diff --git a/doc/esmvalcore/recipe.rst b/doc/esmvalcore/recipe.rst
index c1396a416..6ba46e184 100644
--- a/doc/esmvalcore/recipe.rst
+++ b/doc/esmvalcore/recipe.rst
@@ -147,7 +147,7 @@ arguments):
           operator: mean
         multi_model_statistics:
           span: overlap
-          statistics: [mean ]
+          statistics: [mean]
 
 .. note::
 
@@ -161,20 +161,138 @@ arguments):
 Recipe section: ``diagnostics``
 ===============================
 
-The diagnostics section includes one or more diagnostics. Each diagnostics will
-include:
+The diagnostics section includes one or more diagnostics. Each diagnostic
+section will include:
 
-- a list of which variables to load;
-- a description of the variables (optional);
-- the preprocessor to be applied to each variable;
-- the script to be run;
+- the variable(s) to preprocess, including the preprocessor to be applied to each variable;
+- the diagnostic script(s) to be run;
+- a description of the diagnostic and lists of themes and realms that it applies to;
 - an optional ``additional_datasets`` section.
 
-The ``additional_datasets`` can add datasets beyond those listed in the the
-Datasets_ section. This is useful if specific datasets need to be used only by
-a specific diagnostic. The ``additional_datasets`` can also be used to add
-variable specific datasets. This is also a good way to add observational
-datasets, which are usually variable-specific.
+The diagnostics section defines tasks
+-------------------------------------
+The diagnostic section(s) define the tasks that will be executed when running the recipe.
+For each variable a preprocesing task will be defined and for each diagnostic script a
+diagnostic task will be defined. If variables need to be derived
+from other variables, a preprocessing task for each of the variables
+needed to derive that variable will be defined as well. These tasks can be viewed
+in the main_log_debug.txt file that is produced every run. Each task has a unique
+name that defines the subdirectory where the results of that task are stored. Task
+names start with the name of the diagnostic section followed by a '/' and then
+the name of the variable section for a preprocessing task or the name of the diagnostic
+script section for a diagnostic task.
+
+A (simplified) example diagnostics section could look like
+
+.. code-block:: yaml
+
+  diagnostics:
+    diagnostic_name:
+      description: Air temperature tutorial diagnostic.
+      themes:
+        - phys
+      realms:
+        - atmos
+      variables:
+        variable_name:
+          short_name: ta
+          preprocessor: preprocessor_name
+          mip: Amon
+      scripts:
+        script_name:
+          script: examples/diagnostic.py
+
+
+Note that the example recipe above contains a single diagnostic section
+called ``diagnostic_name`` and will result in two tasks:
+
+- a preprocessing task called ``diagnostic_name/variable_name`` that will preprocess
+  air temperature data for each dataset in the Datasets_ section of the recipe (not shown).
+- a diagnostic task called ``diagnostic_name/script_name``
+
+The path to the script provided in the ``script`` option should be
+either the absolute path to the script, or the path relative to the
+``esmvaltool/diag_scripts`` directory.
+
+Ancestor tasks
+--------------
+Some tasks require the result of other tasks to be ready before they can start,
+e.g. a diagnostic script needs the preprocessed variable data to start. Thus
+each tasks has zero or more ancestor tasks. By default, each diagnostic task
+in a diagnostic section has all variable preprocessing tasks in that same section
+as ancestors. However, this can be changed using the ``ancestors`` keyword. Note
+that wildcard expansion can be used to define ancestors.
+
+.. code-block:: yaml
+
+  diagnostics:
+    diagnostic_1:
+      variables:
+        airtemp:
+          short_name: ta
+          preprocessor: preprocessor_name
+          mip: Amon
+      scripts:
+        script_a:
+          script: diagnostic_a.py
+    diagnostic_2:
+      variables:
+        precip:
+          short_name: pr
+          preprocessor: preprocessor_name
+          mip: Amon
+      scripts:
+        script_b:
+          script: diagnostic_b.py
+          ancestors: [diagnostic_1/script_a, precip]
+
+
+The example recipe above will result in four tasks:
+
+- a preprocessing task called ``diagnostic_1/airtemp``
+- a diagnostic task called ``diagnostic_1/script_a``
+- a preprocessing task called ``diagnostic_2/precip``
+- a diagnostic task called ``diagnostic_2/script_b``
+
+the preprocessing tasks do not have any ancestors, while the diagnostic_a.py
+script will receive the preprocessed air temperature data
+(has ancestor ``diagnostic_1/airtemp``) and the diagnostic_b.py
+script will receive the results of diagnostic_a.py and the preprocessed precipitation
+data (has ancestors ``diagnostic_1/script_a`` and ``diagnostic_2/precip``).
+
+Task priority
+-------------
+Tasks are assigned a priority, with tasks appearing earlier on in the recipe
+getting higher priority. The tasks will be executed sequentially or in parellel,
+depending on the setting of ``max_parallel_tasks`` in the :ref:`user configuration file`.
+When there are fewer than ``max_parallel_tasks`` running, tasks will be started
+according to their priority. For obvious reasons, only tasks that are not waiting for
+ancestor tasks can be started. This feature makes it possible to
+reduce the processing time of recipes with many tasks, by placing tasks that
+take relatively long near the top of the recipe. Of course this only works when
+settings ``max_parallel_tasks`` to a value larger than 1. The current priority
+and run time of individual tasks can be seen in the log messages shown when
+running the tool (a lower number means higher priority).
+
+Variable and dataset definitions
+--------------------------------
+To define a variable/dataset combination that corresponds to an actual
+variable from a dataset, the keys in each variable section
+are combined with the keys of each dataset definition. If two versions of the same
+key are provided, then the key in the datasets section will take precedence
+over the keys in variables section. For many recipes it makes more sense to
+define the ``start_year`` and ``end_year`` items in the variable section,
+because the diagnostic script assumes that all the data has the same time
+range.
+
+Diagnostic and variable specific datasets
+-----------------------------------------
+The ``additional_datasets`` option can be used to add datasets beyond those
+listed in the Datasets_ section. This is useful if specific datasets need to
+be used only by a specific diagnostic or variable, i.e. it can be added both
+at diagnostic level, where it will apply to all variables in that diagnostic
+section or at individual variable level. For example, this can be a good way
+to add observational datasets, which are usually variable-specific.
 
