swift.ipynb

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    "import fsspec\n",
    "async def get_client(**kwargs):\n",
    "    import aiohttp\n",
    "    import aiohttp_retry\n",
    "    retry_options = aiohttp_retry.ExponentialRetry(\n",
    "            attempts=3,\n",
    "            exceptions={OSError, aiohttp.ServerDisconnectedError})\n",
    "    retry_client = aiohttp_retry.RetryClient(raise_for_status=False, retry_options=retry_options)\n",
    "    return retry_client"
   ]
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   "id": "d7073410-50a1-45f1-87ed-40b098033df3",
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      "#cloud-config\n",
      "password: pangeo\n",
      "chpasswd: { expire: False }\n",
      "ssh_pwauth: True\n",
      "\n"
     ]
    }
   ],
   "source": [
    "import fsspec\n",
    "filepath=\"https://object-store.cloud.muni.cz/swift/v1/testfred\"\n",
    "\n",
    "\n",
    "filepath=\"https://object-store.cloud.muni.cz/swift/v1/foss4g-data/test/userdata.txt\"\n",
    "\n",
    "with fsspec.open(filepath, \"r\") as f:\n",
    "    print(f.read())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "9592218b-f2fe-4bfd-b9f7-f794a350e428",
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    {
     "name": "stdout",
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     "text": [
      "--2022-07-29 15:47:15--  https://object-store.cloud.muni.cz/swift/v1/testfred/t_1.nc\n",
      "Resolving object-store.cloud.muni.cz (object-store.cloud.muni.cz)... 147.251.62.11\n",
      "Connecting to object-store.cloud.muni.cz (object-store.cloud.muni.cz)|147.251.62.11|:443... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 37954 (37K) [application/x-netcdf]\n",
      "Saving to: ‘t_1.nc’\n",
      "\n",
      "t_1.nc              100%[===================>]  37.06K   152KB/s    in 0.2s    \n",
      "\n",
      "2022-07-29 15:47:16 (152 KB/s) - ‘t_1.nc’ saved [37954/37954]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "!wget https://object-store.cloud.muni.cz/swift/v1/testfred/t_1.nc\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "2d7cfea2-501b-42a4-aad2-8830ab761579",
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (time: 4, lat: 25, lon: 53)\n",
       "Coordinates:\n",
       "  * lat      (lat) float32 75.0 72.5 70.0 67.5 65.0 ... 25.0 22.5 20.0 17.5 15.0\n",
       "  * lon      (lon) float32 200.0 202.5 205.0 207.5 ... 322.5 325.0 327.5 330.0\n",
       "  * time     (time) datetime64[ns] 2013-01-01 ... 2013-01-01T18:00:00\n",
       "Data variables:\n",
       "    air      (time, lat, lon) float32 241.2 242.5 243.5 ... 297.8 298.0 297.9\n",
       "Attributes:\n",
       "    Conventions:  COARDS\n",
       "    title:        4x daily NMC reanalysis (1948)\n",
       "    description:  Data is from NMC initialized reanalysis\\n(4x/day).  These a...\n",
       "    platform:     Model\n",
       "    references:   http://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanaly...\n",
       "    history:      Thu Jul 28 19:01:29 2022: ncks --mk_rec_dmn time files/test...\n",
       "    NCO:          netCDF Operators version 5.1.0 (Homepage = http://nco.sf.ne...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-cc510fd5-75e6-4ba8-8e2f-edb5a2c7b683' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-cc510fd5-75e6-4ba8-8e2f-edb5a2c7b683' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 4</li><li><span class='xr-has-index'>lat</span>: 25</li><li><span class='xr-has-index'>lon</span>: 53</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-35538015-b36e-4a63-a72e-0d59428802a9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-35538015-b36e-4a63-a72e-0d59428802a9' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>75.0 72.5 70.0 ... 20.0 17.5 15.0</div><input id='attrs-a671b8c8-5df7-48a1-b8eb-349827385669' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a671b8c8-5df7-48a1-b8eb-349827385669' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-18179f02-1afe-40ad-9acf-bcb257a38b42' class='xr-var-data-in' type='checkbox'><label for='data-18179f02-1afe-40ad-9acf-bcb257a38b42' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([75. , 72.5, 70. , 67.5, 65. , 62.5, 60. , 57.5, 55. , 52.5, 50. , 47.5,\n",
       "       45. , 42.5, 40. , 37.5, 35. , 32.5, 30. , 27.5, 25. , 22.5, 20. , 17.5,\n",
