diff --git a/sparcl/notebooks/sparcl-examples.ipynb b/sparcl/notebooks/sparcl-examples.ipynb
index a7c88ff..c1ef4b4 100644
--- a/sparcl/notebooks/sparcl-examples.ipynb
+++ b/sparcl/notebooks/sparcl-examples.ipynb
@@ -18,7 +18,7 @@
    "outputs": [],
    "source": [
     "__author__ = 'Steve Pothier <steve.pothier@noirlab.edu>'\n",
-    "__version__ = '20240224' # yyyymmdd; \n",
+    "__version__ = '20240306' # yyyymmdd; \n",
     "__keywords__ = ['HowTo', 'astronomy', 'tutorial', 'client', 'sparcl', 'NOIRlab']"
    ]
   },
@@ -63,7 +63,9 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "from pprint import pformat as pf\n",
@@ -102,24 +104,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
+   "execution_count": 2,
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Requirement already satisfied: sparclclient in /home/pothiers/sandbox/sparclclient/venv/lib/python3.10/site-packages (1.2.2b6)\n",
+      "Requirement already satisfied: sparclclient in /Users/alice.jacques/anaconda3/lib/python3.8/site-packages (1.2.2b5)\n",
       "Collecting sparclclient\n",
-      "  Downloading sparclclient-1.2.2b7-py2.py3-none-any.whl.metadata (566 bytes)\n",
-      "Downloading sparclclient-1.2.2b7-py2.py3-none-any.whl (111 kB)\n",
-      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m111.9/111.9 kB\u001b[0m \u001b[31m2.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m \u001b[36m0:00:01\u001b[0m\n",
-      "\u001b[?25hInstalling collected packages: sparclclient\n",
+      "  Downloading sparclclient-1.2.2b8-py2.py3-none-any.whl.metadata (566 bytes)\n",
+      "Downloading sparclclient-1.2.2b8-py2.py3-none-any.whl (111 kB)\n",
+      "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m111.7/111.7 kB\u001b[0m \u001b[31m2.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0ma \u001b[36m0:00:01\u001b[0m\n",
+      "\u001b[?25h\u001b[33mWARNING: Error parsing requirements for requests: [Errno 2] No such file or directory: '/Users/alice.jacques/anaconda3/lib/python3.8/site-packages/requests-2.24.0.dist-info/METADATA'\u001b[0m\u001b[33m\n",
+      "\u001b[0m\u001b[33mDEPRECATION: pyodbc 4.0.0-unsupported has a non-standard version number. pip 24.0 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of pyodbc or contact the author to suggest that they release a version with a conforming version number. Discussion can be found at https://github.com/pypa/pip/issues/12063\u001b[0m\u001b[33m\n",
+      "\u001b[0mInstalling collected packages: sparclclient\n",
       "  Attempting uninstall: sparclclient\n",
-      "    Found existing installation: sparclclient 1.2.2b6\n",
-      "    Uninstalling sparclclient-1.2.2b6:\n",
-      "      Successfully uninstalled sparclclient-1.2.2b6\n",
-      "Successfully installed sparclclient-1.2.2b7\n"
+      "    Found existing installation: sparclclient 1.2.2b5\n",
+      "    Uninstalling sparclclient-1.2.2b5:\n",
+      "      Successfully uninstalled sparclclient-1.2.2b5\n",
+      "Successfully installed sparclclient-1.2.2b8\n",
+      "\n",
+      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.3.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m24.0\u001b[0m\n",
+      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n"
      ]
     }
    ],
@@ -133,14 +142,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
+   "execution_count": 3,
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Run started: 2024-03-06 07:12:12.121248\n"
+      "Run started: 2024-03-06 11:50:13.175789\n"
      ]
     }
    ],
@@ -165,9 +176,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 4,
    "metadata": {
-    "scrolled": true
+    "scrolled": true,
+    "tags": []
    },
    "outputs": [
     {
@@ -187,7 +199,7 @@
     "server = 'https://sparc1.datalab.noirlab.edu'       # internal TEST Server\n",
     "#server = 'http://localhost:8050'                    # internal DEV Server\n",
     "\n",
-    "priv_dr = 'SDSS-DR17'\n",
+    "priv_dr = 'SDSS-DR17-test'\n",
     "\n",
     "# Authenticated Users that are never authorized for anything important.\n",
     "# These are authenticated on both Public and Test SSO servers.\n",
@@ -199,16 +211,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "metadata": {
-    "scrolled": true
+    "scrolled": true,
+    "tags": []
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "client=(sparclclient:1.2.2b7, api:11.0, http://localhost:8050/sparc, client_hash=1223070d1915675d0589eeb5844f9c3d535498d4, verbose=False, connect_timeout=1.1, read_timeout=5400.0)\n"
+      "client=(sparclclient:1.2.2b8, api:11.0, https://sparc1.datalab.noirlab.edu/sparc, client_hash=, verbose=False, connect_timeout=1.1, read_timeout=5400.0)\n"
      ]
     }
    ],
@@ -238,16 +251,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {},
+   "execution_count": 6,
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "{'BOSS-DR16', 'DESI-EDR', 'SDSS-DR16', 'SDSS-DR17'}"
+       "{'BOSS-DR16', 'DESI-EDR', 'SDSS-DR16', 'SDSS-DR17-test'}"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -267,9 +282,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 7,
    "metadata": {
-    "scrolled": true
+    "scrolled": true,
+    "tags": []
    },
    "outputs": [],
    "source": [
@@ -279,8 +295,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {},
+   "execution_count": 8,
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "data": {
@@ -288,7 +306,7 @@
        "['dec', 'flux', 'ra', 'sparcl_id', 'specid', 'wavelength']"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -308,8 +326,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
-   "metadata": {},
+   "execution_count": 9,
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "data": {
@@ -333,7 +353,7 @@
        "    >>> client = SparclClient()\n",
        "    >>> client.get_all_fields()\n",
        "    ['data_release', 'datasetgroup', 'dateobs', 'dateobs_center', 'dec', 'exptime', 'flux', 'instrument', 'ivar', 'mask', 'model', 'ra', 'redshift', 'redshift_err', 'redshift_warning', 'site', 'sparcl_id', 'specid', 'specprimary', 'spectype', 'survey', 'targetid', 'telescope', 'wave_sigma', 'wavelength', 'wavemax', 'wavemin']\n",
