dropblox/DropBlox_coding_competition.ipynb

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      "source": [
        "# PyData DropBlox coding competition 🧱\n",
        "This Notebook shows you how to generate submissions. The real optimization work is up to you! ✌🏻 \n",
        "\n",
        "> Hosted by [GoDataDriven](https://godatadriven.com/) for PyConDE & PyData Berlin 2022.\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "I193GlrrPshR"
      },
      "source": [
        "Import definitions"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "5nljvNsQM-S7"
      },
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      "source": [
        "from typing import List\n",
        "\n",
        "# Data types\n",
        "from common.data_models import (\n",
        "    Field,\n",
        "    Block,\n",
        "    Rewards,\n",
        "    Solution\n",
        ")\n",
        "\n",
        "# Puzzle helper functions\n",
        "from common.score_evaluation import (\n",
        "    parse_puzzle,\n",
        "    write_solution,\n",
        "    drop_block,\n",
        "    drop_blocks\n",
        ")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yJyvNoBPOpY-"
      },
      "source": [
        "Read puzzle specification file"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "id": "ZAimvAxqhrBy"
      },
      "outputs": [],
      "source": [
        "field: Field\n",
        "blocks: List[Block]\n",
        "rewards: Rewards\n",
        "field, blocks, rewards = parse_puzzle(\n",
        "    \"./puzzle.txt\"\n",
        ")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "d4gp3zhKPXaK"
      },
      "source": [
        "## Example submission"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CNWt46l4M5Yp"
      },
      "source": [
        "Check out the first block"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 24,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tSPKZgB3M3-H",
        "outputId": "18d7daf0-a1ac-46b3-8517-0ce51e5ff481"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "Block:\n",
              "🟧🟧🟧\n",
              "🟧⬜️🟧\n",
              "⬜️⬜️🟧"
            ]
          },
          "execution_count": 24,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "first_block = blocks[0]\n",
        "first_block"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TZbqsPNQM1UT"
      },
      "source": [
        "Drop it somewhere"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 25,
      "metadata": {
        "id": "2f_a4iRNN22F"
      },
      "outputs": [],
      "source": [
        "x = 0\n",
        "drop_block(field, first_block, x)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bJ9XuS4BOLX8"
      },
      "source": [
        "Check out the field"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Csf_Vs6RODGL",
        "outputId": "501e1dca-626f-4e31-c75b-4bcf4b0d0174"
      },
      "outputs": [],
      "source": [
        "field"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SBLSamhqP8rq"
      },
      "source": [
        "Create a solution object:\n",
        "\n",
        "→ Dropping block `0` at index `0`"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "2a0_-SciP8zG"
      },
      "outputs": [],
      "source": [
        "block_ids = [0]\n",
        "block_positions = [0]\n",
        "solution = Solution(block_ids=block_ids, block_positions=block_positions)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UPZHZj6aPyAS"
      },
      "source": [
        "## Writing the solution file"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iVlTISFZON1q"
      },
      "source": [
        "Write our solution to disk 💾"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Wis3JpFNMrl5"
      },
      "outputs": [],
      "source": [
        "write_solution(solution, \"solution.txt\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zEl-rw9yQ10E"
      },
      "source": [
        "Submit your solution 🎉  ! Upload at:\n",
        "\n",
        "[https://dropblox.azurewebsites.net/submit](https://dropblox.azurewebsites.net/submit)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## About\n",
        "> Competition hosted by [GoDataDriven](https://godatadriven.com/) for PyConDE & PyData Berlin 2022."
      ]
    }
  ],
  "metadata": {
    "colab": {
      "name": "PyData DropBlox coding competition",
      "provenance": []
    },
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