Autocorrect python file

Autocorrect/autocorrectreal.ipynb

@@ -1,131 +0,0 @@
-{
-  "cells": [
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "wOvxbAShg-_s",
-        "outputId": "0e9a0f9a-fd6e-4ce0-81f6-8da736bd06be"
-      },
-      "outputs": [],
-      "source": [
-        "from google.colab import drive\n",
-        "drive.mount('/content/drive')"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "THLGsHmchJ9g",
-        "outputId": "d590fb47-7b15-4176-9b6e-719090ed2cbd"
-      },
-      "outputs": [],
-      "source": [
-        "!pip install textdistance"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "eFxAvy03hPCX"
-      },
-      "outputs": [],
-      "source": [
-        "import re\n",
-        "from collections import Counter\n",
-        "import numpy as np\n",
-        "import pandas as pd\n",
-        "import textdistance\n",
-        "\n",
-        "w = []\n",
-        "with open('/content/drive/MyDrive/words.txt', 'r') as f:\n",
-        "  file_name_data = f.read()\n",
-        "  file_name_data = file_name_data.lower()\n",
-        "  w = re.findall('\\w+', file_name_data)\n",
-        "\n",
-        "v = set(w)"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "RPON8Pm7h9Dx",
-        "outputId": "dd1309fd-3362-41c9-8f19-affe4739df3e"
-      },
-      "outputs": [],
-      "source": [
-        "print(f\"First 10 words: \\n{w[0:10]}\")\n",
-        "print(f\"{len(v)} total words \")"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "U4s_UDWKig11"
-      },
-      "outputs": [],
-      "source": [
-        "from nltk.metrics.distance import edit_distance\n",
-        "def edit(input_sentence):\n",
-        "  sentence = input_sentence.split()\n",
-        "  \n",
-        "  for i in sentence:\n",
-        "    if i.lower() in w:\n",
-        "      continue\n",
-        "    else:\n",
-        "      distances = ((edit_distance(i,\n",
-        "                                    word), word)\n",
-        "                     for word in w)\n",
-        "      closest = min(distances)\n",
-        "      sentence[sentence.index(i)] = closest[1]\n",
-        "  output_sentence = ' '.join(sentence)\n",
-        "\n",
-        "  return output_sentence"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "c0af01o_i5X0",
-        "outputId": "fff4600b-163d-40c8-ce3b-c0b735ec286e"
-      },
-      "outputs": [],
-      "source": [
-        "print(edit(\"My namee is  uncele Steven\"))\n",
-        "print(edit(\"moneeyeh is greeat\"))"
-      ]
-    }
-  ],
-  "metadata": {
-    "colab": {
-      "name": "autocorrectreal.ipynb",
-      "provenance": []
-    },
-    "kernelspec": {
-      "display_name": "Python 3",
-      "name": "python3"
-    },
-    "language_info": {
-      "name": "python"
-    }
-  },
-  "nbformat": 4,
-  "nbformat_minor": 0
-}

Autocorrect/autocorrectreal.py

@@ -0,0 +1,47 @@
+# -*- coding: utf-8 -*-
+"""autocorrectreal.ipynb
+
+Automatically generated by Colaboratory.
+
+Original file is located at
+    https://colab.research.google.com/drive/1aH5mYp1dxyn55XMjtVUllBvg37nqGVir
+"""
+
+from google.colab import drive
+drive.mount('/content/drive')
+
+!pip install textdistance
+
+import re
+from collections import Counter
+import numpy as np
+import pandas as pd
+import textdistance
+
+w = []
+with open('/content/drive/MyDrive/words.txt', 'r') as f:
+  file_name_data = f.read()
+  file_name_data = file_name_data.lower()
+  w = re.findall('\w+', file_name_data)
+
+print(f"First 10 words: \n{w[0:10]}")
+print(f"{len(w)} total words ")
+
+from nltk.metrics.distance import edit_distance
+def edit(input_sentence):
+  sentence = input_sentence.split()
+  
+  for i in sentence:
+    if i.lower() in w:
+      continue
+    else:
+      distances = ((edit_distance(i,word),word)for word in w)
+      closest = min(distances)
+      sentence[sentence.index(i)] = closest[1]
+  output_sentence = ' '.join(sentence)
+
+  return output_sentence
+
+print(edit("My namee is uncele sdtevven"))
+print(edit("moneeyeh is greeat"))
+print(edit("establishe that nitrgen is theh essentil vegchtable as of animal living matter"))