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Create ruff_notebook crate (#7039)

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## Summary

This PR moves `ruff/jupyter` into its own `ruff_notebook` crate. Beyond
the move itself, there were a few challenges:

1. `ruff_notebook` relies on the source map abstraction. I've moved the
source map into `ruff_diagnostics`, since it doesn't have any
dependencies on its own and is used alongside diagnostics.
2. `ruff_notebook` has a couple tests for end-to-end linting and
autofixing. I had to leave these tests in `ruff` itself.
3. We had code in `ruff/jupyter` that relied on Python lexing, in order
to provide a more targeted error message in the event that a user saves
a `.py` file with a `.ipynb` extension. I removed this in order to avoid
a dependency on the parser, it felt like it wasn't worth retaining just
for that dependency.

## Test Plan

`cargo test`
This commit is contained in:
Charlie Marsh 2023-09-01 14:56:44 +01:00 • committed by GitHub
parent 08e246764f
commit afcd00da56
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GPG key ID: 4AEE18F83AFDEB23
48 changed files with 274 additions and 253 deletions
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32
crates/ruff_notebook/resources/test/fixtures/jupyter/R.ipynb vendored Normal file
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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"print(paste(\"Hello\",\"WoRld\"))\n"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "R",
"language": "R",
"name": "ir"
},
"language_info": {
"codemirror_mode": "r",
"file_extension": ".r",
"mimetype": "text/x-r-source",
"name": "R",
"pygments_lexer": "r",
"version": "3.2.3"
}
},
"nbformat": 4,
"nbformat_minor": 2
}

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crates/ruff_notebook/resources/test/fixtures/jupyter/add_missing_cell_id.ipynb vendored Normal file
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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import math\n",
"import os\n",
"\n",
"math.pi"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python (ruff)",
"language": "python",
"name": "ruff"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.3"
}
},
"nbformat": 4,
"nbformat_minor": 5
}

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crates/ruff_notebook/resources/test/fixtures/jupyter/after_fix.ipynb vendored Normal file
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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"id": "1",
"metadata": {},
"outputs": [],
"source": [
"import math\n",
"\n",
"math.pi"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python (ruff)",
"language": "python",
"name": "ruff"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.3"
}
},
"nbformat": 4,
"nbformat_minor": 5
}

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crates/ruff_notebook/resources/test/fixtures/jupyter/before_fix.ipynb vendored Normal file
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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"id": "1",
"metadata": {},
"outputs": [],
"source": [
"import math\n",
"import os\n",
"\n",
"math.pi"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python (ruff)",
"language": "python",
"name": "ruff"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.3"
}
},
"nbformat": 4,
"nbformat_minor": 5
}

8
crates/ruff_notebook/resources/test/fixtures/jupyter/cell/cell_magic.json vendored Normal file
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{
"execution_count": null,
"cell_type": "code",
"id": "1",
"metadata": {},
"outputs": [],
"source": ["%%timeit\n", "print('hello world')"]
}

8
crates/ruff_notebook/resources/test/fixtures/jupyter/cell/code_and_magic.json vendored Normal file
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{
"execution_count": null,
"cell_type": "code",
"id": "1",
"metadata": {},
"outputs": [],
"source": ["def foo():\n", " pass\n", "\n", "%timeit foo()"]
}

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crates/ruff_notebook/resources/test/fixtures/jupyter/cell/markdown.json vendored Normal file
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{
"cell_type": "markdown",
"id": "1",
"metadata": {},
"source": ["This is a markdown cell\n", "Some more content"]
}

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crates/ruff_notebook/resources/test/fixtures/jupyter/cell/only_code.json vendored Normal file
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{
"execution_count": null,
"cell_type": "code",
"id": "1",
"metadata": {},
"outputs": [],
"source": ["def foo():\n", " pass"]
}

8
crates/ruff_notebook/resources/test/fixtures/jupyter/cell/only_magic.json vendored Normal file
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{
"execution_count": null,
"cell_type": "code",
"id": "1",
"metadata": {},
"outputs": [],
"source": "%timeit print('hello world')"
}

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crates/ruff_notebook/resources/test/fixtures/jupyter/invalid_extension.ipynb vendored Normal file
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#!/usr/bin/env python
# coding: utf-8
# In[1]:
def unused_variable():
x = 1
y = 2
print(f"cell one: {y}")
unused_variable()
# Let's do another mistake
# In[2]:
def mutable_argument(z=set()):
print(f"cell two: {z}")
mutable_argument()

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crates/ruff_notebook/resources/test/fixtures/jupyter/ipy_escape_command.ipynb vendored Normal file
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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"id": "eab4754a-d6df-4b41-8ee8-7e23aef440f9",
"metadata": {},
"outputs": [],
"source": [
"import math\n",
"\n",
"%matplotlib inline\n",
"\n",
"import os\n",
"\n",
"_ = math.pi"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "2b0e2986-1b87-4bb6-9b1d-c11ca1decd87",
"metadata": {},
"outputs": [],
"source": [
"%%timeit\n",
"import sys"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python (ruff)",
"language": "python",
"name": "ruff"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.3"
}
},
"nbformat": 4,
"nbformat_minor": 5
}

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crates/ruff_notebook/resources/test/fixtures/jupyter/ipy_escape_command_expected.ipynb vendored Normal file
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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"id": "cad32845-44f9-4a53-8b8c-a6b1bb3f3378",
"metadata": {},
"outputs": [],
"source": [
"import math\n",
"\n",
"%matplotlib inline\n",
"\n",
"\n",
"_ = math.pi"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "d7b8e967-8b4a-493b-b6f7-d5cecfb3a5c3",
"metadata": {},
"outputs": [],
"source": [
"%%timeit\n",
"import sys"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python (ruff)",
"language": "python",
"name": "ruff"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.3"
}
},
"nbformat": 4,
"nbformat_minor": 5
}

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crates/ruff_notebook/resources/test/fixtures/jupyter/isort.ipynb vendored Normal file
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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"id": "0c7535f6-43cb-423f-bfe1-d263b8f55da0",
"metadata": {},
"outputs": [],
"source": [
"from pathlib import Path\n",
"import random\n",
"import math"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "c066fa1a-5682-47af-8c17-5afec3cf4ad0",
"metadata": {},
"outputs": [],
"source": [
"from typing import Any\n",
"import collections\n",
"# Newline should be added here\n",
"def foo():\n",
" pass"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "16214f6f-bb32-4594-81be-79fb27c6ec92",
"metadata": {},
"outputs": [],
"source": [
"from pathlib import Path\n",
"import sys\n",
"\n",
"%matplotlib \\\n",
" --inline\n",
"\n",
"import math\n",
"import abc"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python (ruff)",
"language": "python",
"name": "ruff"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.3"
}
},
"nbformat": 4,
"nbformat_minor": 5
}

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@ -0,0 +1,70 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"id": "663ba955-baca-4f34-9ebb-840d2573ae3f",
"metadata": {},
"outputs": [],
"source": [
"import math\n",
"import random\n",
"from pathlib import Path"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "d0adfe23-8aea-47e9-bf67-d856cfcb96ea",
"metadata": {},
"outputs": [],
"source": [
"import collections\n",
"from typing import Any\n",
"\n",
"\n",
"# Newline should be added here\n",
"def foo():\n",
" pass"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "6d6c55c6-4a34-4662-914b-4ee11c9c24a5",
"metadata": {},
"outputs": [],
"source": [
"import sys\n",
"from pathlib import Path\n",
"\n",
"%matplotlib \\\n",
" --inline\n",
"\n",
"import abc\n",
"import math"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python (ruff)",
"language": "python",
"name": "ruff"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.3"
}
},
"nbformat": 4,
"nbformat_minor": 5
}

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crates/ruff_notebook/resources/test/fixtures/jupyter/no_cell_id.ipynb vendored Normal file
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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import math\n",
"import os\n",
"\n",
"math.pi"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python (ruff)",
"language": "python",
"name": "ruff"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.3"
}
},
"nbformat": 4,
"nbformat_minor": 2
}

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crates/ruff_notebook/resources/test/fixtures/jupyter/no_trailing_newline.ipynb vendored Normal file
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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"id": "4cec6161-f594-446c-ab65-37395bbb3127",
"metadata": {},
"outputs": [],
"source": [
"import math\n",
"import os\n",
"\n",
"_ = math.pi"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python (ruff)",
"language": "python",
"name": "ruff"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.3"
}
},
"nbformat": 4,
"nbformat_minor": 5
}

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broken "§=($/=()

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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"id": "a0efffbc-85f1-4513-bf49-5387ec3a2a4e",
"metadata": {},
"outputs": [],
"source": [
"def f():\n",
" foo1 = %matplotlib --list\n",
" foo2: list[str] = %matplotlib --list"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "6e0b2b50-43f2-4f59-951d-9404dd560ae4",
"metadata": {},
"outputs": [],
"source": [
"def f():\n",
" bar1 = !pwd\n",
" bar2: str = !pwd"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python (ruff)",
"language": "python",
"name": "ruff"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.3"
}
},
"nbformat": 4,
"nbformat_minor": 5
}

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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"id": "24426ef2-046c-453e-b809-05b56e7355e0",
"metadata": {},
"outputs": [],
"source": [
"def f():\n",
" %matplotlib --list\n",
" %matplotlib --list"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "3d98fdae-b86b-476e-b4db-9d3ce5562682",
"metadata": {},
"outputs": [],
"source": [
"def f():\n",
" !pwd\n",
" !pwd"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python (ruff)",
"language": "python",
"name": "ruff"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.3"
}
},
"nbformat": 4,
"nbformat_minor": 5
}

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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"ExecuteTime": {
"end_time": "2023-03-08T23:01:09.782916Z",
"start_time": "2023-03-08T23:01:09.705831Z"
},
"collapsed": false,
"jupyter": {
"outputs_hidden": false
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"cell one: 2\n"
]
}
],
"source": [
"def unused_variable():\n",
" x = 1\n",
" y = 2\n",
" print(f\"cell one: {y}\")\n",
"\n",
"unused_variable()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's do another mistake"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"ExecuteTime": {
"end_time": "2023-03-08T23:01:09.915760Z",
"start_time": "2023-03-08T23:01:09.733809Z"
},
"collapsed": true,
"jupyter": {
"outputs_hidden": true
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"cell two: set()\n"
]
}
],
"source": [
"def mutable_argument(z=set()):\n",
" print(f\"cell two: {z}\")\n",
"\n",
"mutable_argument()\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's create an empty cell"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Multi-line empty cell!"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"print(\"after empty cells\")"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python (ruff)",
"language": "python",
"name": "ruff"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.3"
}
},
"nbformat": 4,
"nbformat_minor": 4
}

1
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{}