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add smart open
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‎Chapter1/list/get_elements.ipynb

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@@ -54,6 +54,28 @@
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"random.choice(to_do_tonight)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"id": "5d5760fe",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"3"
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]
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},
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"execution_count": 6,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"l = [1, 2, 3]\n",
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"l.pop()"
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]
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},
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{
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"cell_type": "markdown",
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"id": "dc955503",
@@ -229,6 +251,155 @@
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"print(f'Run {expSize} experiments. Using heapq is {ratio} times'\n",
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"' faster than using sorting')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "7f42e002",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"CPU times: user 26.4 ms, sys: 7.96 ms, total: 34.3 ms\n",
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"Wall time: 34.8 ms\n"
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]
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}
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],
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"source": [
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"list_data = list(range(1000000))\n",
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"%time squared_list = [x**2 for x in list_data]\n",
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"# Output: CPU times: user 150 ms, sys: 1.72 ms, total: 152 ms"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "cd67a3fb",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"CPU times: user 9 ms, sys: 830 μs, total: 9.83 ms\n",
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"Wall time: 1.59 ms\n"
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]
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}
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],
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"source": [
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"import numpy as np\n",
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"\n",
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"np_data = np.arange(1000000)\n",
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"%time squared_np = np_data**2\n",
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"# Output: CPU times: user 1.62 ms, sys: 965 µs, total: 2.59 ms"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"id": "285c5f3f",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[0, 1, 2, 3, 4]\n"
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]
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}
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],
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"source": [
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"lst = [1, 2, 3]\n",
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"lst.append(4)\n",
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"lst.insert(0, 0)\n",
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"print(lst) # Output: [0, 1, 2, 3, 4]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 17,
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"id": "0f34505e",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[0.84147098 0.90929743 0.14112001]\n",
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"[11 22 33]\n"
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]
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}
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],
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"source": [
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"arr = np.array([1, 2, 3])\n",
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"print(np.sin(arr)) # Output: [0.84147098 0.90929743 0.14112001]\n",
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"print(arr + np.array([10, 20, 30])) # Output: [11 22 33]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 18,
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"id": "de7323ba",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"3\n"
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]
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}
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],
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"source": [
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"nested_list = [[1, 2], [3, 4], [5, 6]]\n",
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"print(nested_list[1][0]) # Output: 3"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 19,
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"id": "e5382f00",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"(3, 2)\n",
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"[2 4 6]\n"
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]
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}
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],
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"source": [
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"matrix = np.array([[1, 2], [3, 4], [5, 6]])\n",
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"print(matrix.shape) # Output: (3, 2)\n",
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"print(matrix[:, 1]) # Output: [2 4 6]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 20,
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"id": "887d0537",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Mean: 3.5, Standard Deviation: 1.707825127659933\n"
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]
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}
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],
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"source": [
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"import numpy as np\n",
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"\n",
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"data = np.array([[1, 2, 3], [4, 5, 6]])\n",
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"mean = np.mean(data)\n",
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"std_dev = np.std(data)\n",
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"print(f\"Mean: {mean}, Standard Deviation: {std_dev}\")"
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]
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}
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],
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"metadata": {
@@ -248,7 +419,7 @@
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.9"
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"version": "3.11.6"
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},
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"toc": {
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"base_numbering": 1,

