performance-python.ipynb

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   "id": "2261137f-589d-4ee2-87d7-eedeaa549d7a",
   "metadata": {},
   "source": [
    "---\n",
    "title: \"Strategies for Optimizing Your Python Code\"\n",
    "author: \"Kyle Niemeyer\"\n",
    "date: \"19 February 2025\"\n",
    "institute: \"Oregon State University\"\n",
    "format:\n",
    "  revealjs:\n",
    "    output-file: performance-python-revealjs.html\n",
    "    incremental: true\n",
    "    fig-align: center\n",
    "    fig-responsive: true\n",
    "    toc: false\n",
    "    code-block-height: 650px\n",
    "  html: default\n",
    "highlight-style: arrow\n",
    "execute:\n",
    "  echo: true\n",
    "jupyter: python3\n",
    "include-in-header:\n",
    "  text: |\n",
    "    <style>\n",
    "    .cell-output-stdout {\n",
    "      overflow-y: scroll;\n",
    "      max-height: 600px;\n",
    "    }\n",
    "    </style>\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0d0fb3d5-62d8-4fb5-8bdb-08f2f12ca6b0",
   "metadata": {},
   "source": [
    "# Strategies for Optimizing Your Python Code\n",
    "\n",
    "Acknowledgements: heavily adopted from Jake VanderPlas's 2018 PyCon talk:\n",
    "\n",
    "- original notebook: <https://gist.github.com/jakevdp/256c3ad937af9ec7d4c65a29e5b6d454>\n",
    "- Talk: <https://www.youtube.com/watch?v=zQeYx87mfyw>\n",
    "\n",
    "## K Means: The Algorithm\n",
    "\n",
    "- Guess some cluster centers\n",
    "- Repeat until converged\n",
    "  - assign points to the nearest cluster center\n",
    "  - set the cluster centers to the mean of assigned points\n",
    "\n",
    "## {.smaller}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "6729a421-5196-4cc4-9218-b770491eaba6",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.datasets import make_blobs\n",
    "\n",
    "points, labels_true = make_blobs(\n",
    "    n_samples=5000, centers=4,\n",
    "    random_state=0, cluster_std=0.60\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "94a8c6b1-a0ad-4b01-97c4-61b4d016a014",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#| classes: fragment\n",
    "#| output-location: fragment\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.scatter(points[:, 0], points[:, 1], s=10)\n",
    "plt.xlim(-4, 4)\n",
    "plt.ylim(-2, 10)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "21717c0e-801f-4b9d-97cb-bb16a82f6909",
   "metadata": {},
   "source": [
    "## Basic Python implementation {.smaller}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "b186a5eb-c0b1-4c79-89d4-de864b7c6450",
   "metadata": {},
   "outputs": [],
   "source": [
    "def dist(x, y):\n",
    "    return sum((xi - yi)**2 for xi, yi in zip(x, y))\n",
    "\n",
    "def find_labels(points, centers):\n",
    "    labels = []\n",
    "    for point in points:\n",
    "        distances = [dist(point, center) for center in centers]\n",
    "        labels.append(distances.index(min(distances)))\n",
    "    return labels\n",
    "\n",
    "def compute_centers(points, labels):\n",
    "    n_centers = len(set(labels))\n",
    "    n_dims = len(points[0])\n",
    "    centers = [[0 for i in range(n_dims)] for j in range(n_centers)]\n",
    "    counts = [0 for j in range(n_centers)]\n",
    "    for label, point in zip(labels, points):\n",
    "        counts[label] += 1\n",
    "        centers[label] = [a + b for a, b in zip(centers[label], point)]\n",
    "    return [[x / count for x in center] for center, count in zip(centers, counts)]\n",
    "\n",
    "def kmeans(points, n_clusters):\n",
    "    centers = points[-n_clusters:].tolist()\n",
    "    while True:\n",
    "        old_centers = centers\n",
    "        labels = find_labels(points, centers)\n",
    "        centers = compute_centers(points, labels)\n",
    "        if centers == old_centers:\n",
    "            break\n",
    "    return labels"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d80f48d-3e8c-47af-a564-537531e0ae62",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "b8190b53-53da-47db-baff-4931490e5507",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[5, 3, 4, 5, 0, 4, 9, 6, 0, 7]"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#| output-location: fragment\n",
    "kmeans(points, 10)[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "e0ed2f93-9ccd-40cd-8952-a0d0a3a467e6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.76 s ± 31 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
     ]
    }
   ],
   "source": [
    "#| classes: fragment\n",
    "#| output-location: fragment\n",
    "%timeit kmeans(points, 10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "65b2b9f1-7c03-43ec-919d-41ac47e2de10",
   "metadata": {},
   "source": [
    "# Strategy #1: line profiling\n",
    "\n",
    "Put most of your efforts on the parts of the code that actually take the most time. To find those, you can use a line profiling tool (make sure to `pip install line_profiler`)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "9f1a31a3-fdb1-4bda-8d4a-e7c5aff2ed6d",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The line_profiler extension is already loaded. To reload it, use:\n",
      "  %reload_ext line_profiler\n"
     ]
    }
   ],
   "source": [
    "#| classes: fragment\n",
