    "#         ('2020', get_years_gen(2019, 2020), x[1]),\n",
+    "#         ('2020s', get_years_gen(2019, 2029), x[1]),\n",
+    "#         ('2000-2100', get_years_gen(2000, 2100), x[1]),\n",
+    "#         ('1900-2100', get_years_gen(1900, 2100), x[1]),\n",
+    "#         ('1-2100', get_years_gen(1, 2100), x[1]),\n",
+    "    ]\n",
+    "    \n",
+    "    \n",
+    "    return schedule, len(x)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Optimize the last two, so the new one and the most recent before that. That way, there's a lag time, but most of it is set. We can also save the progresss of the model to make the running occur faster"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "NameError",
+     "evalue": "name 'get_years_gen' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+      "\u001b[1;32m<ipython-input-15-df03995773a2>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m     13\u001b[0m     \u001b[1;33m(\u001b[0m\u001b[1;34m'Jun'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mget_months_gen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m2019\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;36m6\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0.85\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     14\u001b[0m     \u001b[1;33m(\u001b[0m\u001b[1;34m'2019'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mget_year_generator\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m2019\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0.85\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 15\u001b[1;33m     \u001b[1;33m(\u001b[0m\u001b[1;34m'2020'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mget_years_gen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m2019\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m2020\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0.85\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     16\u001b[0m     \u001b[1;33m(\u001b[0m\u001b[1;34m'2020s'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mget_years_gen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m2019\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m2029\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0.85\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     17\u001b[0m     \u001b[1;33m(\u001b[0m\u001b[1;34m'2000-2100'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mget_years_gen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m2000\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m2100\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0.85\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
+      "\u001b[1;31mNameError\u001b[0m: name 'get_years_gen' is not defined"
+     ]
+    }
+   ],
+   "source": [
+    "schedule = [\n",
+    "    ('Jul', get_months_gen(2019, [7]), 0.99),\n",
+    "    ('Aug', get_months_gen(2019, [8]), 0.85),\n",
+    "    ('Sep', get_months_gen(2019, [9]), 0.85),\n",
+    "    ('Oct', get_months_gen(2019, [10]), 0.85),\n",
+    "    ('Nov', get_months_gen(2019, [11]), 0.85),\n",
+    "    ('Dec', get_months_gen(2019, [12]), 0.85),\n",
+    "    ('Jan', get_months_gen(2019, [1]), 0.85),\n",
+    "    ('Feb', get_months_gen(2019, [2]), 0.85),\n",
+    "    ('Mar', get_months_gen(2019, [3]), 0.85),\n",
+    "    ('Apr', get_months_gen(2019, [4]), 0.85),\n",
+    "    ('May', get_months_gen(2019, [5]), 0.85),\n",
+    "    ('Jun', get_months_gen(2019, [6]), 0.85),\n",
+    "    ('2019', get_year_generator(2019), 0.85),\n",
+    "    ('2020', get_years_gen(2019, 2020), 0.85),\n",
+    "    ('2020s', get_years_gen(2019, 2029), 0.85),\n",
+    "    ('2000-2100', get_years_gen(2000, 2100), 0.85),\n",
+    "    ('1900-2100', get_years_gen(1900, 2100), 0.85),\n",
+    "    ('1-2100', get_years_gen(1, 2100), 0.85),\n",
+    "]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [],
+   "source": [
+    "run_schedule(schedule)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Minibatch 100 0.5375\n",
+      "Trained July in 6208 samples\n",
+      "Trained Aug in 3072 samples\n",
+      "Trained Sep in 32 samples\n",
+      "Minibatch 100 0.571875\n",
+      "Trained Oct in 6016 samples\n",
+      "Trained Nov in 32 samples\n",
+      "Trained Dec in 64 samples\n",
+      "Trained Jan in 32 samples\n",
+      "Minibatch 100 0.79375\n",
+      "Trained Feb in 3328 samples\n",
+      "Trained Mar in 64 samples\n",
+      "Trained Apr in 32 samples\n",
+      "Trained May in 32 samples\n",
+      "Trained Jun in 1568 samples\n",
+      "Trained Jul-Dec in 32 samples\n",
+      "Trained 2019 in 3008 samples\n",
+      "Minibatch 100 0.75\n",
+      "Trained 2020 in 5312 samples\n",
+      "Minibatch 100 0.584375\n",
+      "Minibatch 200 0.778125\n",
+      "Minibatch 300 0.79375\n",
+      "Trained 2020s in 9856 samples\n",
+      "Minibatch 100 0.509375\n",
+      "Minibatch 200 0.6625\n",
+      "Minibatch 300 0.6875\n",
+      "Minibatch 400 0.75625\n",
+      "Minibatch 500 0.796875\n",
+      "Minibatch 600 0.7875\n",
+      "Trained 2000-2100 in 19904 samples\n",
+      "Trained 1900-2100 in 2944 samples\n",
+      "Minibatch 100 0.45625\n",
+      "Minibatch 200 0.5125\n",
+      "Minibatch 300 0.6125\n",
+      "Minibatch 400 0.65\n",
+      "Minibatch 500 0.65625\n",
+      "Minibatch 600 0.68125\n",
+      "Minibatch 700 0.696875\n",
+      "Minibatch 800 0.721875\n",
+      "Minibatch 900 0.734375\n",
+      "Minibatch 1000 0.746875\n",
+      "Minibatch 1100 0.778125\n",
+      "Minibatch 1200 0.80625\n",
+      "Minibatch 1300 0.825\n",
+      "Trained 1-2100 in 42400 samples\n",
+      "Minibatch 100 0.815625\n",