-       "\u001b[0;31mFile:\u001b[0m      ~/sandbox/sparclclient/venv/lib/python3.10/site-packages/sparcl/client.py\n",
+       "\u001b[0;31mFile:\u001b[0m      ~/anaconda3/lib/python3.8/site-packages/sparcl/client.py\n",
        "\u001b[0;31mType:\u001b[0m      method"
       ]
      },
@@ -347,8 +367,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {},
+   "execution_count": 10,
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -372,8 +394,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
-   "metadata": {},
+   "execution_count": 11,
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "data": {
@@ -381,7 +405,7 @@
        "11.0"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -439,7 +463,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 12,
    "metadata": {
     "editable": true,
     "scrolled": true,
@@ -464,8 +488,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {},
+   "execution_count": 13,
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "out = ['sparcl_id','specid', 'ra', 'dec', 'redshift', 'spectype', 'data_release', 'redshift_err']\n",
@@ -485,16 +511,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 14,
    "metadata": {
-    "scrolled": true
+    "scrolled": true,
+    "tags": []
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "curl -X 'POST' -H 'Content-Type: application/json' -d '{\"outfields\": [\"sparcl_id\", \"specid\", \"ra\", \"dec\", \"redshift\", \"spectype\", \"data_release\", \"redshift_err\"], \"search\": [[\"spectype\", \"GALAXY\"], [\"redshift\", 0.5, 0.9], [\"data_release\", \"BOSS-DR16\", \"SDSS-DR16\"]]}' 'http://localhost:8050/sparc/find/?limit=20' | python3 -m json.tool\n"
+      "curl -X 'POST' -H 'Content-Type: application/json' -d '{\"outfields\": [\"sparcl_id\", \"specid\", \"ra\", \"dec\", \"redshift\", \"spectype\", \"data_release\", \"redshift_err\"], \"search\": [[\"spectype\", \"GALAXY\"], [\"redshift\", 0.5, 0.9], [\"data_release\", \"BOSS-DR16\", \"SDSS-DR16\"]]}' 'https://sparc1.datalab.noirlab.edu/sparc/find/?limit=20' | python3 -m json.tool\n"
      ]
     }
    ],
@@ -513,8 +540,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
-   "metadata": {},
+   "execution_count": 15,
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "data": {
@@ -538,13 +567,13 @@
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>spectype</th>\n",
-       "      <th>specid</th>\n",
        "      <th>sparcl_id</th>\n",
-       "      <th>redshift_err</th>\n",
+       "      <th>ra</th>\n",
+       "      <th>specid</th>\n",
        "      <th>redshift</th>\n",
-       "      <th>data_release</th>\n",
+       "      <th>redshift_err</th>\n",
        "      <th>dec</th>\n",
-       "      <th>ra</th>\n",
+       "      <th>data_release</th>\n",
        "      <th>_dr</th>\n",
        "    </tr>\n",
        "  </thead>\n",
@@ -552,13 +581,241 @@
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>GALAXY</td>\n",
-       "      <td>-6444532452352045056</td>\n",
-       "      <td>bb3d4287-8a2f-479f-9c7f-1053051e4925</td>\n",
-       "      <td>0.000332</td>\n",
-       "      <td>0.761637</td>\n",
+       "      <td>00b0904d-992f-11ee-b7f9-525400aad0aa</td>\n",
+       "      <td>141.63075</td>\n",
+       "      <td>-5672178860774109184</td>\n",
+       "      <td>0.699621</td>\n",
+       "      <td>0.000212</td>\n",
+       "      <td>27.981984</td>\n",
+       "      <td>BOSS-DR16</td>\n",
+       "      <td>BOSS-DR16</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>GALAXY</td>\n",
+       "      <td>010eb4d0-992f-11ee-89de-525400aad0aa</td>\n",
+       "      <td>141.73278</td>\n",
+       "      <td>-5672178036140388352</td>\n",
+       "      <td>0.735681</td>\n",
+       "      <td>0.000296</td>\n",
+       "      <td>27.886212</td>\n",
+       "      <td>BOSS-DR16</td>\n",
+       "      <td>BOSS-DR16</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>GALAXY</td>\n",
+       "      <td>020ed77c-992f-11ee-aefb-525400aad0aa</td>\n",
+       "      <td>141.71671</td>\n",
+       "      <td>-5672175287361318912</td>\n",
+       "      <td>0.577450</td>\n",
+       "      <td>0.000168</td>\n",
+       "      <td>28.225833</td>\n",
+       "      <td>BOSS-DR16</td>\n",
+       "      <td>BOSS-DR16</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>GALAXY</td>\n",
+       "      <td>0262c5c1-992f-11ee-a797-525400aad0aa</td>\n",
+       "      <td>141.77643</td>\n",
+       "      <td>-5672174462727598080</td>\n",
+       "      <td>0.613647</td>\n",
+       "      <td>0.000221</td>\n",
+       "      <td>28.349531</td>\n",
+       "      <td>BOSS-DR16</td>\n",
+       "      <td>BOSS-DR16</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>GALAXY</td>\n",
+       "      <td>0290508b-992f-11ee-94e5-525400aad0aa</td>\n",
+       "      <td>141.69172</td>\n",
+       "      <td>-5672173912971784192</td>\n",
+       "      <td>0.611291</td>\n",
+       "      <td>0.000215</td>\n",
+       "      <td>28.440417</td>\n",
+       "      <td>BOSS-DR16</td>\n",
+       "      <td>BOSS-DR16</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>GALAXY</td>\n",
+       "      <td>02c0f331-992f-11ee-ac38-525400aad0aa</td>\n",
+       "      <td>141.40642</td>\n",
+       "      <td>-5672173363215970304</td>\n",
+       "      <td>0.742280</td>\n",
+       "      <td>0.000316</td>\n",
+       "      <td>27.313360</td>\n",
+       "      <td>BOSS-DR16</td>\n",
+       "      <td>BOSS-DR16</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>GALAXY</td>\n",
+       "      <td>02d858b6-992f-11ee-be88-525400aad0aa</td>\n",
+       "      <td>141.43253</td>\n",
+       "      <td>-5672173088338063360</td>\n",
+       "      <td>0.714333</td>\n",
+       "      <td>0.000307</td>\n",
+       "      <td>27.297940</td>\n",
+       "      <td>BOSS-DR16</td>\n",
+       "      <td>BOSS-DR16</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>GALAXY</td>\n",
+       "      <td>02eef149-992f-11ee-a3b5-525400aad0aa</td>\n",
+       "      <td>141.45293</td>\n",
+       "      <td>-5672172813460156416</td>\n",
+       "      <td>0.763182</td>\n",
+       "      <td>0.000293</td>\n",
+       "      <td>27.502474</td>\n",
+       "      <td>BOSS-DR16</td>\n",