    "#| output: false\n",
    "%load_ext line_profiler"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6e61f493-122f-4cc2-ad20-5d5f53c33875",
   "metadata": {},
   "source": [
    "## {.smaller}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "f582dd65-f59e-485d-aef8-7b22aaeb9864",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timer unit: 1e-09 s\n",
       "\n",
       "Total time: 4.56715 s\n",
       "File: /var/folders/ng/d9rd9fb92c7bxz9fy7vwpj7m0000gp/T/ipykernel_13369/3233416767.py\n",
       "Function: kmeans at line 21\n",
       "\n",
       "Line #      Hits         Time  Per Hit   % Time  Line Contents\n",
       "==============================================================\n",
       "    21                                           def kmeans(points, n_clusters):\n",
       "    22         1     129000.0 129000.0      0.0      centers = points[-n_clusters:].tolist()\n",
       "    23        54       9000.0    166.7      0.0      while True:\n",
       "    24        54      45000.0    833.3      0.0          old_centers = centers\n",
       "    25        54 4389825000.0    8e+07     96.1          labels = find_labels(points, centers)\n",
       "    26        54  177088000.0    3e+06      3.9          centers = compute_centers(points, labels)\n",
       "    27        54      57000.0   1055.6      0.0          if centers == old_centers:\n",
       "    28         1          0.0      0.0      0.0              break\n",
       "    29         1       1000.0   1000.0      0.0      return labels"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#| output-location: fragment\n",
    "%lprun -f kmeans kmeans(points, 10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "745ed218-6397-48a4-827f-284fffeb57a1",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "437849b5-508e-41bb-82fb-b3ff0fb48139",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "44e4ca83-0fce-4c4d-bc6f-fb5f33cc0b08",
   "metadata": {},
   "source": [
    "## {.smaller}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "f7045428-6760-44c2-935d-928a8e83b01f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timer unit: 1e-09 s\n",
       "\n",
       "Total time: 4.57433 s\n",
       "File: /var/folders/ng/d9rd9fb92c7bxz9fy7vwpj7m0000gp/T/ipykernel_13369/3233416767.py\n",
       "Function: find_labels at line 4\n",
       "\n",
       "Line #      Hits         Time  Per Hit   % Time  Line Contents\n",
       "==============================================================\n",
       "     4                                           def find_labels(points, centers):\n",
       "     5        54      72000.0   1333.3      0.0      labels = []\n",
       "     6    270054   52908000.0    195.9      1.2      for point in points:\n",
       "     7   2970000 4415870000.0   1486.8     96.5          distances = [dist(point, center) for center in centers]\n",
       "     8    270000  105452000.0    390.6      2.3          labels.append(distances.index(min(distances)))\n",
       "     9        54      24000.0    444.4      0.0      return labels"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#| output-location: fragment\n",
    "%lprun -f find_labels kmeans(points, 10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "60c90671-079f-46ad-8dc5-d19339a62f19",
   "metadata": {},
   "source": [
    "The majority of the compute time (~97% of the `find_labels` function, which itself takes up ~96% of the total `kmeans` function) is spent in calculating the distances, which is an operation repeated over the arrays of point locations.\n",
    "\n",
    "For repeated operations on arrays, Numpy is your first place to turn.\n",
    "\n",
    "# 2. NumPy Vectorization / Broadcasting\n",
    "\n",
    "Optimizes repeated operations on arrays.\n",
    "\n",
    "## {.smaller}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "984df99b-8e32-40e8-bd44-faae2948b81c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "def find_labels(points, centers):\n",
    "    diff = (points[:, None, :] - centers)\n",
    "    distances = (diff**2).sum(-1)\n",
    "    return distances.argmin(1)\n",
    "\n",
    "def compute_centers(points, labels):\n",
    "    n_centers = len(set(labels))\n",
    "    n_dims = len(points[0])\n",
    "    \n",
    "    centers = [[0 for i in range(n_dims)] for j in range(n_centers)]\n",
    "    counts = [0 for j in range(n_centers)]\n",
    "    \n",
    "    for label, point in zip(labels, points):\n",
    "        counts[label] += 1\n",
    "        centers[label] = [a + b for a, b in zip(centers[label], point)]\n",
    "        \n",
    "    return [[x / count for x in center] for center, count in zip(centers, counts)]\n",
    "\n",
    "def compute_centers(points, labels):\n",
    "    n_centers = len(set(labels))\n",
    "    return np.array([points[labels == i].mean(0) for i in range(n_centers)])\n",
    "\n",
    "def kmeans(points, n_clusters):\n",
    "    centers = points[-n_clusters:]\n",
    "    while True:\n",
    "        old_centers = centers\n",
    "        labels = find_labels(points, centers)\n",
    "        centers = compute_centers(points, labels)\n",
    "        if np.all(centers == old_centers):\n",
    "            break\n",
