Quick Start • Installation • Documentation
ecmwf-datastores-client#
ECMWF Data Stores Service (DSS) API Python client.
Important
This software is Graduated and subject to ECMWF’s guidelines on Software Maturity.
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_URLandECMWF_DATASTORES_KEYenvironment variables.From a configuration file, which must be located at
~/.ecmwfdatastoresrcor at the path specified by theECMWF_DATASTORES_RC_FILEenvironment 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")
Note
All Python code examples in this README are automatically tested as part of the unit test suite.
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
{...}
>>> remote.status
'successful'
>>> remote.results_ready
True
>>> remote.created_at # See also started_at, finished_at, updated_at
datetime.datetime(...)
>>> remote.download("target_6.grib")
'target_6.grib'
>>> remote.get_receipt()
{...}
>>> 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
Developer Workflow#
1. Set Up the Environment#
Configure your virtual environment and pre-commit hooks:
make install
Note
This project uses uv for dependency management. Commit the generated uv.lock file to version control.
2. Run Quality Assurance#
Check formatting, linting, and lockfile consistency:
make qa
3. Commit and Push#
Save and push any automatically formatted changes:
git add .
git commit -m "format codebase and sync lockfile"
git push origin HEAD
The CI/CD pipeline triggers on pull requests, merges to main/upstream, and new releases.
Using the Makefile#
All development tasks are exposed as self-documenting targets in the Makefile. To see a complete list of available targets and their descriptions, run:
make help
This displays all available utility commands, including:
Environment setup:
make installQuality assurance:
make qaUnit tests:
make unit-testsType checking:
make type-check
To run the full set of quality checks, tests, and build steps in a single command, use:
make all
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.