diff --git a/examples/google_colab_demo.ipynb b/examples/google_colab_demo.ipynb old mode 100755 new mode 100644 index d4da04c..c403e54 --- a/examples/google_colab_demo.ipynb +++ b/examples/google_colab_demo.ipynb @@ -1 +1,601 @@ -{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"provenance":[],"authorship_tag":"ABX9TyNEI9rTz4+ntKYE4pKlYlvm"},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"}},"cells":[{"cell_type":"markdown","source":["# GoNB - A Go Notebook Kernel for Jupyter\n","\n","See the [tutorial in github](https://github.com/janpfeifer/gonb/blob/e15ac2e8e3fe/examples/tutorial.ipynb). The repository is in [github.com/janpfeifer/gonb](https://github.com/janpfeifer/gonb).\n","\n","\n","\n","## Installation in Google's Colab\n","\n","Run the following cell once only. It will install Go, GoNB and restart the kernel so it uses Go instead of the provided Python.\n","\n","It takes a couple of minutes ... but only needs to be done once.\n","\n","When creating other GoNB notebooks with Google's Colab, you will have to copy the cell below (or do something similar).\n","\n","**Disclaimer**: this is highly not documented or official, but seems to be supported by Colab (it works). Likely this way of replacing the kernel will break without notice. Please reach out to project in [github.com/janpfeifer/gonb](https://github.com/janpfeifer/gonb) if there are any issues.\n"],"metadata":{"id":"FWzjioUI63tT"}},{"cell_type":"code","execution_count":null,"metadata":{"id":"3PaXSu67xkrg","colab":{"base_uri":"https://localhost:8080/"},"outputId":"255c5bb5-e54c-43a3-ea9d-edfed8a10bf0","cellView":"form"},"outputs":[{"output_type":"stream","name":"stdout","text":["env: GOROOT=/content/go\n","go version go1.20 linux/amd64\n","\u001b[7;39;32m[3d60d1eb]\u001b[0m 2023/02/12 11:03:33 Go (gonb) kernel configuration installed in \"/root/.local/share/jupyter/kernels/gonb/kernel.json\".\n"]}],"source":["#@title Install Go, `goimports` and Gote code.\n","\n","# Install Go and goimports.\n","!mkdir -p cache\n","!wget -q -O cache/go.tar.gz 'https://go.dev/dl/go1.23.1.linux-amd64.tar.gz'\n","!tar xzf cache/go.tar.gz\n","%env GOROOT=/content/go\n","!ln -sf \"/content/go/bin/go\" /usr/bin/go\n","!go version\n","\n","# Install gonb, goimports, gopls.\n","!go install github.com/janpfeifer/gonb@latest 2> /dev/null\n","!ln -sf /root/go/bin/gonb /usr/bin/gonb\n","!go install golang.org/x/tools/cmd/goimports@latest 2> /dev/null\n","!ln -sf /root/go/bin/goimports /usr/bin/goimports\n","!go install golang.org/x/tools/gopls@latest 2> /dev/null\n","!ln -sf /root/go/bin/gopls /usr/bin/gopls\n","\n","# Install gonb kernel configuration.\n","!gonb --install\n","\n","# Python code to replace ipython kernel with GoNB.\n","import os\n","import ipykernel_launcher\n","\n","call_kernel_code='''\n","import os\n","import sys\n","\n","connection_file = sys.argv[2]\n","os\n","try:\n"," os.execl(\"/usr/bin/gonb\", \"/usr/bin/gonb\", \"--kernel\", connection_file)\n","finally:\n"," from ipykernel import kernelapp as app\n"," app.launch_new_instance()\n","'''\n","new_file = '/tmp/gonb_ipykernel_launcher.py'\n","# old_file = '/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py'\n","old_file = ipykernel_launcher.__file__\n","with open(new_file, 'w') as f:\n"," f.write(call_kernel_code)\n","os.replace(new_file, old_file)\n","\n","# Finally kill current kernel to force restart.\n","import os; import sys; sys.stdout.flush(); os.kill(os.getpid(), 9)\n"]},{"cell_type":"markdown","source":["The cell above will crash the current kernel after replacing it with GoNB. It's normal. Run it once only, it takes a couple of minutes. After that you will be running a GoNB kernel."],"metadata":{"id":"lbPHZ_rjOavo"}},{"cell_type":"markdown","source":["## Demo\n","\n","From here below you can delete and put your own code.\n","\n","\n","First ..."],"metadata":{"id":"izIU9VTs-Fc4"}},{"cell_type":"code","source":["%%\n","fmt.Printf(\"Hello World!\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"XH7zQH3D7TmR","executionInfo":{"status":"ok","timestamp":1676196232052,"user_tz":-60,"elapsed":479,"user":{"displayName":"Jan Pfeifer","userId":"08334700909596354782"}},"outputId":"8058bddd-9449-491c-900f-5488f823e7bf"},"execution_count":2,"outputs":[{"output_type":"stream","name":"stdout","text":["Hello World!"]