Project Icon

gophernotes

Jupyter和nteract的Go语言交互式内核

Gophernotes作为Jupyter和nteract的Go语言内核,实现了在交互式环境中编写和执行Go代码。它支持创建融合代码、公式、可视化和说明文本的文档,便于分享和协作。该工具涵盖了Go的主要语法特性,为数据分析等应用提供了灵活的开发平台,但在Windows系统上使用第三方包时有一定限制。

alt tag

Build Status License

gophernotes - Use Go in Jupyter notebooks and nteract

gophernotes is a Go kernel for Jupyter notebooks and nteract. It lets you use Go interactively in a browser-based notebook or desktop app. Use gophernotes to create and share documents that contain live Go code, equations, visualizations and explanatory text. These notebooks, with the live Go code, can then be shared with others via email, Dropbox, GitHub and the Jupyter Notebook Viewer. Go forth and do data science, or anything else interesting, with Go notebooks!

Acknowledgements - This project utilizes a Go interpreter called gomacro under the hood to evaluate Go code interactively. The gophernotes logo was designed by the brilliant Marcus Olsson and was inspired by Renee French's original Go Gopher design.

Examples

Jupyter Notebook:

nteract:

Example Notebooks (download and run them locally, follow the links to view in Github, or use the Jupyter Notebook Viewer):

Installation

Prerequisites

Linux or FreeBSD

The instructions below should work both on Linux and on FreeBSD.

Method 1: quick installation as module

  go install github.com/gopherdata/gophernotes@v0.7.5
  mkdir -p ~/.local/share/jupyter/kernels/gophernotes
  cd ~/.local/share/jupyter/kernels/gophernotes
  cp "$(go env GOPATH)"/pkg/mod/github.com/gopherdata/gophernotes@v0.7.5/kernel/*  "."
  chmod +w ./kernel.json # in case copied kernel.json has no write permission
  sed "s|gophernotes|$(go env GOPATH)/bin/gophernotes|" < kernel.json.in > kernel.json

Method 2: manual installation from GOPATH

  mkdir -p "$(go env GOPATH)"/src/github.com/gopherdata
  cd "$(go env GOPATH)"/src/github.com/gopherdata
  git clone https://github.com/gopherdata/gophernotes
  cd gophernotes
  git checkout -f v0.7.5
  go install
  mkdir -p ~/.local/share/jupyter/kernels/gophernotes
  cp kernel/* ~/.local/share/jupyter/kernels/gophernotes
  cd ~/.local/share/jupyter/kernels/gophernotes
  chmod +w ./kernel.json # in case copied kernel.json has no write permission
  sed "s|gophernotes|$(go env GOPATH)/bin/gophernotes|" < kernel.json.in > kernel.json

To confirm that the gophernotes binary is installed in GOPATH, execute it directly:

  "$(go env GOPATH)"/bin/gophernotes

and you should see the following:

2017/09/20 10:33:12 Need a command line argument specifying the connection file.

Note - if you have the JUPYTER_PATH environmental variable set or if you are using an older version of Jupyter, you may need to copy this kernel config to another directory. You can check which directories will be searched by executing:

  jupyter --data-dir

Mac

Important Note - gomacro relies on the plugin package when importing third party libraries. This package works reliably on Mac OS X with Go 1.10.2+ as long as you never execute the command strip gophernotes.

Method 1: quick installation as module

  go install github.com/gopherdata/gophernotes@v0.7.5
  mkdir -p ~/Library/Jupyter/kernels/gophernotes
  cd ~/Library/Jupyter/kernels/gophernotes
  cp "$(go env GOPATH)"/pkg/mod/github.com/gopherdata/gophernotes@v0.7.5/kernel/*  "."
  chmod +w ./kernel.json # in case copied kernel.json has no write permission
  sed "s|gophernotes|$(go env GOPATH)/bin/gophernotes|" < kernel.json.in > kernel.json

Method 2: manual installation from GOPATH

  mkdir -p "$(go env GOPATH)"/src/github.com/gopherdata
  cd "$(go env GOPATH)"/src/github.com/gopherdata
  git clone https://github.com/gopherdata/gophernotes
  cd gophernotes
  git checkout -f v0.7.5
  go install
  mkdir -p ~/Library/Jupyter/kernels/gophernotes
  cp kernel/* ~/Library/Jupyter/kernels/gophernotes
  cd ~/Library/Jupyter/kernels/gophernotes
  chmod +w ./kernel.json # in case copied kernel.json has no write permission
  sed "s|gophernotes|$(go env GOPATH)/bin/gophernotes|" < kernel.json.in > kernel.json

To confirm that the gophernotes binary is installed in GOPATH, execute it directly:

  "$(go env GOPATH)"/bin/gophernotes

and you should see the following:

2017/09/20 10:33:12 Need a command line argument specifying the connection file.

