add content

Author: khuyentran1401

Chapter2/functools.ipynb

@@ -21,38 +21,69 @@
    "id": "0f82baff",
    "metadata": {},
    "source": [
-    "Dataclasses require manual implementation of validation.\n",
+    "Dataclasses require manual implementation of validation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "5b663960-6035-414d-87de-c3b61194ce1f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Validation error: Age must be a valid integer, unable to parse string as an integer\n"
+     ]
+    }
+   ],
+   "source": [
+    "from dataclasses import dataclass\n",
     "\n",
-    "On the other hand, Pydantic offers built-in validation that automatically validates data and provides informative error messages. This makes Pydantic particularly useful when working with data from external sources.\n"
+    "@dataclass\n",
+    "class Dog:\n",
+    "    name: str\n",
+    "    age: int\n",
+    "\n",
+    "    def __post_init__(self):\n",
+    "        if not isinstance(self.name, str):\n",
+    "            raise ValueError(\"Name must be a string\")\n",
+    "            \n",
+    "        try:\n",
+    "            self.age = int(self.age)\n",
+    "        except (ValueError, TypeError):\n",
+    "            raise ValueError(\"Age must be a valid integer, unable to parse string as an integer\")\n",
+    "\n",
+    "# Usage\n",
+    "try:\n",
+    "    dog = Dog(name=\"Bim\", age=\"ten\")\n",
+    "except ValueError as e:\n",
+    "    print(f\"Validation error: {e}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "719ee8e6-1035-457f-a04a-72117521f8e9",
+   "metadata": {},
+   "source": [
+    "On the other hand, Pydantic offers built-in validation that automatically validates data and provides informative error messages. This makes Pydantic particularly useful when working with data from external sources."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "id": "9bc629b5",
    "metadata": {},
    "outputs": [
     {
-     "ename": "ValidationError",
-     "evalue": "1 validation error for Dog\nage\n  Input should be a valid integer, unable to parse string as an integer [type=int_parsing, input_value='ten', input_type=str]\n    For further information visit https://errors.pydantic.dev/2.5/v/int_parsing",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n",
-      "\u001b[0;31mValidationError\u001b[0m                           Traceback (most recent call last)\n",
-      "Cell \u001b[0;32mIn[3], line 9\u001b[0m\n",
-      "\u001b[1;32m      5\u001b[0m     names: \u001b[38;5;28mstr\u001b[39m\n",
-      "\u001b[1;32m      6\u001b[0m     age: \u001b[38;5;28mint\u001b[39m\n",
-      "\u001b[0;32m----> 9\u001b[0m dog \u001b[38;5;241m=\u001b[39m \u001b[43mDog\u001b[49m\u001b[43m(\u001b[49m\u001b[43mnames\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mBim\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mage\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mten\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n",
-      "\n",
-      "File \u001b[0;32m~/book/venv/lib/python3.11/site-packages/pydantic/main.py:164\u001b[0m, in \u001b[0;36mBaseModel.__init__\u001b[0;34m(__pydantic_self__, **data)\u001b[0m\n",
-      "\u001b[1;32m    162\u001b[0m \u001b[38;5;66;03m# `__tracebackhide__` tells pytest and some other tools to omit this function from tracebacks\u001b[39;00m\n",
-      "\u001b[1;32m    163\u001b[0m __tracebackhide__ \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m\n",
-      "\u001b[0;32m--> 164\u001b[0m \u001b[43m__pydantic_self__\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m__pydantic_validator__\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mvalidate_python\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdata\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mself_instance\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m__pydantic_self__\u001b[49m\u001b[43m)\u001b[49m\n",
-      "\n",
-      "\u001b[0;31mValidationError\u001b[0m: 1 validation error for Dog\n",
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Validation error: 1 validation error for Dog\n",
       "age\n",
       "  Input should be a valid integer, unable to parse string as an integer [type=int_parsing, input_value='ten', input_type=str]\n",
-      "    For further information visit https://errors.pydantic.dev/2.5/v/int_parsing"
+      "    For further information visit https://errors.pydantic.dev/2.5/v/int_parsing\n"
      ]
     }
    ],
@@ -61,11 +92,13 @@
     "\n",
     "\n",
     "class Dog(BaseModel):\n",
-    "    names: str\n",
+    "    name: str\n",
     "    age: int\n",
     "\n",
-    "\n",
-    "dog = Dog(names=\"Bim\", age=\"ten\")"
+    "try:\n",
+    "    dog = Dog(name=\"Bim\", age=\"ten\")\n",
+    "except ValueError as e:\n",
+    "    print(f\"Validation error: {e}\")"
    ]
   },
   {
@@ -153,7 +186,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "venv",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },