Descarteslabs

Added
- Add support for user cython modules in tasks.

Changed
- Tasks webhook methods no longer require a group_id if a webhook id is provided.
- catalog_id property on images is no longer supported by the API
- Fix scenes.display handling of single band masked arrays with scalar masks
- Fix problems with incomplete UploadTask instances returned by vectors.FeatureCollection.list_uploads

Added
- Metadata, Catalog, and Scenes now support a new `storage_state` property for managing image metadata and filtering search results. `storage_state="available"` is the default for new images and indicates that the raster data for that scene is available on the Descartes Labs platform. `storage_state="remote"` indicates that the raster data has not yet been processed and made available to client users.
- The following additional colormaps are now supported for bands – 'cool', 'coolwarm', 'hot', 'bwr', 'gist_earth', 'terrain'. Find more details about the colormaps [here](https://matplotlib.org/gallery/color/colormap_reference.html).
- `Scene.ndarray`, `SceneCollection.stack`, and `SceneCollection.mosaic` now support passing a string as the `mask_alpha` argument to allow users to specify an alternate band name to use for masking.
- Scenes now supports a new `save_image` function that allows a user to save a visualization given a filename and extension.
- Tasks now allows you to unambiguously get a function by group id using `get_function_by_id`.
- All Client APIs now accept a `retries` argument to override the default retry configuration. The default remains
the same as the prior behavior, which is to attempt 3 retries on errors which can be retried.

Changed
- Bands of different but compatible types can now be rastered together in `Scene.ndarray()` and `Scene.download()` as well as across multiple scenes in `SceneCollection.mosaic()`, `SceneCollection.stack()` and `SceneCollection.download()`. The result will have the most general data type.
- Vector client functions that accept a `geometry` argument now support passing Shapely shapes in addition to GeoJSON.

Changed
- Removed deprecated method `Metadata.sources()`
- `FeatureCollection.filter(geometry)` will now raise an `InvalidQueryException` if you
try to overwrite an existing geometry in the filter chain. You can only set the
geometry once.

Changed
- Many old and obsolete examples were removed from the package.
- Scene.ndarray, SceneCollection.stack, and SceneCollection.mosaic now will automatically mask alpha if the alpha band is available in the relevant scene(s), and will set mask_alpha to False if the alpha band does not exist.
- FeatureCollection.add, FeatureCollection.upload, Vector.create_feature, Vector.create_features, and Vector.upload_features all accept a fix_geometry string argument that determines how to handle certain problem geometries including those which do not follow counter-clockwise winding order (which is required by the GeoJSON spec but not many popular tools). Allowed values are reject (reject invalid geometries with an error), fix (correct invalid geometries if possible and use this corrected value when creating the feature), and accept (the default) which will correct the geometry for internal use but retain the original geometry in the results.
Vector.get_upload_results and Vector.get_upload_result now accept a pending parameter to include pending uploads in the results. Such pending results will have status: PENDING and, in lieu of a task id, the id attribute will contain the upload id as returned by Vector.upload_features
- UploadTask.status no longer blocks until the upload task is completed, but rather returns the current status of the upload job, which may be PENDING, RUNNING, SUCCESS, or FAILURE.
- The FutureTask.ready and UploadTask.ready property has been added to test whether the task has completed. A return value of True means that if get_result(wait=True) were to be called, it would return without blocking.
- You can now export features to a storage data blob. To export from the vector client, use Vector.export_product_from_query() with a storage key and an optional query. This returns the task id of the export task. You can ask for status using Vector.get_export_results() for all export tasks or Vector.get_export_result() for a specific task by task id.
- FeatureCollection has been extended with this functionality with a FeatureCollection.export() method that takes a storage key. This operates on the filter chain that FeatureCollection represents, or the full product if there is no filter chain. It returns an ExportTask which behaves similar to the FutureTask.
- Catalog.upload_image() and Catalog.upload_ndarray() now will return an upload_id that can be used to query the status of that upload using Catalog.upload_result(). Note that the upload id is the image id and if you use identical image ids Catalog.upload_result() will only show the result of the most recent upload.

Changed
- Fixed issues with `Catalog.upload_ndarray()` under Windows
- Added header to client requests to better debug retries

Changed
- Tasks methods `create_function`, `create_or_get_function`, and `new_group` now have image as a required parameter
- The `name` parameter is renamed to `product_id` in `Vector.create_product`, and `FeatureCollection.create` and `FeatureCollection.copy`. The 'name' parameter is renamed to `new_product_id` in `Vector.create_product_from_query`. Using `name` will continue to work, but will be removed completely in future versions.
- The `name` parameter is no longer required, and is ignored for `Vector.replace_product`, `Vector.update_product`, `FeatureCollection.update` and `FeatureCollection.replace`. This parameter will be removed completely in future versions.

Added
- `Metadata.paged_search` has been added and essentially supports the original behavior of `Metadata.search` prior to release 0.16.0.
This method should generally be avoided in favor of `Metadata.features` (or `Metadata.search`).