+       "      <td>BOSS-DR16</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>GALAXY</td>\n",
+       "      <td>0315e895-992f-11ee-96ce-525400aad0aa</td>\n",
+       "      <td>141.54144</td>\n",
+       "      <td>-5672172263704342528</td>\n",
+       "      <td>0.747819</td>\n",
+       "      <td>0.000286</td>\n",
+       "      <td>27.511042</td>\n",
+       "      <td>BOSS-DR16</td>\n",
+       "      <td>BOSS-DR16</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>GALAXY</td>\n",
+       "      <td>033fb515-992f-11ee-9c1d-525400aad0aa</td>\n",
+       "      <td>141.44884</td>\n",
+       "      <td>-5672171713948528640</td>\n",
+       "      <td>0.567928</td>\n",
+       "      <td>0.000241</td>\n",
+       "      <td>27.600306</td>\n",
+       "      <td>BOSS-DR16</td>\n",
+       "      <td>BOSS-DR16</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>GALAXY</td>\n",
+       "      <td>03a05265-992f-11ee-9683-525400aad0aa</td>\n",
+       "      <td>141.49531</td>\n",
+       "      <td>-5672170614436900864</td>\n",
+       "      <td>0.724495</td>\n",
+       "      <td>0.000278</td>\n",
+       "      <td>27.739271</td>\n",
+       "      <td>BOSS-DR16</td>\n",
+       "      <td>BOSS-DR16</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>GALAXY</td>\n",
+       "      <td>03c80eda-992f-11ee-b4f2-525400aad0aa</td>\n",
+       "      <td>141.42144</td>\n",
+       "      <td>-5672170064681086976</td>\n",
+       "      <td>0.727417</td>\n",
+       "      <td>0.000175</td>\n",
+       "      <td>27.705200</td>\n",
+       "      <td>BOSS-DR16</td>\n",
+       "      <td>BOSS-DR16</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>GALAXY</td>\n",
+       "      <td>03fad572-992f-11ee-a30a-525400aad0aa</td>\n",
+       "      <td>141.62676</td>\n",
+       "      <td>-5672169514925273088</td>\n",
+       "      <td>0.723495</td>\n",
+       "      <td>0.000260</td>\n",
+       "      <td>27.756787</td>\n",
+       "      <td>BOSS-DR16</td>\n",
+       "      <td>BOSS-DR16</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>GALAXY</td>\n",
+       "      <td>04184b57-992f-11ee-bffa-525400aad0aa</td>\n",
+       "      <td>141.50548</td>\n",
+       "      <td>-5672169240047366144</td>\n",
+       "      <td>0.565133</td>\n",
+       "      <td>0.000027</td>\n",
+       "      <td>27.570483</td>\n",
+       "      <td>BOSS-DR16</td>\n",
+       "      <td>BOSS-DR16</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>GALAXY</td>\n",
+       "      <td>0431fcb5-992f-11ee-b884-525400aad0aa</td>\n",
+       "      <td>141.57763</td>\n",
+       "      <td>-5672168965169459200</td>\n",
+       "      <td>0.725325</td>\n",
+       "      <td>0.000210</td>\n",
+       "      <td>27.812046</td>\n",
+       "      <td>BOSS-DR16</td>\n",
+       "      <td>BOSS-DR16</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>GALAXY</td>\n",
+       "      <td>046666c6-992f-11ee-99ce-525400aad0aa</td>\n",
+       "      <td>141.62108</td>\n",
+       "      <td>-5672168415413645312</td>\n",
+       "      <td>0.742185</td>\n",
+       "      <td>0.000264</td>\n",
+       "      <td>27.538922</td>\n",
+       "      <td>BOSS-DR16</td>\n",
+       "      <td>BOSS-DR16</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>GALAXY</td>\n",
+       "      <td>057916a9-992f-11ee-a9ba-525400aad0aa</td>\n",
+       "      <td>141.50010</td>\n",
+       "      <td>-5672165666634575872</td>\n",
+       "      <td>0.574673</td>\n",
+       "      <td>0.000289</td>\n",
+       "      <td>27.976450</td>\n",
+       "      <td>BOSS-DR16</td>\n",
+       "      <td>BOSS-DR16</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>GALAXY</td>\n",
+       "      <td>05f59fc1-992f-11ee-8447-525400aad0aa</td>\n",
+       "      <td>141.40741</td>\n",
+       "      <td>-5672164017367134208</td>\n",
+       "      <td>0.659942</td>\n",
+       "      <td>0.000239</td>\n",
+       "      <td>28.367604</td>\n",
+       "      <td>BOSS-DR16</td>\n",
+       "      <td>BOSS-DR16</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>GALAXY</td>\n",
+       "      <td>062d0b5b-992f-11ee-aa37-525400aad0aa</td>\n",
+       "      <td>141.30648</td>\n",
+       "      <td>-5672163467611320320</td>\n",
+       "      <td>0.660208</td>\n",
+       "      <td>0.000931</td>\n",
+       "      <td>28.392667</td>\n",
+       "      <td>BOSS-DR16</td>\n",
+       "      <td>BOSS-DR16</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>GALAXY</td>\n",
+       "      <td>0666a4e2-992f-11ee-969f-525400aad0aa</td>\n",
+       "      <td>141.50529</td>\n",
+       "      <td>-5672162917855506432</td>\n",
+       "      <td>0.754030</td>\n",
+       "      <td>0.000354</td>\n",
+       "      <td>28.428319</td>\n",
        "      <td>BOSS-DR16</td>\n",
-       "      <td>28.063643</td>\n",
-       "      <td>132.14379</td>\n",
        "      <td>BOSS-DR16</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
@@ -566,14 +823,74 @@
        "</div>"
       ],
       "text/plain": [
-       "  spectype               specid                             sparcl_id  \\\n",
-       "0   GALAXY -6444532452352045056  bb3d4287-8a2f-479f-9c7f-1053051e4925   \n",
+       "   spectype                             sparcl_id         ra  \\\n",
+       "0    GALAXY  00b0904d-992f-11ee-b7f9-525400aad0aa  141.63075   \n",
+       "1    GALAXY  010eb4d0-992f-11ee-89de-525400aad0aa  141.73278   \n",
+       "2    GALAXY  020ed77c-992f-11ee-aefb-525400aad0aa  141.71671   \n",
+       "3    GALAXY  0262c5c1-992f-11ee-a797-525400aad0aa  141.77643   \n",
+       "4    GALAXY  0290508b-992f-11ee-94e5-525400aad0aa  141.69172   \n",
+       "5    GALAXY  02c0f331-992f-11ee-ac38-525400aad0aa  141.40642   \n",
+       "6    GALAXY  02d858b6-992f-11ee-be88-525400aad0aa  141.43253   \n",
+       "7    GALAXY  02eef149-992f-11ee-a3b5-525400aad0aa  141.45293   \n",
+       "8    GALAXY  0315e895-992f-11ee-96ce-525400aad0aa  141.54144   \n",
+       "9    GALAXY  033fb515-992f-11ee-9c1d-525400aad0aa  141.44884   \n",
+       "10   GALAXY  03a05265-992f-11ee-9683-525400aad0aa  141.49531   \n",
