v3.1.0

General

• Due to declining support for Python 3.8 across the ecosystem, we have discontinued our support for Python 3.8. It is expected that the client will continue to function until Python 3.8 is End of Life (October 2024), but we can no longer test new releases against this version.

Catalog

• The Catalog Storage Blob deletion methods have been enhanced to support waiting for completion of the operation. When a blob is deleted, it is removed immediately from the catalog and a background asynchronous task is launched to clean up the contents of the blob from the backing storage. If a blob is deleted and then a new blob with the identical id is immediately created and uploaded before this background task completes, it is possible for the background task to end up deleting the new blob contents. As of this release the Blob instance and class delete methods return a BlobDeletionTaskStatus object which provides a wait_for_completion method which can be used to wait until the background task completes and it is safe to create a new blob with the same id. For the Blob.delete_many method, the wait_for_completion=True parameter can be used to wait for all the supplied blobs to be completely deleted. Note that in the case of the Blob.delete class method, this is a very slight breaking change, as it used to return True or False, and now instead returns a BlobDeletionTaskStatus or None, which have the same truthiness and hence are very likely to behave identically in practical use.

v3.0.5

Bugfix only

General

• The descarteslabs client CLI script generated by the installation process was broken. Now it works!

v3.0.4

A very minor release with some obscure bug fixes.

General

• The descarteslabs client CLI has had an overhaul. Gone is the obsolete support for the Raster client, and added is support for querying Catalog Products, Bands, and Blobs and managing sharing for the same.
• Minor fixes to the authorization flow on login.

Catalog

• Add testing of Blobs.

Compute

• Corrected regular expressions used to parse the memory argument to the Function constructor.
• Improved documentation of the the cpus and memory arguments to the Function constructor.

v3.0.3

General

• Fixed a bug in seldom-used code to clear client state causing an import failure.

v3.0.2

Vector

• Fixed a bug in Table.visualize() which could cause Authorization (401) errors when rendering tiles into an ipyleaflet.Map.

General

• Bumped some minimum dependency version constraints to avoid security vulnerabilities.

v3.0.2rc0

Test fix to Vector visualize

v3.0.1

Vector

• Fixed a bug in Table.visualize() that was causing it to fail.

v3.0.0

Due to a number of breaking changes, the version has been bumped to 3.0.0. However, the vast majority
of typical use patterns in typical user code will not require changes. Please review the specifics
below.

Catalog

• The tags attributes on Catalog objects can now contain up to 32 elements, each up to 1000 characters long.
  But why would you even want to go there?
• Breaking Change: Derived bands, never supported in the AWS environment and catalog products, have been
  removed.
• The new Blob.delete_many method may be used to delete large numbers of blobs efficiently.
• The Blob.get_or_create method didn't allow supplying storage_type, namespace, or name parameters.
  Now it works as expected, either returning a saved Blob from the Catalog, or an unsaved blob that
  you can use to upload and save its data.
• Image methods ndarray and download no longer pass the image's default geocontext geometry as a cutline.
  This is to avoid problems when trying to raster a complete single image in its native CRS and resolution
  where imperfect geometries (due to a simplistic projection to EPSG:4326) can cause some boundary pixels
  to be masked. When passing in an explicit GeoContext to these methods, consider whether any cutline
  geometry is required or not, to avoid these issues.

Compute

• Function and Job objects now have a new environment attribute which can be used to define environment
  variables for the jobs when they are run.
• Breaking Change: The Function.map method previously had no bound on how many jobs could be created at one time.
  This led to operational problems with very large numbers of jobs. Now it submits jobs in batches (up to 1000
  jobs per batch) to avoid request timeouts, and is more robust on retryable errors so that duplicate jobs are not
  submitted accidently. There is still no bound on how many jobs you may create with a single call to Function.map.
  Additionally, since it is possible that some jobs may be successfully submitted, and others not, the return
  value, while still behaving as a list of Jobs, is now a JobBulkCreateResult object which has a is_success
  and an error property which can be used to determine if all submissions were successful, what errors may
  have occurred, and what jobs have actually been created. Only if the first batch fails hard will the method
  raise an exception.
• The Job.statistics member is now typed as a JobStatistics object.
• The efficiency of deleting many jobs at once has been significantly improved using Function.delete and
  Function.delete_jobs. It is still possible to encounter request timeouts with very large numbers of jobs;
  workarounds are now documented in the API documentation for the Function.delete_jobs method.
• The ComputeClient.check_credentials method has been added, so that the client can determine if valid
  user credentials have already been registered with the Compute service.

