jupyter notebook added

747f28a7 · Swen Vermeul · d1f614b1 · 747f28a7
Commit 747f28a7 authored 8 years ago by Swen Vermeul
--- a/src/python/pybis/pybis playground localhost.ipynb
+++ b/src/python/pybis/pybis playground localhost.ipynb
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Using pybis"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Log into openBIS"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "········\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "'vermeul-160707110248298xF6BBB7B360CEB4604AAC9914FFC064A5'"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from pybis import Openbis\n",
+    "import getpass\n",
+    "o = Openbis('https://localhost:8443', verify_certificates=False)\n",
+    "\n",
+    "password = getpass.getpass()\n",
+    "o.login('vermeul',password)\n",
+    "o.token"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## create a sample"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "new_sample = o.new_sample(sample_name='oh_wie_schoen_ist_panama5', space_name='VERMEUL', tags=['uno','due','tre'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'/VERMEUL/OH_WIE_SCHOEN_IST_PANAMA5'"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "new_sample.ident"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## get a sample"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'20160630112919449-91'"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "s = o.get_sample(\"/VERMEUL/OH_WIE_SCHOEN_IST_PANAMA4\")\n",
+    "s.permid"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'/VERMEUL/OH_WIE_SCHOEN_IST_PANAMA4'"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "s.ident"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "datasets = s.get_datasets()\n",
+    "ds1 = datasets[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[{'@id': 1,\n",
+       "  '@type': 'FileInfoDssDTO',\n",
+       "  'crc32Checksum': None,\n",
+       "  'fileSize': '-1',\n",
+       "  'isDirectory': True,\n",
+       "  'pathInDataSet': 'original',\n",
+       "  'pathInListing': 'original'},\n",
+       " {'@id': 2,\n",
+       "  '@type': 'FileInfoDssDTO',\n",
+       "  'crc32Checksum': None,\n",
+       "  'fileSize': '-1',\n",
+       "  'isDirectory': True,\n",
+       "  'pathInDataSet': 'original/results',\n",
+       "  'pathInListing': 'original/results'},\n",
+       " {'@id': 3,\n",
+       "  '@type': 'FileInfoDssDTO',\n",
+       "  'crc32Checksum': -895786725,\n",
+       "  'fileSize': '16',\n",
+       "  'isDirectory': False,\n",
+       "  'pathInDataSet': 'original/results/blublu',\n",
+       "  'pathInListing': 'original/results/blublu'}]"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds1.get_file_list()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "ds1.download('original/results/blublu')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "this is my data."
+     ]
+    }
+   ],
+   "source": [
+    "cat localhost/20160705171928021-202/original/results/blublu"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## create a dataset and upload data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "dataset = o.new_dataset(\n",
+    "    sample=s, type='JUPYTER_NOTEBOOK', \n",
+    "    datastore='DSS1', \n",
+    "    files=['pybis_playground_localhost.ipynb']\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "dataset.register()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Analysis ##\n",
+    "An analysis has a name, description and parent dataset. Anytime it is saved, a new version of it is saved. On openBIS, an analysis is a container object which contains the result datafiles and the jupyter notebook. If an analysis is saved a second time, two new datasets are generated, both having parents of their previous datasets set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "analysis = o.new_analysis(\n",
+    "    parent=dataset,\n",
+    "    name=\"my analysis\",\n",
+    "    description= \"this time, there should be a meaningful explanation\",\n",
+    "    results=[\"results/blublu_processed\"]\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "analysis.save()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## get available dataset types"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>code</th>\n",
+       "      <th>description</th>\n",
+       "      <th>kind</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>ELN_PREVIEW</td>\n",
+       "      <td>ELN Preview image</td>\n",
+       "      <td>PHYSICAL</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>SEQ_FILE</td>\n",
+       "      <td></td>\n",
+       "      <td>PHYSICAL</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>RAW_DATA</td>\n",
+       "      <td></td>\n",
+       "      <td>PHYSICAL</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>ANALYZED_DATA</td>\n",
+       "      <td></td>\n",
+       "      <td>PHYSICAL</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>ATTACHMENT</td>\n",
+       "      <td></td>\n",
+       "      <td>PHYSICAL</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>DRAWING_BOARD</td>\n",
+       "      <td></td>\n",
+       "      <td>PHYSICAL</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>JUPYTER_CONTAINER</td>\n",
+       "      <td>Jupyter Analysis Results</td>\n",
+       "      <td>CONTAINER</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>JUPYTER_NOTEBOOK</td>\n",
