English Thesaurus_Iteration-03.ipynb

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      "Please enter a word:Valkiray\n",
      "Did you mean to type any of the below words?\n",
      "\n",
      "['airway', 'airway', 'Val-Máira']\n",
      "Please enter a word:valkiree\n",
      "Did you mean to type any of the below words?\n",
      "\n",
      "['valise', 'valise', 'valise']\n",
      "Please enter a word:valkirie\n",
      "Did you mean to type any of the below words?\n",
      "\n",
      "['valise', 'valise', 'valise']\n",
      "Please enter a word:valkyrie\n",
      "Did you mean to type any of the below words?\n",
      "\n",
      "['valise', 'valise', 'valise']\n",
      "Please enter a word:mythopological\n",
      "Did you mean to type any of the below words?\n",
      "\n",
      "['mythological', 'mythological', 'mythological']\n",
      "Please enter a word:\\end\n",
      "Terminated!\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "from difflib import SequenceMatcher as sm\n",
    "from difflib import get_close_matches\n",
    "\n",
    "#The next sequence of code imports the raw json file with a dictionary of words and definitions.\n",
    "import json\n",
    "data = json.load(open(\"C:\\\\Users\\\\rajak\\\\Documents\\\\DATA Science Resources\\\\Certifications\\\\Udemy\\\\Course Files\\\\The Python Mega Course_03-2021\\\\English Thesaurus/data.json\"))\n",
    "\n",
    "\n",
    "#This next sequence takes a word as an argument and returns its definition as the output (among other things).\n",
    "#Enter \\end as the input to terminate the program and start again. Otherwise you can not exit the program without\n",
    "#resettig the kernel or causing an error.\n",
    "\n",
    "while True:\n",
    "    word = input(\"Please enter a word:\")\n",
    "    dummy = word\n",
    "    if word == \"\\end\":\n",
    "        print(\"Terminated!\")\n",
    "        break\n",
    "    elif dummy.lower() in data.keys():\n",
    "        dummy1 = dummy.lower()\n",
    "        output = data[dummy1]\n",
    "        print(output)\n",
    "    elif dummy.isnumeric():\n",
    "        print(\"Please enter a word, not a number\")\n",
    "        continue\n",
    "    elif (dummy.isalpha() == False):\n",
    "        print(\"Please enter a word containing only alphabets\")\n",
    "        continue\n",
    "    else:\n",
    "        dummy1 = []\n",
    "        dummy2 = []\n",
    "        for i in range(1,(len(word)+1)):\n",
    "            for j in list(data.keys()):\n",
    "                if j.startswith(word[:i]): #and (len(j) == len(word)):\n",
    "                    dummy1.append(j)\n",
    "            for k in list(data.keys()):\n",
    "                if k.endswith(word[-i::1]): #and (len(k) == len(word)):\n",
    "                    dummy2.append(k)\n",
    "        dummy3 = dummy1 + dummy2\n",
    "        lis3 = get_close_matches(dummy,dummy3)\n",
    "        print(\"Did you mean to type any of the below words?\\n\")\n",
    "        print(lis3)"
   ]
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    "#The next sequence creates a function that claculates the similarity score for two given strings.\n",
    "#The words must be entered as strings, with \" \", otherwise the function will return an error.\n",
    "#However, that will not be a problem for this particular application, since we are only using this function\n",
    "#inside the last for loop in the next code sequence.\n",
    "\n",
    "def similarity_score(w1,w2):\n",
    "    \"\"\"Takes two strings as arguments (include \" \" when writing input strings), and returns a similarity score\n",
    "    based on how many letters and positions match for those two input strings.\"\"\"\n",
    "    lis1 = []\n",
    "    lis2 = []\n",
    "    for l in w1:\n",
    "        lis1.append(l)\n",
    "    for m in w2:\n",
    "        lis2.append(m)\n",
    "    i = 0\n",
    "    if len(w1) < len(w2):\n",
    "        for n in range(len(w1)):\n",
    "            if lis1[n].lower() == lis2[n].lower():\n",
    "                i += 1\n",
    "        return i\n",
    "    else:\n",
    "        for n in range(len(w2)):\n",
    "            if lis1[n].lower() == lis2[n].lower():\n",
    "                i += 1\n",
    "        return i\n",
    "\n",
    "#This function is just for practice. Python has a built-in difflib with a SequenceMatcher function that does\n",
    "#a better job of claculating similarity ratio between strings.\n"
   ]
  },
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     "data": {
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       "4"
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   "source": [
    "similarity_score(\"keraaaatin\",\"Keratin\")"
   ]
  }
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