 Running a simple diagnostic
 ---------------------------
@@ -199,22 +317,9 @@ map scipt, ``ocean/diagnostic_maps.py``.
         Global_Ocean_Surface_regrid_map:
           script: ocean/diagnostic_maps.py
 
-To define a variable/dataset combination, the keys in the diagnostic section
-are combined with the keys from datasets section. If two versions of the same
-key are provided, then the key in the datasets section will take precedence
-over the keys in variables section. For many recipes it makes more sense to
-define the ``start_year`` and ``end_year`` items in the variable section,
-because the diagnostic script assumes that all the data has the same time
-range.
-
-Note that the path to the script provided in the `script` option should be
-either the absolute path to the script, or the path relative to the
-``esmvaltool/diag_scripts`` directory.
-
-
-Passing arguments to a diagnostic
----------------------------------
-The ``diagnostics`` section may include a lot of arguments that can be used by
+Passing arguments to a diagnostic script
+----------------------------------------
+The diagnostic script section(s) may include custom arguments that can be used by
 the diagnostic script; these arguments are stored at runtime in a dictionary
 that is then made available to the diagnostic script via the interface link,
 independent of the language the diagnostic script is written in. Here is an
diff --git a/esmvalcore/_recipe.py b/esmvalcore/_recipe.py
index 684dfa07b..ee0acc2a0 100644
--- a/esmvalcore/_recipe.py
+++ b/esmvalcore/_recipe.py
@@ -1155,6 +1155,7 @@ class Recipe:
         logger.info("Creating tasks from recipe")
         tasks = set()
 
+        priority = 0
         for diagnostic_name, diagnostic in self.diagnostics.items():
             logger.info("Creating tasks for diagnostic %s", diagnostic_name)
 
@@ -1169,7 +1170,10 @@ class Recipe:
                     config_user=self._cfg,
                     task_name=task_name,
                 )
+                for task0 in task.flatten():
+                    task0.priority = priority
                 tasks.add(task)
+                priority += 1
 
             # Create diagnostic tasks
             for script_name, script_cfg in diagnostic['scripts'].items():
@@ -1181,7 +1185,9 @@ class Recipe:
                     settings=script_cfg['settings'],
                     name=task_name,
                 )
+                task.priority = priority
                 tasks.add(task)
+                priority += 1
 
         check.tasks_valid(tasks)
 
diff --git a/esmvalcore/_task.py b/esmvalcore/_task.py
index 8ab7cb68d..135192178 100644
--- a/esmvalcore/_task.py
+++ b/esmvalcore/_task.py
@@ -10,12 +10,12 @@ import subprocess
 import threading
 import time
 from copy import deepcopy
-from multiprocessing import Pool, cpu_count
+from multiprocessing import Pool
 
 import psutil
 import yaml
 
-from ._config import TAGS, replace_tags, DIAGNOSTICS_PATH
+from ._config import DIAGNOSTICS_PATH, TAGS, replace_tags
 from ._provenance import TrackedFile, get_task_provenance
 
 logger = logging.getLogger(__name__)
@@ -193,12 +193,14 @@ def write_ncl_settings(settings, filename, mode='wt'):
 class BaseTask:
     """Base class for defining task classes."""
 