+       "11   GALAXY  03c80eda-992f-11ee-b4f2-525400aad0aa  141.42144   \n",
+       "12   GALAXY  03fad572-992f-11ee-a30a-525400aad0aa  141.62676   \n",
+       "13   GALAXY  04184b57-992f-11ee-bffa-525400aad0aa  141.50548   \n",
+       "14   GALAXY  0431fcb5-992f-11ee-b884-525400aad0aa  141.57763   \n",
+       "15   GALAXY  046666c6-992f-11ee-99ce-525400aad0aa  141.62108   \n",
+       "16   GALAXY  057916a9-992f-11ee-a9ba-525400aad0aa  141.50010   \n",
+       "17   GALAXY  05f59fc1-992f-11ee-8447-525400aad0aa  141.40741   \n",
+       "18   GALAXY  062d0b5b-992f-11ee-aa37-525400aad0aa  141.30648   \n",
+       "19   GALAXY  0666a4e2-992f-11ee-969f-525400aad0aa  141.50529   \n",
+       "\n",
+       "                 specid  redshift  redshift_err        dec data_release  \\\n",
+       "0  -5672178860774109184  0.699621      0.000212  27.981984    BOSS-DR16   \n",
+       "1  -5672178036140388352  0.735681      0.000296  27.886212    BOSS-DR16   \n",
+       "2  -5672175287361318912  0.577450      0.000168  28.225833    BOSS-DR16   \n",
+       "3  -5672174462727598080  0.613647      0.000221  28.349531    BOSS-DR16   \n",
+       "4  -5672173912971784192  0.611291      0.000215  28.440417    BOSS-DR16   \n",
+       "5  -5672173363215970304  0.742280      0.000316  27.313360    BOSS-DR16   \n",
+       "6  -5672173088338063360  0.714333      0.000307  27.297940    BOSS-DR16   \n",
+       "7  -5672172813460156416  0.763182      0.000293  27.502474    BOSS-DR16   \n",
+       "8  -5672172263704342528  0.747819      0.000286  27.511042    BOSS-DR16   \n",
+       "9  -5672171713948528640  0.567928      0.000241  27.600306    BOSS-DR16   \n",
+       "10 -5672170614436900864  0.724495      0.000278  27.739271    BOSS-DR16   \n",
+       "11 -5672170064681086976  0.727417      0.000175  27.705200    BOSS-DR16   \n",
+       "12 -5672169514925273088  0.723495      0.000260  27.756787    BOSS-DR16   \n",
+       "13 -5672169240047366144  0.565133      0.000027  27.570483    BOSS-DR16   \n",
+       "14 -5672168965169459200  0.725325      0.000210  27.812046    BOSS-DR16   \n",
+       "15 -5672168415413645312  0.742185      0.000264  27.538922    BOSS-DR16   \n",
+       "16 -5672165666634575872  0.574673      0.000289  27.976450    BOSS-DR16   \n",
+       "17 -5672164017367134208  0.659942      0.000239  28.367604    BOSS-DR16   \n",
+       "18 -5672163467611320320  0.660208      0.000931  28.392667    BOSS-DR16   \n",
+       "19 -5672162917855506432  0.754030      0.000354  28.428319    BOSS-DR16   \n",
        "\n",
-       "   redshift_err  redshift data_release        dec         ra        _dr  \n",
-       "0      0.000332  0.761637    BOSS-DR16  28.063643  132.14379  BOSS-DR16  "
+       "          _dr  \n",
+       "0   BOSS-DR16  \n",
+       "1   BOSS-DR16  \n",
+       "2   BOSS-DR16  \n",
+       "3   BOSS-DR16  \n",
+       "4   BOSS-DR16  \n",
+       "5   BOSS-DR16  \n",
+       "6   BOSS-DR16  \n",
+       "7   BOSS-DR16  \n",
+       "8   BOSS-DR16  \n",
+       "9   BOSS-DR16  \n",
+       "10  BOSS-DR16  \n",
+       "11  BOSS-DR16  \n",
+       "12  BOSS-DR16  \n",
+       "13  BOSS-DR16  \n",
+       "14  BOSS-DR16  \n",
+       "15  BOSS-DR16  \n",
+       "16  BOSS-DR16  \n",
+       "17  BOSS-DR16  \n",
+       "18  BOSS-DR16  \n",
+       "19  BOSS-DR16  "
       ]
      },
-     "execution_count": 16,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -606,9 +923,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 16,
    "metadata": {
-    "scrolled": true
+    "scrolled": true,
+    "tags": []
    },
    "outputs": [],
    "source": [
@@ -628,8 +946,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
-   "metadata": {},
+   "execution_count": 17,
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "# Define the fields to include in the retrieve function\n",
@@ -638,27 +958,29 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
-   "metadata": {},
+   "execution_count": 18,
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "curl -X 'POST' -H 'Content-Type: application/json' -d '[\"bb3d4287-8a2f-479f-9c7f-1053051e4925\"]' 'http://localhost:8050/sparc/spectras/?include=spectype%2Cmodel%2Cspecid%2Cdata_release%2Civar%2Cflux%2Cwavelength%2Cmask%2Credshift&format=pkl&dataset_list=SDSS-DR16%2CBOSS-DR16' | python3 -m json.tool\n",
-      "CPU times: user 916 µs, sys: 2.36 ms, total: 3.28 ms\n",
-      "Wall time: 49.6 ms\n"
+      "curl -X 'POST' -H 'Content-Type: application/json' -d '[\"00b0904d-992f-11ee-b7f9-525400aad0aa\", \"010eb4d0-992f-11ee-89de-525400aad0aa\", \"020ed77c-992f-11ee-aefb-525400aad0aa\", \"0262c5c1-992f-11ee-a797-525400aad0aa\", \"0290508b-992f-11ee-94e5-525400aad0aa\", \"02c0f331-992f-11ee-ac38-525400aad0aa\", \"02d858b6-992f-11ee-be88-525400aad0aa\", \"02eef149-992f-11ee-a3b5-525400aad0aa\", \"0315e895-992f-11ee-96ce-525400aad0aa\", \"033fb515-992f-11ee-9c1d-525400aad0aa\", \"03a05265-992f-11ee-9683-525400aad0aa\", \"03c80eda-992f-11ee-b4f2-525400aad0aa\", \"03fad572-992f-11ee-a30a-525400aad0aa\", \"04184b57-992f-11ee-bffa-525400aad0aa\", \"0431fcb5-992f-11ee-b884-525400aad0aa\", \"046666c6-992f-11ee-99ce-525400aad0aa\", \"057916a9-992f-11ee-a9ba-525400aad0aa\", \"05f59fc1-992f-11ee-8447-525400aad0aa\", \"062d0b5b-992f-11ee-aa37-525400aad0aa\", \"0666a4e2-992f-11ee-969f-525400aad0aa\"]' 'https://sparc1.datalab.noirlab.edu/sparc/spectras/?include=flux%2Cmask%2Cmodel%2Cwavelength%2Cdata_release%2Credshift%2Civar%2Cspectype%2Cspecid&format=pkl&dataset_list=SDSS-DR16%2CBOSS-DR16' | python3 -m json.tool\n",
+      "CPU times: user 109 ms, sys: 63.9 ms, total: 173 ms\n",
+      "Wall time: 2.25 s\n"
      ]
     },
     {
      "data": {
       "text/plain": [
        "{'status': {'success': True,\n",
-       "  'info': [\"Successfully found 1 records in dr_list=['SDSS-DR16', 'BOSS-DR16']\"],\n",
+       "  'info': [\"Successfully found 20 records in dr_list=['SDSS-DR16', 'BOSS-DR16']\"],\n",
        "  'warnings': []}}"
       ]
      },
-     "execution_count": 19,
+     "execution_count": 18,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -673,28 +995,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
-   "metadata": {},
+   "execution_count": 19,
