v0.1.383

PiperOrigin-RevId: 588813547

.github/workflows/ci-type-verification.yml

@@ -0,0 +1,32 @@
+name: ci-type-verification
+on:
+  # Triggers the workflow when new code is pushed to the master branch.
+  push:
+    branches: [ master ]
+  # Enables running this workflow manually from the Actions tab.
+  workflow_dispatch:
+jobs:
+  build:
+    name: "Type verification"
+    runs-on: ubuntu-latest
+    steps:
+    - name: Cancel previous
+      uses: styfle/[email protected]
+      with:
+        access_token: ${{ github.token }}
+      if: ${{github.ref != 'refs/head/master'}}
+    - uses: actions/checkout@v4
+    - name: Set up Python
+      uses: actions/setup-python@v2
+      with:
+        python-version: 3.11
+    - name: Install EE API
+      run: |
+        pip install -e ./python
+        pip install pyright
+    - name: ee type verification
+      run: |
+        pyright --verifytypes ee
+    - name: ee.cli type verification
+      run: |
+        pyright --verifytypes ee.cli

javascript/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@google/earthengine",
-  "version": "0.1.382",
+  "version": "0.1.383",
   "description": "JavaScript client for Google Earth Engine API.",
   "author": "Google LLC",
   "license": "Apache-2.0",

javascript/src/apiclient.js

@@ -25,7 +25,7 @@ const {trustedResourceUrl} = goog.require('safevalues');
 /** @namespace */
 const apiclient = {};
 
-const API_CLIENT_VERSION = '0.1.382';
+const API_CLIENT_VERSION = '0.1.383';
 
 exports.VERSION = apiVersion.VERSION;
 exports.API_CLIENT_VERSION = API_CLIENT_VERSION;

javascript/src/batch.js

@@ -33,6 +33,9 @@ Export.table = {};
 /** @const */
 Export.video = {};
 
+/** @const */
+Export.classifier = {};
+
 /**
  * ExportTask
  */
@@ -393,6 +396,22 @@ Export.video.toDrive = function(
   return ExportTask.create(serverConfig);
 };
 
+/**
+ * @param {!ComputedObject} classifier
+ * @param {string=} opt_description
+ * @param {string=} opt_assetId
+ * @return {!ExportTask}
+ * @export
+ */
+Export.classifier.toAsset = function(classifier, opt_description, opt_assetId) {
+  const clientConfig =
+      eeArguments.extractFromFunction(Export.classifier.toAsset, arguments);
+  const serverConfig = Export.convertToServerParams(
+      clientConfig, ExportDestination.ASSET, ExportType.CLASSIFIER);
+  return ExportTask.create(serverConfig);
+};
+
+
 ////////////////////////////////////////////////////////////////////////////////
 //                          Internal validation.                              //
 ////////////////////////////////////////////////////////////////////////////////

javascript/src/data.js

@@ -21,6 +21,7 @@ goog.provide('ee.data.AuthPrivateKey');
 goog.provide('ee.data.Band');
 goog.provide('ee.data.BandDescription');
 goog.provide('ee.data.BigQueryTaskConfig');
+goog.provide('ee.data.ClassifierTaskConfig');
 goog.provide('ee.data.DownloadId');
 goog.provide('ee.data.ExportDestination');
 goog.provide('ee.data.ExportState');
@@ -1296,6 +1297,11 @@ ee.data.startProcessing = function(taskId, params, opt_callback) {
     case ee.data.ExportType.MAP:
       const mapRequest = ee.data.prepareExportMapRequest_(params, metadata);
       return handle(call.map().export(call.projectsPath(), mapRequest));
+    case ee.data.ExportType.CLASSIFIER:
+      const classifierRequest =
+          ee.data.prepareExportClassifierRequest_(params, metadata);
+      return handle(
+          call.classifier().export(call.projectsPath(), classifierRequest));
     default:
       throw new Error(
           `Unable to start processing for task of type ${taskType}`);
@@ -1379,6 +1385,27 @@ ee.data.prepareExportMapRequest_ = function(taskConfig, metadata) {
   return mapRequest;
 };
 
