diff --git a/.github/workflows/run-tests.yml b/.github/workflows/run-tests.yml
index a7d4d2e..a8eddc2 100644
--- a/.github/workflows/run-tests.yml
+++ b/.github/workflows/run-tests.yml
@@ -23,10 +23,11 @@ jobs:
           fetch-depth: 0
 
       - name: Check linting
-        uses: rickstaa/action-black@v1
+        uses: psf/black@stable
         id: action_black
         with:
-          black_args: "--check dep_tools"
+          options: "--check" 
+          src: "./dep_tools"
 
   testing:
     runs-on: ubuntu-latest
diff --git a/dep_tools/aws.py b/dep_tools/aws.py
new file mode 100644
index 0000000..41d3309
--- /dev/null
+++ b/dep_tools/aws.py
@@ -0,0 +1,111 @@
+import json
+from io import BytesIO
+from pathlib import Path
+from typing import IO, Union
+
+import boto3
+from botocore.client import BaseClient
+from fiona.io import MemoryFile
+from geopandas import GeoDataFrame
+from odc.geo.xr import to_cog
+from xarray import DataArray, Dataset
+
+from pystac import Item
+
+
+def object_exists(bucket: str, key: str, client: BaseClient | None = None) -> bool:
+    """Check if a key exists in a bucket."""
+    if client is None:
+        client = boto3.client("s3")
+
+    try:
+        client.head_object(Bucket=bucket, Key=key)
+        return True
+    except client.exceptions.ClientError:
+        return False
+
+
+def s3_dump(
+    data: Union[bytes, str, IO], bucket: str, key: str, client: BaseClient, **kwargs
+) -> bool:
+    """Write data to s3 object."""
+
+    r = client.put_object(Bucket=bucket, Key=key, Body=data, **kwargs)
+    code = r["ResponseMetadata"]["HTTPStatusCode"]
+    return 200 <= code < 300
+
+
+def write_to_s3(
+    d: Union[DataArray, Dataset, GeoDataFrame, str],
+    path: Union[str, Path],
+    bucket: str,
+    overwrite: bool = True,
+    use_odc_writer: bool = True,
+    client: BaseClient | None = None,
+    s3_dump_kwargs=dict(),
+    **kwargs,
+):
+    if client is None:
+        client = boto3.client("s3")
+
+    key = str(path).lstrip("/")
+
+    if not overwrite and object_exists(bucket, key, client):
+        return
+
+    if isinstance(d, (DataArray, Dataset)):
+        if use_odc_writer:
+            if "driver" in kwargs:
+                del kwargs["driver"]
+            binary_data = to_cog(d, **kwargs)
+            s3_dump(
+                binary_data,
+                bucket,
+                key,
+                client,
+                ContentType="image/tiff",
+                **s3_dump_kwargs,
+            )
+
+        else:
+            with BytesIO() as binary_data:
+                d.rio.to_raster(binary_data, driver="COG", **kwargs)
+                binary_data.seek(0)
+                s3_dump(
+                    binary_data,
+                    bucket,
+                    key,
+                    client,
+                    ContentType="image/tiff",
+                    **s3_dump_kwargs,
+                )
+
+    elif isinstance(d, GeoDataFrame):
+        with MemoryFile() as buffer:
+            d.to_file(buffer, **kwargs)
+            buffer.seek(0)
+            s3_dump(buffer.read(), bucket, key, client, **s3_dump_kwargs)
+    elif isinstance(d, Item):
+        s3_dump(
+            json.dumps(d.to_dict(), indent=4), bucket, key, client, **s3_dump_kwargs
+        )
+    elif isinstance(d, str):
+        s3_dump(d, bucket, key, client, **s3_dump_kwargs)
+    else:
+        raise ValueError(
+            "You can only write an Xarray DataArray or Dataset, Geopandas GeoDataFrame, Pystac Item, or string"
+        )
+
+
+def write_stac_s3(
+    item: Item,
+    stac_path: str,
+    bucket: str,
+    **kwargs,
+) -> None:
+    item_string = json.dumps(item.to_dict(), indent=4)
+    write_to_s3(
+        item_string, stac_path, bucket=bucket, ContentType="application/json", **kwargs
+    )
+
+    return stac_path
diff --git a/dep_tools/azure.py b/dep_tools/azure.py
index a3f5537..ceb050d 100644
--- a/dep_tools/azure.py
+++ b/dep_tools/azure.py
@@ -1,11 +1,18 @@
+from functools import partial
+import io
+import json
+from multiprocessing.dummy import Pool as ThreadPool
 import os
 from pathlib import Path
 from typing import Union, Generator
 
-import azure.storage.blob
-from azure.storage.blob import ContainerClient
-from functools import partial
-from multiprocessing.dummy import Pool as ThreadPool
+from azure.storage.blob import ContainerClient, ContentSettings
+import fiona
+from geopandas import GeoDataFrame
+from odc.geo.xr import to_cog
+from osgeo import gdal
+from pystac import Item
+from xarray import DataArray, Dataset
 
 
 def get_container_client(
@@ -23,7 +30,7 @@ def get_container_client(
             "'None' is not a valid value for 'credential'. Pass a valid name or set the 'AZURE_STORAGE_SAS_TOKEN' environment variable"
         )
 
