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257 | 257 | },
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258 | 258 | {
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259 | 259 | "data": {
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260 |
| - "application/javascript": [ |
261 |
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262 |
| - " setTimeout(function() {\n", |
263 |
| - " var nbb_cell_id = 42;\n", |
264 |
| - " var nbb_unformatted_code = \"!pytest pytest_benchmark_example.py \";\n", |
265 |
| - " var nbb_formatted_code = \"!pytest pytest_benchmark_example.py\";\n", |
266 |
| - " var nbb_cells = Jupyter.notebook.get_cells();\n", |
267 |
| - " for (var i = 0; i < nbb_cells.length; ++i) {\n", |
268 |
| - " if (nbb_cells[i].input_prompt_number == nbb_cell_id) {\n", |
269 |
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270 |
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271 |
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272 |
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273 |
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274 |
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275 |
| - " }, 500);\n", |
276 |
| - " " |
277 |
| - ], |
| 260 | + "application/javascript": "\n setTimeout(function() {\n var nbb_cell_id = 42;\n var nbb_unformatted_code = \"!pytest pytest_benchmark_example.py \";\n var nbb_formatted_code = \"!pytest pytest_benchmark_example.py\";\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 ", |
278 | 261 | "text/plain": [
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279 | 262 | "<IPython.core.display.Javascript object>"
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280 | 263 | ]
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3570 | 3553 | },
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3571 | 3554 | {
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3572 | 3555 | "data": {
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3573 |
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3574 |
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3575 |
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3576 |
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3577 |
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3578 |
| - " var nbb_formatted_code = \"experience1 = {\\\"machine learning\\\": 2, \\\"python\\\": 3}\\nexperience2 = {\\\"ml\\\": 2, \\\"python\\\": 3}\\n\\nDeepDiff(\\n experience1,\\n experience2,\\n exclude_paths={\\\"root['ml']\\\", \\\"root['machine learning']\\\"},\\n)\";\n", |
3579 |
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3580 |
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3581 |
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3582 |
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3583 |
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3584 |
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3585 |
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3586 |
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3587 |
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3588 |
| - " }, 500);\n", |
3589 |
| - " " |
3590 |
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| 3556 | + "application/javascript": "\n setTimeout(function() {\n var nbb_cell_id = 25;\n var nbb_unformatted_code = \"experience1 = {\\\"machine learning\\\": 2, \\\"python\\\": 3}\\nexperience2 = {\\\"ml\\\": 2, \\\"python\\\": 3}\\n\\nDeepDiff(\\n experience1,\\n experience2,\\n exclude_paths={\\\"root['ml']\\\", \\\"root['machine learning']\\\"},\\n)\";\n var nbb_formatted_code = \"experience1 = {\\\"machine learning\\\": 2, \\\"python\\\": 3}\\nexperience2 = {\\\"ml\\\": 2, \\\"python\\\": 3}\\n\\nDeepDiff(\\n experience1,\\n experience2,\\n exclude_paths={\\\"root['ml']\\\", \\\"root['machine learning']\\\"},\\n)\";\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 ", |
3591 | 3557 | "text/plain": [
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3592 | 3558 | "<IPython.core.display.Javascript object>"
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3593 | 3559 | ]
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3639 | 3605 | },
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3640 | 3606 | {
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3641 | 3607 | "data": {
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3642 |
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3643 |
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3644 |
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3645 |
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3646 |
| - " var nbb_unformatted_code = \"num1 = 0.258\\nnum2 = 0.259\\n\\nDeepDiff(num1, num2, significant_digits=2)\";\n", |
3647 |
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3648 |
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3649 |
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3650 |
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3651 |
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3652 |
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3653 |
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3654 |
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3655 |
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3656 |
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3657 |
| - " }, 500);\n", |
3658 |
| - " " |
3659 |
| - ], |
| 3608 | + "application/javascript": "\n setTimeout(function() {\n var nbb_cell_id = 34;\n var nbb_unformatted_code = \"num1 = 0.258\\nnum2 = 0.259\\n\\nDeepDiff(num1, num2, significant_digits=2)\";\n var nbb_formatted_code = \"num1 = 0.258\\nnum2 = 0.259\\n\\nDeepDiff(num1, num2, significant_digits=2)\";\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 ", |
3660 | 3609 | "text/plain": [
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3661 | 3610 | "<IPython.core.display.Javascript object>"
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3662 | 3611 | ]
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3970 | 3919 | "outputs": [
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3971 | 3920 | {
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3972 | 3921 | "data": {
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3973 |
| - "application/javascript": [ |
3974 |
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3975 |