}]},{"cell_type":"code","source":["import \"bytes\"\n","import svgo \"github.com/ajstarks/svgo\"\n","import \"github.com/janpfeifer/gonb/gonbui\"\n","\n","func Shining(width, height int) string {\n"," buf := bytes.NewBuffer(nil)\n"," canvas := svgo.New(buf)\n"," xp := []int{50, 70, 70, 50, 30, 30}\n"," yp := []int{40, 50, 75, 85, 75, 50}\n"," xl := []int{0, 0, 50, 100, 100}\n"," yl := []int{100, 40, 10, 40, 100}\n"," bgcolor := \"rgb(227,78,25)\"\n"," bkcolor := \"rgb(153,29,40)\"\n"," stcolor := \"rgb(65,52,44)\"\n"," stwidth := 12\n"," stylefmt := \"stroke:%s;stroke-width:%d;fill:%s\"\n"," canvas.Start(width, height)\n"," canvas.Def()\n"," canvas.Gid(\"unit\")\n"," canvas.Polyline(xl, yl, \"fill:none\")\n"," canvas.Polygon(xp, yp)\n"," canvas.Gend()\n"," canvas.Gid(\"runit\")\n"," canvas.TranslateRotate(150, 180, 180)\n"," canvas.Use(0, 0, \"#unit\")\n"," canvas.Gend()\n"," canvas.Gend()\n"," canvas.DefEnd()\n"," canvas.Rect(0, 0, width, height, \"fill:\"+bgcolor)\n"," canvas.Gstyle(fmt.Sprintf(stylefmt, stcolor, stwidth, bkcolor))\n"," for y := 0; y < height; y += 130 {\n"," for x := -50; x < width; x += 100 {\n"," canvas.Use(x, y, \"#unit\")\n"," canvas.Use(x, y, \"#runit\")\n"," }\n"," } \n"," canvas.Gend()\n"," canvas.End()\n"," return buf.String()\n","}\n","\n","%%\n","gonbui.DisplaySVG(Shining(500, 500))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":521},"id":"nqvhyQ-F_0kA","executionInfo":{"status":"ok","timestamp":1676196354972,"user_tz":-60,"elapsed":960,"user":{"displayName":"Jan Pfeifer","userId":"08334700909596354782"}},"outputId":"792f8845-b53f-4b50-cd8b-90f95b75f0dd"},"execution_count":4,"outputs":[{"output_type":"display_data","data":{"text/html":["
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"]},"metadata":{}}]},{"cell_type":"code","source":["import \"github.com/benc-uk/gofract/pkg/fractals\"\n","import \"github.com/benc-uk/gofract/pkg/colors\"\n","\n","%%\n","imgWidth := 320\n","\n","// Default fractal\n","f := fractals.Fractal{\n"," FractType: \"mandelbrot\",\n"," Center: fractals.ComplexPair{-0.6, 0.0},\n"," MagFactor: 1.0,\n"," MaxIter: 90,\n"," W: 3.0,\n"," H: 2.0,\n"," ImgWidth: imgWidth,\n"," JuliaSeed: fractals.ComplexPair{0.355, 0.355},\n"," InnerColor: \"#000000\",\n"," FullScreen: false,\n"," ColorRepeats: 2,\n","}\n","gradient := colors.GradientTable{}\n","gradient.AddToTable(\"#000762\", 0.0)\n","gradient.AddToTable(\"#0B48C3\", 0.2)\n","gradient.AddToTable(\"#ffffff\", 0.4)\n","gradient.AddToTable(\"#E3A000\", 0.5)\n","gradient.AddToTable(\"#000762\", 0.9)\n","imgHeight := int(float64(imgWidth) * float64(f.H/f.W))\n","img := image.NewRGBA(image.Rect(0, 0, f.ImgWidth, imgHeight))\n","lastRenderTime := f.Render(img, gradient)\n","fmt.Printf(\"lastRenderTime=%v\\n\", lastRenderTime)\n","gonbui.DisplayImage(img)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":247},"id":"d2Ne-RIYAk6z","executionInfo":{"status":"ok","timestamp":1676196406676,"user_tz":-60,"elapsed":6767,"user":{"displayName":"Jan Pfeifer","userId":"08334700909596354782"}},"outputId":"dbca57ca-7e1b-4ea6-941b-a42038740b55"},"execution_count":5,"outputs":[{"output_type":"stream","name":"stdout","text":["lastRenderTime=15.59365\n"]},{"output_type":"display_data","data":{"image/png":"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"},"metadata":{}}]},{"cell_type":"code","source":["!*go get -u github.com/erkkah/margaid@d60b2efd2f5acc5d8fbbe13eaf85f1532e11a2fb"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"X1K-fZhMAu1m","executionInfo":{"status":"ok","timestamp":1676196411312,"user_tz":-60,"elapsed":2903,"user":{"displayName":"Jan Pfeifer","userId":"08334700909596354782"}},"outputId":"b815aec7-8daa-4d8d-a8e0-87fcd59115f6"},"execution_count":6,"outputs":[{"output_type":"stream","name":"stderr","text":["go: downloading github.com/erkkah/margaid v0.1.1-0.20230128143048-d60b2efd2f5a\n","go: added github.com/erkkah/margaid v0.1.1-0.20230128143048-d60b2efd2f5a\n"]}]},{"cell_type":"code","source":["import \"bytes\"\n","import \"github.com/janpfeifer/gonb/gonbui\"\n","import mg \"github.com/erkkah/margaid\"\n","\n","func mgPlot(width, height int) string {\n"," randomSeries := mg.NewSeries()\n"," rand.Seed(time.Now().Unix())\n"," for i := float64(0); i < 10; i++ {\n"," randomSeries.Add(mg.MakeValue(i+1, 200*rand.Float64()))\n"," }\n","\n"," testSeries := mg.NewSeries()\n"," multiplier := 2.1\n"," v := 0.33\n"," for i := float64(0); i < 10; i++ {\n"," v *= multiplier\n"," testSeries.Add(mg.MakeValue(i+1, v))\n"," }\n","\n"," diagram := mg.New(width, height,\n"," mg.WithAutorange(mg.XAxis, testSeries),\n"," mg.WithAutorange(mg.YAxis, testSeries),\n"," mg.WithAutorange(mg.Y2Axis, testSeries),\n"," mg.WithProjection(mg.YAxis, mg.Log),\n"," mg.WithInset(70),\n"," mg.WithPadding(2),\n"," mg.WithColorScheme(90),\n"," mg.WithBackgroundColor(\"#f8f8f8\"),\n"," )\n","\n"," diagram.Line(testSeries, mg.UsingAxes(mg.XAxis, mg.YAxis), mg.UsingMarker(\"square\"), mg.UsingStrokeWidth(1))\n"," diagram.Smooth(testSeries, mg.UsingAxes(mg.XAxis, mg.Y2Axis), mg.UsingStrokeWidth(3.14))\n"," diagram.Smooth(randomSeries, mg.UsingAxes(mg.XAxis, mg.YAxis), mg.UsingMarker(\"filled-circle\"))\n"," diagram.Axis(testSeries, mg.XAxis, diagram.ValueTicker('f', 0, 10), false, \"X\")\n"," diagram.Axis(testSeries, mg.YAxis, diagram.ValueTicker('f', 1, 2), true, \"Y\")\n","\n"," diagram.Frame()\n"," diagram.Title(\"A diagram of sorts 📊 📈\")\n"," buf := bytes.NewBuffer(nil)\n"," diagram.Render(buf)\n"," return buf.String()\n","}\n","\n","%%\n","gonbui.DisplaySVG(mgPlot(640, 480))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":501},"id":"Gc9kRoENA8yv","executionInfo":{"status":"ok","timestamp":1676196412109,"user_tz":-60,"elapsed":799,"user":{"displayName":"Jan Pfeifer","userId":"08334700909596354782"}},"outputId":"cf963d37-6497-43f1-e5f0-2a5151152a40"},"execution_count":7,"outputs":[{"output_type":"display_data","data":{"text/html":["