+      "Minibatch 200 0.85625\n",
+      "Minibatch 300 0.85625\n",
+      "Minibatch 400 0.884375\n",
+      "Minibatch 500 0.853125\n",
+      "Minibatch 600 0.85\n",
+      "Minibatch 700 0.890625\n",
+      "Minibatch 800 0.9\n",
+      "Minibatch 900 0.90625\n",
+      "Minibatch 1000 0.90625\n",
+      "Minibatch 1100 0.884375\n",
+      "Minibatch 1200 0.925\n",
+      "Minibatch 1300 0.940625\n",
+      "Minibatch 1400 0.925\n",
+      "Minibatch 1500 0.946875\n",
+      "Minibatch 1600 0.9375\n",
+      "Minibatch 1700 0.94375\n",
+      "Minibatch 1800 0.965625\n",
+      "Minibatch 1900 0.95\n",
+      "Minibatch 2000 0.953125\n",
+      "Minibatch 2100 0.928125\n",
+      "Minibatch 2200 0.940625\n",
+      "Minibatch 2300 0.959375\n",
+      "Minibatch 2400 0.9625\n",
+      "Minibatch 2500 0.959375\n",
+      "Minibatch 2600 0.96875\n",
+      "Minibatch 2700 0.971875\n",
+      "Minibatch 2800 0.96875\n",
+      "Minibatch 2900 0.971875\n",
+      "Minibatch 3000 0.971875\n",
+      "Minibatch 3100 0.9625\n",
+      "Minibatch 3200 0.984375\n",
+      "Minibatch 3300 0.946875\n",
+      "Minibatch 3400 0.95\n",
+      "Minibatch 3500 0.978125\n",
+      "Minibatch 3600 0.975\n",
+      "Minibatch 3700 0.98125\n",
+      "Minibatch 3800 0.975\n",
+      "Minibatch 3900 0.98125\n",
+      "Minibatch 4000 0.98125\n",
+      "Minibatch 4100 0.990625\n",
+      "Minibatch 4200 0.990625\n",
+      "Minibatch 4300 0.978125\n",
+      "Trained 1-2100 in 138720 samples\n",
+      "Training complete after 242656 samples\n"
+     ]
+    }
+   ],
+   "source": [
+    "from itertools import chain\n",
+    "\n",
+    "reset_model()\n",
+    "\n",
+    "schedule = [\n",
+    "    ('July', get_month_generator(2019, 7), 0.85),\n",
+    "    ('Aug', get_months_gen(2019, range(7, 9)), 0.85),\n",
+    "    ('Sep', get_months_gen(2019, range(7, 10)), 0.85),\n",
+    "    ('Oct', get_months_gen(2019, range(7, 11)), 0.85),\n",
+    "    ('Nov', get_months_gen(2019, range(7, 12)), 0.85),\n",
+    "    ('Dec', get_months_gen(2019, range(7, 13)), 0.85),\n",
+    "    ('Jan', get_months_gen(2019, chain(range(1, 2), range(7, 13))), 0.85),\n",
+    "    ('Feb', get_months_gen(2019, chain(range(1, 3), range(7, 13))), 0.85),\n",
+    "    ('Mar', get_months_gen(2019, chain(range(1, 4), range(7, 13))), 0.85),\n",
+    "    ('Apr', get_months_gen(2019, chain(range(1, 5), range(7, 13))), 0.85),\n",
+    "    ('May', get_months_gen(2019, chain(range(1, 6), range(7, 13))), 0.85),\n",
+    "    ('Jun', get_months_gen(2019, chain(range(1, 7), range(7, 13))), 0.85),\n",
+    "    ('Jul-Dec', get_months_gen(2019, chain(range(1, 8), range(7, 13))), 0.85),\n",
+    "    ('2019', get_year_generator(2019), 0.85),\n",
+    "    ('2020', get_years_gen(2019, 2020), 0.85),\n",
+    "    ('2020s', get_years_gen(2019, 2029), 0.85),\n",
+    "    ('2000-2100', get_years_gen(2000, 2100), 0.85),\n",
+    "    ('1900-2100', get_years_gen(1900, 2100), 0.85),\n",
+    "    ('1-2100', get_years_gen(1, 2100), 0.85),\n",
+    "    ('1-2100', get_years_gen(1, 2100), 0.999),\n",
+    "]\n",
+    "\n",
+    "bad_schedule = [\n",
+    "    ('1-2100', get_years_gen(1, 2100), 0.85)\n",
+    "]\n",
+    "\n",
+    "schedule_2 = list(map(lambda item: (item[0], item[1], 0.5), schedule))\n",
+    "schedule_2[-1] = schedule[-1]\n",
+    "\n",
+    "schedule_3 = list(map(lambda item: (item[0], item[1], 0.2), schedule))\n",
+    "schedule_3[-1] = schedule[-1]\n",
+    "\n",
+    "run_schedule(schedule)\n",
+    "\n",
+    "# print('\\n\\n\\n')\n",
+    "# reset_model()\n",
+    "# run_schedule(model, schedule_2)\n",
+    "# print('\\n\\n\\n')\n",
+    "# reset_model()\n",
+    "# run_schedule(model, schedule_3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([0., 0., 0., 0., 0., 0., 1.])"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "convert_to_vector(date(2019,7,28))[1]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[3.21856205e-04, 4.16064868e-04, 3.76252714e-03, 1.97594166e-02,\n",
+       "        8.88420641e-01, 7.28261918e-02, 1.44934375e-02]], dtype=float32)"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "model.predict(convert_to_vector(date(2035,5,18))[0].reshape((1, -1)))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "So far, it seems that a model with 0.85 threshold trains with 160k samples and a model with 0.5 threshold trains with 120k samples.\n",
+    "\n",
+    "I tested a model with no grading. It got 100k batches (3,200k samples) without having improved its' accuracy at all."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Can we train some type of model that takes in training histories and outputs the ideal training history?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 117,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Epoch 1/1\n",
+      "100000/100000 [==============================] - 19s 190us/step - loss: 0.4153 - acc: 0.8324\n"
+     ]
+    }
+   ],
+   "source": [
+    "stuff = model.fit(xs, ys)\n",
+    "\n",
+    "stuff\n",
+    "print(stuff.history['acc'])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Next steps:\n",
+    "\n",
+    "- Overfit on a single sample of say 1000, then as soon as its' prediction is better than chance, move along to another set. \n",
+    "  - Compare to pure random\n",
+    "- Overfit on a sample of just a few, and then start throwing in new ones? - This was the whole strategy from before\n",
+    "  - This would work, but we want our sample to be better than just chance, how do we determine the sample?\n",
+    "\n",
+    "1. Just do in order with random distributions up until a certain threshold\n",
