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    • Swen Vermeul's avatar
    new pybis demo notebook to show the new features  
    Swen Vermeul committed
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           "\n",
       "            <table border=\"1\" class=\"dataframe\">\n",
       "            <thead>\n",
       "                <tr style=\"text-align: right;\">\n",
       "                <th>attribute</th>\n",
       "                <th>value</th>\n",
       "                </tr>\n",
       "            </thead>\n",
       "            <tbody>\n",
       "        <tr> <td>code</td> <td>MY_EXPERIMENT4</td> </tr><tr> <td>permId</td> <td>20160924020719018-358</td> </tr><tr> <td>identifier</td> <td>/MY_NEW_SPACE/VERMEUL_PROJECT/MY_EXPERIMENT4</td> </tr><tr> <td>type</td> <td>DEFAULT_EXPERIMENT</td> </tr><tr> <td>space</td> <td></td> </tr><tr> <td>project</td> <td>/MY_NEW_SPACE/VERMEUL_PROJECT</td> </tr><tr> <td>tags</td> <td>['A_tag', 'another_tag', 'too_late', 'tre']</td> </tr><tr><td>attachments</td><td></td></tr>\n",
       "            </tbody>\n",
       "            </table>\n",
       "        "
      ],
      "text/plain": [
       "<pybis.pybis.Experiment at 0x7f10ecdadd30>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "e = o.get_experiment('/MY_NEW_SPACE/VERMEUL_PROJECT/MY_EXPERIMENT4')\n",
    "e"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "controlled vocabulary: find out which terms are allowed by adding an underscore to the property."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "            <table border=\"1\" class=\"dataframe\">\n",
       "            <thead>\n",
       "                <tr style=\"text-align: right;\">\n",
       "                <th>vocabulary term</th>\n",
       "                <th>label</th>\n",
       "                <th>description</th>\n",
       "                <th>vocabulary</th>\n",
       "                </tr>\n",
       "            </thead>\n",
       "            <tbody>\n",
       "        <tr> <td>CROSS</td> <td>cross</td> <td>The strain was produced by crossing two parent strains</td> <td>ORIGIN</td> </tr><tr> <td>TRANSFORMATION</td> <td>transformation</td> <td>The strain/ cell line was obtained by transformation</td> <td>ORIGIN</td> </tr><tr> <td>SPORULATION</td> <td>transformation sporulation</td> <td>The strain was obtained by sporulating a parent diploid strain</td> <td>ORIGIN</td> </tr><tr> <td>NEGATIVE_SELECTION</td> <td>negative selection</td> <td>The strain/cell line was obtained by negative selection</td> <td>ORIGIN</td> </tr><tr> <td>TRANSFECTION</td> <td>transfection</td> <td>The strain/cell line was obtained by transfection</td> <td>ORIGIN</td> </tr>\n",
       "            </tbody>\n",
       "            </table>\n",
       "        "
      ],
      "text/plain": [
       "<pybis.pybis.Vocabulary at 0x7fbfcacd5a58>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s_new.p.origin_"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "assigning a wrong value to a property will lead to an error:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "Value must be one of these terms: CROSS, TRANSFORMATION, SPORULATION, NEGATIVE_SELECTION, TRANSFECTION",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m\u001b[0m",
      "\u001b[1;31mValueError\u001b[0mTraceback (most recent call last)",
      "\u001b[1;32m<ipython-input-12-d9539d489991>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0ms_new\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0morigin\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m'crozz'\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32m/vagrant_python/PyBis/pybis/pybis.py\u001b[0m in \u001b[0;36m__setattr__\u001b[1;34m(self, name, value)\u001b[0m\n\u001b[0;32m   2099\u001b[0m             \u001b[0mvoc\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_openbis\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_terms\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mname\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2100\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mvalue\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mvoc\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mterms\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2101\u001b[1;33m                 \u001b[1;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"Value must be one of these terms: \"\u001b[0m \u001b[1;33m+\u001b[0m \u001b[1;34m\", \"\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mjoin\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mvoc\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mterms\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   2102\u001b[0m         \u001b[1;32melif\u001b[0m \u001b[0mdata_type\u001b[0m \u001b[1;32min\u001b[0m \u001b[1;33m(\u001b[0m\u001b[1;34m'INTEGER'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'BOOLEAN'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'VARCHAR'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2103\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mcheck_datatype\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata_type\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mValueError\u001b[0m: Value must be one of these terms: CROSS, TRANSFORMATION, SPORULATION, NEGATIVE_SELECTION, TRANSFECTION"
