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b274e1e
function, docs, tests
kandersolar d3bd426
make api key secret accessible to tests
kandersolar 0b5ba09
bit more docs
kandersolar 396833b
handle another API error
kandersolar 749fd5e
lint
kandersolar 6828769
Merge branch 'main' into get_era5
kandersolar 8c1ab6d
fix test
kandersolar fd7f06d
Merge branch 'get_era5' of https://github.com/kandersolar/pvlib-pytho…
kandersolar 8f4da88
fix tests, again
kandersolar 9906815
one more
kandersolar ee7474d
use Timeout instead of Exception
kandersolar f34309e
Apply suggestions from code review
kandersolar 3c8f2f2
rename from ECMWF to ERA5
kandersolar a0aa2c8
Merge branch 'get_era5' of https://github.com/kandersolar/pvlib-pytho…
kandersolar ac6fe82
and fix tests
kandersolar 6568cf6
make unit conversion funcs private
kandersolar 2313c80
Apply suggestions from code review
kandersolar 5d9735c
Merge branch 'get_era5' of https://github.com/kandersolar/pvlib-pytho…
kandersolar 53b90ed
convert input times to UTC if not localized
kandersolar 668b9e2
lint
kandersolar 6065b77
fix test bug
kandersolar 42af726
Merge remote-tracking branch 'upstream/main' into get_era5
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| Original file line number | Diff line number | Diff line change |
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| import requests | ||
| import pandas as pd | ||
| from io import BytesIO, StringIO | ||
| import zipfile | ||
| import time | ||
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| VARIABLE_MAP = { | ||
| # short names | ||
| 'd2m': 'temp_dew', | ||
| 't2m': 'temp_air', | ||
| 'sp': 'pressure', | ||
| 'ssrd': 'ghi', | ||
| 'tp': 'precipitation', | ||
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| # long names | ||
| '2m_dewpoint_temperature': 'temp_dew', | ||
| '2m_temperature': 'temp_air', | ||
| 'surface_pressure': 'pressure', | ||
| 'surface_solar_radiation_downwards': 'ghi', | ||
| 'total_precipitation': 'precipitation', | ||
| } | ||
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| def _same(x): | ||
| return x | ||
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| def _k_to_c(temp_k): | ||
| return temp_k - 273.15 | ||
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| def _j_to_w(j): | ||
| return j / 3600 | ||
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| def _m_to_cm(m): | ||
| return m / 100 | ||
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| UNITS = { | ||
| 'u100': _same, | ||
| 'v100': _same, | ||
| 'u10': _same, | ||
| 'v10': _same, | ||
| 'd2m': _k_to_c, | ||
| 't2m': _k_to_c, | ||
| 'msl': _same, | ||
| 'sst': _k_to_c, | ||
| 'skt': _k_to_c, | ||
| 'sp': _same, | ||
| 'ssrd': _j_to_w, | ||
| 'strd': _j_to_w, | ||
| 'tp': _m_to_cm, | ||
| } | ||
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| def get_era5(latitude, longitude, start, end, variables, api_key, | ||
| map_variables=True, timeout=60, | ||
| url='https://cds.climate.copernicus.eu/api/retrieve/v1/'): | ||
| """ | ||
| Retrieve ERA5 reanalysis data from the ECMWF's Copernicus Data Store. | ||
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| A CDS API key is needed to access this API. Register for one at [1]_. | ||
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| This API [2]_ provides a subset of the full ERA5 dataset. See [3]_ for | ||
| the available variables. Data are available on a 0.25° x 0.25° grid. | ||
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| Parameters | ||
| ---------- | ||
| latitude : float | ||
| In decimal degrees, north is positive (ISO 19115). | ||
| longitude: float | ||
| In decimal degrees, east is positive (ISO 19115). | ||
| start : datetime like or str | ||
| First day of the requested period. Assumed to be UTC if not localized. | ||
| end : datetime like or str | ||
| Last day of the requested period. Assumed to be UTC if not localized. | ||
| variables : list of str | ||
| List of variable names to retrieve, for example | ||
| ``['ghi', 'temp_air']``. Both pvlib and ERA5 names can be used. | ||
| See [1]_ for additional options. | ||
| api_key : str | ||
| ECMWF CDS API key. | ||
| map_variables : bool, default True | ||
| When true, renames columns of the DataFrame to pvlib variable names | ||
| where applicable. Also converts units of some variables. See variable | ||
| :const:`VARIABLE_MAP` and :const:`UNITS`. | ||
| timeout : int, default 60 | ||
| Number of seconds to wait for the requested data to become available | ||
| before timeout. | ||
| url : str, optional | ||
| API endpoint URL. | ||
