168 lines
4.0 KiB
Plaintext
168 lines
4.0 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "fe7a3037-5c49-4097-9a5d-575b958cc7f8",
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"metadata": {},
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"source": [
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"# Data Extraction"
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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": "fc68ad1d-e64c-48b7-9461-50d872d30473",
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"metadata": {},
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"outputs": [],
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"source": [
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"import os\n",
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"from pathlib import Path\n",
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"from pantograph.server import Server"
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]
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},
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{
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"cell_type": "markdown",
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"id": "fd13c644-d731-4f81-964e-584bbd43e51c",
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"metadata": {},
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"source": [
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"## Tactic Invocation\n",
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"\n",
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"Pantograph can extract tactic invocation data from a Lean file. A **tactic\n",
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"invocation** is a tuple containing the before and after goal states, and the\n",
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"tactic which converts the \"before\" state to the \"after\" state.\n",
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"\n",
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"To extract tactic invocation data, use `server.tactic_invocations(file_name)`\n",
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"and supply the file name of the input Lean 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": 2,
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"id": "a0a2a661-e357-4b80-92d1-4172670ab061",
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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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"$PWD: /home/aniva/Projects/atp/PyPantograph/examples/Example\n",
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"==== #0 ====\n",
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"/-- Ensure that Aesop is running -/\n",
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"example : α → α :=\n",
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" by aesop\n",
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"\n",
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"\n",
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"==== #1 ====\n",
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"example : ∀ (p q: Prop), p ∨ q → q ∨ p := by\n",
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" intro p q h\n",
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" -- Here are some comments\n",
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" cases h\n",
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" . apply Or.inr\n",
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" assumption\n",
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" . apply Or.inl\n",
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" assumption\n",
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"\n",
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"==== Invocations ====\n",
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"α : Sort ?u.7\n",
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"⊢ α → α\n",
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"aesop\n",
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"\n",
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"\n",
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"⊢ ∀ (p q : Prop), p ∨ q → q ∨ p\n",
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"intro p q h\n",
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"p q : Prop\n",
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"h : p ∨ q\n",
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"⊢ q ∨ p\n",
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"\n",
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"p q : Prop\n",
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"h : p ∨ q\n",
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"⊢ q ∨ p\n",
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"cases h\n",
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"case inl\n",
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"p q : Prop\n",
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"h✝ : p\n",
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"⊢ q ∨ p\n",
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"case inr p q : Prop h✝ : q ⊢ q ∨ p\n",
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"\n",
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"case inl\n",
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"p q : Prop\n",
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"h✝ : p\n",
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"⊢ q ∨ p\n",
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"apply Or.inr\n",
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"case inl.h\n",
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"p q : Prop\n",
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"h✝ : p\n",
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"⊢ p\n",
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"\n",
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"case inl.h\n",
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"p q : Prop\n",
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"h✝ : p\n",
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"⊢ p\n",
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"assumption\n",
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"\n",
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"\n",
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"case inr\n",
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"p q : Prop\n",
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"h✝ : q\n",
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"⊢ q ∨ p\n",
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"apply Or.inl\n",
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"case inr.h\n",
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"p q : Prop\n",
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"h✝ : q\n",
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"⊢ q\n",
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"\n",
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"case inr.h\n",
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"p q : Prop\n",
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"h✝ : q\n",
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"⊢ q\n",
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"assumption\n",
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"\n",
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"\n"
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]
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}
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],
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"source": [
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"project_path = Path(os.getcwd()).parent.resolve() / 'examples/Example'\n",
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"print(f\"$PWD: {project_path}\")\n",
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"server = Server(imports=['Example'], project_path=project_path)\n",
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"units, invocations = server.tactic_invocations(project_path / \"Example.lean\")\n",
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"for i, u in enumerate(units):\n",
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" print(f\"==== #{i} ====\")\n",
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" print(u)\n",
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"print(\"==== Invocations ====\")\n",
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"for i in invocations:\n",
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" print(f\"{i.before}\\n{i.tactic}\\n{i.after}\\n\")"
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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": "51f5398b-5416-4dc1-81cd-6d2514758232",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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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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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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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": "3.12.6"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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