Update output from docs. Update path to hats catalogs.

docs/getting-started.rst

@@ -1,5 +1,5 @@
 Getting Started with LSDB
-============
+==========================
 
 Installation
 --------------------------
@@ -70,7 +70,7 @@ Catalog, and specify which columns we want to use from it.
 
     import lsdb
     ztf = lsdb.read_hats(
-        'https://data.lsdb.io/unstable/ztf/ztf_dr14/',
+        'https://data.lsdb.io/hats/ztf/ztf_dr14/',
         columns=["ra", "dec", "ps1_objid", "nobs_r", "mean_mag_r"],
     )
     >> ztf
@@ -133,9 +133,9 @@ get accurate results. This should be provided with the catalog by the catalog's
 .. code-block:: python
 
     gaia = lsdb.read_hats(
-        'https://data.lsdb.io/unstable/gaia_dr3/gaia/',
+        'https://data.lsdb.io/hats/gaia/gaia/',
         columns=["ra", "dec", "phot_g_n_obs", "phot_g_mean_flux", "pm"],
-        margin_cache="https://data.lsdb.io/unstable/gaia_dr3/gaia_10arcs/",
+        margin_cache="https://data.lsdb.io/hats/gaia/gaia_10arcs/",
     )
 
 Once we've got our other catalog, we can crossmatch the two together!

docs/index.rst

@@ -57,7 +57,6 @@ Using this Guide
    :hidden:
 
    Home page <self>
-   Installation <installation>
    Getting Started <getting-started>
    Tutorials <tutorials>
    API Reference <autoapi/index>

docs/tutorials.rst

@@ -26,6 +26,7 @@ A more in-depth look into how LSDB works
     :name: Advanced Topics
 
     Topic: Import catalogs <tutorials/import_catalogs>
+    Topic: Accessing Remote Data <tutorials/remote_data>
     Topic: Margins <tutorials/margins>
     Topic: Performance Testing <tutorials/performance>
 

docs/tutorials/filtering_large_catalogs.ipynb

@@ -82,7 +82,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "surveys_path = \"https://data.lsdb.io/unstable/\""
+    "surveys_path = \"https://data.lsdb.io/hats/\""
    ]
   },
   {
@@ -384,7 +384,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "hipscatenv",
+   "display_name": "demo",
    "language": "python",
    "name": "python3"
   },
@@ -398,7 +398,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.14"
+   "version": "3.12.3"
   }
  },
  "nbformat": 4,

docs/tutorials/getting_data.ipynb

@@ -33,7 +33,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "gaia_dr3 = lsdb.read_hats(\"https://data.lsdb.io/unstable/gaia_dr3/gaia/\")\n",
+    "gaia_dr3 = lsdb.read_hats(\"https://data.lsdb.io/hats/gaia/gaia/\")\n",
     "gaia_dr3"
    ]
   },
@@ -73,8 +73,8 @@
    "outputs": [],
    "source": [
     "gaia_dr3 = lsdb.read_hats(\n",
-    "    \"https://data.lsdb.io/unstable/gaia_dr3/gaia/\",\n",
-    "    margin_cache=\"https://data.lsdb.io/unstable/gaia_dr3/gaia_10arcs/\",\n",
+    "    \"https://data.lsdb.io/hats/gaia/gaia/\",\n",
+    "    margin_cache=\"https://data.lsdb.io/hats/gaia/gaia_10arcs/\",\n",
     "    columns=[\n",
     "        \"source_id\",\n",
     "        \"ra\",\n",

docs/tutorials/import_catalogs.ipynb

@@ -38,7 +38,9 @@
    "id": "529d9e23",
    "metadata": {},
    "source": [
-    "We will be importing `small_sky_order1` from a single CSV file:"
+    "We will be importing `small_sky` from a single CSV file.\n",
+    "\n",
+    "Let's define the input and output paths:"
    ]
   },
   {
@@ -52,37 +54,14 @@
     }
    },
    "outputs": [],
-   "source": [
-    "catalog_name = \"small_sky_order1\"\n",
-    "test_data_dir = Path.cwd() / \"..\" / \"..\" / \"tests\" / \"data\""
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "8b37826f",
-   "metadata": {},
-   "source": [
-    "Let's define the input and output paths:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "59e857888ae9ea70",
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2023-11-10T15:14:55.958272Z",
-     "start_time": "2023-11-10T15:14:55.924340Z"
-    }
-   },
-   "outputs": [],
    "source": [
     "# Input paths\n",
-    "catalog_dir = test_data_dir / catalog_name\n",
-    "catalog_csv_path = catalog_dir / f\"{catalog_name}.csv\"\n",
+    "test_data_dir = Path.cwd() / \"..\" / \"..\" / \"tests\" / \"data\"\n",
+    "catalog_csv_path = test_data_dir / \"raw\" / \"small_sky\" / \"small_sky.csv\"\n",
     "\n",
     "# Temporary directory for the intermediate/output files\n",
-    "tmp_dir = tempfile.TemporaryDirectory()"
+    "tmp_dir = tempfile.TemporaryDirectory()\n",
+    "tmp_path = Path(tmp_dir.name)"
    ]
   },
   {
@@ -120,7 +99,7 @@
     ")\n",
     "\n",
     "# Save it to disk in HATS format\n",
-    "catalog.to_hats(f\"{tmp_dir.name}/from_dataframe\")"
+    "catalog.to_hats(tmp_path / \"from_dataframe\")"
    ]
   },
   {
@@ -196,7 +175,7 @@
     "    file_reader=\"csv\",\n",
     "    input_file_list=[catalog_csv_path],\n",
     "    output_artifact_name=\"from_import_pipeline\",\n",
-    "    output_path=tmp_dir.name,\n",
+    "    output_path=tmp_path,\n",
     "    resume=False,\n",
     ")\n",
     "\n",
@@ -226,7 +205,7 @@
    },
    "outputs": [],
    "source": [
-    "from_dataframe_catalog = lsdb.read_hats(f\"{tmp_dir.name}/from_dataframe\")\n",
+    "from_dataframe_catalog = lsdb.read_hats(tmp_path / \"from_dataframe\")\n",
     "from_dataframe_catalog"
    ]
   },
@@ -242,7 +221,7 @@
    },
    "outputs": [],
    "source": [
-    "from_import_pipeline_catalog = lsdb.read_hats(f\"{tmp_dir.name}/from_import_pipeline\")\n",
+    "from_import_pipeline_catalog = lsdb.read_hats(tmp_path / \"from_import_pipeline\")\n",
     "from_import_pipeline_catalog"
    ]
   },
@@ -284,11 +263,19 @@
    "source": [
     "tmp_dir.cleanup()"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "240241dc",
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "demo",
    "language": "python",
    "name": "python3"
   },
@@ -302,7 +289,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.14"
+   "version": "3.12.3"
   }
  },
  "nbformat": 4,