From 9b625c73ec25b24e1d9d34b34447c58f76d03dcc Mon Sep 17 00:00:00 2001 From: Mike Kittridge Date: Tue, 1 Nov 2022 16:09:15 -0600 Subject: [PATCH 1/4] integrated hdf5tools better --- tethysts/datasets/__init__.py | 31 ------ tethysts/main.py | 43 ++++---- tethysts/tests/test_tethysts.py | 184 +++++++++++++++++++++++--------- tethysts/utils.py | 128 ++++++++++------------ 4 files changed, 213 insertions(+), 173 deletions(-) delete mode 100644 tethysts/datasets/__init__.py diff --git a/tethysts/datasets/__init__.py b/tethysts/datasets/__init__.py deleted file mode 100644 index ba8c7bf..0000000 --- a/tethysts/datasets/__init__.py +++ /dev/null @@ -1,31 +0,0 @@ -import os - - -__all__ = ['available', 'get_path'] - -_module_path = os.path.dirname(__file__) -_available_dir = [p for p in next(os.walk(_module_path))[1] - if not p.startswith('__')] -_ts_dir_files = os.listdir(os.path.join(_module_path, 'time_series')) -_available_ts = {p.split('.')[0]: p for p in _ts_dir_files if p.endswith('.zst')} -available = list(_available_ts.keys()) - - -def get_path(dataset): - """ - Get the path to the data file. - Parameters - ---------- - dataset : str - The name of the dataset. - - Returns - str path - """ - if dataset in _available_ts: - return os.path.abspath( - os.path.join(_module_path, 'time_series', _available_ts[dataset])) - else: - msg = "The dataset '{data}' is not available. ".format(data=dataset) - msg += "Available datasets are {}".format(", ".join(available)) - raise ValueError(msg) diff --git a/tethysts/main.py b/tethysts/main.py index 38add10..237f3bf 100644 --- a/tethysts/main.py +++ b/tethysts/main.py @@ -14,7 +14,8 @@ import copy # from multiprocessing.pool import ThreadPool import concurrent.futures -from tethysts.utils import read_json_zstd, spatial_query, get_nearest_from_extent, public_remote_key, chunk_filters, download_results, make_run_date_key, update_nested, results_concat +from tethysts import utils +# import utils from s3tethys import get_object_s3, s3_client, decompress_stream_to_object from typing import List, Union import tethys_data_models as tdm @@ -98,10 +99,10 @@ def __init__(self, remotes: List[tdm.base.Remote] = None, cache: Union[pathlib.P _ = self.get_datasets(remotes) elif remotes is None: - resp = requests.get(public_remote_key) + resp = requests.get(utils.public_remote_key) resp.raise_for_status() - remotes = read_json_zstd(resp.content) + remotes = utils.read_json_zstd(resp.content) _ = self.get_datasets(remotes) elif remotes != 'pass': @@ -251,7 +252,7 @@ def get_stations(self, stn_obj = get_object_s3(**remote) stn_list = orjson.loads(decompress_stream_to_object(stn_obj, 'zstd').read()) stn_dict = {s['station_id']: s for s in stn_list if isinstance(s, dict)} - update_nested(self._stations, dataset_id, vd, stn_dict) + utils.update_nested(self._stations, dataset_id, vd, stn_dict) except: print('No stations.json.zst file in S3 bucket') return None @@ -266,7 +267,7 @@ def get_stations(self, stn_dict = {s_id: s for s_id, s in stn_dict.items() if pd.Timestamp(s['time_range']['to_date']) <= to_date1} ## Spatial query - stn_ids = spatial_query(stn_dict, geometry, lat, lon, distance) + stn_ids = utils.spatial_query(stn_dict, geometry, lat, lon, distance) if isinstance(stn_ids, list): stn_list1 = [stn_dict[s] for s in stn_ids] @@ -289,7 +290,7 @@ def _get_stns_rc_key(self, dataset_id: str, key_name, version_date: str = None): # Check version_date version_date = self._get_version_date(dataset_id, version_date) - vd_key = make_run_date_key(version_date) + vd_key = utils.make_run_date_key(version_date) stn_key = self._key_patterns[system_version][key_name].format(dataset_id=dataset_id, version_date=vd_key) return stn_key @@ -319,7 +320,7 @@ def _get_results_chunks(self, dataset_id: str, version_date: str = None): rc_list = orjson.loads(decompress_stream_to_object(stn_obj, 'zstd').read()) - update_nested(self._results_chunks, dataset_id, version_date, rc_list) + utils.update_nested(self._results_chunks, dataset_id, version_date, rc_list) return rc_list @@ -433,7 +434,7 @@ def get_results(self, bands: Union[List[int], int] = None, squeeze_dims: bool = False, output_path: Union[str, pathlib.Path] = None, - compression: str = 'gzip', + compression: str = 'lzf', threads: int = 30, # include_chunk_vars: bool = False ): @@ -513,14 +514,14 @@ def get_results(self, stn_dict = self._stations[dataset_id][vd] # Run the spatial query - stn_ids = spatial_query(stn_dict, geometry, lat, lon, None) + stn_ids = utils.spatial_query(stn_dict, geometry, lat, lon, None) else: raise ValueError('A station_id, point geometry or a combination of lat and lon must be passed.') ## Get results chunks rc_list = self._get_results_chunks(dataset_id, vd) - chunks = chunk_filters(rc_list, stn_ids, time_interval, from_date, to_date, heights, bands) + chunks = utils.chunk_filters(rc_list, stn_ids, time_interval, from_date, to_date, heights, bands) if chunks: @@ -530,39 +531,39 @@ def get_results(self, if not 'public_url' in remote: s3 = s3_client(remote['connection_config'], threads) remote['s3'] = s3 - + futures = [] for chunk in chunks: remote['chunk'] = chunk remote['from_date'] = from_date remote['to_date'] = to_date - f = executor.submit(download_results, **remote) + f = executor.submit(utils.download_results, **remote) futures.append(f) runs = concurrent.futures.wait(futures) - + results_list = [r.result() for r in runs[0]] - + ## Clear xarray cache...because it loves caching everything... ## This is to ensure that xarray will open the file rather than opening a cache ## The next xarray version should have this issue fixed: ## https://github.com/pydata/xarray/pull/4879 xr.backends.file_manager.FILE_CACHE.clear() - + ## combine results - xr3 = results_concat(results_list, output_path=output_path, from_date=from_date, to_date=to_date, from_mod_date=from_mod_date, to_mod_date=to_mod_date, compression=compression) - + xr3 = utils.results_concat(results_list, output_path=output_path, from_date=from_date, to_date=to_date, compression=compression) + ## Convert to new version attrs = xr3.attrs.copy() if 'version' in attrs: attrs['system_version'] = attrs.pop('version') - + ## Extra spatial query if data are stored in blocks if ('grid' in result_type) and ((geom_type == 'Point') or (isinstance(lat, float) and isinstance(lon, float))): - xr3 = get_nearest_from_extent(xr3, geometry, lat, lon) - + xr3 = utils.get_nearest_from_extent(xr3, geometry, lat, lon) + ## Filters xr3.attrs['version_date'] = pd.Timestamp(vd).tz_localize(None).isoformat() - + if squeeze_dims: xr3 = xr3.squeeze_dims() diff --git a/tethysts/tests/test_tethysts.py b/tethysts/tests/test_tethysts.py index 5f7e1b8..76165be 100644 --- a/tethysts/tests/test_tethysts.py +++ b/tethysts/tests/test_tethysts.py @@ -4,6 +4,8 @@ @author: Mike K """ import os +import pathlib +import shutil from tethysts import Tethys import pandas as pd import os @@ -14,47 +16,58 @@ ############################################## ### Parameters -remote1 = {'bucket': 'ecan-env-monitoring', 'public_url': 'https://b2.tethys-ts.xyz/file/', 'version': 