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add pytest-mock
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‎Chapter5/testing.ipynb

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"By using mocks in these ways, we can create more reliable and controlled unit tests for our data projects, ensuring that our code behaves correctly under various conditions."
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]
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},
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{
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"cell_type": "markdown",
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"id": "3e516385",
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"metadata": {},
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"source": [
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"### pytest-mock vs unittest.mock: Simplifying Mocking in Python Tests"
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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": null,
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"id": "d6041e6a",
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"metadata": {
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"tags": [
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"hide-cell"
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]
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},
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"outputs": [],
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"source": [
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"!pip install pytest-mock"
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]
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},
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{
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"cell_type": "markdown",
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"id": "350f5aa4",
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"metadata": {},
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"source": [
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"Traditional mocking with unittest.mock often requires repetitive setup and teardown code, which can make test code harder to read and maintain. \n",
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"\n",
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"pytest-mock addresses this issue by leveraging pytest's fixture system, simplifying the mocking process and reducing boilerplate code.\n",
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"\n",
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"Consider the following example that demonstrates the difference between unittest.mock and pytest-mock.\n",
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"\n",
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"Using unittest.mock:"
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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": 5,
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"id": "ed814822",
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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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"Overwriting test_rm_file.py\n"
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]
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}
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],
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"source": [
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"%%writefile test_rm_file.py\n",
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"from unittest.mock import patch\n",
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"import os\n",
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"\n",
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"\n",
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"def rm_file(filename):\n",
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" os.remove(filename)\n",
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"\n",
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"\n",
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"def test_with_unittest_mock():\n",
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" with patch(\"os.remove\") as mock_remove:\n",
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" rm_file(\"file\")\n",
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" mock_remove.assert_called_once_with(\"file\")"
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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": 4,
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"id": "2e9d8b1d",
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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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"\u001b[1m============================= test session starts ==============================\u001b[0m\n",
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"platform darwin -- Python 3.11.2, pytest-7.4.3, pluggy-1.3.0\n",
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"rootdir: /Users/khuyentran/book/Efficient_Python_tricks_and_tools_for_data_scientists/Chapter5\n",
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"plugins: dvc-3.28.0, hydra-core-1.3.2, typeguard-4.1.5, mock-3.14.0, anyio-4.2.0, hypothesis-6.88.4\n",
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"collected 1 item \u001b[0m\n",
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"\n",
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"test_rm_file.py \u001b[32m.\u001b[0m\u001b[32m [100%]\u001b[0m\n",
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"\n",
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"\u001b[32m============================== \u001b[32m\u001b[1m1 passed\u001b[0m\u001b[32m in 0.01s\u001b[0m\u001b[32m ===============================\u001b[0m\n",
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"\u001b[0m"
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]
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}
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],
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"source": [
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"!pytest test_rm_file.py"
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]
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},
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{
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"cell_type": "markdown",
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"id": "0607964b",
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"metadata": {},
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"source": [
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"Using pytest-mock:"
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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": 3,
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"id": "2e772780",
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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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"Writing test_rm_file.py\n"
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]
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}
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],
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"source": [
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"%%writefile test_rm_file.py\n",
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"import os\n",
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"\n",
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"\n",
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"def rm_file(filename):\n",
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" os.remove(filename)\n",
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"\n",
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"\n",
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"def test_unix_fs(mocker):\n",
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" mocker.patch(\"os.remove\")\n",
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" rm_file(\"file\")\n",
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" os.remove.assert_called_once_with(\"file\")"
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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": 8,
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"id": "f74a6fca",
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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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"\u001b[1m============================= test session starts ==============================\u001b[0m\n",
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"platform darwin -- Python 3.11.2, pytest-7.4.3, pluggy-1.3.0\n",
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"rootdir: /Users/khuyentran/book/Efficient_Python_tricks_and_tools_for_data_scientists/Chapter5\n",
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"plugins: dvc-3.28.0, hydra-core-1.3.2, typeguard-4.1.5, mock-3.14.0, anyio-4.2.0, hypothesis-6.88.4\n",
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"collected 1 item \u001b[0m\n",
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"\n",
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"test_rm_file.py \u001b[32m.\u001b[0m\u001b[32m [100%]\u001b[0m\n",
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"\n",
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"\u001b[32m============================== \u001b[32m\u001b[1m1 passed\u001b[0m\u001b[32m in 0.01s\u001b[0m\u001b[32m ===============================\u001b[0m\n",
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"\u001b[0m"
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]
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}
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],
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"source": [
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"!pytest test_rm_file.py"
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]
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},
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{
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"cell_type": "markdown",
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"id": "4f873409",
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"metadata": {},
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"source": [
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"Key differences:\n",
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"\n",
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"1. Setup: pytest-mock uses the `mocker` fixture, automatically provided by pytest, eliminating the need to import patching utilities.\n",
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"\n",
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"2. Patching: With pytest-mock, you simply call `mocker.patch('os.remove')`, whereas unittest.mock requires a context manager or decorator.\n",
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"\n",
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"3. Cleanup: pytest-mock automatically undoes mocking after the test, while unittest.mock relies on the context manager for cleanup.\n",
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"\n",
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"4. Accessing mocks: pytest-mock allows direct access to the patched function (e.g., `os.remove.assert_called_once_with()`), while unittest.mock requires accessing the mock through a variable (e.g., `mock_remove.assert_called_once_with()`)."
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]
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},
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{
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"cell_type": "markdown",
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"id": "2ca3e0b7",
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"metadata": {},
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"source": [
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"[Link to pytest-mock](https://bit.ly/4dBDAOE)."
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
@@ -4728,7 +4909,7 @@
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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": "3.11.6"
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"version": "3.11.2"
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},
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"toc": {
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"base_numbering": 1,

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