     ]
    }
   ],
   "source": [
    "s_new.p.origin = 'crozz'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "s_new.p. + TAB autocompletes all available properties for that given sample type. To show the current attributes of our new sample just use this:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "s_new.p.mating_type = 'ALPHA'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "            <table border=\"1\" class=\"dataframe\">\n",
       "            <thead>\n",
       "                <tr style=\"text-align: right;\">\n",
       "                <th>attribute</th>\n",
       "                <th>value</th>\n",
       "                </tr>\n",
       "            </thead>\n",
       "            <tbody>\n",
       "        <tr> <td>identifier</td> <td>None</td> </tr><tr> <td>permId</td> <td>None</td> </tr><tr> <td>code</td> <td>None</td> </tr><tr> <td>type</td> <td>None</td> </tr><tr> <td>space</td> <td>VERMEUL</td> </tr><tr> <td>project</td> <td>None</td> </tr><tr> <td>experiment</td> <td>None</td> </tr><tr> <td>parents</td> <td>None</td> </tr><tr> <td>children</td> <td>None</td> </tr><tr> <td>tags</td> <td>None</td> </tr>\n",
       "            </tbody>\n",
       "            </table>\n",
       "        "
      ],
      "text/plain": [
       "<pybis.pybis.Sample at 0x7f52d7cfb630>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s_new"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## working with datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from pybis import Openbis\n",
    "o = Openbis(url='https://localhost:8443', verify_certificates=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "            <table border=\"1\" class=\"dataframe\">\n",
       "            <thead>\n",
       "                <tr style=\"text-align: right;\">\n",
       "                <th>attribute</th>\n",
       "                <th>value</th>\n",
       "                </tr>\n",
       "            </thead>\n",
       "            <tbody>\n",
       "        <tr> <td>code</td> <td>CHILD_OF_SAMPLE1</td> </tr><tr> <td>permId</td> <td>20160705234504004-206</td> </tr><tr> <td>identifier</td> <td>/MY_NEW_SPACE/CHILD_OF_SAMPLE1</td> </tr><tr> <td>type</td> <td>UNKNOWN</td> </tr><tr> <td>space</td> <td>MY_NEW_SPACE</td> </tr><tr> <td>experiment</td> <td>/MY_NEW_SPACE/VERMEUL_PROJECT/MY_EXPERIMENT4</td> </tr><tr> <td>container</td> <td></td> </tr><tr> <td>components</td> <td></td> </tr><tr> <td>tags</td> <td>['A_tag', 'due']</td> </tr><tr><td>attachments</td><td></td></tr>\n",
       "            </tbody>\n",
       "            </table>\n",
       "        "
      ],
      "text/plain": [
       "<pybis.pybis.Sample at 0x7f89bae953c8>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "o.get_sample('/MY_NEW_SPACE/CHILD_OF_SAMPLE1')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "            <table border=\"1\" class=\"dataframe\">\n",
       "            <thead>\n",
       "                <tr style=\"text-align: right;\">\n",
       "                <th>attribute</th>\n",
       "                <th>value</th>\n",
       "                </tr>\n",
       "            </thead>\n",
       "            <tbody>\n",
       "        <tr> <td>code</td> <td>MY_EXPERIMENT4</td> </tr><tr> <td>permId</td> <td>20160924020719018-358</td> </tr><tr> <td>identifier</td> <td>/MY_NEW_SPACE/VERMEUL_PROJECT/MY_EXPERIMENT4</td> </tr><tr> <td>type</td> <td>DEFAULT_EXPERIMENT</td> </tr><tr> <td>space</td> <td></td> </tr><tr> <td>project</td> <td>/MY_NEW_SPACE/VERMEUL_PROJECT</td> </tr><tr> <td>tags</td> <td>['A_tag', 'another_tag', 'too_late', 'tre']</td> </tr><tr><td>attachments</td><td></td></tr>\n",
       "            </tbody>\n",
       "            </table>\n",
       "        "
      ],
      "text/plain": [
       "<pybis.pybis.Experiment at 0x7f2b0cbd14e0>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s.get_experiment()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "            <table border=\"1\" class=\"dataframe\">\n",
       "            <thead>\n",
       "                <tr style=\"text-align: right;\">\n",
       "                <th>attribute</th>\n",
       "                <th>value</th>\n",
       "                </tr>\n",
       "            </thead>\n",
       "            <tbody>\n",
       "        <tr> <td>code</td> <td>HOW_WONDERFUL</td> </tr><tr> <td>permId</td> <td>20160630105304285-81</td> </tr><tr> <td>identifier</td> <td>/MY_NEW_SPACE/HOW_WONDERFUL</td> </tr><tr> <td>type</td> <td>UNKNOWN</td> </tr><tr> <td>space</td> <td>MY_NEW_SPACE</td> </tr><tr> <td>experiment</td> <td>/MY_NEW_SPACE/VERMEUL_PROJECT/MY_EXPERIMENT4</td> </tr><tr> <td>container</td> <td></td> </tr><tr> <td>components</td> <td></td> </tr><tr> <td>tags</td> <td>['CREATE_JSON_TAG']</td> </tr><tr><td>attachments</td><td>Bildschirmfoto 2016-10-14 um 23.01.06.png</td></tr>\n",
       "            </tbody>\n",
       "            </table>\n",
       "        "
      ],
      "text/plain": [
       "<pybis.pybis.Sample at 0x7f89bae8bd30>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s = o.get_sample('/MY_NEW_SPACE/HOW_WONDERFUL')\n",
    "s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "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>properties</th>\n",
