From 07ead8977ae0f591afcb2660102895e4f47abbf1 Mon Sep 17 00:00:00 2001 From: Victoria McDonald <49625194+torimcd@users.noreply.github.com> Date: Thu, 1 Aug 2024 11:35:00 -0700 Subject: [PATCH] issue-193: Add Dynamo DB Table for SWOT Prior Lakes (#209) * add code to handle prior lakes shapefiles, add test prior lake data * update terraform to add prior lake table * fix tests, change to smaller test data file, changelog * linting * reconfigure main load_data method to make more readable and pass linting * lint * lint * fix string casting to lower storage req & update test responses to handle different rounding pattern in coords * update load benchmarking function for linting and add unit test * try parent collection for lakes * update version parsing for parent collection * fix case error * fix lake id reference * add logging to troubleshoot too large features * add item size logging and remove error raise for batch write * clean up logging statements & move numeric_columns assignment * update batch logging statement * Rename constant * Fix temp dir security risk https://rules.sonarsource.com/python/RSPEC-5443/ * Fix temp dir security risk https://rules.sonarsource.com/python/RSPEC-5443/ * fix code coverage calculation --------- Co-authored-by: Frank Greguska <89428916+frankinspace@users.noreply.github.com> --- CHANGELOG.md | 1 + .../{swot_reach_node_shp.py => swot_shp.py} | 83 +- hydrocron/db/load_data.py | 82 +- hydrocron/db/schema.py | 17 +- hydrocron/utils/constants.py | 86 +- pyproject.toml | 4 + terraform/hydrocron-dynamo.tf | 27 + terraform/hydrocron-iam.tf | 3 +- tests/conftest.py | 15 +- ...0240713T111741_20240713T112027_PIC0_01.zip | Bin 0 -> 3405941 bytes ...0240713T111741_20240713T112027_PIC0_01.dbf | Bin 0 -> 6662438 bytes ...0240713T111741_20240713T112027_PIC0_01.prj | 1 + ...0240713T111741_20240713T112027_PIC0_01.shp | Bin 0 -> 4162800 bytes ...713T111741_20240713T112027_PIC0_01.shp.xml | 550 ++++++++ ...0240713T111741_20240713T112027_PIC0_01.shx | Bin 0 -> 43212 bytes tests/test_api.py | 3 +- tests/test_connection.py | 3 +- tests/test_data/api_query_results_csv.csv | 2 +- .../test_data/api_query_results_geojson.json | 1132 ++++++++--------- .../api_query_results_geojson_compact.json | 1132 ++++++++--------- tests/test_hydrocron_database.py | 24 +- tests/test_io_swot_reach_node_shp.py | 61 +- tests/test_track_ingest.py | 2 +- 23 files changed, 1975 insertions(+), 1253 deletions(-) rename hydrocron/db/io/{swot_reach_node_shp.py => swot_shp.py} (68%) create mode 100644 tests/data/SWOT_L2_HR_LakeSP_Prior_018_100_GR_20240713T111741_20240713T112027_PIC0_01.zip create mode 100644 tests/data/SWOT_L2_HR_LakeSP_Prior_018_100_GR_20240713T111741_20240713T112027_PIC0_01/SWOT_L2_HR_LakeSP_Prior_018_100_GR_20240713T111741_20240713T112027_PIC0_01.dbf create mode 100644 tests/data/SWOT_L2_HR_LakeSP_Prior_018_100_GR_20240713T111741_20240713T112027_PIC0_01/SWOT_L2_HR_LakeSP_Prior_018_100_GR_20240713T111741_20240713T112027_PIC0_01.prj create mode 100644 tests/data/SWOT_L2_HR_LakeSP_Prior_018_100_GR_20240713T111741_20240713T112027_PIC0_01/SWOT_L2_HR_LakeSP_Prior_018_100_GR_20240713T111741_20240713T112027_PIC0_01.shp create mode 100644 