12345678910X1.02.04.08.016.032.064.0128.0256.0512.0YA diagram of sorts 📊 📈
"]},"metadata":{}}]},{"cell_type":"markdown","source":["# More ... and Help"],"metadata":{"id":"kE40IkXiBMVo"}},{"cell_type":"code","source":["%help"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"DMucr82cBItc","executionInfo":{"status":"ok","timestamp":1676196416166,"user_tz":-60,"elapsed":3,"user":{"displayName":"Jan Pfeifer","userId":"08334700909596354782"}},"outputId":"67065c5e-43f4-4164-8773-c509ae333216"},"execution_count":8,"outputs":[{"output_type":"stream","name":"stdout","text":["GoNB is a Go kernel that compiles and executed on-the-fly Go code. \n","\n","When executing a cell, *GoNB* will save the cell contents (except non-Go commands see\n","below) into a \"main.go\" file, compile and execute it.\n","\n","It also saves any global declarations (imports, functions, types, variables, constants)\n","and reuse them at the next cell execution -- so you can define a function in one\n","cell, and reuse in the next one. Just the \"func main()\" is not reused.\n","\n","A \"hello world\" example would look like:\n","\n","\tfunc main() {\n","\t\tfmt.Printf(\"Hello world!\\n\");\n","\t}\n","\n","But to avoid having to type \"func main()\" all the time, you can use \"%%\" and everything\n","after is wrapped inside a \"func main() { ... }\". So our revised \"hello world\" looks like:\n","\n","\t%%\n","\tfmt.Printf(\"Hello world!\\n\")\n","\n","\n","- \"init()\" functions: since there is always only one definition per function name, \n"," it's not possible for each cell to have it's own init() function. Instead GoNB\n"," converts any function named \"init_()\" to \"init()\" before compiling and\n"," executing. This way each cell can create its own \"init_...()\" and have it called\n"," at every cell execution.\n","\n","Special non-Go commands: \n","\n","- \"%main\" or \"%%\": Marks the lines as follows to be wrapped in a \"func main() {...}\" during \n"," execution. A shortcut to quickly execute code. It also automatically includes \"flag.Parse()\"\n"," as the very first statement.\n","- \"%args\": Sets arguments to be passed when executing the Go code. This allows one to\n"," use flags as a normal program.\n","- \"%autoget\" and \"%noautoget\": Default is \"%autoget\", which automatically does \"go get\" for\n"," packages not yet available.\n","- \"%env VAR value\": Sets the environment variable VAR to the given value. These variables\n"," will be available both for Go code as well as for shell scripts.\n","- \"%reset\": clears all memorized declarations (imports, functions, variables, types and \n"," constants).\n","- \"%with_inputs\": will prompt for inputs for the next shell command. Use this if\n"," the next shell command (\"!\") you execute reads the stdin. Jupyter will require\n"," you to enter one last value after the shell script executes.\n","- \"%with_password\": will prompt for a password passed to the next shell command.\n"," Do this is if your next shell command requires a password.\n","\n","Executing shell commands:\n","\n","- \"!\": executes the given command on a new shell. It makes it easy to run\n"," commands on the kernels box, for instance to install requirements, or quickly\n"," check contents of directories or files. Lines ending in \"\\\" are continued on\n"," the next line -- so multi-line commands can be entered. But each command is\n"," executed in its own shell, that is, variables and state is not carried over.\n","- \"!*\": same as \"!\" except it first changes directory to\n"," the temporary directory used to compile the go code -- the latest execution\n"," is always saved in the file \"main.go\". It's also where the \"go.mod\" file for\n"," the notebook is created and maintained. Useful for manipulating \"go.mod\",\n"," for instance to get a package from some specific version, something \n"," like \"!*go get github.com/my/package@v3\".\n"]}]}]} +{ + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "provenance": [] + }, + "kernelspec": { + "name": "gonb", + "display_name": "Go (gonb)" + } + }, + "cells": [ + { + "cell_type": "markdown", + "source": [ + "# GoNB - A Go Notebook Kernel for Jupyter\n", + "\n", + "See the [tutorial in github](https://github.com/janpfeifer/gonb/blob/e15ac2e8e3fe/examples/tutorial.ipynb). The repository is in [github.com/janpfeifer/gonb](https://github.com/janpfeifer/gonb).