    "    return labels"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c77e1f70-eab9-4356-a171-508fcca8bc50",
   "metadata": {},
   "source": [
    "--- "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "c57f5236-7e7c-4fa2-b710-56c4240b633a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([5, 3, 4, 5, 0, 4, 9, 6, 0, 7])"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kmeans(points, 10)[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "70125749-f1df-4f68-9494-7bfc37101e41",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "76 ms ± 169 μs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
     ]
    }
   ],
   "source": [
    "#| classes: fragment\n",
    "#| output-location: fragment\n",
    "%timeit kmeans(points, 10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "662453ed-4446-4a73-bbfb-1dedf3b4b516",
   "metadata": {},
   "source": [
    "::: fragment\n",
    "Using NumPy takes the algorithm down from nearly three seconds to below one hundred milliseconds!\n",
    ":::\n",
    "\n",
    "::: fragment\n",
    "The key here is that repeated operations have been pushed into a **compiled layer**. Use NumPy everywhere when doing numerical calculations with arrays.\n",
    ":::\n",
    "\n",
    "\n",
    "## Use NumPy everywhere!\n",
    "\n",
    "::: fragment\n",
    "Advantages:\n",
    ":::\n",
    "\n",
    "- Python overhead per array rather than per array element\n",
    "- Compact domain specific language for array operations\n",
    "- NumPy is widely available\n",
    "\n",
    "::: fragment\n",
    "Disadvantages:\n",
    "::: \n",
    "\n",
    "- Batch operations can lead to excessive memory usage\n",
    "- Different way of thinking about writing code\n",
    "\n",
    "## {.smaller}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "0f6d7abb-0b63-4467-b2e5-3b3162f79361",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timer unit: 1e-09 s\n",
       "\n",
       "Total time: 0.142411 s\n",
       "File: /var/folders/ng/d9rd9fb92c7bxz9fy7vwpj7m0000gp/T/ipykernel_13369/2497051821.py\n",
       "Function: kmeans at line 25\n",
       "\n",
       "Line #      Hits         Time  Per Hit   % Time  Line Contents\n",
       "==============================================================\n",
       "    25                                           def kmeans(points, n_clusters):\n",
       "    26         1      98000.0  98000.0      0.1      centers = points[-n_clusters:]\n",
       "    27        54      15000.0    277.8      0.0      while True:\n",
       "    28        54      11000.0    203.7      0.0          old_centers = centers\n",
       "    29        54   97292000.0    2e+06     68.3          labels = find_labels(points, centers)\n",
       "    30        54   43640000.0 808148.1     30.6          centers = compute_centers(points, labels)\n",
       "    31        54    1355000.0  25092.6      1.0          if np.all(centers == old_centers):\n",
       "    32         1          0.0      0.0      0.0              break\n",
       "    33         1          0.0      0.0      0.0      return labels"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#| output-location: fragment\n",
    "%lprun -f kmeans kmeans(points, 10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "dd8ad25c-2521-4d17-a00e-a8c770188d83",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timer unit: 1e-09 s\n",
       "\n",
       "Total time: 4.60709 s\n",
       "File: /var/folders/ng/d9rd9fb92c7bxz9fy7vwpj7m0000gp/T/ipykernel_13369/3233416767.py\n",
       "Function: find_labels at line 4\n",
       "\n",
       "Line #      Hits         Time  Per Hit   % Time  Line Contents\n",
       "==============================================================\n",
       "     4                                           def find_labels(points, centers):\n",
       "     5        54      52000.0    963.0      0.0      labels = []\n",
       "     6    270054   52181000.0    193.2      1.1      for point in points:\n",
       "     7   2970000 4453916000.0   1499.6     96.7          distances = [dist(point, center) for center in centers]\n",
       "     8    270000  100907000.0    373.7      2.2          labels.append(distances.index(min(distances)))\n",
       "     9        54      33000.0    611.1      0.0      return labels"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#| classes: fragment\n",
    "#| output-location: fragment\n",
    "%lprun -f find_labels kmeans(points, 10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "37bb5639-0c65-4980-a325-e762af4bfa9c",
   "metadata": {},
   "source": [
    "## {.smaller}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "6b373d59-a55c-4d4d-baa6-d6b2b9134d12",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timer unit: 1e-09 s\n",
       "\n",
       "Total time: 0.276425 s\n",
       "File: /var/folders/ng/d9rd9fb92c7bxz9fy7vwpj7m0000gp/T/ipykernel_13369/3233416767.py\n",
       "Function: compute_centers at line 11\n",
       "\n",
       "Line #      Hits         Time  Per Hit   % Time  Line Contents\n",
       "==============================================================\n",
       "    11                                           def compute_centers(points, labels):\n",
       "    12        54    2770000.0  51296.3      1.0      n_centers = len(set(labels))\n",
