Go (golang) Jupyter Notebook kernel and an interactive REPL
Since go1.10, this Go kernel has performance issue due to a performance regression in Go tool chain.
Also, this Go kernel can not be built with go1.12 due to another regression in Go tool chain.
Now, the compiler options this kernel relies on are completely broken and I'm not sure when they will fix the regressions. Unfortunately, they don't plan to fix this in go1.13 as of July 8th 2019. If you are interested in using this kernel, please upvote the bugs. For a while, please use other Go kernels if you want to use the later version of Go with Jupyter notebook.
- Write and execute Go (golang) interactively like Python.
- Jupyter Notebook integration
- Full Go (golang) language spec support. 100% gc (go compiler) compatible.
- Code completion and inspection in Jupyter Notebooks
- Display images, HTML, JavaScript, SVG, etc...
- Currently, lgo is only supported on Linux. But you can use lgo on Mac and Windows with virtual machines or Docker.
You can view example notebooks of lgo from Example notebooks on Jupyter nbviewer
If you want to execute these notebooks, you can try these notebooks on your browser without installation from
Thanks to binder (mybinder.org), you can try lgo on your browsers with temporary docker containers on binder. Open your temporary Jupyter Notebook from the button above and enjoy lgo.
- Install Docker and Docker Compose.
- Clone the respository and run the docker container with docker-compose.
> git clone https://github.com/yunabe/lgo.git
> cd lgo/docker/jupyter
> docker-compose up -d
If you want to use a port other than 8888 on host, update ports config in lgo/docker/jupyter/docker-compose.yaml before running docker-compose up.
- Get the URL to open the Jupyter Notebook
> docker-compose exec jupyter jupyter notebook list
Currently running servers:
http://0.0.0.0:8888/?token=50dfee7e328bf86e70c234a2f06021e1df63a19641c86676 :: /examples
- Open the Jupyter Notebook server with the authentication token above.
If you are using Linux or Mac OS, you can use start/stop scripts instead. Web browser will open the URL automatically.
# start server
> ./up.sh
# stop server
> ./down.sh- lgo is supported only on Linux at this moment. On Windows or Mac OS, use virtual machines or dockers.
- Install Go 1.9 or Go 1.8.
- Install Jupyter Notebook
- Install ZMQ
- e.g.
sudo apt-get install libzmq3-dev
- e.g.
- Install pkg-config
- e.g.
sudo apt-get install pkg-config
- e.g.
go get github.com/yunabe/lgo/cmd/lgo && go get -d github.com/yunabe/lgo/cmd/lgo-internal- This installs
lgocommand into your$(go env GOPATH)/bin
- This installs
- Set
LGOPATHenvironment variablelgo installwill install binaries into the directory specified withLGOPATH.- You can use any empty directory with write permission as
LGOPATH.
- Run
lgo install- This installs std libraries and the internal lgo tool into
LGOPATHwith specific compiler flags. - If
lgo installfails, please check install log stored in$LGOPATH/install.log
- This installs std libraries and the internal lgo tool into
- (Optional) Run
lgo installpkg [packages]to install third-party packages toLGOPATH- You can preinstall third-party packages into
LGOPATH. - This step is optional. If packages are not preinstalled, lgo installs the packages on the fly.
- But, installing packages is a heavy and slow process. I recommend you to preinstall packages which you will use in the future with high probability.
- If
lgo installpkgfails, please check the log stored in$LGOPATH/installpkg.log. - See go's manual about the format of
[packages]args.
- You can preinstall third-party packages into
- Install the kernel configuration to Jupyter Notebook
python $(go env GOPATH)/src/github.com/yunabe/lgo/bin/install_kernel- Make sure to use the same version of
pythonas you used to installjupyter. For example, usepython3instead ofpythonif you installjupyterwithpip3.
- (Optional) If you want to use
lgowith JupyterLab, install a jupyterlab extension forlgojupyter labextension install @yunabe/lgo_extension- This extension adds "Go Format" button to the toolbar in JupyterLab.
