{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Test `pidgy.tangle`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "        import pidgy, ast"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['BlockLexer',\n",
       " 'ExtraSyntax',\n",
       " 'IPython',\n",
       " 'Tangle',\n",
       " '__all__',\n",
       " '__builtins__',\n",
       " '__doc__',\n",
       " '__file__',\n",
       " '__loader__',\n",
       " '__name__',\n",
       " '__package__',\n",
       " '__spec__',\n",
       " '__test__',\n",
       " 'ast',\n",
       " 'demojize',\n",
       " 'init_json',\n",
       " 'mistune',\n",
       " 'normalizer',\n",
       " 'pidgy',\n",
       " 'pidgyManager',\n",
       " 'tangle',\n",
       " 'typing']"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "    dir(pidgy.tangle)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "    tangle = pidgy.tangle.Tangle()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "    s = \"\"\"---\n",
    "    a: front matter\n",
    "    ---\n",
    "    \n",
    "    This is a paragraph.\n",
    "    \n",
    "    * a list\n",
    "    \n",
    "        def f():\n",
    "        \n",
    "    A docstring\n",
    "        \n",
    "            print\n",
    "    \n",
    "    \"\"\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Unnormalized tokens."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'type': 'front_matter', 'text': '\\na: front matter\\n'},\n",
       " {'type': 'paragraph', 'text': 'This is a paragraph.'},\n",
       " {'type': 'list_start', 'ordered': False},\n",
       " {'type': 'loose_item_start'},\n",
       " {'type': 'text', 'text': 'a list'},\n",
       " {'type': 'newline'},\n",
       " {'type': 'text', 'text': '  def f():'},\n",
       " {'type': 'list_item_end'},\n",
       " {'type': 'list_end'},\n",
       " {'type': 'paragraph', 'text': 'A docstring'},\n",
       " {'type': 'code', 'lang': None, 'text': '    print'}]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "    \n",
    "    tangle.parse(s, normalize=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Normalized block tokens    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'type': 'front_matter', 'text': '\\na: front matter\\n'},\n",
       " {'type': 'paragraph',\n",
       "  'text': '\\nThis is a paragraph.\\n\\n* a list\\n\\n    def f():\\n    \\nA docstring'},\n",
       " {'type': 'code', 'lang': None, 'text': '\\n    \\n        print'}]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "    tangle.parse(s, normalize=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Normalized block tokens    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "        locals().update(__import__('ruamel.yaml').yaml.safe_load(\n",
      "        \"\"\"a: front matter\"\"\"\n",
      "        ))\n",
      "\n",
      "        \"\"\"This is a paragraph.\n",
      "\n",
      "        * a list\n",
      "\n",
      "            def f():\n",
      "    \n",
      "        A docstring\"\"\"\n",
      "    \n",
      "        print\n"
     ]
    }
   ],
   "source": [
    "    print(tangle.stringify(tangle.parse(s)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "    transform = pidgy.tangle.pidgyManager().transform_cell"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "locals().update(__import__('ruamel.yaml').yaml.safe_load(\n",
      "\"\"\"a: front matter\"\"\"\n",
      "))\n",
      "\n",
      "\"\"\"This is a paragraph.\n",
      "\n",
      "* a list\n",
      "\n",
      "    def f():\n",
      "    \n",
      "A docstring\"\"\"\n",
      "    \n",
      "print\n",
      "\n"
     ]
    }
   ],
   "source": [
    "    print(transform(s))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "    _robot_face__panda_face_  = 10\n",
      "\n"
     ]
    }
   ],
   "source": [
    "    print(pidgy.tangle.demojize(\"\"\"\n",
    "        🤖🐼 = 10\n",
    "    \"\"\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<_ast.Return at 0x10b3afeb8>]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "    ast.parse(transform(\"\"\"\n",
    "        return 100\n",
    "    \"\"\")).body"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<_ast.Call at 0x109043080>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "    pidgy.tangle.ExtraSyntax().visit(ast.parse(transform(\"\"\"\n",
    "        return 100\n",
    "    \"\"\"))).body[0].value"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}