+    "  - Test different thresholds for progression, 50% accuracy, 90%, etc\n",
+    "2. Change distribution to reflect the learning that needs to happen\n",
+    "  - If you get a certain month right 90% of the time, only show it 10% of the time or something like that - determine this distrubtion\n",
+    "3. Learn the distribution using some kind of statistics or model\n",
+    "4. Create an ml model that perfects this situation\n",
+    "\n",
+    "Also, should be considering taking a month where we know the date and asking for another date. So if we know that today is the 18th and a Thursday, we can infer that tomorrow is the 19th and a Friday."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/Dates/Exploration.ods b/Dates/Exploration.ods
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diff --git a/Dates/Flashcards.ipynb b/Dates/Flashcards.ipynb
new file mode 100644
index 0000000..a624371
--- /dev/null
+++ b/Dates/Flashcards.ipynb
@@ -0,0 +1,229 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Generate date flashcards for Anki\n",
+    "https://github.com/kerrickstaley/genanki"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1270607229"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import random\n",
+    "\n",
+    "def get_id():\n",
+    "    return random.randrange(1<<32)\n",
+    "get_id()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import genanki\n",
+    "\n",
+    "front_back = genanki.Model(\n",
+    "  get_id(),\n",
+    "  'Front Back Model',\n",
+    "  fields=[\n",
+    "    {'name': 'Front'},\n",
+    "    {'name': 'Back'},\n",
+    "  ],\n",
+    "  templates=[\n",
+    "    {\n",
+    "      'name': 'Card',\n",
+    "      'qfmt': '{{Front}}',\n",
+    "      'afmt': '{{Back}}',\n",
+    "    },\n",
+    "  ]\n",
+    ")\n",
+    "\n",
+    "def make_deck(cards, name):\n",
+    "    # Cards is a list of fields\n",
+    "    deck = genanki.Deck(get_id(), name)\n",
+    "    \n",
+    "    for card in cards:\n",
+    "        note = genanki.Note(\n",
+    "            model=front_back,\n",
+    "            fields=card\n",
+    "        )\n",
+    "        deck.add_note(note)\n",
+    "    \n",
+    "    return deck\n",
+    "\n",
+    "def write_decks(decks, name):\n",
+    "    genanki.Package(decks).write_to_file(f'{name}.apkg')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "presidents = [    \n",
+    "    \"George Washington\",\n",
+    "    \"John Adams\",\n",
+    "    \"Thomas Jefferson\",\n",
+    "    \"James Madison\",\n",
+    "    \"James Monroe\",\n",
+    "    \"John Quincy Adams\",\n",
+    "    \"Andrew Jackson\",\n",
+    "    \"Martin Van Buren\",\n",
+    "    \"William Henry Harrison\",\n",
+    "    \"John Tyler\",\n",
+    "    \"James K. Polk\",\n",
+    "    \"Zachary Taylor\",\n",
+    "    \"Millard Fillmore\",\n",
+    "    \"Franklin Pierce\",\n",
+    "    \"James Buchanan\",\n",
+    "    \"Abraham Lincoln\",\n",
+    "    \"Andrew Johnson\",\n",
+    "    \"Ulysses S. Grant\",\n",
+    "    \"Rutherford B. Hayes\",\n",
+    "    \"James A. Garfield\",\n",
+    "    \"Chester A. Arthur\",\n",
+    "    \"Grover Cleaveland (First term)\",\n",
+    "    \"Benjamin Harrison\",\n",
+    "    \"Grover Cleaveland (Second term)\",\n",
+    "    \"William McKinley\",\n",
+    "    \"Theodore Roosevelt\",\n",
+    "    \"William Howard Taft\",\n",
+    "    \"Woodrow Wilson\",\n",
+    "    \"Warren G. Harding\",\n",
+    "    \"Calvin Coolidge\",\n",
+    "    \"Herbert Hoover\",\n",
+    "    \"Franklin D. Roosevelt\",\n",
+    "    \"Harry S. Truman\",\n",
+    "    \"Dwight D. Eisenhower\",\n",
+    "    \"John F. Kennedy\",\n",
+    "    \"Lyndon B. Johnson\",\n",
+    "    \"Richard Nixon\",\n",
+    "    \"Gerald Ford\",\n",
+    "    \"Jimmy Carter\",\n",
+    "    \"Ronald Reagan\",\n",
+    "    \"George H. W. Bush\",\n",
+    "    \"Bill Clinton\",\n",
+    "    \"George W. Bush\",\n",
+    "    \"Barack Obama\",\n",
+    "    \"Donald Trump\",\n",
+    "]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def ordinal(n):\n",
+    "    s = str(n)\n",
+    "    if 10 < n < 20:\n",
+    "        s += 'th'\n",
+    "    elif n % 10 == 1:\n",
+    "        s += 'st'\n",
+    "    elif n % 10 == 2:\n",
+    "        s += 'nd'\n",
+    "    elif n % 10 == 3:\n",
+    "        s += 'rd'\n",
+    "    else:\n",
+    "        s += 'th'\n",
+    "    return s\n",
+    "\n",
+    "def ordgen():\n",
+    "    i = 1\n",
+    "    while True:\n",
+    "        yield ordinal(i)\n",
+    "        i += 1\n",
+    "name_first = []\n",
+    "num_first = []\n",
+    "for name, num in zip(presidents, ordgen()):\n",
+    "    card = [name, num]\n",
+    "    card2 = [num, name]\n",
+    "    name_first.append(card)\n",
+    "    num_first.append(card2)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "name_first"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import random\n",
+    "from IPython.display import clear_output\n",
+    "while True:\n",
+    "    clear_output()\n",
+    "    x, y = random.choice(name_first)\n",
+    "    if input(x) != '':\n",
+    "        break\n",
+    "    if input(y) != '':\n",
+    "        break"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "write_decks([make_deck(name_first, 'Name first'), make_deck(num_first, 'Number first')], 'presidents')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/Dates/Flashcards_1.ipynb b/Dates/Flashcards_1.ipynb
new file mode 100644
index 0000000..185f2ec
--- /dev/null
+++ b/Dates/Flashcards_1.ipynb
@@ -0,0 +1,250 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Generate date flashcards for Anki\n",
