diff --git a/.github/workflows/tests+pypi.yml b/.github/workflows/tests+pypi.yml
index 6709fb32..bc5648e6 100644
--- a/.github/workflows/tests+pypi.yml
+++ b/.github/workflows/tests+pypi.yml
@@ -224,13 +224,16 @@ jobs:
           cd ../../../
           rm -rf libmpdataxx
 
+      - uses: julia-actions/setup-julia@v2
+      - run: julia --version
+
       # https://github.com/numba/numba/issues/6350#issuecomment-728174860
       - if: matrix.platform == 'ubuntu-latest'
         run: echo NUMBA_THREADING_LAYER=omp >> $GITHUB_ENV
 
       - env:
           NUMBA_OPT: 1
-        run: python -m pytest --durations=10 -p no:unraisableexception -We tests/devops_tests/test_notebooks.py
+        run: python -m pytest -rP -vv --durations=10 -p no:unraisableexception -We tests/devops_tests/test_notebooks.py
 
       - if: ${{ matrix.platform == 'ubuntu-latest' && matrix.python-version == '3.11'}}
         run: |
diff --git a/examples/PyMPDATA_examples/trixi_comparison/advection_comparison.ipynb b/examples/PyMPDATA_examples/trixi_comparison/advection_comparison.ipynb
new file mode 100644
index 00000000..b35ce079
--- /dev/null
+++ b/examples/PyMPDATA_examples/trixi_comparison/advection_comparison.ipynb
@@ -0,0 +1,627 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "e333839d",
+   "metadata": {},
+   "source": [
+    "[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/open-atmos/PyMPDATA.git/main?urlpath=lab/tree/examples/PyMPDATA_examples/advection_diffusion_2d/advection-diffusion-2d.ipynb)\n",
+    "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/open-atmos/examples/blob/main/examples/PyMPDATA_examples/advection_diffusion_2d/advection-diffusion-2d.ipynb)"
+   ]
+  },
+  {
+   "metadata": {},
+   "cell_type": "markdown",
+   "source": [
+    "# Introduction\n",
+    "Trixi.jl is a numerical simulation framework for conservation laws written in Julia. It is based on the Discontinuous Galerkin (DG) method and for the purpose of this comparison, we will use the StructuredMesh for data representation.\n",
+    "\n",
+    "This notebook compares the results of a simple advection equation solved in 2D by PyMPDATA and Trixi.jl.\n",
+    "The general flow of the notebook is as follows:\n",
+    "1. We define the advection equation and the common settings for both PyMPDATA and Trixi.jl in the JSON file.\n",
+    "2. We run the simulation in Trixi.jl and save the results.\n",
+    "3. We use Trixi2Vtk to convert the results to a vtk file.\n",
+    "4. We reshape the results from Trixi.jl to match the shape of the results from PyMPDATA.\n",
+    "5. We run the simulation in PyMPDATA for a bigger nx and ny, to account for the polynomial degree in Trixi.jl. \n",
+    "6. We compare the results from PyMPDATA and Trixi.jl.\n",
+    "7. We assert that the results are close to each other, this is to ensure that the implementation of PyMPDATA is correct.\n",
+    "\n",
+    "To run the notebook, Julia and the following Julia packages are required:\n",
+    "- JSON\n",
+    "- Trixi\n",
+    "- OrdinaryDiffEq\n",
+    "- Trixi2Vtk\n",
+    "- Pkg"
+   ],
+   "id": "2448bffa3ee6d9ff"
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0f162ce9-5704-4464-8b67-be8c86ecabc8",
+   "metadata": {},
+   "source": [
+    "## common settings"
+   ]
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-10-17T20:54:15.785252Z",
+     "start_time": "2024-10-17T20:54:15.764141Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "SETUP = {\n",
+    "    \"nx\": 32,\n",
+    "    \"ny\": 32,\n",
+    "    \"ux\": 0.25,\n",
+    "    \"uy\": 0.25,\n",
