xarray_repr_caching_issue.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import xarray as xr\n",
    "from pathlib import Path\n",
    "import numpy as np\n",
    "\n",
    "def test_repr(nx):\n",
    "    ds = xr.DataArray(np.random.rand(nx))\n",
    "    path = Path(\"saved_on_disk.nc\")\n",
    "    if path.exists():\n",
    "        path.unlink()\n",
    "    ds.to_netcdf(path)\n",
    "    return path"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# all good here:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<xarray.Dataset>\n",
      "Dimensions:                        (dim_0: 4)\n",
      "Dimensions without coordinates: dim_0\n",
      "Data variables:\n",
      "    __xarray_dataarray_variable__  (dim_0) float64 ...\n",
      "<xarray.Dataset>\n",
      "Dimensions:                        (dim_0: 5)\n",
      "Dimensions without coordinates: dim_0\n",
      "Data variables:\n",
      "    __xarray_dataarray_variable__  (dim_0) float64 ...\n"
     ]
    }
   ],
   "source": [
    "test_repr(4)\n",
    "print(xr.open_dataset(\"saved_on_disk.nc\"))\n",
    "test_repr(5)\n",
    "print(xr.open_dataset(\"saved_on_disk.nc\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## one use of `repr` triggers issue:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:                        (dim_0: 5)\n",
       "Dimensions without coordinates: dim_0\n",
       "Data variables:\n",
       "    __xarray_dataarray_variable__  (dim_0) float64 0.4297 0.9539 ... 0.6777</pre><div class='xr-wrap' hidden><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-362f7cfb-479a-4010-992e-0689d9180ac4' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-362f7cfb-479a-4010-992e-0689d9180ac4' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>dim_0</span>: 5</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-cfa5ac4e-7ac2-4229-b3e7-a595999e78c3' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-cfa5ac4e-7ac2-4229-b3e7-a595999e78c3' class='xr-section-summary'  title='Expand/collapse section'>Coordinates: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-d09dbec3-b72e-48ce-a324-8f6b6d8ade48' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d09dbec3-b72e-48ce-a324-8f6b6d8ade48' 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>__xarray_dataarray_variable__</span></div><div class='xr-var-dims'>(dim_0)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-81b2998d-c1f8-4bb4-98e8-070c75071085' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-81b2998d-c1f8-4bb4-98e8-070c75071085' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dbfc4e5c-771e-4dc4-aaa8-0036c1353beb' class='xr-var-data-in' type='checkbox'><label for='data-dbfc4e5c-771e-4dc4-aaa8-0036c1353beb' 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'></dl></div><div class='xr-var-data'><pre>array([0.429706, 0.953915, 0.516308, 0.135891, 0.677652])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a4a154ca-641a-487b-bdda-c22eec455441' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a4a154ca-641a-487b-bdda-c22eec455441' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:                        (dim_0: 5)\n",
       "Dimensions without coordinates: dim_0\n",
       "Data variables:\n",
       "    __xarray_dataarray_variable__  (dim_0) float64 ..."
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xr.open_dataset(\"saved_on_disk.nc\")"
   ]
  },
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## note that now even the printed object shows a wrong size, even so a new file with size 4 was created:"
   ]
  },
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   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<xarray.Dataset>\n",
      "Dimensions:                        (dim_0: 5)\n",
      "Dimensions without coordinates: dim_0\n",
      "Data variables:\n",
      "    __xarray_dataarray_variable__  (dim_0) float64 ...\n"
     ]
    }
   ],
   "source": [
    "test_repr(4)\n",
    "print(xr.open_dataset(\"saved_on_disk.nc\"))"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
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