platform/processingLevel concept-id aliasing, DATASET Constants, constants no longer top level imports

CHANGELOG.md

@@ -28,10 +28,13 @@ and uses [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 ------
 ## [v.7.0.0](https://github.com/asfadmin/Discovery-asf_search/compare/v6.7.3...v.7.0.0)
 ### Added
+- Added `collectionAlias` to `ASFSearchOptions` validator map as config param. Set to `False` to disable concept-id aliasing behaviour for `processingLevel` and `platform`.
 - Adds warning when scenes in stack are missing state vectors, and logs baseline warnings with `ASF_LOGGER`
 - Adds `OPERA-S1-CALIBRATION` entry to `dataset_collections` and corresponding `OPERA_S1_CALIBRATION` constant to `DATASET.py`, used to search for OPERA-S1 `CSLC` and `RTC` calibration data.
 
 ### Changed
+- Constants are no longer top level import, are now accessible through respective modules
+- `processingLevel` and `platform` are now aliased by collection concept-ids, (lists of concept ids by their processing levels/platforms viewable in `dataset.py`), improving search performance and dodging subquery system
 - Baseline stacking no longer excludes products with missing state vectors from final stack, like SearchAPI
 - `OPERA-S1` dataset no longer includes calibration data (moved to new dataset)
 - Adds optional `ASFSession` constructor keyword arguments for new class variables:

asf_search/ASFSearchOptions/config.py

@@ -5,4 +5,5 @@
     'host': INTERNAL.CMR_HOST,
     'provider': INTERNAL.DEFAULT_PROVIDER,
     'session': ASFSession(),
+    'collectionAlias': True
 }

asf_search/ASFSearchOptions/validator_map.py

@@ -66,5 +66,6 @@ def validate(key, value):
     # Config parameters       Parser
     'session':                parse_session,
     'host':                   parse_string,
-    'provider':               parse_string
+    'provider':               parse_string,
+    'collectionAlias':        bool,
 }

asf_search/CMR/__init__.py

@@ -2,4 +2,4 @@
 from .subquery import build_subqueries
 from .translate import translate_product, translate_opts, get_additional_fields
 from .field_map import field_map
-from .datasets import dataset_collections
+from .datasets import dataset_collections, collections_per_platform, collections_by_processing_level, get_concept_id_alias, get_dataset_concept_ids

asf_search/CMR/datasets.py

@@ -1,3 +1,6 @@
+from typing import List
+
+
 dataset_collections = {
     "SENTINEL-1": {
         "SENTINEL-1A_SLC": ["C1214470488-ASF", "C1205428742-ASF", "C1234413245-ASFDEV"],
@@ -327,7 +330,7 @@
 }
 
 collections_per_platform = {
-    "Sentinel-1A": [
+    "SENTINEL-1A": [
         "C1214470488-ASF",
         "C1214470533-ASF",
         "C1214470576-ASF",
@@ -413,7 +416,7 @@
         "C1244598379-ASFDEV",
         "C1240784657-ASFDEV",
     ],
-    "Sentinel-1B": [
+    "SENTINEL-1B": [
         "C1327985661-ASF",
         "C1327985645-ASF",
         "C1595422627-ASF",
@@ -729,7 +732,7 @@
 }
 
 
-collections_by_processing_level: {
+collections_by_processing_level = {
     "SLC": [
         "C1214470488-ASF",
         "C1205428742-ASF",
@@ -1071,3 +1074,40 @@
     "SLOPE": ["C1214408428-ASF", "C1210599503-ASF"],
     "STOKES": ["C1214419355-ASF", "C1210599673-ASF"],
 }
+
+#################### Helper Methods ####################
+
+def get_concept_id_alias(param_list: List[str], collections_dict: dict) -> List[str]:
+    """
+    param: param_list (List[str]): list of search values to alias
+    param: collections_dict (dict): The search value to concept-id dictionary to read from
+
+    returns List[str]: Returns a list of concept-ids that correspond to the given list of search values
+    If any of the search values are not keys in the collections_dict, this will instead returns an empty list. 
+    """
+    concept_id_aliases = []
+    for param in param_list:
+        if alias := collections_dict.get(param):
+            concept_id_aliases.extend(alias)
+        else:
+            return []
+
+    return concept_id_aliases
+
+def get_dataset_concept_ids(datasets: List[str]) -> List[str]:
+    """
+    Returns concept-ids for provided dataset(s)
+    If an invalid datset is provided a ValueError is raised
+
+    :param `datasets` (`List[str]`): a list of datasets to grab concept-ids for
+    :returns `List[str]`: the list of concept-ids associated with the given datasets
+    """
+    output = []
+    for dataset in datasets:
+        if collections_by_short_name := dataset_collections.get(dataset):
+            for concept_ids in collections_by_short_name.values():
+                output.extend(concept_ids)
+        else:
+            raise ValueError(f'Could not find dataset named "{dataset}" provided for dataset keyword.')
+
+    return output