-    return azure.storage.blob.ContainerClient(
+    return ContainerClient(
         f"https://{storage_account}.blob.core.windows.net",
         container_name=container_name,
         credential=credential,
@@ -71,3 +78,83 @@ def list_blob_container(
         blob_name = blob_record["name"]
         if blob_name.endswith(suffix):
             yield blob_name
+
+
+def build_vrt(
+    bounds: list,
+    prefix: str = "",
+    suffix: str = "",
+) -> Path:
+    blobs = [
+        f"/vsiaz/output/{blob.name}"
+        for blob in get_container_client().list_blobs(name_starts_with=prefix)
+        if blob.name.endswith(suffix)
+    ]
+
+    local_prefix = Path(prefix).stem
+    vrt_file = f"data/{local_prefix}.vrt"
+    gdal.BuildVRT(vrt_file, blobs, outputBounds=bounds)
+    return Path(vrt_file)
+
+
+def write_stac_blob_storage(
+    item: Item,
+    stac_path: str,
+    **kwargs,
+) -> str | None:
+    item_json = json.dumps(item.to_dict(), indent=4)
+    write_to_blob_storage(
+        item_json,
+        stac_path,
+        content_settings=ContentSettings(content_type="application/json"),
+        **kwargs,
+    )
+    return stac_path
+
+
+def write_to_blob_storage(
+    d: Union[DataArray, Dataset, GeoDataFrame, str],
+    path: Union[str, Path],
+    overwrite: bool = True,
+    use_odc_writer: bool = False,
+    client: ContainerClient | None = None,
+    **kwargs,
+) -> None:
+    # Allowing for a shared container client, which might be
+    # more efficient. If not provided, get one.
+    if client is None:
+        client = get_container_client()
+    blob_client = client.get_blob_client(str(path))
+    if not overwrite and blob_client.exists():
+        return
+
+    if isinstance(d, (DataArray, Dataset)):
+        if use_odc_writer:
+            if "driver" in kwargs:
+                del kwargs["driver"]
+            binary_data = to_cog(d, **kwargs)
+            blob_client.upload_blob(
+                binary_data, overwrite=overwrite, connection_timeout=TIMEOUT_SECONDS
+            )
+        else:
+            with io.BytesIO() as buffer:
+                # This is needed or rioxarray doesn't know what type it is writing
+                if "driver" not in kwargs:
+                    kwargs["driver"] = "COG"
+                d.rio.to_raster(buffer, **kwargs)
+                buffer.seek(0)
+                blob_client.upload_blob(
+                    buffer, overwrite=overwrite, connection_timeout=TIMEOUT_SECONDS
+                )
+
+    elif isinstance(d, GeoDataFrame):
+        with fiona.io.MemoryFile() as buffer:
+            d.to_file(buffer, **kwargs)
+            buffer.seek(0)
+            blob_client.upload_blob(buffer, overwrite=overwrite)
+    elif isinstance(d, str):
+        blob_client.upload_blob(d, overwrite=overwrite, **kwargs)
+    else:
+        raise ValueError(
+            "You can only write an Xarray DataArray or Dataset, or Geopandas GeoDataFrame"
+        )
diff --git a/dep_tools/grids.py b/dep_tools/grids.py
new file mode 100644
index 0000000..5229997
--- /dev/null
+++ b/dep_tools/grids.py
@@ -0,0 +1,91 @@
+from typing import Literal
+
+import antimeridian
+import geopandas as gpd
+from geopandas import GeoDataFrame, GeoSeries
+from odc.geo import XY, BoundingBox
+from odc.geo.gridspec import GridSpec
+from shapely.geometry import shape
+
+# This EPSG code is what we're using for now
+# but it's not ideal, as its not an equal area projection...
+PACIFIC_EPSG = "EPSG:3832"
+
+
+def grid(
+    resolution: int | float = 30,
+    crs=PACIFIC_EPSG,
+    return_type: Literal["GridSpec", "GeoSeries", "GeoDataFrame"] = "GridSpec",
+    intersect_with: GeoDataFrame | None = None,
+) -> GridSpec | GeoSeries | GeoDataFrame:
+    """Returns a GridSpec or GeoSeries representing the Pacific grid, optionally
+    intersected with an area of interest.
+
+    Args:
+        resolution: The resolution, in meters, of the output. As tiles are
+            defined to be 96,000 meters on each side, it should divide 96,000
+            evenly.
+        crs: The desired crs of the output.
+        return_type: The return type. If intersect_with (see below) is not None,
+            this is ignored.
+        intersect_with: The output is intersected with the supplied GeoDataFrame
+            before returning, returning only tiles which overlap with those
+            features. Forces the output to be a GeoDataFrame.
+    """
+
+    if intersect_with is not None:
+        full_grid = _geoseries(resolution, crs)
+        return _intersect_grid(full_grid, intersect_with)
+
+    return {
+        "GridSpec": _gridspec,
+        "GeoSeries": _geoseries,
+        "GeoDataFrame": _geodataframe,
+    }[return_type](resolution, crs)
+
+
+def _intersect_grid(grid: GeoSeries, areas_of_interest):
+    return gpd.sjoin(
+        gpd.GeoDataFrame(geometry=grid), areas_of_interest.to_crs(grid.crs)
+    ).drop(columns=["index_right"])
+
+
+def _gridspec(resolution, crs=PACIFIC_EPSG):
+    gridspec_origin = XY(-3000000.0, -4000000.0)
+
+    side_in_meters = 96_000
+    shape = (side_in_meters / resolution, side_in_meters / resolution)
+
+    return GridSpec(
+        crs=crs,
+        tile_shape=shape,
+        resolution=resolution,
+        origin=gridspec_origin,
+    )
+
+
+def _geodataframe(resolution, crs=PACIFIC_EPSG):
+    return GeoDataFrame(geometry=_geoseries(resolution, crs), crs=crs)
+
+
+def _geoseries(resolution, crs) -> GeoSeries:
+    bounds = BoundingBox(120, -30, 280, 30, crs="EPSG:4326").to_crs(crs)
+    tiles = _gridspec(resolution, crs).tiles(bounds)
+    geometry, index = zip(
+        *[(a_tile[1].boundingbox.polygon.geom, a_tile[0]) for a_tile in tiles]
+    )
+
+    gs = gpd.GeoSeries(geometry, index, crs=PACIFIC_EPSG)
+    if crs != PACIFIC_EPSG:
+        gs = gs.to_crs(crs)
+        if crs == 4326:
+            gs = gs.apply(lambda geom: shape(antimeridian.fix_shape(geom)))
+
+    return gs
+
+
+# The origin is in the projected CRS. This works for Landsat.
+PACIFIC_GRID_30 = grid()
+
+# This grid is for Sentinel-2 and has the same footprint
+PACIFIC_GRID_10 = grid(resolution=10)
diff --git a/dep_tools/loaders.py b/dep_tools/loaders.py
index e867416..e31b815 100644
--- a/dep_tools/loaders.py
+++ b/dep_tools/loaders.py
@@ -1,13 +1,14 @@
 from abc import ABC, abstractmethod
 
 from geopandas import GeoDataFrame
-import odc.stac
+from odc.geo.geobox import GeoBox
+from odc.geo.geom import Geometry
+from odc.stac import load as stac_load
 from rasterio.errors import RasterioError, RasterioIOError
+import rioxarray
 from stackstac import stack
 from xarray import DataArray, Dataset, concat
 
-from dep_tools.searchers import Searcher
-
 
 class Loader(ABC):
     """A loader loads data."""
@@ -26,15 +27,6 @@ def load(self, items, area):
         pass
 
 
-class SearchLoader(Loader):
-    def __init__(self, searcher: Searcher, loader: StacLoader):
-        self.searcher = searcher
-        self.loader = loader
-
-    def load(self, area):
-        return self.loader.load(self.searcher.search(area), area)
-
-
 class OdcLoader(StacLoader):
     def __init__(
         self,
@@ -47,41 +39,48 @@ def __init__(
         self._clip_to_area = clip_to_area
         self._load_as_dataset = load_as_dataset
 
-    def load(self, items, areas: GeoDataFrame) -> Dataset | DataArray:
+    def load(self, items, areas: GeoDataFrame | GeoBox) -> Dataset | DataArray:
         # If `nodata` is passed as an arg, or the stac item contains the nodata
         # value, xr[variable].nodata will be set on load.
-        xr = odc.stac.load(
+
+        load_geometry = (
+            dict(geopolygon=areas)
+            if isinstance(areas, GeoDataFrame)
+            else dict(geobox=areas)
+        )
+
+        ds = stac_load(
             items,
-            geopolygon=areas,
+            **load_geometry,
             **self._kwargs,
         )
 
-        # TODO: need to handle cases where nodata is _not_ set on load. (see
-        # landsat qr_radsat band)
-        for name in xr:
+        for name in ds:
             # Since nan is more-or-less universally accepted as a nodata value,
             # if the dtype of a band is some sort of floating point, then recode
             # existing values that are equal to the value set on load to nan
-            if xr[name].dtype.kind == "f":
+            if ds[name].dtype.kind == "f":
                 # Should I make this an option?
-                if "nodata" in xr[name].attrs.keys():
-                    xr[name] = xr[name].where(xr[name] != xr[name].nodata, float("nan"))
-                xr[name].attrs["nodata"] = float("nan")
-            # To be helpful, set the nodata so rioxarray can understand it too.
-            xr[name].rio.write_nodata(xr[name].nodata, inplace=True)
+                if "nodata" in ds[name].attrs.keys():
+                    ds[name] = ds[name].where(ds[name] != ds[name].nodata, float("nan"))
+                ds[name].attrs["nodata"] = float("nan")
+            # To be helpful, set the nodata for rioxarray accessor
+            ds[name].rio.write_nodata(ds[name].attrs.get("nodata"), inplace=True)
 
         if self._clip_to_area:
-            xr = xr.rio.clip(
-                areas.to_crs(xr.odc.crs).geometry, all_touched=True, from_disk=True
-            )
-            # Clip loses this, so re-set.
-            for name in xr:
-                xr[name].attrs["nodata"] = xr[name].rio.nodata
+            if isinstance(areas, GeoBox):
+                raise ValueError(
+                    "Clip not supported for GeoBox (nor should it be needed)"
+                )
+
+            geom = Geometry(areas.geometry.unary_union, crs=areas.crs)
+            ds = ds.odc.mask(geom)
 
         if not self._load_as_dataset:
-            xr = xr.to_array("band").rename("data").rio.write_crs(xr.odc.crs)
+            da = ds.to_array("band").rename("data").rio.write_crs(data.odc.crs)
+            return da
 
-        return xr
+        return ds
 
 
 class StackStacLoader(StacLoader):
diff --git a/dep_tools/namers.py b/dep_tools/namers.py
index b7bdaf4..2cc53c6 100644
--- a/dep_tools/namers.py
+++ b/dep_tools/namers.py
@@ -1,9 +1,6 @@
 from abc import ABC, abstractmethod
-from dataclasses import dataclass
 
 
-# Should probably be renamed to AssetPath at earliest opportunity
-# to avoid confusion with stac items
 class ItemPath(ABC):
     def __init__(self) -> None:
         pass
@@ -13,18 +10,29 @@ def path(self) -> str:
         return ""
 