       "      <th>type</th>\n",
       "      <th>sample</th>\n",
       "      <th>registrationDate</th>\n",
       "      <th>modificationDate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>20160721002154012-269</td>\n",
       "      <td>{}</td>\n",
       "      <td>JUPYTER_NOTEBOOK</td>\n",
       "      <td>/MY_NEW_SPACE/HOW_WONDERFUL</td>\n",
       "      <td>2016-07-21 00:22:11</td>\n",
       "      <td>2016-11-06 22:59:21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20160721002157457-270</td>\n",
       "      <td>{}</td>\n",
       "      <td>JUPYTER_RESULT</td>\n",
       "      <td>/MY_NEW_SPACE/HOW_WONDERFUL</td>\n",
       "      <td>2016-07-21 00:22:11</td>\n",
       "      <td>2016-11-06 22:59:21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20160721002157457-271</td>\n",
       "      <td>{'NAME': 'my_delightful_analysis', 'DESCRIPTIO...</td>\n",
       "      <td>JUPYTER_CONTAINER</td>\n",
       "      <td>/MY_NEW_SPACE/HOW_WONDERFUL</td>\n",
       "      <td>2016-07-21 00:22:11</td>\n",
       "      <td>2016-11-21 00:51:47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>20160721005440169-272</td>\n",
       "      <td>{}</td>\n",
       "      <td>JUPYTER_NOTEBOOK</td>\n",
       "      <td>/MY_NEW_SPACE/HOW_WONDERFUL</td>\n",
       "      <td>2016-07-21 00:54:51</td>\n",
       "      <td>2016-11-06 22:59:21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20160721005441238-273</td>\n",
       "      <td>{}</td>\n",
       "      <td>JUPYTER_RESULT</td>\n",
       "      <td>/MY_NEW_SPACE/HOW_WONDERFUL</td>\n",
       "      <td>2016-07-21 00:54:51</td>\n",
       "      <td>2016-11-06 22:59:21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>20160818092513667-332</td>\n",
       "      <td>{}</td>\n",
       "      <td>JUPYTER_NOTEBOOK</td>\n",
       "      <td>/MY_NEW_SPACE/HOW_WONDERFUL</td>\n",
       "      <td>2016-08-18 09:25:15</td>\n",
       "      <td>2016-11-06 22:59:21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>20160818092513706-333</td>\n",
       "      <td>{}</td>\n",
       "      <td>JUPYTER_RESULT</td>\n",
       "      <td>/MY_NEW_SPACE/HOW_WONDERFUL</td>\n",
       "      <td>2016-08-18 09:25:15</td>\n",
       "      <td>2016-11-06 22:59:21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>20160826103944978-335</td>\n",
       "      <td>{}</td>\n",
       "      <td>JUPYTER_NOTEBOOK</td>\n",
       "      <td>/MY_NEW_SPACE/HOW_WONDERFUL</td>\n",
       "      <td>2016-08-26 10:39:46</td>\n",
       "      <td>2016-11-06 22:59:21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>20160826103945007-336</td>\n",
       "      <td>{}</td>\n",
       "      <td>JUPYTER_RESULT</td>\n",
       "      <td>/MY_NEW_SPACE/HOW_WONDERFUL</td>\n",
       "      <td>2016-08-26 10:39:46</td>\n",
       "      <td>2016-11-06 22:59:21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>20160929145446441-365</td>\n",
       "      <td>{}</td>\n",
       "      <td>JUPYTER_NOTEBOOK</td>\n",
       "      <td>/MY_NEW_SPACE/HOW_WONDERFUL</td>\n",
       "      <td>2016-09-29 14:54:47</td>\n",
       "      <td>2016-11-06 22:59:21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>20160929145446460-366</td>\n",
       "      <td>{}</td>\n",
       "      <td>JUPYTER_RESULT</td>\n",
       "      <td>/MY_NEW_SPACE/HOW_WONDERFUL</td>\n",
       "      <td>2016-09-29 14:54:47</td>\n",
       "      <td>2016-11-06 22:59:21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>20160929145446460-367</td>\n",
       "      <td>{'NAME': 'crc32 check', 'DESCRIPTION': 'should...</td>\n",
       "      <td>JUPYTER_CONTAINER</td>\n",
       "      <td>/MY_NEW_SPACE/HOW_WONDERFUL</td>\n",
       "      <td>2016-09-29 14:54:47</td>\n",
       "      <td>2016-11-06 22:59:21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>20161121005146312-396</td>\n",
       "      <td>{}</td>\n",
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       "      <td>/MY_NEW_SPACE/HOW_WONDERFUL</td>\n",
       "      <td>2016-11-21 00:51:47</td>\n",
       "      <td>2016-11-21 00:53:59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>20161121005146338-397</td>\n",
       "      <td>{}</td>\n",
       "      <td>JUPYTER_RESULT</td>\n",
       "      <td>/MY_NEW_SPACE/HOW_WONDERFUL</td>\n",
       "      <td>2016-11-21 00:51:47</td>\n",
       "      <td>2016-11-21 00:53:59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>20161121005146338-398</td>\n",
       "      <td>{'NAME': 'my new data analysis', 'DESCRIPTION'...</td>\n",
       "      <td>JUPYTER_CONTAINER</td>\n",
       "      <td>/MY_NEW_SPACE/HOW_WONDERFUL</td>\n",
       "      <td>2016-11-21 00:51:47</td>\n",
       "      <td>2016-11-21 00:53:59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>20161121005357966-399</td>\n",
       "      <td>{}</td>\n",
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           "      <td>JUPYTER_NOTEBOOK</td>\n",
       "      <td>/MY_NEW_SPACE/HOW_WONDERFUL</td>\n",
       "      <td>2016-11-21 00:53:59</td>\n",
       "      <td>2016-11-21 00:53:59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>20161121005357983-400</td>\n",
       "      <td>{}</td>\n",
       "      <td>JUPYTER_RESULT</td>\n",
