Integrate dask-labextension into binder deployment (dask#38)

* update versions
* move .images to images
* Add postBuild script and JupyterLab workspace
* add Welcome file
* add dask-horizontal logo image

Work done with @ian-r-rose

Welcome.md

@@ -0,0 +1,29 @@
+
+<img src="images/dask-horizontal.svg" width="50%" align="right">
+
+Welcome To Dask Examples
+========================
+
+This is a live session from which you can run example notebooks showing how to use Dask.
+
+A file browser listing example notebooks is available to the left.  There are overview notebooks about topics like arrays, dataframes, and machine learning at the top-level, as well as more focused notebooks within sub-directories.
+
+Dask dashboard plots are available to the right.  These will activate when you
+run the cells in your Jupyter notebooks that create a Dask `Client` (these are already written for you).
+
+To get started, double click on a notebook on the left, like `dataframes.ipynb`, and start running through the Jupyter notebook cells.
+
+Learn More
+----------
+
+Links are available within each notebook for additional documentation on that topic.
+
+For more information about Dask in general please visit [dask.pydata.org](https://dask.pydata.org).
+
+For more information about these examples please visit [github.com/dask/dask-examples](https://github.com/dask/dask-examples)
+
+
+Where is this running?
+----------------------
+
+This session is running on [mybinder.org](https://mybinder.org), a service designed and maintained by the Jupyter community, generously funded by the Gordon and Betty Moore Foundation, and currently running on Google Cloud Platform.

array.ipynb

@@ -6,7 +6,7 @@
    "source": [
     "# Dask Arrays\n",
     "\n",
-    "<img src=\".images/dask-array-black-text.svg\" \n",
+    "<img src=\"images/dask-array-black-text.svg\" \n",
     "     align=\"right\"\n",
     "     alt=\"Dask arrays are blocked numpy arrays\">\n",
     "     \n",

binder/environment.yml

@@ -1,14 +1,15 @@
 channels:
-  - defaults
   - conda-forge
 dependencies:
-  - bokeh=0.12
-  - dask==0.18.2
-  - dask-ml==0.9.0
-  - distributed==1.22.1
+  - bokeh=0.13
+  - dask=0.19.1
+  - dask-ml=0.9.0
+  - distributed=1.23.1
+  - jupyterlab=0.34
+  - nodejs=8.9
   - numpy
   - pandas
-  - pyarrow==0.9.0
+  - pyarrow==0.10.0
   - scikit-learn
   - matplotlib
   - nbserverproxy

binder/jupyterlab-workspace.json

@@ -0,0 +1,93 @@
+{
+  "data": {
+    "layout-restorer:data": {
+      "main": {
+        "dock": {
+          "type": "split-area",
+          "orientation": "horizontal",
+          "sizes": [
+            0.5,
+            0.5
+          ],
+          "children": [
+            {
+              "type": "tab-area",
+              "currentIndex": 0,
+              "widgets": [
+                "application-mimedocuments:Welcome.md:Markdown Preview"
+              ]
+            },
+            {
+              "type": "split-area",
+              "orientation": "vertical",
+              "sizes": [
+                0.67,
+                0.33
+              ],
+              "children": [
+                {
+                  "type": "tab-area",
+                  "currentIndex": 0,
+                  "widgets": [
+                    "dask-dashboard-launcher:individual-task-stream"
+                  ]
+                },
+                {
+                  "type": "tab-area",
+                  "currentIndex": 0,
+                  "widgets": [
+                    "dask-dashboard-launcher:individual-progress"
+                  ]
+                }
+              ]
+            }
+          ]
+        },
+        "mode": "multiple-document",
+        "current": "application-mimedocuments:Welcome.md:Markdown Preview"
+      },
+      "left": {
+        "collapsed": false,
+        "current": "filebrowser",
+        "widgets": [
+          "filebrowser",
+          "running-sessions",
+          "dask-dashboard-launcher",
+          "command-palette",
+          "tab-manager"
+        ]
+      },
+      "right": {
+        "collapsed": true,
+        "widgets": []
+      }
+    },
+    "file-browser-filebrowser:cwd": {
+      "path": ""
+    },
+    "dask-dashboard-launcher:individual-task-stream": {
+      "data": {
+        "route": "individual-task-stream",
+        "label": "Task Stream"
+      }
+    },
+    "dask-dashboard-launcher:individual-progress": {
+      "data": {
+        "route": "individual-progress",
+        "label": "Progress"
+      }
+    },
+    "dask-dashboard-launcher": {
+      "url": "DASK_DASHBOARD_URL"
+    },
+    "application-mimedocuments:Welcome.md:Markdown Preview": {
+      "data": {
+        "path": "Welcome.md",
+        "factory": "Markdown Preview"
+      }
+    }
+  },
+  "metadata": {
+    "id": "/lab"
+  }
+}

binder/make_workspace.py

@@ -0,0 +1,12 @@
+import os, shutil
+from jupyterlab_launcher.workspaces_handler import _slug
+
+service_path = os.environ.get('JUPYTERHUB_SERVICE_PREFIX')
+home = os.environ.get('HOME')
+workspace_path = service_path.strip('/') + '/lab' if service_path else '/lab'
+filename = _slug(workspace_path, '') + '.jupyterlab-workspace'
+shutil.copy(
+        './binder/jupyterlab-workspace.json',
+        f'{home}/.jupyter/lab/workspaces/{filename}'
+        )
+

binder/postBuild

@@ -0,0 +1,4 @@
+#!/bin/bash
+
+# Install the JupyterLab dask-labextension
+jupyter labextension install dask-labextension

binder/start

@@ -0,0 +1,12 @@
+#!/bin/bash
+
+# Replace DASK_DASHBOARD_URL with the proxy location
+sed -i -e "s|DASK_DASHBOARD_URL|/user/${JUPYTERHUB_USER}/proxy/8787|g" binder/jupyterlab-workspace.json
+
+# Copy into the workspaces directory
+# NOTE: this relies on internal path logic to the JupyterLab workspaces handler.
+# As soon as a CLI becomes available for this, we should use that.
+mkdir -p ${HOME}/.jupyter/lab/workspaces
+python ./binder/make_workspace.py
+
+exec "$@"

dataframe.ipynb

@@ -6,7 +6,7 @@
    "source": [
     "# Dask DataFrames\n",
     "\n",
-    "<img src=\".images/dask-dataframe.svg\" \n",
+    "<img src=\"images/dask-dataframe.svg\" \n",
     "     align=\"right\"\n",
     "     width=\"20%\"\n",
     "     alt=\"Dask dataframes are blocked Pandas dataframes\">\n",
@@ -356,7 +356,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.5"
+   "version": "3.6.4"
   }
  },
  "nbformat": 4,

machine-learning.ipynb

@@ -27,7 +27,7 @@
    "source": [
     "## Distributed Training\n",
     "\n",
-    "<img src=\".images/scikit-learn-logo-notext.png\"/> <img src=\".images/joblib_logo.svg\" width=\"20%\"/> \n",
+    "<img src=\"images/scikit-learn-logo-notext.png\"/> <img src=\"images/joblib_logo.svg\" width=\"20%\"/> \n",
     "\n",
     "Scikit-learn uses [joblib](http://joblib.readthedocs.io/) for single-machine parallelism. This lets you train most estimators (anything that accepts an `n_jobs` parameter) using all the cores of your laptop or workstation.\n",
     "\n",

machine-learning/distributed-scikit-learn-for-cpu-bound-problems.ipynb

@@ -58,7 +58,7 @@
    "source": [
     "## Distributed Training\n",
     "\n",
-    "<img src=\".images/scikit-learn-logo-notext.png\"/> <img src=\".images/joblib_logo.svg\" width=\"20%\"/> \n",
+    "<img src=\"images/scikit-learn-logo-notext.png\"/> <img src=\"images/joblib_logo.svg\" width=\"20%\"/> \n",
     "\n",
     "Scikit-learn uses [joblib](http://joblib.readthedocs.io/) for single-machine parallelism. This lets you train most estimators (anything that accepts an `n_jobs` parameter) using all the cores of your laptop or workstation.\n",
     "\n",