Quick Start • Installation • Documentation

[!IMPORTANT] This software is Incubating and subject to ECMWF’s guidelines on Software Maturity.

ecmwf-datastores-client#

ECMWF Data Stores Service (DSS) API Python client.

Technical documentation: https://ecmwf.github.io/ecmwf-datastores-client/

Installation#

Install with conda:

$ conda install -c conda-forge ecmwf-datastores-client

Install with pip:

$ pip install ecmwf-datastores-client

Configuration#

The Client requires the url to the API root and a valid API key. These can be provided in three ways, in order of precedence:

As keyword arguments when instantiating the Client.
Via the ECMWF_DATASTORES_URL and ECMWF_DATASTORES_KEY environment variables.
From a configuration file, which must be located at ~/.ecmwfdatastoresrc or at the path specified by the ECMWF_DATASTORES_RC_FILE environment variable.

$ cat $HOME/.ecmwfdatastoresrc
url: https://cds.climate.copernicus.eu/api
key: xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx

Quick Start#

Configure the logging level to display INFO messages:

>>> import logging
>>> logging.basicConfig(level="INFO")

Instantiate the API client and optionally verify authentication:

>>> from ecmwf.datastores import Client
>>> client = Client()
>>> client.check_authentication()  # optional check
{...}

Retrieve data:

>>> collection_id = "reanalysis-era5-pressure-levels"
>>> request = {
...     "product_type": ["reanalysis"],
...     "variable": ["temperature"],
...     "year": ["2022"],
...     "month": ["01"],
...     "day": ["01"],
...     "time": ["00:00"],
...     "pressure_level": ["1000"],
...     "data_format": "grib",
...     "download_format": "unarchived"
...     }

>>> client.retrieve(collection_id, request, target="target_1.grib")  # blocks
'target_1.grib'

Alternative methods to retrieve data:

>>> remote = client.submit(collection_id, request)  # doesn't block
>>> remote
Remote(...)
>>> remote.download("target_2.grib")  # blocks
'target_2.grib'

>>> results = client.submit_and_wait_on_results(collection_id, request)  # blocks
>>> results
Results(...)
>>> results.download("target_3.grib")
'target_3.grib'

>>> client.download_results(remote.request_id, "target_4.grib")  # blocks
'target_4.grib'

List all collection IDs sorted by last update:

>>> collections = client.get_collections(sortby="update")

>>> collection_ids = []
>>> while collections is not None:  # Loop over pages
...     collection_ids.extend(collections.collection_ids)
...     collections = collections.next  # Move to the next page

>>> collection_ids
[...]
>>> collection_id in collection_ids
True

Explore a collection:

>>> collection = client.get_collection(collection_id)

>>> collection.id == collection_id
True
>>> collection.title
'...'
>>> collection.description
'...'

>>> collection.published_at
datetime.datetime(...)
>>> collection.updated_at
datetime.datetime(...)

>>> collection.begin_datetime
datetime.datetime(...)
>>> collection.end_datetime
datetime.datetime(...)
>>> collection.bbox
(...)

>>> collection.submit(request)
Remote(...)

>>> collection.apply_constraints(request)
{...}

Interact with results:

>>> results = client.get_results(remote.request_id)

>>> results.content_length > 0
True
>>> results.content_type
'application/x-grib'
>>> results.location
'...'

>>> results.download("target_5.grib")
'target_5.grib'

List all successful jobs, sorted by newest first:

>>> jobs = client.get_jobs(sortby="-created", status="successful")

>>> request_ids = []
>>> while jobs is not None:  # Loop over pages
...     request_ids.extend(jobs.request_ids)
...     jobs = jobs.next  # Move to the next page

>>> request_ids
[...]
>>> remote.request_id in request_ids
True

Interact with a previously submitted job:

>>> remote = client.get_remote(remote.request_id)

>>> remote.collection_id == collection_id
True
>>> remote.request == request
True

>>> remote.status
'successful'
>>> remote.results_ready
True

>>> remote.created_at
datetime.datetime(...)
>>> remote.started_at
datetime.datetime(...)
>>> remote.finished_at
datetime.datetime(...)
>>> remote.updated_at == remote.finished_at
True

>>> remote.download("target_6.grib")
'target_6.grib'

>>> remote.get_results()
Results(...)

>>> remote.delete()
{...}

Apply constraints and find the number of available days in a given month:

>>> month = {"year": "2000", "month": "02"}
>>> constrained_request = client.apply_constraints(collection_id, month)

>>> len(constrained_request["day"])
29

Workflow for developers/contributors#

For best experience create a new conda environment (e.g. DEVELOP) with Python 3.11:

conda create -n DEVELOP -c conda-forge python=3.11
conda activate DEVELOP

Before pushing to GitHub, run the following commands:

Update conda environment: make conda-env-update
Install this package: pip install -e .
Sync with the latest template (optional): make template-update
Run quality assurance checks: make qa
Run tests: make unit-tests
Run the static type checker: make type-check
Build the documentation (see Sphinx tutorial): make docs-build

License#

Copyright 2022, European Union.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.