diff --git a/notebooks/SaveTasks.ipynb b/notebooks/SaveTasks.ipynb
new file mode 100644
index 00000000..eab39c8e
--- /dev/null
+++ b/notebooks/SaveTasks.ipynb
@@ -0,0 +1,494 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "0de3635b-fc48-4e50-ac81-ceb865f32dc1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "# These are the default AWS configurations for the Analysis Sandbox.\n",
+    "# that are set in the environmnet variables. \n",
+    "aws_default_config = {\n",
+    "    #'AWS_NO_SIGN_REQUEST': 'YES', \n",
+    "    'AWS_SECRET_ACCESS_KEY': 'fake',\n",
+    "    'AWS_ACCESS_KEY_ID': 'fake',\n",
+    "}\n",
+    "\n",
+    "# To access public bucket, need to remove the AWS credentials in \n",
+    "# the environment variables or the following error will occur.\n",
+    "# PermissionError: The AWS Access Key Id you provided does not exist in our records.\n",
+    "\n",
+    "for key in aws_default_config.keys():\n",
+    "    if key in os.environ:\n",
+    "        del os.environ[key]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "f5ba7e34-981d-4174-aff8-1313978bb357",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import logging\n",
+    "import os\n",
+    "import queue\n",
+    "from threading import Thread\n",
+    "\n",
+    "import click\n",
+    "import datacube\n",
+    "import fsspec\n",
+    "from odc.dscache import create_cache\n",
+    "from odc.dscache.apps.slurpy import EOS, qmap\n",
+    "from odc.dscache.tools import (\n",
+    "    bin_dataset_stream,\n",
+    "    dataset_count,\n",
+    "    db_connect,\n",
+    "    dictionary_from_product_list,\n",
+    "    mk_raw2ds,\n",
+    "    ordered_dss,\n",
+    "    raw_dataset_stream,\n",
+    ")\n",
+    "from odc.dscache.tools.tiling import parse_gridspec_with_name\n",
+    "from odc.stats.model import DateTimeRange\n",
+    "from tqdm import tqdm\n",
+    "\n",
+    "from deafrica_conflux.cli.logs import logging_setup\n",
+    "from deafrica_conflux.hopper import bin_solar_day, persist\n",
+    "from deafrica_conflux.io import (\n",
+    "    check_dir_exists,\n",
+    "    check_file_exists,\n",
+    "    check_if_s3_uri,\n",
+    "    find_geotiff_files,\n",
+    ")\n",
+    "from deafrica_conflux.text import parse_tile_ids"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "1f678da9-eaf3-4811-b0f6-e0dcc650a4fc",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "verbose = 1\n",
+    "# Grid name africa_{10|20|30|60}\n",
+    "grid_name = \"africa_30\"\n",
+    "# Datacube product to search datasets for.\n",
+    "product = \"wofs_ls\"\n",
+    "# Only extract datasets for a given time range,\" \"Example '2020-05--P1M' month of May 2020\n",
+    "temporal_range = \"2023-03--P3M\"\n",
+    "# Compression setting for zstandard 1-fast, 9+ good but slow\n",
+    "complevel = 6\n",
+    "# Path to the directory containing the polygons raster files.\n",
+    "polygons_rasters_directory = \"s3://deafrica-waterbodies-dev/waterbodies/v0.0.2/senegal_basin/conflux/historical_extent_rasters\"\n",
+    "# Regular expression for filename matching when searching for the polygons raster files.\n",
+    "pattern = \".*\"\n",
+    "# Overwrite existing cache file.\n",
+    "overwrite = True\n",
+    "# Directory to write the cache file to.\n",
+    "output_directory = \"s3://deafrica-waterbodies-dev/waterbodies/v0.0.2/senegal_basin/conflux/\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "dff56126-bec4-4ef4-866d-31882088c74f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Set up logger.\n",
+    "logging_setup(verbose)\n",
+    "_log = logging.getLogger(__name__)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "d10883bf-c871-4be6-8c8d-0a9f0755caec",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Support pathlib Paths.\n",