4} +base_path = os.path.join(os.path.split(os.path.realpath(os.path.dirname(__file__)))[0], 'datasets/tests') -# remote2 = {'bucket': 'nz-open-modelling-consortium', 'public_url': 'https://b2.nzrivers.xyz/file/', 'version': 3} +# remote1 = {'bucket': 'ecan-env-monitoring', 'public_url': 'https://b2.tethys-ts.xyz/file/', 'version': 4} +remote2 = {'bucket': 'nz-open-modelling-consortium', 'public_url': 'https://b2.nzrivers.xyz/file/', 'version': 4} +remote3 = {'bucket': 'fire-emergency-nz', 'public_url': 'https://b2.tethys-ts.xyz/file/', 'version': 4} +remote4 = {'bucket': 'ecan-env-monitoring', 'public_url': 'https://b2.tethys-ts.xyz/file', 'version': 4} +remote5 = {'bucket': 'gwrc-env', 'public_url': 'https://b2.tethys-ts.xyz/file', 'version': 4} -remote3 = {'bucket': 'nz-open-modelling-consortium', 'public_url': 'https://b2.nzrivers.xyz/file/', 'version': 4} - -dataset_id = '361ce2acd56b13da82390a69' -station_ids = '0e1952877050606d5cf9c0db' +dataset_id = '7751c5f1bf47867fb109d7eb' # dataset_id = 'c3a09c8a5da175897916e8e8' # station_ids = '4db28a9db0cb036507490887' remotes = [ - {'remote': remote1, - 'dataset_id': 'c3a09c8a5da175897916e8e8', - 'station_ids': '2e64175a7b3f0b62b8e4c685', - 'assert': - {'datasets': 1, - 'stations': 1, + {'remote': remote2, + 'dataset_id': dataset_id, + 'heights': [10], + 'assert': + {'datasets': 1, + 'stations': 2, 'versions': 0, - 'results': 1, + 'results': 0, } - }, - # {'remote': remote2, - # 'dataset_id': 'f27574a7b38eab5b0bc2b3d7', - # 'station_ids': '9c90243e84b8c5b17f0726c4', - # 'assert': - # {'datasets': 1, - # 'stations': 1, - # 'versions': 0, - # 'results': 1, - # } - # }, + }, {'remote': remote3, - 'dataset_id': dataset_id, - 'station_ids': station_ids, + 'dataset_id': 'dddb02cd5cb7ae191311ab19', + 'heights': None, 'assert': {'datasets': 1, - 'stations': 1, + 'stations': 2, 'versions': 0, - 'results': 0, + 'results': 1, + } + }, + {'remote': remote4, + 'dataset_id': 'f16774ea29f024a306c7fc7a', + 'heights': None, + 'assert': + {'datasets': 1, + 'stations': 2, + 'versions': 0, + 'results': 1, + } + }, + {'remote': remote5, + 'dataset_id': '9568f663d566aabb62a8e98e', + 'heights': None, + 'assert': + {'datasets': 1, + 'stations': 2, + 'versions': 0, + 'results': 1, } }, ] @@ -65,14 +78,57 @@ # geometry2 = shape(geometry1).buffer(0.5) lat = -42.8 lon = 172.0 -distance = 0.1 +distance = 1 + +# test_h5 = os.path.join(base_path, 'test.h5') + +bp = pathlib.Path(base_path) + +bp.mkdir(parents=True, exist_ok=True) ###################################### ### Testing +# for remote in remotes: +# print(remote) +# t1 = Tethys([remote['remote']]) +# # t1 = Tethys([remote['remote']], cache=base_path) + +# ## Datasets +# datasets = t1.datasets +# assert len(datasets) > remote['assert']['datasets'] + +# dataset_id = remote['dataset_id'] +# heights = remote['heights'] + +# ## Stations +# stn_list1 = t1.get_stations(dataset_id) +# assert len(stn_list1) > remote['assert']['stations'] + +# ## Versions +# rv1 = t1.get_versions(dataset_id) +# assert len(rv1) > remote['assert']['versions'] + +# ## Results +# station_ids = [s['station_id'] for s in stn_list1[:2]] + +# data1 = t1.get_results(dataset_id, station_ids, heights=heights) +# assert len(data1) > remote['assert']['results'] +# # data1.close() +# # del data1 + +# # Save +# test_h5 = os.path.join(base_path, dataset_id + '_test.h5') +# s2 = t1.get_results(dataset_id, station_ids, heights=heights, output_path=test_h5) +# assert len(s2) > 0 +# # s2.close() +# # del s2 + +# os.remove(test_h5) + @pytest.mark.parametrize('remote', remotes) -def