-    def __init__(self, ancestors=None, name=''):
+    def __init__(self, ancestors=None, name='', products=None):
         """Initialize task."""
         self.ancestors = [] if ancestors is None else ancestors
+        self.products = set() if products is None else set(products)
         self.output_files = None
         self.name = name
         self.activity = None
+        self.priority = 0
 
     def initialize_provenance(self, recipe_entity):
         """Initialize task provenance activity."""
@@ -224,8 +226,11 @@ class BaseTask:
                 input_files.extend(task.run())
             logger.info("Starting task %s in process [%s]", self.name,
                         os.getpid())
+            start = datetime.datetime.now()
             self.output_files = self._run(input_files)
-            logger.info("Successfully completed task %s", self.name)
+            runtime = datetime.datetime.now() - start
+            logger.info("Successfully completed task %s (priority %s) in %s",
+                        self.name, self.priority, runtime)
 
         return self.output_files
 
@@ -254,10 +259,9 @@ class DiagnosticTask(BaseTask):
 
     def __init__(self, script, settings, output_dir, ancestors=None, name=''):
         """Create a diagnostic task."""
-        super(DiagnosticTask, self).__init__(ancestors=ancestors, name=name)
+        super().__init__(ancestors=ancestors, name=name)
         self.script = script
         self.settings = settings
-        self.products = set()
         self.output_dir = output_dir
         self.cmd = self._initialize_cmd(script)
         self.log = os.path.join(settings['run_dir'], 'log.txt')
@@ -266,8 +270,7 @@ class DiagnosticTask(BaseTask):
 
     def _initialize_cmd(self, script):
         """Create a an executable command from script."""
-        diagnostics_root = os.path.join(
-            DIAGNOSTICS_PATH, 'diag_scripts')
+        diagnostics_root = os.path.join(DIAGNOSTICS_PATH, 'diag_scripts')
         script_file = os.path.abspath(os.path.join(diagnostics_root, script))
 
         if not os.path.isfile(script_file):
@@ -456,8 +459,8 @@ class DiagnosticTask(BaseTask):
             env['MPLBACKEND'] = 'Agg'
         else:
             # Make diag_scripts path available to diagostics scripts
-            env['diag_scripts'] = os.path.join(
-                DIAGNOSTICS_PATH, 'diag_scripts')
+            env['diag_scripts'] = os.path.join(DIAGNOSTICS_PATH,
+                                               'diag_scripts')
 
         cmd = list(self.cmd)
         settings_file = self.write_settings()
@@ -601,53 +604,46 @@ def _run_tasks_sequential(tasks):
     n_tasks = len(get_flattened_tasks(tasks))
     logger.info("Running %s tasks sequentially", n_tasks)
 
-    for task in get_independent_tasks(tasks):
+    tasks = get_independent_tasks(tasks)
+    for task in sorted(tasks, key=lambda t: t.priority):
         task.run()
 
 
 def _run_tasks_parallel(tasks, max_parallel_tasks=None):
     """Run tasks in parallel."""
     scheduled = get_flattened_tasks(tasks)
-    running = []
-    results = []
+    running = {}
 
     n_scheduled, n_running = len(scheduled), len(running)
     n_tasks = n_scheduled
 
-    pool = Pool(processes=max_parallel_tasks)
-
-    logger.info("Running %s tasks using at most %s processes", n_tasks,
-                max_parallel_tasks or cpu_count())
+    if max_parallel_tasks is None:
+        max_parallel_tasks = os.cpu_count()
+    if max_parallel_tasks > n_tasks:
+        max_parallel_tasks = n_tasks
+    logger.info("Running %s tasks using %s processes", n_tasks,
+                max_parallel_tasks)
 
     def done(task):
         """Assume a task is done if it not scheduled or running."""
         return not (task in scheduled or task in running)
 
+    pool = Pool(processes=max_parallel_tasks)
     while scheduled or running:
         # Submit new tasks to pool
-        just_scheduled = []
-        for task in scheduled:
-            if not task.ancestors or all(done(t) for t in task.ancestors):
-                result = pool.apply_async(_run_task, [task])
-                results.append(result)
-                running.append(task)
-                just_scheduled.append(task)
-        for task in just_scheduled:
-            scheduled.remove(task)
+        for task in sorted(scheduled, key=lambda t: t.priority):
+            if len(running) >= max_parallel_tasks:
+                break
+            if all(done(t) for t in task.ancestors):
+                future = pool.apply_async(_run_task, [task])
+                running[task] = future
+                scheduled.remove(task)
 