+    "    \"dt\": 0.025,\n",
+    "    \"tmax\": 2.0,\n",
+    "    \"polydeg\": 2,\n",
+    "    \"omega\": 3.141592,\n",
+    "    \"min_x\": -1.0,\n",
+    "    \"min_y\": -1.0,\n",
+    "    \"max_x\": 1.0,\n",
+    "    \"max_y\": 1.0\n",
+    "}\n",
+    "\n",
+    "assert SETUP[\"nx\"] == SETUP[\"ny\"]\n",
+    "\n",
+    "import json\n",
+    "import subprocess\n",
+    "with open('setup.json', 'w', encoding='UTF-8') as f:\n",
+    "    json.dump(SETUP, f)"
+   ],
+   "id": "dff76910f0610a2d",
+   "outputs": [],
+   "execution_count": 1
+  },
+  {
+   "metadata": {},
+   "cell_type": "markdown",
+   "source": [
+    "## Trixi.jl"
+   ],
+   "id": "52cd27020f7efe9"
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-10-17T20:54:15.972485Z",
+     "start_time": "2024-10-17T20:54:15.955869Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "%%writefile trixi.jl\n",
+    "import Pkg\n",
+    "Pkg.add([\"JSON\", \"Trixi\", \"OrdinaryDiffEq\", \"Trixi2Vtk\"])\n",
+    "using JSON\n",
+    "using Trixi\n",
+    "using OrdinaryDiffEq\n",
+    "using Trixi2Vtk\n",
+    "\n",
+    "setup = JSON.parsefile(\"./setup.json\")\n",
+    "\n",
+    "advection_velocity = (setup[\"ux\"], setup[\"uy\"])\n",
+    "equations = LinearScalarAdvectionEquation2D(advection_velocity)\n",
+    "solver = DGSEM(polydeg = setup[\"polydeg\"])\n",
+    "\n",
+    "function initial_condition(x, t, equations::LinearScalarAdvectionEquation2D)\n",
+    "    return SVector(sin(setup[\"omega\"]*sum(x)) + 1)\n",
+    "end\n",
+    "\n",
+    "cells_per_dimension = (setup[\"nx\"], setup[\"ny\"])\n",
+    "coordinates_min = (setup[\"min_x\"], setup[\"min_y\"])\n",
+    "coordinates_max = (setup[\"max_x\"], setup[\"max_y\"])\n",
+    "\n",
+    "mesh = StructuredMesh(cells_per_dimension, coordinates_min, coordinates_max)\n",
+    "semi = SemidiscretizationHyperbolic(mesh, equations, initial_condition, solver)\n",
+    "\n",
+    "tspan = (0.0, setup[\"tmax\"])\n",
+    "ode = semidiscretize(semi, tspan);\n",
+    "\n",
+    "summary_callback = SummaryCallback()\n",
+    "save_solution = SaveSolutionCallback(save_initial_solution = false, interval=100)\n",
+    "\n",
+    "stepsize_callback = StepsizeCallback(cfl = 1.6)\n",
+    "\n",
+    "callbacks = CallbackSet(summary_callback, save_solution, stepsize_callback)\n",
+    "\n",
+    "time_int_tol = 1e-6\n",
+    "sol = solve(ode, CarpenterKennedy2N54();\n",
+    "            abstol = time_int_tol,\n",
+    "            reltol = time_int_tol,\n",
+    "            dt = setup[\"dt\"],\n",
+    "            ode_default_options()..., callback = callbacks);\n",
+    "\n",
+    "summary_callback()"
+   ],
+   "id": "6586bff9a39d588f",
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Overwriting trixi.jl\n"
+     ]
+    }
+   ],
+   "execution_count": 2
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-10-17T20:54:58.817780Z",
+     "start_time": "2024-10-17T20:54:16.041469Z"
+    }
+   },
+   "cell_type": "code",
+   "source": "subprocess.run([\"julia\", \"trixi.jl\"], check=True)",
+   "id": "56fb8302adfc01e7",
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "CompletedProcess(args=['julia', 'trixi.jl'], returncode=0)"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "execution_count": 3
+  },
+  {
+   "metadata": {},
+   "cell_type": "markdown",
+   "source": "## PyMPDATA",
+   "id": "a30cc2b4961f1be7"
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-10-17T20:54:59.897488Z",
+     "start_time": "2024-10-17T20:54:58.817780Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "import numpy as np\n",
+    "import meshio\n",