       "      <td>/MY_NEW_SPACE/HOW_WONDERFUL</td>\n",
       "      <td>2016-11-21 00:53:59</td>\n",
       "      <td>2016-11-21 00:53:59</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
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          ],
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         "execution_count": 21,
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         "metadata": {},
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        "s.get_datasets()"
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       "execution_count": 22,
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       "metadata": {
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   "source": [
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        "ds = s.get_datasets()[11]"
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       ]
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       "execution_count": 23,
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         "execution_count": 22,
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       "execution_count": 30,
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         "execution_count": 30,
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        "ds.get_files()[['pathInDataSet']]"
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     "ename": "TypeError",
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     "traceback": [
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      "\u001b[1;31mTypeError\u001b[0m: get_datasets() got an unexpected keyword argument 'withSamples'"
     ]
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        }
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        "o.get_datasets(withSamples='20160630105304285-81')"
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       "      <td>/MY_NEW_SPACE/HOW_WONDERFUL</td>\n",
       "      <td>2016-11-21 00:51:47</td>\n",
       "      <td>2016-11-21 00:53:59</td>\n",
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           "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
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           "<pybis.pybis.Things at 0x7fa301974c18>"
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          ]
     },
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         "execution_count": 5,
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         "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
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        "o.get_datasets(type='JUPYTER_CONTAINER')"
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       ]
  },
  {
   "cell_type": "code",
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       "execution_count": 66,
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       "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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         "data": {
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          "text/html": [
       "\n",
       "            <table border=\"1\" class=\"dataframe\">\n",
       "            <thead>\n",
       "                <tr style=\"text-align: right;\">\n",
       "                <th>attribute</th>\n",
       "                <th>value</th>\n",
       "                </tr>\n",
       "            </thead>\n",
       "            <tbody>\n",
       "        <tr> <td>code</td> <td>20160721002157457-271</td> </tr><tr> <td>permId</td> <td>20160721002157457-271</td> </tr><tr> <td>type</td> <td>JUPYTER_CONTAINER</td> </tr><tr> <td>experiment</td> <td>/MY_NEW_SPACE/VERMEUL_PROJECT/MY_EXPERIMENT4</td> </tr><tr> <td>sample</td> <td>/MY_NEW_SPACE/HOW_WONDERFUL</td> </tr><tr> <td>parents</td> <td>[]</td> </tr><tr> <td>children</td> <td>['20160817175233002-331', '20161121005146338-398']</td> </tr><tr> <td>container</td> <td></td> </tr><tr> <td>components</td> <td></td> </tr><tr> <td>tags</td> <td>[]</td> </tr>\n",
       "            </tbody>\n",
       "            </table>\n",
       "        "
      ],
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           "<pybis.pybis.DataSet at 0x7f3140f570f0>"
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          ]
     },
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         "execution_count": 66,
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         "metadata": {},
     "output_type": "execute_result"
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        }
   ],
   "source": [
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        "ds = o.get_dataset('20160721002157457-271')\n",
    "ds"
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       ]
  },
  {
   "cell_type": "code",
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       "execution_count": 10,
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       "metadata": {
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        "collapsed": false,
    "scrolled": true
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       },
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       "outputs": [],
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       "source": [