 
-@dataclass
-class DepItemPath(ItemPath):
-    sensor: str
-    dataset_id: str
-    version: str
-    time: str
-    zero_pad_numbers: bool = False
-
-    def __post_init__(self):
+class GenericItemPath(ItemPath):
+    def __init__(
+        self,
+        sensor: str,
+        dataset_id: str,
+        version: str,
+        time: str,
+        prefix: str = "dep",
+        zero_pad_numbers: bool = False,
+    ):
+        self.sensor = sensor
+        self.dataset_id = dataset_id
+        self.version = version
+        self.time = time
+        self.prefix = prefix
+        self.zero_pad_numbers = zero_pad_numbers
         self.version = self.version.replace(".", "-")
-        self._folder_prefix = f"dep_{self.sensor}_{self.dataset_id}/{self.version}"
-        self.item_prefix = f"dep_{self.sensor}_{self.dataset_id.replace('/','_')}"
+        self._folder_prefix = (
+            f"{self.prefix}_{self.sensor}_{self.dataset_id}/{self.version}"
+        )
+        self.item_prefix = (
+            f"{self.prefix}_{self.sensor}_{self.dataset_id.replace('/','_')}"
+        )
 
     def _format_item_id(
         self, item_id: list[str | int] | tuple[str | int] | str, join_str="/"
@@ -65,10 +73,35 @@ def log_path(self) -> str:
         return f"{self._folder_prefix}/logs/{self.item_prefix}_{self.time}_log.csv"
 
 
+class DepItemPath(GenericItemPath):
+    pass
+
+
+class S3ItemPath(GenericItemPath):
+    def __init__(
+        self,
+        bucket: str,
+        sensor: str,
+        dataset_id: str,
+        version: str,
+        time: str,
+        prefix: str = "dep",
+        zero_pad_numbers: bool = False,
+    ):
+        super().__init__(
+            sensor=sensor,
+            dataset_id=dataset_id,
+            version=version,
+            time=time,
+            prefix=prefix,
+            zero_pad_numbers=zero_pad_numbers,
+        )
+        self.bucket = bucket
+
+
 class LocalPath(DepItemPath):
-    def __init__(self, local_folder: str, **kwargs):
-        # Need to create an abc for DepItemPath and drop this
+    def __init__(self, local_folder: str, prefix: str = "dep", **kwargs):
         super().__init__(**kwargs)
         self._folder_prefix = (
-            f"{local_folder}/dep_{self.sensor}_{self.dataset_id}/{self.version}"
+            f"{local_folder}/{prefix}_{self.sensor}_{self.dataset_id}/{self.version}"
         )
diff --git a/dep_tools/s2_utils.py b/dep_tools/s2_utils.py
index 2d38817..fcf1bef 100644
--- a/dep_tools/s2_utils.py
+++ b/dep_tools/s2_utils.py
@@ -27,10 +27,12 @@ def mask_clouds(
     for field in [CLOUD_SHADOWS, CLOUD_HIGH_PROBABILITY]:
         bitmask |= 1 << field
 
+    scl = "scl" if "scl" in xr else "SCL"
+
     try:
-        cloud_mask = xr.sel(band="SCL").astype("uint16") & bitmask != 0
+        cloud_mask = xr.sel(band=scl).astype("uint16") & bitmask != 0
     except KeyError:
-        cloud_mask = xr.SCL.astype("uint16") & bitmask != 0
+        cloud_mask = xr[scl].astype("uint16") & bitmask != 0
 
     if filters is not None:
         cloud_mask = mask_cleanup(cloud_mask, filters)
diff --git a/dep_tools/searchers.py b/dep_tools/searchers.py
index 9387e46..e6f00b5 100644
--- a/dep_tools/searchers.py
+++ b/dep_tools/searchers.py
@@ -1,17 +1,14 @@
-from abc import ABC, abstractmethod
 import warnings
+from abc import ABC, abstractmethod
 
 from geopandas import GeoDataFrame, read_file
+from odc.geo.geobox import GeoBox
 from pystac import ItemCollection
-import pystac_client
+from pystac_client import Client
 
 from dep_tools.exceptions import EmptyCollectionError
 from dep_tools.landsat_utils import items_in_pathrows, pathrows_in_area
-from dep_tools.utils import (
-    fix_bad_epsgs,
-    remove_bad_items,
-    search_across_180,
-)
+from dep_tools.utils import fix_bad_epsgs, remove_bad_items, search_across_180
 
 
 class Searcher(ABC):
@@ -47,15 +44,15 @@ class PystacSearcher(Searcher):
 
     def __init__(
         self,
-        client: pystac_client.Client | None = None,
+        catalog: str,
         raise_empty_collection_error: bool = True,
         **kwargs,
     ):
-        self._client = client
+        self._client = Client.open(catalog)
         self._raise_errors = raise_empty_collection_error
         self._kwargs = kwargs
 
-    def search(self, area: GeoDataFrame) -> ItemCollection:
+    def search(self, area: GeoDataFrame | GeoBox) -> ItemCollection:
         """Search for stac items within the bounds of the corresponding area.
 
         Args:
@@ -102,20 +99,21 @@ class LandsatPystacSearcher(PystacSearcher):
 
     def __init__(
         self,
-        client: pystac_client.Client | None = None,
+        catalog: str = "https://planetarycomputer.microsoft.com/api/stac/v1/",
+        collections: list[str] | None = ["landsat-c2-l2"],
         raise_empty_collection_error: bool = True,
         search_intersecting_pathrows: bool = False,
-        exclude_platforms: list | None = None,
+        exclude_platforms: list[str] | None = None,
         only_tier_one: bool = False,
         fall_back_to_tier_two: bool = False,
         **kwargs,
     ):
         super().__init__(
-            client=client,
+            catalog=catalog,
             raise_empty_collection_error=raise_empty_collection_error,
             **kwargs,
         )
-        self._kwargs["collections"] = ["landsat-c2-l2"]
+        self._kwargs["collections"] = collections
         self._search_intersecting_pathrows = search_intersecting_pathrows
         self._exclude_platforms = exclude_platforms
         self._only_tier_one = only_tier_one
@@ -125,10 +123,12 @@ def __init__(
         # we might look to combine.
         if "query" in self._kwargs.keys():
             warnings.warn(
-                "`query` argument being ignored. To send a query directly, use `PystacSearcher`."
+                "Portions of `query` argument may be replaced. To specify the full query directly, use `PystacSearcher`."
             )
+            query = kwargs.pop("query")
+        else:
+            query = {}
 
-        query = {}
         if self._exclude_platforms is not None:
             landsat_platforms = ["landsat-5", "landsat-7", "landsat-8", "landsat-9"]
             query["platform"] = {
diff --git a/dep_tools/stac_utils.py b/dep_tools/stac_utils.py
index 2175813..7e343a7 100644
--- a/dep_tools/stac_utils.py
+++ b/dep_tools/stac_utils.py
@@ -1,67 +1,102 @@
-import datetime
+from datetime import datetime
 import json
+from pathlib import Path
 
 import numpy as np
-from pystac import Item
+from pandas import DataFrame
+from pystac import Asset, Item, MediaType
 from rio_stac.stac import create_stac_item
 from urlpath import URL
 from xarray import DataArray, Dataset
 
-from azure.storage.blob import ContentSettings
 
-from .utils import write_to_blob_storage, write_to_local_storage
+from .aws import object_exists
+from .namers import DepItemPath, S3ItemPath
+from .processors import Processor
 
 
-def write_stac(
-    xr: DataArray | Dataset,
-    path: str,
-    stac_url,
-    writer=write_to_blob_storage,
-    **kwargs,
-) -> None:
-    item = _get_stac_item(xr, path, **kwargs)
-    item_json = json.dumps(item.to_dict(), indent=4)
-    writer(
-        item_json,
-        stac_url,
-        content_settings=ContentSettings(content_type="application/json"),
-    )
-
-    return stac_url
-
-
-def write_stac_local(xr: DataArray | Dataset, path: str, stac_url, **kwargs):
-    write_stac(
-        xr, path, stac_url, writer=write_to_local_storage, remote=False, **kwargs
-    )
-
-
-write_stac_blob_storage = write_stac
+class StacCreator(Processor):
+    def __init__(
+        self,
+        itempath: DepItemPath,
+        remote: bool = True,
+        collection_url_root: str = "https://stac.staging.digitalearthpacific.org/collections",
+        **kwargs,
+    ):
+        self._itempath = itempath
+        self._remote = remote
+        self._collection_url_root = collection_url_root
+        self._kwargs = kwargs
+
+    def process(
+        self,
+        data: DataArray | Dataset,
+        item_id: str,
+    ) -> Item | str:
+        return get_stac_item(
+            itempath=self._itempath,
+            item_id=item_id,
+            data=data,
+            remote=self._remote,
+            collection_url_root=self._collection_url_root,
+            **self._kwargs,
+        )
 