+    "polygons_rasters_directory = str(polygons_rasters_directory)\n",
+    "output_directory = str(output_directory)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "6e14e4c0-7229-4050-ad46-7b856f690724",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[2023-12-04 13:12:53,642] {credentials.py:611} INFO - Found credentials in shared credentials file: ~/.aws/credentials\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Create the output directory if it does not exist.\n",
+    "is_s3 = check_if_s3_uri(output_directory)\n",
+    "if is_s3:\n",
+    "    fs = fsspec.filesystem(\"s3\")\n",
+    "else:\n",
+    "    fs = fsspec.filesystem(\"file\")\n",
+    "\n",
+    "if not check_dir_exists(output_directory):\n",
+    "    fs.makedirs(output_directory, exist_ok=True)\n",
+    "    _log.info(f\"Created directory {output_directory}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "49fba8ab-edd1-4f9d-9a09-bf410e251689",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Validate the product\n",
+    "products = [product]\n",
+    "# Connect to the datacube.\n",
+    "dc = datacube.Datacube()\n",
+    "# Get all products.\n",
+    "all_products = {p.name: p for p in dc.index.products.get_all()}\n",
+    "if len(products) == 0:\n",
+    "    raise ValueError(\"Have to supply at least one product\")\n",
+    "else:\n",
+    "    for p in products:\n",
+    "        if p not in all_products:\n",
+    "            raise ValueError(f\"No such product found: {p}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "ea6ea2dc-e82d-4497-8ea5-e44edb5a2daf",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[2023-12-04 13:12:54,194] {1838406043.py:11} INFO - Deleted s3://deafrica-waterbodies-dev/waterbodies/v0.0.2/senegal_basin/conflux/wofs_ls_2023-03--P3M.db\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Parse the temporal range.\n",
+    "temporal_range_ = DateTimeRange(temporal_range)\n",
+    "\n",
+    "output_db_fn = f\"{product}_{temporal_range_.short}.db\"\n",
+    "output_db_fp = os.path.join(output_directory, output_db_fn)\n",
+    "\n",
+    "# Check if the output file exists.\n",
+    "if check_file_exists(output_db_fp):\n",
+    "    if overwrite:\n",
+    "        fs.delete(output_db_fp, recursive=True)\n",
+    "        _log.info(f\"Deleted {output_db_fp}\")\n",
+    "        # Delete the local file created before uploading to s3.\n",
+    "        if is_s3:\n",
+    "            if check_file_exists(output_db_fn):\n",
+    "                fsspec.filesystem(\"file\").delete(output_db_fn)\n",
+    "                _log.info(f\"Deleted local file created before uploading to s3 {output_db_fn}\")\n",
+    "    else:\n",
+    "        raise FileExistsError(f\"{output_db_fp} exists!\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "45cdca5a-3047-4b37-883c-4e99d26639e8",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[2023-12-04 13:12:54,199] {2478973304.py:3} INFO - Query: {'time': (datetime.datetime(2023, 3, 1, 0, 0), datetime.datetime(2023, 5, 31, 23, 59, 59, 999999))}\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Create the query to find the datasets.\n",
+    "query = {\"time\": (temporal_range_.start, temporal_range_.end)}\n",
+    "_log.info(f\"Query: {query}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "5e71ea03-f7f7-42a4-a2d8-d88606e3bc9e",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[2023-12-04 13:12:54,205] {279200897.py:1} INFO - Getting dataset counts\n",