\n", + "\n", + "\n", + "## Installation in Google's Colab\n", + "\n", + "1. Run the installation cell just below once only. It will install Go, GoNB and a couple of Go tools needed to provide auto-complete.\n", + "\n", + " It takes a couple of minutes ... but only needs to be done once.\n", + "\n", + " When creating other GoNB notebooks with Google's Colab, you will have to copy the cell below (or do something similar).\n", + "\n", + "2. Restart the session: under `Runtime` menu, click on `Restart Session`\n", + "\n", + "3. After it restarts, if you should be able to change the runtim to **GoNB**. Under the `Runtime` menu, click on the entry `Change Runtime Type`. Don't change the hardware accelerator (otherwise you'll have to restart the installation), but change the runtime type to `Go (gonb)`\n", + "\n", + "4. Restart the session again: under `Runtime` menu, click on `Restart Session`\n", + "\n", + "**Disclaimer**: this is highly not documented or official, but seems to be supported by Colab (it works). This method has broken before without notice. Please reach out to project in [github.com/janpfeifer/gonb](https://github.com/janpfeifer/gonb) if there are any issues.\n", + "\n", + "\n" + ], + "metadata": { + "id": "FWzjioUI63tT" + } + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "3PaXSu67xkrg", + "outputId": "bc7a90b5-cd54-4091-8c26-d69212559a13", + "colab": { + "base_uri": "https://localhost:8080/" + }, + "cellView": "form" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Installing go ...env: GOROOT=/content/go\n", + " done.\n", + "go version go1.23.1 linux/amd64\n", + "Installing gonb ... done.\n", + "Installing goimports ... done.\n", + "Installing gopls ... done.\n", + "I0923 20:27:38.817564 7307 install.go:121] \u001b[7;39;32m[a14e2312]\u001b[0m Go (gonb) kernel configuration installed in \"/root/.local/share/jupyter/kernels/gonb/kernel.json\".\n", + "Done!\n" + ] + } + ], + "source": [ + "#@title Install Go, `goimports` and GoNB code.\n", + "\n", + "# Install Go and goimports.\n", + "!echo -n \"Installing go ...\"\n", + "!mkdir -p cache\n", + "!wget -q -O cache/go.tar.gz 'https://go.dev/dl/go1.23.1.linux-amd64.tar.gz'\n", + "!tar xzf cache/go.tar.gz\n", + "%env GOROOT=/content/go\n", + "!ln -sf \"/content/go/bin/go\" /usr/bin/go\n", + "!echo \" done.\"\n", + "!go version\n", + "\n", + "# Install gonb, goimports, gopls.\n", + "!echo -n \"Installing gonb ...\"\n", + "!go install github.com/janpfeifer/gonb@latest >& /tmp/output || cat /tmp/output\n", + "!echo \" done.\"\n", + "!ln -sf /root/go/bin/gonb /usr/bin/gonb\n", + "\n", + "!echo -n \"Installing goimports ...\"\n", + "!go install golang.org/x/tools/cmd/goimports@latest >& /tmp/output || cat /tmp/output\n", + "!echo \" done.\"\n", + "!ln -sf /root/go/bin/goimports /usr/bin/goimports\n", + "\n", + "!echo -n \"Installing gopls ...\"\n", + "!go install golang.org/x/tools/gopls@latest >& /tmp/output || cat /tmp/output\n", + "!echo \" done.\"\n", + "!ln -sf /root/go/bin/gopls /usr/bin/gopls\n", + "\n", + "# Install gonb kernel configuration.\n", + "!gonb --install --logtostderr\n", + "!echo \"Done!\"" + ] + }, + { + "cell_type": "markdown", + "source": [ + "The cell above shoudl be run only once, and then followed by a change of runtime to `Go (gonb)`. See detailed instructions above." + ], + "metadata": { + "id": "lbPHZ_rjOavo" + } + }, + { + "cell_type": "markdown", + "source": [ + "## Demo\n", + "\n", + "From here below you can delete and put your own code.\n", + "\n", + "\n", + "First ..." + ], + "metadata": { + "id": "izIU9VTs-Fc4" + } + }, + { + "cell_type": "code", + "source": [ + "%%\n", + "fmt.Printf(\"Hello World!\")" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "XH7zQH3D7TmR", + "outputId": "362d4597-e91d-491f-c72a-fc08e3685abf" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Hello World!" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "import \"bytes\"\n", + "import svgo \"github.com/ajstarks/svgo\"\n", + "import \"github.com/janpfeifer/gonb/gonbui\"\n", + "\n", + "func Shining(width, height int) string {\n", + " buf := bytes.NewBuffer(nil)\n", + " canvas := svgo.New(buf)\n", + " xp := []int{50, 70, 70, 50, 30, 30}\n", + " yp := []int{40, 50, 75, 85, 75, 50}\n", + " xl := []int{0, 0, 50, 100, 100}\n", + " yl := []int{100, 40, 10, 40, 100}\n", + " bgcolor := \"rgb(227,78,25)\"\n", + " bkcolor := \"rgb(153,29,40)\"\n", + " stcolor := \"rgb(65,52,44)\"\n", + " stwidth := 12\n", + " stylefmt := \"stroke:%s;stroke-width:%d;fill:%s\"\n", + " canvas.Start(width, height)\n", + " canvas.Def()\n", + " canvas.Gid(\"unit\")\n", + " canvas.Polyline(xl, yl, \"fill:none\")\n", + " canvas.Polygon(xp, yp)\n", + " canvas.Gend()\n", + " canvas.Gid(\"runit\")\n", + " canvas.TranslateRotate(150, 180, 180)\n", + " canvas.Use(0, 0, \"#unit\")\n", + " canvas.Gend()\n", + " canvas.Gend()\n", + " canvas.DefEnd()\n", + " canvas.Rect(0, 0, width, height, \"fill:\"+bgcolor)\n", + " canvas.Gstyle(fmt.Sprintf(stylefmt, stcolor, stwidth, bkcolor))\n", + " for y := 0; y < height; y += 130 {\n", + " for x := -50; x < width; x += 100 {\n", + " canvas.Use(x, y, \"#unit\")\n", + " canvas.Use(x, y, \"#runit\")\n", + " }\n", + " }\n", + " canvas.Gend()\n", + " canvas.End()\n", + " return buf.String()\n", + "}\n", + "\n", + "%%\n", + "gonbui.DisplaySVG(Shining(500, 500))" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 522 + }, + "id": "nqvhyQ-F_0kA", + "outputId": "ca3add57-fee4-48bd-a4db-e725b46a1c83" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/html": [ + "
