├── .gitignore ├── 1_Expand_and_Capture.ipynb ├── 2_Data_Exchange.ipynb ├── 3_SoS_Magics.html ├── 3_SoS_Magics.ipynb ├── 4_Notebook_to_Workflow.ipynb ├── 5_Workflow_features.ipynb ├── 6_Task.ipynb ├── Dockerfile ├── LICENSE ├── README.md ├── REQUIRE ├── python-and-julia.ipynb ├── python-and-r.ipynb └── sos-notebook.png /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | build/ 12 | develop-eggs/ 13 | dist/ 14 | downloads/ 15 | eggs/ 16 | .eggs/ 17 | lib/ 18 | lib64/ 19 | parts/ 20 | sdist/ 21 | var/ 22 | wheels/ 23 | *.egg-info/ 24 | .installed.cfg 25 | *.egg 26 | MANIFEST 27 | 28 | # PyInstaller 29 | # Usually these files are written by a python script from a template 30 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 31 | *.manifest 32 | *.spec 33 | 34 | # Installer logs 35 | pip-log.txt 36 | pip-delete-this-directory.txt 37 | 38 | # Unit test / coverage reports 39 | htmlcov/ 40 | .tox/ 41 | .coverage 42 | .coverage.* 43 | .cache 44 | nosetests.xml 45 | coverage.xml 46 | *.cover 47 | .hypothesis/ 48 | .pytest_cache/ 49 | 50 | # Translations 51 | *.mo 52 | *.pot 53 | 54 | # Django stuff: 55 | *.log 56 | local_settings.py 57 | db.sqlite3 58 | 59 | # Flask stuff: 60 | instance/ 61 | .webassets-cache 62 | 63 | # Scrapy stuff: 64 | .scrapy 65 | 66 | # Sphinx documentation 67 | docs/_build/ 68 | 69 | # PyBuilder 70 | target/ 71 | 72 | # Jupyter Notebook 73 | .ipynb_checkpoints 74 | 75 | # pyenv 76 | .python-version 77 | 78 | # celery beat schedule file 79 | celerybeat-schedule 80 | 81 | # SageMath parsed files 82 | *.sage.py 83 | 84 | # Environments 85 | .env 86 | .venv 87 | env/ 88 | venv/ 89 | ENV/ 90 | env.bak/ 91 | venv.bak/ 92 | 93 | # Spyder project settings 94 | .spyderproject 95 | .spyproject 96 | 97 | # Rope project settings 98 | .ropeproject 99 | 100 | # mkdocs documentation 101 | /site 102 | 103 | # mypy 104 | .mypy_cache/ 105 | -------------------------------------------------------------------------------- /1_Expand_and_Capture.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "metadata": { 6 | "kernel": "SoS" 7 | }, 8 | "source": [ 9 | "# Working with subkernels" 10 | ] 11 | }, 12 | { 13 | "cell_type": "markdown", 14 | "metadata": { 15 | "kernel": "SoS" 16 | }, 17 | "source": [ 18 | "Unless you would like to start multiple versions of the same kernel or link a language module to a kernel that is not recognized by SoS, you can start a subkernel simply by selecting the language from the language dropdown to the top right corner of each cell." 19 | ] 20 | }, 21 | { 22 | "cell_type": "markdown", 23 | "metadata": { 24 | "kernel": "SoS" 25 | }, 26 | "source": [ 27 | "## Sending input to subkernel" 28 | ] 29 | }, 30 | { 31 | "cell_type": "markdown", 32 | "metadata": { 33 | "kernel": "SoS" 34 | }, 35 | "source": [ 36 | "The SoS language is based on Python 3.6+ so \n", 37 | "any python statements are acceptable\n" 38 | ] 39 | }, 40 | { 41 | "cell_type": "code", 42 | "execution_count": 1, 43 | "metadata": { 44 | "kernel": "SoS" 45 | }, 46 | "outputs": [], 47 | "source": [ 48 | "filename = '1_Expand_and_Capture.ipynb'" 49 | ] 50 | }, 51 | { 52 | "cell_type": "code", 53 | "execution_count": 2, 54 | "metadata": { 55 | "kernel": "Bash", 56 | "scrolled": true 57 | }, 58 | "outputs": [ 59 | { 60 | "name": "stdout", 61 | "output_type": "stream", 62 | "text": [ 63 | " 352 1_Expand_and_Capture.ipynb\n" 64 | ] 65 | } 66 | ], 67 | "source": [ 68 | "wc -l 1_Expand_and_Capture.ipynb" 69 | ] 70 | }, 71 | { 72 | "cell_type": "markdown", 73 | "metadata": { 74 | "kernel": "Bash" 75 | }, 76 | "source": [ 77 | "With magic `%expand`, cell content is expanded as Python f-string before sending to the subkernel" 78 | ] 79 | }, 80 | { 81 | "cell_type": "code", 82 | "execution_count": 3, 83 | "metadata": { 84 | "kernel": "Bash" 85 | }, 86 | "outputs": [ 87 | { 88 | "name": "stdout", 89 | "output_type": "stream", 90 | "text": [ 91 | " 352 1_Expand_and_Capture.ipynb\n" 92 | ] 93 | } 94 | ], 95 | "source": [ 96 | "%expand\n", 97 | "wc -l {filename}" 98 | ] 99 | }, 100 | { 101 | "cell_type": "code", 102 | "execution_count": 4, 103 | "metadata": { 104 | "kernel": "JavaScript" 105 | }, 106 | "outputs": [ 107 | { 108 | "data": { 109 | "text/plain": [ 110 | "{ cells: \n", 111 | " [ { cell_type: 'markdown', metadata: [Object], source: [Array] },\n", 112 | " { cell_type: 'markdown', metadata: [Object], source: [Array] },\n", 113 | " { cell_type: 'markdown', metadata: [Object], source: [Array] },\n", 114 | " { cell_type: 'markdown', metadata: [Object], source: [Array] },\n", 115 | " { cell_type: 'code',\n", 116 | " execution_count: 1,\n", 117 | " metadata: [Object],\n", 118 | " outputs: [],\n", 119 | " source: [Array] },\n", 120 | " { cell_type: 'code',\n", 121 | " execution_count: 2,\n", 122 | " metadata: [Object],\n", 123 | " outputs: [Array],\n", 124 | " source: [Array] },\n", 125 | " { cell_type: 'markdown', metadata: [Object], source: [Array] },\n", 126 | " { cell_type: 'code',\n", 127 | " execution_count: 3,\n", 128 | " metadata: [Object],\n", 129 | " outputs: [Array],\n", 130 | " source: [Array] },\n", 131 | " { cell_type: 'code',\n", 132 | " execution_count: 4,\n", 133 | " metadata: [Object],\n", 134 | " outputs: [Array],\n", 135 | " source: [Array] },\n", 136 | " { cell_type: 'markdown', metadata: [Object], source: [Array] },\n", 137 | " { cell_type: 'code',\n", 138 | " execution_count: 5,\n", 139 | " metadata: [Object],\n", 140 | " outputs: [Array],\n", 141 | " source: [Array] },\n", 142 | " { cell_type: 'code',\n", 143 | " execution_count: 6,\n", 144 | " metadata: [Object],\n", 145 | " outputs: [Array],\n", 146 | " source: [Array] },\n", 147 | " { cell_type: 'code',\n", 148 | " execution_count: 7,\n", 149 | " metadata: [Object],\n", 150 | " outputs: [Array],\n", 151 | " source: [Array] },\n", 152 | " { cell_type: 'code',\n", 153 | " execution_count: 8,\n", 154 | " metadata: [Object],\n", 155 | " outputs: [Array],\n", 156 | " source: [Array] } ],\n", 157 | " metadata: \n", 158 | " { kernelspec: { display_name: 'SoS', language: 'sos', name: 'sos' },\n", 159 | " language_info: \n", 160 | " { codemirror_mode: 'sos',\n", 161 | " file_extension: '.sos',\n", 162 | " mimetype: 'text/x-sos',\n", 163 | " name: 'sos',\n", 164 | " nbconvert_exporter: 'sos_notebook.converter.SoS_Exporter',\n", 165 | " pygments_lexer: 'sos' },\n", 166 | " sos: { kernels: [Array], panel: [Object], version: '0.9.16.7' } },\n", 167 | " nbformat: 4,\n", 168 | " nbformat_minor: 2 }" 169 | ] 170 | }, 171 | "execution_count": 4, 172 | "metadata": {}, 173 | "output_type": "execute_result" 174 | } 175 | ], 176 | "source": [ 177 | "%expand\n", 178 | "var fs = require('fs');\n", 179 | "JSON.parse(fs.readFileSync(\"{filename}\", 'utf8'));" 180 | ] 181 | }, 182 | { 183 | "cell_type": "markdown", 184 | "metadata": { 185 | "kernel": "JavaScript" 186 | }, 187 | "source": [ 188 | "## Capture output from subkernels" 189 | ] 190 | }, 191 | { 192 | "cell_type": "code", 193 | "execution_count": 5, 194 | "metadata": { 195 | "kernel": "Bash" 196 | }, 197 | "outputs": [ 198 | { 199 | "name": "stdout", 200 | "output_type": "stream", 201 | "text": [ 202 | " 352 1_Expand_and_Capture.ipynb\n" 203 | ] 204 | } 205 | ], 206 | "source": [ 207 | "%capture --to res\n", 208 | "%expand\n", 209 | "wc -l {filename}" 210 | ] 211 | }, 212 | { 213 | "cell_type": "code", 214 | "execution_count": 6, 215 | "metadata": { 216 | "kernel": "SoS" 217 | }, 218 | "outputs": [ 219 | { 220 | "data": { 221 | "text/plain": [ 222 | "' 352 1_Expand_and_Capture.ipynb\\n'" 223 | ] 224 | }, 225 | "execution_count": 6, 226 | "metadata": {}, 227 | "output_type": "execute_result" 228 | } 229 | ], 230 | "source": [ 231 | "res" 232 | ] 233 | }, 234 | { 235 | "cell_type": "code", 236 | "execution_count": 7, 237 | "metadata": { 238 | "kernel": "sparql" 239 | }, 240 | "outputs": [ 241 | { 242 | "data": { 243 | "text/html": [ 244 | "
Endpoint set to: http://dbpedia.org/sparql
Display: table
" 245 | ], 246 | "text/plain": [ 247 | "Endpoint set to: http://dbpedia.org/sparql\n", 248 | "Display: table\n" 249 | ] 250 | }, 251 | "metadata": {}, 252 | "output_type": "display_data" 253 | }, 254 | { 255 | "data": { 256 | "text/html": [ 257 | "
property
http://www.w3.org/2002/07/owl#differentFrom
http://www.w3.org/2000/01/rdf-schema#seeAlso
http://www.w3.org/2002/07/owl#sameAs
Total: 3, Shown: 3
" 258 | ] 259 | }, 260 | "metadata": {}, 261 | "output_type": "display_data" 262 | } 263 | ], 264 | "source": [ 265 | "%capture html --to result\n", 266 | "\n", 267 | "%endpoint http://dbpedia.org/sparql\n", 268 | "%display table \n", 269 | "SELECT DISTINCT ?property\n", 270 | "WHERE {\n", 271 | " ?s ?property ?person .\n", 272 | " ?person rdf:type foaf:Person .\n", 273 | "}\n", 274 | "LIMIT 3" 275 | ] 276 | }, 277 | { 278 | "cell_type": "code", 279 | "execution_count": 8, 280 | "metadata": { 281 | "kernel": "SoS" 282 | }, 283 | "outputs": [ 284 | { 285 | "data": { 286 | "text/plain": [ 287 | "['http://www.w3.org/2002/07/owl#differentFrom',\n", 288 | " 'http://www.w3.org/2000/01/rdf-schema#seeAlso',\n", 289 | " 'http://www.w3.org/2002/07/owl#sameAs']" 290 | ] 291 | }, 292 | "execution_count": 8, 293 | "metadata": {}, 294 | "output_type": "execute_result" 295 | } 296 | ], 297 | "source": [ 298 | "from bs4 import BeautifulSoup as Soup\n", 299 | "html = Soup(result, 'html.parser') \n", 300 | "[a['href'] for a in html.find_all('a')]" 301 | ] 302 | } 303 | ], 304 | "metadata": { 305 | "kernelspec": { 306 | "display_name": "SoS", 307 | "language": "sos", 308 | "name": "sos" 309 | }, 310 | "language_info": { 311 | "codemirror_mode": "sos", 312 | "file_extension": ".sos", 313 | "mimetype": "text/x-sos", 314 | "name": "sos", 315 | "nbconvert_exporter": "sos_notebook.converter.SoS_Exporter", 316 | "pygments_lexer": "sos" 317 | }, 318 | "sos": { 319 | "kernels": [ 320 | [ 321 | "Bash", 322 | "bash", 323 | "Bash", 324 | "#E6EEFF" 325 | ], 326 | [ 327 | "JavaScript", 328 | "javascript", 329 | "JavaScript", 330 | "#c8e1ae" 331 | ], 332 | [ 333 | "SoS", 334 | "sos", 335 | "", 336 | "" 337 | ] 338 | ], 339 | "panel": { 340 | "displayed": true, 341 | "height": "251.571px", 342 | "style": "side" 343 | }, 344 | "version": "0.9.16.7" 345 | } 346 | }, 347 | "nbformat": 4, 348 | "nbformat_minor": 2 349 | } 350 | -------------------------------------------------------------------------------- /2_Data_Exchange.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "metadata": { 6 | "kernel": "SoS" 7 | }, 8 | "source": [ 9 | "# Exchange of variables" 10 | ] 11 | }, 12 | { 13 | "cell_type": "markdown", 14 | "metadata": { 15 | "kernel": "SoS" 16 | }, 17 | "source": [ 18 | "## Three ways of transferring variables" 19 | ] 20 | }, 21 | { 22 | "cell_type": "markdown", 23 | "metadata": { 24 | "kernel": "SoS" 25 | }, 26 | "source": [ 27 | "### Magic `%get` and `%put`" 28 | ] 29 | }, 30 | { 31 | "cell_type": "code", 32 | "execution_count": 1, 33 | "metadata": { 34 | "kernel": "SoS" 35 | }, 36 | "outputs": [], 37 | "source": [ 38 | "n=5" 39 | ] 40 | }, 41 | { 42 | "cell_type": "code", 43 | "execution_count": 2, 44 | "metadata": { 45 | "kernel": "R" 46 | }, 47 | "outputs": [], 48 | "source": [ 49 | "%get n\n", 50 | "rn <- rnorm(n)" 51 | ] 52 | }, 53 | { 54 | "cell_type": "code", 55 | "execution_count": 3, 56 | "metadata": { 57 | "kernel": "SoS" 58 | }, 59 | "outputs": [ 60 | { 61 | "data": { 62 | "text/plain": [ 63 | "[-0.717208726490722,\n", 64 | " -0.716307792602076,\n", 65 | " 0.210121660734453,\n", 66 | " -1.50107629089392,\n", 67 | " 0.105600079729086]" 68 | ] 69 | }, 70 | "execution_count": 3, 71 | "metadata": {}, 72 | "output_type": "execute_result" 73 | } 74 | ], 75 | "source": [ 76 | "%get rn --from R\n", 77 | "rn" 78 | ] 79 | }, 80 | { 81 | "cell_type": "code", 82 | "execution_count": 4, 83 | "metadata": { 84 | "kernel": "SoS" 85 | }, 86 | "outputs": [], 87 | "source": [ 88 | "rn = [x+1 for x in rn]" 89 | ] 90 | }, 91 | { 92 | "cell_type": "code", 93 | "execution_count": 5, 94 | "metadata": { 95 | "kernel": "SoS" 96 | }, 97 | "outputs": [], 98 | "source": [ 99 | "%put rn --to R" 100 | ] 101 | }, 102 | { 103 | "cell_type": "code", 104 | "execution_count": 6, 105 | "metadata": { 106 | "kernel": "R" 107 | }, 108 | "outputs": [ 109 | { 110 | "data": { 111 | "text/html": [ 112 | "
    \n", 113 | "\t
  1. 0.282791273509278
    2. \n", 114 | "\t
  2. 0.283692207397924
    3. \n", 115 | "\t
  3. 1.21012166073445
    4. \n", 116 | "\t
  4. -0.50107629089392
    5. \n", 117 | "\t
  5. 1.10560007972909
    6. \n", 118 | "
\n" 119 | ], 120 | "text/latex": [ 121 | "\\begin{enumerate*}\n", 122 | "\\item 0.282791273509278\n", 123 | "\\item 0.283692207397924\n", 124 | "\\item 1.21012166073445\n", 125 | "\\item -0.50107629089392\n", 126 | "\\item 1.10560007972909\n", 127 | "\\end{enumerate*}\n" 128 | ], 129 | "text/markdown": [ 130 | "1. 0.282791273509278\n", 131 | "2. 0.283692207397924\n", 132 | "3. 1.21012166073445\n", 133 | "4. -0.50107629089392\n", 134 | "5. 1.10560007972909\n", 135 | "\n", 136 | "\n" 137 | ], 138 | "text/plain": [ 139 | "[1] 0.2827913 0.2836922 1.2101217 -0.5010763 1.1056001" 140 | ] 141 | }, 142 | "metadata": {}, 143 | "output_type": "display_data" 144 | } 145 | ], 146 | "source": [ 147 | "rn" 148 | ] 149 | }, 150 | { 151 | "cell_type": "markdown", 152 | "metadata": { 153 | "kernel": "R" 154 | }, 155 | "source": [ 156 | "### Magic `%with`" 157 | ] 158 | }, 159 | { 160 | "cell_type": "code", 161 | "execution_count": 7, 162 | "metadata": { 163 | "kernel": "SoS" 164 | }, 165 | "outputs": [], 166 | "source": [ 167 | "n=5" 168 | ] 169 | }, 170 | { 171 | "cell_type": "code", 172 | "execution_count": 8, 173 | "metadata": { 174 | "kernel": "R" 175 | }, 176 | "outputs": [], 177 | "source": [ 178 | "%with R -i n -o rn\n", 179 | "rn <- rnorm(n)" 180 | ] 181 | }, 182 | { 183 | "cell_type": "code", 184 | "execution_count": 9, 185 | "metadata": { 186 | "kernel": "SoS" 187 | }, 188 | "outputs": [ 189 | { 190 | "data": { 191 | "text/plain": [ 192 | "[-0.200078426229837,\n", 193 | " -0.425017555400589,\n", 194 | " 0.749107473681659,\n", 195 | " -0.333266605572932,\n", 196 | " 1.09653643921428]" 197 | ] 198 | }, 199 | "execution_count": 9, 200 | "metadata": {}, 201 | "output_type": "execute_result" 202 | } 203 | ], 204 | "source": [ 205 | "rn" 206 | ] 207 | }, 208 | { 209 | "cell_type": "markdown", 210 | "metadata": { 211 | "kernel": "SoS" 212 | }, 213 | "source": [ 214 | "### `sos`-named Variables" 215 | ] 216 | }, 217 | { 218 | "cell_type": "code", 219 | "execution_count": 10, 220 | "metadata": { 221 | "kernel": "SoS" 222 | }, 223 | "outputs": [], 224 | "source": [ 225 | "sos_n = 5" 226 | ] 227 | }, 228 | { 229 | "cell_type": "code", 230 | "execution_count": 11, 231 | "metadata": { 232 | "kernel": "R" 233 | }, 234 | "outputs": [], 235 | "source": [ 236 | "sos_rn <- rnorm(sos_n)" 237 | ] 238 | }, 239 | { 240 | "cell_type": "code", 241 | "execution_count": 12, 242 | "metadata": { 243 | "kernel": "SoS" 244 | }, 245 | "outputs": [ 246 | { 247 | "data": { 248 | "text/plain": [ 249 | "[-0.493718017873675,\n", 250 | " 0.00641199595342825,\n", 251 | " 3.18527800389836,\n", 252 | " -0.53589119458946,\n", 253 | " 1.3786041453922]" 254 | ] 255 | }, 256 | "execution_count": 12, 257 | "metadata": {}, 258 | "output_type": "execute_result" 259 | } 260 | ], 261 | "source": [ 262 | "sos_rn" 263 | ] 264 | }, 265 | { 266 | "cell_type": "markdown", 267 | "metadata": { 268 | "kernel": "SoS" 269 | }, 270 | "source": [ 271 | "## Transfer variables of other types" 272 | ] 273 | }, 274 | { 275 | "cell_type": "code", 276 | "execution_count": 13, 277 | "metadata": { 278 | "kernel": "R" 279 | }, 280 | "outputs": [], 281 | "source": [ 282 | "a = 3\n", 283 | "b = c(3, 2, 1)" 284 | ] 285 | }, 286 | { 287 | "cell_type": "code", 288 | "execution_count": 14, 289 | "metadata": { 290 | "kernel": "SoS" 291 | }, 292 | "outputs": [], 293 | "source": [ 294 | "%get a b --from R" 295 | ] 296 | }, 297 | { 298 | "cell_type": "code", 299 | "execution_count": 15, 300 | "metadata": { 301 | "kernel": "SoS" 302 | }, 303 | "outputs": [ 304 | { 305 | "data": { 306 | "text/plain": [ 307 | "3" 308 | ] 309 | }, 310 | "execution_count": 15, 311 | "metadata": {}, 312 | "output_type": "execute_result" 313 | } 314 | ], 315 | "source": [ 316 | "a" 317 | ] 318 | }, 319 | { 320 | "cell_type": "code", 321 | "execution_count": 16, 322 | "metadata": { 323 | "kernel": "SoS" 324 | }, 325 | "outputs": [ 326 | { 327 | "data": { 328 | "text/plain": [ 329 | "[3, 2, 1]" 330 | ] 331 | }, 332 | "execution_count": 16, 333 | "metadata": {}, 334 | "output_type": "execute_result" 335 | } 336 | ], 337 | "source": [ 338 | "b" 339 | ] 340 | }, 341 | { 342 | "cell_type": "code", 343 | "execution_count": 17, 344 | "metadata": { 345 | "kernel": "SoS" 346 | }, 347 | "outputs": [ 348 | { 349 | "name": "stderr", 350 | "output_type": "stream", 351 | "text": [ 352 | "Loading required package: feather\n" 353 | ] 354 | }, 355 | { 356 | "data": { 357 | "text/html": [ 358 | "
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mpgcyldisphpdratwtqsecvsamgearcarb
Mazda RX421.06.0160.0110.03.902.62016.460.01.04.04.0
Mazda RX4 Wag21.06.0160.0110.03.902.87517.020.01.04.04.0
Datsun 71022.84.0108.093.03.852.32018.611.01.04.01.0
Hornet 4 Drive21.46.0258.0110.03.083.21519.441.00.03.01.0
Hornet Sportabout18.78.0360.0175.03.153.44017.020.00.03.02.0
Valiant18.16.0225.0105.02.763.46020.221.00.03.01.0
Duster 36014.38.0360.0245.03.213.57015.840.00.03.04.0
Merc 240D24.44.0146.762.03.693.19020.001.00.04.02.0
Merc 23022.84.0140.895.03.923.15022.901.00.04.02.0
Merc 28019.26.0167.6123.03.923.44018.301.00.04.04.0
Merc 280C17.86.0167.6123.03.923.44018.901.00.04.04.0
Merc 450SE16.48.0275.8180.03.074.07017.400.00.03.03.0
Merc 450SL17.38.0275.8180.03.073.73017.600.00.03.03.0
Merc 450SLC15.28.0275.8180.03.073.78018.000.00.03.03.0
Cadillac Fleetwood10.48.0472.0205.02.935.25017.980.00.03.04.0
Lincoln Continental10.48.0460.0215.03.005.42417.820.00.03.04.0
Chrysler Imperial14.78.0440.0230.03.235.34517.420.00.03.04.0
Fiat 12832.44.078.766.04.082.20019.471.01.04.01.0
Honda Civic30.44.075.752.04.931.61518.521.01.04.02.0
Toyota Corolla33.94.071.165.04.221.83519.901.01.04.01.0
Toyota Corona21.54.0120.197.03.702.46520.011.00.03.01.0
Dodge Challenger15.58.0318.0150.02.763.52016.870.00.03.02.0
AMC Javelin15.28.0304.0150.03.153.43517.300.00.03.02.0
Camaro Z2813.38.0350.0245.03.733.84015.410.00.03.04.0
Pontiac Firebird19.28.0400.0175.03.083.84517.050.00.03.02.0
Fiat X1-927.34.079.066.04.081.93518.901.01.04.01.0
Porsche 914-226.04.0120.391.04.432.14016.700.01.05.02.0
Lotus Europa30.44.095.1113.03.771.51316.901.01.05.02.0
Ford Pantera L15.88.0351.0264.04.223.17014.500.01.05.04.0
Ferrari Dino19.76.0145.0175.03.622.77015.500.01.05.06.0
Maserati Bora15.08.0301.0335.03.543.57014.600.01.05.08.0
Volvo 142E21.44.0121.0109.04.112.78018.601.01.04.02.0
\n", 840 | "
" 841 | ], 842 | "text/plain": [ 843 | " mpg cyl disp hp drat wt qsec vs am gear carb\n", 844 | "Mazda RX4 21.0 6.0 160.0 110.0 3.90 2.620 16.46 0.0 1.0 4.0 4.0\n", 845 | "Mazda RX4 Wag 21.0 6.0 160.0 110.0 3.90 2.875 17.02 0.0 1.0 4.0 4.0\n", 846 | "Datsun 710 22.8 4.0 108.0 93.0 3.85 2.320 18.61 1.0 1.0 4.0 1.0\n", 847 | "Hornet 4 Drive 21.4 6.0 258.0 110.0 3.08 3.215 19.44 1.0 0.0 3.0 1.0\n", 848 | "Hornet Sportabout 18.7 8.0 360.0 175.0 3.15 3.440 17.02 0.0 0.0 3.0 2.0\n", 849 | "Valiant 18.1 6.0 225.0 105.0 2.76 3.460 20.22 1.0 0.0 3.0 1.0\n", 850 | "Duster 360 14.3 8.0 360.0 245.0 3.21 3.570 15.84 0.0 0.0 3.0 4.0\n", 851 | "Merc 240D 24.4 4.0 146.7 62.0 3.69 3.190 20.00 1.0 0.0 4.0 2.0\n", 852 | "Merc 230 22.8 4.0 140.8 95.0 3.92 3.150 22.90 1.0 0.0 4.0 2.0\n", 853 | "Merc 280 19.2 6.0 167.6 123.0 3.92 3.440 18.30 1.0 0.0 4.0 4.0\n", 854 | "Merc 280C 17.8 6.0 167.6 123.0 3.92 3.440 18.90 1.0 0.0 4.0 4.0\n", 855 | "Merc 450SE 16.4 8.0 275.8 180.0 3.07 4.070 17.40 0.0 0.0 3.0 3.0\n", 856 | "Merc 450SL 17.3 8.0 275.8 180.0 3.07 3.730 17.60 0.0 0.0 3.0 3.0\n", 857 | "Merc 450SLC 15.2 8.0 275.8 180.0 3.07 3.780 18.00 0.0 0.0 3.0 3.0\n", 858 | "Cadillac Fleetwood 10.4 8.0 472.0 205.0 2.93 5.250 17.98 0.0 0.0 3.0 4.0\n", 859 | "Lincoln Continental 10.4 8.0 460.0 215.0 3.00 5.424 17.82 0.0 0.0 3.0 4.0\n", 860 | "Chrysler Imperial 14.7 8.0 440.0 230.0 3.23 5.345 17.42 0.0 0.0 3.0 4.0\n", 861 | "Fiat 128 32.4 4.0 78.7 66.0 4.08 2.200 19.47 1.0 1.0 4.0 1.0\n", 862 | "Honda Civic 30.4 4.0 75.7 52.0 4.93 1.615 18.52 1.0 1.0 4.0 2.0\n", 863 | "Toyota Corolla 33.9 4.0 71.1 65.0 4.22 1.835 19.90 1.0 1.0 4.0 1.0\n", 864 | "Toyota Corona 21.5 4.0 120.1 97.0 3.70 2.465 20.01 1.0 0.0 3.0 1.0\n", 865 | "Dodge Challenger 15.5 8.0 318.0 150.0 2.76 3.520 16.87 0.0 0.0 3.0 2.0\n", 866 | "AMC Javelin 15.2 8.0 304.0 150.0 3.15 3.435 17.30 0.0 0.0 3.0 2.0\n", 867 | "Camaro Z28 13.3 8.0 350.0 245.0 3.73 3.840 15.41 0.0 0.0 3.0 4.0\n", 868 | "Pontiac Firebird 19.2 8.0 400.0 175.0 3.08 3.845 17.05 0.0 0.0 3.0 2.0\n", 869 | "Fiat X1-9 27.3 4.0 79.0 66.0 4.08 1.935 18.90 1.0 1.0 4.0 1.0\n", 870 | "Porsche 914-2 26.0 4.0 120.3 91.0 4.43 2.140 16.70 0.0 1.0 5.0 2.0\n", 871 | "Lotus Europa 30.4 4.0 95.1 113.0 3.77 1.513 16.90 1.0 1.0 5.0 2.0\n", 872 | "Ford Pantera L 15.8 8.0 351.0 264.0 4.22 3.170 14.50 0.0 1.0 5.0 4.0\n", 873 | "Ferrari Dino 19.7 6.0 145.0 175.0 3.62 2.770 15.50 0.0 1.0 5.0 6.0\n", 874 | "Maserati Bora 15.0 8.0 301.0 335.0 3.54 3.570 14.60 0.0 1.0 5.0 8.0\n", 875 | "Volvo 142E 21.4 4.0 121.0 109.0 4.11 2.780 18.60 1.0 1.0 4.0 2.0" 876 | ] 877 | }, 878 | "execution_count": 17, 879 | "metadata": {}, 880 | "output_type": "execute_result" 881 | } 882 | ], 883 | "source": [ 884 | "%get mtcars --from R\n", 885 | "mtcars" 886 | ] 887 | }, 888 | { 889 | "cell_type": "code", 890 | "execution_count": 18, 891 | "metadata": { 892 | "kernel": "SoS", 893 | "scrolled": false 894 | }, 895 | "outputs": [ 896 | { 897 | "data": { 898 | "text/html": [ 899 | "

SoS

\n", 900 | "\n", 901 | "\n", 902 | "\n", 903 | "\n", 904 | "
SoS Version
0.9.16.8
\n", 905 | "

R

\n", 906 | "\n", 907 | "\n", 908 | "\n", 909 | "\n", 910 | "\n", 911 | "\n", 912 | "\n", 913 | "\n", 914 | "\n", 937 | "\n", 938 | "
Kernel
ir
Language
R
R version 3.5.0 (2018-04-23)\n",
915 |        "Platform: x86_64-apple-darwin13.4.0 (64-bit)\n",
916 |        "Running under: macOS Sierra 10.12.5\n",
917 |        "\n",
918 |        "Matrix products: default\n",
919 |        "BLAS/LAPACK: /Users/bpeng1/anaconda3/envs/JupyterCon18/lib/libopenblasp-r0.2.20.dylib\n",
920 |        "\n",
921 |        "locale:\n",
922 |        "[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8\n",
923 |        "\n",
924 |        "attached base packages:\n",
925 |        "[1] stats     graphics  grDevices utils     datasets  methods   base     \n",
926 |        "\n",
927 |        "other attached packages:\n",
928 |        "[1] feather_0.3.1\n",
929 |        "\n",
930 |        "loaded via a namespace (and not attached):\n",
931 |        " [1] Rcpp_0.12.18    digest_0.6.15   crayon_1.3.4    IRdisplay_0.5.0\n",
932 |        " [5] repr_0.15.0     jsonlite_1.5    magrittr_1.5    evaluate_0.11  \n",
933 |        " [9] pillar_1.3.0    rlang_0.2.2     stringi_1.2.4   uuid_0.1-2     \n",
934 |        "[13] IRkernel_0.8.11 tools_3.5.0     stringr_1.3.1   hms_0.4.2      \n",
935 |        "[17] compiler_3.5.0  pkgconfig_2.0.2 base64enc_0.1-3 htmltools_0.3.6\n",
936 |        "[21] pbdZMQ_0.3-3    tibble_1.4.2
\n" 939 | ] 940 | }, 941 | "metadata": {}, 942 | "output_type": "display_data" 943 | } 944 | ], 945 | "source": [ 946 | "%sessioninfo" 947 | ] 948 | } 949 | ], 950 | "metadata": { 951 | "kernelspec": { 952 | "display_name": "SoS", 953 | "language": "sos", 954 | "name": "sos" 955 | }, 956 | "language_info": { 957 | "codemirror_mode": "sos", 958 | "file_extension": ".sos", 959 | "mimetype": "text/x-sos", 960 | "name": "sos", 961 | "nbconvert_exporter": "sos_notebook.converter.SoS_Exporter", 962 | "pygments_lexer": "sos" 963 | }, 964 | "sos": { 965 | "kernels": [ 966 | [ 967 | "R", 968 | "ir", 969 | "R", 970 | "#DCDCDA" 971 | ], 972 | [ 973 | "SoS", 974 | "sos", 975 | "", 976 | "" 977 | ] 978 | ], 979 | "panel": { 980 | "displayed": true, 981 | "height": 0, 982 | "style": "side" 983 | }, 984 | "version": "0.9.16.7" 985 | } 986 | }, 987 | "nbformat": 4, 988 | "nbformat_minor": 2 989 | } 990 | -------------------------------------------------------------------------------- /3_SoS_Magics.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "metadata": { 6 | "kernel": "SoS" 7 | }, 8 | "source": [ 9 | "# SoS Magics (Preview, session, and report)" 10 | ] 11 | }, 12 | { 13 | "cell_type": "code", 14 | "execution_count": 1, 15 | "metadata": { 16 | "kernel": "SoS", 17 | "tags": [ 18 | "report_output" 19 | ] 20 | }, 21 | "outputs": [ 22 | { 23 | "data": { 24 | "text/html": [ 25 | "\n", 26 | " \n", 27 | " \n", 28 | " \n", 29 | " \n", 30 | " \n", 31 | " \n", 32 | " \n", 33 | " \n", 34 | "\n", 35 | "\n", 36 | "\n", 37 | "\n", 38 | "\n", 39 | "\n", 40 | "\n", 41 | "\n", 42 | "\n", 43 | "\n", 44 | "\n", 45 | "\n", 46 | "\n", 47 | "\n", 48 | "
RevisionAuthorDateMessage
514e219Bo Peng2018-08-21Update notebooks
4a06c81Bo Peng2018-08-18Update figures
6bc69eeBo Peng2018-08-18Update magics noterbook and slides
b625104Bo Peng2018-08-17Complete preview magic
cfa7fb1Bo Peng2018-08-16Add skeleton of examples
" 49 | ] 50 | }, 51 | "metadata": {}, 52 | "output_type": "display_data" 53 | } 54 | ], 55 | "source": [ 56 | "%revisions" 57 | ] 58 | }, 59 | { 60 | "cell_type": "markdown", 61 | "metadata": { 62 | "kernel": "SoS" 63 | }, 64 | "source": [ 65 | "## `%preview`" 66 | ] 67 | }, 68 | { 69 | "cell_type": "code", 70 | "execution_count": 2, 71 | "metadata": { 72 | "kernel": "SoS" 73 | }, 74 | "outputs": [ 75 | { 76 | "name": "stderr", 77 | "output_type": "stream", 78 | "text": [ 79 | "Loading required package: feather\n" 80 | ] 81 | } 82 | ], 83 | "source": [ 84 | "%preview mtcars\n", 85 | "%get mtcars --from R" 86 | ] 87 | }, 88 | { 89 | "cell_type": "code", 90 | "execution_count": 3, 91 | "metadata": { 92 | "kernel": "R", 93 | "tags": [ 94 | "report_output" 95 | ] 96 | }, 97 | "outputs": [ 98 | { 99 | "data": { 100 | "text/html": [ 101 | "pdf: 2" 102 | ], 103 | "text/latex": [ 104 | "\\textbf{pdf:} 2" 105 | ], 106 | "text/markdown": [ 107 | "**pdf:** 2" 108 | ], 109 | "text/plain": [ 110 | "pdf \n", 111 | " 2 " 112 | ] 113 | }, 114 | "metadata": {}, 115 | "output_type": "display_data" 116 | }, 117 | { 118 | "data": { 119 | "text/html": [ 120 | "
%preview scatterplot.png
" 121 | ] 122 | }, 123 | "metadata": {}, 124 | "output_type": "display_data" 125 | }, 126 | { 127 | "data": { 128 | "text/html": [ 129 | "
> scatterplot.png (17.9 KiB):
" 130 | ], 131 | "text/plain": [ 132 | "\n", 133 | "> scatterplot.png (17.9 KiB):" 134 | ] 135 | }, 136 | "metadata": {}, 137 | "output_type": "display_data" 138 | }, 139 | { 140 | "data": { 141 | "image/png": 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" 142 | }, 143 | "metadata": {}, 144 | "output_type": "display_data" 145 | } 146 | ], 147 | "source": [ 148 | "%preview -n scatterplot.png\n", 149 | "png('scatterplot.png', width=500, height=300)\n", 150 | "plot(mtcars$wt, mtcars$mpg, main=\"Scatterplot of mtcars\", \n", 151 | " xlab=\"Car Weight\", ylab=\"Miles Per Gallon \")\n", 152 | "dev.off()" 153 | ] 154 | }, 155 | { 156 | "cell_type": "code", 157 | "execution_count": 4, 158 | "metadata": { 159 | "kernel": "JavaScript" 160 | }, 161 | "outputs": [ 162 | { 163 | "data": { 164 | "text/plain": [ 165 | "{ 'Mazda RX4': \n", 166 | " { mpg: 21,\n", 167 | " cyl: 6,\n", 168 | " disp: 160,\n", 169 | " hp: 110,\n", 170 | " drat: 3.9,\n", 171 | " wt: 2.62,\n", 172 | " qsec: 16.46,\n", 173 | " vs: 0,\n", 174 | " am: 1,\n", 175 | " gear: 4,\n", 176 | " carb: 4 },\n", 177 | " 'Mazda RX4 Wag': \n", 178 | " { mpg: 21,\n", 179 | " cyl: 6,\n", 180 | " disp: 160,\n", 181 | " hp: 110,\n", 182 | " drat: 3.9,\n", 183 | " wt: 2.875,\n", 184 | " qsec: 17.02,\n", 185 | " vs: 0,\n", 186 | " am: 1,\n", 187 | " gear: 4,\n", 188 | " carb: 4 },\n", 189 | " 'Datsun 710': \n", 190 | " { mpg: 22.8,\n", 191 | " cyl: 4,\n", 192 | " disp: 108,\n", 193 | " hp: 93,\n", 194 | " drat: 3.85,\n", 195 | " wt: 2.32,\n", 196 | " qsec: 18.61,\n", 197 | " vs: 1,\n", 198 | " am: 1,\n", 199 | " gear: 4,\n", 200 | " carb: 1 },\n", 201 | " 'Hornet 4 Drive': \n", 202 | " { mpg: 21.4,\n", 203 | " cyl: 6,\n", 204 | " disp: 258,\n", 205 | " hp: 110,\n", 206 | " drat: 3.08,\n", 207 | " wt: 3.215,\n", 208 | " qsec: 19.44,\n", 209 | " vs: 1,\n", 210 | " am: 0,\n", 211 | " gear: 3,\n", 212 | " carb: 1 },\n", 213 | " 'Hornet Sportabout': \n", 214 | " { mpg: 18.7,\n", 215 | " cyl: 8,\n", 216 | " disp: 360,\n", 217 | " hp: 175,\n", 218 | " drat: 3.15,\n", 219 | " wt: 3.44,\n", 220 | " qsec: 17.02,\n", 221 | " vs: 0,\n", 222 | " am: 0,\n", 223 | " gear: 3,\n", 224 | " carb: 2 },\n", 225 | " Valiant: \n", 226 | " { mpg: 18.1,\n", 227 | " cyl: 6,\n", 228 | " disp: 225,\n", 229 | " hp: 105,\n", 230 | " drat: 2.76,\n", 231 | " wt: 3.46,\n", 232 | " qsec: 20.22,\n", 233 | " vs: 1,\n", 234 | " am: 0,\n", 235 | " gear: 3,\n", 236 | " carb: 1 },\n", 237 | " 'Duster 360': \n", 238 | " { mpg: 14.3,\n", 239 | " cyl: 8,\n", 240 | " disp: 360,\n", 241 | " hp: 245,\n", 242 | " drat: 3.21,\n", 243 | " wt: 3.57,\n", 244 | " qsec: 15.84,\n", 245 | " vs: 0,\n", 246 | " am: 0,\n", 247 | " gear: 3,\n", 248 | " carb: 4 },\n", 249 | " 'Merc 240D': \n", 250 | " { mpg: 24.4,\n", 251 | " cyl: 4,\n", 252 | " disp: 146.7,\n", 253 | " hp: 62,\n", 254 | " drat: 3.69,\n", 255 | " wt: 3.19,\n", 256 | " qsec: 20,\n", 257 | " vs: 1,\n", 258 | " am: 0,\n", 259 | " gear: 4,\n", 260 | " carb: 2 },\n", 261 | " 'Merc 230': \n", 262 | " { mpg: 22.8,\n", 263 | " cyl: 4,\n", 264 | " disp: 140.8,\n", 265 | " hp: 95,\n", 266 | " drat: 3.92,\n", 267 | " wt: 3.15,\n", 268 | " qsec: 22.9,\n", 269 | " vs: 1,\n", 270 | " am: 0,\n", 271 | " gear: 4,\n", 272 | " carb: 2 },\n", 273 | " 'Merc 280': \n", 274 | " { mpg: 19.2,\n", 275 | " cyl: 6,\n", 276 | " disp: 167.6,\n", 277 | " hp: 123,\n", 278 | " drat: 3.92,\n", 279 | " wt: 3.44,\n", 280 | " qsec: 18.3,\n", 281 | " vs: 1,\n", 282 | " am: 0,\n", 283 | " gear: 4,\n", 284 | " carb: 4 },\n", 285 | " 'Merc 280C': \n", 286 | " { mpg: 17.8,\n", 287 | " cyl: 6,\n", 288 | " disp: 167.6,\n", 289 | " hp: 123,\n", 290 | " drat: 3.92,\n", 291 | " wt: 3.44,\n", 292 | " qsec: 18.9,\n", 293 | " vs: 1,\n", 294 | " am: 0,\n", 295 | " gear: 4,\n", 296 | " carb: 4 },\n", 297 | " 'Merc 450SE': \n", 298 | " { mpg: 16.4,\n", 299 | " cyl: 8,\n", 300 | " disp: 275.8,\n", 301 | " hp: 180,\n", 302 | " drat: 3.07,\n", 303 | " wt: 4.07,\n", 304 | " qsec: 17.4,\n", 305 | " vs: 0,\n", 306 | " am: 0,\n", 307 | " gear: 3,\n", 308 | " carb: 3 },\n", 309 | " 'Merc 450SL': \n", 310 | " { mpg: 17.3,\n", 311 | " cyl: 8,\n", 312 | " disp: 275.8,\n", 313 | " hp: 180,\n", 314 | " drat: 3.07,\n", 315 | " wt: 3.73,\n", 316 | " qsec: 17.6,\n", 317 | " vs: 0,\n", 318 | " am: 0,\n", 319 | " gear: 3,\n", 320 | " carb: 3 },\n", 321 | " 'Merc 450SLC': \n", 322 | " { mpg: 15.2,\n", 323 | " cyl: 8,\n", 324 | " disp: 275.8,\n", 325 | " hp: 180,\n", 326 | " drat: 3.07,\n", 327 | " wt: 3.78,\n", 328 | " qsec: 18,\n", 329 | " vs: 0,\n", 330 | " am: 0,\n", 331 | " gear: 3,\n", 332 | " carb: 3 },\n", 333 | " 'Cadillac Fleetwood': \n", 334 | " { mpg: 10.4,\n", 335 | " cyl: 8,\n", 336 | " disp: 472,\n", 337 | " hp: 205,\n", 338 | " drat: 2.93,\n", 339 | " wt: 5.25,\n", 340 | " qsec: 17.98,\n", 341 | " vs: 0,\n", 342 | " am: 0,\n", 343 | " gear: 3,\n", 344 | " carb: 4 },\n", 345 | " 'Lincoln Continental': \n", 346 | " { mpg: 10.4,\n", 347 | " cyl: 8,\n", 348 | " disp: 460,\n", 349 | " hp: 215,\n", 350 | " drat: 3,\n", 351 | " wt: 5.424,\n", 352 | " qsec: 17.82,\n", 353 | " vs: 0,\n", 354 | " am: 0,\n", 355 | " gear: 3,\n", 356 | " carb: 4 },\n", 357 | " 'Chrysler Imperial': \n", 358 | " { mpg: 14.7,\n", 359 | " cyl: 8,\n", 360 | " disp: 440,\n", 361 | " hp: 230,\n", 362 | " drat: 3.23,\n", 363 | " wt: 5.345,\n", 364 | " qsec: 17.42,\n", 365 | " vs: 0,\n", 366 | " am: 0,\n", 367 | " gear: 3,\n", 368 | " carb: 4 },\n", 369 | " 'Fiat 128': \n", 370 | " { mpg: 32.4,\n", 371 | " cyl: 4,\n", 372 | " disp: 78.7,\n", 373 | " hp: 66,\n", 374 | " drat: 4.08,\n", 375 | " wt: 2.2,\n", 376 | " qsec: 19.47,\n", 377 | " vs: 1,\n", 378 | " am: 1,\n", 379 | " gear: 4,\n", 380 | " carb: 1 },\n", 381 | " 'Honda Civic': \n", 382 | " { mpg: 30.4,\n", 383 | " cyl: 4,\n", 384 | " disp: 75.7,\n", 385 | " hp: 52,\n", 386 | " drat: 4.93,\n", 387 | " wt: 1.615,\n", 388 | " qsec: 18.52,\n", 389 | " vs: 1,\n", 390 | " am: 1,\n", 391 | " gear: 4,\n", 392 | " carb: 2 },\n", 393 | " 'Toyota Corolla': \n", 394 | " { mpg: 33.9,\n", 395 | " cyl: 4,\n", 396 | " disp: 71.1,\n", 397 | " hp: 65,\n", 398 | " drat: 4.22,\n", 399 | " wt: 1.835,\n", 400 | " qsec: 19.9,\n", 401 | " vs: 1,\n", 402 | " am: 1,\n", 403 | " gear: 4,\n", 404 | " carb: 1 },\n", 405 | " 'Toyota Corona': \n", 406 | " { mpg: 21.5,\n", 407 | " cyl: 4,\n", 408 | " disp: 120.1,\n", 409 | " hp: 97,\n", 410 | " drat: 3.7,\n", 411 | " wt: 2.465,\n", 412 | " qsec: 20.01,\n", 413 | " vs: 1,\n", 414 | " am: 0,\n", 415 | " gear: 3,\n", 416 | " carb: 1 },\n", 417 | " 'Dodge Challenger': \n", 418 | " { mpg: 15.5,\n", 419 | " cyl: 8,\n", 420 | " disp: 318,\n", 421 | " hp: 150,\n", 422 | " drat: 2.76,\n", 423 | " wt: 3.52,\n", 424 | " qsec: 16.87,\n", 425 | " vs: 0,\n", 426 | " am: 0,\n", 427 | " gear: 3,\n", 428 | " carb: 2 },\n", 429 | " 'AMC Javelin': \n", 430 | " { mpg: 15.2,\n", 431 | " cyl: 8,\n", 432 | " disp: 304,\n", 433 | " hp: 150,\n", 434 | " drat: 3.15,\n", 435 | " wt: 3.435,\n", 436 | " qsec: 17.3,\n", 437 | " vs: 0,\n", 438 | " am: 0,\n", 439 | " gear: 3,\n", 440 | " carb: 2 },\n", 441 | " 'Camaro Z28': \n", 442 | " { mpg: 13.3,\n", 443 | " cyl: 8,\n", 444 | " disp: 350,\n", 445 | " hp: 245,\n", 446 | " drat: 3.73,\n", 447 | " wt: 3.84,\n", 448 | " qsec: 15.41,\n", 449 | " vs: 0,\n", 450 | " am: 0,\n", 451 | " gear: 3,\n", 452 | " carb: 4 },\n", 453 | " 'Pontiac Firebird': \n", 454 | " { mpg: 19.2,\n", 455 | " cyl: 8,\n", 456 | " disp: 400,\n", 457 | " hp: 175,\n", 458 | " drat: 3.08,\n", 459 | " wt: 3.845,\n", 460 | " qsec: 17.05,\n", 461 | " vs: 0,\n", 462 | " am: 0,\n", 463 | " gear: 3,\n", 464 | " carb: 2 },\n", 465 | " 'Fiat X1-9': \n", 466 | " { mpg: 27.3,\n", 467 | " cyl: 4,\n", 468 | " disp: 79,\n", 469 | " hp: 66,\n", 470 | " drat: 4.08,\n", 471 | " wt: 1.935,\n", 472 | " qsec: 18.9,\n", 473 | " vs: 1,\n", 474 | " am: 1,\n", 475 | " gear: 4,\n", 476 | " carb: 1 },\n", 477 | " 'Porsche 914-2': \n", 478 | " { mpg: 26,\n", 479 | " cyl: 4,\n", 480 | " disp: 120.3,\n", 481 | " hp: 91,\n", 482 | " drat: 4.43,\n", 483 | " wt: 2.14,\n", 484 | " qsec: 16.7,\n", 485 | " vs: 0,\n", 486 | " am: 1,\n", 487 | " gear: 5,\n", 488 | " carb: 2 },\n", 489 | " 'Lotus Europa': \n", 490 | " { mpg: 30.4,\n", 491 | " cyl: 4,\n", 492 | " disp: 95.1,\n", 493 | " hp: 113,\n", 494 | " drat: 3.77,\n", 495 | " wt: 1.513,\n", 496 | " qsec: 16.9,\n", 497 | " vs: 1,\n", 498 | " am: 1,\n", 499 | " gear: 5,\n", 500 | " carb: 2 },\n", 501 | " 'Ford Pantera L': \n", 502 | " { mpg: 15.8,\n", 503 | " cyl: 8,\n", 504 | " disp: 351,\n", 505 | " hp: 264,\n", 506 | " drat: 4.22,\n", 507 | " wt: 3.17,\n", 508 | " qsec: 14.5,\n", 509 | " vs: 0,\n", 510 | " am: 1,\n", 511 | " gear: 5,\n", 512 | " carb: 4 },\n", 513 | " 'Ferrari Dino': \n", 514 | " { mpg: 19.7,\n", 515 | " cyl: 6,\n", 516 | " disp: 145,\n", 517 | " hp: 175,\n", 518 | " drat: 3.62,\n", 519 | " wt: 2.77,\n", 520 | " qsec: 15.5,\n", 521 | " vs: 0,\n", 522 | " am: 1,\n", 523 | " gear: 5,\n", 524 | " carb: 6 },\n", 525 | " 'Maserati Bora': \n", 526 | " { mpg: 15,\n", 527 | " cyl: 8,\n", 528 | " disp: 301,\n", 529 | " hp: 335,\n", 530 | " drat: 3.54,\n", 531 | " wt: 3.57,\n", 532 | " qsec: 14.6,\n", 533 | " vs: 0,\n", 534 | " am: 1,\n", 535 | " gear: 5,\n", 536 | " carb: 8 },\n", 537 | " 'Volvo 142E': \n", 538 | " { mpg: 21.4,\n", 539 | " cyl: 4,\n", 540 | " disp: 121,\n", 541 | " hp: 109,\n", 542 | " drat: 4.11,\n", 543 | " wt: 2.78,\n", 544 | " qsec: 18.6,\n", 545 | " vs: 1,\n", 546 | " am: 1,\n", 547 | " gear: 4,\n", 548 | " carb: 2 } }" 549 | ] 550 | }, 551 | "execution_count": 4, 552 | "metadata": {}, 553 | "output_type": "execute_result" 554 | } 555 | ], 556 | "source": [ 557 | "%get mtcars --from R\n", 558 | "mtcars" 559 | ] 560 | }, 561 | { 562 | "cell_type": "markdown", 563 | "metadata": { 564 | "kernel": "SoS" 565 | }, 566 | "source": [ 567 | "## `%sessioninfo`" 568 | ] 569 | }, 570 | { 571 | "cell_type": "code", 572 | "execution_count": 5, 573 | "metadata": { 574 | "kernel": "SoS", 575 | "tags": [ 576 | "report_output" 577 | ] 578 | }, 579 | "outputs": [ 580 | { 581 | "data": { 582 | "text/html": [ 583 | "

SoS

\n", 584 | "\n", 585 | "\n", 586 | "\n", 587 | "\n", 588 | "
SoS Version
0.9.16.8
\n", 589 | "

R

\n", 590 | "\n", 591 | "\n", 592 | "\n", 593 | "\n", 594 | "\n", 595 | "\n", 596 | "\n", 597 | "\n", 598 | "\n", 621 | "\n", 622 | "
Kernel
ir
Language
R
R version 3.5.0 (2018-04-23)\n",
599 |        "Platform: x86_64-apple-darwin13.4.0 (64-bit)\n",
600 |        "Running under: macOS Sierra 10.12.5\n",
601 |        "\n",
602 |        "Matrix products: default\n",
603 |        "BLAS/LAPACK: /Users/bpeng1/anaconda3/envs/JupyterCon18/lib/libopenblasp-r0.2.20.dylib\n",
604 |        "\n",
605 |        "locale:\n",
606 |        "[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8\n",
607 |        "\n",
608 |        "attached base packages:\n",
609 |        "[1] stats     graphics  grDevices utils     datasets  methods   base     \n",
610 |        "\n",
611 |        "other attached packages:\n",
612 |        "[1] feather_0.3.1\n",
613 |        "\n",
614 |        "loaded via a namespace (and not attached):\n",
615 |        " [1] Rcpp_0.12.18    digest_0.6.15   crayon_1.3.4    IRdisplay_0.5.0\n",
616 |        " [5] repr_0.15.0     jsonlite_1.5    magrittr_1.5    evaluate_0.11  \n",
617 |        " [9] pillar_1.3.0    rlang_0.2.2     stringi_1.2.4   uuid_0.1-2     \n",
618 |        "[13] IRkernel_0.8.11 tools_3.5.0     stringr_1.3.1   hms_0.4.2      \n",
619 |        "[17] compiler_3.5.0  pkgconfig_2.0.2 base64enc_0.1-3 htmltools_0.3.6\n",
620 |        "[21] pbdZMQ_0.3-3    tibble_1.4.2
\n", 623 | "

JavaScript

\n", 624 | "\n", 625 | "\n", 626 | "\n", 627 | "\n", 628 | "\n", 629 | "\n", 630 | "\n", 631 | "
Kernel
javascript
Language
JavaScript
\n" 632 | ] 633 | }, 634 | "metadata": {}, 635 | "output_type": "display_data" 636 | } 637 | ], 638 | "source": [ 639 | "%sessioninfo" 640 | ] 641 | }, 642 | { 643 | "cell_type": "markdown", 644 | "metadata": { 645 | "kernel": "SoS" 646 | }, 647 | "source": [ 648 | "## `%sossave`" 649 | ] 650 | }, 651 | { 652 | "cell_type": "code", 653 | "execution_count": 6, 654 | "metadata": { 655 | "kernel": "SoS" 656 | }, 657 | "outputs": [ 658 | { 659 | "data": { 660 | "text/html": [ 661 | "
Workflow saved to 3_SoS_Magics.html
" 662 | ], 663 | "text/plain": [ 664 | "Workflow saved to 3_SoS_Magics.html\n" 665 | ] 666 | }, 667 | "metadata": {}, 668 | "output_type": "display_data" 669 | } 670 | ], 671 | "source": [ 672 | "%sossave --to html --force" 673 | ] 674 | } 675 | ], 676 | "metadata": { 677 | "kernelspec": { 678 | "display_name": "SoS", 679 | "language": "sos", 680 | "name": "sos" 681 | }, 682 | "language_info": { 683 | "codemirror_mode": "sos", 684 | "file_extension": ".sos", 685 | "mimetype": "text/x-sos", 686 | "name": "sos", 687 | "nbconvert_exporter": "sos_notebook.converter.SoS_Exporter", 688 | "pygments_lexer": "sos" 689 | }, 690 | "sos": { 691 | "kernels": [], 692 | "panel": { 693 | "displayed": true, 694 | "height": 0, 695 | "style": "side" 696 | }, 697 | "version": "0.9.16.7" 698 | } 699 | }, 700 | "nbformat": 4, 701 | "nbformat_minor": 2 702 | } 703 | -------------------------------------------------------------------------------- /4_Notebook_to_Workflow.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "metadata": { 6 | "kernel": "SoS" 7 | }, 8 | "source": [ 9 | "## Creation of a SoS workflow from interactive analysis" 10 | ] 11 | }, 12 | { 13 | "cell_type": "markdown", 14 | "metadata": { 15 | "kernel": "SoS" 16 | }, 17 | "source": [ 18 | "## Basic Syntax" 19 | ] 20 | }, 21 | { 22 | "cell_type": "markdown", 23 | "metadata": { 24 | "kernel": "SoS" 25 | }, 26 | "source": [ 27 | "### Script format of function calls" 28 | ] 29 | }, 30 | { 31 | "cell_type": "code", 32 | "execution_count": 1, 33 | "metadata": { 34 | "kernel": "SoS" 35 | }, 36 | "outputs": [], 37 | "source": [ 38 | "res_file = 'test.pdf'" 39 | ] 40 | }, 41 | { 42 | "cell_type": "code", 43 | "execution_count": 2, 44 | "metadata": { 45 | "kernel": "SoS" 46 | }, 47 | "outputs": [ 48 | { 49 | "name": "stdout", 50 | "output_type": "stream", 51 | "text": [ 52 | "null device \n", 53 | " 1 \n" 54 | ] 55 | } 56 | ], 57 | "source": [ 58 | "R(f'''\n", 59 | "pdf('{res_file}')\n", 60 | "plot(0, 0)\n", 61 | "dev.off()\n", 62 | "''', workdir='result')" 63 | ] 64 | }, 65 | { 66 | "cell_type": "markdown", 67 | "metadata": { 68 | "kernel": "SoS" 69 | }, 70 | "source": [ 71 | "is equivalent to" 72 | ] 73 | }, 74 | { 75 | "cell_type": "code", 76 | "execution_count": 3, 77 | "metadata": { 78 | "kernel": "SoS" 79 | }, 80 | "outputs": [ 81 | { 82 | "name": "stdout", 83 | "output_type": "stream", 84 | "text": [ 85 | "null device \n", 86 | " 1 \n" 87 | ] 88 | } 89 | ], 90 | "source": [ 91 | "R: expand=True, workdir='result'\n", 92 | " pdf('{res_file}')\n", 93 | " plot(0, 0)\n", 94 | " dev.off() " 95 | ] 96 | }, 97 | { 98 | "cell_type": "markdown", 99 | "metadata": { 100 | "kernel": "SoS" 101 | }, 102 | "source": [ 103 | "Or with different sigil" 104 | ] 105 | }, 106 | { 107 | "cell_type": "code", 108 | "execution_count": 4, 109 | "metadata": { 110 | "kernel": "SoS" 111 | }, 112 | "outputs": [ 113 | { 114 | "name": "stdout", 115 | "output_type": "stream", 116 | "text": [ 117 | "null device \n", 118 | " 1 \n" 119 | ] 120 | } 121 | ], 122 | "source": [ 123 | "R: expand='${ }', workdir='result'\n", 124 | " pdf('${res_file}')\n", 125 | " plot(0, 0)\n", 126 | " dev.off() " 127 | ] 128 | }, 129 | { 130 | "cell_type": "code", 131 | "execution_count": 5, 132 | "metadata": { 133 | "kernel": "SoS" 134 | }, 135 | "outputs": [], 136 | "source": [ 137 | "[RNASeq_20 (QC)]\n", 138 | "\n", 139 | "parameter: fastq_files = list\n", 140 | "\n", 141 | "input: fastq_files, group_by=1\n", 142 | "depends: executable('fastqc')\n", 143 | "output: f'{_input:bn}_fastqc_html'\n", 144 | "\n", 145 | "print(f'Processing {_input}')\n", 146 | "\n", 147 | "task: walltime='30m'\n", 148 | "\n", 149 | "sh: expand=True\n", 150 | " fastqc {_input}" 151 | ] 152 | }, 153 | { 154 | "cell_type": "markdown", 155 | "metadata": { 156 | "kernel": "SoS" 157 | }, 158 | "source": [ 159 | "### Interactive data analysis" 160 | ] 161 | }, 162 | { 163 | "cell_type": "markdown", 164 | "metadata": { 165 | "kernel": "SoS" 166 | }, 167 | "source": [ 168 | "Interactive data analysis can be performed in cells with different kernels as follows. Because SoS is an extension to Python 3, you can use arbitrary Python statements in SoS cells." 169 | ] 170 | }, 171 | { 172 | "cell_type": "code", 173 | "execution_count": 6, 174 | "metadata": { 175 | "kernel": "SoS" 176 | }, 177 | "outputs": [], 178 | "source": [ 179 | "excel_file = 'data/DEG.xlsx'\n", 180 | "csv_file = 'DEG.csv'\n", 181 | "figure_file = 'output.pdf'" 182 | ] 183 | }, 184 | { 185 | "cell_type": "code", 186 | "execution_count": 7, 187 | "metadata": { 188 | "kernel": "Bash" 189 | }, 190 | "outputs": [], 191 | "source": [ 192 | "%expand\n", 193 | "xlsx2csv {excel_file} > {csv_file}" 194 | ] 195 | }, 196 | { 197 | "cell_type": "code", 198 | "execution_count": 8, 199 | "metadata": { 200 | "kernel": "R" 201 | }, 202 | "outputs": [ 203 | { 204 | "data": { 205 | "text/html": [ 206 | "pdf: 2" 207 | ], 208 | "text/latex": [ 209 | "\\textbf{pdf:} 2" 210 | ], 211 | "text/markdown": [ 212 | "**pdf:** 2" 213 | ], 214 | "text/plain": [ 215 | "pdf \n", 216 | " 2 " 217 | ] 218 | }, 219 | "metadata": {}, 220 | "output_type": "display_data" 221 | } 222 | ], 223 | "source": [ 224 | "%expand\n", 225 | "data <- read.csv('{csv_file}')\n", 226 | "pdf('{figure_file}')\n", 227 | "plot(data$log2FoldChange, data$stat)\n", 228 | "dev.off()" 229 | ] 230 | }, 231 | { 232 | "cell_type": "markdown", 233 | "metadata": { 234 | "kernel": "R" 235 | }, 236 | "source": [ 237 | "### Convert to SoS actions" 238 | ] 239 | }, 240 | { 241 | "cell_type": "code", 242 | "execution_count": 1, 243 | "metadata": { 244 | "kernel": "SoS" 245 | }, 246 | "outputs": [], 247 | "source": [ 248 | "excel_file = 'data/DEG.xlsx'\n", 249 | "csv_file = 'DEG.csv'\n", 250 | "figure_file = 'output.pdf'" 251 | ] 252 | }, 253 | { 254 | "cell_type": "code", 255 | "execution_count": 5, 256 | "metadata": { 257 | "kernel": "SoS" 258 | }, 259 | "outputs": [], 260 | "source": [ 261 | "sh: expand=True\n", 262 | " xlsx2csv {excel_file} > {csv_file}" 263 | ] 264 | }, 265 | { 266 | "cell_type": "code", 267 | "execution_count": 6, 268 | "metadata": { 269 | "kernel": "SoS" 270 | }, 271 | "outputs": [ 272 | { 273 | "name": "stdout", 274 | "output_type": "stream", 275 | "text": [ 276 | "null device \n", 277 | " 1 \n" 278 | ] 279 | } 280 | ], 281 | "source": [ 282 | "R: expand=True\n", 283 | " data <- read.csv('{csv_file}')\n", 284 | " pdf('{figure_file}')\n", 285 | " plot(data$log2FoldChange, data$stat)\n", 286 | " dev.off()" 287 | ] 288 | }, 289 | { 290 | "cell_type": "markdown", 291 | "metadata": { 292 | "kernel": "R" 293 | }, 294 | "source": [ 295 | "### Conversion to a SoS Workflow" 296 | ] 297 | }, 298 | { 299 | "cell_type": "markdown", 300 | "metadata": { 301 | "kernel": "R" 302 | }, 303 | "source": [ 304 | "SoS workflows within a SoS Notebook are defined by sections marked by section headers (`[name: option]`). A `[global]` section should be used for definitions that will be used by all steps.\n", 305 | "\n", 306 | "You also need to convert scripts to SoS actions so that they can be executed as **complete** scripts. Remember also to change the cell type from subkernel to SoS." 307 | ] 308 | }, 309 | { 310 | "cell_type": "code", 311 | "execution_count": 7, 312 | "metadata": { 313 | "kernel": "SoS" 314 | }, 315 | "outputs": [], 316 | "source": [ 317 | "[global]\n", 318 | "excel_file = 'data/DEG.xlsx'\n", 319 | "csv_file = 'DEG.csv'\n", 320 | "figure_file = 'output.pdf'" 321 | ] 322 | }, 323 | { 324 | "cell_type": "code", 325 | "execution_count": 8, 326 | "metadata": { 327 | "kernel": "SoS" 328 | }, 329 | "outputs": [], 330 | "source": [ 331 | "[plot_1 (convert)]\n", 332 | "sh: expand=True\n", 333 | " xlsx2csv {excel_file} > {csv_file}" 334 | ] 335 | }, 336 | { 337 | "cell_type": "code", 338 | "execution_count": 9, 339 | "metadata": { 340 | "kernel": "SoS" 341 | }, 342 | "outputs": [], 343 | "source": [ 344 | "[plot_2 (plot)]\n", 345 | "R: expand=True\n", 346 | " data <- read.csv('{csv_file}')\n", 347 | " pdf('{figure_file}')\n", 348 | " plot(data$log2FoldChange, data$stat)\n", 349 | " dev.off()" 350 | ] 351 | }, 352 | { 353 | "cell_type": "code", 354 | "execution_count": 10, 355 | "metadata": { 356 | "kernel": "SoS" 357 | }, 358 | "outputs": [ 359 | { 360 | "name": "stdout", 361 | "output_type": "stream", 362 | "text": [ 363 | "null device \n", 364 | " 1 \n" 365 | ] 366 | }, 367 | { 368 | "data": { 369 | "text/html": [ 370 | "
INFO: Workflow plot (ID=e9a443b49c71e268) is executed successfully with 2 completed steps.
" 371 | ] 372 | }, 373 | "metadata": {}, 374 | "output_type": "display_data" 375 | } 376 | ], 377 | "source": [ 378 | "%sosrun plot" 379 | ] 380 | }, 381 | { 382 | "cell_type": "code", 383 | "execution_count": 16, 384 | "metadata": { 385 | "kernel": "SoS" 386 | }, 387 | "outputs": [ 388 | { 389 | "data": { 390 | "text/html": [ 391 | "" 426 | ], 427 | "text/plain": [ 428 | "#!/usr/bin/env sos-runner\n", 429 | "#fileformat=SOS1.0\n", 430 | "\n", 431 | "[RNASeq_20 (QC)]\n", 432 | "\n", 433 | "parameter: fastq_files = list\n", 434 | "\n", 435 | "input: fastq_files, group_by=1\n", 436 | "depends: executable('fastqc')\n", 437 | "output: f'{_input:bn}_fastqc_html'\n", 438 | "\n", 439 | "print(f'Processing {_input}')\n", 440 | "\n", 441 | "task: walltime='30m'\n", 442 | "\n", 443 | "sh: expand=True\n", 444 | " fastqc {_input}\n", 445 | "\n", 446 | "[global]\n", 447 | "excel_file = 'data/DEG.xlsx'\n", 448 | "csv_file = 'DEG.csv'\n", 449 | "figure_file = 'output.pdf'\n", 450 | "\n", 451 | "[plot_1 (convert)]\n", 452 | "sh: expand=True\n", 453 | " xlsx2csv {excel_file} > {csv_file}\n", 454 | "\n", 455 | "[plot_2 (plot)]\n", 456 | "R: expand=True\n", 457 | " data <- read.csv('{csv_file}')\n", 458 | " pdf('{figure_file}')\n", 459 | " plot(data$log2FoldChange, data$stat)\n", 460 | " dev.off()\n", 461 | "\n" 462 | ] 463 | }, 464 | "metadata": {}, 465 | "output_type": "display_data" 466 | } 467 | ], 468 | "source": [ 469 | "%preview --workflow" 470 | ] 471 | } 472 | ], 473 | "metadata": { 474 | "kernelspec": { 475 | "display_name": "SoS", 476 | "language": "sos", 477 | "name": "sos" 478 | }, 479 | "language_info": { 480 | "codemirror_mode": "sos", 481 | "file_extension": ".sos", 482 | "mimetype": "text/x-sos", 483 | "name": "sos", 484 | "nbconvert_exporter": "sos_notebook.converter.SoS_Exporter", 485 | "pygments_lexer": "sos" 486 | }, 487 | "sos": { 488 | "default_kernel": "SoS", 489 | "kernels": [ 490 | [ 491 | "Bash", 492 | "bash", 493 | "Bash", 494 | "#E6EEFF" 495 | ], 496 | [ 497 | "R", 498 | "ir", 499 | "R", 500 | "#DCDCDA" 501 | ], 502 | [ 503 | "SoS", 504 | "sos", 505 | "", 506 | "" 507 | ] 508 | ], 509 | "panel": { 510 | "displayed": false, 511 | "height": 0, 512 | "style": "side" 513 | }, 514 | "version": "0.16.11" 515 | } 516 | }, 517 | "nbformat": 4, 518 | "nbformat_minor": 2 519 | } 520 | -------------------------------------------------------------------------------- /6_Task.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "metadata": { 6 | "kernel": "SoS" 7 | }, 8 | "source": [ 9 | "## External tasks" 10 | ] 11 | }, 12 | { 13 | "cell_type": "markdown", 14 | "metadata": { 15 | "kernel": "SoS" 16 | }, 17 | "source": [ 18 | "The following workflow has a single step that generates a number of files with the number specified by parameter `num`." 19 | ] 20 | }, 21 | { 22 | "cell_type": "markdown", 23 | "metadata": { 24 | "kernel": "SoS" 25 | }, 26 | "source": [ 27 | "The following cell will not be executed directly (with `Ctrl-Enter` or `Shift-Enter`) because it is a formal SoS cell. It has to be executed by magic `%run` or `%sosrun`." 28 | ] 29 | }, 30 | { 31 | "cell_type": "code", 32 | "execution_count": 1, 33 | "metadata": { 34 | "kernel": "SoS" 35 | }, 36 | "outputs": [], 37 | "source": [ 38 | "[no_task]\n", 39 | "parameter: num = 2\n", 40 | "\n", 41 | "input: for_each = {'i': range(num)}\n", 42 | "output: f'test_{i}.txt'\n", 43 | "\n", 44 | "sh: expand=True\n", 45 | " sleep {3*i}\n", 46 | " echo test_{i} > test_{i}.txt\n", 47 | " echo \"Test_{i}.txt generated\"" 48 | ] 49 | }, 50 | { 51 | "cell_type": "code", 52 | "execution_count": 2, 53 | "metadata": { 54 | "kernel": "SoS" 55 | }, 56 | "outputs": [ 57 | { 58 | "name": "stdout", 59 | "output_type": "stream", 60 | "text": [ 61 | "Test_0.txt generated\n", 62 | "Test_1.txt generated\n" 63 | ] 64 | } 65 | ], 66 | "source": [ 67 | "%sosrun no_task" 68 | ] 69 | }, 70 | { 71 | "cell_type": "markdown", 72 | "metadata": { 73 | "kernel": "SoS" 74 | }, 75 | "source": [ 76 | "When we rerun the workflow with option `--num 3` to generate one more file, the first two are ignored because they have already been generated." 77 | ] 78 | }, 79 | { 80 | "cell_type": "code", 81 | "execution_count": 3, 82 | "metadata": { 83 | "kernel": "SoS" 84 | }, 85 | "outputs": [ 86 | { 87 | "name": "stdout", 88 | "output_type": "stream", 89 | "text": [ 90 | "Test_2.txt generated\n" 91 | ] 92 | } 93 | ], 94 | "source": [ 95 | "%sosrun no_task --num 3" 96 | ] 97 | }, 98 | { 99 | "cell_type": "markdown", 100 | "metadata": { 101 | "kernel": "SoS" 102 | }, 103 | "source": [ 104 | "Keyword `task` separates the reset of the step process as external tasks:" 105 | ] 106 | }, 107 | { 108 | "cell_type": "code", 109 | "execution_count": 4, 110 | "metadata": { 111 | "kernel": "SoS" 112 | }, 113 | "outputs": [], 114 | "source": [ 115 | "[task]\n", 116 | "parameter: num = 2\n", 117 | "\n", 118 | "input: for_each = {'i': range(num)}\n", 119 | "output: f'test_{i}.txt'\n", 120 | "\n", 121 | "task:\n", 122 | "sh: expand=True\n", 123 | " sleep {5*i}\n", 124 | " echo test_{i} > test_{i}.txt\n", 125 | " echo \"Test_{i}.txt generated\"" 126 | ] 127 | }, 128 | { 129 | "cell_type": "code", 130 | "execution_count": 8, 131 | "metadata": { 132 | "kernel": "SoS", 133 | "scrolled": true 134 | }, 135 | "outputs": [ 136 | { 137 | "data": { 138 | "text/html": [ 139 | "
2 tasks completed: 0d99,99f5
