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https://github.com/MetaCubeX/mihomo
A simple Python Pydantic model for Honkai: Star Rail parsed data from the Mihomo API.
https://github.com/MetaCubeX/mihomo
honkai-star-rail mihomo python star-rail-api
Last synced: 12 days ago
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A simple Python Pydantic model for Honkai: Star Rail parsed data from the Mihomo API.
- Host: GitHub
- URL: https://github.com/MetaCubeX/mihomo
- Owner: MetaCubeX
- License: mit
- Created: 2021-05-20T11:06:33.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2024-05-28T16:12:30.000Z (6 months ago)
- Last Synced: 2024-05-29T07:18:27.148Z (6 months ago)
- Topics: honkai-star-rail, mihomo, python, star-rail-api
- Language: Python
- Homepage: https://wiki.metacubex.one
- Size: 7.75 MB
- Stars: 13,105
- Watchers: 84
- Forks: 2,322
- Open Issues: 337
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# mihomo
A simple python pydantic model (type hint and autocompletion support) for Honkai: Star Rail parsed data from the Mihomo API.
API url: https://api.mihomo.me/sr_info_parsed/{UID}?lang={LANG}
## Installation
```
pip install -U git+https://github.com/KT-Yeh/mihomo.git
```
## Usage
### Basic
There are two parsed data formats:
- V1:
- URL: https://api.mihomo.me/sr_info_parsed/800333171?lang=en&version=v1
- Fetching: use `client.fetch_user_v1(800333171)`
- Data model: `mihomo.models.v1.StarrailInfoParsedV1`
- All models defined in `mihomo/models/v1` directory.
- V2:
- URL: https://api.mihomo.me/sr_info_parsed/800333171?lang=en
- Fetching: use `client.fetch_user(800333171)`
- Data model: `mihomo.models.StarrailInfoParsed`
- All models defined in `mihomo/models` directory.
If you don't want to use `client.get_icon_url` to get the image url everytime, you can use `client.fetch_user(800333171, replace_icon_name_with_url=True)` to get the parsed data with asset urls.
### Example
```py
import asyncio
from mihomo import Language, MihomoAPI
from mihomo.models import StarrailInfoParsed
from mihomo.models.v1 import StarrailInfoParsedV1
client = MihomoAPI(language=Language.EN)
async def v1():
data: StarrailInfoParsedV1 = await client.fetch_user_v1(800333171)
print(f"Name: {data.player.name}")
print(f"Level: {data.player.level}")
print(f"Signature: {data.player.signature}")
print(f"Achievements: {data.player_details.achievements}")
print(f"Characters count: {data.player_details.characters}")
print(f"Profile picture url: {client.get_icon_url(data.player.icon)}")
for character in data.characters:
print("-----------")
print(f"Name: {character.name}")
print(f"Rarity: {character.rarity}")
print(f"Level: {character.level}")
print(f"Avatar url: {client.get_icon_url(character.icon)}")
print(f"Preview url: {client.get_icon_url(character.preview)}")
print(f"Portrait url: {client.get_icon_url(character.portrait)}")
async def v2():
data: StarrailInfoParsed = await client.fetch_user(800333171, replace_icon_name_with_url=True)
print(f"Name: {data.player.name}")
print(f"Level: {data.player.level}")
print(f"Signature: {data.player.signature}")
print(f"Profile picture url: {data.player.avatar.icon}")
for character in data.characters:
print("-----------")
print(f"Name: {character.name}")
print(f"Rarity: {character.rarity}")
print(f"Portrait url: {character.portrait}")
asyncio.run(v1())
asyncio.run(v2())
```
### Tools
`from mihomo import tools`
#### Remove Duplicate Character
```py
data = await client.fetch_user(800333171)
data = tools.remove_duplicate_character(data)
```
#### Merge Character Data
```py
old_data = await client.fetch_user(800333171)
# Change characters in game and wait for the API to refresh
# ...
new_data = await client.fetch_user(800333171)
data = tools.merge_character_data(new_data, old_data)
```
### Data Persistence
Take pickle and json as an example
```py
import pickle
import zlib
from mihomo import MihomoAPI, Language, StarrailInfoParsed
client = MihomoAPI(language=Language.EN)
data = await client.fetch_user(800333171)
# Save
pickle_data = zlib.compress(pickle.dumps(data))
print(len(pickle_data))
json_data = data.json(by_alias=True, ensure_ascii=False)
print(len(json_data))
# Load
data_from_pickle = pickle.loads(zlib.decompress(pickle_data))
data_from_json = StarrailInfoParsed.parse_raw(json_data)
print(type(data_from_pickle))
print(type(data_from_json))
```