+       "      <td>Analysis Notebook Files</td>\n",
+       "      <td>PHYSICAL</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>UNKNOWN</td>\n",
+       "      <td>Unknown</td>\n",
+       "      <td>PHYSICAL</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>JUPYTER_RESULT</td>\n",
+       "      <td>Analysis Results Files</td>\n",
+       "      <td>PHYSICAL</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                code               description       kind\n",
+       "0        ELN_PREVIEW         ELN Preview image   PHYSICAL\n",
+       "1           SEQ_FILE                             PHYSICAL\n",
+       "2           RAW_DATA                             PHYSICAL\n",
+       "3      ANALYZED_DATA                             PHYSICAL\n",
+       "4         ATTACHMENT                             PHYSICAL\n",
+       "5      DRAWING_BOARD                             PHYSICAL\n",
+       "6  JUPYTER_CONTAINER  Jupyter Analysis Results  CONTAINER\n",
+       "7   JUPYTER_NOTEBOOK   Analysis Notebook Files   PHYSICAL\n",
+       "8            UNKNOWN                   Unknown   PHYSICAL\n",
+       "9     JUPYTER_RESULT    Analysis Results Files   PHYSICAL"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "o.get_dataset_types()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.5.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
+%% Cell type:markdown id: tags:
+# Using pybis
+%% Cell type:markdown id: tags:
+## Log into openBIS
+%% Cell type:code id: tags:
+``` python
+from pybis import Openbis
+import getpass
+o = Openbis('https://localhost:8443', verify_certificates=False)
+password = getpass.getpass()
+o.login('vermeul',password)
+o.token
+```
+%% Output
+    ········
+    'vermeul-160707110248298xF6BBB7B360CEB4604AAC9914FFC064A5'
+%% Cell type:markdown id: tags:
+## create a sample
+%% Cell type:code id: tags:
+``` python
+new_sample = o.new_sample(sample_name='oh_wie_schoen_ist_panama5', space_name='VERMEUL', tags=['uno','due','tre'])
+```
+%% Cell type:code id: tags:
+``` python
+new_sample.ident
+```
+%% Output
+    '/VERMEUL/OH_WIE_SCHOEN_IST_PANAMA5'
+%% Cell type:markdown id: tags:
+## get a sample
+%% Cell type:code id: tags:
+``` python
+s = o.get_sample("/VERMEUL/OH_WIE_SCHOEN_IST_PANAMA4")
+s.permid
+```
+%% Output
+    '20160630112919449-91'
+%% Cell type:code id: tags:
+``` python
+s.ident
+```
+%% Output
+    '/VERMEUL/OH_WIE_SCHOEN_IST_PANAMA4'
+%% Cell type:code id: tags:
+``` python
+datasets = s.get_datasets()
+ds1 = datasets[0]
+```
+%% Cell type:code id: tags:
+``` python
+ds1.get_file_list()
+```
+%% Output
+    [{'@id': 1,
+      '@type': 'FileInfoDssDTO',
+      'crc32Checksum': None,
+      'fileSize': '-1',
+      'isDirectory': True,
+      'pathInDataSet': 'original',
+      'pathInListing': 'original'},
+     {'@id': 2,
+      '@type': 'FileInfoDssDTO',
+      'crc32Checksum': None,
+      'fileSize': '-1',
+      'isDirectory': True,
+      'pathInDataSet': 'original/results',
+      'pathInListing': 'original/results'},
+     {'@id': 3,
+      '@type': 'FileInfoDssDTO',
+      'crc32Checksum': -895786725,
+      'fileSize': '16',
+      'isDirectory': False,
+      'pathInDataSet': 'original/results/blublu',
+      'pathInListing': 'original/results/blublu'}]
+%% Cell type:code id: tags:
+``` python
+ds1.download('original/results/blublu')
+```
+%% Cell type:code id: tags:
+``` python
+cat localhost/20160705171928021-202/original/results/blublu
+```
+%% Output
+    this is my data.
+%% Cell type:markdown id: tags:
+## create a dataset and upload data
+%% Cell type:code id: tags:
+``` python
+dataset = o.new_dataset(
+    sample=s, type='JUPYTER_NOTEBOOK',
+    datastore='DSS1',
+    files=['pybis_playground_localhost.ipynb']
+)
+```
+%% Cell type:code id: tags:
+``` python
+dataset.register()
+```
+%% Cell type:markdown id: tags:
+## Analysis ##
+An analysis has a name, description and parent dataset. Anytime it is saved, a new version of it is saved. On openBIS, an analysis is a container object which contains the result datafiles and the jupyter notebook. If an analysis is saved a second time, two new datasets are generated, both having parents of their previous datasets set.
+%% Cell type:code id: tags:
+``` python
+analysis = o.new_analysis(
+    parent=dataset,
+    name="my analysis",
+    description= "this time, there should be a meaningful explanation",
+    results=["results/blublu_processed"]
+)
+```
+%% Cell type:code id: tags:
+``` python
+analysis.save()
+```
+%% Cell type:markdown id: tags:
+## get available dataset types
+%% Cell type:code id: tags:
+``` python
+o.get_dataset_types()
+```
+%% Output
+                    code               description       kind
+    0        ELN_PREVIEW         ELN Preview image   PHYSICAL
+    1           SEQ_FILE                             PHYSICAL
+    2           RAW_DATA                             PHYSICAL
+    3      ANALYZED_DATA                             PHYSICAL
+    4         ATTACHMENT                             PHYSICAL
+    5      DRAWING_BOARD                             PHYSICAL
+    6  JUPYTER_CONTAINER  Jupyter Analysis Results  CONTAINER
+    7   JUPYTER_NOTEBOOK   Analysis Notebook Files   PHYSICAL
+    8            UNKNOWN                   Unknown   PHYSICAL
+    9     JUPYTER_RESULT    Analysis Results Files   PHYSICAL