diff --git a/.github/workflows/build-pipeline.yml b/.github/workflows/build-pipeline.yml index db822ec3..9582a68b 100644 --- a/.github/workflows/build-pipeline.yml +++ b/.github/workflows/build-pipeline.yml @@ -84,7 +84,7 @@ jobs: poetry run flake8 podaac - name: Test and coverage run: | - poetry run pytest --junitxml=build/reports/pytest.xml --cov=podaac/ --cov-report=xml:build/reports/coverage.xml -m "not aws and not integration" tests/ + poetry run pytest -n auto --junitxml=build/reports/pytest.xml --cov=podaac/ --cov-report=xml:build/reports/coverage.xml -m "not aws and not integration" tests/ - name: SonarCloud Scan id: sonarcloud uses: sonarsource/sonarcloud-github-action@master @@ -295,3 +295,15 @@ jobs: git config user.email "${GITHUB_ACTOR}@users.noreply.github.com" git tag -a "${{ env.software_version }}" -m "Version ${{ env.software_version }}" git push origin "${{ env.software_version }}" + + - name: Deploy Harmony + env: + ENV: ${{ env.venue }} + CMR_USER: ${{ secrets.CMR_USER }} + CMR_PASS: ${{ secrets.CMR_PASS }} + if: | + github.ref == 'refs/heads/main' || + startsWith(github.ref, 'refs/heads/release') + working-directory: deployment + run: + poetry run python harmony_deploy.py --tag ${{ env.software_version }} diff --git a/deployment/harmony_deploy.py b/deployment/harmony_deploy.py new file mode 100644 index 00000000..57e46f97 --- /dev/null +++ b/deployment/harmony_deploy.py @@ -0,0 +1,67 @@ +import os +import requests +import json +import logging +import argparse +from requests.auth import HTTPBasicAuth + +# Environment variables +ENV = os.getenv('ENV') +CMR_USER = os.getenv('CMR_USER') +CMR_PASS = os.getenv('CMR_PASS') + +def bearer_token() -> str: + tokens = [] + headers = {'Accept': 'application/json'} + url = f"https://{'uat.' if ENV == 'uat' else ''}urs.earthdata.nasa.gov/api/users" + + # First just try to get a token that already exists + try: + resp = requests.get(url + "/tokens", headers=headers, auth=HTTPBasicAuth(CMR_USER, CMR_PASS)) + response_content = json.loads(resp.content) + + for x in response_content: + tokens.append(x['access_token']) + + except Exception: # noqa E722 + logging.warning("Error getting the token - check user name and password", exc_info=True) + + # No tokens exist, try to create one + if not tokens: + try: + resp = requests.post(url + "/token", headers=headers, auth=HTTPBasicAuth(CMR_USER, CMR_PASS)) + response_content = json.loads(resp.content) + tokens.append(response_content['access_token']) + except Exception: # noqa E722 + logging.warning("Error getting the token - check user name and password", exc_info=True) + + # If still no token, then we can't do anything + if not tokens: + raise RuntimeError("Unable to get bearer token from EDL") + + return next(iter(tokens)) + +if __name__ == "__main__": + + parser = argparse.ArgumentParser(description="Update the service image tag.") + parser.add_argument("--tag", help="The new tag version to update.", required=True) + args = parser.parse_args() + + url = f"https://harmony.{'uat.' if ENV == 'uat' else ''}earthdata.nasa.gov/service-image-tag/podaac-l2-subsetter" + token = bearer_token() + + headers = { + "Authorization": f"Bearer {token}", + "Content-type": "application/json" + } + data = { + "tag": args.tag + } + + response = requests.put(url, headers=headers, json=data) + + print(response.status_code) + try: + print(response.json()) + except json.JSONDecodeError: + print("Response content is not in JSON format") diff --git a/podaac/subsetter/dimension_cleanup.py b/podaac/subsetter/dimension_cleanup.py