       "       15. ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>200.0 202.5 205.0 ... 327.5 330.0</div><input id='attrs-a05de151-d013-4255-a428-f179459d747a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a05de151-d013-4255-a428-f179459d747a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ced7524b-e9b3-4b88-9243-41367fac9586' class='xr-var-data-in' type='checkbox'><label for='data-ced7524b-e9b3-4b88-9243-41367fac9586' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([200. , 202.5, 205. , 207.5, 210. , 212.5, 215. , 217.5, 220. , 222.5,\n",
       "       225. , 227.5, 230. , 232.5, 235. , 237.5, 240. , 242.5, 245. , 247.5,\n",
       "       250. , 252.5, 255. , 257.5, 260. , 262.5, 265. , 267.5, 270. , 272.5,\n",
       "       275. , 277.5, 280. , 282.5, 285. , 287.5, 290. , 292.5, 295. , 297.5,\n",
       "       300. , 302.5, 305. , 307.5, 310. , 312.5, 315. , 317.5, 320. , 322.5,\n",
       "       325. , 327.5, 330. ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2013-01-01 ... 2013-01-01T18:00:00</div><input id='attrs-3f3ee585-f33e-46e3-bb3d-12f7075d62fe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3f3ee585-f33e-46e3-bb3d-12f7075d62fe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8474ee70-1522-40d3-8bba-3d6ccacb1cfd' class='xr-var-data-in' type='checkbox'><label for='data-8474ee70-1522-40d3-8bba-3d6ccacb1cfd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>Time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2013-01-01T00:00:00.000000000&#x27;, &#x27;2013-01-01T06:00:00.000000000&#x27;,\n",
       "       &#x27;2013-01-01T12:00:00.000000000&#x27;, &#x27;2013-01-01T18:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-80ac6408-bd01-4a0d-a3a5-61203ddf2331' class='xr-section-summary-in' type='checkbox'  checked><label for='section-80ac6408-bd01-4a0d-a3a5-61203ddf2331' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>air</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-99c2411a-045a-4f63-a7e7-fb04b51eb2cd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-99c2411a-045a-4f63-a7e7-fb04b51eb2cd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d8665a68-53e8-4377-a49a-9f6c08db914b' class='xr-var-data-in' type='checkbox'><label for='data-d8665a68-53e8-4377-a49a-9f6c08db914b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>4xDaily Air temperature at sigma level 995</dd><dt><span>units :</span></dt><dd>degK</dd><dt><span>precision :</span></dt><dd>2</dd><dt><span>GRIB_id :</span></dt><dd>11</dd><dt><span>GRIB_name :</span></dt><dd>TMP</dd><dt><span>var_desc :</span></dt><dd>Air temperature</dd><dt><span>dataset :</span></dt><dd>NMC Reanalysis</dd><dt><span>level_desc :</span></dt><dd>Surface</dd><dt><span>statistic :</span></dt><dd>Individual Obs</dd><dt><span>parent_stat :</span></dt><dd>Other</dd><dt><span>actual_range :</span></dt><dd>[185.16 322.1 ]</dd></dl></div><div class='xr-var-data'><pre>array([[[241.2    , 242.5    , ..., 235.5    , 238.59999],\n",
       "        [243.79999, 244.5    , ..., 235.29999, 239.29999],\n",
       "        ...,\n",
       "        [295.9    , 296.19998, ..., 295.9    , 295.19998],\n",
       "        [296.29   , 296.79   , ..., 296.79   , 296.6    ]],\n",
       "\n",
       "       [[242.09999, 242.7    , ..., 233.59999, 235.79999],\n",
       "        [243.59999, 244.09999, ..., 232.5    , 235.7    ],\n",
       "        ...,\n",
       "        [296.19998, 296.69998, ..., 295.5    , 295.1    ],\n",
       "        [296.29   , 297.19998, ..., 296.4    , 296.6    ]],\n",
       "\n",
       "       [[242.29999, 242.2    , ..., 236.09999, 238.7    ],\n",
       "        [244.59999, 244.39   , ..., 232.     , 235.7    ],\n",
       "        ...,\n",
       "        [296.19998, 296.5    , ..., 296.     , 295.6    ],\n",
       "        [296.4    , 296.29   , ..., 297.     , 296.79   ]],\n",
       "\n",
       "       [[241.89   , 241.79999, ..., 235.5    , 237.59999],\n",
       "        [246.29999, 245.29999, ..., 231.5    , 234.5    ],\n",
       "        ...,\n",
       "        [297.     , 297.5    , ..., 296.6    , 296.29   ],\n",
       "        [297.5    , 297.69998, ..., 298.     , 297.9    ]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-71fb64ac-2766-42b3-8b7e-6402a83683c6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-71fb64ac-2766-42b3-8b7e-6402a83683c6' class='xr-section-summary' >Attributes: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>COARDS</dd><dt><span>title :</span></dt><dd>4x daily NMC reanalysis (1948)</dd><dt><span>description :</span></dt><dd>Data is from NMC initialized reanalysis\n",
