Update colab notebook

examples/pysr_demo.ipynb

@@ -15,68 +15,9 @@
     "id": "tQ1r1bbb0yBv"
    },
    "source": [
-    "\n",
     "## Instructions\n",
     "1. Work on a copy of this notebook: _File_ > _Save a copy in Drive_ (you will need a Google account).\n",
-    "2. (Optional) If you would like to do the deep learning component of this tutorial, turn on the GPU with Edit->Notebook settings->Hardware accelerator->GPU\n",
-    "3. Execute the following cell (click on it and press Ctrl+Enter) to install Julia. This may take a minute or so.\n",
-    "4. Continue to the next section.\n",
-    "\n",
-    "_Notes_:\n",
-    "* If your Colab Runtime gets reset (e.g., due to inactivity), repeat steps 3, 4.\n",
-    "* After installation, if you want to change the Julia version or activate/deactivate the GPU, you will need to reset the Runtime: _Runtime_ > _Delete and disconnect runtime_ and repeat steps 2-4."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "COndi88gbDgO"
-   },
-   "source": [
-    "**Run the following code to install Julia**"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "colab": {
-     "base_uri": "https://localhost:8080/"
-    },
-    "id": "GIeFXS0F0zww",
-    "outputId": "5399ed75-f77f-47c5-e53b-4b2f231f2839"
-   },
-   "outputs": [],
-   "source": [
-    "!curl -fsSL https://install.julialang.org | sh -s -- -y --default-channel 1.10"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "colab": {
-     "base_uri": "https://localhost:8080/"
-    },
-    "id": "Iu9X-Y-YNmwM",
-    "outputId": "ee14af65-043a-4ad6-efa0-3cdcc48a4eb8"
-   },
-   "outputs": [],
-   "source": [
-    "# Make julia available on PATH:\n",
-    "!ln -s $HOME/.juliaup/bin/julia /usr/local/bin/julia\n",
-    "\n",
-    "# Test it works:\n",
-    "!julia --version"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "id": "ORv1c6xvbDgV"
-   },
-   "source": [
-    "Install PySR"
+    "2. (Optional) If you would like to do the deep learning component of this tutorial, turn on the GPU with Edit->Notebook settings->Hardware accelerator->GPU\n"
    ]
   },
   {
@@ -91,36 +32,23 @@
    },
    "outputs": [],
    "source": [
-    "!pip install pysr && python -m pysr install"
+    "!pip install -U pysr"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {
-    "id": "etTMEV0wDqld"
-   },
+   "metadata": {},
    "source": [
-    "Colab's printing is non-standard, so we need to manually initialize Julia and redirect its printing. Normally, however, this is not required, and PySR will automatically start Julia during the first call to `.fit`:"
+    "Julia and Julia dependencies are installed at first import:"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "id": "j666aOI8xWF_"
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "def init_colab_printing():\n",
-    "    from pysr.julia_helpers import init_julia\n",
-    "    from julia.tools import redirect_output_streams\n",
-    "\n",
-    "    julia_kwargs = dict(optimize=3, threads=\"auto\", compiled_modules=False)\n",
-    "    init_julia(julia_kwargs=julia_kwargs)\n",
-    "    redirect_output_streams()\n",
-    "\n",
-    "\n",
-    "init_colab_printing()"
+    "import pysr"
    ]
   },
   {
@@ -129,7 +57,7 @@
     "id": "qeCPKd9wldEK"
    },
    "source": [
-    "Now, let's import all of our libraries:"
+    "Now, let's import everything else as well as the PySRRegressor:\n"
    ]
   },
   {
@@ -815,26 +743,7 @@
     "where $p_i$ is the $i$th prime number, and $x$ is the input feature.\n",
     "\n",
     "Let's see if we can discover this using\n",
-    "the [Primes.jl](https://github.com/JuliaMath/Primes.jl) package.\n",
-    "\n",
-    "First, let's get the Julia backend\n",
-    "Here, we might choose to manually specify unlimited threads, `-O3`,\n",
-    "and `compile_modules=False`, although this will only propagate if Julia has not yet started:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "id": "yUC4BMuHG-KN"
-   },
-   "outputs": [],
-   "source": [
-    "import pysr\n",
-    "\n",
-    "jl = pysr.julia_helpers.init_julia(\n",
-    "    julia_kwargs=dict(optimize=3, threads=\"auto\", compiled_modules=False)\n",
-    ")"
+    "the [Primes.jl](https://github.com/JuliaMath/Primes.jl) package."
    ]
   },
   {
@@ -859,7 +768,9 @@
    },
    "outputs": [],
    "source": [
-    "jl.eval(\n",
+    "from pysr import jl\n",
+    "\n",
+    "jl.seval(\n",
     "    \"\"\"\n",
     "import Pkg\n",
     "Pkg.add(\"Primes\")\n",
@@ -885,7 +796,7 @@
    },
    "outputs": [],
    "source": [
-    "jl.eval(\"import Primes\")"
+    "jl.seval(\"import Primes\")"
    ]
   },
   {
@@ -906,7 +817,7 @@
    },
    "outputs": [],
    "source": [
-    "jl.eval(\n",
+    "jl.seval(\n",
     "    \"\"\"\n",
     "function p(i::T) where T\n",
     "    if 0.5 < i < 1000\n",