In this video, we dive further into the Pydantic library in Python. This is based on the following blog post:
[ Ссылка ]

We'll learn a number of things, including:

* How to define nested Pydantic models, forming parent-child relationships that allow us to model complex data that contains relationships.
* Using typing.Literal to constrain values on a field
* Defining default values for fields
* Generating JSON Schema from Pydantic models
* Auto-generating Pydantic models from JSON Schema definitions

Github data: [ Ссылка ]

📌 𝗖𝗵𝗮𝗽𝘁𝗲𝗿𝘀:
00:00 Intro
03:47 Adding new Pydantic model for nested data
05:19 Adding a link to nested model in parent Pydantic class
07:38 The effect of the Union type on a Pydantic field
10:29 Constraining field values with Python Literal type
12:53 Adding custom validator function to check list length
15:05 JSON Schema outputs with Pydantic models
18:46 Auto-generating Pydantic models from JSON Schema with datamodel-code-generator

☕️ 𝗕𝘂𝘆 𝗺𝗲 𝗮 𝗰𝗼𝗳𝗳𝗲𝗲:
To support the channel and encourage new videos, please consider buying me a coffee here:
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▶️ Full Playlist:
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𝗦𝗼𝗰𝗶𝗮𝗹 𝗠𝗲𝗱𝗶𝗮:
📖 Blog: [ Ссылка ]
👾 Github: [ Ссылка ]
🐦 Twitter: [ Ссылка ]

📚 𝗙𝘂𝗿𝘁𝗵𝗲𝗿 𝗿𝗲𝗮𝗱𝗶𝗻𝗴 𝗮𝗻𝗱 𝗶𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻:
Pydantic Blog post: [ Ссылка ]
Github Dataset: [ Ссылка ]
Pydantic Models: [ Ссылка ]
Pydantic Validators: [ Ссылка ]
Pydantic Schema: [ Ссылка ]
JSON Schema: [ Ссылка ]

#python #pydantic #datascience

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