+    "from open_atmos_jupyter_utils import show_plot\n",
+    "import matplotlib.pyplot as plt\n",
+    "from PyMPDATA import Solver, ScalarField, VectorField, Stepper, Options\n",
+    "from PyMPDATA.boundary_conditions import Periodic\n",
+    "import os"
+   ],
+   "id": "9aaadc4a5234804a",
+   "outputs": [],
+   "execution_count": 4
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-10-17T20:54:59.904992Z",
+     "start_time": "2024-10-17T20:54:59.898836Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "dt = SETUP[\"dt\"]\n",
+    "tmax = SETUP[\"tmax\"]\n",
+    "nt = int(tmax / dt)\n",
+    "\n",
+    "nx = SETUP[\"nx\"] * SETUP[\"polydeg\"] + 1\n",
+    "ny = SETUP[\"ny\"] * SETUP[\"polydeg\"] + 1\n",
+    "ux  = SETUP[\"ux\"]\n",
+    "uy = SETUP[\"uy\"]\n",
+    "omega = SETUP[\"omega\"]\n",
+    "\n",
+    "min_x, min_y = SETUP[\"min_x\"], SETUP[\"min_y\"]\n",
+    "max_x, max_y = SETUP[\"max_x\"], SETUP[\"max_y\"]\n",
+    "dx_temp = (max_x - min_x) / (nx - 1)\n",
+    "dy_temp = (max_y - min_y) / (ny - 1)\n",
+    "min_x, max_x = min_x - dx_temp/2, max_x + dx_temp/2\n",
+    "min_y, max_y = min_y - dy_temp/2, max_y + dy_temp/2\n",
+    "dx = (max_x - min_x) / nx\n",
+    "dy = (max_y - min_y) / ny\n",
+    "Cx = ux * dt / dx\n",
+    "Cy = uy * dt / dy"
+   ],
+   "id": "9a0f60b51e32ce3e",
+   "outputs": [],
+   "execution_count": 5
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-10-17T20:54:59.949432Z",
+     "start_time": "2024-10-17T20:54:59.908312Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "opt = Options(n_iters=3)\n",
+    "boundary_conditions = (Periodic(), Periodic())"
+   ],
+   "id": "64e3274fa4ac14a6",
+   "outputs": [],
+   "execution_count": 6
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-10-17T20:54:59.966791Z",
+     "start_time": "2024-10-17T20:54:59.949432Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "def initial_condition():\n",
+    "    return np.array(\n",
+    "    [\n",
+    "        np.sin(omega*(x+y)) + 1 for x in np.linspace(min_x, max_x, nx)\n",
+    "        for y in np.linspace(min_y, max_y, ny)\n",
+    "    ],\n",
+    "    dtype=float\n",
+    ").reshape((nx, ny))\n",
+    "\n",
+    "advectee = ScalarField(data=initial_condition(), halo=opt.n_halo, boundary_conditions=boundary_conditions)"
+   ],
+   "id": "cab790be5c425ea5",
+   "outputs": [],
+   "execution_count": 7
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-10-17T20:54:59.976655Z",
+     "start_time": "2024-10-17T20:54:59.966791Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "field_x = np.full((nx+1, ny), Cx, dtype=opt.dtype)\n",
+    "field_y = np.full((nx, ny+1), Cy, dtype=opt.dtype)\n",
+    "\n",
+    "advector = VectorField(\n",
+    "    data=(field_x, field_y),\n",
+    "    halo=opt.n_halo,\n",
+    "    boundary_conditions=(boundary_conditions[0], Periodic())\n",
+    ")"
+   ],
+   "id": "b454a74473b8f900",
+   "outputs": [],
+   "execution_count": 8
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-10-17T20:55:00.539653Z",
+     "start_time": "2024-10-17T20:54:59.977172Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "stepper = Stepper(options=opt, n_dims=2)\n",
+    "solver = Solver(stepper=stepper, advector=advector, advectee=advectee)"
+   ],
+   "id": "ce055b2d3a61a491",
+   "outputs": [],
+   "execution_count": 9
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-10-17T20:55:00.546502Z",
+     "start_time": "2024-10-17T20:55:00.539653Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "vmin = np.min(solver.advectee.get())\n",