tests/data/SWOT_L2_HR_LakeSP_Prior_018_100_GR_20240713T111741_20240713T112027_PIC0_01/SWOT_L2_HR_LakeSP_Prior_018_100_GR_20240713T111741_20240713T112027_PIC0_01.shp.xml create mode 100644 tests/data/SWOT_L2_HR_LakeSP_Prior_018_100_GR_20240713T111741_20240713T112027_PIC0_01/SWOT_L2_HR_LakeSP_Prior_018_100_GR_20240713T111741_20240713T112027_PIC0_01.shx diff --git a/CHANGELOG.md b/CHANGELOG.md index ec083570..3a0c3a73 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -8,6 +8,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0 ### Added - Issue 198 - Implement track ingest lambda function CMR and Hydrocron queries + - Issue 193 - Add new Dynamo table for prior lake data ### Changed ### Deprecated ### Removed diff --git a/hydrocron/db/io/swot_reach_node_shp.py b/hydrocron/db/io/swot_shp.py similarity index 68% rename from hydrocron/db/io/swot_reach_node_shp.py rename to hydrocron/db/io/swot_shp.py index 4dc2e468..6d11234b 100644 --- a/hydrocron/db/io/swot_reach_node_shp.py +++ b/hydrocron/db/io/swot_shp.py @@ -1,8 +1,9 @@ """ -Unpacks SWOT Reach & Node Shapefiles +Unpacks SWOT Shapefiles """ import os.path import json +import tempfile from datetime import datetime, timezone from importlib import resources import xml.etree.ElementTree as ET @@ -20,7 +21,7 @@ def read_shapefile(filepath, obscure_data, columns, s3_resource=None): """ - Reads a SWOT River Reach shapefile packaged as a zip + Reads a SWOT shapefile packaged as a zip Parameters ---------- @@ -41,34 +42,36 @@ def read_shapefile(filepath, obscure_data, columns, s3_resource=None): to the database table """ filename = os.path.basename(filepath) - lambda_temp_file = '/tmp/' + filename - if filepath.startswith('s3'): - bucket_name, key = filepath.replace("s3://", "").split("/", 1) - logging.info("Opening granule %s from bucket %s", key, bucket_name) + with tempfile.TemporaryDirectory() as lambda_temp_dir_name: + lambda_temp_file = os.path.join(lambda_temp_dir_name, filename) + if filepath.startswith('s3'): + bucket_name, key = filepath.replace("s3://", "").split("/", 1) + logging.info("Opening granule %s from bucket %s", key, bucket_name) - s3_resource.Bucket(bucket_name).download_file(key, lambda_temp_file) + s3_resource.Bucket(bucket_name).download_file(key, lambda_temp_file) - shp_file = gpd.read_file('zip://' + lambda_temp_file) - with zipfile.ZipFile(lambda_temp_file) as archive: - shp_xml_tree = ET.fromstring(archive.read(filename[:-4] + ".shp.xml")) + shp_file = gpd.read_file('zip://' + lambda_temp_file) + with zipfile.ZipFile(lambda_temp_file) as archive: + shp_xml_tree = ET.fromstring(archive.read(filename[:-4] + ".shp.xml")) - elif filepath.startswith('https'): - _, bucket_name, key = filepath.replace("https://", "").split("/", 2) - logging.info("Opening granule %s from bucket %s", key, bucket_name) + elif filepath.startswith('https'): + _, bucket_name, key = filepath.replace("https://", "").split("/", 2) + logging.info("Opening granule %s from bucket %s", key, bucket_name) - s3_resource.Bucket(bucket_name).download_file(key, lambda_temp_file) + s3_resource.Bucket(bucket_name).download_file(key, lambda_temp_file) - shp_file = gpd.read_file('zip://' + lambda_temp_file) - with zipfile.ZipFile(lambda_temp_file) as archive: - shp_xml_tree = ET.fromstring(archive.read(filename[:-4] + ".shp.xml")) - else: - shp_file = gpd.read_file('zip://' + filepath) - with zipfile.ZipFile(filepath) as archive: - shp_xml_tree = ET.fromstring(archive.read(filename[:-4] + ".shp.xml")) + shp_file = gpd.read_file('zip://' + lambda_temp_file) + with zipfile.ZipFile(lambda_temp_file) as archive: + shp_xml_tree = ET.fromstring(archive.read(filename[:-4] + ".shp.xml")) + else: + shp_file = gpd.read_file('zip://' + filepath) + with zipfile.ZipFile(filepath) as archive: + shp_xml_tree = ET.fromstring(archive.read(filename[:-4] + ".shp.xml")) - numeric_columns = shp_file[columns].select_dtypes(include=[np.number]).columns if obscure_data: + numeric_columns = shp_file[columns].select_dtypes(include=[np.number]).columns + shp_file[numeric_columns] = np.where( (np.rint(shp_file[numeric_columns]) != -999) & (np.rint(shp_file[numeric_columns]) != -99999999) & @@ -76,7 +79,6 @@ def read_shapefile(filepath, obscure_data, columns, s3_resource=None): np.random.default_rng().integers(low=2, high=10)*shp_file[numeric_columns], shp_file[numeric_columns]) - shp_file = shp_file.astype(str) filename_attrs = parse_from_filename(filename) xml_attrs = parse_metadata_from_shpxml(shp_xml_tree) @@ -84,15 +86,12 @@ def read_shapefile(filepath, obscure_data, columns, s3_resource=None): attributes = filename_attrs | xml_attrs items = assemble_attributes(shp_file, attributes) - if os.path.exists(lambda_temp_file): - os.remove(lambda_temp_file) - return items def parse_metadata_from_shpxml(xml_elem): """ - Read the SWORD version number from the shp.xml file + Read the prior database (SWORD or PLD) version number from the shp.xml file and add to the database fields Parameters @@ -108,14 +107,16 @@ def parse_metadata_from_shpxml(xml_elem): # get SWORD version for globs in xml_elem.findall('global_attributes'): prior_db_files = globs.find('xref_prior_river_db_files').text + metadata_attrs = {'sword_version': prior_db_files[-5:-3]} - metadata_attrs = { - 'sword_version': prior_db_files[-5:-3] - } + # get PLD version + for globs in xml_elem.findall('global_metadata'): + prior_db_files = globs.find('xref_prior_lake_db_file').text + metadata_attrs = {'PLD_version': prior_db_files[-10:-7]} # get units on fields that have them for child in xml_elem: - if child.tag == 'attributes': + if child.tag in ('attributes', 'attribute_metadata'): for field in child: try: units = field.find('units').text @@ -130,27 +131,29 @@ def parse_metadata_from_shpxml(xml_elem): return metadata_attrs -def assemble_attributes(file_as_str, attributes): +def assemble_attributes(geodf, attributes): """ Helper function to concat file attributes to records Parameters ---------- - file_as_str : string - The file records as a string + geodf : geodataframe + The file records as a geodataframe attributes : dict A dictionary of attributes to concatenate """ items = [] - - for _index, row in file_as_str.iterrows(): + # rework to use dataframe instead of file as string + for _index, row in geodf.iterrows(): shp_attrs = json.loads( row.to_json(default_handler=str)) item_attrs = shp_attrs | attributes + + item_attrs = {key: str(item_attrs[key]) for key in item_attrs.keys()} items.append(item_attrs) return items @@ -177,14 +180,18 @@ def parse_from_filename(filename): collection = "" collection_version = "" - if 'Reach' in