\"\n@@ -1265,34 +1265,34 @@\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 18,\n \"metadata\": {\n \"execution\": {\n- \"iopub.execute_input\": \"2026-10-04T03:35:59.973057Z\",\n- \"iopub.status.busy\": \"2026-10-04T03:35:59.972732Z\",\n- \"iopub.status.idle\": \"2026-10-04T03:35:59.977941Z\",\n- \"shell.execute_reply\": \"2026-10-04T03:35:59.977351Z\"\n+ \"iopub.execute_input\": \"2025-08-31T21:18:16.666766Z\",\n+ \"iopub.status.busy\": \"2025-08-31T21:18:16.666448Z\",\n+ \"iopub.status.idle\": \"2025-08-31T21:18:16.671528Z\",\n+ \"shell.execute_reply\": \"2025-08-31T21:18:16.670956Z\"\n }\n },\n \"outputs\": [],\n \"source\": [\n \"%config InlineBackend.figure_formats = ['png']\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 19,\n \"metadata\": {\n \"execution\": {\n- \"iopub.execute_input\": \"2026-10-04T03:35:59.979699Z\",\n- \"iopub.status.busy\": \"2026-10-04T03:35:59.979486Z\",\n- \"iopub.status.idle\": \"2026-10-04T03:36:00.050503Z\",\n- \"shell.execute_reply\": \"2026-10-04T03:36:00.049747Z\"\n+ \"iopub.execute_input\": \"2025-08-31T21:18:16.673295Z\",\n+ \"iopub.status.busy\": \"2025-08-31T21:18:16.673082Z\",\n+ \"iopub.status.idle\": \"2025-08-31T21:18:16.740891Z\",\n+ \"shell.execute_reply\": \"2025-08-31T21:18:16.740317Z\"\n }\n },\n \"outputs\": [\n {\n \"data\": {\n \"image/png\": 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\",\n \"text/plain\": [\n@@ -1316,34 +1316,34 @@\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 20,\n \"metadata\": {\n \"execution\": {\n- \"iopub.execute_input\": \"2026-10-04T03:36:00.052552Z\",\n- \"iopub.status.busy\": \"2026-10-04T03:36:00.052337Z\",\n- \"iopub.status.idle\": \"2026-10-04T03:36:00.057148Z\",\n- \"shell.execute_reply\": \"2026-10-04T03:36:00.056370Z\"\n+ \"iopub.execute_input\": \"2025-08-31T21:18:16.742711Z\",\n+ \"iopub.status.busy\": \"2025-08-31T21:18:16.742494Z\",\n+ \"iopub.status.idle\": \"2025-08-31T21:18:16.747104Z\",\n+ \"shell.execute_reply\": \"2025-08-31T21:18:16.746541Z\"\n }\n },\n \"outputs\": [],\n \"source\": [\n \"%config InlineBackend.figure_formats = ['png2x']\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 21,\n \"metadata\": {\n \"execution\": {\n- \"iopub.execute_input\": \"2026-10-04T03:36:00.058909Z\",\n- \"iopub.status.busy\": \"2026-10-04T03:36:00.058688Z\",\n- \"iopub.status.idle\": \"2026-10-04T03:36:00.154180Z\",\n- \"shell.execute_reply\": \"2026-10-04T03:36:00.153640Z\"\n+ \"iopub.execute_input\": \"2025-08-31T21:18:16.748891Z\",\n+ \"iopub.status.busy\": \"2025-08-31T21:18:16.748676Z\",\n+ \"iopub.status.idle\": \"2025-08-31T21:18:16.841361Z\",\n+ \"shell.execute_reply\": \"2025-08-31T21:18:16.840783Z\"\n }\n },\n \"outputs\": [\n {\n \"data\": {\n \"image/png\": 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\",\n \"text/plain\": [\n@@ -1374,18 +1374,18 @@\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 22,\n \"metadata\": {\n \"execution\": {\n- \"iopub.execute_input\": \"2026-10-04T03:36:00.155964Z\",\n- \"iopub.status.busy\": \"2026-10-04T03:36:00.155747Z\",\n- \"iopub.status.idle\": \"2026-10-04T03:36:00.290420Z\",\n- \"shell.execute_reply\": \"2026-10-04T03:36:00.289697Z\"\n+ \"iopub.execute_input\": \"2025-08-31T21:18:16.843177Z\",\n+ \"iopub.status.busy\": \"2025-08-31T21:18:16.842962Z\",\n+ \"iopub.status.idle\": \"2025-08-31T21:18:16.976455Z\",\n+ \"shell.execute_reply\": \"2025-08-31T21:18:16.975761Z\"\n }\n },\n \"outputs\": [\n {\n \"ename\": \"RuntimeError\",\n \"evalue\": \"'widget is not a recognised GUI loop or backend name\",\n \"output_type\": \"error\",\n@@ -1412,18 +1412,18 @@\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 23,\n \"metadata\": {\n \"execution\": {\n- \"iopub.execute_input\": \"2026-10-04T03:36:00.292299Z\",\n- \"iopub.status.busy\": \"2026-10-04T03:36:00.292086Z\",\n- \"iopub.status.idle\": \"2026-10-04T03:36:00.429979Z\",\n- \"shell.execute_reply\": \"2026-10-04T03:36:00.429384Z\"\n+ \"iopub.execute_input\": \"2025-08-31T21:18:16.978370Z\",\n+ \"iopub.status.busy\": \"2025-08-31T21:18:16.978159Z\",\n+ \"iopub.status.idle\": \"2025-08-31T21:18:17.112047Z\",\n+ \"shell.execute_reply\": \"2025-08-31T21:18:17.111453Z\"\n }\n },\n \"outputs\": [\n {\n \"data\": {\n \"image/png\": 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\",\n \"text/plain\": [\n@@ -1455,35 +1455,35 @@\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 24,\n \"metadata\": {\n \"execution\": {\n- \"iopub.execute_input\": \"2026-10-04T03:36:00.432051Z\",\n- \"iopub.status.busy\": \"2026-10-04T03:36:00.431830Z\",\n- \"iopub.status.idle\": \"2026-10-04T03:36:00.642171Z\",\n- \"shell.execute_reply\": \"2026-10-04T03:36:00.641469Z\"\n+ \"iopub.execute_input\": \"2025-08-31T21:18:17.113873Z\",\n+ \"iopub.status.busy\": \"2025-08-31T21:18:17.113658Z\",\n+ \"iopub.status.idle\": \"2025-08-31T21:18:17.319314Z\",\n+ \"shell.execute_reply\": \"2025-08-31T21:18:17.318646Z\"\n }\n },\n \"outputs\": [],\n \"source\": [\n \"import numpy as np\\n\",\n \"import pandas as pd\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 25,\n \"metadata\": {\n \"execution\": {\n- \"iopub.execute_input\": \"2026-10-04T03:36:00.644382Z\",\n- \"iopub.status.busy\": \"2026-10-04T03:36:00.643996Z\",\n- \"iopub.status.idle\": \"2026-10-04T03:36:00.653752Z\",\n- \"shell.execute_reply\": \"2026-10-04T03:36:00.652907Z\"\n+ \"iopub.execute_input\": \"2025-08-31T21:18:17.321937Z\",\n+ \"iopub.status.busy\": \"2025-08-31T21:18:17.321582Z\",\n+ \"iopub.status.idle\": \"2025-08-31T21:18:17.330805Z\",\n+ \"shell.execute_reply\": \"2025-08-31T21:18:17.330253Z\"\n }\n },\n \"outputs\": [\n {\n \"data\": {\n \"text/html\": [\n \"\\n\",\n@@ -1619,34 +1619,34 @@\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 