asf_search/CMR/subquery.py

@@ -1,57 +1,111 @@
-from typing import List
+from typing import List, Optional, Tuple
 import itertools
 from copy import copy
 
 from asf_search.ASFSearchOptions import ASFSearchOptions
 from asf_search.constants import CMR_PAGE_SIZE
 
+from asf_search.CMR.datasets import collections_by_processing_level, collections_per_platform, dataset_collections, get_concept_id_alias, get_dataset_concept_ids
+from numpy import intersect1d, union1d
 
 def build_subqueries(opts: ASFSearchOptions) -> List[ASFSearchOptions]:
     """
     Build a list of sub-queries using the cartesian product of all the list parameters described by opts
 
     :param opts: The search options to split into sub-queries
-
     :return list: A list of ASFSearchOptions objects
     """
     params = dict(opts)
 
     # Break out two big list offenders into manageable chunks
-    if params.get('granule_list') is not None:
-        params['granule_list'] = chunk_list(params['granule_list'], CMR_PAGE_SIZE)
-    if params.get('product_list') is not None:
-        params['product_list'] = chunk_list(params['product_list'], CMR_PAGE_SIZE)
+    for chunked_key in ['granule_list', 'product_list']:
+        if params.get(chunked_key) is not None:
+            params[chunked_key] = chunk_list(params[chunked_key], CMR_PAGE_SIZE)
 
     list_param_names = ['platform', 'season', 'collections', 'dataset']  # these parameters will dodge the subquery system
     skip_param_names = ['maxResults']# these params exist in opts, but shouldn't be passed on to subqueries at ALL
 
-    params = dict([ (k, v) for k, v in params.items() if k not in skip_param_names ])
-
+    collections, aliased_keywords = get_keyword_concept_ids(params, opts.collectionAlias)
+    params['collections'] = list(union1d(collections, params.get('collections', [])))
+
+    for keyword in [*skip_param_names, *aliased_keywords]:
+        params.pop(keyword, None)
+
     subquery_params, list_params = {}, {}
-    for k, v in params.items():
-        if k in list_param_names:
-            list_params[k] = v
+    for key, value in params.items():
+        if key in list_param_names:
+            list_params[key] = value
         else:
-            subquery_params[k] = v
-
+            subquery_params[key] = value
+    
     sub_queries = cartesian_product(subquery_params)
+    return [_build_subquery(query, opts, list_params) for query in sub_queries]
 
-    final_sub_query_opts = []
-    for query in sub_queries:
-        q = dict()
-        for p in query:
-            q.update(p)
-        q['provider'] = opts.provider
-        q['host'] = opts.host
-        q['session'] = copy(opts.session)
-        for key in list_params.keys():
-            q[key] = list_params[key]
-
-        final_sub_query_opts.append(ASFSearchOptions(**q))
-
-    return final_sub_query_opts
+def _build_subquery(query: List[Tuple[dict]], opts: ASFSearchOptions, list_params: dict) -> ASFSearchOptions:
+    """
+    Composes query dict and list params into new ASFSearchOptions object
 
