dynamic_arrays.ipynb

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  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "source": [
        "import ctypes\n",
        "# to create C type ka array"
      ],
      "metadata": {
        "id": "QZ5u8mep3z4q"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "class MeraList:\n",
        "\n",
        "  def __init__(self):\n",
        "    self.size = 1\n",
        "    self.n = 0\n",
        "    # create a C type ka array with size -> self.size\n",
        "    self.A = self.__make_array(self.size)\n",
        "\n",
        "  def __len__(self):\n",
        "    return self.n\n",
        "\n",
        "  def append(self,item):\n",
        "    # check if vacant\n",
        "    if self.n == self.size:\n",
        "      # array is full -> resize\n",
        "      self.__resize(self.size*2)\n",
        "\n",
        "    self.A[self.n] = item\n",
        "    self.n = self.n + 1\n",
        "\n",
        "  def pop(self):\n",
        "    if self.n == 0:\n",
        "      return 'Empty List'\n",
        "    print(self.A[self.n-1])\n",
        "    self.n = self.n - 1\n",
        "\n",
        "  def clear(self):\n",
        "    self.n = 0\n",
        "    self.size = 1\n",
        "\n",
        "  def find(self,item):\n",
        "\n",
        "    for i in range(self.n):\n",
        "      if self.A[i] == item:\n",
        "        return i\n",
        "    return 'ValueError - not in list'\n",
        "\n",
        "  def insert(self,pos,item):\n",
        "\n",
        "    if self.n == self.size:\n",
        "      self.__resize(self.size*2)\n",
        "\n",
        "    for i in range(self.n,pos,-1):\n",
        "      self.A[i] = self.A[i-1]\n",
        "\n",
        "    self.A[pos] = item\n",
        "    self.n = self.n + 1\n",
        "\n",
        "  def remove(self,item):\n",
        "    # search and get pos\n",
        "    pos = self.find(item)\n",
        "    if type(pos) == int:\n",
        "      # delete\n",
        "      self.__delitem__(pos)\n",
        "    else:\n",
        "      return pos\n",
        "\n",
        "  def __resize(self,new_capacity):\n",
        "    # create a new array with new capacity\n",
        "    B = self.__make_array(new_capacity)\n",
        "    self.size = new_capacity\n",
        "    # copy the content of old array to new one\n",
        "    for i in range(self.n):\n",
        "      B[i] = self.A[i]\n",
        "    # reassign A\n",
        "    self.A = B\n",
        "\n",
        "  def __str__(self):\n",
        "    result = ''\n",
        "    for i in range(self.n):\n",
        "      result = result + str(self.A[i]) + ','\n",
        "\n",
        "    return '[' + result[:-1] + ']'\n",
        "\n",
        "  def __getitem__(self,index):\n",
        "\n",
        "    if 0<= index < self.n:\n",
        "      return self.A[index]\n",
        "    else:\n",
        "      return 'IndexError'\n",
        "\n",
        "  def __delitem__(self,pos):\n",
        "    # delete pos wala item\n",
        "    if 0<= pos < self.n:\n",
        "      for i in range(pos,self.n-1):\n",
        "        self.A[i] = self.A[i+1]\n",
        "\n",
        "      self.n = self.n - 1\n",
        "\n",
        "  def __make_array(self,capacity):\n",
        "    # referential array(C type)\n",
        "    return (capacity*ctypes.py_object)()"
      ],
      "metadata": {
        "id": "FJ_5iTUh4Jcv"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "L = MeraList()"
      ],
      "metadata": {
        "id": "0dr0QIug5WXt"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "L.append(1)\n",
        "L.append('hello')\n",
        "L.append(False)\n",
        "L.append(4.5)"
      ],
      "metadata": {
        "id": "kRiwtEgJ5Y5l"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(L)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JrdjNFWC8Wbn",
        "outputId": "170821bd-8d0f-4016-aa9d-f064cb270e64"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[1,False]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "L.remove(4.5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "WbFSLfpy8tK-",
        "outputId": "75daf089-3d0c-4d19-8f49-7930d70e06af"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'ValueError - not in list'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 175
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "L = [10,20,30]\n",
        "L"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "eFiGLQqB5emG",
        "outputId": "e3000a0e-d9d7-4018-f312-84ad7288287f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[10, 20, 30]"
            ]
          },
          "metadata": {},
          "execution_count": 161
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "L.remove(200)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 168
        },
        "id": "PdLotNNm5vo7",
        "outputId": "51db0c71-0370-4d25-cdac-955b50c6ff0f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "ValueError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-166-94e77ffffe0d>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mL\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mremove\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m200\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;31mValueError\u001b[0m: list.remove(x): x not in list"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "L"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AO7K_n7-5wxT",
        "outputId": "737f3c40-e31a-4b0c-9920-b369e77b2625"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[10]"
            ]
          },
          "metadata": {},
          "execution_count": 165
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "JtTWvkXL-6za"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}