Criado usando o Colab

metsumesquita · metsumesquita · commit aaabbdf93c62 · 2024-09-17T23:22:07.000-03:00
diff --git a/ESTUDO_DE_PYTHON_.ipynb b/ESTUDO_DE_PYTHON_.ipynb
@@ -3,10 +3,11 @@
     {
       "cell_type": "markdown",
       "metadata": {
-        "id": "view-in-github"
+        "id": "view-in-github",
+        "colab_type": "text"
       },
       "source": [
-        "<a href=\"https://colab.research.google.com/github/metsumesquita/Python_resumo/blob/main/ESTUDO_DE_PYTHON.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+        "<a href=\"https://colab.research.google.com/github/metsumesquita/Python_resumo/blob/main/ESTUDO_DE_PYTHON_.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
       ]
     },
     {
@@ -32,7 +33,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 3,
+      "execution_count": null,
       "metadata": {
         "id": "fnjTKFkCu0nx"
       },
@@ -43,7 +44,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 4,
+      "execution_count": null,
       "metadata": {
         "id": "llWCVCCyS2DW"
       },
@@ -1132,13 +1133,6 @@
         "print(elevar)"
       ]
     },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "QyuPhr8rAaS-"
-      },
-      "source": []
-    },
     {
       "cell_type": "code",
       "execution_count": null,
@@ -1683,6 +1677,59 @@
         "#esse o ano é bissexto"
       ]
     },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "##numeros interios ou float"
+      ],
+      "metadata": {
+        "id": "H58t1a6Vumv_"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "\n",
+        "numero =input(\"infome um numero qualquer\")\n",
+        "divisor= input(\"informe um valor para dividir o numero qualquer que voce informou\")\n",
+        "\n",
+        "if numero%divisor==0 :\n",
+        "    print(\"Este número: \" + str(numero) + \" é divisível por \" + str(divisor))\n",
+        "else :\n",
+        "     print(\"este numero: \" + str(numero) + \" não divisivel por \" + str(divisor))\n",
+        "\n"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 245
+        },
+        "id": "csMaEnRMuy7i",
+        "outputId": "8e5a0bdb-1175-46c5-8f57-b92ab0c14349"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "infome um numero qualquer30\n",
+            "informe um valor para dividir o numero qualquer que voce informou3\n"
+          ]
+        },
+        {
+          "output_type": "error",
+          "ename": "TypeError",
+          "evalue": "not all arguments converted during string formatting",
+          "traceback": [
+            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+            "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
+            "\u001b[0;32m<ipython-input-19-414d8d89e0c1>\u001b[0m in \u001b[0;36m<cell line: 4>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0mdivisor\u001b[0m\u001b[0;34m=\u001b[0m \u001b[0minput\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"informe um valor para dividir o numero qualquer que voce informou\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0;32mif\u001b[0m \u001b[0mnumero\u001b[0m\u001b[0;34m%\u001b[0m\u001b[0mdivisor\u001b[0m\u001b[0;34m==\u001b[0m\u001b[0;36m0\u001b[0m \u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      5\u001b[0m     \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Este número: \"\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnumero\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;34m\" é divisível por \"\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdivisor\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0;32melse\u001b[0m \u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+            "\u001b[0;31mTypeError\u001b[0m: not all arguments converted during string formatting"
+          ]
+        }
+      ]
+    },
     {
       "cell_type": "markdown",
       "metadata": {
@@ -3052,9 +3099,27 @@
         "id": "s0b6x1-XRSa9"
       },
       "source": [
-        "#FIFO FALTA"
+        "#FIFO (First In, First Out) FALTA\n",
+        "####não necessamente é uma lista\n",
+        "\n",
+        "\n",
+        "FALTAAA"
       ]
     },
+    {
+      "cell_type": "code",
+      "source": [
+        "# https://www.otaviomiranda.com.br/2020/filas-em-python-com-deque-queue/\n",
+        "#https://www.oreilly.com/library/view/python-cookbook/0596001673/ch17s15.html\n",
+        "# https://medium.com/@khasnobis.sanjit890/linear-data-structure-queue-in-python-fifo-first-in-first-out-bbd03f6b3b0f\n",
+        "#https://www.simplilearn.com/tutorials/python-tutorial/queue-in-python#:~:text=Python%20list%20is%20used%20as,to%20maintain%20the%20FIFO%20manner."
