nogil-py314-test.ipynb

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     "text": [
      "1.8.0\n",
      "False\n"
     ]
    }
   ],
   "source": [
    "import sklearn\n",
    "import sys\n",
    "print(sklearn.__version__)\n",
    "print(sys._is_gil_enabled())"
   ]
  },
  {
   "cell_type": "code",
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   "id": "6085de42-8235-4007-b6c5-9b88cc44139c",
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(150, 4)\n",
      "(569, 30)\n"
     ]
    }
   ],
   "source": [
    "from sklearn import svm, datasets\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "import joblib\n",
    "iris = datasets.load_iris()\n",
    "data = datasets.load_breast_cancer()\n",
    "\n",
    "print(iris.data.shape)\n",
    "print(data.data.shape)\n",
    "parameters = {'kernel':('linear', 'rbf'),\n",
    "             'C':[1, 10]}\n",
    "svc1 = svm.SVC()\n",
    "clf1 = GridSearchCV(svc1, \n",
    "                   param_grid=parameters,\n",
    "                  n_jobs=10)"
   ]
  },
  {
   "cell_type": "code",
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "6.28 s ± 59.9 ms per loop (mean ± std. dev. of 7 runs, 3 loops each)\n"
     ]
    }
   ],
   "source": [
    "%%timeit -n 3\n",
    "with joblib.parallel_config(backend='threading'):\n",
    "    clf1.fit(data.data, data.target)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "7164ac60-e615-4421-aa0e-964c7afc7361",
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    "execution": {
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   "outputs": [],
   "source": [
    "svc2 = svm.SVC()\n",
    "clf2 = GridSearchCV(svc2, \n",
    "                   param_grid=parameters,\n",
    "                    n_jobs=10\n",
    "                  )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "4b15777d-ae4e-4ca0-bd40-ea4a2fdbb8fb",
   "metadata": {
    "execution": {
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "6.55 s ± 189 ms per loop (mean ± std. dev. of 7 runs, 3 loops each)\n"
     ]
    }
   ],
   "source": [
    "%%timeit -n 3\n",
    "with joblib.parallel_config(backend='loky'):\n",
    "    clf2.fit(data.data, data.target)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "1ac8480d-1a03-46e4-b984-c616a3636921",
   "metadata": {
    "execution": {
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   "outputs": [],
   "source": [
    "from math import sqrt\n",
    "import numpy as np\n",
    "from joblib import Parallel, delayed, parallel_backend\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "688f6b21-213b-4c8c-9745-5ddc27192eb9",
   "metadata": {
    "execution": {
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "46.1 ms ± 3.35 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
     ]
    }
   ],
   "source": [
    "%%timeit -n 10\n",
    "with parallel_backend('loky', n_jobs=5):\n",
    "    a = Parallel()(delayed(np.sqrt)(i ** 2) for i in range(10000))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "4527816e-8c60-4a4b-8e8c-710d215b142d",
   "metadata": {
    "execution": {
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "157 ms ± 2.42 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
     ]
    }
   ],
   "source": [
    "%%timeit -n 10\n",
    "with parallel_backend('threading', n_jobs=5):\n",
    "    a = Parallel()(delayed(np.sqrt)(i ** 2) for i in range(10000))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "46becdc3-b946-495e-8d82-066ee3eced4c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-12-13T06:33:52.864865Z",
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     "iopub.status.idle": "2025-12-13T06:34:12.357516Z",
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     "shell.execute_reply.started": "2025-12-13T06:33:52.864827Z"
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "278 ms ± 3.83 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
     ]
    }
   ],
   "source": [
    "%%timeit -n 10\n",
    "with parallel_backend('multiprocessing', n_jobs=5):\n",
    "    a = Parallel()(delayed(np.sqrt)(i ** 2) for i in range(10000))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d6822d6f-d679-4057-80c5-8fb0e75ec538",
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   "source": []
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