Skip to main content

Python Behavior Tree Framework with C++ Core

Project description

PSBTree 行为树引擎

基于 C++ 和 Python 实现的高性能行为树引擎,支持顺序和并行执行模式,适用于机器人控制、游戏 AI 和自动化系统。

项目结构

.
├── src/                    # 源代码目录
│   └── psbtree/            # 主包目录
│       ├── engine/         # 引擎实现(顺序和并行)
│       ├── nodes/          # 节点实现(动作、条件、控制、装饰器)
│       ├── plugins/        # 插件系统
│       └── utils/          # 工具函数
├── sample/                 # 示例代码
├── tests/                  # 测试代码
├── doc/                    # 文档
├── source_cpp/             # C++ 源代码
├── dependencies/           # 依赖项
├── scripts/                # 构建脚本
├── pyproject.toml          # 项目配置
├── setup.py                # 安装脚本
└── README.md               # 项目文档

核心功能

  • 行为树引擎: 支持顺序和并行执行模式
  • 节点系统: 提供丰富的节点类型(动作、条件、控制、装饰器)
  • 高性能: 核心功能使用 C++ 实现,通过 Cython 与 Python 集成
  • 授权系统: 内置授权验证机制
  • 插件扩展: 支持通过插件系统扩展功能

快速开始

  1. 安装依赖:

    pip install -r requirements.txt
    
  2. 安装包:

    pip install .
    
  3. 设置授权码:

    from psbtree import set_sk_code
    set_sk_code("您的授权码")
    
  4. 运行示例:

    python sample/sequential_engine_sample.py
    

依赖管理

核心依赖包括:

  • loguru: 日志记录
  • psdec: 授权验证
  • opencv-python: 图像处理(示例中使用)

使用示例

顺序引擎示例

from psbtree.engine.sequential_engine import SequentialEngine
from psbtree.nodes import SimpleActionNode, TreeNode, NodeStatus
from psbtree import set_sk_code

# 设置授权码
set_sk_code("您的授权码")

# 创建顺序引擎
engine = SequentialEngine()

# 注册节点
engine.register_action_class(YourActionNode, "YourActionNode")

# 定义行为树XML
xml_text = """
<root BTCPP_format="4">
    <BehaviorTree ID="MainTree">
        <Sequence name="root_sequence">
            <YourActionNode />
        </Sequence>
    </BehaviorTree>
</root>
"""

# 从XML创建行为树
engine.create_tree_from_text(xml_text)

# 运行行为树
status = engine.tick_once()

并行引擎示例

from psbtree.engine.parallel_engine import ParallelEngine
from psbtree.nodes import SimpleActionNode, TreeNode, NodeStatus
from psbtree import set_sk_code

# 设置授权码
set_sk_code("您的授权码")

# 创建并行引擎
engine = ParallelEngine()

# 注册节点
engine.register_action_class(YourActionNode, "YourActionNode")

# 定义多个行为树XML
xml_text_tree0 = """
<root BTCPP_format="4">
    <BehaviorTree ID="Tree0">
        <Sequence name="root_sequence">
            <YourActionNode />
        </Sequence>
    </BehaviorTree>
</root>
"""

# 从XML创建行为树
tree_id0 = engine.create_tree_from_text(xml_text_tree0, "tree0")

# 运行行为树
status0 = engine.tick_once(tree_id0)

开发指南

  • 使用 SimpleActionNode 作为基类创建自定义节点
  • 通过 ports 静态变量定义节点的输入输出端口
  • 实现 tick 静态方法定义节点的行为
  • 使用 XML 格式定义行为树结构
  • 遵循行为树设计模式最佳实践

贡献

欢迎提交 PR 和 issue。请确保:

  • 代码符合项目编码规范
  • 包含必要的单元测试
  • 更新相关文档

许可证

MIT License

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

psbtree-0.1.15-cp313-cp313-manylinux_2_28_x86_64.whl (7.5 MB view details)

Uploaded CPython 3.13manylinux: glibc 2.28+ x86-64

psbtree-0.1.15-cp312-cp312-manylinux_2_28_x86_64.whl (7.6 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.28+ x86-64

psbtree-0.1.15-cp311-cp311-manylinux_2_28_x86_64.whl (7.6 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.28+ x86-64

psbtree-0.1.15-cp310-cp310-manylinux_2_28_x86_64.whl (7.2 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.28+ x86-64

psbtree-0.1.15-cp39-cp39-manylinux_2_28_x86_64.whl (7.2 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.28+ x86-64

File details

Details for the file psbtree-0.1.15-cp313-cp313-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for psbtree-0.1.15-cp313-cp313-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 8f1db6feef3a7ace6376ebe7315dd10d91dd2bcbced4049437ea40b09c86acda
MD5 33ac067fc8a055359cc1c02b1da8b8de
BLAKE2b-256 2c4b9c33fd04e2fb00dcbb7765852b04c319c4c49a9e83317bcc0932c9a4289e

See more details on using hashes here.

File details

Details for the file psbtree-0.1.15-cp312-cp312-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for psbtree-0.1.15-cp312-cp312-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 1e310086bf53b792df5c3c635e51f459396d08db7e84d51c0055e59ddc669451
MD5 1b53e287445796759995dce0cc628a1f
BLAKE2b-256 ed5479482105434eb97d0e75f3d8f35ef86acd0af432560a66dfbb6e723f8093

See more details on using hashes here.

File details

Details for the file psbtree-0.1.15-cp311-cp311-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for psbtree-0.1.15-cp311-cp311-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 329bfc770792f0fbcda9deb95fe40bcba5c1543617f2386d048a6d0af8de4295
MD5 5f36aec6d439172fdb386a669cc83096
BLAKE2b-256 a67765be49af85d76e484417df56d2f654840243d6ff44e8da036d826805ac95

See more details on using hashes here.

File details

Details for the file psbtree-0.1.15-cp310-cp310-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for psbtree-0.1.15-cp310-cp310-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 efddc700fc92deca928f27df2f481ced29a06a52fbcf375805fce5ebcf929143
MD5 9bfaab30b8211c09f54056fa87ba3f58
BLAKE2b-256 2f6c67cb4ccfb6214937941e686a63e3eea4215e1f4dc35072994cb0057bb8d5

See more details on using hashes here.

File details

Details for the file psbtree-0.1.15-cp39-cp39-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for psbtree-0.1.15-cp39-cp39-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 61bd9693eb3738624ef116a140cd617ffc4a8f900055f867cb8e37aeebbedb39
MD5 9f843e6c38e52acf4f265bcde784a647
BLAKE2b-256 22b1a7f56d19ea54c46f878a6d462f2afa00e55561d76e1e8fd3298abb2d4f45

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page