       "(4x/day).  These are the 0.9950 sigma level values.</dd><dt><span>platform :</span></dt><dd>Model</dd><dt><span>references :</span></dt><dd>http://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanalysis.html</dd><dt><span>history :</span></dt><dd>Thu Jul 28 19:01:29 2022: ncks --mk_rec_dmn time files/test_1356998400000000000.nc files/t_1.nc</dd><dt><span>NCO :</span></dt><dd>netCDF Operators version 5.1.0 (Homepage = http://nco.sf.net, Code = http://github.com/nco/nco)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (time: 4, lat: 25, lon: 53)\n",
       "Coordinates:\n",
       "  * lat      (lat) float32 75.0 72.5 70.0 67.5 65.0 ... 25.0 22.5 20.0 17.5 15.0\n",
       "  * lon      (lon) float32 200.0 202.5 205.0 207.5 ... 322.5 325.0 327.5 330.0\n",
       "  * time     (time) datetime64[ns] 2013-01-01 ... 2013-01-01T18:00:00\n",
       "Data variables:\n",
       "    air      (time, lat, lon) float32 ...\n",
       "Attributes:\n",
       "    Conventions:  COARDS\n",
       "    title:        4x daily NMC reanalysis (1948)\n",
       "    description:  Data is from NMC initialized reanalysis\\n(4x/day).  These a...\n",
       "    platform:     Model\n",
       "    references:   http://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanaly...\n",
       "    history:      Thu Jul 28 19:01:29 2022: ncks --mk_rec_dmn time files/test...\n",
       "    NCO:          netCDF Operators version 5.1.0 (Homepage = http://nco.sf.ne..."
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds = xr.open_dataset('./t_1.nc',engine='netcdf4')\n",
    "ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "82b8f672-e4ea-4330-83d8-b424a02757e5",
   "metadata": {},
   "outputs": [
    {
     "ename": "UnicodeDecodeError",
     "evalue": "'utf-8' codec can't decode byte 0x89 in position 0: invalid start byte",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mUnicodeDecodeError\u001b[0m                        Traceback (most recent call last)",
      "Input \u001b[0;32mIn [15]\u001b[0m, in \u001b[0;36m<cell line: 12>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      7\u001b[0m \u001b[38;5;66;03m#filepath=\"https://object-store.cloud.muni.cz/swift/v1/foss4g-data/test/userdata.txt\"\u001b[39;00m\n\u001b[1;32m      8\u001b[0m \u001b[38;5;66;03m#filepath=\"https://object-store.cloud.muni.cz/swift/v1/foss4g-data/\"\u001b[39;00m\n\u001b[1;32m      9\u001b[0m \u001b[38;5;66;03m#filepath=\"https://object-store.cloud.muni.cz/swift/v1/foss4g-data/test/ECMWF_ERA-40_subset.nc\"\u001b[39;00m\n\u001b[1;32m     12\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m fsspec\u001b[38;5;241m.\u001b[39mopen(filepath, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mr\u001b[39m\u001b[38;5;124m\"\u001b[39m) \u001b[38;5;28;01mas\u001b[39;00m f:\n\u001b[0;32m---> 13\u001b[0m     \u001b[38;5;28mprint\u001b[39m(\u001b[43mf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mread\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m)\n",
      "File \u001b[0;32m/srv/conda/envs/notebook/lib/python3.9/codecs.py:322\u001b[0m, in \u001b[0;36mBufferedIncrementalDecoder.decode\u001b[0;34m(self, input, final)\u001b[0m\n\u001b[1;32m    319\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mdecode\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;28minput\u001b[39m, final\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m):\n\u001b[1;32m    320\u001b[0m     \u001b[38;5;66;03m# decode input (taking the buffer into account)\u001b[39;00m\n\u001b[1;32m    321\u001b[0m     data \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mbuffer \u001b[38;5;241m+\u001b[39m \u001b[38;5;28minput\u001b[39m\n\u001b[0;32m--> 322\u001b[0m     (result, consumed) \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_buffer_decode\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdata\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43merrors\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfinal\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    323\u001b[0m     \u001b[38;5;66;03m# keep undecoded input until the next call\u001b[39;00m\n\u001b[1;32m    324\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mbuffer \u001b[38;5;241m=\u001b[39m data[consumed:]\n",
      "\u001b[0;31mUnicodeDecodeError\u001b[0m: 'utf-8' codec can't decode byte 0x89 in position 0: invalid start byte"
     ]
    }
   ],
   "source": [
    "import fsspec\n",
    "filepath=\"https://object-store.cloud.muni.cz/swift/v1/testfred/\"\n",
    "filepath=\"https://object-store.cloud.muni.cz/swift/v1/testfred/t_1.nc\"\n",