       "    13        54     101000.0   1870.4      0.0      n_dims = len(points[0])\n",
       "    14      1674     420000.0    250.9      0.2      centers = [[0 for i in range(n_dims)] for j in range(n_centers)]\n",
       "    15       594     100000.0    168.4      0.0      counts = [0 for j in range(n_centers)]\n",
       "    16    270054   49242000.0    182.3     17.8      for label, point in zip(labels, points):\n",
       "    17    270000   30445000.0    112.8     11.0          counts[label] += 1\n",
       "    18    810000  192816000.0    238.0     69.8          centers[label] = [a + b for a, b in zip(centers[label], point)]\n",
       "    19      1674     531000.0    317.2      0.2      return [[x / count for x in center] for center, count in zip(centers, counts)]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#| output-location: fragment\n",
    "%lprun -f compute_centers kmeans(points, 10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a9b863e6-ba41-428b-81e2-01fc9b894696",
   "metadata": {},
   "source": [
    "::: fragment\n",
    "We can see that the time is now somewhat balanced between calculating the distances between points, and computing the centers of the clusters.\n",
    ":::"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fe158352-1738-4850-ac7c-855659671dc5",
   "metadata": {},
   "source": [
    "# 3. Special Data Structures\n",
    "\n",
    "To further speed up this algorithm, we can use special data structures to help further, provided by the `scikit-learn` and `pandas` packages.\n",
    "\n",
    "First, use the KD Tree structure designed for nearest neighbor searches, provided by `scikit-learn`.\n",
    "\n",
    "---\n",
    "\n",
    "NumPy code:\n",
    "``` {.python .fragment}\n",
    "import numpy as np\n",
    "\n",
    "def find_labels(points, centers):\n",
    "    diff = (points[:, None, :] - centers) ** 2\n",
    "    distances = diff.sum(-1)\n",
    "    return distances.argmin(1)\n",
    "```\n",
    "\n",
    "::: fragment\n",
    "KD-Tree code:\n",
    ":::\n",
    "``` {.python .fragment}\n",
    "from scipy.spatial import cKDTree\n",
    "\n",
    "def find_labels(points, centers):\n",
    "    distances, labels = cKDTree(centers).query(points, 1)\n",
    "    return labels\n",
    "```\n",
    "\n",
    "---\n",
    "\n",
    "Then, computing the centers of the clusters is essentially a \"group-by\" operation: group values by their label, then aggregate those values in the groups. Pandas offers a very efficient group-by operation in its `DataFrame` structure. \n",
    "\n",
    "::: fragment\n",
    "NumPy code:\n",
    "::: \n",
    "``` {.python .fragment}\n",
    "def compute_centers(points, labels):\n",
    "    n_centers = len(set(labels))\n",
    "    return np.array([points[labels == i].mean(0) for i in range(n_centers)])\n",
    "```\n",
    "\n",
    "::: fragment\n",
    "Pandas code:\n",
    ":::\n",
    "``` {.python .fragment}\n",
    "import pandas as pd\n",
    "\n",
    "def compute_centers(points, labels):\n",
    "    df = pd.DataFrame(points)\n",
    "    return df.groupby(labels).mean().values\n",
    "```\n",
    "\n",
    "--- "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "d34a7465-458d-4795-8af0-a889f1bd012f",
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy.spatial import cKDTree\n",
    "import pandas as pd\n",
    "\n",
    "def find_labels(points, centers):\n",
    "    distances, labels = cKDTree(centers).query(points, 1)\n",
    "    return labels\n",
    "\n",
    "def compute_centers(points, labels):\n",
    "    df = pd.DataFrame(points)\n",
    "    return df.groupby(labels).mean().values\n",
    "\n",
    "def kmeans(points, n_clusters):\n",
    "    centers = points[-n_clusters:]\n",
    "    while True:\n",
    "        old_centers = centers\n",
    "        labels = find_labels(points, centers)\n",
    "        centers = compute_centers(points, labels)\n",
    "        if np.all(centers == old_centers):\n",
    "            break\n",
    "    return labels"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "180d2193-2a4f-4c3b-88b6-a88c4eae4437",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "3dfdce3c-ffa4-4c83-96c0-46f27ae7a17d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([5, 3, 4, 5, 0, 4, 9, 6, 0, 7])"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#| output-location: fragment\n",
    "kmeans(points, 10)[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "61e193d4-d58c-4eec-8720-ed61b88a3cd8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "53.6 ms ± 277 μs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
     ]
    }
   ],
   "source": [
    "#| classes: fragment\n",
    "#| output-location: fragment\n",
    "%timeit kmeans(points, 10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "144cee38-f78a-4dfc-ba3e-1e222c3a82c6",
   "metadata": {},
   "source": [
    "## {.smaller}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "b90312ce-2a73-4702-9f17-46d7180c359d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timer unit: 1e-09 s\n",
       "\n",
       "Total time: 0.08276 s\n",
       "File: /var/folders/ng/d9rd9fb92c7bxz9fy7vwpj7m0000gp/T/ipykernel_13369/3764998874.py\n",
       "Function: kmeans at line 12\n",
