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add pydantic number constraint
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‎Chapter2/dataclasses.ipynb

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"if not isinstance(dog.age, int):\n",
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" raise ValueError(\"Dog's age must be an integer.\")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "addd6347",
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"metadata": {},
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"source": [
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"### Simplify Data Validation with Pydantic"
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]
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},
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{
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"cell_type": "markdown",
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"id": "e4bb3a40",
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"metadata": {},
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"source": [
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"Dataclasses require manual implementation of validation.\n",
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"\n",
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"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"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "3aaa4b09",
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"metadata": {},
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"outputs": [
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{
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"ename": "ValidationError",
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"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",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mValidationError\u001b[0m Traceback (most recent call last)",
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"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",
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"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",
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"\u001b[0;31mValidationError\u001b[0m: 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"
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]
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}
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],
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"source": [
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"from pydantic import BaseModel\n",
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"\n",
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"\n",
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"class Dog(BaseModel):\n",
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" names: str\n",
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" age: int\n",
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"\n",
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"\n",
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"dog = Dog(names=\"Bim\", age=\"ten\")"
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]
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}
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],
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"metadata": {

‎Chapter2/pydantic.ipynb

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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "3569bdc8",
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"metadata": {},
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"source": [
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"## Pydantic"
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]
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},
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{
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"cell_type": "markdown",
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"id": "ada65a73",
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"metadata": {},
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"source": [
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"### Simplify Data Validation with Pydantic"
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]
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},
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{
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"cell_type": "markdown",
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"id": "0f82baff",
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"metadata": {},
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"source": [
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"Dataclasses require manual implementation of validation.\n",
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"\n",
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"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"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "9bc629b5",
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"metadata": {},
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"outputs": [
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{
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"ename": "ValidationError",
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"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",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n",
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"\u001b[0;31mValidationError\u001b[0m Traceback (most recent call last)\n",
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"Cell \u001b[0;32mIn[3], line 9\u001b[0m\n",
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"\u001b[1;32m 5\u001b[0m names: \u001b[38;5;28mstr\u001b[39m\n",
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"\u001b[1;32m 6\u001b[0m age: \u001b[38;5;28mint\u001b[39m\n",
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"\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",
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"\n",
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"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",
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"\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",
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"\u001b[1;32m 163\u001b[0m __tracebackhide__ \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m\n",
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"\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",
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"\n",
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"\u001b[0;31mValidationError\u001b[0m: 1 validation error for Dog\n",
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"age\n",
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" Input should be a valid integer, unable to parse string as an integer [type=int_parsing, input_value='ten', input_type=str]\n",
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" For further information visit https://errors.pydantic.dev/2.5/v/int_parsing"
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]
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}
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],
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"source": [
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"from pydantic import BaseModel\n",
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"\n",
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"\n",
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"class Dog(BaseModel):\n",
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" names: str\n",
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" age: int\n",
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"\n",
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"\n",
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"dog = Dog(names=\"Bim\", age=\"ten\")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "15dd5037",
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"metadata": {},
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"source": [
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"### Use Pydantic's Field Class to Validate Numbers and Dates"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "eb27ed75",
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"metadata": {
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"tags": [
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"hide-cell"
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]
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},
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"outputs": [],
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"source": [
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"!pip install pydantic"
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]
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},
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{
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"cell_type": "markdown",
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"id": "082a6675",
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"metadata": {},
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"source": [