+      "[2023-12-04 13:12:54,263] {279200897.py:6} INFO - ..wofs_ls:   22,852\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/usr/local/lib/python3.10/dist-packages/datacube/drivers/postgres/_api.py:752: RemovedIn20Warning: Deprecated API features detected! These feature(s) are not compatible with SQLAlchemy 2.0. To prevent incompatible upgrades prior to updating applications, ensure requirements files are pinned to \"sqlalchemy<2.0\". Set environment variable SQLALCHEMY_WARN_20=1 to show all deprecation warnings.  Set environment variable SQLALCHEMY_SILENCE_UBER_WARNING=1 to silence this message. (Background on SQLAlchemy 2.0 at: https://sqlalche.me/e/b8d9)\n",
+      "  select(\n"
+     ]
+    }
+   ],
+   "source": [
+    "_log.info(\"Getting dataset counts\")\n",
+    "counts = {p: dataset_count(dc.index, product=p, **query) for p in products}\n",
+    "\n",
+    "n_total = 0\n",
+    "for p, c in counts.items():\n",
+    "    _log.info(f\"..{p}: {c:8,d}\")\n",
+    "    n_total += c\n",
+    "\n",
+    "if n_total == 0:\n",
+    "    raise ValueError(\"No datasets found\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "8c500ee6-fb6e-41c6-87ad-273ebcf7c016",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[2023-12-04 13:12:54,268] {2806460463.py:1} INFO - Training compression dictionary...\n",
+      "[2023-12-04 13:12:54,479] {2806460463.py:3} INFO - Done\n"
+     ]
+    }
+   ],
+   "source": [
+    "_log.info(\"Training compression dictionary...\")\n",
+    "zdict = dictionary_from_product_list(dc, products, samples_per_product=50, query=query)\n",
+    "_log.info(\"Done\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "fafe21e5-2f5a-4fa7-8574-38aee3af329c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "if is_s3:\n",
+    "    cache = create_cache(output_db_fn, zdict=zdict, complevel=complevel, truncate=True)\n",
+    "else:\n",
+    "    cache = create_cache(output_db_fp, zdict=zdict, complevel=complevel, truncate=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "5e3774fd-422d-470a-9dd0-c0dbb22cffe5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "raw2ds = mk_raw2ds(all_products)\n",
+    "\n",
+    "def db_task(products, conn, q):\n",
+    "    for p in products:\n",
+    "        if len(query) == 0:\n",
+    "            dss = map(raw2ds, raw_dataset_stream(p, conn))\n",
+    "        else:\n",
+    "            dss = ordered_dss(dc, product=p, **query)\n",
+    "\n",
+    "        for ds in dss:\n",
+    "            q.put(ds)\n",
+    "    q.put(EOS)\n",
+    "\n",
+    "conn = db_connect()\n",
+    "q = queue.Queue(maxsize=10_000)\n",
+    "db_thread = Thread(target=db_task, args=(products, conn, q))\n",
+    "db_thread.start()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "be571216-39da-4107-b3c6-2681d87151a6",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dss = qmap(lambda ds: ds, q, eos_marker=EOS)\n",
+    "dss = cache.tee(dss)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "ffe57a0f-1a78-4344-b0cd-c73c7ae91441",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Processing   22,852 wofs_ls datasets: 100%|██████████| 22852/22852 [00:35<00:00, 639.99it/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "cells = {}\n",
+    "grid, gridspec = parse_gridspec_with_name(grid_name)\n",
+    "cache.add_grid(gridspec, grid)\n",
+    "\n",
+    "cfg = dict(grid=grid)\n",
+    "cache.append_info_dict(\"stats/\", dict(config=cfg))\n",
+    "\n",
+    "dss = bin_dataset_stream(gridspec, dss, cells, persist=persist)\n",
+    "\n",
+    "label = f\"Processing {n_total:8,d} {product} datasets\"\n",
+    "with tqdm(dss, desc=label, total=n_total) as dss:\n",
+    "    for _ in dss:\n",
+    "        pass"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "8aff909f-2855-4369-970e-c37fdabf5bf0",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[2023-12-04 13:13:30,265] {250296155.py:2} INFO - Total bins: 4511\n",