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" + ] + }, + "metadata": {} + } + ] + }, + { + "cell_type": "code", + "source": [ + "import \"github.com/benc-uk/gofract/pkg/fractals\"\n", + "import \"github.com/benc-uk/gofract/pkg/colors\"\n", + "\n", + "%%\n", + "imgWidth := 320\n", + "\n", + "// Default fractal\n", + "f := fractals.Fractal{\n", + " FractType: \"mandelbrot\",\n", + " Center: fractals.ComplexPair{-0.6, 0.0},\n", + " MagFactor: 1.0,\n", + " MaxIter: 90,\n", + " W: 3.0,\n", + " H: 2.0,\n", + " ImgWidth: imgWidth,\n", + " JuliaSeed: fractals.ComplexPair{0.355, 0.355},\n", + " InnerColor: \"#000000\",\n", + " FullScreen: false,\n", + " ColorRepeats: 2,\n", + "}\n", + "gradient := colors.GradientTable{}\n", + "gradient.AddToTable(\"#000762\", 0.0)\n", + "gradient.AddToTable(\"#0B48C3\", 0.2)\n", + "gradient.AddToTable(\"#ffffff\", 0.4)\n", + "gradient.AddToTable(\"#E3A000\", 0.5)\n", + "gradient.AddToTable(\"#000762\", 0.9)\n", + "imgHeight := int(float64(imgWidth) * float64(f.H/f.W))\n", + "img := image.NewRGBA(image.Rect(0, 0, f.ImgWidth, imgHeight))\n", + "lastRenderTime := f.Render(img, gradient)\n", + "fmt.Printf(\"lastRenderTime=%v\\n\", lastRenderTime)\n", + "gonbui.DisplayImage(img)" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 248 + }, + "id": "d2Ne-RIYAk6z", + "outputId": "b2aa576e-71da-48ab-866d-53f33495a846" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "lastRenderTime=26.491124\n" + ] + }, + { + "output_type": "display_data", + "data": { + "image/png": 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" + }, + "metadata": {} + } + ] + }, + { + "cell_type": "code", + "source": [ + "import \"bytes\"\n", + "import \"github.com/janpfeifer/gonb/gonbui\"\n", + "import mg \"github.com/erkkah/margaid\"\n", + "\n", + "func mgPlot(width, height int) string {\n", + " randomSeries := mg.NewSeries()\n", + " rand.Seed(time.Now().Unix())\n", + " for i := float64(0); i < 10; i++ {\n", + " randomSeries.Add(mg.MakeValue(i+1, 200*rand.Float64()))\n", + " }\n", + "\n", + " testSeries := mg.NewSeries()\n", + " multiplier := 2.1\n", + " v := 0.33\n", + " for i := float64(0); i < 10; i++ {\n", + " v *= multiplier\n", + " testSeries.Add(mg.MakeValue(i+1, v))\n", + " }\n", + "\n", + " diagram := mg.New(width, height,\n", + " mg.WithAutorange(mg.XAxis, testSeries),\n", + " mg.WithAutorange(mg.YAxis, testSeries),\n", + " mg.WithAutorange(mg.Y2Axis, testSeries),\n", + " mg.WithProjection(mg.YAxis, mg.Log),\n", + " mg.WithInset(70),\n", + " mg.WithPadding(2),\n", + " mg.WithColorScheme(90),\n", + " mg.WithBackgroundColor(\"#f8f8f8\"),\n", + " )\n", + "\n", + " diagram.Line(testSeries, mg.UsingAxes(mg.XAxis, mg.YAxis), mg.UsingMarker(\"square\"), mg.UsingStrokeWidth(1))\n", + " diagram.Smooth(testSeries, mg.UsingAxes(mg.XAxis, mg.Y2Axis), mg.UsingStrokeWidth(3.14))\n", + " diagram.Smooth(randomSeries, mg.UsingAxes(mg.XAxis, mg.YAxis), mg.UsingMarker(\"filled-circle\"))\n", + " diagram.Axis(testSeries, mg.XAxis, diagram.ValueTicker('f', 0, 10), false, \"X\")\n", + " diagram.Axis(testSeries, mg.YAxis, diagram.ValueTicker('f', 1, 2), true, \"Y\")\n", + "\n", + " diagram.Frame()\n", + " diagram.Title(\"A diagram of sorts 📊 📈\")\n", + " buf := bytes.NewBuffer(nil)\n", + " diagram.Render(buf)\n", + " return buf.String()\n", + "}\n", + "\n", + "%%\n", + "gonbui.DisplaySVG(mgPlot(640, 480))" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 502 + }, + "id": "Gc9kRoENA8yv", + "outputId": "513a555b-d37d-4a03-9f5f-9e919b6801c1" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/html": [ + "
12345678910X1.02.04.08.016.032.064.0128.0256.0512.0YA diagram of sorts 📊 📈
" + ] + }, + "metadata": {} + } + ] + }, + { + "cell_type": "code", + "source": [ + "import (\n", + "\t\"math/rand\"\n", + "\t\"github.com/go-echarts/go-echarts/v2/charts\"\n", + "\t\"github.com/go-echarts/go-echarts/v2/opts\"\n", + "\t\"github.com/go-echarts/go-echarts/v2/types\"\n", + " gonb_echarts \"github.com/janpfeifer/gonb-echarts\"\n", + " \"github.com/janpfeifer/must\"\n", + ")\n", + "\n", + "func toLineData[In any](data []In) []opts.LineData {\n", + " r := make([]opts.LineData, len(data))\n", + " for ii, v := range data {\n", + " r[ii].Value = v\n", + " }\n", + " return r\n", + "}\n", + "\n", + "%%\n", + "stackedLine := charts.NewLine()\n", + "stackedLine.SetGlobalOptions(\n", + " charts.WithTitleOpts(opts.Title{Title: \"Stacked Line\",}),\n", + " charts.WithTooltipOpts(opts.Tooltip{Show: opts.Bool(true), Trigger: \"axis\"}),\n", + ")\n", + "seriesOpt := charts.WithLineChartOpts(opts.LineChart{\n", + " Stack: \"Total\",\n", + " ShowSymbol: opts.Bool(true),\n", + "})\n", + "\n", + "stackedLine.