       "\n",
       "Line #      Hits         Time  Per Hit   % Time  Line Contents\n",
       "==============================================================\n",
       "    12                                           def kmeans(points, n_clusters):\n",
       "    13         1       8000.0   8000.0      0.0      centers = points[-n_clusters:]\n",
       "    14        54       8000.0    148.1      0.0      while True:\n",
       "    15        54       9000.0    166.7      0.0          old_centers = centers\n",
       "    16        54   56628000.0    1e+06     68.4          labels = find_labels(points, centers)\n",
       "    17        54   25563000.0 473388.9     30.9          centers = compute_centers(points, labels)\n",
       "    18        54     543000.0  10055.6      0.7          if np.all(centers == old_centers):\n",
       "    19         1          0.0      0.0      0.0              break\n",
       "    20         1       1000.0   1000.0      0.0      return labels"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#| output-location: fragment\n",
    "%lprun -f kmeans kmeans(points, 10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6ea45a2b-9768-4145-9b03-c75c71e22d6f",
   "metadata": {},
   "source": [
    "::: fragment\n",
    "Runtime reduced down to ~54 ms, compared to:\n",
    ":::\n",
    "\n",
    "- 2.7 s in pure Python\n",
    "- 76 ms with NumPy vectorization\n",
    "\n",
    "::: fragment\n",
    "by taking advantage of specialized data structures designed for the exact low-level algorithms we need.\n",
    ":::\n",
    "\n",
    "## {.smaller}\n",
    "\n",
    "Other useful data structures include:\n",
    "\n",
    "- `scipy.spatial`: for spatial queries like distances, nearest neighbors, etc.\n",
    "- `pandas`: for SQL-like grouping & aggregation\n",
    "- `xarray`: for grouping across multiple dimensions\n",
    "- `scipy.sparse`: sparse matrices for two-dimensional structured data\n",
    "- `sparse` package: for N-dimensional structured data\n",
    "- `scipy.sparse.csgraph`: for graph-like problems (e.g., finding shortest paths)\n",
    "\n",
    "::: fragment\n",
    "Advantages: these are often the fastest possible way to solve a particular problem.\n",
    ":::\n",
    "\n",
    "::: fragment\n",
    "Disadvantages: require broad & deep understanding of both algorithms and their available implementations.\n",
    "::: "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "02578b4c-830f-4512-83a7-a49296c385ea",
   "metadata": {},
   "source": [
    "# 4. Cython\n",
    "\n",
    "Combine powers of C with Python. \n",
    "\n",
    "::: fragment\n",
    "We can do this by adding types, then Cython knows how to compile it down to C code.\n",
    ":::\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "dc0d3209-d320-4569-8d12-49d5e1dd56f6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The Cython extension is already loaded. To reload it, use:\n",
      "  %reload_ext Cython\n"
     ]
    }
   ],
   "source": [
    "#| output: false\n",
    "%load_ext Cython"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "d863c439-9a32-4bf1-b08e-0e11e8ba37f6",
   "metadata": {},
   "outputs": [],
   "source": [
    "#| classes: fragment\n",
    "# Python version\n",
    "\n",
    "def dist(x, y):\n",
    "    dist = 0\n",
    "    for i in range(len(x)):\n",
    "        dist += (x[i] - y[i]) ** 2\n",
    "    return dist\n",
    "\n",
    "def find_labels(points, centers):\n",
    "    labels = []\n",
    "    for point in points:\n",
    "        distances = [dist(point, center) for center in centers]\n",
    "        labels.append(distances.index(min(distances)))\n",
    "    return labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "4bdb57b5-468c-4612-a8a2-99c9d734f01b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "34.4 ms ± 370 μs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
     ]
    }
   ],
   "source": [
    "#| classes: fragment\n",
    "#| output-location: fragment\n",
    "centers = points[:10]\n",
    "%timeit find_labels(points, centers)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3270e9a8-5c9a-4cb5-aa92-26929573fe73",
   "metadata": {},
   "source": [
    "--- "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "4708bc21-93ac-4ee8-83ca-984856833654",
   "metadata": {},
   "outputs": [],
   "source": [
    "%%cython\n",
    "#| output: false\n",
    "\n",
    "cimport numpy as np\n",
    "\n",
    "cdef double dist(double[:] x, double[:] y):\n",
    "    cdef double dist = 0\n",
    "    for i in range(len(x)):\n",
    "        dist += (x[i] - y[i]) ** 2\n",
    "    return dist\n",
    "\n",
    "def find_labels(points, centers):\n",
    "    labels = []\n",
    "    for point in points:\n",
    "        distances = [dist(point, center) for center in centers]\n",
    "        labels.append(distances.index(min(distances)))\n",
    "    return labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "ad286d6f-f5ce-4760-8abc-f970fd07677d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "20.3 ms ± 241 μs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
     ]
    }
   ],
   "source": [
    "#| classes: fragment\n",
    "#| output-location: fragment\n",
    "centers = points[:10]\n",