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "{'redshift': 0.761636912822723,\n",
+       "{'redshift': 0.6996206641197205,\n",
        " 'spectype': 'GALAXY',\n",
-       " 'specid': -6444532452352045056,\n",
        " 'data_release': 'BOSS-DR16',\n",
-       " 'model': array([-0.01559776, -0.01588696, -0.01609746, ...,  0.94615489,\n",
-       "         0.92513317,  0.8983984 ]),\n",
+       " 'specid': -5672178860774109184,\n",
+       " 'model': array([-0.0319225 , -0.03274626, -0.03301667, ...,  0.9404546 ,\n",
+       "         0.93845838,  0.93815029]),\n",
        " 'mask': array([88080384, 88080384, 88080384, ..., 83886080, 83886080, 83886080]),\n",
        " 'ivar': array([0., 0., 0., ..., 0., 0., 0.]),\n",
-       " 'flux': array([0.19426258, 0.19424935, 0.19423614, ..., 0.27637786, 0.2763944 ,\n",
-       "        0.27641097]),\n",
-       " 'wavelength': array([ 3580.13991843,  3580.96437103,  3581.78901348, ...,\n",
-       "        10368.11964061, 10370.50726326, 10372.89543574]),\n",
+       " 'flux': array([-10.93883896, -10.93841362, -10.93798828, ...,   0.68531734,\n",
+       "          0.68533301,   0.68534863]),\n",
+       " 'wavelength': array([ 3585.91507517,  3586.7408577 ,  3587.56683039, ...,\n",
+       "        10370.50726326, 10372.89543574, 10375.28415818]),\n",
        " '_dr': 'BOSS-DR16'}"
       ]
      },
-     "execution_count": 20,
+     "execution_count": 19,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -712,34 +1036,36 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
-   "metadata": {},
+   "execution_count": 20,
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.legend.Legend at 0x7f47bfced810>"
+       "<matplotlib.legend.Legend at 0x7fc998221e50>"
       ]
      },
-     "execution_count": 21,
+     "execution_count": 20,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "a2854906526c42f49c1fc769732e5228",
+       "model_id": "5891aa489f2c4c638d8867117bee47b3",
        "version_major": 2,
        "version_minor": 0
       },
-      "image/png": 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",
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",
       "text/html": [
        "\n",
        "            <div style=\"display: inline-block;\">\n",
        "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
        "                    Figure\n",
        "                </div>\n",
-       "                <img 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' 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+       "                <img 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' width=800.0/>\n",
        "            </div>\n",
        "        "
       ],
@@ -772,7 +1098,9 @@
   {
    "cell_type": "code",
    "execution_count": 22,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -789,7 +1117,9 @@
   {
    "cell_type": "code",
    "execution_count": 23,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "#import sparcl.gather_2d\n",
@@ -823,7 +1153,9 @@
   {
    "cell_type": "code",
    "execution_count": 24,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "if show_help:\n",
@@ -834,7 +1166,9 @@
   {
    "cell_type": "code",
    "execution_count": 25,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -852,14 +1186,18 @@
    "cell_type": "code",
    "execution_count": 26,
    "metadata": {
-    "scrolled": true
+    "scrolled": true,
+    "tags": []
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
        "{'Loggedin_As': 'test_user_1@noirlab.edu',\n",
-       " 'Authorized_Datasets': {'BOSS-DR16', 'DESI-EDR', 'SDSS-DR16', 'SDSS-DR17'}}"
+       " 'Authorized_Datasets': {'BOSS-DR16',\n",
+       "  'DESI-EDR',\n",
+       "  'SDSS-DR16',\n",
+       "  'SDSS-DR17-test'}}"
       ]
      },
      "execution_count": 26,
@@ -874,7 +1212,9 @@
   {
    "cell_type": "code",
    "execution_count": 27,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -891,7 +1231,9 @@
   {
    "cell_type": "code",
    "execution_count": 28,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "data": {
@@ -926,7 +1268,9 @@
   {
    "cell_type": "code",
    "execution_count": 29,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -943,13 +1287,15 @@
   {
    "cell_type": "code",
    "execution_count": 30,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "curl -X 'POST' -H 'Content-Type: application/json' -d '{\"outfields\": [\"sparcl_id\", \"specid\", \"ra\", \"dec\", \"redshift\", \"spectype\", \"data_release\", \"redshift_err\"], \"search\": [[\"spectype\", \"GALAXY\"], [\"redshift\", 0.5, 0.9], [\"data_release\", \"BOSS-DR16\", \"SDSS-DR16\"]]}' 'http://localhost:8050/sparc/find/?limit=2' | python3 -m json.tool\n",
+      "curl -X 'POST' -H 'Content-Type: application/json' -d '{\"outfields\": [\"sparcl_id\", \"specid\", \"ra\", \"dec\", \"redshift\", \"spectype\", \"data_release\", \"redshift_err\"], \"search\": [[\"spectype\", \"GALAXY\"], [\"redshift\", 0.5, 0.9], [\"data_release\", \"BOSS-DR16\", \"SDSS-DR16\"]]}' 'https://sparc1.datalab.noirlab.edu/sparc/find/?limit=2' | python3 -m json.tool\n",
       "{'META': {'endpoint': 'sparc/find'},\n",
       " 'PARAMETERS': {'limit': 2,\n",
       "                'include': 'dec,ra,sparcl_id,specid',\n",
@@ -957,7 +1303,7 @@
       "                'user': None,\n",
       "                'format': 'json',\n",
       "                'drs': ['BOSS-DR16', 'SDSS-DR16'],\n",
-      "                'private_drs': ['SDSS-DR17'],\n",
+      "                'private_drs': ['SDSS-DR17-test'],\n",
       "                'username': 'Anonymous',\n",
       "                'json_payload': {'outfields': ['sparcl_id',\n",
       "                                               'specid',\n",
@@ -973,18 +1319,18 @@
       "                                             'BOSS-DR16',\n",
       "                                             'SDSS-DR16']]}},\n",
       " 'HEADER': {'spectype': 'category',\n",
-      "            'specid': 'np.int64',\n",
       "            'sparcl_id': 'str',\n",
-      "            'redshift_err': 'np.float64',\n",
+      "            'ra': 'np.float64',\n",
+      "            'specid': 'np.int64',\n",