+    "https://github.com/kerrickstaley/genanki"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from datetime import date"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "522800796"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import random\n",
+    "\n",
+    "def get_id():\n",
+    "    return random.randrange(1<<32)\n",
+    "get_id()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import genanki\n",
+    "\n",
+    "front_back = genanki.Model(\n",
+    "  get_id(),\n",
+    "  'Front Back Model',\n",
+    "  fields=[\n",
+    "    {'name': 'Date'},\n",
+    "    {'name': 'Day'},\n",
+    "  ],\n",
+    "  templates=[\n",
+    "    {\n",
+    "      'name': 'Date Card',\n",
+    "      'qfmt': '{{Date}}',\n",
+    "      'afmt': '{{Day}}',\n",
+    "    },\n",
+    "  ]\n",
+    ")\n",
+    "\n",
+    "def make_deck(cards, name):\n",
+    "    # Cards is a list of fields\n",
+    "    deck = genanki.Deck(get_id(), name)\n",
+    "    \n",
+    "    for card in cards:\n",
+    "        note = genanki.Note(\n",
+    "            model=front_back,\n",
+    "            fields=card\n",
+    "        )\n",
+    "        deck.add_note(note)\n",
+    "    \n",
+    "    return deck\n",
+    "\n",
+    "def write_decks(decks, name='dates'):\n",
+    "    genanki.Package(decks).write_to_file(f'{name}.apkg')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "date(2019, 8, 28).weekday()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import calendar\n",
+    "\n",
+    "def make_august_weekday_deck(days_string):\n",
+    "    wkday_map = {\n",
+    "        'M': 0,\n",
+    "        'T': 1,\n",
+    "        'W': 2,\n",
+    "        'R': 3, \n",
+    "        'F': 4, \n",
+    "        'S': 5,\n",
+    "        'U': 6\n",
+    "    }\n",
+    "    \n",
+    "    days = sorted([wkday_map[day] for day in days_string])\n",
+    "    \n",
+    "    names = [calendar.day_abbr[i] for i in days]\n",
+    "    name = 'August, 2019 (' + ', '.join(names) + ')'\n",
+    "    \n",
+    "    cards = []\n",
+    "    for i in range(31):\n",
+    "        day = date(2019, 8, i+1)\n",
+    "        if day.weekday() not in days:\n",
+    "            continue\n",
+    "        date_string = day.strftime('%B %d, %Y')\n",
+    "        day_string = day.strftime('%A')\n",
+    "        cards.append([date_string, day_string])\n",
+    "        \n",
+    "    return make_deck(cards, name)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def make_august_decks():\n",
+    "    \n",
+    "    schedule = 'MRSWUTF'\n",
+    "    \n",
+    "    decks = []\n",
+    "    \n",
+    "    for i in range(1, len(schedule)):\n",
+    "        decks.append(make_august_weekday_deck(schedule[0:i+1]))\n",
+    "        \n",
+    "    write_decks(decks, 'August')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "make_august_decks()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from calendar import monthrange\n",
+    "def make_month_deck(month, year=2019):\n",
+    "    \n",
+    "    name = date(year, month, 1).strftime('%B, %Y')\n",
+    "    \n",
+    "    cards = []\n",
+    "    for i in range(monthrange(2019, month)[1]):\n",
+    "        day = date(2019, month, i+1)\n",
+    "        date_string = day.strftime('%B %d, %Y')\n",
+    "        day_string = day.strftime('%A')\n",
+    "        cards.append([date_string, day_string])\n",
+    "        \n",
+    "    return make_deck(cards, name)\n",
+    "\n",
+    "def make_months_deck(months, year=2019):\n",
+    "    \n",
+    "    name = ', '.join([date(year, month, 1).strftime('%B') for month in months]) + date(year, 1, 1).strftime(' - %Y')\n",
+    "    \n",
+    "    cards = []\n",
+    "    for month in months:\n",
+    "        for i in range(monthrange(2019, month)[1]):\n",
+    "            day = date(2019, month, i+1)\n",
+    "            date_string = day.strftime('%B %d, %Y')\n",
+    "            day_string = day.strftime('%A')\n",
+    "            cards.append([date_string, day_string])\n",
+    "        \n",
+    "    return make_deck(cards, name)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "write_decks([make_month_deck(9)], 'September')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "write_decks([make_months_deck([8, 9])], 'Aug,Sept')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/Dates/Personal Trainer.ipynb b/Dates/Personal Trainer.ipynb
new file mode 100644
index 0000000..43535ef
--- /dev/null
+++ b/Dates/Personal Trainer.ipynb	
@@ -0,0 +1,117 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from datetime import date\n",
+    "from calendar import day_abbr, monthrange\n",
+    "\n",
+    "\n",
+    "def month_wkdy(month, days_string='MTWRFSU', year=2019):\n",
+    "    wkday_map = {\n",
+    "        'M': 0,\n",
+    "        'T': 1,\n",
+    "        'W': 2,\n",
+    "        'R': 3, \n",
+    "        'F': 4, \n",
+    "        'S': 5,\n",
+    "        'U': 6\n",
+    "    }\n",
+    "    \n",
+    "    days = sorted([wkday_map[day] for day in days_string])\n",
+    "    \n",
+    "    names = [day_abbr[i] for i in days]\n",
+    "    \n",
+    "    name = date(year, month, 1).strftime('%B, %Y (' + ', '.join(names) + ')')\n",
+    "    \n",
+    "    cards = []\n",
+    "    for i in range(monthrange(2019, month)[1]):\n",
+    "        day = date(2019, month, i+1)\n",
+    "        if day.weekday() not in days:\n",
+    "            continue\n",
+    "        date_string = day.strftime('%B %d, %Y')\n",
+    "        day_string = day.strftime('%A')\n",
+    "        cards.append([date_string, day_string])\n",
+    "        \n",
+    "    return cards\n",