+      "[2023-12-04 13:13:30,266] {250296155.py:3} INFO - Filtering bins by required tiles...\n",
+      "[2023-12-04 13:13:30,394] {io.py:460} INFO - Found 60 GeoTIFF files.\n",
+      "[2023-12-04 13:13:30,395] {250296155.py:7} INFO - Found 60 tiles.\n",
+      "[2023-12-04 13:13:30,419] {250296155.py:12} INFO - Total bins: 60\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Find the required tiles.\n",
+    "_log.info(f\"Total bins: {len(cells):d}\")\n",
+    "_log.info(\"Filtering bins by required tiles...\")\n",
+    "geotiff_files = find_geotiff_files(path=polygons_rasters_directory, pattern=pattern)\n",
+    "\n",
+    "tiles_ids = [parse_tile_ids(file) for file in geotiff_files]\n",
+    "_log.info(f\"Found {len(tiles_ids)} tiles.\")\n",
+    "_log.debug(f\"Tile ids: {tiles_ids}\")\n",
+    "\n",
+    "# Filter cells by tile ids.\n",
+    "cells = {k: v for k, v in cells.items() if k in tiles_ids}\n",
+    "_log.info(f\"Total bins: {len(cells):d}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "a82a1b48-396e-498b-8c39-4838dd831cd7",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[2023-12-04 13:13:30,436] {2957611989.py:13} INFO - Total of 572 unique dataset IDs after filtering\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Saving 1715 tasks to disk: 100%|██████████| 1715/1715 [00:02<00:00, 599.19it/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "tasks = bin_solar_day(cells)\n",
+    "\n",
+    "# Remove duplicate source uuids.\n",
+    "# Duplicates occur when queried datasets are captured around UTC midnight\n",
+    "# and around weekly boundary\n",
+    "tasks = {k: set(dss) for k, dss in tasks.items()}\n",
+    "\n",
+    "tasks_uuid = {k: [ds.id for ds in dss] for k, dss in tasks.items()}\n",
+    "\n",
+    "all_ids = set()\n",
+    "for k, dss in tasks_uuid.items():\n",
+    "    all_ids.update(dss)\n",
+    "_log.info(f\"Total of {len(all_ids):,d} unique dataset IDs after filtering\")\n",
+    "\n",
+    "label = f\"Saving {len(tasks)} tasks to disk\"\n",
+    "with tqdm(tasks_uuid.items(), desc=label, total=len(tasks_uuid)) as groups:\n",
+    "    for group in groups:\n",
+    "        cache.add_grid_tile(grid, group[0], group[1])\n",
+    "\n",
+    "db_thread.join()\n",
+    "cache.close()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "d7c249cc-dee2-4ab8-bd2f-3f9fb99dcbc5",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[2023-12-04 13:13:33,586] {2328381222.py:5} INFO - Cache file written to s3://deafrica-waterbodies-dev/waterbodies/v0.0.2/senegal_basin/conflux/wofs_ls_2023-03--P3M.db\n",
+      "[2023-12-04 13:13:33,587] {2328381222.py:9} INFO - Writing summary to s3://deafrica-waterbodies-dev/waterbodies/v0.0.2/senegal_basin/conflux/wofs_ls_2023-03--P3M.csv\n"
+     ]
+    }
+   ],
+   "source": [
+    "if is_s3:\n",
+    "    fs.upload(output_db_fn, output_db_fp, recursive=False)\n",
+    "    fsspec.filesystem(\"file\").delete(output_db_fn)\n",
+    "\n",
+    "_log.info(f\"Cache file written to {output_db_fp}\")\n",
+    "\n",
+    "# pylint:disable=too-many-locals\n",
+    "csv_path = os.path.join(output_directory, f\"{product}_{temporal_range}.csv\")\n",
+    "_log.info(f\"Writing summary to {csv_path}\")\n",
+    "with fs.open(csv_path, \"wt\", encoding=\"utf8\") as f:\n",
+    "    f.write('\"T\",\"X\",\"Y\",\"datasets\",\"days\"\\n')\n",
+    "    for p, x, y in sorted(tasks):\n",
+    "        dss = tasks[(p, x, y)]\n",
+    "        n_dss = len(dss)\n",
+    "        n_days = len(set(ds.time.date() for ds in dss))\n",
+    "        line = f'\"{p}\", {x:+05d}, {y:+05d}, {n_dss:4d}, {n_days:4d}\\n'\n",
+    "        f.write(line)"
+   ]
+  }
+ ],
+ "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": "3.10.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}