Note - if you have the JUPYTER_PATH environmental variable set or if you are using an older version of Jupyter, you may need to copy this kernel config to another directory. You can check which directories will be searched by executing:

  jupyter --data-dir

Windows

Important Note - gomacro relies on the plugin package when importing third party libraries. This package is only supported on Linux and Mac OS X currently. Thus, if you need to utilize third party packages in your Go notebooks and you are running on Windows, you should use the Docker install and run gophernotes/Jupyter in Docker.

  1. Download gophernotes inside GOPATH, compile and install it

    go env GOPATH > temp.txt
    set /p GOPATH=<temp.txt
    mkdir %GOPATH%\src\github.com\gopherdata
    cd /d %GOPATH%\src\github.com\gopherdata
    git clone https://github.com/gopherdata/gophernotes
    cd gophernotes
    git checkout -f v0.7.5
    go install
    
  2. Copy the kernel config:

    mkdir %APPDATA%\jupyter\kernels\gophernotes
    xcopy %GOPATH%\src\github.com\gopherdata\gophernotes\kernel %APPDATA%\jupyter\kernels\gophernotes /s
    

    Note, if you have the JUPYTER_PATH environmental variable set or if you are using an older version of Jupyter, you may need to copy this kernel config to another directory. You can check which directories will be searched by executing:

    jupyter --data-dir
    
  3. Update %APPDATA%\jupyter\kernels\gophernotes\kernel.json with the FULL PATH to your gophernotes.exe (usually in %GOPATH%\bin). For example:

    {
        "argv": [
          "C:\\gopath\\bin\\gophernotes.exe",
          "{connection_file}"
          ],
        "display_name": "Go",
        "language": "go",
        "name": "go"
    }
    

Docker

You can try out or run Jupyter + gophernotes without installing anything using Docker. To run a Go notebook that only needs things from the standard library, run:

  docker run -it -p 8888:8888 gopherdata/gophernotes

Or to run a Go notebook with access to common Go data science packages (gonum, gota, golearn, etc.), run:

  docker run -it -p 8888:8888 gopherdata/gophernotes:latest-ds

In either case, running this command should output a link that you can follow to access Jupyter in a browser. Also, to save notebooks to and/or load notebooks from a location outside of the Docker image, you should utilize a volume mount. For example:

  docker run -it -p 8888:8888 -v /path/to/local/notebooks:/path/to/notebooks/in/docker gopherdata/gophernotes

Getting Started

Jupyter

  • If you completed one of the local installs above (i.e., not the Docker install), start the jupyter notebook server:

    jupyter notebook
    
  • Select Go from the New drop down menu.

  • Have fun!

nteract

  • Launch nteract.

  • From the nteract menu select Language -> Go.

  • Have fun!

Special commands

In addition to Go code, the following special commands are also supported - they must be on a line by their own:

  • %cd [path]
  • %go111module {on|off}
  • %help
  • $ shell_command [args...]

Limitations

gophernotes uses gomacro under the hood to evaluate Go code interactively. You can evaluate most any Go code with gomacro, but there are some limitations, which are discussed in further detail here. Most notably, gophernotes does NOT support:

  • importing third party packages when running natively on Windows - This is a current limitation of the Go plugin package.
  • some corner cases on interpreted interfaces, as interface -> interface type switch and type assertion, are not implemented yet.
  • some corner cases on recursive types may not work correctly.
  • conversion from typed constant to interpreted interface is not implemented. Workaround: assign the constant to a variable, then convert the variable to the interpreted interface type.
  • conversions from/to unsafe.Pointer are not supported.
  • goto is only partially implemented.
  • out-of-order code in the same cell is supported, but not heavily tested. It has some known limitations for composite literals.

Also, creation of new named types is emulated, and their methods are visible only to interpreted code.