\n", + " SetGlobalOptions(charts.WithYAxisOpts(opts.YAxis{Type: \"value\"}))\n", + "stackedLine.\n", + " SetXAxis([]string{\"Mon\", \"Tue\", \"Wed\", \"Thu\", \"Fri\", \"Sat\", \"Sun\"}).\n", + " AddSeries(\"Email\", toLineData([]int{120, 132, 101, 134, 90, 230, 210}), seriesOpt).\n", + " AddSeries(\"Union Ads\", toLineData([]int{220, 182, 191, 234, 290, 330, 310}), seriesOpt).\n", + " AddSeries(\"Video Ads\", toLineData([]int{150, 232, 201, 154, 190, 330, 410}), seriesOpt).\n", + " AddSeries(\"Direct\", toLineData([]int{320, 332, 301, 334, 390, 330, 320}), seriesOpt).\n", + " AddSeries(\"Search Engine\", toLineData([]int{820, 932, 901, 934, 1290, 1330, 1320}), seriesOpt)\n", + "\n", + "must.M(gonb_echarts.Display(stackedLine, \"width: 1024px; height:400px; background: white;\"))" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 417 + }, + "id": "piKyK1e9LmNu", + "outputId": "c59c6fd4-9db1-4891-e946-475e9fa8e067" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/html": [ + "
" + ] + }, + "metadata": {} + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "# More ... and Help" + ], + "metadata": { + "id": "kE40IkXiBMVo" + } + }, + { + "cell_type": "code", + "source": [ + "%help" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 1000 + }, + "id": "DMucr82cBItc", + "outputId": "b8612706-f610-4895-cffa-fe704eeaca8b" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/markdown": "## GoNB Help Page\n\n**GoNB** is a Go kernel that compiles and executes on-the-fly Go code.\n\nWhen executing a cell, **GoNB** will save the cell contents (except non-Go commands see\nbelow) into a `main.go` file, compile and execute it.\n\nIt also saves any global declarations (imports, functions, types, variables, constants)\nand reuse them at the next cell execution -- so you can define a function in one\ncell, and reuse in the next one. Just the `func main()` is not reused.\n\nA `hello world` example would look like:\n\n```go\nfunc main() {\n fmt.Printf(`Hello world!\\n`);\n}\n\n```\n\nBut to avoid having to type `func main()` all the time, you can use `%%` and everything\nafter is wrapped inside a `func main() { ... }`. \nSo our revised `hello world` looks like:\n\n```go\n%%\nfmt.Printf(`Hello world!\\n`)\n\n```\n\n\n### Init Functions -- `func init()`\n\nSince there is always only one definition per function name, it's not possible for\neach cell to have its own init() function. \nInstead, **GoNB** converts any function named `init_something()` to `init()` before \ncompiling and executing. \nThis way each cell can create its own `init_...()` and have it called at every cell execution.\n\n\n### Special non-Go Commands\n\n- `%% []` or `%main []`: Marks the lines as follows to be wrapped in a `func main() {...}` during\n execution. A shortcut to quickly execute code. It also automatically includes `flag.Parse()`\n as the very first statement. Anything after`%%` or `%main` are taken as arguments\n to be passed to the program -- it resets previous values given by `%args`.\n- `%args `: Sets arguments to be passed when executing the Go code. This allows one to\n use flags as a normal program. Notice that if a value after `%%` or `%main` is given, it will\n overwrite the values here.\n- `%exec []`: this will call the function `my_func()`, and optionally set the program arguments.\n Behind the scenes it creates a trivial `func main()` that parses the flags and calls `my_func()` (without any\n parameters or return values).\n- `%autoget` and `%noautoget`: Default is `%autoget`, which automatically does `go get` for\n packages not yet available.\n- `%cd []`: Change current directory of the Go kernel, and the directory from where\n the cells are executed. If no directory is given it reports the current directory.\n- `%env VAR value`: Sets the environment variable VAR to the given value. These variables\n will be available both for Go code and for shell scripts.\n- `%goflags `: Configures list of extra arguments to pass to `go build` when compiling the\n code for execution of a cell.\n If no values are given, it simply shows the current setting.\n To reset its value, use `%goflags \"\"\"`.\n See example on how to use this in the [tutorial](https://github.com/janpfeifer/gonb/blob/main/examples/tutorial.ipynb). \n- `%with_inputs`: will prompt for inputs for the next shell command. Use this if\n the next shell command (`!`) you execute reads the stdin. Jupyter will require\n you to enter one last value after the shell script executes.\n- `%with_password`: will prompt for a password passed to the next shell command.\n Do this is if your next shell command requires a password.