+    param: query: the cartesian search query options
+    param: opts: the search options to pull config options from (provider, host, session)
+    param: list_params: the subquery parameters
+    """
+    q = dict()
+    for p in query:
+        q.update(p)
+    return ASFSearchOptions(
+        **q,
+         provider= opts.provider,
+         host= opts.host,
+         session= copy(opts.session),
+         **list_params
+    )
+
+def get_keyword_concept_ids(params: dict, use_collection_alias: bool=True) -> dict:
+    """
+    Gets concept-ids for dataset, platform, processingLevel keywords
+    processingLevel is scoped by dataset or platform concept-ids when available
+
+    : param params: search parameter dictionary pre-CMR translation
+    : param use_collection_alias: whether or not to alias platform and processingLevel with concept-ids
+    : returns two lists: 
+        - list of concept-ids for dataset, platform, and processingLevel
+        - list of aliased keywords to remove from final parameters
+    """
+    collections = []
+    aliased_keywords = []
+
+    if use_collection_alias:
+        if 'processingLevel' in params.keys():
+            collections = get_concept_id_alias(params.get('processingLevel'), collections_by_processing_level)
+            if len(collections):
+                aliased_keywords.append('processingLevel')
+
+        if 'platform' in params.keys():
+            platform_concept_ids = get_concept_id_alias(
+                    [platform.upper() for platform in params.get('platform')], 
+                    collections_per_platform
+                )
+            if len(platform_concept_ids):
+                aliased_keywords.append('platform')
+                collections = _get_intersection(platform_concept_ids, collections)
+
+    if 'dataset' in params.keys():
+        aliased_keywords.append('dataset')
+        dataset_concept_ids = get_dataset_concept_ids(params.get('dataset'))
+        collections = _get_intersection(dataset_concept_ids, collections)
+
+    return collections, aliased_keywords
 
+def _get_intersection(keyword_concept_ids: List[str], intersecting_ids: List[str]) -> List[str]:
+    """
+    Returns the intersection between two lists. If the second list is empty the first list
+    is return unchaged
+    """
+    if len(intersecting_ids):
+        return list(intersect1d(intersecting_ids, keyword_concept_ids))
+
+    return keyword_concept_ids
+
 def chunk_list(source: List, n: int) -> List:
     """
     Breaks a longer list into a list of lists, each of length n
@@ -70,7 +124,7 @@ def cartesian_product(params):
     return p
 
 
-def format_query_params(params):
+def format_query_params(params) -> List[List[dict]]:
     listed_params = []
 
     for param_name, param_val in params.items():
@@ -80,7 +134,7 @@ def format_query_params(params):
     return listed_params
 
 
-def translate_param(param_name, param_val):
+def translate_param(param_name, param_val) -> List[dict]:
     param_list = []
 
     if not isinstance(param_val, list):

asf_search/CMR/translate.py

@@ -1,13 +1,14 @@
 from datetime import datetime
 from typing import Any, Dict, List
 from asf_search.ASFSearchOptions import ASFSearchOptions
+from asf_search.CMR.datasets import get_concept_id_alias
 from asf_search.constants import CMR_PAGE_SIZE
 import re
 from shapely import wkt
 from shapely.geometry import Polygon
 from shapely.geometry.base import BaseGeometry
 from .field_map import field_map
-from .datasets import dataset_collections
+from .datasets import dataset_collections, collections_per_platform
 
 import logging
 
@@ -48,19 +49,6 @@ def translate_opts(opts: ASFSearchOptions) -> list:
     if any(key in dict_opts for key in ['start', 'end', 'season']):
         dict_opts = fix_date(dict_opts)
 
-    if 'dataset' in dict_opts:
-        if 'collections' not in dict_opts:
-            dict_opts['collections'] = []
-
-        for dataset in dict_opts['dataset']:
-            if collections_by_short_name := dataset_collections.get(dataset):
-                for concept_ids in collections_by_short_name.values():
-                    dict_opts['collections'].extend(concept_ids)
-            else:
-                raise ValueError(f'Could not find dataset named "{dataset}" provided for dataset keyword.')
-
-        dict_opts.pop('dataset')
-
     # convert the above parameters to a list of key/value tuples
     cmr_opts = []
     for (key, val) in dict_opts.items():
@@ -99,15 +87,10 @@ def translate_opts(opts: ASFSearchOptions) -> list:
 
     return cmr_opts
 
-
 def should_use_asf_frame(cmr_opts):
     asf_frame_platforms = ['SENTINEL-1A', 'SENTINEL-1B', 'ALOS']
-    asf_frame_datasets = ['SENTINEL-1', 'OPERA-S1', 'SLC-BURST', 'ALOS PALSAR', 'ALOS AVNIR-2']
 