test_tethys(remote): +def test_tethys_memory(remote): """ """ @@ -91,24 +147,56 @@ def test_tethys(remote): assert len(rv1) > remote['assert']['versions'] ## Results - data1 = t1.get_results(remote['dataset_id'], remote['station_ids']) + station_ids = [s['station_id'] for s in stn_list1[:2]] + + data1 = t1.get_results(remote['dataset_id'], station_ids, heights=remote['heights']) assert len(data1) > remote['assert']['results'] + # Save + test_h5 = os.path.join(base_path, remote['dataset_id'] + '_test.h5') + s2 = t1.get_results(remote['dataset_id'], station_ids, heights=remote['heights'], output_path=test_h5) + assert len(s2) > 0 -## initialise for the rest of the tests -t1 = Tethys([remote3]) + os.remove(test_h5) + # shutil.rmtree(base_path) + + +@pytest.mark.parametrize('remote', remotes) +def test_tethys_cache(remote): + """ + + """ + t1 = Tethys([remote['remote']], cache=base_path) + + ## Datasets + datasets = t1.datasets + assert len(datasets) > remote['assert']['datasets'] + + ## Stations + stn_list1 = t1.get_stations(remote['dataset_id']) + assert len(stn_list1) > remote['assert']['stations'] + ## Versions + rv1 = t1.get_versions(remote['dataset_id']) + assert len(rv1) > remote['assert']['versions'] + + ## Results + station_ids = [s['station_id'] for s in stn_list1[:2]] + + data1 = t1.get_results(remote['dataset_id'], station_ids, heights=remote['heights']) + assert len(data1) > remote['assert']['results'] + + # Save + test_h5 = os.path.join(base_path, remote['dataset_id'] + '_test.h5') + s2 = t1.get_results(remote['dataset_id'], station_ids, heights=remote['heights'], output_path=test_h5) + assert len(s2) > 0 + + # os.remove(test_h5) + shutil.rmtree(base_path) -# @pytest.mark.parametrize('output', outputs) -# def test_get_results(output): -# data1 = t1.get_results(dataset_id, station_ids, squeeze_dims=True, output=output) -# if output == 'xarray': -# assert len(data1.time) > 90 -# elif output == 'dict': -# assert len(data1['coords']['time']['data']) > 90 -# elif output == 'json': -# assert len(data1) > 90 +## initialise for the rest of the tests +t1 = Tethys([remote2]) def test_get_nearest_station1(): @@ -130,25 +218,17 @@ def test_get_intersection_stations1(): def test_get_nearest_results1(): - s1 = t1.get_results(dataset_id, geometry=geometry1) + s1 = t1.get_results(dataset_id, geometry=geometry1, heights=[10]) assert len(s1) > 0 def test_get_nearest_results2(): - s2 = t1.get_results(dataset_id, lat=lat, lon=lon) + s2 = t1.get_results(dataset_id, lat=lat, lon=lon, heights=[10]) assert len(s2) > 0 -def test_save_h5(): - s2 = t1.get_results(dataset_id, station_ids, output_path='test1.h5') - - assert len(s2) == 1 - - os.remove('test1.h5') - - diff --git a/tethysts/utils.py b/tethysts/utils.py index 53c1d7c..9c95e68 100644 --- a/tethysts/utils.py +++ b/tethysts/utils.py @@ -26,10 +26,11 @@ from pydantic import HttpUrl # import shutil # import gzip -import hdf5tools +from hdf5tools import H5 import s3tethys # import smart_open # import psutil +from pprint import pprint pd.options.display.max_columns = 10 @@ -496,61 +497,49 @@ def chunk_filters(results_chunks, stn_ids, time_interval=None, from_date=None, t # return data -def remove_results_junk(data): - """ +# def remove_results_junk(data): +# """ - """ - chunk_vars = [v for v in list(data.variables) if 'chunk' in v] - if chunk_vars: - data = data.drop_vars(chunk_vars) - - # crap_vars = [v for v in list(data.variables) if 'string' in v] - # if crap_vars: - # data = data.drop_vars(crap_vars) - - # if 