filename: + if 'RiverSP_Reach' in filename: collection = constants.SWOT_REACH_COLLECTION_NAME collection_version = constants.SWOT_REACH_COLLECTION_VERSION - if 'Node' in filename: + if 'RiverSP_Node' in filename: collection = constants.SWOT_NODE_COLLECTION_NAME collection_version = constants.SWOT_NODE_COLLECTION_VERSION + if 'LakeSP_Prior' in filename: + collection = constants.SWOT_PRIOR_LAKE_COLLECTION_NAME + collection_version = constants.SWOT_PRIOR_LAKE_COLLECTION_VERSION + filename_attrs = { 'cycle_id': filename_components[5], 'pass_id': filename_components[6], diff --git a/hydrocron/db/load_data.py b/hydrocron/db/load_data.py index c2f9e8ad..257204a2 100755 --- a/hydrocron/db/load_data.py +++ b/hydrocron/db/load_data.py @@ -11,7 +11,7 @@ from botocore.exceptions import ClientError from hydrocron.db import HydrocronTable -from hydrocron.db.io import swot_reach_node_shp +from hydrocron.db.io import swot_shp from hydrocron.utils import connection from hydrocron.utils import constants @@ -49,6 +49,9 @@ def lambda_handler(event, _): # noqa: E501 # pylint: disable=W0613 case constants.SWOT_NODE_TABLE_NAME: collection_shortname = constants.SWOT_NODE_COLLECTION_NAME feature_type = 'Node' + case constants.SWOT_PRIOR_LAKE_TABLE_NAME: + collection_shortname = constants.SWOT_PRIOR_LAKE_COLLECTION_NAME + feature_type = 'LakeSP_prior' case constants.DB_TEST_TABLE_NAME: collection_shortname = constants.SWOT_REACH_COLLECTION_NAME feature_type = 'Reach' @@ -95,6 +98,9 @@ def granule_handler(event, _): if ("Node" in granule_path) & (table_name != constants.SWOT_NODE_TABLE_NAME): raise TableMisMatch(f"Error: Cannot load Node data into table: '{table_name}'") + if ("LakeSP_Prior" in granule_path) & (table_name != constants.SWOT_PRIOR_LAKE_TABLE_NAME): + raise TableMisMatch(f"Error: Cannot load Prior Lake data into table: '{table_name}'") + logging.info("Value of load_benchmarking_data is: %s", load_benchmarking_data) obscure_data = "true" in os.getenv("OBSCURE_DATA").lower() @@ -102,7 +108,7 @@ def granule_handler(event, _): if load_benchmarking_data == "True": logging.info("Loading benchmarking data") - items = swot_reach_node_shp.load_benchmarking_data() + items = swot_shp.load_benchmarking_data() else: logging.info("Setting up S3 connection") s3_resource = connection.s3_resource @@ -158,6 +164,18 @@ def cnm_handler(event, _): InvocationType='Event', Payload=event2) + if 'LakeSP_Prior' in granule_uri: + event2 = ('{"body": {"granule_path": "' + granule_uri + + '","table_name": "' + constants.SWOT_PRIOR_LAKE_TABLE_NAME + + '","load_benchmarking_data": "' + load_benchmarking_data + '"}}') + + logging.info("Invoking granule load lambda with event json %s", str(event2)) + + lambda_client.invoke( + FunctionName=os.environ['GRANULE_LAMBDA_FUNCTION_NAME'], + InvocationType='Event', + Payload=event2) + def find_new_granules(collection_shortname, start_date, end_date): """ @@ -208,7 +226,7 @@ def read_data(granule_path, obscure_data, s3_resource=None): if 'Reach' in granule_path: logging.info("Start reading reach shapefile") - items = swot_reach_node_shp.read_shapefile( + items = swot_shp.read_shapefile( granule_path, obscure_data, constants.REACH_DATA_COLUMNS, @@ -216,12 +234,20 @@ def read_data(granule_path, obscure_data, s3_resource=None): if 