- Run
jupyter notebookcommand to start Juyputer Notebook and select "Go (lgo)" from New Notebook menu. - To show documents of packages, functions and variables in your code, move the cursor to the identifier you want to inspect and press
Shift-Tab. - Press
Tabto complete code - Click
Format Gobutton in the toolbar to format code. - lgo works with JupyterLab. To use lgo from JupyterLab, install JupyterLab and run
jupyter lab.
You can use lgo from command line with Jupyter Console or build-in REPL mode of lgo
Run jupyter console --kernel lgo
In [1]: a, b := 3, 4
In [2]: func sum(x, y int) int {
: return x + y
: }
In [3]: import "fmt"
In [4]: fmt.Sprintf("sum(%d, %d) = %d", a, b, sum(a, b))
sum(3, 4) = 7Run lgo run
$ lgo run
>>> a, b := 3, 4
>>> func sum(x, y int) int {
... return x + y
... }
>>> import "fmt"
>>> fmt.Sprintf("sum(%d, %d) = %d", a, b, sum(a, b))
sum(3, 4) = 7The packages you want to use in lgo must be prebuilt and installed into $LGOPATH by lgo install command.
Please make sure to run lgo install after you fetch a new package with go get command.
Please run lgo install --clean after you update go version.
lgo install installs prebuilt packages into $LGOPATH.
When you update go version, you need to reinstall these prebuilt packages with the newer go
because binary formats of prebuilt packages may change in the newer version of go.
To display HTML and images in lgo, use _ctx.Display.
See the example of _ctx.Display in an example notebook
In lgo, you can interrupt execution by pressing "Stop" button (or pressing I, I) in Jupyter Notebook and pressing Ctrl-C in the interactive shell.
However, as you may know, Go does not allow you to cancel running goroutines with Ctrl-C. Go does not provide any API to cancel specific goroutines. The standard way to handle cancellation in Go today is to use context.Context (Read Go Concurrency Patterns: Context if you are not familiar with context.Context in Go).
lgo creates a special context _ctx on every execution and _ctx is cancelled when the execution is cancelled. Please pass _ctx as a context.Context param of Go libraries you want to cancel. Here is an example notebook of cancellation in lgo.
In lgo, memory is managed by the garbage collector of Go. Memory not referenced from any variables or goroutines is collected and released automatically.
One caveat of memory management in lgo is that memory referenced from global variables are not released automatically when the global variables are shadowed by other global variables with the same names. For example, if you run the following code blocks, the 32MB RAM reserved in [1] is not released after executing [2] and [3] because
[2]does not reset the value ofbin[1]. It just defines another global variablebwith the same name and shadows the reference to the firstb.[3]resetsbdefined in[2]. The memory reserved in[2]will be released after[3]. But the memory reserved in[1]will not be released.
[1]
// Assign 32MB ram to b.
b := make([]byte, 1 << 25)
[2]
// This shadows the first b.
b := make([]byte, 1 << 24)
[3]
// This sets nil to the second b.
b = nil
lgo works with go1.10. But the overhead of code execution is 4-5x larger in go1.10 than go1.9.
It is due to a regression of the cache mechnism of go install in go1.10.
I recommend you to use lgo with go1.9 until the bug is fixed in go1.10.
gore, which was released in Feb 2015, is the most famous REPL implementation for Go as of Dec 2017. gore is a great tool to try out very short code snippets in REPL style.
But gore does not fit to data science or heavy data processing at all.
gore executes your inputs by concatinating all of your inputs,
wrapping it with main function and running it with go run command.
This means every time you input your code, gore executes all your inputs from the begining.
For example, if you are writing something like
- Loads a very large CSV file as an input. It takes 1 min to load.