    "\n",
    "#filepath=\"https://object-store.cloud.muni.cz/swift/v1/foss4g-data/test/userdata.txt\"\n",
    "#filepath=\"https://object-store.cloud.muni.cz/swift/v1/foss4g-data/\"\n",
    "#filepath=\"https://object-store.cloud.muni.cz/swift/v1/foss4g-data/test/ECMWF_ERA-40_subset.nc\"\n",
    "\n",
    "\n",
    "with fsspec.open(filepath, \"r\") as f:\n",
    "    print(f.read())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "3450927a-8a22-4114-b460-70b4c6b8812f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<OpenFile 'https://object-store.cloud.muni.cz/swift/v1/testfred/t_1.nc'>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f=fsspec.open(filepath, \"r\") \n",
    "f"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "5136cf61-1f1a-44fe-9c25-56e6f14060b9",
   "metadata": {},
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "'_io.TextIOWrapper' object has no attribute '__fspath__'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "Input \u001b[0;32mIn [25]\u001b[0m, in \u001b[0;36m<cell line: 3>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mxarray\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mxr\u001b[39;00m\n\u001b[0;32m----> 3\u001b[0m ds \u001b[38;5;241m=\u001b[39m \u001b[43mxr\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen_dataset\u001b[49m\u001b[43m(\u001b[49m\u001b[43mf\u001b[49m\u001b[43m,\u001b[49m\u001b[43mengine\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mnetcdf4\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m/srv/conda/envs/notebook/lib/python3.9/site-packages/xarray/backends/api.py:495\u001b[0m, in \u001b[0;36mopen_dataset\u001b[0;34m(filename_or_obj, engine, chunks, cache, decode_cf, mask_and_scale, decode_times, decode_timedelta, use_cftime, concat_characters, decode_coords, drop_variables, backend_kwargs, *args, **kwargs)\u001b[0m\n\u001b[1;32m    483\u001b[0m decoders \u001b[38;5;241m=\u001b[39m _resolve_decoders_kwargs(\n\u001b[1;32m    484\u001b[0m     decode_cf,\n\u001b[1;32m    485\u001b[0m     open_backend_dataset_parameters\u001b[38;5;241m=\u001b[39mbackend\u001b[38;5;241m.\u001b[39mopen_dataset_parameters,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    491\u001b[0m     decode_coords\u001b[38;5;241m=\u001b[39mdecode_coords,\n\u001b[1;32m    492\u001b[0m )\n\u001b[1;32m    494\u001b[0m overwrite_encoded_chunks \u001b[38;5;241m=\u001b[39m kwargs\u001b[38;5;241m.\u001b[39mpop(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124moverwrite_encoded_chunks\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[0;32m--> 495\u001b[0m backend_ds \u001b[38;5;241m=\u001b[39m \u001b[43mbackend\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen_dataset\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    496\u001b[0m \u001b[43m    \u001b[49m\u001b[43mfilename_or_obj\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    497\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdrop_variables\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdrop_variables\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    498\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mdecoders\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    499\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    500\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    501\u001b[0m ds \u001b[38;5;241m=\u001b[39m _dataset_from_backend_dataset(\n\u001b[1;32m    502\u001b[0m     backend_ds,\n\u001b[1;32m    503\u001b[0m     filename_or_obj,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    510\u001b[0m     \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs,\n\u001b[1;32m    511\u001b[0m )\n\u001b[1;32m    512\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m ds\n",
      "File \u001b[0;32m/srv/conda/envs/notebook/lib/python3.9/site-packages/xarray/backends/netCDF4_.py:552\u001b[0m, in \u001b[0;36mNetCDF4BackendEntrypoint.open_dataset\u001b[0;34m(self, filename_or_obj, mask_and_scale, decode_times, concat_characters, decode_coords, drop_variables, use_cftime, decode_timedelta, group, mode, format, clobber, diskless, persist, lock, autoclose)\u001b[0m\n\u001b[1;32m    532\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mopen_dataset\u001b[39m(\n\u001b[1;32m    533\u001b[0m     \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m    534\u001b[0m     filename_or_obj,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    549\u001b[0m     autoclose\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m,\n\u001b[1;32m    550\u001b[0m ):\n\u001b[0;32m--> 552\u001b[0m     filename_or_obj \u001b[38;5;241m=\u001b[39m \u001b[43m_normalize_path\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfilename_or_obj\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    553\u001b[0m     store \u001b[38;5;241m=\u001b[39m NetCDF4DataStore\u001b[38;5;241m.