'Node' in granule_path: logging.info("Start reading node shapefile") - items = swot_reach_node_shp.read_shapefile( + items = swot_shp.read_shapefile( granule_path, obscure_data, constants.NODE_DATA_COLUMNS, s3_resource=s3_resource) + if 'LakeSP_Prior' in granule_path: + logging.info("Start reading prior lake shapefile") + items = swot_shp.read_shapefile( + granule_path, + obscure_data, + constants.PRIOR_LAKE_DATA_COLUMNS, + s3_resource=s3_resource) + return items @@ -247,33 +273,27 @@ def load_data(dynamo_resource, table_name, items): raise MissingTable(f"Hydrocron table '{table_name}' does not exist.") from err raise err - if hydrocron_table.table_name == constants.SWOT_REACH_TABLE_NAME: - - if len(items) > 5: - logging.info("Batch adding %s reach items", len(items)) - for i in range(5): - logging.info("Item reach_id: %s", items[i]['reach_id']) - hydrocron_table.batch_fill_table(items) - - else: - logging.info("Adding reach items to table individually") - for item_attrs in items: - logging.info("Item reach_id: %s", item_attrs['reach_id']) - hydrocron_table.add_data(**item_attrs) - - elif hydrocron_table.table_name == constants.SWOT_NODE_TABLE_NAME: - - if len(items) > 5: - logging.info("Batch adding %s node items", len(items)) - for i in range(5): - logging.info("Item node_id: %s", items[i]['node_id']) - hydrocron_table.batch_fill_table(items) + match hydrocron_table.table_name: + case constants.SWOT_REACH_TABLE_NAME: + feature_name = 'reach' + feature_id = feature_name + '_id' + case constants.SWOT_NODE_TABLE_NAME: + feature_name = 'node' + feature_id = feature_name + '_id' + case constants.SWOT_PRIOR_LAKE_TABLE_NAME: + feature_name = 'prior_lake' + feature_id = 'lake_id' + case _: + logging.warning('Items cannot be parsed, file reader not implemented for table %s', hydrocron_table.table_name) - else: - logging.info("Adding node items to table individually") - for item_attrs in items: - logging.info("Item node_id: %s", item_attrs['node_id']) - hydrocron_table.add_data(**item_attrs) + if len(items) > 5: + logging.info("Batch adding %s %s items. First 5 feature ids in batch: ", len(items), feature_name) + for i in range(5): + logging.info("Item %s: %s", feature_id, items[i][feature_id]) + hydrocron_table.batch_fill_table(items) else: - logging.warning('Items cannot be parsed, file reader not implemented for table %s', hydrocron_table.table_name) + logging.info("Adding %s items to table individually", feature_name) + for item_attrs in items: + logging.info("Item %s: %s", feature_id, item_attrs[feature_id]) + hydrocron_table.add_data(**item_attrs) diff --git a/hydrocron/db/schema.py b/hydrocron/db/schema.py index 7913a25b..dd6f9660 100644 --- a/hydrocron/db/schema.py +++ b/hydrocron/db/schema.py @@ -2,6 +2,7 @@ Hydrocron Table module """ import logging +import sys from botocore.exceptions import ClientError from boto3.dynamodb.conditions import Key @@ -114,12 +115,24 @@ def batch_fill_table(self, items): try: with table.batch_writer() as writer: for item in items: - writer.put_item(Item=item) + logger.info( + "Item %s size: %s", + item[self.partition_key_name], + str(sys.getsizeof(item)) + ) + if sys.getsizeof(item) < 300000: + writer.put_item(Item=item) + else: + logger.Warning( + "Item