-    asf_frame_collections = []
-    for dataset in asf_frame_datasets:
-        for concept_ids in dataset_collections.get(dataset).values():
-            asf_frame_collections.extend(concept_ids)
+    asf_frame_collections = get_concept_id_alias(asf_frame_platforms, collections_per_platform)
 
     return any([
         p[0] == 'platform[]' and p[1].upper() in asf_frame_platforms

asf_search/__init__.py

@@ -23,7 +23,7 @@
 from .ASFProduct import ASFProduct
 from .ASFSearchResults import ASFSearchResults
 from .ASFSearchOptions import ASFSearchOptions, validators
-from .constants import *
+from .constants import BEAMMODE, FLIGHT_DIRECTION, INSTRUMENT, PLATFORM, POLARIZATION, PRODUCT_TYPE, INTERNAL, DATASET
 from .exceptions import *
 from .health import *
 from .search import *

asf_search/search/error_reporting.py

@@ -1,5 +1,6 @@
 from typing import Dict
-from asf_search import ASFSearchOptions, ERROR_REPORTING_ENDPOINT
+from asf_search import ASFSearchOptions
+from asf_search import INTERNAL
 import requests
 import logging
 
@@ -19,7 +20,7 @@ def report_search_error(search_options: ASFSearchOptions, message: str):
     message=f"Error Message: {str(message)}\nUser Agent: {user_agent} \
     \nSearch Options: {{\n{search_options_list}\n}}"
 
-    response = requests.post(f'https://{ERROR_REPORTING_ENDPOINT}', data={'Message': "This error message and info was automatically generated:\n\n" + message})
+    response = requests.post(f'https://{INTERNAL.ERROR_REPORTING_ENDPOINT}', data={'Message': "This error message and info was automatically generated:\n\n" + message})
 
     try:
         response.raise_for_status()

asf_search/search/search_generator.py

@@ -75,7 +75,10 @@ def search_generator(
     if maxResults is not None and \
         (getattr(opts, 'granule_list', False) or getattr(opts, 'product_list', False)):
             raise ValueError("Cannot use maxResults along with product_list/granule_list.")
-
+
+    if opts.dataset is not None and opts.platform is not None:
+        raise ValueError("Cannot use dataset along with platform keyword in search.")
+
     preprocess_opts(opts)
 
     url = '/'.join(s.strip('/') for s in [f'https://{opts.host}', f'{INTERNAL.CMR_GRANULE_PATH}'])

examples/1-Basic_Overview.ipynb

@@ -419,7 +419,7 @@
    "source": [
     "# asf-search queries CMR with page sizes of 500, \n",
     "# so setting maxResults=1000 means asf-search will have to query cmr twice, each time returning 500 products\n",
-    "large_results_generator = asf.search_generator(maxResults=1000, platform=asf.SENTINEL1A)\n",
+    "large_results_generator = asf.search_generator(maxResults=1000, platform=asf.PLATFORM.SENTINEL1A)\n",
     "\n",
     "with open(\"search_results.metalink\", \"w\") as f:\n",
     "    f.writelines(asf.export.results_to_metalink(large_results_generator))"

examples/5-Download.ipynb

@@ -220,7 +220,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "results_with_zips = asf.search(platform=asf.constants.PLATFORM.SENTINEL1, processingLevel=asf.constants.PRODUCT_TYPE.GRD_HD, maxResults=250)\n",
+    "results_with_zips = asf.search(platform=asf.PLATFORM.SENTINEL1, processingLevel=asf.PRODUCT_TYPE.GRD_HD, maxResults=250)\n",
     "\n",
     "with results_with_zips[0].remotezip(session=user_pass_session) as z:\n",
     "    file_paths = [file.filename for file in z.filelist if file.filename.endswith('.tiff')]\n",