\u001b[39mopen(\n\u001b[1;32m    554\u001b[0m         filename_or_obj,\n\u001b[1;32m    555\u001b[0m         mode\u001b[38;5;241m=\u001b[39mmode,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    562\u001b[0m         autoclose\u001b[38;5;241m=\u001b[39mautoclose,\n\u001b[1;32m    563\u001b[0m     )\n\u001b[1;32m    565\u001b[0m     store_entrypoint \u001b[38;5;241m=\u001b[39m StoreBackendEntrypoint()\n",
      "File \u001b[0;32m/srv/conda/envs/notebook/lib/python3.9/site-packages/xarray/backends/common.py:23\u001b[0m, in \u001b[0;36m_normalize_path\u001b[0;34m(path)\u001b[0m\n\u001b[1;32m     21\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_normalize_path\u001b[39m(path):\n\u001b[1;32m     22\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(path, os\u001b[38;5;241m.\u001b[39mPathLike):\n\u001b[0;32m---> 23\u001b[0m         path \u001b[38;5;241m=\u001b[39m \u001b[43mos\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfspath\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpath\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     25\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(path, \u001b[38;5;28mstr\u001b[39m) \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m is_remote_uri(path):\n\u001b[1;32m     26\u001b[0m         path \u001b[38;5;241m=\u001b[39m os\u001b[38;5;241m.\u001b[39mpath\u001b[38;5;241m.\u001b[39mabspath(os\u001b[38;5;241m.\u001b[39mpath\u001b[38;5;241m.\u001b[39mexpanduser(path))\n",
      "File \u001b[0;32m/srv/conda/envs/notebook/lib/python3.9/site-packages/fsspec/core.py:99\u001b[0m, in \u001b[0;36mOpenFile.__fspath__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m     97\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__fspath__\u001b[39m(\u001b[38;5;28mself\u001b[39m):\n\u001b[1;32m     98\u001b[0m     \u001b[38;5;66;03m# may raise if cannot be resolved to local file\u001b[39;00m\n\u001b[0;32m---> 99\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m__fspath__\u001b[49m()\n",
      "\u001b[0;31mAttributeError\u001b[0m: '_io.TextIOWrapper' object has no attribute '__fspath__'"
     ]
    }
   ],
   "source": [
    "import xarray as xr\n",
    "\n",
    "ds = xr.open_dataset(f,engine='netcdf4')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "f5a31c11-0fdc-4052-b66f-e10642be1422",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "syntax error, unexpected WORD_WORD, expecting SCAN_ATTR or SCAN_DATASET or SCAN_ERROR\n",
      "context: NoSuchKey^\n"
     ]
    },
    {
     "ename": "OSError",
     "evalue": "[Errno -90] NetCDF: file not found: b'https://object-store.cloud.muni.cz/swift/v1/testfred/t_1.nc'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "File \u001b[0;32m/srv/conda/envs/notebook/lib/python3.9/site-packages/xarray/backends/file_manager.py:199\u001b[0m, in \u001b[0;36mCachingFileManager._acquire_with_cache_info\u001b[0;34m(self, needs_lock)\u001b[0m\n\u001b[1;32m    198\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 199\u001b[0m     file \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_cache\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_key\u001b[49m\u001b[43m]\u001b[49m\n\u001b[1;32m    200\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m:\n",
      "File \u001b[0;32m/srv/conda/envs/notebook/lib/python3.9/site-packages/xarray/backends/lru_cache.py:53\u001b[0m, in \u001b[0;36mLRUCache.__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m     52\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_lock:\n\u001b[0;32m---> 53\u001b[0m     value \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_cache\u001b[49m\u001b[43m[\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m]\u001b[49m\n\u001b[1;32m     54\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_cache\u001b[38;5;241m.\u001b[39mmove_to_end(key)\n",
      "\u001b[0;31mKeyError\u001b[0m: [<class 'netCDF4._netCDF4.Dataset'>, ('https://object-store.cloud.muni.cz/swift/v1/testfred/t_1.nc',), 'r', (('clobber', True), ('diskless', False), ('format', 'NETCDF4'), ('persist', False))]",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[0;31mOSError\u001b[0m                                   Traceback (most recent call last)",