\n\n**Notes**: \n\n1. The special commands below can be used in the start of the line as is, or prefixed by a `//gonb:`, which may be easier\non some IDEs if editing the code externally (since these special commands are not proper Go). \nSo `//gonb:%%` is the same as `%%` \n2. All these commands are executed **before** any Go code in the same cell.\n\n\n### Managing Memorized Definitions\n\n- `%list` (or `%ls`): Lists all memorized definitions (imports, constants, types, variables and\n functions) that are carried from one cell to another.\n- `%remove ` (or `%rm `): Removes (forgets) given definition(s). Use as key the\n value(s) listed with `%ls`.\n- `%reset [go.mod]` clears all memorized definitions (imports, constants, types, functions, etc.)\n as well as re-initializes the `go.mod` file. \n If the optional `go.mod` parameter is given, it will re-initialize only the `go.mod` file -- \n useful when testing different set up of versions of libraries.\n\n\n### Executing Shell Commands\n\n- `!`: executes the given command on a new shell. It makes it easy to run\n commands on the kernels box, for instance to install requirements, or quickly\n check contents of directories or files. Lines ending in `\\` are continued on\n the next line -- so multi-line commands can be entered. But each command is\n executed in its own shell, that is, variables and state is not carried over.\n- `!*`: same as `!` except it first changes directory to\n the temporary directory used to compile the go code -- the latest execution\n is always saved in the file `main.go`. It's also where the `go.mod` file for\n the notebook is created and maintained. Useful for manipulating `go.mod`,\n for instance to get a package from some specific version, something\n like `!*go get github.com/my/package@v3`.\n\nNotice that when the cell is executed, first all shell commands are executed, and only after that, if there is\nany Go code in the cell, it is executed.\n\n### Running a Debugger\n\nWhile **GoNB** doesn't (yet) talk the debug protocol with JupyterLab, it's easy to start a GUI debugger\nfrom a cell, if being executed on the same machine as the browser.\n\nThe common Go debugger recommendation is [delve](https://github.com/go-delve/delve), and in particular its front-end\n[gdlv](https://github.com/aarzilli/gdlv). And to make it simpler **GoNB** includes a small wrapper script \n[`ndlv`](https://github.com/janpfeifer/gonb/blob/main/cmd/ndlv/ndlv) to\nset the directory and program name to the last cell executed. Copy or link that script somewhere in your `PATH`\n(maybe `${HOME}/bin` if you have such directory set up).\n\nTo open the debugger, after executing a cell you want to debug, you create and execute a new cell with this single shell command:\n\n```\n!ndlv\n```\n\n### Tracking of Go Files In Development:\n\nA convenient way to develop programs or libraries in **GoNB** is to use replace\nrules in **GoNB**'s `go.mod` to your program or library being developed and test\nyour program from **GoNB** -- see the \n[Tutorial]((https://github.com/janpfeifer/gonb/blob/main/examples/tutorial.ipynb))'s\nsection \"Developing Go libraries with a notebook\" for different ways of achieving this.\n\nTo manipulate the list of files tracked for changes:\n\n- `%track [file_or_directory]`: add file or directory to list of tracked files,\n which are monitored by **GoNB** (and 'gopls') for auto-complete or contextual help.\n If no file is given, it lists the currently tracked files.\n- `%untrack [file_or_directory][...]`: remove file or directory from list of tracked files.\n If suffixed with `...` it will remove all files prefixed with the string given (without the\n `...`). If no file is given, it lists the currently tracked files.\n\n\n### Environment Variables\n\nFor convenience, **GoNB** defines the following environment variables -- available for the shell\nscripts (`!` and `!*`) and for the Go cells:\n\n- `GONB_DIR`: the directory where commands are executed from. This can be changed with `%cd`.\n- `GONB_TMP_DIR`: the directory where the temporary Go code, with the cell code, is stored\n and compiled. This is the directory where `!*` scripts are executed. It only changes when a kernel\n is restarted, and a new temporary directory is created.\n- `GONB_PIPE`: is the _named pipe_ directory used to communicate rich content (HTML, images)\n to the kernel. Only available for _Go_ cells, and a new one is created at every execution.\n This is used by the `**GoNB**ui`` functions described above, and doesn't need to be accessed directly.\n\n### Widgets\n\nThe package `gonbui/widgets` offers widgets that can be used to interact in a more\ndynamic way, using the HTML element in the browser. E.g.: buttons, sliders.\n\nIt's not necessary to do anything, but, to help debug the communication system\nwith the front-end, **GoNB** offers a couple of special commands:\n\n- `%widgets` - install the javascript needed to communicate with the frontend.