+    "vmax = np.max(solver.advectee.get())"
+   ],
+   "id": "5290dbc73bd36d29",
+   "outputs": [],
+   "execution_count": 10
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-10-17T20:55:33.467534Z",
+     "start_time": "2024-10-17T20:55:00.547019Z"
+    }
+   },
+   "cell_type": "code",
+   "source": "_ = solver.advance(n_steps=nt)",
+   "id": "b29adee15e8ff545",
+   "outputs": [],
+   "execution_count": 11
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-10-17T20:55:33.475062Z",
+     "start_time": "2024-10-17T20:55:33.469404Z"
+    }
+   },
+   "cell_type": "code",
+   "source": "pympdata_result_state = solver.advectee.get().copy()",
+   "id": "f59fd725765b765e",
+   "outputs": [],
+   "execution_count": 12
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-10-17T20:55:34.277608Z",
+     "start_time": "2024-10-17T20:55:33.478136Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "plt.imshow(pympdata_result_state, cmap='viridis', vmin=vmin, vmax=vmax)\n",
+    "plt.colorbar()\n",
+    "plt.xlabel('x')\n",
+    "plt.ylabel('y')\n",
+    "plt.title('PyMDATA solution')\n",
+    "show_plot()"
+   ],
+   "id": "a041cd5f2c2dbaa",
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ],
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+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "HTML(value=\"<a href='.\\\\tmp5dn26voe.pdf' target='_blank'>.\\\\tmp5dn26voe.pdf</a><br>\")"
+      ],
+      "application/vnd.jupyter.widget-view+json": {
+       "version_major": 2,
+       "version_minor": 0,
+       "model_id": "3bcbfcb213bf4e0ea60a2233169c1f18"
+      }
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "execution_count": 13
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-10-17T20:55:34.285578Z",
+     "start_time": "2024-10-17T20:55:34.277608Z"
+    }
+   },
+   "cell_type": "code",
+   "source": "solution_filename = [f for f in os.listdir(\"./out\") if \"solution\" in f][0]",
+   "id": "c58862c96237cccf",
+   "outputs": [],
+   "execution_count": 14
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-10-17T20:55:34.308041Z",
+     "start_time": "2024-10-17T20:55:34.288863Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "%%writefile to_vtk.jl\n",
+    "using Trixi2Vtk\n",
+    "trixi2vtk(joinpath(\"out\", ARGS[1]))"
+   ],
+   "id": "8d35a730ab764f86",
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Overwriting to_vtk.jl\n"
+     ]
+    }
+   ],
+   "execution_count": 15
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-10-17T20:55:46.898943Z",
+     "start_time": "2024-10-17T20:55:34.308041Z"
+    }
+   },
+   "cell_type": "code",
+   "source": "subprocess.run([\"julia\", \"to_vtk.jl\", solution_filename], check=True)",
+   "id": "960cee65b6c01544",
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "CompletedProcess(args=['julia', 'to_vtk.jl', 'solution_000030.h5'], returncode=0)"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "execution_count": 16
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-10-17T20:55:46.910997Z",
+     "start_time": "2024-10-17T20:55:46.899967Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "try:\n",
+    "    vtu_filename = [f for f in os.listdir(\"./\") if \"vtu\" in f][0]\n",
+    "    mesh = meshio.read(vtu_filename)\n",
+    "    trixi_points = ((mesh.points[:,:2] + 1)*SETUP[\"nx\"]*SETUP[\"polydeg\"]/2).round().astype(np.int16)\n",
+    "    assert trixi_points.shape[0] == SETUP[\"nx\"]**2 * (SETUP[\"polydeg\"] + 1)**2\n",
+    "except Exception as e:\n",
+    "    e.args += (list(os.walk(os.path.curdir)),)\n",
+    "    raise e"
+   ],
+   "id": "451911db51e18682",