      "Input \u001b[0;32mIn [26]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0m ds \u001b[38;5;241m=\u001b[39m \u001b[43mxr\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen_dataset\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mhttps://object-store.cloud.muni.cz/swift/v1/testfred/t_1.nc\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43mengine\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mnetcdf4\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m/srv/conda/envs/notebook/lib/python3.9/site-packages/xarray/backends/api.py:495\u001b[0m, in \u001b[0;36mopen_dataset\u001b[0;34m(filename_or_obj, engine, chunks, cache, decode_cf, mask_and_scale, decode_times, decode_timedelta, use_cftime, concat_characters, decode_coords, drop_variables, backend_kwargs, *args, **kwargs)\u001b[0m\n\u001b[1;32m    483\u001b[0m decoders \u001b[38;5;241m=\u001b[39m _resolve_decoders_kwargs(\n\u001b[1;32m    484\u001b[0m     decode_cf,\n\u001b[1;32m    485\u001b[0m     open_backend_dataset_parameters\u001b[38;5;241m=\u001b[39mbackend\u001b[38;5;241m.\u001b[39mopen_dataset_parameters,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    491\u001b[0m     decode_coords\u001b[38;5;241m=\u001b[39mdecode_coords,\n\u001b[1;32m    492\u001b[0m )\n\u001b[1;32m    494\u001b[0m overwrite_encoded_chunks \u001b[38;5;241m=\u001b[39m kwargs\u001b[38;5;241m.\u001b[39mpop(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124moverwrite_encoded_chunks\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[0;32m--> 495\u001b[0m backend_ds \u001b[38;5;241m=\u001b[39m \u001b[43mbackend\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen_dataset\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    496\u001b[0m \u001b[43m    \u001b[49m\u001b[43mfilename_or_obj\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    497\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdrop_variables\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdrop_variables\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    498\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mdecoders\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    499\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    500\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    501\u001b[0m ds \u001b[38;5;241m=\u001b[39m _dataset_from_backend_dataset(\n\u001b[1;32m    502\u001b[0m     backend_ds,\n\u001b[1;32m    503\u001b[0m     filename_or_obj,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    510\u001b[0m     \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs,\n\u001b[1;32m    511\u001b[0m )\n\u001b[1;32m    512\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m ds\n",
      "File \u001b[0;32m/srv/conda/envs/notebook/lib/python3.9/site-packages/xarray/backends/netCDF4_.py:553\u001b[0m, in \u001b[0;36mNetCDF4BackendEntrypoint.open_dataset\u001b[0;34m(self, filename_or_obj, mask_and_scale, decode_times, concat_characters, decode_coords, drop_variables, use_cftime, decode_timedelta, group, mode, format, clobber, diskless, persist, lock, autoclose)\u001b[0m\n\u001b[1;32m    532\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mopen_dataset\u001b[39m(\n\u001b[1;32m    533\u001b[0m     \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m    534\u001b[0m     filename_or_obj,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    549\u001b[0m     autoclose\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m,\n\u001b[1;32m    550\u001b[0m ):\n\u001b[1;32m    552\u001b[0m     filename_or_obj \u001b[38;5;241m=\u001b[39m _normalize_path(filename_or_obj)\n\u001b[0;32m--> 553\u001b[0m     store \u001b[38;5;241m=\u001b[39m \u001b[43mNetCDF4DataStore\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    554\u001b[0m \u001b[43m        \u001b[49m\u001b[43mfilename_or_obj\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    555\u001b[0m \u001b[43m        \u001b[49m\u001b[43mmode\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmode\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    556\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;28;43mformat\u001b[39;49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mformat\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m    557\u001b[0m \u001b[43m        \u001b[49m\u001b[43mgroup\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mgroup\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    558\u001b[0m \u001b[43m        \u001b[49m\u001b[43mclobber\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mclobber\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    559\u001b[0m \u001b[43m        \u001b[49m\u001b[43mdiskless\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdiskless\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    560\u001b[0m \u001b[43m        \u001b[49m\u001b[43mpersist\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpersist\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    561\u001b[0m \u001b[43m        \u001b[49m\u001b[43mlock\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlock\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    562\u001b[0m \u001b[43m        \u001b[49m\u001b[43mautoclose\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mautoclose\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    563\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    565\u001b[0m     store_entrypoint \u001b[38;5;241m=\u001b[39m StoreBackendEntrypoint()\n\u001b[1;32m    566\u001b[0m     \u001b[38;5;28;01mwith\u001b[39;00m close_on_error(store):\n",
      "File \u001b[0;32m/srv/conda/envs/notebook/lib/python3.9/site-packages/xarray/backends/netCDF4_.py:382\u001b[0m, in \u001b[0;36mNetCDF4DataStore.open\u001b[0;34m(cls, filename, mode, format, group, clobber, diskless, persist, lock, lock_maker, autoclose)\u001b[0m\n\u001b[1;32m    376\u001b[0m kwargs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mdict\u001b[39m(\n\u001b[1;32m    377\u001b[0m     clobber\u001b[38;5;241m=\u001b[39mclobber, diskless\u001b[38;5;241m=\u001b[39mdiskless, persist\u001b[38;5;241m=\u001b[39mpersist, \u001b[38;5;28mformat\u001b[39m\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mformat\u001b[39m\n\u001b[1;32m    378\u001b[0m )\n\u001b[1;32m    379\u001b[0m manager \u001b[38;5;241m=\u001b[39m CachingFileManager(\n\u001b[1;32m    380\u001b[0m     netCDF4\u001b[38;5;241m.\u001b[39mDataset, filename, mode\u001b[38;5;241m=\u001b[39mmode, kwargs\u001b[38;5;241m=\u001b[39mkwargs\n\u001b[1;32m    381\u001b[0m )\n\u001b[0;32m--> 382\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mcls\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mmanager\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mgroup\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mgroup\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmode\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmode\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlock\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlock\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mautoclose\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mautoclose\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m/srv/conda/envs/notebook/lib/python3.9/site-packages/xarray/backends/netCDF4_.py:330\u001b[0m, in \u001b[0;36mNetCDF4DataStore.__init__\u001b[0;34m(self, manager, group, mode, lock, autoclose)\u001b[0m\n\u001b[1;32m    328\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_group \u001b[38;5;241m=\u001b[39m group\n\u001b[1;32m    329\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_mode \u001b[38;5;241m=\u001b[39m mode\n\u001b[0;32m--> 330\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mformat \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mds\u001b[49m\u001b[38;5;241m.\u001b[39mdata_model\n\u001b[1;32m    331\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_filename \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mds\u001b[38;5;241m.\u001b[39mfilepath()\n\u001b[1;32m    332\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mis_remote \u001b[38;5;241m=\u001b[39m is_remote_uri(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_filename)\n",
      "File \u001b[0;32m/srv/conda/envs/notebook/lib/python3.9/site-packages/xarray/backends/netCDF4_.py:391\u001b[0m, in \u001b[0;36mNetCDF4DataStore.ds\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    389\u001b[0m \u001b[38;5;129m@property\u001b[39m\n\u001b[1;32m    390\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mds\u001b[39m(\u001b[38;5;28mself\u001b[39m):\n\u001b[0;32m--> 391\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_acquire\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m/srv/conda/envs/notebook/lib/python3.9/site-packages/xarray/backends/netCDF4_.py:385\u001b[0m, in \u001b[0;36mNetCDF4DataStore._acquire\u001b[0;34m(self, needs_lock)\u001b[0m\n\u001b[1;32m    384\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_acquire\u001b[39m(\u001b[38;5;28mself\u001b[39m, needs_lock\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m):\n\u001b[0;32m--> 385\u001b[0m     \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_manager\u001b[38;5;241m.\u001b[39macquire_context(needs_lock) \u001b[38;5;28;01mas\u001b[39;00m root:\n\u001b[1;32m    386\u001b[0m         ds \u001b[38;5;241m=\u001b[39m _nc4_require_group(root, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_group, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_mode)\n\u001b[1;32m    387\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m ds\n",
