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docs/Pydantic Core/01_basemodel.md

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+layout: default
+title: "BaseModel"
+parent: "Pydantic Core"
+nav_order: 1
+---
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 # Chapter 1: BaseModel - Your Data Blueprint
 
 Welcome to the Pydantic tutorial! We're excited to guide you through the powerful features of Pydantic, starting with the absolute core concept: `BaseModel`.

docs/Pydantic Core/02_fields__fieldinfo___field_function_.md

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+layout: default
+title: "Fields (FieldInfo & Field function)"
+parent: "Pydantic Core"
+nav_order: 2
+---
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 # Chapter 2: Customizing Your Blueprint's Rooms - Fields
 
 In [Chapter 1: BaseModel - Your Data Blueprint](01_basemodel.md), we learned how `BaseModel` acts like a blueprint for our data, defining the expected structure and types using simple Python type hints. We saw how Pydantic uses this blueprint to parse, validate, and serialize data.

docs/Pydantic Core/03_configuration__configdict___configwrapper_.md

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+---
+layout: default
+title: "Configuration (ConfigDict & ConfigWrapper)"
+parent: "Pydantic Core"
+nav_order: 3
+---
+
 # Chapter 3: Configuring Your Blueprint - Model Settings
 
 In [Chapter 1](01_basemodel.md), we learned about `BaseModel` as our data blueprint, and in [Chapter 2](02_fields__fieldinfo___field_function_.md), we saw how `Field()` lets us add specific notes (like defaults or aliases) to individual rooms (fields) on that blueprint.

docs/Pydantic Core/04_custom_logic__decorators___annotated_helpers_.md

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+---
+layout: default
+title: "Custom Logic (Decorators & Annotated Helpers)"
+parent: "Pydantic Core"
+nav_order: 4
+---
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 # Chapter 4: Custom Logic (Decorators & Annotated Helpers)
 
 In [Chapter 3: Configuration (ConfigDict / ConfigWrapper)](03_configuration__configdict___configwrapper_.md), we learned how to set global rules for our data blueprints using `model_config`. But what if we need more specific, custom rules or transformations that go beyond simple settings?

docs/Pydantic Core/05_core_schema___validation_serialization.md

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+---
+layout: default
+title: "Core Schema & Validation/Serialization"
+parent: "Pydantic Core"
+nav_order: 5
+---
+
 # Chapter 5: Core Schema & Validation/Serialization
 
 In the previous chapters, we've seen how to define data structures using [BaseModel](01_basemodel.md), customize fields with [Field()](02_fields__fieldinfo___field_function_.md), set model-wide behavior with [Configuration](03_configuration__configdict___configwrapper_.md), and even add [Custom Logic](04_custom_logic__decorators___annotated_helpers_.md) using decorators. You might be wondering: how does Pydantic take all these Python definitions and use them to perform such fast and reliable validation and serialization?

docs/Pydantic Core/06_typeadapter.md

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+layout: default
+title: "TypeAdapter"
+parent: "Pydantic Core"
+nav_order: 6
+---
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 # Chapter 6: TypeAdapter - Your Universal Data Handler
 
 Welcome to the final chapter of our Pydantic Core tutorial! In [Chapter 5: Core Schema & Validation/Serialization](05_core_schema___validation_serialization.md), we dove deep into how Pydantic uses the `CoreSchema` and the `pydantic-core` engine to efficiently validate and serialize data for your `BaseModel` classes.