Dataset docs overhaul

api-reference/tilebox.datasets/Collection.delete.mdx

@@ -1,10 +1,10 @@
 ---
 title: Collection.delete
-icon: download
+icon: layer-group
 ---
 
 ```python
-def Collection.delete(datapoints: xr.Dataset) -> int
+def Collection.delete(datapoints: DatapointIDs) -> int
 ```
 
 Delete datapoints from the collection.
@@ -17,8 +17,17 @@ Datapoints are identified and deleted by their ids.
 
 ## Parameters
 
-<ParamField path="datapoints" type="xr.Dataset">
-    An [`xarray.Dataset`](/sdks/python/xarray) containing an "id" variable consisting of datapoint IDs to delete.
+<ParamField path="datapoints" type="DatapointIDs">
+  Datapoint IDs to delete from the collection.
+
+  Supported `DatapointIDs` types are.
+  - A `pandas.DataFrame` containing an `id` column.
+  - A `pandas.Series` containing datapoint IDs.
+  - An `xarray.Dataset` containing an "id" variable.
+  - An `xarray.DataArray` containing datapoint IDs.
+  - A `numpy.ndarray` containing datapoint IDs.
+  - A `Collection[UUID]` containing datapoint IDs as python built-in `UUID` objects, e.g. `list[UUID]`.
+  - A `Collection[str]` containing datapoint IDs as strings, e.g. `list[str]`.
 </ParamField>
 
 ## Returns
@@ -27,8 +36,19 @@ The number of datapoints that were deleted.
 
 <RequestExample>
 ```python Python
-datapoints = collection.load("2023-05-01 12:45:33.423")
-
-n_deleted = collection.delete(datapoints)
+collection.delete([
+  "0195c87a-49f6-5ffa-e3cb-92215d057ea6",
+  "0195c87b-bd0e-3998-05cf-af6538f34957",
+])
 ```
 </RequestExample>
+
+## Errors
+
+<ParamField path="NotFoundError" type="No such collection: Non-existent-Collection">
+  One of the data points is not found in the collection. If any of the data points are not found,
+  nothing will be deleted.
+</ParamField>
+<ParamField path="ValueError" type="Invalid UUID">
+  One of the specified ids is not a valid UUID
+</ParamField>

api-reference/tilebox.datasets/Collection.find.mdx

@@ -1,6 +1,6 @@
 ---
 title: Collection.find
-icon: download
+icon: layer-group
 ---
 
 ```python

api-reference/tilebox.datasets/Collection.info.mdx

@@ -1,6 +1,6 @@
 ---
 title: Collection.info
-icon: download
+icon: layer-group
 ---
 
 ```python

api-reference/tilebox.datasets/Collection.ingest.mdx

@@ -0,0 +1,62 @@
+---
+title: Collection.ingest
+icon: layer-group
+---
+
+```python
+def Collection.ingest(
+    data: IngestionData,
+    allow_existing: bool = True
+) -> list[UUID]
+```
+
+Ingest data into a collection.
+
+<Note>
+  You need to have write permission on the collection to be able to delete datapoints.
+</Note>
+
+## Parameters
+
+<ParamField path="data" type="IngestionData">
+  The data to ingest.
+
+  Supported `IngestionData` data types are:
+  - A `pandas.DataFrame`, mapping the column names to dataset fields.
+  - An `xarray.Dataset`, mapping variables and coordinates to dataset fields.
+  - `Iterable`, `dict` or `nd-array`: Ingest any object that can be converted to a `pandas.DataFrame` using
+    it's constructor, equivalent to `ingest(pd.DataFrame(data))`.
+</ParamField>
+<ParamField path="allow_existing" type="bool">
+  Datapoint fields are used to generate a deterministic unique `UUID` for each
+  datapoint in a collection. Duplicate datapoints result in the same ID being generated.
+  If `allow_existing` is `True`, `ingest` will skip those datapoints, since they already exist.
+  If `allow_existing` is `False`, `ingest` will raise an error if any of the generated datapoint IDs already exist.
+  Defaults to `True`.
+</ParamField>
+
+## Returns
+
+List of datapoint ids that were ingested, including the IDs of already existing datapoints in case of duplicates and 
+`allow_existing=True`.
+
+<RequestExample>
+```python Python
+import pandas as pd
+
+collection.ingest(pd.DataFrame({
+    "time": [
+      "2023-05-01T12:00:00Z",
+      "2023-05-02T12:00:00Z",
+    ],
+    "value": [1, 2],
+    "sensor": ["A", "B"],
+}))
+```
+</RequestExample>
+
+## Errors
+
+<ParamField path="ArgumentError" type="found existing datapoints with same id">
+  If `allow_existing` is `False` and any of the datapoints attempting to ingest already exist.
+</ParamField>

api-reference/tilebox.datasets/Collection.load.mdx

@@ -1,6 +1,6 @@
 ---
 title: Collection.load
-icon: download
+icon: layer-group
 ---
 
 ```python
@@ -32,7 +32,7 @@ If no data exists for the requested time or interval, an empty `xarray.Dataset`
 </ParamField>
 
 <ParamField path="skip_data" type="bool">
-  If `True`, the response contains only the [datapoint metadata](/datasets/timeseries) without the actual dataset-specific fields. Defaults to `False`.
+  If `True`, the response contains only the [required fields for the dataset type](/datasets/types/timeseries) without the actual dataset-specific fields. Defaults to `False`.
 </ParamField>
 
 <ParamField path="show_progress" type="bool">

api-reference/tilebox.datasets/Dataset.collection.mdx

@@ -1,6 +1,6 @@
 ---
 title: Dataset.collection
-icon: layer-group
+icon: database
 ---
 
 ```python

api-reference/tilebox.datasets/Dataset.collections.mdx

@@ -1,6 +1,6 @@
 ---
 title: Dataset.collections
-icon: layer-group
+icon: database
 ---
 
 ```python

api-reference/tilebox.datasets/Dataset.create_collection.mdx

@@ -1,6 +1,6 @@
 ---
 title: Dataset.create_collection
-icon: layer-group
+icon: database
 ---
 
 ```python

api-reference/tilebox.datasets/Dataset.get_or_create_collection.mdx

@@ -1,6 +1,7 @@
 ---
 title: Dataset.get_or_create_collection
-icon: layer-group
+sidebarTitle: Dataset.get_or_create_c...
+icon: database
 ---
 
 ```python