| - " setTimeout(function() {\n", |
3976 |
| - " var nbb_cell_id = 18;\n", |
3977 |
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3978 |
| - " var nbb_formatted_code = \"from deepchecks.checks.integrity.new_category import CategoryMismatchTrainTest\\nfrom deepchecks.base import Dataset\\nimport pandas as pd\";\n", |
3979 |
| - " var nbb_cells = Jupyter.notebook.get_cells();\n", |
3980 |
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3981 |
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3982 |
| - " if (nbb_cells[i].get_text() == nbb_unformatted_code) {\n", |
3983 |
| - " nbb_cells[i].set_text(nbb_formatted_code);\n", |
3984 |
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3985 |
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3986 |
| - " }\n", |
3987 |
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3988 |
| - " }, 500);\n", |
3989 |
| - " " |
3990 |
| - ], |
| 3922 | + "application/javascript": "\n setTimeout(function() {\n var nbb_cell_id = 18;\n var nbb_unformatted_code = \"from deepchecks.checks.integrity.new_category import CategoryMismatchTrainTest\\nfrom deepchecks.base import Dataset\\nimport pandas as pd\";\n var nbb_formatted_code = \"from deepchecks.checks.integrity.new_category import CategoryMismatchTrainTest\\nfrom deepchecks.base import Dataset\\nimport pandas as pd\";\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 ", |
3991 | 3923 | "text/plain": [
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3992 | 3924 | "<IPython.core.display.Javascript object>"
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3993 | 3925 | ]
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4015 | 3947 | "outputs": [
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4016 | 3948 | {
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4017 | 3949 | "data": {
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4018 |
| - "application/javascript": [ |
4019 |
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4020 |
| - " setTimeout(function() {\n", |
4021 |
| - " var nbb_cell_id = 19;\n", |
4022 |
| - " var nbb_unformatted_code = \"train = pd.DataFrame({'col1': ['a', 'b', 'c']})\\ntest = pd.DataFrame({'col1': ['c', 'd', 'e']})\\n\\ntrain_ds = Dataset(train, cat_features=['col1'])\\ntest_ds = Dataset(test, cat_features=['col1'])\";\n", |
4023 |
| - " var nbb_formatted_code = \"train = pd.DataFrame({\\\"col1\\\": [\\\"a\\\", \\\"b\\\", \\\"c\\\"]})\\ntest = pd.DataFrame({\\\"col1\\\": [\\\"c\\\", \\\"d\\\", \\\"e\\\"]})\\n\\ntrain_ds = Dataset(train, cat_features=[\\\"col1\\\"])\\ntest_ds = Dataset(test, cat_features=[\\\"col1\\\"])\";\n", |
4024 |
| - " var nbb_cells = Jupyter.notebook.get_cells();\n", |
4025 |
| - " for (var i = 0; i < nbb_cells.length; ++i) {\n", |
4026 |
| - " if (nbb_cells[i].input_prompt_number == nbb_cell_id) {\n", |
4027 |
| - " if (nbb_cells[i].get_text() == nbb_unformatted_code) {\n", |
4028 |
| - " nbb_cells[i].set_text(nbb_formatted_code);\n", |
4029 |
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4030 |
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4031 |
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4032 |
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4033 |
| - " }, 500);\n", |
4034 |
| - " " |
4035 |
| - ], |
| 3950 | + "application/javascript": "\n setTimeout(function() {\n var nbb_cell_id = 19;\n var nbb_unformatted_code = \"train = pd.DataFrame({'col1': ['a', 'b', 'c']})\\ntest = pd.DataFrame({'col1': ['c', 'd', 'e']})\\n\\ntrain_ds = Dataset(train, cat_features=['col1'])\\ntest_ds = Dataset(test, cat_features=['col1'])\";\n var nbb_formatted_code = \"train = pd.DataFrame({\\\"col1\\\": [\\\"a\\\", \\\"b\\\", \\\"c\\\"]})\\ntest = pd.DataFrame({\\\"col1\\\": [\\\"c\\\", \\\"d\\\", \\\"e\\\"]})\\n\\ntrain_ds = Dataset(train, cat_features=[\\\"col1\\\"])\\ntest_ds = Dataset(test, cat_features=[\\\"col1\\\"])\";\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 ", |
4036 | 3951 | "text/plain": [
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4037 | 3952 | "<IPython.core.display.Javascript object>"
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4038 | 3953 | ]
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4117 | 4032 | },
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4118 | 4033 | {
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4119 | 4034 | "data": {
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4120 |
| - "application/javascript": [ |
4121 |
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4122 |
| - " setTimeout(function() {\n", |
4123 |
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4124 |
| - " var nbb_unformatted_code = \"CategoryMismatchTrainTest().run(train_ds, test_ds)\";\n", |
4125 |
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4126 |
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4127 |
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4128 |
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4129 |
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4130 |
| - " nbb_cells[i].set_text(nbb_formatted_code);\n", |
4131 |
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4132 |
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4133 |
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4134 |
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4135 |
| - " }, 500);\n", |
4136 |
| - " " |
4137 |
| - ], |
| 4035 | + "application/javascript": "\n setTimeout(function() {\n var nbb_cell_id = 22;\n var nbb_unformatted_code = \"CategoryMismatchTrainTest().run(train_ds, test_ds)\";\n var nbb_formatted_code = \"CategoryMismatchTrainTest().run(train_ds, test_ds)\";\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 ", |
4138 | 4036 | "text/plain": [
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4139 | 4037 | "<IPython.core.display.Javascript object>"
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4140 | 4038 | ]
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5011 | 4909 | "name": "python",
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5012 | 4910 | "nbconvert_exporter": "python",
|
5013 | 4911 | "pygments_lexer": "ipython3",
|
5014 |
| - "version": "3.11.6" |
| 4912 | + "version": "3.11.2" |
5015 | 4913 | },
|
5016 | 4914 | "toc": {
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5017 | 4915 | "base_numbering": 1,
|
|
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