    "%timeit find_labels(points, centers)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8c770765-69eb-4bb0-9f08-a7eff79a975f",
   "metadata": {},
   "source": [
    "## {.smaller}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "8c37fb83-1675-4b76-8c6c-57370aa7d9ec",
   "metadata": {},
   "outputs": [],
   "source": [
    "%%cython\n",
    "\n",
    "cimport numpy as np\n",
    "import numpy as np\n",
    "\n",
    "cdef double dist(double[:] x, double[:] y):\n",
    "    cdef double dist = 0\n",
    "    for i in range(len(x)):\n",
    "        dist += (x[i] - y[i]) ** 2\n",
    "    return dist\n",
    "\n",
    "def find_labels(double[:, :] points, double[:, :] centers):\n",
    "    cdef int n_points = points.shape[0]\n",
    "    cdef int n_centers = centers.shape[0]\n",
    "    cdef double[:] labels = np.zeros(n_points)\n",
    "    cdef double distance, nearest_distance\n",
    "    cdef int nearest_index\n",
    "    \n",
    "    for i in range(n_points):\n",
    "        nearest_distance = np.inf\n",
    "        for j in range(n_centers):\n",
    "            distance = dist(points[i], centers[j])\n",
    "            if distance < nearest_distance:\n",
    "                nearest_distance = distance\n",
    "                nearest_index = j\n",
    "        labels[i] = nearest_index\n",
    "    return np.asarray(labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "1c279597-5940-4470-9809-44f5f871c5d3",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "347 μs ± 906 ns per loop (mean ± std. dev. of 7 runs, 1,000 loops each)\n"
     ]
    }
   ],
   "source": [
    "#| classes: fragment\n",
    "#| output-location: fragment\n",
    "centers = points[:10]\n",
    "%timeit find_labels(points, centers)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5a0d40c7-d949-4eb7-bbac-47418a996796",
   "metadata": {},
   "source": [
    "--- \n",
    "\n",
    "Advantages:\n",
    "\n",
    "- Python-like code at C-like speeds!\n",
    "\n",
    "::: fragment\n",
    "Disadvantages:\n",
    ":::\n",
    "\n",
    "- Explicit type annotation can be cumbersome\n",
    "- Often requires restructuring code\n",
    "- Code build becomes more complicated\n",
    "\n",
    "::: fragment\n",
    "Use for operations that can't easily be expressed in NumPy.\n",
    ":::"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5d20a2fe-2e09-4eb1-957f-120f0790a57e",
   "metadata": {},
   "source": [
    "# 5. Numba\n",
    "\n",
    "[Numba](https://numba.pydata.org) is a just-in-time (JIT) compiler that compiles Python functions to optimized machine code at runtime using the industry-standard LLVM compiler library.\n",
    "\n",
    "::: fragment\n",
    "Numba can *infer* the types without being explicitly told what they are.\n",
    "::: \n",
    "\n",
    "::: fragment\n",
    "We can frequently accelerate Python code *very* easily using Numba, simply by adding the `@numba.jit(nopython=True)` decorator to functions.\n",
    ":::\n",
    "\n",
    "--- "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "2f74d6a6-54e9-4433-b216-c5e5d59e7ea4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# pure Python version\n",
    "def dist(x, y):\n",
    "    dist = 0\n",
    "    for i in range(len(x)):\n",
    "        dist += (x[i] - y[i]) ** 2\n",
    "    return dist\n",
    "\n",
    "\n",
    "def find_labels(points, centers):\n",
    "    labels = []\n",
    "    min_dist = np.inf\n",
    "    min_label = 0\n",
    "    for i in range(len(points)):\n",
    "        for j in range(len(centers)):\n",
    "            distance = dist(points[i], centers[j])\n",
    "            if distance < min_dist:\n",
    "                min_dist, min_label = distance, j\n",
    "        labels.append(min_label)\n",
    "    return labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "35feb51f-491c-4e44-b801-aecdf0d34083",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "34.1 ms ± 240 μs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
     ]
    }
   ],
   "source": [
    "#| classes: fragment\n",
    "#| output-location: fragment\n",
    "centers = points[:10]\n",
    "%timeit find_labels(points, centers)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "05aed37f-0985-4d50-8648-1fc92dc72e75",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "e9740f2b-6c9e-41bc-9c56-bd135a287db2",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numba\n",
    "\n",
    "@numba.jit(nopython=True)\n",
    "def dist(x, y):\n",
    "    dist = 0\n",
    "    for i in range(len(x)):\n",
    "        dist += (x[i] - y[i]) ** 2\n",
    "    return dist\n",
    "\n",
    "@numba.jit(nopython=True)\n",
    "def find_labels(points, centers):\n",
    "    labels = []\n",
    "    min_dist = np.inf\n",
    "    min_label = 0\n",
    "    for i in range(len(points)):\n",
    "        for j in range(len(centers)):\n",
    "            distance = dist(points[i], centers[j])\n",
    "            if distance < min_dist:\n",
    "                min_dist, min_label = distance, j\n",
    "        labels.append(min_label)\n",
    "    return labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "20688153-a854-4878-96bd-71586773595b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "106 μs ± 7.21 μs per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
