Add additional features to support SDF to Zarr conversion

docs/api/adapters.md

@@ -0,0 +1,4 @@
+
+::: polaris.dataset._adapters
+    options:
+        filters: ["!^_"]

docs/api/converters.md

@@ -0,0 +1,18 @@
+::: polaris.dataset.converters.Converter
+    options:
+        filters: ["!^_"]
+
+---
+
+
+::: polaris.dataset.converters.SDFConverter
+    options:
+        filters: ["!^_"]
+
+---
+
+::: polaris.dataset.converters.ZarrConverter
+    options:
+        filters: ["!^_"]
+
+---

docs/api/factory.md

@@ -0,0 +1,11 @@
+::: polaris.dataset.DatasetFactory
+    options:
+        filters: ["!^_"]
+
+---
+
+::: polaris.dataset.create_dataset_from_file
+    options:
+        filters: ["!^_"]
+
+---

docs/tutorials/basics.ipynb

@@ -3,7 +3,13 @@
   {
    "cell_type": "markdown",
    "id": "40f99374-b47e-4f84-bdb9-148a11f9c07d",
-   "metadata": {},
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
    "source": [
     "# The Basics\n",
     "\n",
@@ -12,7 +18,7 @@
     "    <p>This tutorial walks you through the basic usage of Polaris. We will first login to the hub and will then see how easy it is to load a dataset or benchmark from it. Finally, we will train a simple baseline to submit a first set of results!</p>\n",
     "</div>\n",
     "\n",
-    "Polaris is designed to standardize the process of constructing datasets, specifying benchmarks and evaluating novel machine learning techniques within the realms of biology, chemistry, and drug discovery.\n",
+    "Polaris is designed to standardize the process of constructing datasets, specifying benchmarks and evaluating novel machine learning techniques within the realm of drug discovery.\n",
     "\n",
     "While the Polaris library can be used independently from the <a href=\"https://polarishub.io/\">Polaris Hub</a>, the two were designed to seamlessly work together. The hub provides various pre-made, high quality datasets and benchmarks to develop and evaluate novel ML methods. In this tutorial, we will see how easy it is to load and use these datasets and benchmarks."
    ]
@@ -22,6 +28,10 @@
    "execution_count": 1,
    "id": "3d66f466",
    "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
     "tags": [
      "remove_cell"
     ]
@@ -761,7 +771,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "results.name = f\"hello-world-result\"\n",
+    "# For a complete list of meta-data, check out the BenchmarkResults object\n",
+    "results.name = \"hello-world-result\"\n",
     "results.github_url = \"https://github.com/polaris-hub/polaris-hub\"\n",
     "results.paper_url = \"https://polarishub.io/\"\n",
     "results.description = \"Hello, World!\""

docs/tutorials/custom_dataset_benchmark.ipynb

@@ -3,15 +3,20 @@
   {
    "cell_type": "markdown",
    "id": "172ae3e5",
-   "metadata": {},
+   "metadata": {
+    "editable": true,
+    "slideshow": {
+     "slide_type": ""
+    },
+    "tags": []
+   },
    "source": [
-    "# Custom datasets and benchmarks\n",
     "<div class=\"admonition abstract highlight\">\n",
     "    <p class=\"admonition-title\">In short</p>\n",
     "    <p>This tutorial walks you through the dataset and benchmark data-structures. After creating our own custom dataset and benchmark, we will learn how to upload it to the Hub!</p>\n",
     "</div>\n",
     "\n",
-    "We have already seen how easy it is to load a benchmark or dataset from the Polaris Hub. Let's now see how you could create your own!"
+    "We have already seen how easy it is to load a benchmark or dataset from the Polaris Hub. Let's now learn a bit more about the underlying data model by creating our own dataset and benchmark!"
    ]
   },
   {
@@ -626,7 +631,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.6"
+   "version": "3.12.2"
   }
  },
  "nbformat": 4,

docs/tutorials/data_curation.ipynb

@@ -5,8 +5,6 @@
    "id": "40f99374-b47e-4f84-bdb9-148a11f9c07d",
    "metadata": {},
    "source": [
-    "# Dataset curation\n",
-    "\n",
     "<div class=\"admonition abstract highlight\">\n",
     "    <p class=\"admonition-title\">In short</p>\n",
     "    <p>This tutorial shows how we can use the curation API of the Polaris library to check and improve the quality of a dataset.</p>\n",
@@ -3767,7 +3765,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.6"
+   "version": "3.12.2"
   }
  },
  "nbformat": 4,