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| Raises | ||
| ------ | ||
| Exception | ||
| If ``timeout`` is reached without the job finishing. | ||
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| Returns | ||
| ------- | ||
| data : pd.DataFrame | ||
| Time series data. The index corresponds to the start of the interval. | ||
| meta : dict | ||
| Metadata. | ||
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| References | ||
| ---------- | ||
| .. [1] https://cds.climate.copernicus.eu/ | ||
| .. [2] https://cds.climate.copernicus.eu/datasets/reanalysis-era5-single-levels-timeseries?tab=overview | ||
| .. [3] https://confluence.ecmwf.int/pages/viewpage.action?pageId=505390919 | ||
| """ # noqa: E501 | ||
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| def _to_utc_dt_notz(dt): | ||
| dt = pd.to_datetime(dt) | ||
| if dt.tzinfo is not None: | ||
| dt = dt.tz_convert("UTC") | ||
| return dt | ||
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| start = _to_utc_dt_notz(start).strftime("%Y-%m-%d") | ||
| end = _to_utc_dt_notz(end).strftime("%Y-%m-%d") | ||
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| headers = {'PRIVATE-TOKEN': api_key} | ||
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| # allow variables to be specified with pvlib names | ||
| reverse_map = {v: k for k, v in VARIABLE_MAP.items()} | ||
| variables = [reverse_map.get(k, k) for k in variables] | ||
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| # Step 1: submit data request (add it to the queue) | ||
| params = { | ||
| "inputs": { | ||
| "variable": variables, | ||
| "location": {"longitude": longitude, "latitude": latitude}, | ||
| "date": [f"{start}/{end}"], | ||
| "data_format": "csv" | ||
| } | ||
| } | ||
| slug = "processes/reanalysis-era5-single-levels-timeseries/execution" | ||
| response = requests.post(url + slug, json=params, headers=headers, | ||
| timeout=timeout) | ||
| submission_response = response.json() | ||
| if not response.ok: | ||
| raise Exception(submission_response) # likely need to accept license | ||
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| job_id = submission_response['jobID'] | ||
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| # Step 2: poll until the data request is ready | ||
| slug = "jobs/" + job_id | ||
| poll_interval = 1 | ||
| num_polls = 0 | ||
| while True: | ||
| response = requests.get(url + slug, headers=headers, timeout=timeout) | ||
| poll_response = response.json() | ||
| job_status = poll_response['status'] | ||
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| if job_status == 'successful': | ||
| break # ready to proceed to next step | ||
| elif job_status == 'failed': | ||
| msg = ( | ||
| 'Request failed. Please check the ECMWF website for details: ' | ||
| 'https://cds.climate.copernicus.eu/requests?tab=all' | ||
| ) | ||
| raise Exception(msg) | ||
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| num_polls += 1 | ||
| if num_polls * poll_interval > timeout: | ||
| raise requests.exceptions.Timeout( | ||
| 'Request timed out. Try increasing the timeout parameter or ' | ||
| 'reducing the request size.' | ||
| ) | ||
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| time.sleep(1) | ||
|
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Could consider reducing this to 0.5 |
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| # Step 3: get the download link for our requested dataset | ||
| slug = "jobs/" + job_id + "/results" | ||
| response = requests.get(url + slug, headers=headers, timeout=timeout) | ||
| results_response = response.json() | ||
| download_url = results_response['asset']['value']['href'] | ||
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| # Step 4: finally, download our dataset. it's a zipfile of one CSV | ||
| response = requests.get(download_url, timeout=timeout) | ||
| zipbuffer = BytesIO(response.content) | ||
| archive = zipfile.ZipFile(zipbuffer) | ||
| filename = archive.filelist[0].filename | ||
| csvbuffer = StringIO(archive.read(filename).decode('utf-8')) | ||
| df = pd.read_csv(csvbuffer) | ||
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| # and parse into the usual formats | ||
| metadata = submission_response['metadata'] # include messages from ECMWF | ||
| metadata['jobID'] = job_id | ||
| if not df.empty: | ||
| metadata['latitude'] = df['latitude'].values[0] | ||
| metadata['longitude'] = df['longitude'].values[0] | ||
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| df.index = pd.to_datetime(df['valid_time']).dt.tz_localize('UTC') | ||