'geometry' in data.dims: - # stn_vars = [v for v in list(data.data_vars) if ('time' not in data[v].dims) and (v not in ['station_id', 'lon', 'lat'])] - # data = data.drop_vars(stn_vars) - - if 'station_geometry' in data.dims: - stn_vars = [d for d in data.variables if 'station_geometry' in data[d].dims] - data = data.drop_vars(stn_vars) - - return data - - -def result_filters(data, from_date=None, to_date=None, from_mod_date=None, to_mod_date=None): +# """ +# chunk_vars = [v for v in list(data.variables) if 'chunk' in v] +# if chunk_vars: +# data = data.drop_vars(chunk_vars) + +# # crap_vars = [v for v in list(data.variables) if 'string' in v] +# # if crap_vars: +# # data = data.drop_vars(crap_vars) + +# # if 'geometry' in data.dims: +# # stn_vars = [v for v in list(data.data_vars) if ('time' not in data[v].dims) and (v not in ['station_id', 'lon', 'lat'])] +# # data = data.drop_vars(stn_vars) + +# if 'station_geometry' in data.dims: +# stn_vars = [d for d in data.variables if 'station_geometry' in data[d].dims] +# data = data.drop_vars(stn_vars) + +# return data + + +def result_filters(h5, from_date=None, to_date=None): """ """ - data = remove_results_junk(data) + h5 = h5.sel(exclude_coords=['station_geometry', 'chunk_date']) + ## Time filters if isinstance(from_date, (str, pd.Timestamp, datetime)): - from_date1 = pd.Timestamp(from_date) + from_date1 = np.datetime64(from_date) else: from_date1 = None if isinstance(to_date, (str, pd.Timestamp, datetime)): - to_date1 = pd.Timestamp(to_date) + to_date1 = np.datetime64(to_date) else: to_date1 = None - if isinstance(from_mod_date, (str, pd.Timestamp, datetime)): - from_mod_date1 = pd.Timestamp(from_mod_date) - else: - from_mod_date1 = None - if isinstance(to_mod_date, (str, pd.Timestamp, datetime)): - to_mod_date1 = pd.Timestamp(to_mod_date) - else: - to_mod_date1 = None - if (to_date1 is not None) or (from_date1 is not None): - data = data.sel(time=slice(from_date1, to_date1)) + h5 = h5.sel({'time': slice(from_date1, to_date1)}) - if (to_mod_date1 is not None) or (from_mod_date1 is not None): - if 'modified_date' in data: - data = data.sel(modified_date=slice(from_mod_date1, to_mod_date1)) - - return data + return h5 # def process_results_output(ts_xr, output='xarray', squeeze_dims=False): @@ -691,16 +680,16 @@ def result_filters(data, from_date=None, to_date=None, from_mod_date=None, to_mo # if str(file_path2).endswith('.zst'): # file_path2 = os.path.splitext(file_path2)[0] # dctx = zstd.ZstdDecompressor() - + # with open(file_path2, 'wb') as f: # dctx.copy_stream(stream, f, read_size=chunk_size, write_size=chunk_size) - + # elif str(file_path2).endswith('.gz'): # file_path2 = os.path.splitext(file_path2)[0] - + # with gzip.open(stream, 'rb') as s_file, open(file_path2, 'wb') as d_file: # shutil.copyfileobj(s_file, d_file, chunk_size) - + # else: # with open(file_path2, 'wb') as f: # chunk = stream.read(chunk_size) @@ -726,16 +715,19 @@ def result_filters(data, from_date=None, to_date=None, from_mod_date=None, to_mo # return file_path2 -def process_dataset(data, from_date=None, to_date=None): - """ - Stupid xarray being inefficient at parsing file objects... - """ - data = result_filters(data, from_date, to_date) +# def process_dataset(data, from_date=None, to_date=None): +# """ +# Stupid xarray being inefficient at parsing file objects... +# """ +# ## Remove junk fields +# h1 = H5(data).sel(exclude_coords=['station_geometry', 'chunk_date']) - data_obj = io.BytesIO() - hdf5tools.xr_to_hdf5(data, data_obj) +# h2 = result_filters(h1, from_date, to_date) - return data_obj +# data_obj = io.BytesIO() +# h2.to_hdf5(data_obj) + +# return data_obj def download_results(chunk: dict, bucket: str, s3: botocore.client.BaseClient = None, connection_config: dict = None, public_url: HttpUrl = None, cache: Union[pathlib.Path] = None, from_date=None, to_date=None, return_raw=False): @@ -755,7 +747,9 @@ def download_results(chunk: dict, bucket: str, s3: botocore.client.BaseClient = if chunk['key'].endswith('.zst'): data = xr.load_dataset(s3tethys.decompress_stream_to_object(file_obj, 'zstd')) - hdf5tools.xr_to_hdf5(data, chunk_path) + H5(data).sel(exclude_coords=['station_geometry', 'chunk_date']).to_hdf5(chunk_path) + data.close() + del data else: s3tethys.stream_to_file(file_obj, chunk_path) @@ -771,10 +765,13 @@ def download_results(chunk: dict, bucket: str, s3: botocore.client.BaseClient = else: data = xr.load_dataset(io.BytesIO(file_obj.read()), engine='h5netcdf') - data_obj = process_dataset(data, from_date=from_date, to_date=to_date) + h1 = H5(data).sel(exclude_coords=['station_geometry', 'chunk_date']) + data_obj = io.BytesIO() + h1.to_hdf5(data_obj) data.close() del data + del h1 del file_obj @@ -842,25 +839,18 @@ def xr_concat(datasets: List[xr.Dataset]): return xr3 -def results_concat(results_list, output_path=None, from_date=None, to_date=None, from_mod_date=None, to_mod_date=None, compression='gzip'): +def results_concat(results_list, output_path=None, from_date=None, to_date=None, compression='lzf'): """ """ if output_path is None: - temp_path = io.BytesIO() - else: - temp_path = output_path + '.temp' - - hdf5tools.combine_hdf5(results_list, temp_path, compression='zstd') + output_path = io.BytesIO() - xr3 = xr.open_dataset(temp_path, engine='h5netcdf', cache=False) - xr3 = result_filters(xr3, from_date, to_date, from_mod_date, to_mod_date) + h1 = H5(results_list) + h1 = result_filters(h1, from_date, to_date) + h1.to_hdf5(output_path, compression=compression) - if isinstance(output_path, (str, pathlib.Path)): - hdf5tools.xr_to_hdf5(xr3, output_path, compression=compression) - xr3.close() - xr3 = xr.open_dataset(output_path, engine='h5netcdf', cache=False) - os.remove(temp_path) + xr3 = xr.open_dataset(output_path, engine='h5netcdf', cache=False) return xr3 From 3ed9e0730141fb93831a3b653d3f8c292fb6f494 Mon Sep 17 00:00:00 2001 From: Mike Kittridge Date: Tue, 1 Nov 2022 19:17:32 -0600 Subject: [PATCH 2/4] cleaned up --- tethysts/utils.py | 70 ----------------------------------------------- 1 file changed, 70 deletions(-) diff --git a/tethysts/utils.py b/tethysts/utils.py index 9c95e68..88c7e54 100644 --- a/tethysts/utils.py +++ b/tethysts/utils.py @@ -872,76 +872,6 @@ def results_concat(results_list, output_path=None, from_date=None, to_date=None, - - - - - - -## Currently not working because of cloudflare CDN -# def get_zstd_url_data(url, request_type='get', headers=None, chunk_size=524288, **kwargs): -# """ - -# """ -# h1 = {'Accept-Encoding': 'zstd'} -# if isinstance(headers, dict): -# h1.update(headers) - -# if request_type.lower() == 'get': -# r1 = requests.get -# elif request_type.lower() == 'post': -# r1 = requests.post -# else: -# raise ValueError('request_type must be either get or post.') - -# with r1(url, stream=True, timeout=300, headers=h1) as r: -# r.raise_for_status() -# stream = ResponseStream(r.iter_content(chunk_size)) - -# dctx = zstd.ZstdDecompressor() -# with dctx.stream_reader(stream) as reader: -# data = reader.read() - -# return data - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - From 