ETH-Map_to_(x,y,z,w).ipynb

eth-map_to_-x-y-z-w.ipynb

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  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyNsGdBEi/nlOHMsCJkhwUW3",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/gist/CY0xZ/227b3d01616ba55205040dfb45dc6b3c/eth-map_to_-x-y-z-w.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pip install matplotlib numpy"
      ],
      "metadata": {
        "id": "YfGHKFmuAkjt"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "pip install eth_keys"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2m1_ZkZCCz-2",
        "outputId": "201a5a1d-32c7-45a8-e558-ce8c3ba546cb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting eth_keys\n",
            "  Downloading eth_keys-0.4.0-py3-none-any.whl (21 kB)\n",
            "Collecting eth-utils<3.0.0,>=2.0.0 (from eth_keys)\n",
            "  Downloading eth_utils-2.2.0-py3-none-any.whl (23 kB)\n",
            "Collecting eth-typing<4,>=3.0.0 (from eth_keys)\n",
            "  Downloading eth_typing-3.4.0-py3-none-any.whl (6.0 kB)\n",
            "Collecting eth-hash>=0.3.1 (from eth-utils<3.0.0,>=2.0.0->eth_keys)\n",
            "  Downloading eth_hash-0.5.2-py3-none-any.whl (8.6 kB)\n",
            "Collecting cytoolz>=0.10.1 (from eth-utils<3.0.0,>=2.0.0->eth_keys)\n",
            "  Downloading cytoolz-0.12.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.9 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.9/1.9 MB\u001b[0m \u001b[31m22.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: toolz>=0.8.0 in /usr/local/lib/python3.10/dist-packages (from cytoolz>=0.10.1->eth-utils<3.0.0,>=2.0.0->eth_keys) (0.12.0)\n",
            "Installing collected packages: eth-typing, eth-hash, cytoolz, eth-utils, eth_keys\n",
            "Successfully installed cytoolz-0.12.2 eth-hash-0.5.2 eth-typing-3.4.0 eth-utils-2.2.0 eth_keys-0.4.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pip install eth-hash[pycryptodome]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jCNslC6rDGFg",
        "outputId": "5e3b78aa-e406-4567-eea4-f0975285f898"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: eth-hash[pycryptodome] in /usr/local/lib/python3.10/dist-packages (0.5.2)\n",
            "Collecting pycryptodome<4,>=3.6.6 (from eth-hash[pycryptodome])\n",
            "  Downloading pycryptodome-3.18.0-cp35-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.1 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.1/2.1 MB\u001b[0m \u001b[31m12.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hInstalling collected packages: pycryptodome\n",
            "Successfully installed pycryptodome-3.18.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from eth_keys import keys\n",
        "from eth_utils import decode_hex\n",
        "import os\n",
        "import hashlib # for SHA256 computation\n",
        "import binascii # for conversion between Hexa and bytes\n",
        "\n",
        "def EntropyHex(z):\n",
        "    entropy = binascii.b2a_hex(os.urandom(z))\n",
        "    data = entropy.strip() # cleaning of data\n",
        "    data = binascii.unhexlify(data)\n",
        "    h = hashlib.sha256(data).hexdigest()\n",
        "    return h , entropy\n",
        "\n",
        "random_key, entropy = EntropyHex(1)\n",
        "priv_key_bytes = decode_hex('0x'+random_key)\n",
        "priv_key = keys.PrivateKey(priv_key_bytes)\n",
        "pub_key = priv_key.public_key\n",
        "address = pub_key.to_checksum_address()\n",
        "\n",
        "print(\"Entropy:\",entropy)\n",
        "print(\"Random Key Generated:\",random_key)\n",
        "print(\"Private Key:\", priv_key)\n",
        "print(\"Public Key:\", pub_key)\n",
        "print(\"Public Address:\", pub_key.to_checksum_address())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9vMz9kNyC_pd",
        "outputId": "e3c9cee5-e9d4-4c83-d20b-f193967aece7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Entropy: b'4c65'\n",
            "Random Key Generated: a2fbc754b9ee1dc5a793eeb2c804c5e6cf962f680909050f28a69b6cdfdbab89\n",
            "Private Key: 0xa2fbc754b9ee1dc5a793eeb2c804c5e6cf962f680909050f28a69b6cdfdbab89\n",
            "Public Key: 0x4f346907855e391838890db8c1f5336378af65d7e8a4332066819a53c3d1998bddc3ecc49807b55a3b700096669dbaf5948481e22baa49f2ae9f39e8427b3764\n",
            "Public Address: 0x2801F56FDbA197Cb74e5dc2C73de2337012Ff0dB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "address = []\n",
        "for i in range(0,50):\n",
        "    random_key, entropy = EntropyHex(1)\n",
        "    address.append(keys.PrivateKey(decode_hex('0x'+random_key)).public_key.to_checksum_address())\n",
        "\n",
        "unique_list = list(filter(lambda x: address.count(x) == 1, address))\n",