\n This is usually not needed, since it happens automatically when using Widgets.\n- `%widgets_hb` - send a _heartbeat_ signal to the front-end and wait for the\n reply.\n Used for debugging only.\n\n### Writing for WASM (WebAssembly) (Experimental)\n\n**GoNB** can also compile to WASM and run in the notebook. This is experimental, and likely to change\n(feedback is very welcome), and can be used to write interactive widgets in Go, in the notebook.\n\nWhen a cell with `%wasm` is executed, a temporary directory is created under the Jupyter root directory\ncalled `jupyter_files//` and the cell is compiled to a wasm file and put in that \ndirectory.\n\nThen **GONB** outputs the javascript needed to run the compiled wam.\n\nIn the Go code, the following extra constants/variables are created in the global namespace, and can be used\nin your Go code:\n\n- `GonbWasmDir`, `GonbWasmUrl`: the directory and url (served by Jupyter) where the generated `.wasm` files are read.\n Potentially, the user can use it to serve other files.\n These are unique for the kernel, but shared among cells.\n- `GonbWasmDivId`: When a `%wasm` cell is executed, an empty `
\">
`\n is created with a unique id -- every cell will have a different one.\n This is where the Wasm code can dynamically create content.\n\nThe following environment variables are set when `%wasm` is created:\n\n- `GONB_WASM_SUBDIR`, `GONB_WASM_URL`: the directory and url (served by Jupyter) where the generated `.wasm` files are read.\n Potentially, the user can use it to serve other files.\n These environment variables are available for shell scripts (`!...` and `!*...` special commands) and non-wasm \n programs if they want to serve different files from there.\n\n\n### Writing Tests and Benchmarks\n\nIf a cell includes the `%test` command (anywhere in cell), it is compiled with `go test`\n(as opposed to `go build`).\nThis can be very useful both to demonstrate tests, or simply help develop/debug them in a notebook.\n\nIf `%test` is given without any flags, it uses by default the flags `-test.v` (verbose) and `-test.run` defined\nwith the list of the tests defined in the current cell. \nThat is, it will run only the tests in the current cell. \nAlso, if there are any benchmarks in the current cell, it appends the flag `-test.bench=.` and runs the benchmarks\ndefined in the current cell.\n\nAlternatively one can use `%test `, and the `flags` are passed to the binary compiled with `go test`. \nRemember that test flags require to be prefixed with `test.`. \nSo for a verbose output, use `%test -test.v`. \nFor benchmarks, run `%test -test.bench=. -test.run=Benchmark`. \n\nSee examples in the [`gotest.ipynb` notebook here](https://github.com/janpfeifer/gonb/blob/main/examples/tests/gotest.ipynb).\n\n\n### Cell Magic\n\nThe following are special commands that change how the cell is interpreted, so they are prefixed with `%%` (two '%'\nsymbols). They try to follow [IPython's Cell Magic](https://ipython.readthedocs.io/en/stable/interactive/magics.html#cell-magics).\n\nThey must always appear as the first line of the cell.\n\nThe contents in the cells are not assumed to be Go, so auto-complete and contextual help are disabled in those cells.\n\n#### `%%writefile`\n\n```\n%%writefile [-a] \n```\n\nWrite contents of the cell (except the first line with the '%%writefile') to the given ``. If `-a` is given\nit will append the cell contents to the file.\n\nThis can be handy if for instance the notebook needs to write a configuration file, or simply to dump the code inside\nthe cell into some file.\n\nFile path passes through a tilde (`~`) expansion to the user's home directory, as well as environment variable substitution (e.g.: `${HOME}` or `$MY_DIR/a/b`). \n\n### `%%script`, `%%bash` and `%%sh`\n\n```\n%%script \n```\n\nExecute `` and feed it (`STDIN`) with the contents of the cell. The `%%bash` and `%%sh` magic is an alias to `%%script bash` and `%%script sh` respectively.\n\nGenerally, a convenient way to run larger scripts.\n\n\n### Other\n\n- `%goworkfix`: work around 'go get' inability to handle 'go.work' files. If you are\n using 'go.work' file to point to locally modified modules, consider using this. It creates\n 'go mod edit --replace' rules to point to the modules pointed to the 'use' rules in 'go.work'\n file.\n It overwrites/updates 'replace' rules for those modules, if they already exist. See \n [tutorial](https://github.com/janpfeifer/gonb/blob/main/examples/tutorial.ipynb) for an example.\n\n### Links\n\n- [github.com/janpfeifer/gonb](https://github.com/janpfeifer/gonb) - GitHub page.\n- [Tutorial](https://github.com/janpfeifer/gonb/blob/main/examples/tutorial.ipynb).\n- [go.dev](https://pkg.go.dev/github.com/janpfeifer/gonb) package reference." + }, + "metadata": {} + } + ] + } + ] +} \ No newline at end of file