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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:

  1. As keyword arguments when instantiating the Client.
  2. Via the ECMWF_DATASTORES_URL and ECMWF_DATASTORES_KEY environment variables.
  3. 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")

[!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 install
  • Quality assurance: make qa
  • Unit tests: make unit-tests
  • Type 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.

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