+      ],
+      "metadata": {
+        "id": "FOOPAX0gaaTK"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
     {
       "cell_type": "markdown",
       "metadata": {
@@ -3622,7 +3687,7 @@
         "#modificamos o parametro que quebra do nosso string\n",
         "def get_mail(string):\n",
         "    li = list(string.split(\"@\"))\n",
-        "    #pegamos a 2 parte da saber o tipo da fonte de email \n",
+        "    #pegamos a 2 parte da saber o tipo da fonte de email\n",
         "    return li[1]\n",
         "   #retornamos o tipo\n",
         "\n",
@@ -3638,7 +3703,9 @@
     {
       "cell_type": "code",
       "execution_count": null,
-      "metadata": {},
+      "metadata": {
+        "id": "Kj2CB7vxXYnM"
+      },
       "outputs": [],
       "source": [
         "# Definição do dicionário de produtos e listas de itens\n",
@@ -3692,7 +3759,7 @@
         "        return i\n",
         "    else:\n",
         "        return -1\n",
-        "    \n",
+        "\n",
         "# Função para calcular o preço da bebida com base na quantidade\n",
         "def calcular_preço_bebida(posição):\n",
         "    qtd = int(input(\"Informe a quantidade do item que você deseja: \"))\n",
@@ -3720,7 +3787,7 @@
         "        print(f\"O valor total para {escolhido} é: R${totalB:.2f}\")\n",
         "    else:\n",
         "        print(\"Item não encontrado na lista de bebidas.\")\n",
-        "        \n",
+        "\n",
         "elif opçãolista == 2:\n",
         "    escolhido = input(\"Informe por escrito qual o nome do item selecionado: \")\n",
         "    posição = itemPosiçãoC(escolhido)\n",
@@ -3957,6 +4024,15 @@
         "np.linspace(0., 8., 6)\n"
       ]
     },
+    {
+      "cell_type": "code",
+      "source": [],
+      "metadata": {
+        "id": "HkHS5NkFhk_Y"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
     {
       "cell_type": "code",
       "execution_count": null,
@@ -4920,6 +4996,109 @@
         "    return \"<p>Hello, World!</p>\""
       ]
     },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "REDES NEURAIS\n",
+        "https://medium.com/geekculture/understanding-the-basics-of-neural-networks-for-beginners-9c26630d08\n",
+        "https://machinelearningmastery.com/implement-perceptron-algorithm-scratch-python/\n",
+        "https://www.simplilearn.com/tutorials/deep-learning-tutorial/neural-network\n"
+      ],
+      "metadata": {
+        "id": "iON51fPHBCH6"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [],
+      "metadata": {
+        "id": "Bwkt1psWBCej"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [],
+      "metadata": {
+        "id": "SW9Hr3hXBDDz"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [],
+      "metadata": {
+        "id": "AmP6Vwk5BC1K"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "#criando arquivos aparti deste"
+      ],
+      "metadata": {
+        "id": "veL3Yb0oZFYO"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "import nbformat\n",
+        "\n",
+        "# Caminho para o arquivo do notebook\n",
+        "file_path = \"/mnt/data/ESTUDO_DE_PYTHON_.ipynb\"\n",
+        "\n",
+        "# Carregando o notebook\n",
+        "with open(file_path, \"r\", encoding=\"utf-8\") as file:\n",
+        "    notebook = nbformat.read(file, as_version=4)\n",
+        "\n",
+        "# Verificando as seções (células) do notebook\n",
+        "notebook_cells = notebook.cells\n",
+        "len(notebook_cells), notebook_cells[0], notebook_cells[-1]\n"
+      ],
+      "metadata": {
+        "id": "BUXq77YdZIvd"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "# Função para criar um novo notebook com um subconjunto de células\n",
+        "def create_notebook(cells, path):\n",
+        "    new_notebook = nbformat.v4.new_notebook()\n",
+        "    new_notebook.cells = cells\n",
+        "    with open(path, 'w', encoding='utf-8') as f:\n",
+        "        nbformat.write(new_notebook, f)\n",
+        "\n",
+        "# Dividindo as células em três partes\n",
+        "part1_cells = notebook_cells[:76]\n",
+        "part2_cells = notebook_cells[76:152]\n",
+        "part3_cells = notebook_cells[152:]\n",
+        "\n",
+        "# Caminhos para os novos arquivos\n",
+        "part1_path = \"/mnt/data/ESTUDO_DE_PYTHON_part1.ipynb\"\n",
+        "part2_path = \"/mnt/data/ESTUDO_DE_PYTHON_part2.ipynb\"\n",
+        "part3_path = \"/mnt/data/ESTUDO_DE_PYTHON_part3.ipynb\"\n",
+        "\n",
+        "# Criando os novos notebooks\n",
+        "create_notebook(part1_cells, part1_path)\n",
+        "create_notebook(part2_cells, part2_path)\n",
+        "create_notebook(part3_cells, part3_path)\n",
+        "\n",
+        "part1_path, part2_path, part3_path\n"
+      ],
+      "metadata": {
+        "id": "ihVx3DA-ZL8E"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
     {
       "cell_type": "markdown",
       "metadata": {
@@ -5007,7 +5186,7 @@
   "metadata": {
     "colab": {
       "provenance": [],
-      "toc_visible": true
+      "include_colab_link": true
     },
     "kernelspec": {
       "display_name": "Python 3",
@@ -5028,4 +5207,4 @@
   },
   "nbformat": 4,
   "nbformat_minor": 0
-}
+}