 
-def _get_stac_item(
-    xr: DataArray | Dataset,
-    path: str,
-    collection: str,
+def get_stac_item(
+    itempath: DepItemPath,
+    item_id: str,
+    data: DataArray | Dataset,
     remote: bool = True,
+    collection_url_root: str = "https://stac.staging.digitalearthpacific.org/collections",
     **kwargs,
-) -> Item:
-    az_prefix = URL("https://deppcpublicstorage.blob.core.windows.net/output")
-    blob_url = az_prefix / path if remote else path
+) -> Item | str:
+    prefix = Path("./")
+    # Remote means not local
+    # TODO: neaten local file writing up
+    if remote:
+        # Or, isinstance(itempath, S3ItemPath)
+        if hasattr(itempath, "bucket"):
+            # Writing to S3
+            prefix = URL(f"s3://{getattr(itempath,'bucket')}")
+        else:
+            # Default to Azure
+            prefix = URL("https://deppcpublicstorage.blob.core.windows.net/output")
+
     properties = {}
-    if "stac_properties" in xr.attrs:
+    if "stac_properties" in data.attrs:
         properties = (
-            json.loads(xr.attrs["stac_properties"].replace("'", '"'))
-            if isinstance(xr.attrs["stac_properties"], str)
-            else xr.attrs["stac_properties"]
+            json.loads(data.attrs["stac_properties"].replace("'", '"'))
+            if isinstance(data.attrs["stac_properties"], str)
+            else data.attrs["stac_properties"]
         )
 
-    collection_url = (
-        f"https://stac.staging.digitalearthpacific.org/collections/{collection}"
-    )
-    return create_stac_item(
-        str(blob_url),
-        asset_roles=["data"],
+    paths = [itempath.path(item_id, variable) for variable in data]
+
+    assets = {
+        variable: Asset(
+            media_type=MediaType.COG,
+            href=str(prefix / path),
+            roles=["data"],
+        )
+        for variable, path in zip(data, paths)
+    }
+    stac_id = itempath.basename(item_id)
+    collection = itempath.item_prefix
+    collection_url = f"{collection_url_root}/{collection}"
+
+    input_datetime = properties.get("datetime", None)
+    if input_datetime is not None:
+        format_string = (
+            "%Y-%m-%dT%H:%M:%S.%fZ" if "." in input_datetime else "%Y-%m-%dT%H:%M:%SZ"
+        )
+        input_datetime = datetime.strptime(input_datetime, format_string)
+
+    item = create_stac_item(
+        str(prefix / paths[0]),
+        id=stac_id,
+        input_datetime=input_datetime,
+        assets=assets,
         with_proj=True,
         properties=properties,
         collection_url=collection_url,
@@ -69,6 +104,32 @@ def _get_stac_item(
         **kwargs,
     )
 
+    stac_url = str(prefix / itempath.stac_path(item_id))
+    item.set_self_href(stac_url)
+
+    return item
+
+
+def write_stac_local(item: Item, stac_path: str) -> None:
+    with open(stac_path, "w") as f:
+        json.dump(item.to_dict(), f, indent=4)
+
+
+def existing_stac_items(possible_ids: list, itempath: S3ItemPath) -> list:
+    """Returns only those ids which have an existing stac item."""
+    return [
+        id
+        for id in possible_ids
+        if object_exists(itempath.bucket, itempath.stac_path(id))
+    ]
+
+
+def remove_items_with_existing_stac(grid: DataFrame, itempath: S3ItemPath) -> DataFrame:
+    """Filter a dataframe to only include items which don't have an existing stac output.
+    The dataframe must have an index which corresponds to ids for the given itempath.
+    """
+    return grid[~grid.index.isin(existing_stac_items(list(grid.index), itempath))]
+
 
 def set_stac_properties(
     input_xr: DataArray | Dataset, output_xr: DataArray | Dataset
@@ -94,9 +155,7 @@ def set_stac_properties(
         start_datetime=start_datetime,
         datetime=start_datetime,
         end_datetime=end_datetime,
-        created=np.datetime_as_string(
-            np.datetime64(datetime.datetime.now()), timezone="UTC"
-        ),
+        created=np.datetime_as_string(np.datetime64(datetime.now()), timezone="UTC"),
     )
 
     return output_xr
diff --git a/dep_tools/task.py b/dep_tools/task.py
index 5b437fe..e075a6f 100644
--- a/dep_tools/task.py
+++ b/dep_tools/task.py
@@ -4,17 +4,20 @@
 from geopandas import GeoDataFrame
 
 from .exceptions import EmptyCollectionError, NoOutputError
-from .loaders import Loader
-from .processors import Processor
-from .writers import Writer
+from .loaders import Loader, StacLoader
+from .processors import Processor, XrPostProcessor
+from .namers import S3ItemPath
+from .searchers import Searcher
+from .stac_utils import set_stac_properties, StacCreator
+from .writers import Writer, AwsDsCogWriter, AwsStacWriter
 
-task_id = str
+TaskID = str
 
 
 class Task(ABC):
     def __init__(
         self,
-        task_id: task_id,
+        task_id: TaskID,
         loader: Loader,
         processor: Processor,
         writer: Writer,
@@ -34,7 +37,7 @@ def run(self):
 class AreaTask(Task):
     def __init__(
         self,
-        id: task_id,
+        id: TaskID,
         area: GeoDataFrame,
         loader: Loader,
         processor: Processor,
@@ -55,16 +58,100 @@ def run(self):
         return paths
 
 
+class StacTask(AreaTask):
+    def __init__(
+        self,
+        id: TaskID,
+        area: GeoDataFrame,
+        searcher: Searcher,
+        loader: StacLoader,
+        processor: Processor,
+        writer: Writer,
+        post_processor: Processor | None = None,
+        stac_creator: StacCreator | None = None,
+        stac_writer: Writer | None = None,
+        logger: Logger = getLogger(),
+    ):
+        """Implementation of a typical DEP product pipeline as a series of
+        generic operations. For a defined location (identified by an id and
+        a spatial region), search for and then load appropriate input data,
+        process that data to create an output, optionally post-process that
+        output to prep for writing, then write. Also allows for
+        optional creation and writing of a stac item document.
+        """
+        super().__init__(id, area, loader, processor, writer, logger)
+        self.id = id
+        self.searcher = searcher
+        self.post_processor = post_processor
+        self.stac_creator = stac_creator
+        self.stac_writer = stac_writer
+
+    def run(self):
+        items = self.searcher.search(self.area)
+        input_data = self.loader.load(items, self.area)
+
+        processor_kwargs = (
+            dict(area=self.area) if self.processor.send_area_to_processor else dict()
+        )
+
+        output_data = set_stac_properties(
+            input_data, self.processor.process(input_data, **processor_kwargs)
+        )
+
+        if self.post_processor is not None:
+            output_data = self.post_processor.process(output_data)
+
+        paths = self.writer.write(output_data, self.id)
+
+        if self.stac_creator is not None and self.stac_writer is not None:
+            stac_item = self.stac_creator.process(output_data, self.id)
+            self.stac_writer.write(stac_item, self.id)
+
+        return paths
+
+
+class AwsStacTask(StacTask):
+    def __init__(
+        self,
+        itempath: S3ItemPath,
+        id: TaskID,
+        area,
+        searcher: Searcher,
+        loader: StacLoader,
+        processor: Processor,
+        post_processor: Processor | None = XrPostProcessor(),
+        logger: Logger = getLogger(),
+        **kwargs,
+    ):
+        """A StacTask with typical parameters to write to s3 storage."""
+        writer = kwargs.pop("writer", AwsDsCogWriter(itempath))
+        stac_creator = kwargs.pop("stac_creator", StacCreator(itempath))
+        stac_writer = kwargs.pop("stac_writer", AwsStacWriter(itempath))
+        super().__init__(
+            id=id,
+            area=area,
+            searcher=searcher,
+            loader=loader,
+            processor=processor,
+            post_processor=post_processor,
+            writer=writer,
+            stac_creator=stac_creator,
+            stac_writer=stac_writer,
+            logger=logger,
+            **kwargs,
+        )
+
+
 class ErrorCategoryAreaTask(AreaTask):
     def run(self):
         try:
             input_data = self.loader.load(self.area)
         except EmptyCollectionError as e:
-            self.logger.info([self.id, "no items for areas"])
+            self.logger.error([self.id, "no items for areas"])
             raise e
 
         except Exception as e:
-            self.logger.info([self.id, "load error", e])
+            self.logger.error([self.id, "load error", e])
             raise e
 
         processor_kwargs = (
@@ -73,11 +160,11 @@ def run(self):
         try:
             output_data = self.processor.process(input_data, **processor_kwargs)
         except Exception as e:
-            self.logger.info([self.id, "processor error", e])
+            self.logger.error([self.id, "processor error", e])
             raise e
 
         if output_data is None:
-            self.logger.info([self.id, "no output from processor"])
+            self.logger.error([self.id, "no output from processor"])
             raise NoOutputError()
         try:
             paths = self.writer.write(output_data, self.id)
@@ -90,41 +177,32 @@ def run(self):
         return paths
 