Vector

• The Vector client library, previously available as the descarteslabs-vector package on PyPI, has
  now been integrated into the Descartes Labs Python Client (this package). It should no longer be
  installed separately.
• Visualization support (ipyleaflet.Map) is enabled when ipyleaflet is available. It is not
  installed by default, but can be installed manually, or by installing the descarteslabs python
  client with the viz extra (e.g. pip install descarteslabs[viz]). Note that in order to be
  compatible with jupyterlab notebooks, the visualize() method no longer returns the layer, it
  just adds it to the supplied map.
• The Vector package now has a VectorClient API client, with the usual support for get_default_client()
  and set_default_client(). Most constructors and methods now accept an optional client= parameter
  if you need to use something other than the default client.
• Configuration is now accomplished using the standard descarteslabs.config package. In particular,
  the vector_url setting is used to specify the default Vector host. The VECTOR_API_HOST environment
  variable is no longer consulted.
• Vector client methods now raise standard descarteslabs.exceptions Exception classes rather than
  the descarteslabs.vector.vector_exceptions classes of the old client.
• The is_spatial= parameter previously accepted by many methods and functions is now deprecated
  and ignored. It is not required because existing type information always determines if an operation
  is spatial or not. Warnings will be generated if it is used.
• Be advised that feature upload and download (query) do not currently support or impose any limits,
  and thus allow operations so large and slow that timeouts or other failures may occur. A future
  version will implement limits and batching, so that large operations can be supported reliably.
  Until then, the user may wish to implement their own batching were possible to avoid encountering
  network limits and timeouts.

General

• The old client version v1.12.1 is reaching end of life and will longer be supported as of February 2024.
  You can expect the version to stop working at any point after that as legacy backend support is turned off.
• Breaking Change: The deprecated Scenes client API has been removed.
• Breaking Change: The deprecated Metadata client API has been removed.
• The minimum required version of urllib3 has been bumped to 1.26.18 to address a security vulnerability.
• The minimum required version of shapely has been bumped to 2.0.0 to address thread safety issues.
• Python 3.7, formerly deprecated, is no longer supported.
• Python 3.12 is not yet officially supported due to the lack of support from blosc. However, if you
  are able to provide a functional blosc on your own, then 3.12 should work.
• Urllib3 2.X is now supported.
• Geopandas, Pydantic, and PyArrow have been added as core dependencies to support the Vector client.
• For those users of the clear_client_state function (not common), the bands cache for the Catalog client
  is now cleared also.

(note that these release notes are duplicated from the non-public v3.0.0rc0)

v3.0.0rc0

Due to a number of breaking changes, the version has been bumped to 3.0.0. However, the vast majority
of typical use patterns in typical user code will not require changes. Please review the specifics
below.

Catalog

• The tags attributes on Catalog objects can now contain up to 32 elements, each up to 1000 characters long.
  But why would you even want to go there?
• Breaking Change: Derived bands, never supported in the AWS environment and catalog products, have been
  removed.
• The new Blob.delete_many method may be used to delete large numbers of blobs efficiently.
• The Blob.get_or_create method didn't allow supplying storage_type, namespace, or name parameters.
  Now it works as expected, either returning a saved Blob from the Catalog, or an unsaved blob that
  you can use to upload and save its data.
• Image methods ndarray and download no longer pass the image's default geocontext geometry as a cutline.
  This is to avoid problems when trying to raster a complete single image in its native CRS and resolution
  where imperfect geometries (due to a simplistic projection to EPSG:4326) can cause some boundary pixels
  to be masked. When passing in an explicit GeoContext to these methods, consider whether any cutline
  geometry is required or not, to avoid these issues.