+
+/**
+ * Creates an ExportClassifierRequest for a given ClassifierTaskConfig.
+ *
+ * @param {!Object} taskConfig classifier task configuration params.
+ * @param {!Object} metadata associated with the export request.
+ * @return {!ee.api.ExportClassifierRequest}
+ * @private
+ */
+ee.data.prepareExportClassifierRequest_ = function(taskConfig, metadata) {
+  const classifierRequest =
+      ee.rpc_convert_batch.taskToExportClassifierRequest(taskConfig);
+  classifierRequest.expression =
+      ee.data.expressionAugmenter_(classifierRequest.expression, metadata);
+  if (taskConfig['workloadTag']) {
+    classifierRequest.workloadTag = taskConfig['workloadTag'];
+  }
+  return classifierRequest;
+};
+
+
 /**
  * Creates an image asset ingestion task.
  *
@@ -2195,6 +2222,7 @@ ee.data.resetWorkloadTag = function(opt_resetDefault) {
  */
 ee.data.AssetType = {
   ALGORITHM: 'Algorithm',
+  CLASSIFIER: 'Classifier',
   FEATURE_VIEW: 'FeatureView',
   FOLDER: 'Folder',
   FEATURE_COLLECTION: 'FeatureCollection',
@@ -2211,6 +2239,7 @@ ee.data.ExportType = {
   MAP: 'EXPORT_TILES',
   TABLE: 'EXPORT_FEATURES',
   VIDEO: 'EXPORT_VIDEO',
+  CLASSIFIER: 'EXPORT_CLASSIFIER'
 };
 
 /** @enum {string} The status of the export. */
@@ -3419,6 +3448,24 @@ ee.data.ImageExportFormatConfig;
  */
 ee.data.MapTaskConfig;
 
+/**
+ * An object for specifying configuration of a task to export a classifier
+ * as an asset.
+ *
+ * @typedef {{
+ *   id: string,
+ *   type: string,
+ *   sourceUrl: (undefined|string),
+ *   description: (undefined|string),
+ *   element: (undefined|!ee.ComputedObject),
+ *   assetId: (undefined|string),
+ *   maxWorkers: (undefined|number),
+ *   workloadTag: (undefined|string),
+ * }}
+ */
+ee.data.ClassifierTaskConfig;
+
+
 /**
  * An object for specifying configuration of a task to export feature
  * collections to a FeatureView.

python/ee/__init__.py

@@ -1,7 +1,7 @@
 #!/usr/bin/env python3
 """The EE Python library."""
 
-__version__ = '0.1.382'
+__version__ = '0.1.383'
 
 # Using lowercase function naming to match the JavaScript names.
 # pylint: disable=g-bad-name

python/ee/batch.py

@@ -29,6 +29,7 @@ class Type(str, enum.Enum):
     EXPORT_MAP = 'EXPORT_TILES'
     EXPORT_TABLE = 'EXPORT_FEATURES'
     EXPORT_VIDEO = 'EXPORT_VIDEO'
+    EXPORT_CLASSIFIER = 'EXPORT_CLASSIFIER'
 
   class State(str, enum.Enum):
     """The state of a Task."""
@@ -129,6 +130,8 @@ def start(self) -> None:
       result = data.exportTable(self._request_id, self.config)
     elif self.task_type == Task.Type.EXPORT_VIDEO:
       result = data.exportVideo(self._request_id, self.config)
+    elif self.task_type == Task.Type.EXPORT_CLASSIFIER:
+      result = data.exportClassifier(self._request_id, self.config)
     else:
       raise ee_exception.EEException(
           'Unknown Task type "{}"'.format(self.task_type))
@@ -959,6 +962,55 @@ def toDrive(collection, description='myExportVideoTask',
                                             Task.ExportDestination.DRIVE)
       return _create_export_task(config, Task.Type.EXPORT_VIDEO)
 
+  class classifier:
+    """A class with static methods to start classifier export tasks."""
+
+    def __init__(self):
+      """Forbids class instantiation."""
+      raise AssertionError('This class cannot be instantiated.')
+
+    def __new__(cls,
+                classifier,
+                description='myExportClassifierTask',
+                config=None):
+      """Export an EE Classifier.
+
+      Args:
+        classifier: The feature collection to be exported.
+        description: Human-readable name of the task.
+        config: A dictionary that will be copied and used as parameters
+            for the task:
+            - assetId: The destination asset ID.
+      Returns:
+        An unstarted Task that exports the table.
+      """
+      config = (config or {}).copy()
+      return Export.classifier.toAsset(classifier, description, **config)
+
+    # Disable argument usage check; arguments are accessed using locals().
+    # pylint: disable=unused-argument
+    @staticmethod
+    def toAsset(classifier,
+                description='myExportClassifierTask',
+                assetId=None,
+                overwrite=False,
+                **kwargs):
+      """Creates a task to export an EE Image to an EE Asset.
+
+      Args:
+        classifier: The classifier to be exported.
+        description: Human-readable name of the task.
+        assetId: The destination asset ID.
+        overwrite: If an existing asset can be overwritten by this export.
+        **kwargs: Holds other keyword arguments.
+      Returns:
+        An unstarted Task that exports the image as an Earth Engine Asset.
+      """
+      config = _capture_parameters(locals(), ['classifier'])
+      config = _prepare_classifier_export_config(classifier, config,
+                                                 Task.ExportDestination.ASSET)
+      return _create_export_task(config, Task.Type.EXPORT_CLASSIFIER)
+
 # Mapping from file formats to prefixes attached to format specific config.
 FORMAT_PREFIX_MAP = {'GEOTIFF': 'tiff', 'TFRECORD': 'tfrecord'}
 

python/ee/data.py

@@ -1780,6 +1780,33 @@ def exportMap(request_id: str, params: Dict[str, Any]) -> Any:
   )
 