 
-class MultiAreaTask(ABC):
+class MultiAreaTask:
     def __init__(
         self,
-        ids: list[task_id],
+        ids: list[TaskID],
         areas: GeoDataFrame,
+        logger,
         task_class: type[AreaTask],
-        loader: Loader,
-        processor: Processor,
-        writer: Writer,
-        logger: Logger = getLogger(),
         fail_on_error: bool = True,
+        **kwargs,
     ):
         self.ids = ids
         self.areas = areas
-        self.loader = loader
-        self.processor = processor
-        self.writer = writer
-        self.logger = logger
         self.task_class = task_class
         self.fail_on_error = fail_on_error
+        self.logger = logger
+        self._kwargs = kwargs
 
     def run(self):
         for id in self.ids:
             try:
-                self.task_class(
-                    id,
-                    self.areas.loc[[id]],
-                    self.loader,
-                    self.processor,
-                    self.writer,
-                    self.logger,
-                ).run()
+                paths = self.task_class(id, self.areas.loc[[id]], **self._kwargs).run()
+                self.logger.info([id, "complete", paths])
             except Exception as e:
                 if self.fail_on_error:
                     raise e
+                self.logger.error([id, "error", [], e])
                 continue
 
 
diff --git a/dep_tools/utils.py b/dep_tools/utils.py
index 75374c6..cb7e70b 100644
--- a/dep_tools/utils.py
+++ b/dep_tools/utils.py
@@ -1,31 +1,46 @@
-import io
+from logging import INFO, Formatter, Logger, StreamHandler, getLogger
 from pathlib import Path
 from typing import Dict, List, Union
 
-import fiona
+from antimeridian import bbox as antimeridian_bbox
+from antimeridian import (
+    fix_multi_polygon,
+    fix_polygon,
+    fix_line_string,
+    fix_multi_line_string,
+)
+from geopandas import GeoDataFrame
 import numpy as np
+from odc.geo.geobox import GeoBox as GeoBox
+from odc.geo.xr import write_cog
 import planetary_computer
-import pystac_client
-import rasterio
-import rioxarray
-import xarray as xr
-from azure.storage.blob import ContainerClient
-from dask.distributed import Client, Lock
-from geocube.api.core import make_geocube
-from geopandas import GeoDataFrame
-from odc.geo.xr import to_cog, write_cog
-from osgeo import gdal
 from pystac import ItemCollection
+import pystac_client
 from retry import retry
-from shapely.geometry import LineString, MultiLineString
+from shapely.geometry import LineString, MultiLineString, GeometryCollection
 from xarray import DataArray, Dataset
 
-from .azure import get_container_client
-
 # Set the timeout to five minutes, which is an extremely long time
 TIMEOUT_SECONDS = 60 * 5
 
 
+def get_logger(prefix: str, name: str) -> Logger:
+    """Set up a simple logger"""
+    console = StreamHandler()
+    time_format = "%Y-%m-%d %H:%M:%S"
+    console.setFormatter(
+        Formatter(
+            fmt=f"%(asctime)s %(levelname)s ({prefix}):  %(message)s",
+            datefmt=time_format,
+        )
+    )
+
+    log = getLogger(name)
+    log.addHandler(console)
+    log.setLevel(INFO)
+    return log
+
+
 def shift_negative_longitudes(
     geometry: Union[LineString, MultiLineString]
 ) -> Union[LineString, MultiLineString]:
@@ -49,28 +64,21 @@ def shift_negative_longitudes(
 BBOX = list[float]
 
 
-def bbox_across_180(region: GeoDataFrame) -> BBOX | tuple[BBOX, BBOX]:
-    # Previously we just used region.to_crs(4326).total_bounds but if the geom
-    # is split right at the antimeridian (see landsat pathrow 073072), output
-    # will have zero width (since min and max will be -180 and 180)
-    # So get the bounds for all geoms in region, remove the 180s and calculate
-    # the min and max values ourselves
-    region_ll = GeoDataFrame(region.to_crs(4326))
-    x_values = (
-        region_ll.explode(index_parts=True).bounds.minx.tolist()
-        + region_ll.explode(index_parts=True).bounds.maxx.tolist()
-    )
-    # Possible we just do a direct compare, we shall see if this causes issues
-    # with locations _really close_ to 180 but not touching it
-    tolerance = 1e-5
-    x_values = [i for i in x_values if abs(180 - abs(i)) > tolerance]
-
-    y_values = (
-        region_ll.explode(index_parts=True).bounds.miny.tolist()
-        + region_ll.explode(index_parts=True).bounds.maxy.tolist()
-    )
-
-    bbox = [min(x_values), min(y_values), max(x_values), max(y_values)]
+def bbox_across_180(region: GeoDataFrame | GeoBox) -> BBOX | tuple[BBOX, BBOX]:
+    if isinstance(region, GeoBox):
+        geometry = region.geographic_extent.geom
+    else:
+        geometry = region.to_crs(4326).geometry.make_valid().explode()
+        geometry = geometry[
+            geometry.geom_type.isin(["Polygon", "MultiPolygon"])
+        ].unary_union
+
+    geometry = _fix_geometry(geometry)
+    bbox = antimeridian_bbox(geometry)
+    # Sometimes they still come through with the negative value first, see
+    # https://github.com/gadomski/antimeridian/issues/134
+    if bbox[0] < 0 and bbox[2] > 0:
+        bbox[0], bbox[2] = bbox[2], bbox[0]
 
     # Now fix some coord issues
     # If the lower left X coordinate is greater than 180 it needs to shift
@@ -81,28 +89,48 @@ def bbox_across_180(region: GeoDataFrame) -> BBOX | tuple[BBOX, BBOX]:
         if bbox[2] > 180:
             bbox[2] = bbox[2] - 360
 
-    # These are Pacific specific tests!
-    bbox_crosses_antimeridian = (bbox[0] < 0 and bbox[2] > 0) or (
+    # These are Pacific specific tests, meaning e.g. we know that these aren't
+    # areas that are crossing 0 longitude.
+    bbox_crosses_antimeridian = (bbox[0] > 0 and bbox[2] < 0) or (
         bbox[0] < 180 and bbox[2] > 180
     )
+
     if bbox_crosses_antimeridian:
         # Split into two bboxes across the antimeridian
-        xmax_ll, ymin_ll = bbox[0], bbox[1]
-        xmin_ll, ymax_ll = bbox[2], bbox[3]
+        xmin, ymin = bbox[0], bbox[1]
+        xmax, ymax = bbox[2], bbox[3]
 
-        xmax_ll = xmax_ll - 360 if xmax_ll > 180 else xmax_ll
-
-        left_bbox = BBOX([xmin_ll, ymin_ll, 180, ymax_ll])
-        right_bbox = BBOX([-180, ymin_ll, xmax_ll, ymax_ll])
+        xmax = xmax - 360 if xmax > 180 else xmax
+        left_bbox = BBOX([xmin, ymin, 180, ymax])
+        right_bbox = BBOX([-180, ymin, xmax, ymax])
         return (left_bbox, right_bbox)
     else:
         return BBOX(bbox)
 
 
+def _fix_geometry(geometry):
+    if isinstance(geometry, GeometryCollection):
+        return GeometryCollection(
+            [_fix_geometry(a_geometry) for a_geometry in geometry.geoms]
+        )
+    match geometry.geom_type:
+        case "Polygon":
+            geometry = fix_polygon(geometry)
+        case "MultiPolygon":
+            geometry = fix_multi_polygon(geometry)
+        case "LineString":
+            geometry = fix_line_string(geometry)
+        case "MultiLineString":
+            geometry = fix_multi_line_string(geometry)
+        case _:
+            raise ValueError(f"Unsupported geometry type: {geometry.type}")
+    return geometry
+
+
 # retry is for search timeouts which occasionally occur
 @retry(tries=5, delay=1)
 def search_across_180(
-    region: GeoDataFrame, client: pystac_client.Client | None = None, **kwargs
+    region: GeoDataFrame | GeoBox, client: pystac_client.Client | None = None, **kwargs
 ) -> ItemCollection:
     """
     region: A GeoDataFrame.
@@ -118,10 +146,15 @@ def search_across_180(
     bbox = bbox_across_180(region)
 
     if isinstance(bbox, tuple):
-        return ItemCollection(
-            list(client.search(bbox=bbox[0], **kwargs).items())
-            + list(client.search(bbox=bbox[1], **kwargs).items())
-        )
+        first_result = list(client.search(bbox=bbox[0], **kwargs).items())
+        first_ids = [item.id for item in first_result]
+
+        second_result = list(client.search(bbox=bbox[1], **kwargs).items())
+        unique_second_result = [
+            item for item in second_result if item.id not in first_ids
+        ]
+
+        return ItemCollection(first_result + unique_second_result)
     else:
         return client.search(bbox=bbox, **kwargs).item_collection()
 
