Python Regular Expressions Made Easy # 14+15 -  Look arounds .ipynb

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   "source": [
    "#Welcome to look arounds"
   ]
  },
  {
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   "source": [
    "#Allows us to confirm that some sort of subpattern is ahead or behind\n",
    "#main pattern\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
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   },
   "outputs": [],
   "source": [
    "import re"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "outputs": [],
   "source": [
    "# 4 types of look arounds\n",
    "\n",
    "Positive look ahead   ?=\n",
    "\n",
    "Negative look ahead   ?!\n",
    "\n",
    "Positive look behind  ?<=\n",
    "\n",
    "Negative look behind ?<!\n",
    "\n",
    "\n",
    "#similar syntax\n",
    "\n",
    "?:   #non-capturing groups\n",
    "    \n",
    "?P   #naming groups\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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   },
   "source": [
    "#### Simple example of positive look ahead"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
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   "outputs": [],
   "source": [
    "#In the below string we are looking to consume the second column value\n",
    "#only if the first column starts with ABC and the last column \n",
    "#has the value 'active'\n",
    "\n",
    "#So only the first row and last row satisfies this condition which will\n",
    "#output the value '1.1.1.1' and 'x.x.x.x'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": true
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   "outputs": [],
   "source": [
    "string ='''ABC1    1.1.1.1    20151118    active\n",
    "           ABC2    2.2.2.2    20151118    inactive\n",
    "           ABC3    x.x.x.x    xxxxxxxx    active'''\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "pattern =re.compile('ABC\\w\\s+(\\S+)\\s+\\S+\\s+(?=active)')#positive look-ahead"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
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   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['1.1.1.1', 'x.x.x.x']"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "re.findall(pattern, string)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "re.search(pattern, string)"
   ]
  },
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   "outputs": [],
   "source": [
    "# However, we can also use non-capturing group"
   ]
  },
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   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
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   "outputs": [],
   "source": [
    "pattern =re.compile('ABC\\w\\s+(\\S+)\\s+\\S+\\s+(?:active)')#non-caputuring group"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['1.1.1.1', 'x.x.x.x']"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "re.findall(pattern, string)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<_sre.SRE_Match object; span=(0, 37), match='ABC1    1.1.1.1    20151118    active'>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "re.search(pattern, string)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Difference between non-caputure groups and look arounds\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#Look aheads dont' consume, non-capture groups consume"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "string ='abababacb'                   #whereever a's are surrounded by b\n",
    "                                      #so in our case we have two cases"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "pattern = re.compile('(?:b)(a)(?:b)')          #non-capturing group"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['a']"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "re.findall(pattern, string)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "string ='abababacb'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "pattern = re.compile('(?<=b)(a)(?=b)')  #look around"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['a', 'a']"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "re.findall(pattern, string)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Capture the entire look around "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "string ='abababacb'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "pattern = re.compile('(?=(bab))') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['bab', 'bab']"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "re.findall(pattern, string)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#Another example of positive look ahead"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import re\n",
    "string = 'I love cherries, apples, and strawberries.'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "pattern2 = re.compile(r'(\\w+)(?=\\.|,)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['cherries', 'apples', 'strawberries']"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "re.findall(pattern2,string)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "pattern2 = re.compile(r'(\\w+)(?:\\.|,)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['cherries', 'apples', 'strawberries']"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "re.findall(pattern2,string)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### consecutive look around fallacy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "string = '''cherry 100 red\n",
    "            apple  150 green\n",
    "            grapes 200 \n",
    "            '''\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "pattern = re.compile(r'[a-z]+\\s*(?= \\d+)(?=\\s*)(?=[a-z]+)')     #zero-width assertion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "re.findall(pattern,string)                           #consecutives are not really consecutives"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "pattern = re.compile(r'[a-z]+\\s*(?=\\d+\\s*[a-z]+)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['cherry ', 'apple  ']"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "re.findall(pattern,string)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#Password validation example  #order doesn't matter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "pattern = re.compile('(?=.*[a-z])(?=.*[A-Z])(?=.*[0-9])(?=.*[!?.])\\S+')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "string = 'AZN#3232!abbb32..'\n",
    "string2 = 'AZN#3232abbb3232'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<_sre.SRE_Match object; span=(0, 17), match='AZN#3232!abbb32..'>"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "re.search(pattern, string)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "re.search(pattern, string2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#If we didn't use look arounds we would need to use this complicated pattern\n",
    "\n",
    "(?:.*[a-z].*[A-Z].*[0-9].*[!?.])|(?:.*[A-Z][a-z].*[0-9].*[!?.])|(?:.*[0-9].*[a-z].*[A-Z].*[!?.])|(?:.*[!?.].*[a-z`].*[A-Z].*[0-9])|(?:.*[A-Z][a-z].*[!?.].*[0-9])|..."
   ]
  },
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    "collapsed": true
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    "collapsed": true
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