26,\n \"metadata\": {\n \"execution\": {\n- \"iopub.execute_input\": \"2026-10-04T03:36:00.655537Z\",\n- \"iopub.status.busy\": \"2026-10-04T03:36:00.655320Z\",\n- \"iopub.status.idle\": \"2026-10-04T03:36:00.658286Z\",\n- \"shell.execute_reply\": \"2026-10-04T03:36:00.657484Z\"\n+ \"iopub.execute_input\": \"2025-08-31T21:18:17.332693Z\",\n+ \"iopub.status.busy\": \"2025-08-31T21:18:17.332480Z\",\n+ \"iopub.status.idle\": \"2025-08-31T21:18:17.335267Z\",\n+ \"shell.execute_reply\": \"2025-08-31T21:18:17.334699Z\"\n }\n },\n \"outputs\": [],\n \"source\": [\n \"from IPython.display import Markdown\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 27,\n \"metadata\": {\n \"execution\": {\n- \"iopub.execute_input\": \"2026-10-04T03:36:00.660228Z\",\n- \"iopub.status.busy\": \"2026-10-04T03:36:00.660003Z\",\n- \"iopub.status.idle\": \"2026-10-04T03:36:00.663919Z\",\n- \"shell.execute_reply\": \"2026-10-04T03:36:00.663193Z\"\n+ \"iopub.execute_input\": \"2025-08-31T21:18:17.337038Z\",\n+ \"iopub.status.busy\": \"2025-08-31T21:18:17.336828Z\",\n+ \"iopub.status.idle\": \"2025-08-31T21:18:17.340804Z\",\n+ \"shell.execute_reply\": \"2025-08-31T21:18:17.340249Z\"\n }\n },\n \"outputs\": [\n {\n \"data\": {\n \"text/markdown\": [\n \"\\n\",\n@@ -1718,18 +1718,18 @@\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 28,\n \"metadata\": {\n \"execution\": {\n- \"iopub.execute_input\": \"2026-10-04T03:36:00.665774Z\",\n- \"iopub.status.busy\": \"2026-10-04T03:36:00.665560Z\",\n- \"iopub.status.idle\": \"2026-10-04T03:36:00.669640Z\",\n- \"shell.execute_reply\": \"2026-10-04T03:36:00.669064Z\"\n+ \"iopub.execute_input\": \"2025-08-31T21:18:17.342601Z\",\n+ \"iopub.status.busy\": \"2025-08-31T21:18:17.342391Z\",\n+ \"iopub.status.idle\": \"2025-08-31T21:18:17.346501Z\",\n+ \"shell.execute_reply\": \"2025-08-31T21:18:17.345948Z\"\n }\n },\n \"outputs\": [\n {\n \"data\": {\n \"text/html\": [\n \"\\n\",\n@@ -1740,15 +1740,15 @@\n \" frameborder=\\\"0\\\"\\n\",\n \" allowfullscreen\\n\",\n \" \\n\",\n \" >\\n\",\n \" \"\n ],\n \"text/plain\": [\n- \"\"\n+ \"\"\n ]\n },\n \"execution_count\": 28,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n }\n ],\n@@ -1835,18 +1835,18 @@\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 29,\n \"metadata\": {\n \"execution\": {\n- \"iopub.execute_input\": \"2026-10-04T03:36:00.671437Z\",\n- \"iopub.status.busy\": \"2026-10-04T03:36:00.671225Z\",\n- \"iopub.status.idle\": \"2026-10-04T03:36:00.675334Z\",\n- \"shell.execute_reply\": \"2026-10-04T03:36:00.674506Z\"\n+ \"iopub.execute_input\": \"2025-08-31T21:18:17.348444Z\",\n+ \"iopub.status.busy\": \"2025-08-31T21:18:17.348234Z\",\n+ \"iopub.status.idle\": \"2025-08-31T21:18:17.352218Z\",\n+ \"shell.execute_reply\": \"2025-08-31T21:18:17.351653Z\"\n }\n },\n \"outputs\": [\n {\n \"data\": {\n \"application/javascript\": [\n \"\\n\",\n@@ -1881,18 +1881,18 @@\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 30,\n \"metadata\": {\n \"execution\": {\n- \"iopub.execute_input\": \"2026-10-04T03:36:00.677075Z\",\n- \"iopub.status.busy\": \"2026-10-04T03:36:00.676847Z\",\n- \"iopub.status.idle\": \"2026-10-04T03:36:00.680317Z\",\n- \"shell.execute_reply\": \"2026-10-04T03:36:00.679571Z\"\n+ \"iopub.execute_input\": \"2025-08-31T21:18:17.354021Z\",\n+ \"iopub.status.busy\": \"2025-08-31T21:18:17.353811Z\",\n+ \"iopub.status.idle\": \"2025-08-31T21:18:17.357247Z\",\n+ \"shell.execute_reply\": \"2025-08-31T21:18:17.356708Z\"\n }\n },\n \"outputs\": [\n {\n \"data\": {\n \"text/x-haskell\": [\n \"main = putStrLn \\\"Hello, world!\\\"\"\n@@ -1922,18 +1922,18 @@\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 31,\n \"metadata\": {\n \"execution\": {\n- \"iopub.execute_input\": \"2026-10-04T03:36:00.682137Z\",\n- \"iopub.status.busy\": \"2026-10-04T03:36:00.681927Z\",\n- \"iopub.status.idle\": \"2026-10-04T03:36:00.685192Z\",\n- \"shell.execute_reply\": \"2026-10-04T03:36:00.684512Z\"\n+ \"iopub.execute_input\": \"2025-08-31T21:18:17.359052Z\",\n+ \"iopub.status.busy\": \"2025-08-31T21:18:17.358842Z\",\n+ \"iopub.status.idle\": \"2025-08-31T21:18:17.362221Z\",\n+ \"shell.execute_reply\": \"2025-08-31T21:18:17.361659Z\"\n }\n },\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n@@ -1963,18 +1963,18 @@\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 32,\n \"metadata\": {\n \"execution\": {\n- \"iopub.execute_input\": \"2026-10-04T03:36:00.686955Z\",\n- \"iopub.status.busy\": \"2026-10-04T03:36:00.686747Z\",\n- \"iopub.status.idle\": \"2026-10-04T03:36:00.692129Z\",\n- \"shell.execute_reply\": \"2026-10-04T03:36:00.691382Z\"\n+ \"iopub.execute_input\": \"2025-08-31T21:18:17.363996Z\",\n+ \"iopub.status.busy\": \"2025-08-31T21:18:17.363764Z\",\n+ \"iopub.status.idle\": \"2025-08-31T21:18:17.368802Z\",\n+ \"shell.execute_reply\": \"2025-08-31T21:18:17.368228Z\"\n }\n },\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n@@ -2021,18 +2021,18 @@\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 33,\n \"metadata\": {\n \"execution\": {\n- \"iopub.execute_input\": \"2026-10-04T03:36:00.693937Z\",\n- \"iopub.status.busy\": \"2026-10-04T03:36:00.693723Z\",\n- \"iopub.status.idle\": \"2026-10-04T03:36:00.698418Z\",\n- \"shell.execute_reply\": \"2026-10-04T03:36:00.697715Z\"\n+ \"iopub.execute_input\": \"2025-08-31T21:18:17.370647Z\",\n+ \"iopub.status.busy\": \"2025-08-31T21:18:17.370437Z\",\n+ \"iopub.status.idle\": \"2025-08-31T21:18:17.374909Z\",\n+ \"shell.execute_reply\": \"2025-08-31T21:18:17.374330Z\"\n }\n },\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n@@ -2067,18 +2067,18 @@\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 34,\n \"metadata\": {\n \"execution\": {\n- \"iopub.execute_input\": \"2026-10-04T03:36:00.700219Z\",\n- \"iopub.status.busy\": \"2026-10-04T03:36:00.700005Z\",\n- \"iopub.status.idle\": \"2026-10-04T03:36:00.704290Z\",\n- \"shell.execute_reply\": \"2026-10-04T03:36:00.703564Z\"\n+ \"iopub.execute_input\": \"2025-08-31T21:18:17.376680Z\",\n+ \"iopub.status.busy\": \"2025-08-31T21:18:17.376469Z\",\n+ \"iopub.status.idle\": \"2025-08-31T21:18:17.380729Z\",\n+ \"shell.execute_reply\": \"2025-08-31T21:18:17.380161Z\"\n }\n },\n \"outputs\": [\n {\n \"name\": \"stdout\",\n \"output_type\": \"stream\",\n \"text\": [\n"}]}]}, {"source1": "./usr/share/doc/python-nbsphinx/html/configuring-kernels.ipynb", "source2": "./usr/share/doc/python-nbsphinx/html/configuring-kernels.ipynb", "unified_diff": null, "details": [{"source1": "Pretty-printed", "source2": "Pretty-printed", "comments": ["Similarity: 0.999609375%", "Differences: {\"'cells'\": \"{5: {'metadata': {'execution': {'iopub.execute_input': '2025-08-31T21:18:21.648049Z', \"", " \"'iopub.status.busy': '2025-08-31T21:18:21.647828Z', 'iopub.status.idle': \"", " \"'2025-08-31T21:18:21.653979Z', 'shell.execute_reply': \"", " \"'2025-08-31T21:18:21.653437Z'}}}}\"}"], "unified_diff": "@@ -63,18 +63,18 @@\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 1,\n \"metadata\": {\n \"execution\": {\n- \"iopub.execute_input\": \"2026-10-04T03:36:04.889351Z\",\n- \"iopub.status.busy\": \"2026-10-04T03:36:04.889139Z\",\n- \"iopub.status.idle\": \"2026-10-04T03:36:04.895948Z\",\n- \"shell.execute_reply\": \"2026-10-04T03:36:04.895054Z\"\n+ \"iopub.execute_input\": \"2025-08-31T21:18:21.648049Z\",\n+ \"iopub.status.busy\": \"2025-08-31T21:18:21.647828Z\",\n+ \"iopub.status.idle\": \"2025-08-31T21:18:21.653979Z\",\n+ \"shell.execute_reply\": \"2025-08-31T21:18:21.653437Z\"\n }\n },\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"'Hello from conf.py!'\"\n"}]}, {"source1": "./usr/share/doc/python-nbsphinx/html/custom-css.ipynb", "source2": "./usr/share/doc/python-nbsphinx/html/custom-css.ipynb", "unified_diff": null, "details": [{"source1": "Pretty-printed", "source2": "Pretty-printed", "comments": ["Similarity: 0.9994791666666667%", "Differences: {\"'cells'\": \"{5: {'metadata': {'execution': {'iopub.execute_input': '2025-08-31T21:18:23.439575Z', \"", " \"'iopub.status.busy': '2025-08-31T21:18:23.439348Z', 'iopub.status.idle': \"", " \"'2025-08-31T21:18:23.445577Z', 'shell.execute_reply': \"", " \"'2025-08-31T21:18:23.445073Z'}}}}\"}"], "unified_diff": "@@ -118,18 +118,18 @@\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 1,\n \"metadata\": {\n \"execution\": {\n- \"iopub.execute_input\": \"2026-10-04T03:36:06.333525Z\",\n- \"iopub.status.busy\": \"2026-10-04T03:36:06.333302Z\",\n- \"iopub.status.idle\": \"2026-10-04T03:36:06.339410Z\",\n- \"shell.execute_reply\": \"2026-10-04T03:36:06.338539Z\"\n+ \"iopub.execute_input\": \"2025-08-31T21:18:23.439575Z\",\n+ \"iopub.status.busy\": \"2025-08-31T21:18:23.439348Z\",\n+ \"iopub.status.idle\": \"2025-08-31T21:18:23.445577Z\",\n+ \"shell.execute_reply\": \"2025-08-31T21:18:23.445073Z\"\n }\n },\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n \"42\"\n"}]}, {"source1": "./usr/share/doc/python-nbsphinx/html/gallery/cell-metadata.html", "source2": "./usr/share/doc/python-nbsphinx/html/gallery/cell-metadata.html", "unified_diff": "@@ -117,15 +117,15 @@\n
\n \n
\n
\n
\n-<matplotlib.image.AxesImage at 0x7f10b939bb60>\n+<matplotlib.image.AxesImage at 0x7f62984abb60>\n
\n
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\n
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\n

\n", "details": [{"source1": "html2text {}", "source2": "html2text {}", "unified_diff": "@@ -24,15 +24,15 @@\n z = (1 - x / 2 + x ** 5 + y ** 3) * np.exp(-x ** 2 - y ** 2)\n [4]:\n zmax = np.max(np.abs(z))\n [5]:\n fig, ax = plt.subplots(figsize=[5, 3.5])\n ax.imshow(z, vmin=-zmax, vmax=zmax)\n [5]:\n-
\n+\n [../_images/gallery_cell-metadata_7_1.svg]\n *\b**\b**\b**\b**\b**\b* _\bn\bn_\bb\bb_\bs\bs_\bp\bp_\bh\bh_\bi\bi_\bn\bn_\bx\bx *\b**\b**\b**\b**\b**\b*\n *\b**\b**\b**\b* N\bNa\bav\bvi\big\bga\bat\bti\bio\bon\bn *\b**\b**\b**\b*\n * _\bI_\bn_\bs_\bt_\ba_\bl_\bl_\ba_\bt_\bi_\bo_\bn\n * _\bU_\bs_\ba_\bg_\be\n * _\bC_\bo_\bn_\bf_\bi_\bg_\bu_\br_\ba_\bt_\bi_\bo_\bn\n * _\bM_\ba_\br_\bk_\bd_\bo_\bw_\bn_\b _\bC_\be_\bl_\bl_\bs\n"}]}, {"source1": "./usr/share/doc/python-nbsphinx/html/gallery/cell-metadata.ipynb.gz", "source2": "./usr/share/doc/python-nbsphinx/html/gallery/cell-metadata.ipynb.gz", "unified_diff": null, "details": [{"source1": "cell-metadata.ipynb", "source2": "cell-metadata.ipynb", "unified_diff": null, "details": [{"source1": "Pretty-printed", "source2": "Pretty-printed", "comments": ["Similarity: 0.9981915020489239%", "Differences: {\"'cells'\": \"{2: {'metadata': {'execution': {'iopub.execute_input': '2025-08-31T21:18:25.504333Z', \"", " \"'iopub.status.busy': '2025-08-31T21:18:25.504121Z', 'iopub.status.idle': \"", " \"'2025-08-31T21:18:25.901009Z', 'shell.execute_reply': \"", " \"'2025-08-31T21:18:25.900332Z'}}}, 3: {'metadata': {'execution': \"", " \"{'iopub.execute_input': '2025-08-31T21:18:25.903599Z', 'iopub.status.busy': \"", " \"'2025-08-31T21:18:25.903322Z', 'iopub.status.idle': '2025-08-31T21:18:2 [\u2026]"], "unified_diff": "@@ -35,35 +35,35 @@\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 1,\n \"metadata\": {\n \"execution\": {\n- \"iopub.execute_input\": \"2026-10-04T03:36:08.197950Z\",\n- \"iopub.status.busy\": \"2026-10-04T03:36:08.197742Z\",\n- \"iopub.status.idle\": \"2026-10-04T03:36:08.588254Z\",\n- \"shell.execute_reply\": \"2026-10-04T03:36:08.587354Z\"\n+ \"iopub.execute_input\": \"2025-08-31T21:18:25.504333Z\",\n+ \"iopub.status.busy\": \"2025-08-31T21:18:25.504121Z\",\n+ \"iopub.status.idle\": \"2025-08-31T21:18:25.901009Z\",\n+ \"shell.execute_reply\": \"2025-08-31T21:18:25.900332Z\"\n }\n },\n \"outputs\": [],\n \"source\": [\n \"import matplotlib.pyplot as plt\\n\",\n \"import numpy as np\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 2,\n \"metadata\": {\n \"execution\": {\n- \"iopub.execute_input\": \"2026-10-04T03:36:08.590349Z\",\n- \"iopub.status.busy\": \"2026-10-04T03:36:08.590066Z\",\n- \"iopub.status.idle\": \"2026-10-04T03:36:08.593371Z\",\n- \"shell.execute_reply\": \"2026-10-04T03:36:08.592617Z\"\n+ \"iopub.execute_input\": \"2025-08-31T21:18:25.903599Z\",\n+ \"iopub.status.busy\": \"2025-08-31T21:18:25.903322Z\",\n+ \"iopub.status.idle\": \"2025-08-31T21:18:25.906227Z\",\n+ \"shell.execute_reply\": \"2025-08-31T21:18:25.905675Z\"\n }\n },\n \"outputs\": [],\n \"source\": [\n \"plt.rcParams['image.cmap'] = 'coolwarm'\\n\",\n \"plt.rcParams['image.origin'] = 'lower'\"\n ]\n@@ -77,61 +77,61 @@\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 3,\n \"metadata\": {\n \"execution\": {\n- \"iopub.execute_input\": \"2026-10-04T03:36:08.595382Z\",\n- \"iopub.status.busy\": \"2026-10-04T03:36:08.595171Z\",\n- \"iopub.status.idle\": \"2026-10-04T03:36:08.599038Z\",\n- \"shell.execute_reply\": \"2026-10-04T03:36:08.598218Z\"\n+ \"iopub.execute_input\": \"2025-08-31T21:18:25.907978Z\",\n+ \"iopub.status.busy\": \"2025-08-31T21:18:25.907731Z\",\n+ \"iopub.status.idle\": \"2025-08-31T21:18:25.911317Z\",\n+ \"shell.execute_reply\": \"2025-08-31T21:18:25.910744Z\"\n }\n },\n \"outputs\": [],\n \"source\": [\n \"x, y = np.meshgrid(np.arange(-3, 3, 0.1), np.arange(-2, 2, 0.1))\\n\",\n \"z = (1 - x / 2 + x ** 5 + y ** 3) * np.exp(-x ** 2 - y ** 2)\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 4,\n \"metadata\": {\n \"execution\": {\n- \"iopub.execute_input\": \"2026-10-04T03:36:08.600816Z\",\n- \"iopub.status.busy\": \"2026-10-04T03:36:08.600609Z\",\n- \"iopub.status.idle\": \"2026-10-04T03:36:08.603603Z\",\n- \"shell.execute_reply\": \"2026-10-04T03:36:08.602816Z\"\n+ \"iopub.execute_input\": \"2025-08-31T21:18:25.912981Z\",\n+ \"iopub.status.busy\": \"2025-08-31T21:18:25.912776Z\",\n+ \"iopub.status.idle\": \"2025-08-31T21:18:25.915559Z\",\n+ \"shell.execute_reply\": \"2025-08-31T21:18:25.915004Z\"\n }\n },\n \"outputs\": [],\n \"source\": [\n \"zmax = np.max(np.abs(z))\"\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 5,\n \"metadata\": {\n \"execution\": {\n- \"iopub.execute_input\": \"2026-10-04T03:36:08.605296Z\",\n- \"iopub.status.busy\": \"2026-10-04T03:36:08.605091Z\",\n- \"iopub.status.idle\": \"2026-10-04T03:36:08.932455Z\",\n- \"shell.execute_reply\": \"2026-10-04T03:36:08.931869Z\"\n+ \"iopub.execute_input\": \"2025-08-31T21:18:25.917268Z\",\n+ \"iopub.status.busy\": \"2025-08-31T21:18:25.917062Z\",\n+ \"iopub.status.idle\": \"2025-08-31T21:18:26.251204Z\",\n+ \"shell.execute_reply\": \"2025-08-31T21:18:26.250609Z\"\n },\n \"nbsphinx-thumbnail\": {\n \"tooltip\": \"This tooltip message was defined in cell metadata\"\n }\n },\n \"outputs\": [\n {\n \"data\": {\n \"text/plain\": [\n- \"\"\n+ \"\"\n ]\n },\n \"execution_count\": 5,\n \"metadata\": {},\n \"output_type\": \"execute_result\"\n },\n {\n@@ -173,28 +173,28 @@\n \" \\n\",\n \" \\n\",\n- \" \\n\",\n+ \" \\n\",\n \" \\n\",\n+ 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"./usr/share/doc/python-nbsphinx/html/gallery/cell-tag.html", "unified_diff": "@@ -82,15 +82,15 @@\n \n
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]\n+[]\n [../_images/gallery_cell-tag_4_1.svg]\n Although the next cell has an image, it won\u2019t be used as the thumbnail, due to\n the tag on the one above.\n [3]:\n fig, ax = plt.subplots(figsize=[6, 3])\n ax.scatter(range(10), [0, 8, 9, 1, -8, -10, -3, 7, 10, 4])\n [3]:\n-\n+\n [../_images/gallery_cell-tag_6_1.svg]\n *\b**\b**\b**\b**\b**\b* _\bn\bn_\bb\bb_\bs\bs_\bp\bp_\bh\bh_\bi\bi_\bn\bn_\bx\bx *\b**\b**\b**\b**\b**\b*\n *\b**\b**\b**\b* N\bNa\bav\bvi\big\bga\bat\bti\bio\bon\bn *\b**\b**\b**\b*\n * _\bI_\bn_\bs_\bt_\ba_\bl_\bl_\ba_\bt_\bi_\bo_\bn\n * _\bU_\bs_\ba_\bg_\be\n * _\bC_\bo_\bn_\bf_\bi_\bg_\bu_\br_\ba_\bt_\bi_\bo_\bn\n * _\bM_\ba_\br_\bk_\bd_\bo_\bw_\bn_\b _\bC_\be_\bl_\bl_\bs\n"}]}, {"source1": "./usr/share/doc/python-nbsphinx/html/gallery/cell-tag.ipynb.gz", "source2": "./usr/share/doc/python-nbsphinx/html/gallery/cell-tag.ipynb.gz", "unified_diff": null, "details": [{"source1": "cell-tag.ipynb", "source2": "cell-tag.ipynb", "unified_diff": null, "details": 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\"iopub.execute_input\": \"2025-08-31T21:18:30.650605Z\",\n+ \"iopub.status.busy\": \"2025-08-31T21:18:30.650392Z\",\n+ \"iopub.status.idle\": \"2025-08-31T21:18:31.051805Z\",\n+ \"shell.execute_reply\": \"2025-08-31T21:18:31.050955Z\"\n }\n },\n \"outputs\": [],\n \"source\": [\n \"import matplotlib.pyplot as plt\\n\",\n \"import numpy as np\"\n ]\n@@ -52,18 +52,18 @@\n ]\n },\n {\n \"cell_type\": \"code\",\n \"execution_count\": 2,\n \"metadata\": {\n \"execution\": {\n- \"iopub.execute_input\": \"2026-10-04T03:36:13.299885Z\",\n- \"iopub.status.busy\": \"2026-10-04T03:36:13.299613Z\",\n- \"iopub.status.idle\": \"2026-10-04T03:36:13.580726Z\",\n- \"shell.execute_reply\": \"2026-10-04T03:36:13.580171Z\"\n+ \"iopub.execute_input\": \"2025-08-31T21:18:31.054363Z\",\n+ \"iopub.status.busy\": \"2025-08-31T21:18:31.054076Z\",\n+ \"iopub.status.idle\": \"2025-08-31T21:18:31.334866Z\",\n+ \"shell.execute_reply\": \"2025-08-31T21:18:31.334044Z\"\n }\n },\n \"outputs\": [\n {\n \"data\": {\n 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\",\n \"text/plain\": [\n"}]}]}]}]}]}]}