     ]
    }
   ],
   "source": [
    "#| classes: fragment\n",
    "#| output-location: fragment\n",
    "centers = points[:10]\n",
    "%timeit find_labels(points, centers)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "356cbaf6-72a5-4059-932a-f40a4e10501d",
   "metadata": {},
   "source": [
    "--- \n",
    "\n",
    "Advantages:\n",
    "\n",
    "- Python code JIT-compiled to Fortran speeds!\n",
    "\n",
    "::: fragment\n",
    "Disadvantages:\n",
    ":::\n",
    "\n",
    "- Heavy dependency chain (LLVM)\n",
    "- Some Python constructs not supported\n",
    "- Still a bit finnicky\n",
    "\n",
    "::: fragment\n",
    "Recommendation: definitely use for analysis scripts, but be more cautious using in packages as a dependency.\n",
    "::: \n",
    "\n",
    "::: fragment\n",
    "Also possible to automatically parallelize loops on CPUs and GPUs, but this requires special care.\n",
    ":::"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "adb920ce-edf1-4a85-b127-e3d3a93ec344",
   "metadata": {},
   "source": [
    "# 6. Dask\n",
    "\n",
    "Useful for when your data becomes too large for a single machine's memory, or you want to distribute your work across systems.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "573b96af-bdc4-45cb-9220-15dbc8cf67be",
   "metadata": {},
   "source": [
    "--- \n",
    "\n",
    "Typical data manipulation with NumPy:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "d0040688-ad7c-44d2-b527-a75e70250739",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-14.778280420773221\n"
     ]
    }
   ],
   "source": [
    "#| classes: fragment\n",
    "#| output-location: fragment\n",
    "import numpy as np\n",
    "a = np.random.randn(1000)\n",
    "b = a * 4\n",
    "b_min = b.min()\n",
    "print(b_min)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "22d8ab46-b0a7-4053-990e-a1c306b6d677",
   "metadata": {},
   "source": [
    "--- \n",
    "\n",
    "Same operation with Dask:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "836d2e54-2cda-4d9e-85cd-e885621ee3ec",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dask.array<min-aggregate, shape=(), dtype=float64, chunksize=(), chunktype=numpy.ndarray>\n"
     ]
    }
   ],
   "source": [
    "#| classes: fragment\n",
    "#| output-location: fragment\n",
    "import dask.array as da\n",
    "a2 = da.from_array(a, chunks=200)\n",
    "b2 = a2 * 4\n",
    "b2_min = b2.min()\n",
    "print(b2_min)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "818e664f-7b25-4f00-8ac1-a783491c2087",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float64(-14.778280420773221)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#| classes: fragment\n",
    "#| output-location: fragment\n",
    "b2_min.compute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "6fc9c5eb-aadb-42a3-850d-72c43d50f0ac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#| classes: fragment\n",
    "#| output: false\n",
    "b2_min.visualize(filename=\"dask_ex.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "841c530c-b724-4cae-9de4-f9ef01af9712",
   "metadata": {},
   "source": [
    "--- \n",
    "\n",
    "![](dask_ex.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "955449dc-b4c5-497f-9ea9-36ae102ee1a8",
   "metadata": {},
   "source": [
    "--- "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "335cd68d-ea55-43f9-a9cf-205aa2c5b8d0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 5.94673918, 14.00964977, 13.12598814, ..., 64.21143425,\n",
       "       67.46733724, 51.7011693 ])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#| output-location: fragment\n",
    "from dask import array as da\n",
    "from dask import dataframe as dd\n",
    "\n",
    "points_dask = da.from_array(points, chunks=1000)\n",
    "result = (points_dask ** 2).sum(1)\n",
    "result.compute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "ea6a8993-c911-4ba8-9267-83691c2c2dbb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#| output: false\n",
    "#| classes: fragment\n",
    "result.visualize(filename='dask_distance.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ba2101eb-4f9e-44c0-8bf6-9169f03db09a",
   "metadata": {},
   "source": [
    "--- \n",
    "\n",
    "![](./dask_distance.png)\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "a3835851-f46b-47e7-b964-8af2cd4e3c4d",
   "metadata": {},
   "outputs": [],
   "source": [
    "from dask import array as da\n",
    "\n",
    "def find_labels(points, centers):\n",
    "    diff = (points[:, None, :] - centers)\n",
    "    distances = (diff ** 2).sum(-1)\n",
    "    return distances.argmin(1)\n",
    "\n",
    "centers = points[:10]\n",
    "\n",
    "points_dask = da.from_array(points, chunks=1000)\n",
    "centers_dask = da.from_array(centers, chunks=5)\n",
    "\n",
    "labels_dask = find_labels(points_dask, centers_dask)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "3bdf4a39-1a02-4c69-af6e-8aac65e8d063",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 1, 2, ..., 6, 9, 6])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#| classes: fragment\n",
    "#| output-location: fragment\n",
    "labels_dask.compute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "de454229-7628-47f5-b702-d03b9a4780e9",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#| classes: fragment\n",