261e07305a3a35944498605f577d964827d8b814 Mon Sep 17 00:00:00 2001 From: Mike Kittridge Date: Tue, 1 Nov 2022 19:22:22 -0600 Subject: [PATCH 3/4] added new version --- conda/meta.yaml | 4 ++-- setup.py | 4 ++-- tethysts/tests/test1.h5 | Bin 2626019 -> 0 bytes 3 files changed, 4 insertions(+), 4 deletions(-) delete mode 100644 tethysts/tests/test1.h5 diff --git a/conda/meta.yaml b/conda/meta.yaml index 37d1e55..9b4b36a 100644 --- a/conda/meta.yaml +++ b/conda/meta.yaml @@ -1,5 +1,5 @@ {% set name = "tethysts" %} -{% set version = "4.5.4" %} +{% set version = "4.5.5" %} # {% set sha256 = "ae2cc83fb5a75e8dc3e1b2c2137deea412c8a4c7c9acca52bf4ec59de52a80c9" %} # sha256 is the prefered checksum -- you can get it for a file with: @@ -44,7 +44,7 @@ requirements: - requests - shapely - tethys-data-models >=0.4.11 - - hdf5tools >=0.0.7 + - hdf5tools >=0.1.3 - s3tethys >=0.0.4 test: diff --git a/setup.py b/setup.py index 90f2fd2..b520630 100644 --- a/setup.py +++ b/setup.py @@ -10,7 +10,7 @@ name = 'tethysts' main_package = 'tethysts' datasets = 'datasets/time_series' -version = '4.5.4' +version = '4.5.5' descrip = 'tethys time series S3 extraction' # The below code is for readthedocs. To have sphinx/readthedocs interact with @@ -19,7 +19,7 @@ if os.environ.get('READTHEDOCS', False) == 'True': INSTALL_REQUIRES = [] else: - INSTALL_REQUIRES = ['zstandard', 'pandas', 'xarray', 'scipy', 'orjson', 'requests', 'shapely', 'tethys-data-models>=0.4.11', 'hdf5tools>=0.0.7', 's3tethys>=0.0.4'] + INSTALL_REQUIRES = ['zstandard', 'pandas', 'xarray', 'scipy', 'orjson', 'requests', 'shapely', 'tethys-data-models>=0.4.11', 'hdf5tools>=0.1.3', 's3tethys>=0.0.4'] # Get the long description from the README file with open(os.path.join(here, 'README.rst'), encoding='utf-8') as f: diff --git a/tethysts/tests/test1.h5 b/tethysts/tests/test1.h5 deleted file mode 100644 index 0531ac1c6cb7b64f5d340d663310dbde74ded365..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 2626019 zcmd421yoy6yr&zq6lkFiEiJ*_-5r9vYj6z~+}+*X-Q6X)wWUs5+}*7$Edx32+&lB` ztoPoUd27AB+I&ZL_BrRv{{0V-BmyEXc@O(JHX0Td=wG}3+g2V>BR4Vs-I2<+&#wp( 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12 +++++++----- 4 files changed, 17 insertions(+), 15 deletions(-) diff --git a/conda/meta.yaml b/conda/meta.yaml index 9b4b36a..4e6537d 100644 --- a/conda/meta.yaml +++ b/conda/meta.yaml @@ -1,5 +1,5 @@ {% set name = "tethysts" %} -{% set version = "4.5.5" %} +{% set version = "4.5.6" %} # {% set sha256 = "ae2cc83fb5a75e8dc3e1b2c2137deea412c8a4c7c9acca52bf4ec59de52a80c9" %} # sha256 is the prefered checksum -- you can get it for a file with: @@ -44,7 +44,7 @@ requirements: - requests - shapely - tethys-data-models >=0.4.11 - - hdf5tools >=0.1.3 + - hdf5tools >=0.1.4 - s3tethys >=0.0.4 test: diff --git a/setup.py b/setup.py index b520630..d6ab8b4 100644 --- a/setup.py +++ b/setup.py @@ -10,7 +10,7 @@ name = 'tethysts' main_package = 'tethysts' datasets = 'datasets/time_series' -version = '4.5.5' +version = '4.5.6' descrip = 'tethys time series S3 extraction' # The below code is for readthedocs. To have sphinx/readthedocs interact with @@ -19,7 +19,7 @@ if os.environ.get('READTHEDOCS', False) == 'True': INSTALL_REQUIRES = [] else: - INSTALL_REQUIRES = ['zstandard', 'pandas', 'xarray', 'scipy', 'orjson', 'requests', 'shapely', 'tethys-data-models>=0.4.11', 'hdf5tools>=0.1.3', 's3tethys>=0.0.4'] + INSTALL_REQUIRES = ['zstandard', 'pandas', 'xarray', 'scipy', 'orjson', 'requests', 'shapely', 'tethys-data-models>=0.4.11', 'hdf5tools>=0.1.4', 's3tethys>=0.0.4'] # Get