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Honkai: Star Rail Mihomo API Parser (Pydantic Models)

A Python library using Pydantic for parsing Honkai: Star Rail game data from the Mihomo API, providing structured access to player profiles, characters, relics, and more.

Python
Added on 2025年6月30日
View on GitHub
Honkai: Star Rail Mihomo API Parser (Pydantic Models) preview
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Project Introduction

Summary

This project provides a Python library built with Pydantic to easily fetch, validate, and parse data from the Mihomo API for Honkai: Star Rail. It turns raw JSON into structured Python objects, making it simple for developers to build applications and tools.

Problem Solved

Accessing and structuring raw data from the Mihomo API can be complex and error-prone without clear data models. This project provides robust, type-hinted models and parsing logic.

Core Features

Pydantic Data Models

Define Pydantic models for core HSR entities like characters, relics, stats, and player profiles, ensuring data integrity.

API Integration & Parsing

Handle requests to the Mihomo API and validate/parse responses directly into Pydantic model instances.

Simplified Data Access

Abstract complex API structures into easy-to-access Python objects, simplifying data usage.

Tech Stack

Python
Pydantic
requests
typing

使用场景

The structured data provided by this library can be used in various Honkai: Star Rail related applications and projects:

场景一:开发玩家数据面板

Details

Build web or desktop applications that display a player's profile, character builds, relic stats, and progress.

User Value

Provides reliable, typed data for displaying complex in-game information clearly and accurately.

场景二:构建数据分析工具

Details

Create tools that analyze character stats, relic efficiencies, or team compositions based on fetched player data.

User Value

Offers structured data ready for computational analysis and algorithm development.

场景三:社区工具/机器人集成

Details

Power Discord bots or other community tools that need to retrieve and present specific player information on demand.

User Value

Simplifies fetching and presenting player data in conversational or automated contexts.

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