@@ -187,55 +220,6 @@ def write_to_local_storage(
         )
 
 
-def write_to_blob_storage(
-    d: Union[DataArray, Dataset, GeoDataFrame, str],
-    path: Union[str, Path],
-    overwrite: bool = True,
-    use_odc_writer: bool = False,
-    client: ContainerClient | None = None,
-    **kwargs,
-) -> None:
-    # Allowing for a shared container client, which might be
-    # more efficient. If not provided, get one.
-    if client is None:
-        client = get_container_client()
-    blob_client = client.get_blob_client(str(path))
-    if not overwrite and blob_client.exists():
-        return
-
-    if isinstance(d, (DataArray, Dataset)):
-        if use_odc_writer:
-            if "driver" in kwargs:
-                del kwargs["driver"]
-            binary_data = to_cog(d, **kwargs)
-            blob_client.upload_blob(
-                binary_data, overwrite=overwrite, connection_timeout=TIMEOUT_SECONDS
-            )
-        else:
-            with io.BytesIO() as buffer:
-                # This is needed or rioxarray doesn't know what type it is
-                # writing
-                if not "driver" in kwargs:
-                    kwargs["driver"] = "COG"
-                d.rio.to_raster(buffer, **kwargs)
-                buffer.seek(0)
-                blob_client.upload_blob(
-                    buffer, overwrite=overwrite, connection_timeout=TIMEOUT_SECONDS
-                )
-
-    elif isinstance(d, GeoDataFrame):
-        with fiona.io.MemoryFile() as buffer:
-            d.to_file(buffer, **kwargs)
-            buffer.seek(0)
-            blob_client.upload_blob(buffer, overwrite=overwrite)
-    elif isinstance(d, str):
-        blob_client.upload_blob(d, overwrite=overwrite, **kwargs)
-    else:
-        raise ValueError(
-            "You can only write an Xarray DataArray or Dataset, or Geopandas GeoDataFrame"
-        )
-
-
 def scale_to_int16(
     xr: Union[DataArray, Dataset],
     output_multiplier: int,
@@ -254,93 +238,33 @@ def scale_da(da: DataArray):
         return (
             da.where(da.notnull(), output_nodata)
             .astype("int16")
-            .rio.write_nodata(output_nodata)
+            .rio.write_nodata(output_nodata)  # for rioxarray
+            .assign_attrs(nodata=output_nodata)  # for odc
         )
 
     if isinstance(xr, Dataset):
         for var in xr:
             xr[var] = scale_da(xr[var])
-            xr[var].rio.write_nodata(output_nodata, inplace=True)
+            # Assuming this needs to be redone?
+            xr[var].rio.write_nodata(output_nodata, inplace=True).assign_attrs(
+                nodata=output_nodata
+            )
     else:
         xr = scale_da(xr)
 
     return xr
 
 
-def raster_bounds(raster_path: Path) -> List:
-    """Returns the bounds for a raster file at the given path"""
-    with rasterio.open(raster_path) as t:
-        return list(t.bounds)
-
-
-def gpdf_bounds(gpdf: GeoDataFrame) -> List[float]:
-    """Returns the bounds for the give GeoDataFrame, and makes sure
-    it doesn't cross the antimeridian."""
-    bbox = gpdf.to_crs("EPSG:4326").total_bounds
-    # Or the opposite!
-    bbox_crosses_antimeridian = bbox[0] < 0 and bbox[2] > 0
-    if bbox_crosses_antimeridian:
-        # This may be overkill, but nothing else was really working
-        bbox[0] = -179.9999999999
-        bbox[2] = 179.9999999999
-    return bbox
-
-
-def build_vrt(
-    bounds: List,
-    prefix: str = "",
-    suffix: str = "",
-) -> Path:
-    blobs = [
-        f"/vsiaz/output/{blob.name}"
-        for blob in get_container_client().list_blobs(name_starts_with=prefix)
-        if blob.name.endswith(suffix)
-    ]
-
-    local_prefix = Path(prefix).stem
-    vrt_file = f"data/{local_prefix}.vrt"
-    gdal.BuildVRT(vrt_file, blobs, outputBounds=bounds)
-    return Path(vrt_file)
-
-
-def _local_prefix(prefix: str) -> str:
-    return Path(prefix).stem
-
-
-def _mosaic_file(prefix: str) -> str:
-    return f"data/{_local_prefix(prefix)}.tif"
-
-
-def mosaic_scenes(
-    prefix: str,
-    bounds: List,
-    client: Client,
-    scale_factor: float = None,
-    overwrite: bool = True,
-) -> None:
-    mosaic_file = _mosaic_file(prefix)
-    if not Path(mosaic_file).is_file() or overwrite:
-        vrt_file = build_vrt(prefix, bounds)
-        rioxarray.open_rasterio(vrt_file, chunks=True).rio.to_raster(
-            mosaic_file,
-            compress="LZW",
-            lock=Lock("rio", client=client),
-        )
-
-        if scale_factor is not None:
-            with rasterio.open(mosaic_file, "r+") as dst:
-                dst.scales = (scale_factor,)
-
-
 def fix_bad_epsgs(item_collection: ItemCollection) -> None:
-    """Repairs soLC08_L2SP_101055_20220612_20220617_02_T2me band epsg codes in stac items loaded from the Planetary
+    """Repairs some band epsg codes in stac items loaded from the Planetary
     Computer stac catalog"""
     # ** modifies in place **
     # See https://github.com/microsoft/PlanetaryComputer/discussions/113
     # Will get fixed at some point and we can remove this
     for item in item_collection:
-        epsg = str(item.properties["proj:epsg"])
-        item.properties["proj:epsg"] = int(f"{epsg[0:3]}{int(epsg[3:]):02d}")
+        if item.collection_id == "landsat-c2-l2":
+            epsg = str(item.properties["proj:epsg"])
+            item.properties["proj:epsg"] = int(f"{epsg[0:3]}{int(epsg[3:]):02d}")
 
 
 def remove_bad_items(item_collection: ItemCollection) -> ItemCollection:
diff --git a/dep_tools/writers.py b/dep_tools/writers.py
index ccb6380..de946be 100644
--- a/dep_tools/writers.py
+++ b/dep_tools/writers.py
@@ -3,134 +3,29 @@
 from functools import partial
 from typing import Callable, Hashable, List
 
-import numpy as np
-from pystac import Asset
-from urlpath import URL
 from xarray import Dataset
 
-from .azure import blob_exists
-from .namers import DepItemPath
-from .processors import Processor, XrPostProcessor
-from .stac_utils import write_stac_blob_storage, write_stac_local
-from .utils import write_to_blob_storage, write_to_local_storage
+from .aws import write_to_s3, write_stac_s3
+from .namers import DepItemPath, S3ItemPath
+from .utils import write_to_local_storage
 
 
 class Writer(ABC):
+    """The base abstract class for writing."""
+
     @abstractmethod
-    def write(self, data, item_id) -> str:
+    def write(self, data, item_id) -> str | list[str]:
         pass
 