+    "\n",
+    "def aug_wkdy(days_string):\n",
+    "    return month_wkdy(8, days_string)\n",
+    "\n",
+    "def sept_wkdy(days_string):\n",
+    "    return month_wkdy(9, days_string)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import random\n",
+    "\n",
+    "def train(cards):\n",
+    "    while True:\n",
+    "        date, day = random.choice(cards)\n",
+    "        if input(date):\n",
+    "            break\n",
+    "        if input(day):\n",
+    "            break\n",
+    "        print()\n",
+    "\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "September 05, 2019\n",
+      "Thursday\n",
+      "\n",
+      "September 05, 2019\n"
+     ]
+    }
+   ],
+   "source": [
+    "train(sept_wkdy('MR'))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

From 3426c417e4a5b059f3b64ef1eb90a115ce919a57 Mon Sep 17 00:00:00 2001
From: Ben Thayer <ben@benthayer.com>
Date: Thu, 26 Sep 2019 14:37:49 -0500
Subject: [PATCH 2/5] Added double days

---
 Dates/Double Day Flashcards.ipynb | 237 ++++++++++++++++++++++++++++++
 1 file changed, 237 insertions(+)
 create mode 100644 Dates/Double Day Flashcards.ipynb

diff --git a/Dates/Double Day Flashcards.ipynb b/Dates/Double Day Flashcards.ipynb
new file mode 100644
index 0000000..9fb8a46
--- /dev/null
+++ b/Dates/Double Day Flashcards.ipynb	
@@ -0,0 +1,237 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Generate date flashcards for Anki\n",
+    "https://github.com/kerrickstaley/genanki"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "from datetime import date"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "1237276931"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import random\n",
+    "\n",
+    "def get_id():\n",
+    "    return random.randrange(1<<32)\n",
+    "get_id()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "import genanki\n",
+    "\n",
+    "# Show any date from month with day\n",
+    "# Show other date from month with blank day\n",
+    "\n",
+    "dday = genanki.Model(\n",
+    "  get_id(),\n",
+    "  'Double Day',\n",
+    "  fields=[\n",
+    "    {'name': 'Date1'},\n",
+    "    {'name': 'Day1'},\n",
+    "    {'name': 'Date2'},\n",
+    "    {'name': 'Day2'},\n",
+    "  ],\n",
+    "  templates=[\n",
+    "    {\n",
+    "      'name': 'Double Day Card',\n",
+    "      'qfmt': '{{Date1}} - {{Day1}}\\n\\n{{Date2}}',\n",
+    "      'afmt': '{{Date1}} - {{Day1}}\\n\\n{{Date2}} - {{Day2}}',\n",
+    "    },\n",
+    "  ]\n",
+    ")\n",
+    "\n",
+    "def make_deck(cards, name):\n",
+    "    # Cards is a list of fields\n",
+    "    deck = genanki.Deck(get_id(), name)\n",
+    "    \n",
+    "    for card in cards:\n",
+    "        note = genanki.Note(\n",
+    "            model=dday,\n",
+    "            fields=card\n",
+    "        )\n",
+    "        deck.add_note(note)\n",
+    "    \n",
+    "    return deck\n",
+    "\n",
+    "def write_decks(decks, name='dates'):\n",
+    "    genanki.Package(decks).write_to_file(f'{name}.apkg')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "date(2019, 8, 28).weekday()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "import random\n",
+    "from datetime import datetime, timedelta\n",
+    "from calendar import monthrange\n",
+    "\n",
+    "def make_double_deck(n=11000):\n",
+    "    year = 2019\n",
+    "    month = random.choice(range(12)) + 1\n",
+    "    max_day = monthrange(year, month)[1]\n",
+    "    \n",
+    "    for i in range(n):\n",
+    "        day = random.choice(range(max_day)) + 1\n",
+    "        reference_day = day\n",
+    "        while day == reference_day:\n",
+    "            reference_day = random.choice(range(max_day)) + 1\n",
+    "    \n",
+    "\n",
+    "def make_double_deck(months, year=2019):\n",
+    "    \n",
+    "    name = ', '.join([date(year, month, 1).strftime('%B') for month in months]) + date(year, 1, 1).strftime(' - %Y')\n",
+    "    \n",
+    "    cards = []\n",
+    "    for month in months:\n",
+    "        for i in range(monthrange(2019, month)[1]):\n",
+    "            day = date(2019, month, i+1)\n",
+    "            date_string = day.strftime('%B %d, %Y')\n",
+    "            day_string = day.strftime('%A')\n",
+    "            cards.append([date_string, day_string])\n",
+    "        \n",
+    "    return make_deck(cards, name)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "write_decks([make_month_deck(9)], 'September')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "write_decks([make_double_deck([i + 1 for i in range (12)])])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1\n",
+      "4\n",
+      "4\n",
+      "0\n",
+      "2\n",
+      "5\n",
+      "0\n",
+      "3\n",
+      "6\n",
+      "1\n",
+      "4\n",
+      "6\n"
+     ]
+    }
+   ],
+   "source": [
+    "from datetime import date\n",
+    "for i in range(12):\n",
+    "    a = date(2019, i + 1, 1)\n",
+    "    print(a.weekday())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

From 099e3256f2317fe5521372f6a4c9bfefa3024d60 Mon Sep 17 00:00:00 2001
From: Ben Thayer <ben@benthayer.com>
Date: Thu, 26 Sep 2019 20:33:50 -0500
Subject: [PATCH 3/5] Renamed files

---
 Dates/{Flashcards_1.ipynb => Date Flashcards.ipynb} | 0
 Dates/{Dates.ipynb => Machine Learning.ipynb}       | 0
 Dates/{Flashcards.ipynb => Presidents.ipynb}        | 0
 3 files changed, 0 insertions(+), 0 deletions(-)
 rename Dates/{Flashcards_1.ipynb => Date Flashcards.ipynb} (100%)
 rename Dates/{Dates.ipynb => Machine Learning.ipynb} (100%)
 rename Dates/{Flashcards.ipynb => Presidents.ipynb} (100%)

diff --git a/Dates/Flashcards_1.ipynb b/Dates/Date Flashcards.ipynb