       "            'redshift': 'np.float64',\n",
-      "            'data_release': 'category',\n",
+      "            'redshift_err': 'np.float64',\n",
       "            'dec': 'np.float64',\n",
-      "            'ra': 'np.float64'},\n",
+      "            'data_release': 'category'},\n",
       " 'WARNINGS': ['OFFSET parameter needs SORT but it was not provided. Using '\n",
       "              \"default 'sparcl_id' for sorting\"]}\n",
-      "{'spectype': 'GALAXY', 'specid': -6444532452352045056, 'sparcl_id': 'bb3d4287-8a2f-479f-9c7f-1053051e4925', 'redshift_err': 0.000331654009642079, 'redshift': 0.761636912822723, 'data_release': 'BOSS-DR16', 'dec': 28.063643, 'ra': 132.14379, '_dr': 'BOSS-DR16'}\n",
+      "{'spectype': 'GALAXY', 'sparcl_id': '00b0904d-992f-11ee-b7f9-525400aad0aa', 'ra': 141.63075000000003, 'specid': -5672178860774109184, 'redshift': 0.6996206641197205, 'redshift_err': 0.00021235186432022601, 'dec': 27.981984, 'data_release': 'BOSS-DR16', '_dr': 'BOSS-DR16'}\n",
       "\n",
-      "SUCCESS: found.count=1 records from FIND\n"
+      "SUCCESS: found.count=2 records from FIND\n"
      ]
     }
    ],
@@ -1009,7 +1355,9 @@
   {
    "cell_type": "code",
    "execution_count": 31,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -1026,7 +1374,9 @@
   {
    "cell_type": "code",
    "execution_count": 32,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "data": {
@@ -1047,14 +1397,16 @@
   {
    "cell_type": "code",
    "execution_count": 33,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "curl -X 'POST' -H 'Content-Type: application/json' -d '{\"outfields\": [\"sparcl_id\", \"specid\", \"ra\", \"dec\", \"redshift\", \"spectype\", \"data_release\", \"redshift_err\"], \"search\": [[\"spectype\", \"GALAXY\"], [\"redshift\", 0.5, 0.9], [\"data_release\", \"BOSS-DR16\", \"SDSS-DR17\"]]}' 'http://localhost:8050/sparc/find/?limit=2' | python3 -m json.tool\n",
-      "SUCCESS: Could not execute find: [UNKNOWN] uname='ANONYMOUS' is declined access to datasets:   SDSS-DR17.  drs_requested={'SDSS-DR17', 'BOSS-DR16'} my_auth={'SDSS-DR16', 'DESI-EDR', 'BOSS-DR16'} [NODRACCESS] None\n"
+      "curl -X 'POST' -H 'Content-Type: application/json' -d '{\"outfields\": [\"sparcl_id\", \"specid\", \"ra\", \"dec\", \"redshift\", \"spectype\", \"data_release\", \"redshift_err\"], \"search\": [[\"spectype\", \"GALAXY\"], [\"redshift\", 0.5, 0.9], [\"data_release\", \"BOSS-DR16\", \"SDSS-DR17-test\"]]}' 'https://sparc1.datalab.noirlab.edu/sparc/find/?limit=2' | python3 -m json.tool\n",
+      "SUCCESS: Could not execute find: [UNKNOWN] uname='ANONYMOUS' is declined access to datasets:   SDSS-DR17-test.  drs_requested={'SDSS-DR17-test', 'BOSS-DR16'} my_auth={'SDSS-DR16', 'DESI-EDR', 'BOSS-DR16'} [NODRACCESS] None\n"
      ]
     }
    ],
@@ -1087,13 +1439,15 @@
   {
    "cell_type": "code",
    "execution_count": 34,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "curl -X 'POST' -H 'Content-Type: application/json' -d '{\"outfields\": [\"sparcl_id\", \"specid\", \"ra\", \"dec\", \"redshift\", \"spectype\", \"data_release\", \"redshift_err\"], \"search\": [[\"spectype\", \"GALAXY\"], [\"redshift\", 0.5, 0.9]]}' 'http://localhost:8050/sparc/find/?limit=2' | python3 -m json.tool\n",
+      "curl -X 'POST' -H 'Content-Type: application/json' -d '{\"outfields\": [\"sparcl_id\", \"specid\", \"ra\", \"dec\", \"redshift\", \"spectype\", \"data_release\", \"redshift_err\"], \"search\": [[\"spectype\", \"GALAXY\"], [\"redshift\", 0.5, 0.9]]}' 'https://sparc1.datalab.noirlab.edu/sparc/find/?limit=2' | python3 -m json.tool\n",
       "FOUND info:\n",
       "{'META': {'endpoint': 'sparc/find'},\n",
       " 'PARAMETERS': {'limit': 2,\n",
@@ -1102,7 +1456,7 @@
       "                'user': None,\n",
       "                'format': 'json',\n",
       "                'drs': ['BOSS-DR16', 'DESI-EDR', 'SDSS-DR16'],\n",
-      "                'private_drs': ['SDSS-DR17'],\n",
+      "                'private_drs': ['SDSS-DR17-test'],\n",
       "                'username': 'Anonymous',\n",
       "                'json_payload': {'outfields': ['sparcl_id',\n",
       "                                               'specid',\n",
@@ -1115,17 +1469,17 @@
       "                                 'search': [['spectype', 'GALAXY'],\n",
       "                                            ['redshift', 0.5, 0.9]]}},\n",
       " 'HEADER': {'spectype': 'category',\n",
-      "            'specid': 'np.int64',\n",
       "            'sparcl_id': 'str',\n",
-      "            'redshift_err': 'np.float64',\n",
+      "            'ra': 'np.float64',\n",
+      "            'specid': 'np.int64',\n",
       "            'redshift': 'np.float64',\n",
-      "            'data_release': 'category',\n",
+      "            'redshift_err': 'np.float64',\n",
       "            'dec': 'np.float64',\n",
-      "            'ra': 'np.float64'},\n",
+      "            'data_release': 'category'},\n",
       " 'WARNINGS': ['OFFSET parameter needs SORT but it was not provided. Using '\n",
       "              \"default 'sparcl_id' for sorting\"]}\n",
       "\n",
-      "FOUND records. found.records[0]={'spectype': 'GALAXY', 'specid': 39627072179543889, 'sparcl_id': '2f79ffc2-71fa-11ee-b0da-08002725f1ef', 'redshift_err': 0.0001345702651861459, 'redshift': 0.6348533970651531, 'data_release': 'DESI-EDR', 'dec': -31.05971652239488, 'ra': 59.93519495098703, '_dr': 'DESI-EDR'}\n"
+      "FOUND records. found.records[0]={'spectype': 'GALAXY', 'sparcl_id': '00769ec9-9931-11ee-97de-525400aad0aa', 'ra': 209.5682103155303, 'specid': 39627920993423532, 'redshift': 0.8685901183006199, 'redshift_err': 3.14371006304597e-05, 'dec': 5.466527188533397, 'data_release': 'DESI-EDR', '_dr': 'DESI-EDR'}\n"
      ]
     }
    ],
@@ -1160,7 +1514,9 @@
   {
    "cell_type": "code",
    "execution_count": 35,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -1177,14 +1533,16 @@
   {
    "cell_type": "code",