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"In addition to checking the type, you may also want to check if numbers and dates match specific constraints. Pydantic's Field class provides keyword arguments that make this easy."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "49c502e7",
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"metadata": {},
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"outputs": [
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{
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"ename": "ValidationError",
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"evalue": "2 validation errors for Song\nrelease_date\n Input should be less than 2024-05-10 [type=less_than, input_value=datetime.date(2024, 6, 1), input_type=date]\n For further information visit https://errors.pydantic.dev/2.5/v/less_than\nbeats_per_minute\n Field required [type=missing, input_value={'title': 'Believer', 'ar...2024, 6, 1), 'bpm': 125}, input_type=dict]\n For further information visit https://errors.pydantic.dev/2.5/v/missing",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mValidationError\u001b[0m Traceback (most recent call last)",
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"Cell \u001b[0;32mIn[1], line 14\u001b[0m\n\u001b[1;32m 10\u001b[0m beats_per_minute: \u001b[38;5;28mint\u001b[39m \u001b[38;5;241m=\u001b[39m Field(multiple_of\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m5\u001b[39m)\n\u001b[1;32m 13\u001b[0m \u001b[38;5;66;03m# Example usage\u001b[39;00m\n\u001b[0;32m---> 14\u001b[0m song1 \u001b[38;5;241m=\u001b[39m \u001b[43mSong\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 15\u001b[0m \u001b[43m \u001b[49m\u001b[43mtitle\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mBeliever\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 16\u001b[0m \u001b[43m \u001b[49m\u001b[43martist\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mImagine Dragons\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 17\u001b[0m \u001b[43m \u001b[49m\u001b[43mduration\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m3.67\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 18\u001b[0m \u001b[43m \u001b[49m\u001b[43mrelease_date\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdate\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m2024\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m6\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 19\u001b[0m \u001b[43m \u001b[49m\u001b[43mbpm\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m125\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 20\u001b[0m \u001b[43m)\u001b[49m\n",
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"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",
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"\u001b[0;31mValidationError\u001b[0m: 2 validation errors for Song\nrelease_date\n Input should be less than 2024-05-10 [type=less_than, input_value=datetime.date(2024, 6, 1), input_type=date]\n For further information visit https://errors.pydantic.dev/2.5/v/less_than\nbeats_per_minute\n Field required [type=missing, input_value={'title': 'Believer', 'ar...2024, 6, 1), 'bpm': 125}, input_type=dict]\n For further information visit https://errors.pydantic.dev/2.5/v/missing"
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]
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}
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],
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"source": [
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"from pydantic import BaseModel, Field\n",
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"from datetime import date\n",
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"\n",
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"\n",
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"class Song(BaseModel):\n",
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" title: str\n",
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" artist: str\n",
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" duration: float = Field(gt=0.0)\n",
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" release_date: date = Field(lt=date.today())\n",
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" beats_per_minute: int = Field(multiple_of=5)\n",
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"\n",
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"\n",
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"song1 = Song(\n",
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" title=\"Believer\",\n",
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" artist=\"Imagine Dragons\",\n",
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" duration=3.67,\n",
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" release_date=date(2024, 6, 1), \n",
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" bpm=125,\n",
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")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "d05c1ff0",
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"metadata": {},
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"outputs": [
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{
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"ename": "ValidationError",
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"evalue": "2 validation errors for Song\nduration\n Input should be greater than 0 [type=greater_than, input_value=0, input_type=int]\n For further information visit https://errors.pydantic.dev/2.5/v/greater_than\nbeats_per_minute\n Field required [type=missing, input_value={'title': 'Thunder', 'art...017, 4, 27), 'bpm': 165}, input_type=dict]\n For further information visit https://errors.pydantic.dev/2.5/v/missing",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mValidationError\u001b[0m Traceback (most recent call last)",
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"Cell \u001b[0;32mIn[2], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m song2 \u001b[38;5;241m=\u001b[39m \u001b[43mSong\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 2\u001b[0m \u001b[43m \u001b[49m\u001b[43mtitle\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mThunder\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 3\u001b[0m \u001b[43m \u001b[49m\u001b[43martist\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mImagine Dragons\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 4\u001b[0m \u001b[43m \u001b[49m\u001b[43mduration\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 5\u001b[0m \u001b[43m \u001b[49m\u001b[43mrelease_date\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdate\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m2017\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m4\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m27\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 6\u001b[0m \u001b[43m \u001b[49m\u001b[43mbpm\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m165\u001b[39;49m\n\u001b[1;32m 7\u001b[0m \u001b[43m)\u001b[49m\n",
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"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",
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"\u001b[0;31mValidationError\u001b[0m: 2 validation errors for Song\nduration\n Input should be greater than 0 [type=greater_than, input_value=0, input_type=int]\n For further information visit https://errors.pydantic.dev/2.5/v/greater_than\nbeats_per_minute\n Field required [type=missing, input_value={'title': 'Thunder', 'art...017, 4, 27), 'bpm': 165}, input_type=dict]\n For further information visit https://errors.pydantic.dev/2.5/v/missing"
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]
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}
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],
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"source": [
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"song2 = Song(\n",
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" title=\"Thunder\",\n",
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" artist=\"Imagine Dragons\",\n",
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" duration=0,\n",
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" release_date=date(2017, 4, 27),\n",
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" bpm=165\n",
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")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "60b73d45",
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"metadata": {},
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"source": [
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"[Learn more about Pydantic's numeric constraints](https://bit.ly/4bbhthb)."
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "venv",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.6"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}

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- file: Chapter2/dataclasses.ipynb
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- file: Chapter2/typing.ipynb
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- file: Chapter2/pathlib.ipynb
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- file: Chapter2/pydantic.ipynb
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- file: Chapter3/Chapter3.md
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sections:
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- file: Chapter3/change_values.ipynb

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