similarity index 100%
rename from Dates/Flashcards_1.ipynb
rename to Dates/Date Flashcards.ipynb
diff --git a/Dates/Dates.ipynb b/Dates/Machine Learning.ipynb
similarity index 100%
rename from Dates/Dates.ipynb
rename to Dates/Machine Learning.ipynb
diff --git a/Dates/Flashcards.ipynb b/Dates/Presidents.ipynb
similarity index 100%
rename from Dates/Flashcards.ipynb
rename to Dates/Presidents.ipynb

From 86934d811c50553990341dd2202fc42aaf79e765 Mon Sep 17 00:00:00 2001
From: Ben Thayer <ben@benthayer.com>
Date: Fri, 27 Sep 2019 01:04:20 -0500
Subject: [PATCH 4/5] Finished adding double day flashcards

---
 Dates/.gitignore                  |   2 +-
 Dates/Double Day Flashcards.ipynb | 125 +++++++++++++++++++++++-------
 2 files changed, 97 insertions(+), 30 deletions(-)

diff --git a/Dates/.gitignore b/Dates/.gitignore
index f7fd723..b184dd6 100644
--- a/Dates/.gitignore
+++ b/Dates/.gitignore
@@ -1 +1 @@
-*.apgk
+*.apkg
diff --git a/Dates/Double Day Flashcards.ipynb b/Dates/Double Day Flashcards.ipynb
index 9fb8a46..ed7cfe0 100644
--- a/Dates/Double Day Flashcards.ipynb	
+++ b/Dates/Double Day Flashcards.ipynb	
@@ -21,16 +21,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "1237276931"
+       "2263097491"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -45,10 +45,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
-   "metadata": {
-    "collapsed": true
-   },
+   "execution_count": 35,
+   "metadata": {},
    "outputs": [],
    "source": [
     "import genanki\n",
@@ -68,8 +66,42 @@
     "  templates=[\n",
     "    {\n",
     "      'name': 'Double Day Card',\n",
-    "      'qfmt': '{{Date1}} - {{Day1}}\\n\\n{{Date2}}',\n",
-    "      'afmt': '{{Date1}} - {{Day1}}\\n\\n{{Date2}} - {{Day2}}',\n",
+    "      'qfmt': \"\"\"\n",
+    "<div style=\"width:100%;text-align:center\">\n",
+    "<div style=\"width:240px;display:inline-block\">\n",
+    "\n",
+    "<div style=\"width:100%;display:inline-block\">\n",
+    "  <div style=\"width:150px;float:left;\" align=\"left\">{{Date1}}</div>\n",
+    "  <div style=\"width:30%;float:right\" align=\"right\">{{Day1}}</div>\n",
+    "  \n",
+    "</div>\n",
+    "<hr>\n",
+    "\n",
+    "<div style=\"width:100%;display:inline-block\">\n",
+    "  <div style=\"width:150px;float:left;\" align=\"left\">{{Date2}}</div>\n",
+    "  <div style=\"width:30%;float:right\" align=\"right\"></div>\n",
+    "</div>\n",
+    "\n",
+    "</div>\n",
+    "</div>\"\"\",\n",
+    "      'afmt': \"\"\"\n",
+    "<div style=\"width:100%;text-align:center\">\n",
+    "<div style=\"width:240px;display:inline-block\">\n",
+    "\n",
+    "<div style=\"width:100%;display:inline-block\">\n",
+    "  <div style=\"width:150px;float:left;\" align=\"left\">{{Date1}}</div>\n",
+    "  <div style=\"width:30%;float:right\" align=\"right\">{{Day1}}</div>\n",
+    "  \n",
+    "</div>\n",
+    "<hr>\n",
+    "\n",
+    "<div style=\"width:100%;display:inline-block\">\n",
+    "  <div style=\"width:150px;float:left;\" align=\"left\">{{Date2}}</div>\n",
+    "  <div style=\"width:30%;float:right\" align=\"right\">{{Day2}}</div>\n",
+    "</div>\n",
+    "\n",
+    "</div>\n",
+    "</div>\"\"\"\n",
     "    },\n",
     "  ]\n",
     ")\n",
@@ -93,7 +125,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 36,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "def write_deck(deck):\n",
+    "    genanki.Package([deck]).write_to_file(f'doubledates.apkg')\n",
+    "\n",
+    "write_deck(make_double_deck())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
    "metadata": {},
    "outputs": [
     {
@@ -102,7 +148,7 @@
        "2"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 31,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -113,7 +159,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 18,
    "metadata": {
     "collapsed": true
    },
@@ -121,33 +167,54 @@
    "source": [
     "import random\n",
     "from datetime import datetime, timedelta\n",
-    "from calendar import monthrange\n",
+    "from calendar import monthrange, month_name\n",
     "\n",
     "def make_double_deck(n=11000):\n",
     "    year = 2019\n",
-    "    month = random.choice(range(12)) + 1\n",
-    "    max_day = monthrange(year, month)[1]\n",
+    "    \n",
+    "    cards = []\n",
     "    \n",
     "    for i in range(n):\n",
+    "        month = random.choice(range(12)) + 1\n",
+    "        max_day = monthrange(year, month)[1]\n",
     "        day = random.choice(range(max_day)) + 1\n",
+    "        \n",
     "        reference_day = day\n",
     "        while day == reference_day:\n",
     "            reference_day = random.choice(range(max_day)) + 1\n",
-    "    \n",
-    "\n",
-    "def make_double_deck(months, year=2019):\n",
-    "    \n",
-    "    name = ', '.join([date(year, month, 1).strftime('%B') for month in months]) + date(year, 1, 1).strftime(' - %Y')\n",
-    "    \n",
-    "    cards = []\n",
-    "    for month in months:\n",
-    "        for i in range(monthrange(2019, month)[1]):\n",
-    "            day = date(2019, month, i+1)\n",
-    "            date_string = day.strftime('%B %d, %Y')\n",
-    "            day_string = day.strftime('%A')\n",
-    "            cards.append([date_string, day_string])\n",
     "        \n",
-    "    return make_deck(cards, name)"
+    "        month_str = month_name[month]\n",
+    "        reference_day_str = date(year, month, reference_day).strftime('%A')\n",
+    "        day_str = date(year, month, day).strftime('%A')\n",
+    "        cards.append((\n",
+    "            f\"{month_str} {reference_day}, {year}\",\n",
+    "            f\"{reference_day_str}\",\n",