 
-class DepWriter(Writer):
-    def __init__(
-        self,
-        itempath: DepItemPath,
-        pre_processor: Processor,
-        cog_writer: Writer,
-        stac_writer: Writer | None,
-    ):
-        self._itempath = itempath
-        self._pre_processor = pre_processor
-        self._cog_writer = cog_writer
-        self._stac_writer = stac_writer
-
-    def _stac_exists(self, item_id):
-        return blob_exists(self._itempath.stac_path(item_id))
-
-    def _all_paths(self, ds: Dataset, item_id: str):
-        # Only problem here is if xr has variables that aren't in the stac
-        # so maybe we need to read stac?
-        paths = [self._itempath.path(item_id, variable) for variable in ds]
-        paths.append(self._itempath.stac_path(item_id))
-        return paths
-
-    def write(self, xr, item_id):
-        if self._stac_exists(item_id):
-            return self._all_paths(xr, item_id)
-        output = self._pre_processor.process(xr)
-        self._cog_writer.write(output, item_id)
-        if self._stac_writer is not None:
-            self._stac_writer.write(output, item_id)
-
-
-class DsWriter(DepWriter):
-    def __init__(
-        self,
-        itempath: DepItemPath,
-        convert_to_int16: bool = True,
-        output_value_multiplier: int = 10000,
-        scale_int16s: bool = False,
-        output_nodata: int = -32767,
-        extra_attrs: dict = {},
-        write_function: Callable = write_to_blob_storage,
-        write_multithreaded: bool = True,
-        write_stac: bool = True,
-        write_stac_function=write_stac_blob_storage,
-        load_before_write: bool = False,
-        **kwargs
-    ):
-        pre_processor = XrPostProcessor(
-            convert_to_int16,
-            output_value_multiplier,
-            scale_int16s,
-            output_nodata,
-            extra_attrs,
-        )
-        cog_writer = DsCogWriter(
-            itempath, write_multithreaded, load_before_write, write_function, **kwargs
-        )
-        stac_writer = StacWriter(itempath, write_stac_function) if write_stac else None
-        super().__init__(itempath, pre_processor, cog_writer, stac_writer)
-
-
-class StacWriter(Writer):
-    def __init__(
-        self,
-        itempath: DepItemPath,
-        write_stac_function: Callable = write_stac_blob_storage,
-    ):
-        self._itempath = itempath
-        self._write_stac_function = write_stac_function
-
-    def write(self, ds: Dataset, item_id):
-        paths = [self._itempath.path(item_id, variable) for variable in ds]
-        assets = {
-            variable: Asset(
-                media_type="image/tiff; application=geotiff; profile=cloud-optimized",
-                href=str(
-                    URL("https://deppcpublicstorage.blob.core.windows.net/output")
-                    / path
-                ),
-                roles=["data"],
-            )
-            for variable, path in zip(ds, paths)
-        }
-        stac_id = self._itempath.basename(item_id)
-        collection = self._itempath.item_prefix
-        # has to be a datetime datetime object
-        datetime = np.datetime64(ds.attrs["stac_properties"]["datetime"]).item()
-        stac_path = self._write_stac_function(
-            ds,
-            paths[0],
-            stac_url=self._itempath.path(item_id, ext=".stac-item.json"),
-            input_datetime=datetime,
-            assets=assets,
-            collection=collection,
-            id=stac_id,
-        )
-        paths.append(stac_path)
-
-        return paths
-
-
 class DsCogWriter(Writer):
     def __init__(
         self,
         itempath: DepItemPath,
         write_multithreaded: bool = False,
         load_before_write: bool = False,
-        write_function: Callable = write_to_blob_storage,
-        **kwargs
+        write_function: Callable = write_to_s3,
+        **kwargs,
     ):
         self._itempath = itempath
         self._write_multithreaded = write_multithreaded
@@ -169,14 +64,73 @@ def get_write_partial(variable: Hashable) -> Callable:
         return paths
 
 
-class LocalDsCogWriter(DsWriter):
+class AwsDsCogWriter(DsCogWriter):
+    def __init__(
+        self,
+        itempath: S3ItemPath,
+        write_multithreaded: bool = False,
+        load_before_write: bool = False,
+        write_function: Callable = write_to_s3,
+        **kwargs,
+    ):
+        super().__init__(
+            itempath=itempath,
+            write_multithreaded=write_multithreaded,
+            load_before_write=load_before_write,
+            write_function=write_function,
+            bucket=itempath.bucket,
+            **kwargs,
+        )
+
+
+class LocalDsCogWriter(DsCogWriter):
     def __init__(self, **kwargs):
         super().__init__(
             write_function=write_to_local_storage,
-            write_stac_function=write_stac_local,
             **kwargs,
         )
 
 
-class AzureDsWriter(DsWriter):
-    pass
+class StacWriter(Writer):
+    def __init__(
+        self,
+        itempath: DepItemPath,
+        write_stac_function: Callable = write_stac_s3,
+        **kwargs,
+    ):
+        self._itempath = itempath
+        self._write_stac_function = write_stac_function
+        self._kwargs = kwargs
+
+    def write(self, item, item_id) -> str:
+        stac_path = self._itempath.stac_path(item_id)
+        self._write_stac_function(item, stac_path, **self._kwargs)
+
+        return item.self_href
+
+
+class AwsStacWriter(StacWriter):
+    def __init__(
+        self,
+        itempath: S3ItemPath,
+        **kwargs,
+    ):
+        super().__init__(
+            itempath=itempath,
+            write_stac_function=write_to_s3,
+            bucket=itempath.bucket,
+            **kwargs,
+        )
+
+
+class LocalStacWriter(StacWriter):
+    def __init__(
+        self,
+        itempath: S3ItemPath,
+        **kwargs,
+    ):
+        super().__init__(
+            itempath=itempath,
+            write_stac_function=write_to_local_storage,
+            **kwargs,
+        )
diff --git a/poetry.lock b/poetry.lock
deleted file mode 100644
index 8c668a9..0000000
--- a/poetry.lock
+++ /dev/null
@@ -1,4036 +0,0 @@
-# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
-
-[[package]]
-name = "affine"
-version = "2.4.0"
-description = "Matrices describing affine transformation of the plane"
-optional = false
-python-versions = ">=3.7"
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-    {file = "affine-2.4.0.tar.gz", hash = "sha256:a24d818d6a836c131976d22f8c27b8d3ca32d0af64c1d8d29deb7bafa4da1eea"},
-]
-
-[package.extras]
-dev = ["coveralls", "flake8", "pydocstyle"]
-test = ["pytest (>=4.6)", "pytest-cov"]
-
-[[package]]
-name = "aiohttp"
-version = "3.9.1"
-description = "Async http client/server framework (asyncio)"
-optional = false
-python-versions = ">=3.8"
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-]
-
-[package.dependencies]
-idna = ">=2.0"
-multidict = ">=4.0"
-
-[[package]]
-name = "zict"
-version = "3.0.0"
-description = "Mutable mapping tools"
-optional = false
-python-versions = ">=3.8"
-files = [
-    {file = "zict-3.0.0-py2.py3-none-any.whl", hash = "sha256:5796e36bd0e0cc8cf0fbc1ace6a68912611c1dbd74750a3f3026b9b9d6a327ae"},
-    {file = "zict-3.0.0.tar.gz", hash = "sha256:e321e263b6a97aafc0790c3cfb3c04656b7066e6738c37fffcca95d803c9fba5"},
-]
-
-[[package]]
-name = "zipp"
-version = "3.17.0"
-description = "Backport of pathlib-compatible object wrapper for zip files"
-optional = false
-python-versions = ">=3.8"
-files = [
-    {file = "zipp-3.17.0-py3-none-any.whl", hash = "sha256:0e923e726174922dce09c53c59ad483ff7bbb8e572e00c7f7c46b88556409f31"},
-    {file = "zipp-3.17.0.tar.gz", hash = "sha256:84e64a1c28cf7e91ed2078bb8cc8c259cb19b76942096c8d7b84947690cabaf0"},
-]
-
-[package.extras]
-docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (<7.2.5)", "sphinx (>=3.5)", "sphinx-lint"]
-testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy (>=0.9.1)", "pytest-ruff"]
-
-[metadata]
-lock-version = "2.0"
-python-versions = "^3.8"
-content-hash = "877476bd6c72d4b5fdd5bdb3412e89544ae0b3cd31f284d947062125da18020e"
diff --git a/poetry.toml b/poetry.toml
deleted file mode 100644
index 6ee81a0..0000000
--- a/poetry.toml
+++ /dev/null
@@ -1,2 +0,0 @@
-[installer]
-no-binary = ["gdal", "rasterio"]
diff --git a/pyproject.toml b/pyproject.toml
index 3d21a10..0c2eba4 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,47 +1,16 @@
-[tool.poetry]
+[build-system]
+requires = ["setuptools"]
+build-backend = "setuptools.build_meta"
+
+[project]
+dynamic = ["dependencies"]
+license = {file = "LICENSE"}
 name = "dep-tools"
+requires-python = ">=3.10"
 version = "0.2.0"
-description = ""
-authors = ["Jesse Anderson <jesse.anderson@gmail.com>"]
-license = "MIT"
-packages = [{include = "dep_tools"}]
-include = ["*.gpkg"]
-
-[tool.poetry.dependencies]
-python = "^3.8"
-azure-storage-blob = "*"
-geopandas = "*"
-dask = {extras = ["complete"], version = "*"}
-dask-gateway = "*"
-geocube = "*"
-gdal = "*"
-pystac-client = "*"
-planetary-computer = "*"
-rioxarray = "*"
-stackstac = "*"
-retry = "*"
-tqdm = "*"
-urlpath = "^1.2.0"
-xarray = "*"
-rio-stac = "^0.8.0"
-odc-stac = "*"
-odc-algo = "*"
-fiona = "^1.9.6"
-
-[tool.poetry.group.dev]
-optional = true
 