      "File \u001b[0;32m/srv/conda/envs/notebook/lib/python3.9/contextlib.py:119\u001b[0m, in \u001b[0;36m_GeneratorContextManager.__enter__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    117\u001b[0m \u001b[38;5;28;01mdel\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39margs, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mkwds, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mfunc\n\u001b[1;32m    118\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 119\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mnext\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgen\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    120\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mStopIteration\u001b[39;00m:\n\u001b[1;32m    121\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mgenerator didn\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mt yield\u001b[39m\u001b[38;5;124m\"\u001b[39m) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;28mNone\u001b[39m\n",
      "File \u001b[0;32m/srv/conda/envs/notebook/lib/python3.9/site-packages/xarray/backends/file_manager.py:187\u001b[0m, in \u001b[0;36mCachingFileManager.acquire_context\u001b[0;34m(self, needs_lock)\u001b[0m\n\u001b[1;32m    184\u001b[0m \u001b[38;5;129m@contextlib\u001b[39m\u001b[38;5;241m.\u001b[39mcontextmanager\n\u001b[1;32m    185\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21macquire_context\u001b[39m(\u001b[38;5;28mself\u001b[39m, needs_lock\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m):\n\u001b[1;32m    186\u001b[0m     \u001b[38;5;124;03m\"\"\"Context manager for acquiring a file.\"\"\"\u001b[39;00m\n\u001b[0;32m--> 187\u001b[0m     file, cached \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_acquire_with_cache_info\u001b[49m\u001b[43m(\u001b[49m\u001b[43mneeds_lock\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    188\u001b[0m     \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m    189\u001b[0m         \u001b[38;5;28;01myield\u001b[39;00m file\n",
      "File \u001b[0;32m/srv/conda/envs/notebook/lib/python3.9/site-packages/xarray/backends/file_manager.py:205\u001b[0m, in \u001b[0;36mCachingFileManager._acquire_with_cache_info\u001b[0;34m(self, needs_lock)\u001b[0m\n\u001b[1;32m    203\u001b[0m     kwargs \u001b[38;5;241m=\u001b[39m kwargs\u001b[38;5;241m.\u001b[39mcopy()\n\u001b[1;32m    204\u001b[0m     kwargs[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmode\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_mode\n\u001b[0;32m--> 205\u001b[0m file \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_opener\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_args\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    206\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_mode \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mw\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[1;32m    207\u001b[0m     \u001b[38;5;66;03m# ensure file doesn't get overridden when opened again\u001b[39;00m\n\u001b[1;32m    208\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_mode \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124ma\u001b[39m\u001b[38;5;124m\"\u001b[39m\n",
      "File \u001b[0;32msrc/netCDF4/_netCDF4.pyx:2307\u001b[0m, in \u001b[0;36mnetCDF4._netCDF4.Dataset.__init__\u001b[0;34m()\u001b[0m\n",
      "File \u001b[0;32msrc/netCDF4/_netCDF4.pyx:1925\u001b[0m, in \u001b[0;36mnetCDF4._netCDF4._ensure_nc_success\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mOSError\u001b[0m: [Errno -90] NetCDF: file not found: b'https://object-store.cloud.muni.cz/swift/v1/testfred/t_1.nc'"
     ]
    }
   ],
   "source": [
    "ds = xr.open_dataset('https://object-store.cloud.muni.cz/swift/v1/testfred/t_1.nc',engine='netcdf4')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e58437f3-29f1-4df7-9e1f-ba803fe8c238",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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