+    "            f\"{month_str} {day}, {year}\",\n",
+    "            f\"{day_str}\",\n",
+    "            \n",
+    "        ))\n",
+    "    \n",
+    "    return make_deck(cards, \"Doubles\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'Thursday'"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "date(2019, 9, 26).strftime(\"%A\")"
    ]
   },
   {

From 29477030f6a93e87540be506fae157d2a0016d3a Mon Sep 17 00:00:00 2001
From: Ben Thayer <ben@benthayer.com>
Date: Fri, 25 Oct 2019 16:23:53 -0500
Subject: [PATCH 5/5] Start date exploration

---
 Dates/Date Flashcards.ipynb |   4 +-
 Dates/Exploration.ipynb     | 334 ++++++++++++++++++++++++++++++++++++
 2 files changed, 336 insertions(+), 2 deletions(-)
 create mode 100644 Dates/Exploration.ipynb

diff --git a/Dates/Date Flashcards.ipynb b/Dates/Date Flashcards.ipynb
index 185f2ec..6ab87c9 100644
--- a/Dates/Date Flashcards.ipynb	
+++ b/Dates/Date Flashcards.ipynb	
@@ -242,9 +242,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.3"
+   "version": "3.6.2"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }
diff --git a/Dates/Exploration.ipynb b/Dates/Exploration.ipynb
new file mode 100644
index 0000000..24084a8
--- /dev/null
+++ b/Dates/Exploration.ipynb
@@ -0,0 +1,334 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from datetime import datetime\n",
+    "from calendar import day_abbr"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "6"
+      ]
+     },
+     "execution_count": 44,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "datetime(2099, 1, 4).weekday()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[0, 28, 56, 84]"
+      ]
+     },
+     "execution_count": 47,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "[i * 28 for i in range(4)]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "73\n",
+      "15\n",
+      "76\n",
+      "71\n",
+      "26\n",
+      "5\n",
+      "41\n",
+      "17\n",
+      "13\n",
+      "75\n",
+      "92\n",
+      "91\n",
+      "9\n",
+      "52\n",
+      "57\n",
+      "67\n",
+      "32\n",
+      "47\n",
+      "82\n",
+      "89\n"
+     ]
+    }
+   ],
+   "source": [
+    "import random\n",
+    "for i in range(20):\n",
+    "    print(random.randint(0, 99))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1\n",
+      "5\n",
+      "5\n",
+      "5\n",
+      "5\n",
+      "0\n",
+      "3\n",
+      "1\n",
+      "3\n",
+      "3\n",
+      "4\n",
+      "2\n",
+      "5\n",
+      "3\n",
+      "2\n",
+      "0\n",
+      "6\n",
+      "3\n",
+      "5\n",
+      "0\n"
+     ]
+    }
+   ],
+   "source": [
+    "x = [\n",
+    "    73,\n",
+    "    15,\n",
+    "    76,\n",
+    "    71,\n",
+    "    26,\n",
+    "    5,\n",
+    "    41,\n",
+    "    17,\n",
+    "    13,\n",
+    "    75,\n",
+    "    92,\n",
+    "    91,\n",
+    "    9,\n",
+    "    52,\n",
+    "    57,\n",
+    "    67,\n",
+    "    32,\n",
+    "    47,\n",
+    "    82,\n",
+    "    89\n",
+    "]\n",
+    "for y in x:\n",
+    "    print(datetime(2000 + y, 7, 11).weekday())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2000: Sat Tue Wed Sat Mon Thu Sat Tue Fri Sun Wed Fri \n",
+      "2001: Mon Thu Thu Sun Tue Fri Sun Wed Sat Mon Thu Sat \n",
+      "2002: Tue Fri Fri Mon Wed Sat Mon Thu Sun Tue Fri Sun \n",
+      "2003: Wed Sat Sat Tue Thu Sun Tue Fri Mon Wed Sat Mon \n",
+      "2004: Thu Sun Mon Thu Sat Tue Thu Sun Wed Fri Mon Wed \n",
+      "2005: Sat Tue Tue Fri Sun Wed Fri Mon Thu Sat Tue Thu \n",
+      "2006: Sun Wed Wed Sat Mon Thu Sat Tue Fri Sun Wed Fri \n",
+      "2007: Mon Thu Thu Sun Tue Fri Sun Wed Sat Mon Thu Sat \n",
+      "2008: Tue Fri Sat Tue Thu Sun Tue Fri Mon Wed Sat Mon \n",
+      "2009: Thu Sun Sun Wed Fri Mon Wed Sat Tue Thu Sun Tue \n",
+      "2010: Fri Mon Mon Thu Sat Tue Thu Sun Wed Fri Mon Wed \n",
+      "2011: Sat Tue Tue Fri Sun Wed Fri Mon Thu Sat Tue Thu \n",
+      "2012: Sun Wed Thu Sun Tue Fri Sun Wed Sat Mon Thu Sat \n",
+      "2013: Tue Fri Fri Mon Wed Sat Mon Thu Sun Tue Fri Sun \n",
+      "2014: Wed Sat Sat Tue Thu Sun Tue Fri Mon Wed Sat Mon \n",
+      "2015: Thu Sun Sun Wed Fri Mon Wed Sat Tue Thu Sun Tue \n",
+      "2016: Fri Mon Tue Fri Sun Wed Fri Mon Thu Sat Tue Thu \n",
+      "2017: Sun Wed Wed Sat Mon Thu Sat Tue Fri Sun Wed Fri \n",
+      "2018: Mon Thu Thu Sun Tue Fri Sun Wed Sat Mon Thu Sat \n",
+      "2019: Tue Fri Fri Mon Wed Sat Mon Thu Sun Tue Fri Sun \n",
+      "2020: Wed Sat Sun Wed Fri Mon Wed Sat Tue Thu Sun Tue \n",
+      "2021: Fri Mon Mon Thu Sat Tue Thu Sun Wed Fri Mon Wed \n",
+      "2022: Sat Tue Tue Fri Sun Wed Fri Mon Thu Sat Tue Thu \n",
+      "2023: Sun Wed Wed Sat Mon Thu Sat Tue Fri Sun Wed Fri \n",
+      "2024: Mon Thu Fri Mon Wed Sat Mon Thu Sun Tue Fri Sun \n",
+      "2025: Wed Sat Sat Tue Thu Sun Tue Fri Mon Wed Sat Mon \n",
+      "2026: Thu Sun Sun Wed Fri Mon Wed Sat Tue Thu Sun Tue \n",
+      "2027: Fri Mon Mon Thu Sat Tue Thu Sun Wed Fri Mon Wed \n",
+      "2028: Sat Tue Wed Sat Mon Thu Sat Tue Fri Sun Wed Fri \n",
+      "2029: Mon Thu Thu Sun Tue Fri Sun Wed Sat Mon Thu Sat \n",
+      "2030: Tue Fri Fri Mon Wed Sat Mon Thu Sun Tue Fri Sun \n",
+      "2031: Wed Sat Sat Tue Thu Sun Tue Fri Mon Wed Sat Mon \n",
+      "2032: Thu Sun Mon Thu Sat Tue Thu Sun Wed Fri Mon Wed \n",
+      "2033: Sat Tue Tue Fri Sun Wed Fri Mon Thu Sat Tue Thu \n",
+      "2034: Sun Wed Wed Sat Mon Thu Sat Tue Fri Sun Wed Fri \n",
+      "2035: Mon Thu Thu Sun Tue Fri Sun Wed Sat Mon Thu Sat \n",
+      "2036: Tue Fri Sat Tue Thu Sun Tue Fri Mon Wed Sat Mon \n",
+      "2037: Thu Sun Sun Wed Fri Mon Wed Sat Tue Thu Sun Tue \n",