- Analyzes the loaded data. For example, calculates max, min, avg, etc..
gore always runs the first step when you calculate something and you need to wait for 1 min every time. This behavior is not acceptable for real data science works. Also, gore is not good at tyring code with side effects (even fmt.Println) because code snippets with side effects are executed repeatedly and repeatedly. lgo chose a totally different approach to execute Go code interactively and does not have the same shortcoming.
gore is a CLI tool and it does not support Jupyter Notebook.
| lgo | gophernotes | |
|---|---|---|
| Backend | gc (go compiler) | An unofficial interpreter |
| Full Go Language Specs | ✔️ | |
| 100% gc compatible | ✔️ | |
| Static typing | ✔️ | to some extent |
| Performance | Fast | Slow |
| Overhead | 500ms | 1ms |
| Cancellation | ✔️ | |
| Code completion | ✔️ | |
| Code inspection | ✔️ | |
| Code formatting | ✔️ | |
| Display HTML and images | ✔️ | |
| Windows, Mac | Use Docker or VM | Partial |
| License | BSD | LGPL |
gophernotes was the first Jupyter kernel for Go, released in Jan 2016.
Before Sep 2017, it used the same technology gore uses to evaluate Go code. This means it did not fit to heavy data processing or data analysis at all.
From Sep 2017, gophernotes switched from go run approach to gomacro, one of unofficial golang interpreters by cosmos72. This solved the problem gore has. Now, the code execution mechnism of gophernotes also fits to heavy data analysis.
The shortcomings of using an unofficial interpreter are
- It does not support all Go language features. Especially, it does not support one of the most important Go feature,
interface. As of go1.10, it is hard to supportinterfacein an interpreter written in Go because of the lack of API inreflectpackage. - Interpreters are generally slow.
- Unofficial interpreters are not well-tested compared to the official gc (go compiler) tools.
The advantages of this approach are
- The overhead of code execution is small because it does not compile and link code.
- Windows/Mac partial support. lgo works only on Linux and you need to use VMs or Docker to run it on Windows/Mac. gophernotes (gomacro) works on Windows/Mac natively if you do not need third-party packages.
These disadvantage and advantages are not something inevitable in interperters. But they are not easy to solve under the limited development resource.
Also, lgo kernel supports more rich features in Jupyter Notebook as of Dec 2017, including code completion, code inspection and images/HTML/JavaScript output supports.
Got an error message like:
Kernel Restarting
The kernel appears to have died. It will restart automatically.
First, please confirm your code does not call os.Exit directly or indirectly.
In lgo, your code is executed in the processs of lgo kernel. If you evaluate os.Exit in lgo, it terminates the lgo kernel process and jupyter notebook server loses the connection with the kernel.
Thus, you must not evaluate os.Exit or functions that call it internally (e.g. log.Fatal) in lgo.
If os.Exit is not the reason of "Dead kernel", please check crash logs of the kernel.
If you run your notebook with jupyter notebook command in a terminal, the crash log should be there.
If you run your notebook in docker, attach the container's terminal with docker attach to view the logs.
If you can see the logs of jupyter notebook, you should see logs like
2018/03/01 20:30:45 lgo-internal failed: exit status 1
[I 22:34:00.500 NotebookApp] KernelRestarter: restarting kernel (1/5)
kernel abcd1234-5678-efghi-xxxx-777eeffcccbb restarted
and you can probably see helpful information before lgo-internal failed message.
Got an error message like:
multiple roots $LGOPATH/pkg &
Failed to build a shared library of github.com/yunabe/lgo/sess7b..7d/exec1: exit status 1
This error occurs when the go command you are currently using is different from the go command you used to run lgo install.
For example, this happens if you update go from 1.9 to 1.10 but did not run lgo install --clean with the new go after the update.
If you encouter this issue, please double-check that you are using go which you used to run lgo install to install packages into $LGOPATH.
Got error messages like:
could not import github.com/yunabe/mylib (/home/yunabe/local/gocode/pkg/linux_amd64/github.com/yunabe/mylib.a: import "github.com/yunabe/mylib": old export format no longer supported (recompile library))
Some libraries installed in your $GOPATH are in the old format, which are built go1.6 or before.
Make sure all libraries under your $GOPATH are recompiled with your current go compiler.
cd $GOPATH/src; go install ./...
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