 
+def exportClassifier(request_id: str, params: Dict[str, Any]) -> Any:
+  """Starts a classifier export task.
+
+  This is a low-level method. The higher-level ee.batch.Export.classifier
+  object is generally preferred for initiating classifier exports.
+
+  Args:
+    request_id (string): A unique ID for the task, from newTaskId. If you are
+      using the cloud API, this does not need to be from newTaskId, (though
+      that's a good idea, as it's a good source of unique strings). It can also
+      be empty, but in that case the request is more likely to fail as it cannot
+      be safely retried.
+    params: The object that describes the export task. If you are using the
+      cloud API, this should be an ExportClassifierRequest. However, the
+      "expression" parameter can be the actual Classifier to be exported, not
+      its serialized form.
+
+  Returns:
+    A dict with information about the created task.
+    If you are using the cloud API, this will be an Operation.
+  """
+  params = params.copy()
+  return _prepare_and_run_export(
+      request_id, params, _get_cloud_projects().classifier().export
+  )
+
+
 def _prepare_and_run_export(
     request_id: str, params: Dict[str, Any], export_endpoint: Any
 ) -> Any:

python/ee/oauth.py

@@ -29,7 +29,7 @@
 import google.auth.transport.requests
 
 from ee import data as ee_data
-from ee.ee_exception import EEException
+from ee import ee_exception
 
 
 # Optional imports used for specific shells.
@@ -94,7 +94,7 @@ def _valid_credentials_exist() -> bool:
     creds = ee_data.get_persistent_credentials()
     creds.refresh(google.auth.transport.requests.Request())
     return True
-  except (EEException, google.auth.exceptions.RefreshError):
+  except (ee_exception.EEException, google.auth.exceptions.RefreshError):
     return False
 
 
@@ -213,7 +213,9 @@ def _obtain_and_write_token(
     fetched_info = json.loads(
         urllib.request.urlopen(fetch_client).read().decode())
     if 'error' in fetched_info:
-      raise EEException('Cannot authenticate: %s' % fetched_info['error'])
+      raise ee_exception.EEException(
+          'Cannot authenticate: %s' % fetched_info['error']
+      )
     client_info = {k: fetched_info[k] for k in ['client_id', 'client_secret']}
     scopes = fetched_info.get('scopes') or scopes
   token = request_token(auth_code.strip(), code_verifier, **client_info)
@@ -524,7 +526,8 @@ def __init__(
           scopes=urllib.parse.quote(' '.join(self.scopes)), **request_info)
       self.code_verifier = ':'.join(request_info[k] for k in nonces)
     else:
-      raise EEException('Unknown auth_mode "%s"' % auth_mode)  # pylint:disable=broad-exception-raised
+      # pylint:disable-next=broad-exception-raised
+      raise ee_exception.EEException('Unknown auth_mode "%s"' % auth_mode)
 
   def save_code(self, code: Optional[str] = None) -> None:
     """Fetches auth code if not given, and saves the generated credentials."""

python/ee/tests/algorithms.json

@@ -15289,6 +15289,12 @@
       "description": "The prediction payload size limit in bytes.  Defaults to 1.5MB (1500000 bytes)",
       "optional": true,
       "defaultValue": null
+    }, {
+      "argumentName": "payloadFormat",
+      "type": "String",
+      "description": "The payload format of entries in prediction requests and responses. One of: [\u0027SERIALIZED_TF_TENSORS, \u0027RAW_JSON\u0027, \u0027ND_ARRAYS\u0027]. Defaults to \u0027SERIALIZED_TF_TENSORS\u0027.",
+      "optional": true,
+      "defaultValue": null
     }]
   }, {
     "name": "algorithms/Model.predictImage",

python/pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "earthengine-api"
-version = "0.1.382"
+version = "0.1.383"
 description = "Earth Engine Python API"
 requires-python = ">=3.7"
 keywords = [
@@ -63,6 +63,7 @@ packages = [
 
 [tool.setuptools.package-data]
 ee = [
+  "py.typed",
   "tests/*.py",
   "tests/*.json",
 ]