    "execution_count": 36,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "curl -X 'POST' -H 'Content-Type: application/json' -d '{\"outfields\": [\"sparcl_id\", \"specid\", \"ra\", \"dec\", \"redshift\", \"spectype\", \"data_release\", \"redshift_err\"], \"search\": [[\"spectype\", \"GALAXY\"], [\"redshift\", 0.5, 0.9], [\"data_release\", \"BOSS-DR16\", \"SDSS-DR17\"]]}' 'http://localhost:8050/sparc/find/?limit=2' | python3 -m json.tool\n",
-      "SUCCESS: Could not execute find: [UNKNOWN] uname='test_user_2@noirlab.edu' is declined access to datasets:   SDSS-DR17.  drs_requested={'SDSS-DR17', 'BOSS-DR16'} my_auth={'SDSS-DR16', 'DESI-EDR', 'BOSS-DR16'} [NODRACCESS] None\n"
+      "curl -X 'POST' -H 'Content-Type: application/json' -d '{\"outfields\": [\"sparcl_id\", \"specid\", \"ra\", \"dec\", \"redshift\", \"spectype\", \"data_release\", \"redshift_err\"], \"search\": [[\"spectype\", \"GALAXY\"], [\"redshift\", 0.5, 0.9], [\"data_release\", \"BOSS-DR16\", \"SDSS-DR17-test\"]]}' 'https://sparc1.datalab.noirlab.edu/sparc/find/?limit=2' | python3 -m json.tool\n",
+      "SUCCESS: Could not execute find: [UNKNOWN] uname='test_user_2@noirlab.edu' is declined access to datasets:   SDSS-DR17-test.  drs_requested={'SDSS-DR17-test', 'BOSS-DR16'} my_auth={'SDSS-DR16', 'DESI-EDR', 'BOSS-DR16'} [NODRACCESS] None\n"
      ]
     }
    ],
@@ -1218,7 +1576,9 @@
   {
    "cell_type": "code",
    "execution_count": 37,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -1235,13 +1595,18 @@
   {
    "cell_type": "code",
    "execution_count": 38,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "data": {
       "text/plain": [
        "{'Loggedin_As': 'test_user_1@noirlab.edu',\n",
-       " 'Authorized_Datasets': {'BOSS-DR16', 'DESI-EDR', 'SDSS-DR16', 'SDSS-DR17'}}"
+       " 'Authorized_Datasets': {'BOSS-DR16',\n",
+       "  'DESI-EDR',\n",
+       "  'SDSS-DR16',\n",
+       "  'SDSS-DR17-test'}}"
       ]
      },
      "execution_count": 38,
@@ -1256,13 +1621,15 @@
   {
    "cell_type": "code",
    "execution_count": 39,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "curl -X 'POST' -H 'Content-Type: application/json' -d '{\"outfields\": [\"sparcl_id\", \"specid\", \"ra\", \"dec\", \"redshift\", \"spectype\", \"data_release\", \"redshift_err\"], \"search\": [[\"spectype\", \"GALAXY\"], [\"redshift\", 0.5, 0.9]]}' 'http://localhost:8050/sparc/find/?limit=2' | python3 -m json.tool\n",
+      "curl -X 'POST' -H 'Content-Type: application/json' -d '{\"outfields\": [\"sparcl_id\", \"specid\", \"ra\", \"dec\", \"redshift\", \"spectype\", \"data_release\", \"redshift_err\"], \"search\": [[\"spectype\", \"GALAXY\"], [\"redshift\", 0.5, 0.9]]}' 'https://sparc1.datalab.noirlab.edu/sparc/find/?limit=2' | python3 -m json.tool\n",
       "FOUND info:\n",
       "{'META': {'endpoint': 'sparc/find'},\n",
       " 'PARAMETERS': {'limit': 2,\n",
@@ -1270,7 +1637,7 @@
       "                'offset': 0,\n",
       "                'format': 'json',\n",
       "                'drs': ['BOSS-DR16', 'DESI-EDR', 'SDSS-DR16'],\n",
-      "                'private_drs': ['SDSS-DR17'],\n",
+      "                'private_drs': ['SDSS-DR17-test'],\n",
       "                'username': 'test_user_1@noirlab.edu',\n",
       "                'json_payload': {'outfields': ['sparcl_id',\n",
       "                                               'specid',\n",
@@ -1283,13 +1650,13 @@
       "                                 'search': [['spectype', 'GALAXY'],\n",
       "                                            ['redshift', 0.5, 0.9]]}},\n",
       " 'HEADER': {'spectype': 'category',\n",
-      "            'specid': 'np.int64',\n",
       "            'sparcl_id': 'str',\n",
-      "            'redshift_err': 'np.float64',\n",
+      "            'ra': 'np.float64',\n",
+      "            'specid': 'np.int64',\n",
       "            'redshift': 'np.float64',\n",
-      "            'data_release': 'category',\n",
+      "            'redshift_err': 'np.float64',\n",
       "            'dec': 'np.float64',\n",
-      "            'ra': 'np.float64'},\n",
+      "            'data_release': 'category'},\n",
       " 'WARNINGS': ['OFFSET parameter needs SORT but it was not provided. Using '\n",
       "              \"default 'sparcl_id' for sorting\"]}\n"
      ]
@@ -1317,7 +1684,9 @@
   {
    "cell_type": "code",
    "execution_count": 40,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -1334,7 +1703,9 @@
   {
    "cell_type": "code",
    "execution_count": 41,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "data": {
@@ -1355,14 +1726,16 @@
   {
    "cell_type": "code",
    "execution_count": 42,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "curl -X 'POST' -H 'Content-Type: application/json' -d '{\"outfields\": [\"sparcl_id\", \"specid\", \"ra\", \"dec\", \"redshift\", \"spectype\", \"data_release\", \"redshift_err\"], \"search\": [[\"spectype\", \"GALAXY\"], [\"redshift\", 0.5, 0.9], [\"data_release\", \"BOSS-DR16\", \"SDSS-DR17\"]]}' 'http://localhost:8050/sparc/find/?limit=2' | python3 -m json.tool\n",
-      "SUCCESS: Could not execute find: [UNKNOWN] uname='ANONYMOUS' is declined access to datasets:   SDSS-DR17.  drs_requested={'SDSS-DR17', 'BOSS-DR16'} my_auth={'SDSS-DR16', 'DESI-EDR', 'BOSS-DR16'} [NODRACCESS] None\n"
+      "curl -X 'POST' -H 'Content-Type: application/json' -d '{\"outfields\": [\"sparcl_id\", \"specid\", \"ra\", \"dec\", \"redshift\", \"spectype\", \"data_release\", \"redshift_err\"], \"search\": [[\"spectype\", \"GALAXY\"], [\"redshift\", 0.5, 0.9], [\"data_release\", \"BOSS-DR16\", \"SDSS-DR17-test\"]]}' 'https://sparc1.datalab.noirlab.edu/sparc/find/?limit=2' | python3 -m json.tool\n",
+      "SUCCESS: Could not execute find: [UNKNOWN] uname='ANONYMOUS' is declined access to datasets:   SDSS-DR17-test.  drs_requested={'SDSS-DR17-test', 'BOSS-DR16'} my_auth={'SDSS-DR16', 'DESI-EDR', 'BOSS-DR16'} [NODRACCESS] None\n"
      ]
     }
    ],
@@ -1403,7 +1776,9 @@
   {
    "cell_type": "code",
    "execution_count": 43,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "data": {
@@ -1424,15 +1799,17 @@
   {
    "cell_type": "code",
    "execution_count": 44,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "curl -X 'POST' -H 'Content-Type: application/json' -d '{\"outfields\": [\"sparcl_id\"], \"search\": [[\"data_release\", \"SDSS-DR16\", \"BOSS-DR16\"]]}' 'http://localhost:8050/sparc/find/?limit=2' | python3 -m json.tool\n",