Compute

• Function and Job objects now have a new environment attribute which can be used to define environment
  variables for the jobs when they are run.
• Breaking Change: The Function.map method previously had no bound on how many jobs could be created at one time.
  This led to operational problems with very large numbers of jobs. Now it submits jobs in batches (up to 1000
  jobs per batch) to avoid request timeouts, and is more robust on retryable errors so that duplicate jobs are not
  submitted accidently. There is still no bound on how many jobs you may create with a single call to Function.map.
  Additionally, since it is possible that some jobs may be successfully submitted, and others not, the return
  value, while still behaving as a list of Jobs, is now a JobBulkCreateResult object which has a is_success
  and an error property which can be used to determine if all submissions were successful, what errors may
  have occurred, and what jobs have actually been created. Only if the first batch fails hard will the method
  raise an exception.
• The Job.statistics member is now typed as a JobStatistics object.
• The efficiency of deleting many jobs at once has been significantly improved using Function.delete and
  Function.delete_jobs. It is still possible to encounter request timeouts with very large numbers of jobs;
  workarounds are now documented in the API documentation for the Function.delete_jobs method.
• The ComputeClient.check_credentials method has been added, so that the client can determine if valid
  user credentials have already been registered with the Compute service.

Vector

• The Vector client library, previously available as the descarteslabs-vector package on PyPI, has
  now been integrated into the Descartes Labs Python Client (this package). It should no longer be
  installed separately.
• Visualization support (ipyleaflet.Map) is enabled when ipyleaflet is available. It is not
  installed by default, but can be installed manually, or by installing the descarteslabs python
  client with the viz extra (e.g. pip install descarteslabs[viz]). Note that in order to be
  compatible with jupyterlab notebooks, the visualize() method no longer returns the layer, it
  just adds it to the supplied map.
• The Vector package now has a VectorClient API client, with the usual support for get_default_client()
  and set_default_client(). Most constructors and methods now accept an optional client= parameter
  if you need to use something other than the default client.
• Configuration is now accomplished using the standard descarteslabs.config package. In particular,
  the vector_url setting is used to specify the default Vector host. The VECTOR_API_HOST environment
  variable is no longer consulted.
• Vector client methods now raise standard descarteslabs.exceptions Exception classes rather than
  the descarteslabs.vector.vector_exceptions classes of the old client.
• The is_spatial= parameter previously accepted by many methods and functions is now deprecated
  and ignored. It is not required because existing type information always determines if an operation
  is spatial or not. Warnings will be generated if it is used.
• Be advised that feature upload and download (query) do not currently support or impose any limits,
  and thus allow operations so large and slow that timeouts or other failures may occur. A future
  version will implement limits and batching, so that large operations can be supported reliably.
  Until then, the user may wish to implement their own batching were possible to avoid encountering
  network limits and timeouts.

General

• The old client version v1.12.1 is reaching end of life and will longer be supported as of February 2024.
  You can expect the version to stop working at any point after that as legacy backend support is turned off.
• Breaking Change: The deprecated Scenes client API has been removed.
• Breaking Change: The deprecated Metadata client API has been removed.
• The minimum required version of urllib3 has been bumped to 1.26.18 to address a security vulnerability.
• The minimum required version of shapely has been bumped to 2.0.0 to address thread safety issues.
• Python 3.7, formerly deprecated, is no longer supported.
• Python 3.12 is not yet officially supported due to the lack of support from blosc. However, if you
  are able to provide a functional blosc on your own, then 3.12 should work.
• Urllib3 2.X is now supported.
• Geopandas, Pydantic, and PyArrow have been added as core dependencies to support the Vector client.
• For those users of the clear_client_state function (not common), the bands cache for the Catalog client
  is now cleared also.

v2.1.2

Compute

• Function.delete_jobs was failing to implement the delete_results parameter, so job result blobs
  were not being deleted. This has been fixed.
• Add delete_results parameter to Function.delete for consistency.
• Job.statistics field added which contains statistics (CPU, memory, and network utilization) for the
  job. This can be used to determine the minimal resources necessary for the Function after some
  representative runs.