too large, could not load: %s %s", + self.partition_key_name, + item[self.partition_key_name] + ) + continue logger.info("Loaded data into table %s.", table.name) except ClientError: logger.exception("Couldn't load data into table %s.", table.name) - raise def run_query(self, partition_key, sort_key=None): """ diff --git a/hydrocron/utils/constants.py b/hydrocron/utils/constants.py index be7d7538..e8f20586 100644 --- a/hydrocron/utils/constants.py +++ b/hydrocron/utils/constants.py @@ -7,17 +7,19 @@ # ----------------- # # TESTING CONSTANTS # # ----------------- # -TEST_SHAPEFILE_PATH = os.path.abspath(os.path.join( + +# -------- River Reach +TEST_REACH_SHAPEFILE_PATH = os.path.abspath(os.path.join( os.path.dirname(os.path.realpath(__file__)), '../..', 'tests', 'data', 'SWOT_L2_HR_RiverSP_Reach_548_011_NA_20230610T193337_20230610T193344_PIA1_01.zip' # noqa E501 )) -TEST_FILENAME = ( +TEST_REACH_FILENAME = ( "SWOT_L2_HR_RiverSP_Reach_548_011_NA_" "20230610T193337_20230610T193344_PIA1_01.zip") -TEST_ITEM_DICT = { +TEST_REACH_ITEM_DICT = { "reach_id": "71224100223", "time": "739741183.129", "time_str": "2023-06-10T19:39:43Z", @@ -28,33 +30,70 @@ } DB_TEST_TABLE_NAME = "hydrocron-swot-test-table" -API_TEST_TABLE_NAME = "hydrocron-swot-reach-table" -TEST_PARTITION_KEY_NAME = 'reach_id' -TEST_SORT_KEY_NAME = 'range_start_time' +API_TEST_REACH_TABLE_NAME = "hydrocron-swot-reach-table" +TEST_REACH_PARTITION_KEY_NAME = 'reach_id' +TEST_REACH_SORT_KEY_NAME = 'range_start_time' TEST_REACH_ID_VALUE = '71224100223' -TEST_TIME_VALUE = '2023-06-10T19:33:37Z' -TEST_WSE_VALUE = '286.2983' -TEST_SWORD_VERSION_VALUE = '15' -TEST_UNITS_FIELD = 'p_lat_units' -TEST_UNITS = 'degrees_north' +TEST_REACH_TIME_VALUE = '2023-06-10T19:33:37Z' +TEST_REACH_WSE_VALUE = '286.2983' +TEST_REACH_SWORD_VERSION_VALUE = '15' +TEST_REACH_UNITS_FIELD = 'p_lat_units' +TEST_REACH_UNITS = 'degrees_north' + +# -------- Prior Lakes +TEST_PLAKE_SHAPEFILE_PATH = os.path.abspath(os.path.join( + os.path.dirname(os.path.realpath(__file__)), + '../..', 'tests', 'data', + 'SWOT_L2_HR_LakeSP_Prior_018_100_GR_20240713T111741_20240713T112027_PIC0_01.zip' # noqa E501 +)) + +TEST_PLAKE_FILENAME = ( + "SWOT_L2_HR_LakeSP_Prior_018_100_GR_20240713T111741_20240713T112027_PIC0_01.zip") + +TEST_PLAKE_ITEM_DICT = { + "lake_id": "9130047472", + "time": "774184696.644", + "time_str": "2024-07-13T11:18:16Z", + "wse": "307.482", + "cycle_id": "018", + "PLD_version": "105", + "area_total_units": "km^2" +} + +DB_TEST_PLAKE_TABLE_NAME = "hydrocron-swot-testlake-table" +API_TEST_PLAKE_TABLE_NAME = "hydrocron-swot-prior-lake-table" +TEST_PLAKE_PARTITION_KEY_NAME = 'lake_id' +TEST_PLAKE_SORT_KEY_NAME = 'range_start_time' +TEST_PLAKE_ID_VALUE = '9130047472' +TEST_PLAKE_TIME_VALUE = '2024-07-13T11:18:16Z' +TEST_PLAKE_WSE_VALUE = '307.482' +TEST_PLAKE_PLD_VERSION_VALUE = '105' +TEST_PLAKE_UNITS_FIELD = 'area_total' +TEST_PLAKE_UNITS = 'km^2' # ------------ # # PROD CONSTANTS # # ------------ # SWOT_REACH_TABLE_NAME = "hydrocron-swot-reach-table" SWOT_NODE_TABLE_NAME = "hydrocron-swot-node-table" +SWOT_PRIOR_LAKE_TABLE_NAME = "hydrocron-swot-prior-lake-table" SWOT_REACH_COLLECTION_NAME = "SWOT_L2_HR_RiverSP_2.0" SWOT_NODE_COLLECTION_NAME = "SWOT_L2_HR_RiverSP_2.0" +SWOT_PRIOR_LAKE_COLLECTION_NAME = "SWOT_L2_HR_LakeSP_2.0" SWOT_REACH_COLLECTION_VERSION = SWOT_REACH_COLLECTION_NAME[19:] SWOT_NODE_COLLECTION_VERSION = SWOT_NODE_COLLECTION_NAME[19:] +SWOT_PRIOR_LAKE_COLLECTION_VERSION = SWOT_PRIOR_LAKE_COLLECTION_NAME[18:] SWOT_REACH_PARTITION_KEY = "reach_id" SWOT_NODE_PARTITION_KEY = "node_id" +SWOT_PRIOR_LAKE_PARTITION_KEY = "lake_id" SWOT_REACH_SORT_KEY = "range_start_time" SWOT_NODE_SORT_KEY = "range_start_time" +SWOT_PRIOR_LAKE_SORT_KEY = "range_start_time" FIELDNAME_REACH_ID = 'reach_id' +FIELDNAME_LAKE_ID = 'lake_id' FIELDNAME_TIME = 'time' FIELDNAME_TIME_STR = 'time_str' FIELDNAME_WSE = 'wse' @@ -62,6 +101,7 @@ FIELDNAME_P_LON = 'p_lon' FIELDNAME_P_LAT = 'p_lat' FIELDNAME_SWORD_VERSION = 'sword_version' +FIELDNAME_PLD_VERSION = 'PLD_version' REACH_DATA_COLUMNS = [ 'wse', 'wse_u', 'wse_r_u', 'wse_c', 'wse_c_u', @@ -104,6 +144,16 @@ 'dry_trop_c', 'wet_trop_c', 'iono_c', 'xovr_cal_c' ] +PRIOR_LAKE_DATA_COLUMNS = [ + 'wse', 'wse_u', 'wse_r_u', 'wse_std', + 'area_total', 'area_tot_u', 'area_detct', 'area_det_u', + 'layovr_val', 'xtrk_dist', 'ds1_l', 'ds1_l_u', 'ds1_q', 'ds1_q_u', + 'ds2_l', 'ds2_l_u', 'ds2_q', 'ds2_q_u', + 'quality_f', 'dark_frac', 'ice_clim_f', 'ice_dyn_f', 'partial_f', + 'xovr_cal_q', 'geoid_hght', 'solid_tide', 'load_tidef', 'load_tideg', 'pole_tide', + 'dry_trop_c', 'wet_trop_c', 'iono_c', 'xovr_cal_c' +] + REACH_ALL_COLUMNS = [ 'reach_id', 'time', 'time_tai', 'time_str', 'p_lat', 'p_lon', 'river_name', 'wse', 'wse_u', 'wse_r_u', 'wse_c', 'wse_c_u', @@ -157,3 +207,17 @@ 'cycle_id', 'pass_id', 'continent_id', 'range_start_time', 'range_end_time', 'crid', 'geometry', 'sword_version', 'collection_shortname', 'crid' ] + +PRIOR_LAKE_ALL_COLUMNS = [ + 'lake_id', 'reach_id', 'obs_id', 'overlap', 'n_overlap', + 'time', 'time_tai', 'time_str', 'wse', 'wse_u', 'wse_r_u', 'wse_std', + 'area_total', 'area_tot_u', 'area_detct', 'area_det_u', + 'layovr_val', 'xtrk_dist', 'ds1_l', 'ds1_l_u', 'ds1_q', 'ds1_q_u', + 'ds2_l', 'ds2_l_u', 'ds2_q', 'ds2_q_u', + 'quality_f', 'dark_frac', 'ice_clim_f', 'ice_dyn_f', 'partial_f', + 'xovr_cal_q', 'geoid_hght', 'solid_tide', 'load_tidef', 'load_tideg', 'pole_tide', + 'dry_trop_c', 'wet_trop_c', 'iono_c', 'xovr_cal_c', 'lake_name', 'p_res_id', + 'p_lon', 'p_lat', 'p_ref_wse', 'p_ref_area', 'p_date_t0', 'p_ds_t0', 'p_storage', + 'cycle_id', 'pass_id', 'continent_id', 'range_start_time', 'range_end_time', + 'crid', 'geometry', 'PLD_version', 'collection_shortname', 'crid' +] diff --git a/pyproject.toml b/pyproject.toml index da550758..fc322bf7 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -47,6 +47,10 @@ matplotlib = "^3.8.3" [tool.poetry.group.test.dependencies] pytz = "^2024.1" +[tool.coverage.run] +source = ['hydrocron'] +relative_files = true + [tool.poetry.scripts] hydrocron_api = "hydrocron.api.