Troubleshooting

gophernotes not found

Depending on your environment, you may need to manually change the path to the gophernotes executable in kernel/kernel.json before copying it to ~/.local/share/jupyter/kernels/gophernotes. You can put the full path to the gophernotes executable here, and you shouldn't have any further issues.

"Kernel error" in a running notebook

Traceback (most recent call last):
  File "/usr/local/lib/python2.7/site-packages/notebook/base/handlers.py", line 458, in wrapper
    result = yield gen.maybe_future(method(self, *args, **kwargs))
  File "/usr/local/lib/python2.7/site-packages/tornado/gen.py", line 1008, in run
    value = future.result()
  ...
  File "/usr/local/Cellar/python/2.7.11/Frameworks/Python.framework/Versions/2.7/lib/python2.7/subprocess.py", line 1335, in _execute_child
    raise child_exception
OSError: [Errno 2] No such file or directory

Stop jupyter, if it's already running.

Add a symlink to /go/bin/gophernotes from your path to the gophernotes executable. If you followed the instructions above, this will be:

sudo ln -s $HOME/go/bin/gophernotes /go/bin/gophernotes

Restart jupyter, and you should now be up and running.

error "could not import C (no metadata for C)" when importing a package

At a first analysis, it seems to be a limitation of the new import mechanism that supports Go modules. You can switch the old (non module-aware) mechanism with the command %go111module off

To re-enable modules support, execute %go111module on

Look at Jupyter notebook's logs for debugging

In order to see the logs for your Jupyter notebook, use the --log-level option

jupyter notebook --log-level
项目侧边栏1项目侧边栏2
推荐项目
Project Cover

豆包MarsCode

豆包 MarsCode 是一款革命性的编程助手,通过AI技术提供代码补全、单测生成、代码解释和智能问答等功能,支持100+编程语言,与主流编辑器无缝集成,显著提升开发效率和代码质量。

Project Cover

AI写歌

Suno AI是一个革命性的AI音乐创作平台,能在短短30秒内帮助用户创作出一首完整的歌曲。无论是寻找创作灵感还是需要快速制作音乐,Suno AI都是音乐爱好者和专业人士的理想选择。

Project Cover

有言AI

有言平台提供一站式AIGC视频创作解决方案,通过智能技术简化视频制作流程。无论是企业宣传还是个人分享,有言都能帮助用户快速、轻松地制作出专业级别的视频内容。

Project Cover

Kimi

Kimi AI助手提供多语言对话支持,能够阅读和理解用户上传的文件内容,解析网页信息,并结合搜索结果为用户提供详尽的答案。无论是日常咨询还是专业问题,Kimi都能以友好、专业的方式提供帮助。

Project Cover

阿里绘蛙

绘蛙是阿里巴巴集团推出的革命性AI电商营销平台。利用尖端人工智能技术,为商家提供一键生成商品图和营销文案的服务,显著提升内容创作效率和营销效果。适用于淘宝、天猫等电商平台,让商品第一时间被种草。

Project Cover

吐司

探索Tensor.Art平台的独特AI模型,免费访问各种图像生成与AI训练工具,从Stable Diffusion等基础模型开始,轻松实现创新图像生成。体验前沿的AI技术,推动个人和企业的创新发展。

Project Cover

SubCat字幕猫

SubCat字幕猫APP是一款创新的视频播放器,它将改变您观看视频的方式!SubCat结合了先进的人工智能技术,为您提供即时视频字幕翻译,无论是本地视频还是网络流媒体,让您轻松享受各种语言的内容。

Project Cover

美间AI

美间AI创意设计平台,利用前沿AI技术,为设计师和营销人员提供一站式设计解决方案。从智能海报到3D效果图,再到文案生成,美间让创意设计更简单、更高效。

Project Cover

AIWritePaper论文写作

AIWritePaper论文写作是一站式AI论文写作辅助工具,简化了选题、文献检索至论文撰写的整个过程。通过简单设定,平台可快速生成高质量论文大纲和全文,配合图表、参考文献等一应俱全,同时提供开题报告和答辩PPT等增值服务,保障数据安全,有效提升写作效率和论文质量。

投诉举报邮箱: service@vectorlightyear.com
@2024 懂AI·鲁ICP备2024100362号-6·鲁公网安备37021002001498号