+      "2038: Fri Mon Mon Thu Sat Tue Thu Sun Wed Fri Mon Wed \n",
+      "2039: Sat Tue Tue Fri Sun Wed Fri Mon Thu Sat Tue Thu \n",
+      "2040: Sun Wed Thu Sun Tue Fri Sun Wed Sat Mon Thu Sat \n",
+      "2041: Tue Fri Fri Mon Wed Sat Mon Thu Sun Tue Fri Sun \n",
+      "2042: Wed Sat Sat Tue Thu Sun Tue Fri Mon Wed Sat Mon \n",
+      "2043: Thu Sun Sun Wed Fri Mon Wed Sat Tue Thu Sun Tue \n",
+      "2044: Fri Mon Tue Fri Sun Wed Fri Mon Thu Sat Tue Thu \n",
+      "2045: Sun Wed Wed Sat Mon Thu Sat Tue Fri Sun Wed Fri \n",
+      "2046: Mon Thu Thu Sun Tue Fri Sun Wed Sat Mon Thu Sat \n",
+      "2047: Tue Fri Fri Mon Wed Sat Mon Thu Sun Tue Fri Sun \n",
+      "2048: Wed Sat Sun Wed Fri Mon Wed Sat Tue Thu Sun Tue \n",
+      "2049: Fri Mon Mon Thu Sat Tue Thu Sun Wed Fri Mon Wed \n",
+      "2050: Sat Tue Tue Fri Sun Wed Fri Mon Thu Sat Tue Thu \n",
+      "2051: Sun Wed Wed Sat Mon Thu Sat Tue Fri Sun Wed Fri \n",
+      "2052: Mon Thu Fri Mon Wed Sat Mon Thu Sun Tue Fri Sun \n",
+      "2053: Wed Sat Sat Tue Thu Sun Tue Fri Mon Wed Sat Mon \n",
+      "2054: Thu Sun Sun Wed Fri Mon Wed Sat Tue Thu Sun Tue \n",
+      "2055: Fri Mon Mon Thu Sat Tue Thu Sun Wed Fri Mon Wed \n",
+      "2056: Sat Tue Wed Sat Mon Thu Sat Tue Fri Sun Wed Fri \n",
+      "2057: Mon Thu Thu Sun Tue Fri Sun Wed Sat Mon Thu Sat \n",
+      "2058: Tue Fri Fri Mon Wed Sat Mon Thu Sun Tue Fri Sun \n",
+      "2059: Wed Sat Sat Tue Thu Sun Tue Fri Mon Wed Sat Mon \n",
+      "2060: Thu Sun Mon Thu Sat Tue Thu Sun Wed Fri Mon Wed \n",
+      "2061: Sat Tue Tue Fri Sun Wed Fri Mon Thu Sat Tue Thu \n",
+      "2062: Sun Wed Wed Sat Mon Thu Sat Tue Fri Sun Wed Fri \n",
+      "2063: Mon Thu Thu Sun Tue Fri Sun Wed Sat Mon Thu Sat \n",
+      "2064: Tue Fri Sat Tue Thu Sun Tue Fri Mon Wed Sat Mon \n",
+      "2065: Thu Sun Sun Wed Fri Mon Wed Sat Tue Thu Sun Tue \n",
+      "2066: Fri Mon Mon Thu Sat Tue Thu Sun Wed Fri Mon Wed \n",
+      "2067: Sat Tue Tue Fri Sun Wed Fri Mon Thu Sat Tue Thu \n",
+      "2068: Sun Wed Thu Sun Tue Fri Sun Wed Sat Mon Thu Sat \n",
+      "2069: Tue Fri Fri Mon Wed Sat Mon Thu Sun Tue Fri Sun \n",
+      "2070: Wed Sat Sat Tue Thu Sun Tue Fri Mon Wed Sat Mon \n",
+      "2071: Thu Sun Sun Wed Fri Mon Wed Sat Tue Thu Sun Tue \n",
+      "2072: Fri Mon Tue Fri Sun Wed Fri Mon Thu Sat Tue Thu \n",
+      "2073: Sun Wed Wed Sat Mon Thu Sat Tue Fri Sun Wed Fri \n",
+      "2074: Mon Thu Thu Sun Tue Fri Sun Wed Sat Mon Thu Sat \n",
+      "2075: Tue Fri Fri Mon Wed Sat Mon Thu Sun Tue Fri Sun \n",
+      "2076: Wed Sat Sun Wed Fri Mon Wed Sat Tue Thu Sun Tue \n",
+      "2077: Fri Mon Mon Thu Sat Tue Thu Sun Wed Fri Mon Wed \n",
+      "2078: Sat Tue Tue Fri Sun Wed Fri Mon Thu Sat Tue Thu \n",
+      "2079: Sun Wed Wed Sat Mon Thu Sat Tue Fri Sun Wed Fri \n",
+      "2080: Mon Thu Fri Mon Wed Sat Mon Thu Sun Tue Fri Sun \n",
+      "2081: Wed Sat Sat Tue Thu Sun Tue Fri Mon Wed Sat Mon \n",
+      "2082: Thu Sun Sun Wed Fri Mon Wed Sat Tue Thu Sun Tue \n",
+      "2083: Fri Mon Mon Thu Sat Tue Thu Sun Wed Fri Mon Wed \n",
+      "2084: Sat Tue Wed Sat Mon Thu Sat Tue Fri Sun Wed Fri \n",
+      "2085: Mon Thu Thu Sun Tue Fri Sun Wed Sat Mon Thu Sat \n",
+      "2086: Tue Fri Fri Mon Wed Sat Mon Thu Sun Tue Fri Sun \n",
+      "2087: Wed Sat Sat Tue Thu Sun Tue Fri Mon Wed Sat Mon \n",
+      "2088: Thu Sun Mon Thu Sat Tue Thu Sun Wed Fri Mon Wed \n",
+      "2089: Sat Tue Tue Fri Sun Wed Fri Mon Thu Sat Tue Thu \n",
+      "2090: Sun Wed Wed Sat Mon Thu Sat Tue Fri Sun Wed Fri \n",
+      "2091: Mon Thu Thu Sun Tue Fri Sun Wed Sat Mon Thu Sat \n",
+      "2092: Tue Fri Sat Tue Thu Sun Tue Fri Mon Wed Sat Mon \n",
+      "2093: Thu Sun Sun Wed Fri Mon Wed Sat Tue Thu Sun Tue \n",
+      "2094: Fri Mon Mon Thu Sat Tue Thu Sun Wed Fri Mon Wed \n",
+      "2095: Sat Tue Tue Fri Sun Wed Fri Mon Thu Sat Tue Thu \n",
+      "2096: Sun Wed Thu Sun Tue Fri Sun Wed Sat Mon Thu Sat \n",
+      "2097: Tue Fri Fri Mon Wed Sat Mon Thu Sun Tue Fri Sun \n",
+      "2098: Wed Sat Sat Tue Thu Sun Tue Fri Mon Wed Sat Mon \n",
+      "2099: Thu Sun Sun Wed Fri Mon Wed Sat Tue Thu Sun Tue \n"
+     ]
+    }
+   ],
+   "source": [
+    "for year in range(2000, 2100):\n",
+    "    line = f\"{year}: \"\n",
+    "    for month in range(1, 13):\n",
+    "        line += day_abbr[datetime(year, month, 1).weekday()] + ' '\n",
+    "    print(line)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Wed Sat Sat Tue Thu Sun Tue Fri Mon Wed Sat Mon \n",
+      "Mon Thu Thu Sun Tue Fri Sun Wed Sat Mon Thu Sat \n",
+      "Sat Tue Wed Sat Mon Thu Sat Tue Fri Sun Wed Fri \n",
+      "Fri Mon Mon Thu Sat Tue Thu Sun Wed Fri Mon Wed \n",
+      "Wed Sat Sat Tue Thu Sun Tue Fri Mon Wed Sat Mon \n",
+      "Mon Thu Thu Sun Tue Fri Sun Wed Sat Mon Thu Sat \n",
+      "Sat Tue Wed Sat Mon Thu Sat Tue Fri Sun Wed Fri \n",
+      "Fri Mon Mon Thu Sat Tue Thu Sun Wed Fri Mon Wed \n",
+      "Wed Sat Sat Tue Thu Sun Tue Fri Mon Wed Sat Mon \n",
+      "Mon Thu Thu Sun Tue Fri Sun Wed Sat Mon Thu Sat \n",
+      "Sat Tue Wed Sat Mon Thu Sat Tue Fri Sun Wed Fri \n",
+      "Fri Mon Mon Thu Sat Tue Thu Sun Wed Fri Mon Wed \n",
+      "Wed Sat Sat Tue Thu Sun Tue Fri Mon Wed Sat Mon \n",
+      "Mon Thu Thu Sun Tue Fri Sun Wed Sat Mon Thu Sat \n",
+      "Sat Tue Wed Sat Mon Thu Sat Tue Fri Sun Wed Fri \n"
+     ]
+    }
+   ],
+   "source": [
+    "for year in range(1000, 2401, 100):\n",
+    "    line = \"\"\n",
+    "    for month in range(1, 13):\n",
+    "        line += day_abbr[datetime(year, month, 1).weekday()] + ' '\n",
+    "    print(line)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}