__main__:__main__" hydrocron_load = 'hydrocron.db.load_data:main' diff --git a/terraform/hydrocron-dynamo.tf b/terraform/hydrocron-dynamo.tf index ed268569..f44f883d 100644 --- a/terraform/hydrocron-dynamo.tf +++ b/terraform/hydrocron-dynamo.tf @@ -50,3 +50,30 @@ resource "aws_dynamodb_table" "hydrocron-swot-node-table" { non_key_attributes = ["node_id", "collection_shortname", "collection_version", "crid", "cycle_id", "pass_id", "continent_id", "ingest_time"] } } + +resource "aws_dynamodb_table" "hydrocron-swot-prior-lake-table" { + name = "hydrocron-swot-prior-lake-table" + billing_mode = "PAY_PER_REQUEST" + hash_key = "lake_id" + range_key = "range_start_time" + attribute { + name = "lake_id" + type = "S" + } + attribute { + name = "range_start_time" + type = "S" + } + attribute { + name = "granuleUR" + type = "S" + } + + global_secondary_index { + name = "GranuleURIndex" + hash_key = "granuleUR" + range_key = "range_start_time" + projection_type = "INCLUDE" + non_key_attributes = ["lake_id", "collection_shortname", "collection_version", "crid", "cycle_id", "pass_id", "continent_id", "ingest_time"] + } +} \ No newline at end of file diff --git a/terraform/hydrocron-iam.tf b/terraform/hydrocron-iam.tf index d142de15..23cf4b52 100644 --- a/terraform/hydrocron-iam.tf +++ b/terraform/hydrocron-iam.tf @@ -70,7 +70,8 @@ data "aws_iam_policy_document" "dynamo-write-policy" { resources = [ aws_dynamodb_table.hydrocron-swot-node-table.arn, - aws_dynamodb_table.hydrocron-swot-reach-table.arn + aws_dynamodb_table.hydrocron-swot-reach-table.arn, + aws_dynamodb_table.hydrocron-swot-prior-lake-table.arn ] } diff --git a/tests/conftest.py b/tests/conftest.py index b448c2bb..d1402728 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -8,12 +8,10 @@ from pytest_dynamodb import factories from hydrocron.db import HydrocronTable -from hydrocron.db.io import swot_reach_node_shp +from hydrocron.db.io import swot_shp from hydrocron.utils import constants -from hydrocron.utils.constants import SWOT_REACH_TABLE_NAME DB_TEST_TABLE_NAME = "hydrocron-swot-test-table" -API_TEST_TABLE_NAME = "hydrocron-swot-reach-table" TEST_SHAPEFILE_PATH = os.path.join( os.path.dirname(os.path.realpath(__file__)), @@ -43,7 +41,7 @@ def hydrocron_dynamo_instance(request, dynamo_test_proc): ) dynamo_db.create_table( - TableName=SWOT_REACH_TABLE_NAME, + TableName=constants.SWOT_REACH_TABLE_NAME, AttributeDefinitions=[ {'AttributeName': 'reach_id', 'AttributeType': 'S'}, {'AttributeName': 'range_start_time', 'AttributeType': 'S'}, @@ -98,14 +96,15 @@ def hydrocron_dynamo_instance(request, dynamo_test_proc): ] ) - hydro_table = HydrocronTable(dynamo_db, SWOT_REACH_TABLE_NAME) + hydro_table = HydrocronTable(dynamo_db, constants.SWOT_REACH_TABLE_NAME) - items = swot_reach_node_shp.read_shapefile( + # load reach table + reach_items = swot_shp.read_shapefile( TEST_SHAPEFILE_PATH, obscure_data=False, columns=constants.REACH_DATA_COLUMNS) - for item_attrs in items: + for item_attrs in reach_items: hydro_table.add_data(**item_attrs) try: @@ -148,7 +147,7 @@ def hydrocron_dynamo_table(dynamo_db_resource): hydro_table = HydrocronTable(dynamo_db_resource, DB_TEST_TABLE_NAME) - items = swot_reach_node_shp.read_shapefile( + items = swot_shp.read_shapefile( TEST_SHAPEFILE_PATH, obscure_data=False, columns=constants.REACH_DATA_COLUMNS) diff --git a/tests/data/SWOT_L2_HR_LakeSP_Prior_018_100_GR_20240713T111741_20240713T112027_PIC0_01.zip b/tests/data/SWOT_L2_HR_LakeSP_Prior_018_100_GR_20240713T111741_20240713T112027_PIC0_01.zip new file mode 100644 index 0000000000000000000000000000000000000000..829b6eaf11ca6629bbb01da5519ae15ce8ab9c31 GIT binary 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