‎Chapter2/itertools.ipynb

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Original file line numberDiff line numberDiff line change
@@ -259,7 +259,24 @@
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"outputs": [
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{
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"data": {
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"application/javascript": "\n setTimeout(function() {\n var nbb_cell_id = 7;\n var nbb_unformatted_code = \"def multiply(x: float, y: float):\\n return x * y\";\n var nbb_formatted_code = \"def multiply(x: float, y: float):\\n return x * y\";\n var nbb_cells = Jupyter.notebook.get_cells();\n for (var i = 0; i < nbb_cells.length; ++i) {\n if (nbb_cells[i].input_prompt_number == nbb_cell_id) {\n if (nbb_cells[i].get_text() == nbb_unformatted_code) {\n nbb_cells[i].set_text(nbb_formatted_code);\n }\n break;\n }\n }\n }, 500);\n ",
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"application/javascript": [
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"\n",
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" setTimeout(function() {\n",
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" var nbb_cell_id = 7;\n",
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" var nbb_unformatted_code = \"def multiply(x: float, y: float):\\n return x * y\";\n",
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" var nbb_formatted_code = \"def multiply(x: float, y: float):\\n return x * y\";\n",
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" var nbb_cells = Jupyter.notebook.get_cells();\n",
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" for (var i = 0; i < nbb_cells.length; ++i) {\n",
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" if (nbb_cells[i].input_prompt_number == nbb_cell_id) {\n",
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" if (nbb_cells[i].get_text() == nbb_unformatted_code) {\n",
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" nbb_cells[i].set_text(nbb_formatted_code);\n",
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" }\n",
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" break;\n",
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" }\n",
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" }\n",
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" }, 500);\n",
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" "
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],
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"text/plain": [
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"<IPython.core.display.Javascript object>"
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]
@@ -297,7 +314,24 @@
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},
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{
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"data": {
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"application/javascript": "\n setTimeout(function() {\n var nbb_cell_id = 14;\n var nbb_unformatted_code = \"nums = [(1, 2), (4, 2), (2, 5)]\\nlist(map(multiply, nums))\";\n var nbb_formatted_code = \"nums = [(1, 2), (4, 2), (2, 5)]\\nlist(map(multiply, nums))\";\n var nbb_cells = Jupyter.notebook.get_cells();\n for (var i = 0; i < nbb_cells.length; ++i) {\n if (nbb_cells[i].input_prompt_number == nbb_cell_id) {\n if (nbb_cells[i].get_text() == nbb_unformatted_code) {\n nbb_cells[i].set_text(nbb_formatted_code);\n }\n break;\n }\n }\n }, 500);\n ",
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"application/javascript": [
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"\n",
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" setTimeout(function() {\n",
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" var nbb_cell_id = 14;\n",
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" var nbb_unformatted_code = \"nums = [(1, 2), (4, 2), (2, 5)]\\nlist(map(multiply, nums))\";\n",
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" var nbb_formatted_code = \"nums = [(1, 2), (4, 2), (2, 5)]\\nlist(map(multiply, nums))\";\n",
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" var nbb_cells = Jupyter.notebook.get_cells();\n",
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" for (var i = 0; i < nbb_cells.length; ++i) {\n",
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" if (nbb_cells[i].input_prompt_number == nbb_cell_id) {\n",
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" if (nbb_cells[i].get_text() == nbb_unformatted_code) {\n",
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" nbb_cells[i].set_text(nbb_formatted_code);\n",
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" }\n",
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" break;\n",
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" }\n",
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" }\n",
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" }, 500);\n",
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" "
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],
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"text/plain": [
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"<IPython.core.display.Javascript object>"
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]
@@ -342,7 +376,24 @@
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},
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{
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"data": {
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"application/javascript": "\n setTimeout(function() {\n var nbb_cell_id = 15;\n var nbb_unformatted_code = \"from itertools import starmap\\n\\nlist(starmap(multiply, nums))\";\n var nbb_formatted_code = \"from itertools import starmap\\n\\nlist(starmap(multiply, nums))\";\n var nbb_cells = Jupyter.notebook.get_cells();\n for (var i = 0; i < nbb_cells.length; ++i) {\n if (nbb_cells[i].input_prompt_number == nbb_cell_id) {\n if (nbb_cells[i].get_text() == nbb_unformatted_code) {\n nbb_cells[i].set_text(nbb_formatted_code);\n }\n break;\n }\n }\n }, 500);\n ",
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"application/javascript": [
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"\n",
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" setTimeout(function() {\n",
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" var nbb_cell_id = 15;\n",
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" var nbb_unformatted_code = \"from itertools import starmap\\n\\nlist(starmap(multiply, nums))\";\n",
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" var nbb_formatted_code = \"from itertools import starmap\\n\\nlist(starmap(multiply, nums))\";\n",
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" var nbb_cells = Jupyter.notebook.get_cells();\n",
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" for (var i = 0; i < nbb_cells.length; ++i) {\n",
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" if (nbb_cells[i].input_prompt_number == nbb_cell_id) {\n",
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" if (nbb_cells[i].get_text() == nbb_unformatted_code) {\n",
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" nbb_cells[i].set_text(nbb_formatted_code);\n",
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" }\n",
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" break;\n",
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" }\n",
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" }\n",
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" }, 500);\n",
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" "
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],
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"text/plain": [
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"<IPython.core.display.Javascript object>"
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]
@@ -715,7 +766,7 @@
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"metadata": {
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"hide_input": false,
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"kernelspec": {
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"display_name": "venv",
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},

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