Sekai Deck Recommendation C++

A C++ optimized version of sekai-calculator with Python bindings, providing both the original brute-force search algorithm and some new randomized algorithms.

Install

This fork’s PyPI name is sekai-deck-recommend-cpp-resona Import name is unchanged: sekai_deck_recommend_cpp.

After a successful v* release:

uv pip install sekai-deck-recommend-cpp-resona

Upstream package

uv pip install sekai-deck-recommend-cpp

Install from source

Prerequisites

• CMake ≥ 3.15
• C++20 compatible compiler (GCC/Clang/MSVC)
• Python 3.10+ with development headers

Steps

# Clone with submodules
git clone --recursive https://github.com/Resonalofi/sekai-deck-recommend-cpp.git
cd sekai-deck-recommend-cpp

# Install via pip (compiles locally)
uv pip install -e . -v
# or: pip install -e . -v

Build for WebAssembly

Install and activate the Emscripten SDK, then configure the browser build with Ninja:

emcmake cmake -S . -B build/wasm -G Ninja \
  -DCMAKE_BUILD_TYPE=Release \
  -DSEKAI_DECK_RECOMMEND_WASM_OUTPUT_DIR=/absolute/path/to/browser/assets
cmake --build build/wasm -j 4

The output directory receives sekai_deck_recommend_wasm.js, sekai_deck_recommend_wasm.wasm, and sekai_deck_recommend_wasm.data. Omit SEKAI_DECK_RECOMMEND_WASM_OUTPUT_DIR to keep the files in the CMake build directory.

Tagged releases and manual runs of the Build and publish WASM to R2 workflow build these assets and synchronize them to a dedicated Cloudflare R2 prefix. Configure the following GitHub Actions repository secrets:

• R2_ENDPOINT: the complete R2 S3 API endpoint
• R2_ACCESS_KEY_ID: the R2 API token access key ID
• R2_SECRET_ACCESS_KEY: the R2 API token secret access key
• R2_BUCKET_NAME: the destination bucket
• R2_WASM_PREFIX: a non-empty prefix reserved for the current WASM assets

The workflow removes remote files under R2_WASM_PREFIX that are not present in the new build. Do not point this secret at the bucket root or a shared prefix.

Build as a native C++ library

The native target is independent from pybind11 and does not change the default wheel build:

cmake -S . -B build/native -G Ninja \
  -DCMAKE_BUILD_TYPE=Release \
  -DSEKAI_DECK_RECOMMEND_BUILD_PYTHON=OFF \
  -DSEKAI_DECK_RECOMMEND_BUILD_NATIVE=ON
cmake --build build/native --parallel

When this project is included with add_subdirectory, link SekaiDeckRecommend::Core and include sekai_deck_recommend/native.h. NativeEngine accepts nlohmann JSON options, including user_data as an object. Copies share parsed master data and music metadata; recommend is a const read operation, so immutable engine snapshots can serve concurrent callers.

The native target only exposes recommendation-domain behavior. HTTP, authentication, remote fetching, cache generations, and deployment remain responsibilities of the consuming service.

Usage

from sekai_deck_recommend_cpp import (
    SekaiDeckRecommend, 
    DeckRecommendOptions,
    DeckRecommendCardConfig
)
   
sekai_deck_recommend = SekaiDeckRecommend()

sekai_deck_recommend.update_masterdata("base/dir/of/masterdata", "jp")
sekai_deck_recommend.update_musicmetas("file/path/of/musicmetas.json", "jp")

options = DeckRecommendOptions()

# optimizing target in ["score", "power", "skill", "bonus"], default is "score"
options.target = "score"

# "ga" for genetic algorithm, "dfs" for brute-force search
# default is "ga"
options.algorithm = "ga"   

options.region = "jp"
options.user_data_file_path = "user/data/file/path.json"
options.live_type = "multi"
options.music_id = 74
options.music_diff = "expert"
options.event_id = 160
# Or simulate a marathon memory event: all attributes +25%, the selected unit +75%.
# options.event_me_unit = "street"

result = sekai_deck_recommend.recommend(options)

For more details of options, please refer the docstring of sekai_deck_recommend.DeckRecommendOptions

Simulation and WorldLink details

The recommendation options accept partial override dictionaries. Before calculation, each explicitly provided field overwrites the corresponding field in this request's user data; omitted fields keep their current user-data value:

options.area_item_config = {
    "mode": "current",              # current, empty, max, uniform, minimum
    "items": {"12": 15, "13": 8},  # per-area-item overrides; 0 disables one item
}
# A flat dictionary is also accepted for fine-grained furniture DIY:
options.area_item_config = {"12": 15, "13": 8, "14": 0}
options.character_rank_config = {
    "mode": "current",              # current, max, fixed
    "overrides": {"17": 60},
}
options.honor_config = {
    "mode": "current",              # current or none
    "overrides": {"12345": {"enabled": False}},
}
options.mysekai_config = {
    "fixtures": {"mode": "current", "rates": {"17": 12.5}},
    "gates": {"mode": "none", "overrides": {"1001": {"enabled": False}}},
    "canvas": {"mode": "none", "include": [123], "exclude": [456]},
}

For WorldLink recommendations, each returned deck includes wl_sub_deck with the selected support cards and their full card state, including level, master rank, skill level, episode status, training image, power breakdown, and support bonus. The main deck also exposes event_diff_attr_bonus_rate and event_shuffle_unit_bonus_rate; each main card's event_bonus_rate is its actual position-dependent event bonus.

Acknowledgments

• Original implementation by xfl03/sekai-calculator
• JSON parsing by nlohmann/json
• Python bindings powered by pybind11