        "print(unique_list)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lh-E2b7TDwQK",
        "outputId": "394f4678-ce13-4786-b96b-266afad25bd0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['0x71e6792c8c6C3AA0539386a2368d467fF9185F6d', '0xE7Dd8b8040e432D1a673De8910Fbc86e6ABf2Cae', '0xfCD843F026BE772168f85Fe59F6777f5d7BEe389', '0xD04769704aEa6F04Bec733824243272E4604314C', '0xe8cbB5cBfe751D03594b6DabDE3b6eAc314B62b1', '0x00CbD387D6A0Ed2f8023535cC40Dc316E5fe3773', '0x3068e228881bA162dd7717cCeBD7C654390224F7', '0x7E7096ac23b7313373f7836B3951B958efbb0393', '0x09B8ba91CC920c871d5777D0822194878b3316d8', '0x24677108f5eE0Cc83c71a205400bB28cBB29E278', '0x355Baad8218F406a92E9411AbDe1d2072f68bA10', '0x6Ea943A1B3D0895cef2308d33753357b19c6fD65', '0xA9669faD8635802929AEcFC6268eB11d82512882', '0xEbe4cd59c6E7f24298668BDe297B8aa69512c3dA', '0x3B3e82c90cdc6547131d36bb2725ada21858E402', '0x1C2AA8a9fD317A8c35460a292011F2810a8cd72c', '0x2B8a9F70eE74655369109b3AFd2029Ae7eb53ecD', '0xC2bea3646CA916854F3e61E8bFD7cdc15a51A5B9', '0x6AA7d0124212711037bF5a9408a81d5ee00725df', '0x73B2f206d9001b5bA91CAC02d679502bd718b62A', '0x6B63EC054421fEB50a0448AC78b592370EcEAE4d', '0x312Fe1DE91a914B678791ec56d4C60A20Ab7ADb3', '0xd428d086f75910707075F4400240F4D9447cc045', '0x09d1C1e0C01f5E8dd2e356CE762799F42c5571e3', '0x0E1e4E68668386c3025A8b22B44caeC8D075F26d', '0x0D0A8bC550cf3BD2AA4bcACC19f95C411E5Dcc3f', '0xedECC9A6bDA5F86A7845AFE69D77F2224665A7e2', '0x66A4E3e0E2B8498FDEE14Ca5bB2B76ED159D120d', '0xa9AcddFACfE4c584173840c631FFC011397449b0', '0x3e40068ceDbD68C2E7f414B2f8B923Dfaea5bd8e', '0x6578F2CEB06344F84024718e5C538D4698032400', '0x63082dD7391Fd6931C90D0a4d9Bc47905EbaDccd', '0xf9FCF1640A410f5969Cba0E8200BB24432D2fF1d', '0x89fAD245c3f0Ff67BE3b75ae3BB0d2f6ddcC25cD', '0x781A78526649d93334e5f1f98D5Cf86044828A5E', '0x2d32Fb4D8B570A753d73206f5f3F4be0381dEf22', '0x8d362265D763Ac90aC94DC7e90DEc2A5E53387cA', '0xd360E8C5D2dBD9EA200C81d92151BB4F97Db2d1C', '0xF104710dE37B1E6265c4cF51320B5ef22bc12947', '0x59BE6f2cD0dB9315Dedf8412db51268A85a82c9F', '0x57FBf5B8228a3992A77b3770733dBCdad397e071', '0xD83344F19067ae27CAb506e4D91EB97C69859cf7', '0xc3711A952222F061cE364172D8865e7F3B1949FE', '0x63eE8f6ebf2397261ac71dE57ADe3dFE2Bf42FB8']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "from mpl_toolkits.mplot3d import Axes3D\n",
        "import numpy as np\n",
        "\n",
        "def convert_hex_to_number(hex_string):\n",
        "    return int(hex_string, 16)\n",
        "\n",
        "def map_to_coordinates(hex_address):\n",
        "    num1 = convert_hex_to_number(hex_address[2:12])\n",
        "    num2 = convert_hex_to_number(hex_address[12:22])\n",
        "    num3 = convert_hex_to_number(hex_address[22:32])\n",
        "    num4 = convert_hex_to_number(hex_address[32:42])\n",
        "\n",
        "    x = num1 / 0xFFFFFFFFFFFFFFFFFFFF\n",
        "    y = num2 / 0xFFFFFFFFFFFFFFFFFFFF\n",
        "    z = num3 / 0xFFFFFFFFFFFFFFFFFFFF\n",
        "    w = num4 / 0xFFFFFFFFFFFFFFFFFFFF\n",
        "\n",
        "    return x, y, z, w\n",
        "\n",
        "def map_to_3d_coordinates(x, y, z, w):\n",
        "    return (x + y) * np.cos(w), (x - y) * np.sin(w), z\n",
        "\n",
        "def main():\n",
        "\n",
        "    fig = plt.figure()\n",
        "    ax = fig.add_subplot(111, projection='3d')\n",
        "\n",
        "    ethereum_addresses = [\n",
        "\n",
        "        \"0x123456789abcdefABCDEF123456789abcdefABCDEF\",\n",
        "        \"0xABCDEF123456789abcdefABCDEF123456789abcdef\",\n",
        "        \"0x9876543210fedcbaFEDCBA9876543210fedcbaFED\",\n",
        "        \"0xFEDCBA9876543210fedcbaFEDCBA9876543210fed\",\n",
        "        \"0x000000000000000000000000000000000000000000\"\n",
        "    ]\n",
        "\n",
        "    for i in range(len(ethereum_addresses)):\n",
        "\n",
        "        x, y, z, w = map_to_coordinates(ethereum_addresses[i])\n",
        "        # Mapear coordenadas 4D a 3D\n",
        "        x_3d, y_3d, z_3d = map_to_3d_coordinates(x, y, z, w)\n",
        "        ax.scatter(x_3d, y_3d, z_3d, c='b', marker='o', alpha=0.3)\n",
        "\n",
        "    ax.set_xlabel('X Label')\n",
        "    ax.set_ylabel('Y Label')\n",
        "    ax.set_zlabel('Z Label')\n",
        "    plt.legend()\n",
        "    plt.show()\n",
        "\n",
        "if __name__ == \"__main__\":\n",
        "    main()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 413
        },
        "id": "PnE-WM8E8C8R",
        "outputId": "9f934b16-029d-437e-ba9b-c7ac6b9a7d2c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "Ch85R1cCFX5D"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}