index 4ba76406..6904ee50 100644 --- a/podaac/subsetter/dimension_cleanup.py +++ b/podaac/subsetter/dimension_cleanup.py @@ -117,8 +117,8 @@ def recreate_pixcore_dimensions(datasets: list): dim_dict = {} count = 0 for dataset in datasets: - dim_list_shape = list(dataset.dims.values()) - current_dims = list(dataset.dims.keys()) + dim_list_shape = list(dataset.sizes.values()) + current_dims = list(dataset.sizes.keys()) rename_list = [] for current_dim, dim_value in zip(current_dims, dim_list_shape): if current_dim not in dim_dict: diff --git a/podaac/subsetter/group_handling.py b/podaac/subsetter/group_handling.py index ee61c76e..5a08528b 100644 --- a/podaac/subsetter/group_handling.py +++ b/podaac/subsetter/group_handling.py @@ -119,12 +119,11 @@ def recombine_grouped_datasets(datasets: List[xr.Dataset], output_file: str, sta for group in groups: base_dataset.createGroup(group) - for dim_name in list(dataset.dims.keys()): + for dim_name in list(dataset.sizes.keys()): new_dim_name = dim_name.split(GROUP_DELIM)[-1] dim_group = _get_nested_group(base_dataset, dim_name) if new_dim_name not in dim_group.dimensions: - dim_group.createDimension(new_dim_name, dataset.dims[dim_name]) - + dim_group.createDimension(new_dim_name, dataset.sizes[dim_name]) # Rename variables _rename_variables(dataset, base_dataset, start_date, time_vars) diff --git a/podaac/subsetter/subset.py b/podaac/subsetter/subset.py index ee7ba7a0..9b1c8497 100644 --- a/podaac/subsetter/subset.py +++ b/podaac/subsetter/subset.py @@ -23,6 +23,7 @@ import json import operator import os +import re from itertools import zip_longest from typing import List, Optional, Tuple, Union import dateutil @@ -270,11 +271,11 @@ def calculate_chunks(dataset: xr.Dataset) -> dict: """ if len(dataset.dims) <= 3: chunk = {dim: 4000 for dim in dataset.dims - if dataset.dims[dim] > 4000 + if dataset.sizes[dim] > 4000 and len(dataset.dims) > 1} else: chunk = {dim: 500 for dim in dataset.dims - if dataset.dims[dim] > 500} + if dataset.sizes[dim] > 500} return chunk @@ -528,7 +529,7 @@ def compute_time_variable_name(dataset: xr.Dataset, lat_var: xr.Variable, total_ return time_vars[0] # Filter variables with 'time' in the name to avoid extra work - time_vars = list(filter(lambda var_name: 'time' in var_name, dataset.dims.keys())) + time_vars = list(filter(lambda var_name: 'time' in var_name, dataset.sizes.keys())) for var_name in time_vars: if var_name not in total_time_vars and "time" in var_name and dataset[var_name].squeeze().dims == lat_var.squeeze().dims: @@ -542,6 +543,15 @@ def compute_time_variable_name(dataset: xr.Dataset, lat_var: xr.Variable, total_ if var_name not in total_time_vars and ('time' == var_name_time.lower() or 'timeMidScan' == var_name_time) and dataset[var_name].squeeze().dims[0] in lat_var.squeeze().dims: return var_name + time_units_pattern = re.compile(r"(days|d|hours|hr|h|minutes|min|m|seconds|sec|s) since \d{4}-\d{2}-\d{2}( \d{2}:\d{2}:\d{2})?") + # Check variables for common time variable indicators + for var_name, var in dataset.variables.items(): + # pylint: disable=too-many-boolean-expressions + if ((('standard_name' in var.attrs and var.attrs['standard_name'] == 'time') or + ('axis' in var.attrs and var.attrs['axis'] == 'T') or + ('units' in var.attrs and time_units_pattern.match(var.attrs['units'])))) and var_name not in total_time_vars: + return var_name + # then check if any variables have 'time' in the string if the above loop doesn't return anything for var_name in list(dataset.data_vars.keys()): var_name_time = var_name.strip(GROUP_DELIM).split(GROUP_DELIM)[-1] diff --git a/poetry.lock b/poetry.lock index 7de16d5b..a1b87271 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.1 and should not be changed by hand. [[package]] name = "alabaster" @@ -13,13 +13,13 @@ files = [ [[package]] name = "astroid" -version = "3.2.0" +version = "3.2.2" description = "An abstract syntax tree for Python with inference support." optional = false python-versions = ">=3.8.0" files = [ - {file = "astroid-3.2.0-py3-none-any.whl", hash = "sha256:16ee8ca5c75ac828783028cc1f967777f0e507c6886a295ad143e0f405b975a2"}, - {file = "astroid-3.2.0.tar.gz", hash = "sha256:f7f829f8506ade59f1b3c6c93d8fac5b1ebc721685fa9af23e9794daf1d450a3"}, + {file = "astroid-3.2.2-py3-none-any.whl", hash = "sha256:e8a0083b4bb28fcffb6207a3bfc9e5d0a68be951dd7e336d5dcf639c682388c0"}, + {file = "astroid-3.2.2.tar.gz", hash = "sha256:8ead48e31b92b2e217b6c9733a21afafe479d52d6e164dd25fb1a770c7c3cf94"}, ] [package.dependencies] @@ -82,17 +82,17 @@ xyzservices = ">=2021.09.1" [[package]] name = "boto3" -version = "1.34.104" +version = "1.34.131" description = "The AWS SDK for Python" optional = false python-versions = ">=3.8" files = [ - {file = 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--- a/pyproject.toml +++ b/pyproject.toml @@ -47,10 +47,12 @@ pytest-cov = "~5" pylint = "^3.0.2" sphinx = "^7.2.6" pytest-benchmark = "~4" -moto = "5.0.2" +moto = "^5.0.2" jsonschema = "^4.20.0" m2r2 = "^0.3.2" sphinx-rtd-theme = "^2.0.0" +pytest-rerunfailures = "^14.0" +pytest-xdist = "^3.6.1" [tool.pytest.ini_options] junit_family = "xunit2" diff --git a/pytest.ini b/pytest.ini new file mode 100644 index 00000000..85c12f3f --- /dev/null +++ b/pytest.ini @@ -0,0 +1,2 @@ +[pytest] +addopts = --reruns 3 --reruns-delay 15 diff --git a/tests/test_subset.py b/tests/test_subset.py index d6bb6fb9..72b52420 100644 --- a/tests/test_subset.py +++ b/tests/test_subset.py @@ -1172,7 +1172,8 @@ def test_temporal_subset_modis_a(data_dir, subset_output_dir, request): bbox=bbox, output_file=join(subset_output_dir, output_file), min_time=min_time, - max_time=max_time + max_time=max_time, + time_var_names=['sst_dtime'] ) in_ds = xr.open_dataset(join(data_dir, file), @@ -1527,6 +1528,7 @@ def test_get_time_squeeze(data_dir, subset_output_dir): os.path.join(subset_output_dir, tropomi_file_name)) nc_dataset = nc.Dataset(os.path.join(subset_output_dir, tropomi_file_name)) + total_time_vars = ['__PRODUCT__time'] args = { 'decode_coords': False, @@ -1540,7 +1542,8 @@ def test_get_time_squeeze(data_dir, subset_output_dir): **args ) as dataset: lat_var_name = subset.compute_coordinate_variable_names(dataset)[0][0] - time_var_name = subset.compute_time_variable_name(dataset, dataset[lat_var_name], []) + time_var_name = subset.compute_time_variable_name(dataset, dataset[lat_var_name], total_time_vars) + print(time_var_name) lat_dims = dataset[lat_var_name].squeeze().dims time_dims = dataset[time_var_name].squeeze().dims assert lat_dims == time_dims @@ -1759,12 +1762,12 @@ def test_get_time_epoch_var(data_dir, subset_output_dir): **args ) as dataset: lat_var_names, _ = subset.compute_coordinate_variable_names(dataset) - time_var_names = [] + time_var_names = ['__PRODUCT__time'] for lat_var_name in lat_var_names: time_var_names.append(subset.compute_time_variable_name( dataset, dataset[lat_var_name], time_var_names )) - epoch_time_var = subset.get_time_epoch_var(dataset, time_var_names[0]) + epoch_time_var = subset.get_time_epoch_var(dataset, time_var_names[1]) assert epoch_time_var.split('__')[-1] == 'time'