    "#| output: false\n",
    "labels_dask.visualize(filename='dask-labels.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "36c0fd46-2ac3-477c-bbca-4267ef312d79",
   "metadata": {},
   "source": [
    "--- \n",
    "\n",
    "![](./dask-labels.png)\n",
    "\n",
    "--- "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "2b768bdd-f5ec-44e1-95e5-0b74e48f545c",
   "metadata": {},
   "outputs": [],
   "source": [
    "from dask import dataframe as dd\n",
    "\n",
    "def compute_centers(points, labels):\n",
    "    points_df = dd.from_dask_array(points, columns=['x', 'y'])\n",
    "    points_df['label'] = dd.from_dask_array(labels)\n",
    "    return points_df.groupby('label')['x', 'y'].mean()\n",
    "\n",
    "result = compute_centers(points_dask, labels_dask)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "d37e4ea3-ecd0-4545-85ff-e12b410849a8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 2.00922872,  1.03540404],\n",
       "       [-2.0667431 ,  2.52306223],\n",
       "       [-0.8672449 ,  3.01911047],\n",
       "       [ 2.22058825, -0.07949264],\n",
       "       [ 0.80306779,  4.89056466],\n",
       "       [-1.70344324,  3.23137327],\n",
       "       [-1.60575186,  7.32973674],\n",
       "       [-0.69320682,  7.69520974],\n",
       "       [ 1.11008872,  3.98520896],\n",
       "       [-1.41988679,  8.41475127]])"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#| classes: fragment\n",
    "#| output-location: fragment\n",
    "result.compute().values"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a018437c-0428-4067-8267-e6e3efc3911a",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "c0c84cc4-24f1-478b-969a-a3f1e5a50f4b",
   "metadata": {},
   "outputs": [],
   "source": [
    "def find_labels(points, centers):\n",
    "    diff = (points[:, None, :] - centers)\n",
    "    distances = (diff ** 2).sum(-1)\n",
    "    return distances.argmin(1)\n",
    "\n",
    "def compute_centers(points, labels):\n",
    "    points_df = dd.from_dask_array(points, columns=['x', 'y'])\n",
    "    points_df['label'] = dd.from_dask_array(labels)\n",
    "    return points_df.groupby('label')['x', 'y'].mean()\n",
    "\n",
    "def kmeans(points, n_clusters):\n",
    "    centers = points[-n_clusters:]\n",
    "    points = da.from_array(points, 1000)\n",
    "    while True:\n",
    "        old_centers = centers\n",
    "        labels = find_labels(points, da.from_array(centers, 5))\n",
    "        centers = compute_centers(points, labels)\n",
    "        centers = centers.compute().values\n",
    "        if np.all(centers == old_centers):\n",
    "            break\n",
    "    return labels.compute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "8106ba2b-b8c8-4f4f-b630-3128d7df94f2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.34 s ± 184 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"
     ]
    }
   ],
   "source": [
    "#| classes: fragment\n",
    "#| output-location: fragment\n",
    "\n",
    "%timeit kmeans(points, 10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1f37a72c-0356-46d1-a22e-9266bb4ab4c3",
   "metadata": {},
   "source": [
    "--- \n",
    "\n",
    "Advantages:\n",
    "\n",
    "- Easy distributed coding, often with no change to NumPy or Pandas code!\n",
    "- Even works locally on out-of-core data\n",
    "\n",
    "::: fragment\n",
    "Disadvantages:\n",
    "::: \n",
    "\n",
    "- High overhead, so not suitable for smaller problems\n",
    "\n",
    "::: fragment\n",
    "Recommendation: use when data size or computation time warrants\n",
    ":::"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "99cbafc5-4c2c-4cf9-9d96-8fe149619f69",
   "metadata": {},
   "source": [
    "# 7. Find an existing implementation\n",
    "\n",
    "::: fragment\n",
    "For example, `scikit-learn`'s k-means:\n",
    ":::"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "d313bc91-5d8b-46ed-9ea0-02785d3479a4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.24 ms ± 98.4 μs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
     ]
    }
   ],
   "source": [
    "#| classes: fragment\n",
    "#| output-location: fragment\n",
    "from sklearn.cluster import KMeans\n",
    "\n",
    "%timeit KMeans(4).fit_predict(points)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4989b9b6-4ba6-4f74-9889-c1080e184909",
   "metadata": {},
   "source": [
    "# Takehome messages {.smaller}\n",
    "\n",
    "1. Start with line profiling to identify expensive parts of code.\n",
    "2. Rely heavily on NumPy arrays and vectorization/broadcasting of array operations.\n",
    "3. Use specialized data structures and associated functions when possible.\n",
    "4. Cython can enable C-like speeds, but makes code more complicated.\n",
    "5. Numba can rapidly speed up many calculations with JIT compilation.\n",
    "6. Dask can enable Distributed operations over large data.\n",
    "7. Don't reinvent the wheel–use existing implementations when possible!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "81d8a0e5-7b5d-494c-9324-b0636458b619",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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