| df = df.drop(columns=['valid_time', 'latitude', 'longitude']) | ||
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| if map_variables: | ||
| # convert units and rename | ||
| for shortname in df.columns: | ||
| converter = UNITS.get(shortname, _same) | ||
| df[shortname] = converter(df[shortname]) | ||
| df = df.rename(columns=VARIABLE_MAP) | ||
|
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| return df, metadata | ||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,94 @@ | ||
| """ | ||
| tests for pvlib/iotools/era5.py | ||
| """ | ||
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| import pandas as pd | ||
| import pytest | ||
| import pvlib | ||
| import requests | ||
| import os | ||
| from tests.conftest import RERUNS, RERUNS_DELAY, requires_ecmwf_credentials | ||
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| @pytest.fixture | ||
| def params(): | ||
| api_key = os.environ["ECMWF_API_KEY"] | ||
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| return { | ||
| 'latitude': 40.01, 'longitude': -80.01, | ||
| 'start': '2020-06-01', 'end': '2020-06-01', | ||
| 'variables': ['ghi', 'temp_air'], | ||
| 'api_key': api_key, | ||
| } | ||
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| @pytest.fixture | ||
| def expected(): | ||
| index = pd.date_range("2020-06-01 00:00", "2020-06-01 23:59", freq="h", | ||
| tz="UTC") | ||
| index.name = 'valid_time' | ||
| temp_air = [16.6, 15.2, 13.5, 11.2, 10.8, 9.1, 7.3, 6.8, 7.6, 7.4, 8.5, | ||
| 8.1, 9.8, 11.5, 14.1, 17.4, 18.3, 20., 20.7, 20.9, 21.5, | ||
| 21.6, 21., 20.7] | ||
| ghi = [153., 18.4, 0., 0., 0., 0., 0., 0., 0., 0., 0., 60., 229.5, | ||
| 427.8, 620.1, 785.5, 910.1, 984.2, 1005.9, 962.4, 844.1, 685.2, | ||
| 526.9, 331.4] | ||
| df = pd.DataFrame({'temp_air': temp_air, 'ghi': ghi}, index=index) | ||
| return df | ||
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| @requires_ecmwf_credentials | ||
| @pytest.mark.remote_data | ||
| @pytest.mark.flaky(reruns=RERUNS, reruns_delay=RERUNS_DELAY) | ||
| def test_get_era5(params, expected): | ||
| df, meta = pvlib.iotools.get_era5(**params) | ||
| pd.testing.assert_frame_equal(df, expected, check_freq=False, atol=0.1) | ||
| assert meta['longitude'] == -80.0 | ||
| assert meta['latitude'] == 40.0 | ||
| assert isinstance(meta['jobID'], str) | ||
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| @requires_ecmwf_credentials | ||
| @pytest.mark.remote_data | ||
| @pytest.mark.flaky(reruns=RERUNS, reruns_delay=RERUNS_DELAY) | ||
| def test_get_era5_timezone(params, expected): | ||
| params['start'] = pd.to_datetime(params['start']).tz_localize('Etc/GMT+8') | ||
| params['end'] = pd.to_datetime(params['end']).tz_localize('Etc/GMT+8') | ||
| df, meta = pvlib.iotools.get_era5(**params) | ||
| pd.testing.assert_frame_equal(df, expected, check_freq=False, atol=0.1) | ||
| assert meta['longitude'] == -80.0 | ||
| assert meta['latitude'] == 40.0 | ||
| assert isinstance(meta['jobID'], str) | ||
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| @requires_ecmwf_credentials | ||
| @pytest.mark.remote_data | ||
| @pytest.mark.flaky(reruns=RERUNS, reruns_delay=RERUNS_DELAY) | ||
| def test_get_era5_map_variables(params, expected): | ||
| df, meta = pvlib.iotools.get_era5(**params, map_variables=False) | ||
| expected = expected.rename(columns={'temp_air': 't2m', 'ghi': 'ssrd'}) | ||
| df['t2m'] -= 273.15 # apply unit conversions manually | ||
| df['ssrd'] /= 3600 | ||
| pd.testing.assert_frame_equal(df, expected, check_freq=False, atol=0.1) | ||
| assert meta['longitude'] == -80.0 | ||
| assert meta['latitude'] == 40.0 | ||
| assert isinstance(meta['jobID'], str) | ||
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| @requires_ecmwf_credentials | ||
| @pytest.mark.remote_data | ||
| @pytest.mark.flaky(reruns=RERUNS, reruns_delay=RERUNS_DELAY) | ||
| def test_get_era5_error(params): | ||
| params['variables'] = ['nonexistent'] | ||
| match = 'Request failed. Please check the ECMWF website' | ||
| with pytest.raises(Exception, match=match): | ||
| df, meta = pvlib.iotools.get_era5(**params) | ||
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| @requires_ecmwf_credentials | ||
| @pytest.mark.remote_data | ||
| @pytest.mark.flaky(reruns=RERUNS, reruns_delay=RERUNS_DELAY) | ||
| def test_get_era5_timeout(params): | ||
| match = 'Request timed out. Try increasing' | ||
| with pytest.raises(requests.exceptions.Timeout, match=match): | ||
| df, meta = pvlib.iotools.get_era5(**params, timeout=1) |
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