-[tool.poetry.group.test]
-optional = true
+[tool.setuptools]
+packages = ["dep_tools"]
 
-[tool.poetry.group.dev.dependencies]
-black = "^23.1.0"
-pylint = "^2.17.1"
-mypy = "^1.1.1"
-
-[tool.poetry.group.test.dependencies]
-pytest = "^7.4.0"
-
-[build-system]
-requires = ["poetry-core"]
-build-backend = "poetry.core.masonry.api"
+[tool.setuptools.dynamic]
+dependencies = { file = ["requirements.txt"] }
diff --git a/requirements.txt b/requirements.txt
new file mode 100644
index 0000000..d39813c
--- /dev/null
+++ b/requirements.txt
@@ -0,0 +1,20 @@
+antimeridian
+azure-storage-blob
+boto3
+dask[complete]
+dask-gateway
+fiona
+gdal
+geocube
+geopandas
+odc-stac
+odc-algo
+pystac-client
+planetary-computer
+rioxarray
+rio-stac>=0.8.0
+stackstac
+retry
+tqdm
+urlpath>=1.2.0
+xarray
diff --git a/tests/data/dep_spysat_wofs/1-0-0/12/34/2021-01-01/dep_spysat_wofs_12_34_2021-01-01_wofs.tif b/tests/data/dep_spysat_wofs/1-0-0/12/34/2021-01-01/dep_spysat_wofs_12_34_2021-01-01_wofs.tif
new file mode 100644
index 0000000..f2bdf9b
Binary files /dev/null and b/tests/data/dep_spysat_wofs/1-0-0/12/34/2021-01-01/dep_spysat_wofs_12_34_2021-01-01_wofs.tif differ
diff --git a/tests/test_aws.py b/tests/test_aws.py
new file mode 100644
index 0000000..da0cab4
--- /dev/null
+++ b/tests/test_aws.py
@@ -0,0 +1,12 @@
+from geopandas import GeoDataFrame
+from shapely import box
+
+from dep_tools.aws import write_to_s3, object_exists
+
+
+# def test_write_to_s3_kwargs():
+#    bucket = "dep-public-staging"
+#    key = "test.gpkg"
+#    d = GeoDataFrame(geometry=[box(-170, 0, -169, 1)])
+#    write_to_s3(d, path=key, bucket=bucket, driver="GPKG")
+#    assert object_exists(bucket, key)
diff --git a/tests/test_depwriter.py b/tests/test_depwriter.py
new file mode 100644
index 0000000..e69de29
diff --git a/tests/test_dswriter.py b/tests/test_dswriter.py
new file mode 100644
index 0000000..d05a9a2
--- /dev/null
+++ b/tests/test_dswriter.py
@@ -0,0 +1,10 @@
+# from dep_tools.writers import DsWriter
+# from dep_tools.namers import DepItemPath
+#
+#
+# def test_kwargs():
+#    itempath = DepItemPath(
+#        sensor="spc_sat", dataset_id="clear_waters", version="1.0", time="1901"
+#    )
+#    writer = DsWriter(itempath=itempath, bucket="dep_bucket")
+#    assert isinstance(writer, DsWriter)
diff --git a/tests/test_get_stac_item.py b/tests/test_get_stac_item.py
index 1b0a79c..491ea00 100644
--- a/tests/test_get_stac_item.py
+++ b/tests/test_get_stac_item.py
@@ -1,25 +1,40 @@
 import rioxarray
 
-from dep_tools.stac_utils import _get_stac_item
+from dep_tools.namers import LocalPath
+from dep_tools.stac_utils import StacCreator
+from dep_tools.writers import StacWriter
 
+from dep_tools.stac_utils import get_stac_item
+from pathlib import Path
 import pytest
 
-TEST_ITEM_URL = "https://deppcpublicstorage.blob.core.windows.net/output/dep_ls_wofs/0-0-2/TV/001/2021/dep_ls_wofs_TV_001_2021_mean.tif"
+DATA_DIR = Path(__file__).parent / "data"
 
 
 @pytest.fixture
 def stac_item():
-    test_path = "dep_ls_wofs/0-0-2/TV/001/2021/dep_ls_wofs_TV_001_2021_mean.tif"
-    test_xr = rioxarray.open_rasterio(TEST_ITEM_URL, chunks=True)
-    item = _get_stac_item(test_xr, test_path, collection="dep_ls_wofs")
+    itempath = LocalPath(
+        str(DATA_DIR),
+        sensor="spysat",
+        dataset_id="wofs",
+        version="1.0.0",
+        time="2021-01-01",
+    )
+    tif = itempath.path("12,34", asset_name="wofs")
+    test_xr = rioxarray.open_rasterio(tif).to_dataset(name="wofs")
+    item = get_stac_item(
+        itempath=itempath,
+        item_id="12,34",
+        data=test_xr,
+        remote=False,
+    )
+
     return item
 
 
 def test_get_stac_item_properties(stac_item):
     properties = stac_item.properties
     keys = [
-        "start_datetime",
-        "end_datetime",
         "proj:epsg",
         "proj:geometry",
         "proj:bbox",
@@ -31,8 +46,11 @@ def test_get_stac_item_properties(stac_item):
 
 
 def test_get_stac_item_collection_id(stac_item):
-    assert stac_item.collection_id == "dep_ls_wofs"
+    assert stac_item.collection_id == "dep_spysat_wofs"
 
 
 def test_stac_asset_href_is_valid(stac_item):
-    assert stac_item.assets["asset"].href == TEST_ITEM_URL
+    assert stac_item.assets["wofs"].href == str(
+        DATA_DIR
+        / "dep_spysat_wofs/1-0-0/12/34/2021-01-01/dep_spysat_wofs_12_34_2021-01-01_wofs.tif"
+    )
diff --git a/tests/test_landsat_mspc_stac_search_fixes.py b/tests/test_landsat_mspc_stac_search_fixes.py
index 90662be..e891dad 100644
--- a/tests/test_landsat_mspc_stac_search_fixes.py
+++ b/tests/test_landsat_mspc_stac_search_fixes.py
@@ -1,6 +1,4 @@
-from re import search
 import geopandas as gpd
-from pystac_client import Client
 import pytest
 from shapely.geometry import box
 
diff --git a/tests/test_searchers.py b/tests/test_searchers.py
index 3e0ceb6..b0f347c 100644
--- a/tests/test_searchers.py
+++ b/tests/test_searchers.py
@@ -1,8 +1,10 @@
 import geopandas as gpd
+import odc.stac
 from pystac import ItemCollection
-from pystac_client import Client
+import planetary_computer as pc
 import pytest
 from shapely.geometry import box
+from xarray import Dataset
 
 from dep_tools.searchers import PystacSearcher, LandsatPystacSearcher
 
@@ -18,12 +20,14 @@ def area() -> gpd.GeoDataFrame:
 
 
 @pytest.fixture
-def mspc_client():
-    return Client.open("https://planetarycomputer.microsoft.com/api/stac/v1")
+def mspc_catalog():
+    return "https://planetarycomputer.microsoft.com/api/stac/v1"
 
 
-def test_PystacSearcher(area):
-    s = PystacSearcher(collections=["landsat-c2-l2"], datetime="2007")
+def test_PystacSearcher(area, mspc_catalog):
+    s = PystacSearcher(
+        catalog=mspc_catalog, collections=["landsat-c2-l2"], datetime="2007"
+    )
     items = s.search(area)
     assert isinstance(items, ItemCollection)
 
@@ -34,3 +38,12 @@ def test_PystacSearcher(area):
 def test_LandsatPystacSearcher_exclude_platforms(area):
     s = LandsatPystacSearcher(exclude_platforms=["landsat-7"])
     s.search(area)
+
+
+def test_unsigned_search(area, mspc_catalog):
+    s = PystacSearcher(
+        catalog=mspc_catalog, collections=["landsat-c2-l2"], datetime="2007"
+    )
+    items = s.search(area)
+    ds = odc.stac.load([items[0]], patch_url=pc.sign, chunks=dict(x=2048, y=2048))
+    assert isinstance(ds, Dataset)