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        "dss = o.get_datasets(type='JUPYTER_CONTAINER')"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "files = ds.get_files()\n",
    "files[0]"
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       ]
  },
  {
   "cell_type": "code",
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       "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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         "name": "stdout",
     "output_type": "stream",
     "text": [
      "Files downloaded to: localhost/20160929145446460-367\n"
     ]
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        }
   ],
   "source": [
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        "ds.download()"
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       ]
  },
  {
   "cell_type": "code",
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       "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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         "name": "stdout",
     "output_type": "stream",
     "text": [
      "localhost/20160929145446460-367\r\n",
      "localhost/20160929145446460-367/original\r\n",
      "localhost/20160929145446460-367/original/JUPYTER_RESULT\r\n",
      "localhost/20160929145446460-367/original/JUPYTER_RESULT/PLATE1_A01_06_GFP.jpg\r\n",
      "localhost/20160929145446460-367/original/JUPYTER_NOTEBOOk\r\n",
      "localhost/20160929145446460-367/original/JUPYTER_NOTEBOOk/pybis demo.ipynb\r\n"
     ]
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        }
   ],
   "source": [
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        "!find localhost/20160929145446460-367"
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       ]
  },
  {
   "cell_type": "code",
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       "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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         "data": {
      "text/plain": [
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           "[{'@id': 1,\n",
       "  '@type': 'FileInfoDssDTO',\n",
       "  'crc32Checksum': 1397688417,\n",
       "  'fileSize': '209715200',\n",
       "  'isDirectory': False,\n",
       "  'pathInDataSet': 'original/JUPYTER_RESULT/large_testfile',\n",
       "  'pathInListing': 'large_testfile'}]"
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          ]
     },
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         "metadata": {},
     "output_type": "execute_result"
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        }
   ],
   "source": [
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        "ds2 = o.get_dataset('20160721002157457-271')\n",
    "ds2.get_file_list(start_folder='original/JUPYTER_RESULT/large_testfile')"
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       ]
  },
  {
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       "cell_type": "code",
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       "execution_count": 17,
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       "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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         "name": "stdout",
     "output_type": "stream",
     "text": [
      "Files downloaded to: localhost/20160721002157457-271\n"
     ]
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        }
   ],
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       "source": [
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        "ds2.download('original/JUPYTER_RESULT/large_testfile')"
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       ]
  },
  {
   "cell_type": "code",
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       "execution_count": 28,
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       "metadata": {
    "collapsed": false
   },
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       "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Files downloaded to: localhost/20160721002157457-271\n"
     ]
    }
   ],
   "source": [
    "ds2.download()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## upload data to openBIS\n",
    "The pybis data ingestion service «jupyter-uploader-api» in the openBIS instance is needed in order to work. Files are first uploaded to session workspace, then the ingestion service is activated which in turn registers 3 datasets:\n",
    "- a JUPYTER_CONTAINER containing:\n",
    "- JUPYTER_NOTEBOOK (containing the notebook files)\n",
    "- JUPYTER_RESULTS (containing any result files)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false
   },
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       "outputs": [
    {
     "data": {
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          "text/html": [
       "\n",
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           "            <table border=\"1\" class=\"dataframe\">\n",
       "            <thead>\n",
       "                <tr style=\"text-align: right;\">\n",
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           "                <th>attribute</th>\n",
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           "                <th>value</th>\n",
       "                </tr>\n",
       "            </thead>\n",
    Show full blame