Tutorials - Loren1166/NautilusTrader- GitHub Wiki

Tutorials 教程

The tutorials provide a guided learning experience with a series of comprehensive step-by-step walkthroughs. Each tutorial targets specific features or workflows, enabling hands-on learning. From basic tasks to more advanced operations, these tutorials cater to a wide range of skill levels.

教程提供一系列全面的分步演练，引导您学习。每个教程都针对特定的功能或工作流程，支持动手学习。从基本任务到更高级的操作，这些教程适合各种技能水平。

info 信息

Each tutorial is generated from a Jupyter notebook located in the docs/tutorials directory. These notebooks not only serve as valuable learning aids but also lets you to execute the code.

每个教程都是从位于 docs/tutorials 目录中的 Jupyter 笔记本生成的。这些笔记本不仅是宝贵的学习辅助工具，还可以让您执行代码。

tip 提示

Make sure you are following the tutorial docs which match the version of NautilusTrader you are running:

确保您遵循与您正在运行的 NautilusTrader 版本相匹配的教程文档：

  • Latest: These docs are built from the HEAD of the master branch and work with the latest stable release. 最新： 这些文档是从 master 分支的 HEAD 构建的，并与最新的稳定版本一起使用。
  • Nightly: These docs are built from the HEAD of the nightly branch and work with bleeding edge and experimental changes/features currently in development. 每晚： 这些文档是从每晚分支的 HEAD 构建的，并与当前正在开发的最前沿和实验性更改/功能一起使用。

Running in docker 在 docker 中运行

Alternatively, a self-contained dockerized Jupyter notebook server is available for download, which does not require any setup or installation. This is the fastest way to get up and running to try out NautilusTrader. Bear in mind that any data will be deleted when the container is deleted.

或者，可以下载一个独立的 dockerized Jupyter 笔记本服务器，它不需要任何设置或安装。这是启动和运行以试用 NautilusTrader 的最快方法。请记住，当容器被删除时，任何数据都将被删除。

To get started, install docker:

要开始使用，请安装 docker：

  1. Go to docker.com and follow the instructions. 转到 docker.com 并按照说明进行操作。
  2. From a terminal, download the latest image. 从终端下载最新的镜像。
docker pull ghcr.io/nautechsystems/jupyterlab:nightly --platform linux/amd64
  1. Run the docker container, exposing the jupyter port: 运行 docker 容器，公开 jupyter 端口：
docker run -p 8888:8888 ghcr.io/nautechsystems/jupyterlab:nightly
  1. Open your web browser to localhost:{port}. 在您的网络浏览器中打开 localhost:{port}。
https://localhost:8888

info 信息

NautilusTrader currently exceeds the rate limit for Jupyter notebook logging (stdout output), this is why log_level in the examples is set to "ERROR". If you lower this level to see more logging then the notebook will hang during cell execution. A fix is currently being investigated which involves either raising the configured rate limits for Jupyter, or throttling the log flushing from Nautilus.

NautilusTrader 目前超过了 Jupyter 笔记本日志记录（标准输出）的速率限制，这就是示例中 log_level 设置为“ERROR”的原因。如果您降低此级别以查看更多日志记录，则笔记本将在单元格执行期间挂起。目前正在调查一个解决方案，该解决方案涉及提高 Jupyter 的配置速率限制，或限制 Nautilus 的日志刷新。