the long description from the README file with open(os.path.join(here, 'README.rst'), encoding='utf-8') as f: diff --git a/tethysts/tests/utest_tethysts.py b/tethysts/tests/utest_tethysts.py index 913cd58..6d06575 100644 --- a/tethysts/tests/utest_tethysts.py +++ b/tethysts/tests/utest_tethysts.py @@ -233,8 +233,8 @@ remote = {'bucket': 'tasman-env', 'public_url': 'https://b2.tethys-ts.xyz/file', 'version': 4} remote = {'bucket': 'noaa-nwm', 'public_url': 'https://b2.tethys-ts.xyz/file', 'version': 4} -# cache = '/media/nvme1/cache/tethys' -cache = '/home/mike/cache/tethys' +cache = '/media/nvme1/cache/tethys' +# cache = '/home/mike/cache/tethys' dataset_id = '7751c5f1bf47867fb109d7eb' dataset_id = '0b2bd62cc42f3096136f11e9' @@ -293,12 +293,12 @@ station_ids = [s['station_id'] for s in stns1 if ref in s['ref']] results1 = self.get_results(dataset_id, station_ids, heights=None) -results1 = self.get_results(dataset_id, station_ids, heights=None, output_path='/home/mike/cache/tethys/test.h5', compression='zstd') +results1 = self.get_results(dataset_id, station_ids, heights=None, output_path='/media/nvme1/cache/tethys/test.h5', compression='zstd') results1 = self.get_results(dataset_id, station_ids, heights=[10, 20, 30, 80], version_date=version_date) results1 = self.get_results(dataset_id, station_ids, heights=[10]) -results1 = self.get_results(dataset_id, station_ids, heights=[10], output_path='/home/mike/cache/tethys/test.h5', compression='zstd') +results1 = self.get_results(dataset_id, station_ids, heights=[10], output_path='/media/nvme1/cache/tethys/test.h5', compression='zstd') results1 = self.get_results(dataset_id, station_ids, heights=[10], from_date='2020-04-01') @@ -450,9 +450,9 @@ # If stations are found, then get the associated results if stn_ids: results = ts.get_results(dataset_id, stn_ids, heights=heights) - + output_file = '{ds}_{min_x}_{min_y}_{max_x}_{max_y}.nc'.format(ds=dataset_id, min_x=min_x, min_y=min_y, max_x=x, max_y=y) - + # Save the file to netcdf (xarray uses an excessive amount of memory when saving to netcdf, so be careful...) results.to_netcdf(os.path.join(output_path, output_file)) results.close() diff --git a/tethysts/utils.py b/tethysts/utils.py index 88c7e54..094d0ad 100644 --- a/tethysts/utils.py +++ b/tethysts/utils.py @@ -746,7 +746,7 @@ def download_results(chunk: dict, bucket: str, s3: botocore.client.BaseClient = chunk_path.parent.mkdir(parents=True, exist_ok=True) if chunk['key'].endswith('.zst'): - data = xr.load_dataset(s3tethys.decompress_stream_to_object(file_obj, 'zstd')) + data = xr.load_dataset(s3tethys.decompress_stream_to_object(io.BytesIO(file_obj.read()), 'zstd')) H5(data).sel(exclude_coords=['station_geometry', 'chunk_date']).to_hdf5(chunk_path) data.close() del data @@ -760,16 +760,18 @@ def download_results(chunk: dict, bucket: str, s3: botocore.client.BaseClient = return file_obj if chunk['key'].endswith('.zst'): - file_obj = s3tethys.decompress_stream_to_object(file_obj, 'zstd') + file_obj = s3tethys.decompress_stream_to_object(io.BytesIO(file_obj.read()), 'zstd') data = xr.load_dataset(file_obj.read(), engine='scipy') else: - data = xr.load_dataset(io.BytesIO(file_obj.read()), engine='h5netcdf') + data = io.BytesIO(file_obj.read()) - h1 = H5(data).sel(exclude_coords=['station_geometry', 'chunk_date']) + h1 = H5(data) data_obj = io.BytesIO() + h1 = result_filters(h1) h1.to_hdf5(data_obj) - data.close() + if isinstance(data, xr.Dataset): + data.close() del data del h1

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