+   "outputs": [],
+   "execution_count": 17
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-10-17T20:55:46.956826Z",
+     "start_time": "2024-10-17T20:55:46.911540Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "try:\n",
+    "    trixi_output = np.zeros(pympdata_result_state.shape)\n",
+    "    for i in range(trixi_points.shape[0]):\n",
+    "        trixi_output[trixi_points[i][0], trixi_points[i][1]] = mesh.point_data['scalar'][i][0]\n",
+    "except Exception as e:\n",
+    "    e.args += (list(mesh.point_data.keys()),)\n",
+    "    e.args += (list(mesh.points.shape),)\n",
+    "    raise e"
+   ],
+   "id": "58595cff705f196c",
+   "outputs": [],
+   "execution_count": 18
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-10-17T20:55:47.264497Z",
+     "start_time": "2024-10-17T20:55:46.956826Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "plt.imshow(trixi_output, cmap='viridis', vmin=vmin, vmax=vmax)\n",
+    "plt.colorbar()\n",
+    "plt.xlabel('x')\n",
+    "plt.ylabel('y')\n",
+    "plt.title(\"Trixi solution\")\n",
+    "show_plot()"
+   ],
+   "id": "a126dbabdf719ee3",
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ],
+      "image/svg+xml": "<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n  \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n<svg xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"374.34235pt\" height=\"325.986375pt\" viewBox=\"0 0 374.34235 325.986375\" xmlns=\"http://www.w3.org/2000/svg\" version=\"1.1\">\n <metadata>\n  <rdf:RDF xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n   <cc:Work>\n    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n    <dc:date>2024-10-17T22:55:47.209431</dc:date>\n    <dc:format>image/svg+xml</dc:format>\n    <dc:creator>\n     <cc:Agent>\n      <dc:title>Matplotlib v3.9.1, https://matplotlib.org/</dc:title>\n     </cc:Agent>\n    </dc:creator>\n   </cc:Work>\n  </rdf:RDF>\n </metadata>\n <defs>\n  <style type=\"text/css\">*{stroke-linejoin: round; stroke-linecap: 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+   },
+   "cell_type": "code",
+   "source": [
+    "residual = pympdata_result_state - trixi_output\n",
+    "rmse = np.sqrt(np.mean(residual**2))\n",
+    "mse = np.mean(residual**2)\n",
+    "max_diff = np.max(np.abs(residual))\n",
+    "min_diff = np.min(np.abs(residual))"
+   ],
+   "id": "ec2fffd2627288b4",
+   "outputs": [],
+   "execution_count": 20
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-10-17T20:55:47.288908Z",
+     "start_time": "2024-10-17T20:55:47.270117Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "assert np.allclose(rmse, 6.94e-2, 0.1)\n",
+    "assert np.allclose(mse, 4.81e-3, 0.1)\n",
+    "assert np.allclose(max_diff, 0.285, 0.1)\n",
+    "assert np.allclose(min_diff, 2.69e-5, 0.1)"
+   ],
+   "id": "a7496a6f898495a3",
+   "outputs": [],
+   "execution_count": 21
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-10-17T20:55:47.293617Z",
+     "start_time": "2024-10-17T20:55:47.289032Z"
+    }
+   },
+   "cell_type": "code",
+   "source": "",
+   "id": "119bd01509fa1ceb",
+   "outputs": [],
+   "execution_count": 21
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/examples/setup.py b/examples/setup.py
index 9b8678d7..9964905e 100644
--- a/examples/setup.py
+++ b/examples/setup.py
@@ -33,8 +33,10 @@ def get_long_description():
         "scipy",
         "pint",
         "joblib",
+        "h5py",
         "sympy",
         "imageio",
+        "meshio",
     ],
     author="https://github.com/open-atmos/PyMPDATA/graphs/contributors",
     license="GPL-3.0",