-      "curl -X 'POST' -H 'Content-Type: application/json' -d '[\"1ec5eb87-c678-4a17-9fec-2fe2982e24b0\", \"bb3d4287-8a2f-479f-9c7f-1053051e4925\"]' 'http://localhost:8050/sparc/spectras/?include=spectype%2Cspecid%2Cdata_release%2Cflux%2Credshift&format=pkl&dataset_list=SDSS-DR16%2CBOSS-DR16' | python3 -m json.tool\n",
-      "Pass: got.records[0].spectype='GALAXY' len(got.records[0].flux)=4621\n"
+      "curl -X 'POST' -H 'Content-Type: application/json' -d '{\"outfields\": [\"sparcl_id\"], \"search\": [[\"data_release\", \"SDSS-DR16\", \"BOSS-DR16\"]]}' 'https://sparc1.datalab.noirlab.edu/sparc/find/?limit=2' | python3 -m json.tool\n",
+      "curl -X 'POST' -H 'Content-Type: application/json' -d '[\"001b11a6-992f-11ee-993c-525400aad0aa\", \"00339b14-992f-11ee-b1b9-525400aad0aa\"]' 'https://sparc1.datalab.noirlab.edu/sparc/spectras/?include=flux%2Cdata_release%2Credshift%2Cspectype%2Cspecid&format=pkl&dataset_list=SDSS-DR16%2CBOSS-DR16' | python3 -m json.tool\n",
+      "Pass: got.records[0].spectype='QSO' len(got.records[0].flux)=4615\n"
      ]
     }
    ],
@@ -1465,15 +1842,17 @@
   {
    "cell_type": "code",
    "execution_count": 45,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "Logged-out successfully.  Previously logged-in with email test_user_3@noirlab.edu.\n",
-      "curl -X 'POST' -H 'Content-Type: application/json' -d '[\"1ec5eb87-c678-4a17-9fec-2fe2982e24b0\", \"bb3d4287-8a2f-479f-9c7f-1053051e4925\"]' 'http://localhost:8050/sparc/spectras/?include=spectype%2Cspecid%2Cdata_release%2Cflux%2Credshift&format=pkl&dataset_list=SDSS-DR16%2CSDSS-DR17%2CBOSS-DR16' | python3 -m json.tool\n",
-      "Correctly could not retrieve: [UNKNOWN] uname='ANONYMOUS' is declined access to datasets:   SDSS-DR17.  drs_requested=['SDSS-DR16', 'SDSS-DR17', 'BOSS-DR16'] my_auth={'SDSS-DR16', 'DESI-EDR', 'BOSS-DR16'} [NODRACCESS] None\n"
+      "curl -X 'POST' -H 'Content-Type: application/json' -d '[\"001b11a6-992f-11ee-993c-525400aad0aa\", \"00339b14-992f-11ee-b1b9-525400aad0aa\"]' 'https://sparc1.datalab.noirlab.edu/sparc/spectras/?include=flux%2Cdata_release%2Credshift%2Cspectype%2Cspecid&format=pkl&dataset_list=SDSS-DR16%2CSDSS-DR17-test%2CBOSS-DR16' | python3 -m json.tool\n",
+      "Correctly could not retrieve: [UNKNOWN] uname='ANONYMOUS' is declined access to datasets:   SDSS-DR17-test.  drs_requested=['SDSS-DR16', 'SDSS-DR17-test', 'BOSS-DR16'] my_auth={'SDSS-DR16', 'DESI-EDR', 'BOSS-DR16'} [NODRACCESS] None\n"
      ]
     }
    ],
@@ -1502,7 +1881,9 @@
   {
    "cell_type": "code",
    "execution_count": 46,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -1519,13 +1900,18 @@
   {
    "cell_type": "code",
    "execution_count": 47,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "data": {
       "text/plain": [
        "{'Loggedin_As': 'test_user_1@noirlab.edu',\n",
-       " 'Authorized_Datasets': {'BOSS-DR16', 'DESI-EDR', 'SDSS-DR16', 'SDSS-DR17'}}"
+       " 'Authorized_Datasets': {'BOSS-DR16',\n",
+       "  'DESI-EDR',\n",
+       "  'SDSS-DR16',\n",
+       "  'SDSS-DR17-test'}}"
       ]
      },
      "execution_count": 47,
@@ -1540,16 +1926,18 @@
   {
    "cell_type": "code",
    "execution_count": 48,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "curl -X 'POST' -H 'Content-Type: application/json' -d '{\"outfields\": [\"sparcl_id\"], \"search\": [[\"data_release\", \"SDSS-DR16\", \"BOSS-DR16\"]]}' 'http://localhost:8050/sparc/find/?limit=2' | python3 -m json.tool\n",
-      "curl -X 'POST' -H 'Content-Type: application/json' -d '[\"1ec5eb87-c678-4a17-9fec-2fe2982e24b0\", \"bb3d4287-8a2f-479f-9c7f-1053051e4925\"]' 'http://localhost:8050/sparc/spectras/?include=spectype%2Cspecid%2Cdata_release%2Cflux%2Credshift&format=pkl&dataset_list=SDSS-DR16%2CSDSS-DR17%2CBOSS-DR16' | python3 -m json.tool\n",
+      "curl -X 'POST' -H 'Content-Type: application/json' -d '{\"outfields\": [\"sparcl_id\"], \"search\": [[\"data_release\", \"SDSS-DR16\", \"BOSS-DR16\"]]}' 'https://sparc1.datalab.noirlab.edu/sparc/find/?limit=2' | python3 -m json.tool\n",
+      "curl -X 'POST' -H 'Content-Type: application/json' -d '[\"001b11a6-992f-11ee-993c-525400aad0aa\", \"00339b14-992f-11ee-b1b9-525400aad0aa\"]' 'https://sparc1.datalab.noirlab.edu/sparc/spectras/?include=flux%2Cdata_release%2Credshift%2Cspectype%2Cspecid&format=pkl&dataset_list=SDSS-DR16%2CSDSS-DR17-test%2CBOSS-DR16' | python3 -m json.tool\n",
       "got.count=2\n",
-      "Pass: got.records[0].spectype='GALAXY' len(got.records[0].flux)=4621\n"
+      "Pass: got.records[0].spectype='QSO' len(got.records[0].flux)=4615\n"
      ]
     }
    ],
@@ -1584,13 +1972,15 @@
   {
    "cell_type": "code",
    "execution_count": 49,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Run finished: 2024-03-06 07:12:30.513140\n"
+      "Run finished: 2024-03-06 11:51:48.820342\n"
      ]
     }
    ],
@@ -1601,7 +1991,9 @@
   {
    "cell_type": "code",
    "execution_count": 50,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -1609,12 +2001,12 @@
      "text": [
       "Logged in successfully with email='test_user_1@noirlab.edu'\n",
       "\n",
-      "client.authorized={'Loggedin_As': 'test_user_1@noirlab.edu', 'Authorized_Datasets': {'SDSS-DR17', 'DESI-EDR', 'SDSS-DR16', 'BOSS-DR16'}}\n",
+      "client.authorized={'Loggedin_As': 'test_user_1@noirlab.edu', 'Authorized_Datasets': {'SDSS-DR16', 'BOSS-DR16', 'DESI-EDR', 'SDSS-DR17-test'}}\n",
       "\n",
       "\n",
       "Logged-out successfully.  Previously logged-in with email test_user_1@noirlab.edu.\n",
       "\n",
-      "client.authorized={'Loggedin_As': 'Anonymous', 'Authorized_Datasets': {'DESI-EDR', 'BOSS-DR16', 'SDSS-DR16'}}\n"
+      "client.authorized={'Loggedin_As': 'Anonymous', 'Authorized_Datasets': {'DESI-EDR', 'SDSS-DR16', 'BOSS-DR16'}}\n"
      ]
     }
    ],
@@ -1625,13 +2017,6 @@
     "client.logout()   # can also be done with client.login(None)\n",
     "print(f'\\n{client.authorized=}')"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
@@ -1650,7 +2035,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.12"
+   "version": "3.8.3"
   },
   "toc": {
    "base_numbering": 1