" 140 | ] 141 | }, 142 | "metadata": {}, 143 | "output_type": "display_data" 144 | }, 145 | { 146 | "name": "stdout", 147 | "output_type": "stream", 148 | "text": [ 149 | "\n" 150 | ] 151 | } 152 | ], 153 | "source": [ 154 | "%sosrun task -s force" 155 | ] 156 | }, 157 | { 158 | "cell_type": "markdown", 159 | "metadata": { 160 | "kernel": "SoS" 161 | }, 162 | "source": [ 163 | "## Concurrent execution and external tasks" 164 | ] 165 | }, 166 | { 167 | "cell_type": "code", 168 | "execution_count": 6, 169 | "metadata": { 170 | "kernel": "SoS" 171 | }, 172 | "outputs": [ 173 | { 174 | "name": "stdout", 175 | "output_type": "stream", 176 | "text": [ 177 | "Counting lines of data/S20_R1.fastq\n", 178 | " 2000 data/S20_R1.fastq\n", 179 | "Counting lines of data/S20_R2.fastq\n", 180 | " 2000 data/S20_R2.fastq\n" 181 | ] 182 | } 183 | ], 184 | "source": [ 185 | "input: 'data/*.fastq', group_by=1, concurrent=True\n", 186 | "\n", 187 | "sh: expand=True\n", 188 | " echo \"Counting lines of {_input}\"\n", 189 | " sleep {5 * _index}\n", 190 | " wc -l {_input}" 191 | ] 192 | }, 193 | { 194 | "cell_type": "code", 195 | "execution_count": 9, 196 | "metadata": { 197 | "kernel": "SoS" 198 | }, 199 | "outputs": [ 200 | { 201 | "data": { 202 | "text/html": [ 203 | "
2 tasks completed: 7dfc,e082
" 204 | ] 205 | }, 206 | "metadata": {}, 207 | "output_type": "display_data" 208 | }, 209 | { 210 | "name": "stdout", 211 | "output_type": "stream", 212 | "text": [ 213 | "\n" 214 | ] 215 | } 216 | ], 217 | "source": [ 218 | "input: 'data/*.fastq', group_by=1\n", 219 | "\n", 220 | "task:\n", 221 | "sh: expand=True\n", 222 | " echo \"Counting lines of {_input}\"\n", 223 | " sleep {5 * _index}\n", 224 | " wc -l {_input}" 225 | ] 226 | } 227 | ], 228 | "metadata": { 229 | "kernelspec": { 230 | "display_name": "SoS", 231 | "language": "sos", 232 | "name": "sos" 233 | }, 234 | "language_info": { 235 | "codemirror_mode": "sos", 236 | "file_extension": ".sos", 237 | "mimetype": "text/x-sos", 238 | "name": "sos", 239 | "nbconvert_exporter": "sos_notebook.converter.SoS_Exporter", 240 | "pygments_lexer": "sos" 241 | }, 242 | "sos": { 243 | "default_kernel": "SoS", 244 | "kernels": [ 245 | [ 246 | "SoS", 247 | "sos", 248 | "", 249 | "" 250 | ] 251 | ], 252 | "panel": { 253 | "displayed": true, 254 | "height": 0, 255 | "style": "side" 256 | }, 257 | "version": "0.9.16.7" 258 | } 259 | }, 260 | "nbformat": 4, 261 | "nbformat_minor": 2 262 | } 263 | -------------------------------------------------------------------------------- /Dockerfile: -------------------------------------------------------------------------------- 1 | # Copyright (c) Bo Peng and the University of Texas MD Anderson Cancer Center 2 | # Distributed under the terms of the 3-clause BSD License. 3 | 4 | FROM vatlab/sos-notebook 5 | 6 | MAINTAINER Bo Peng 7 | 8 | USER root 9 | COPY . ${HOME} 10 | RUN chown -R ${NB_UID} ${HOME} 11 | USER ${NB_USER} 12 | 13 | # Specify the default command to run 14 | CMD ["jupyter", "lab", "--ip", "0.0.0.0"] 15 | 16 | 17 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2017 Stephen Eglen 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # SoS: Using multiple kernels in a notebook 2 | 3 | [Script of Scripts](https://vatlab.github.io/sos-docs) is a polyglot 4 | notebook and a workflow engine. Ignoring the workflow engine part, SoS 5 | Notebook provides a SoS Kernel that acts as a super kernel to all Jupyter 6 | kernels so that you can use multiple Jupyter kernels in a single Jupyter 7 | notebook. Moreover, it provides a number of magics, most importantly `%get` 8 | to exchange variables between live kernels of supported languages. 9 | 10 | ![sos-notebook](sos-notebook.png) 11 | 12 | ## Use SoS with binder 13 | 14 | Although it is almost trivial to install SoS, setting up multiple kernels 15 | in a single binder environment is not very easy at this point. This repository 16 | contains multiple branches that demonstrates how to do it for the languages 17 | you are interested in. For more details, please refer to the [SoS 18 | Documentation](https://vatlab.github.io/sos-docs) on how to set up 19 | different kernels for SoS. 20 | 21 | ### The master branch 22 | 23 | [![Binder](http://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/binder-examples/jupyter-sos/master) 24 | 25 | The master branch uses a `Dockerfile` to set up most kernels that SoS 26 | supports. The docker file is derived from [mdabioinfo/sos-notebook](https://hub.docker.com/r/mdabioinfo/sos-notebook/tags/), which is in turn derived from [Jupyter Notebook Data Science 27 | Stack](https://github.com/jupyter/docker-stacks/tree/master/datascience-notebook) and contains the following kernels: 28 | 29 | * Python 2 kernel for Python 2.7 30 | * Python 3 kernel for Python 3.6 31 | * [Bash kernel](https://github.com/takluyver/bash_kernel) for using bash commands 32 | * [iJavaScript](https://github.com/n-riesco/ijavascript) for node.js 33 | * [iJulia](https://github.com/JuliaLang/IJulia.jl) for Julia 34 | * [ir](https://github.com/IRkernel/IRkernel) kernel for R 35 | * [markdown](https://github.com/vatlab/markdown-kernel) kernel that allows the expansion of SoS (Python) expressions in markdown contents. 36 | * [Octave Kernel](https://github.com/Calysto/octave_kernel) for octave 37 | * [SPARQL kernel](https://github.com/paulovn/sparql-kernel) for Sparql, included to demonstrate how SoS works with 38 | any Jupyter kernel (not in a language that SoS understands) 39 | 40 | SoS also supports other languages such as Ruby, MATLAB, and SAS but they 41 | are not included since this image is already very big. 42 | 43 | This branch includes mostly examples for a talk on SoS during JupyterCon2018. You can watch the talk on Youtube 44 | using [this link](https://www.youtube.com/watch?v=U75eKosFbp8) if you are intested in learning SoS. 45 | 46 | 47 | ### The Python-Julia branch 48 | 49 | [![Binder](http://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/binder-examples/jupyter-sos/python-julia) 50 | 51 | This branch is much more lightweight as it contains only Python 3, Julia, 52 | and SoS kernels. It specifies the environment using 53 | 54 | * `environment.yml`: an anaconda python environment, also installs SoS and SoS Notebook 55 | * `REQURE`: a Julia environment with recommended packages 56 | * `postBuild`: Post build command to install the SoS Kernel. 57 | 58 | This branch contains a notebook `python-and-julia.ipynb` which demonstrates 59 | how to use Python3 and Julia in a single Jupyter notebook. 60 | 61 | ### The Python-R branch 62 | 63 | [![Binder](http://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/binder-examples/jupyter-sos/python-r) 64 | 65 | This branch contains only Python 3, R, and SoS kernels. It specifies the environment using 66 | 67 | * `environment.yml`: an anaconda python environment, also installs SoS and SoS Notebook 68 | * `runtime.txt`: specify version of R as [MRAN](https://mran.microsoft.com/) snapshots 69 | * `install.R`: additional packages to install 70 | * `postBuild`: Post build command to install the SoS Kernel. 71 | 72 | This branch contains a notebook `python-and-r.ipynb` which demonstrates 73 | how to use Python3 and R in a single Jupyter notebook. 74 | 75 | -------------------------------------------------------------------------------- /REQUIRE: -------------------------------------------------------------------------------- 1 | PyPlot 2 | Feather 3 | DataFrames 4 | NamedArrays 5 | -------------------------------------------------------------------------------- /sos-notebook.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/binder-examples/jupyter-sos/b1e5b13c99944371fc0257808d50c15b92e459da/sos-notebook.png --------------------------------------------------------------------------------