         # Handle completed tasks
-        for task, result in zip(running, results):
-            if result.ready():
-                task.output_files, updated_products = result.get()
-                for updated in updated_products:
-                    for original in task.products:
-                        if original.filename == updated.filename:
-                            updated.copy_provenance(target=original)
-                            break
-                    else:
-                        task.products.add(updated)
-                running.remove(task)
-                results.remove(result)
+        ready = {t for t in running if running[t].ready()}
+        for task in ready:
+            _copy_results(task, running[task])
+            running.pop(task)
 
         # Wait if there are still tasks running
         if running:
@@ -658,14 +654,25 @@ def _run_tasks_parallel(tasks, max_parallel_tasks=None):
             n_scheduled, n_running = len(scheduled), len(running)
             n_done = n_tasks - n_scheduled - n_running
             logger.info(
-                "Progress: %s tasks running or queued, %s tasks waiting for "
-                "ancestors, %s/%s done", n_running, n_scheduled, n_done,
-                n_tasks)
+                "Progress: %s tasks running, %s tasks waiting for ancestors, "
+                "%s/%s done", n_running, n_scheduled, n_done, n_tasks)
 
     pool.close()
     pool.join()
 
 
+def _copy_results(task, future):
+    """Update task with the results from the remote process."""
+    task.output_files, updated_products = future.get()
+    for updated in updated_products:
+        for original in task.products:
+            if original.filename == updated.filename:
+                updated.copy_provenance(target=original)
+                break
+        else:
+            task.products.add(updated)
+
+
 def _run_task(task):
     """Run task and return the result."""
     output_files = task.run()
diff --git a/esmvalcore/preprocessor/__init__.py b/esmvalcore/preprocessor/__init__.py
index eac02111a..6793d2c3e 100644
--- a/esmvalcore/preprocessor/__init__.py
+++ b/esmvalcore/preprocessor/__init__.py
@@ -360,9 +360,8 @@ class PreprocessingTask(BaseTask):
             write_ncl_interface=False,
     ):
         """Initialize"""
-        super(PreprocessingTask, self).__init__(ancestors=ancestors, name=name)
         _check_multi_model_settings(products)
-        self.products = set(products)
+        super().__init__(ancestors=ancestors, name=name, products=products)
         self.order = list(order)
         self.debug = debug
         self.write_ncl_interface = write_ncl_interface

Prioritize task execution by recipe order 
This will allow recipe authors to put long running tasks at the beginning of the recipe, so the total run time is minimized when executing recipes in which the duration of the various tasks greatly varies.
diff --git a/tests/integration/test_task.py b/tests/integration/test_task.py
new file mode 100644
index 000000000..4f0f9e854
--- /dev/null
+++ b/tests/integration/test_task.py
@@ -0,0 +1,82 @@
+import os
+from functools import partial
+from multiprocessing.pool import ThreadPool
+
+import pytest
+
+import esmvalcore
+from esmvalcore._task import (BaseTask, _run_tasks_parallel,
+                              _run_tasks_sequential, run_tasks)
+
+
+@pytest.fixture
+def example_tasks():
+    """Example tasks for testing the task runners."""
+    tasks = set()
+    for i in range(3):
+        task = BaseTask(
+            name=f'task{i}',
+            ancestors=[
+                BaseTask(name=f'task{i}-ancestor{j}') for j in range(3)
+            ],
+        )
+        for task0 in task.flatten():
+            task0.priority = i
+        tasks.add(task)
+
+    return tasks
+
+
+@pytest.mark.parametrize('max_parallel_tasks', [1, 2, 3, 4, 16, None])
+def test_run_tasks(monkeypatch, tmp_path, max_parallel_tasks, example_tasks):
+    """Check that tasks are run correctly."""
+    def _run(self, input_files):
+        output_file = tmp_path / self.name
+
+        msg = ('running {} in thread {}, using input {}, generating {}'.format(
+            self.name, os.getpid(), input_files, output_file))
+        print(msg)
+
+        # Check that the output is created just once
+        assert not output_file.exists()
+        output_file.write_text(msg)
+        output_file = str(output_file)
+
+        # Check that ancestor results are provided correctly
+        assert len(self.ancestors) == len(input_files)
+        for ancestor in self.ancestors:
+            assert len(ancestor.output_files) == 1
+            assert ancestor.output_files[0].startswith(output_file)
+            assert str(tmp_path / ancestor.name) in input_files
+
+        return [output_file]
+
+    monkeypatch.setattr(BaseTask, '_run', _run)
+
+    run_tasks(example_tasks, max_parallel_tasks)
+
+    for task in example_tasks:
+        print(task.name, task.output_files)
+        assert task.output_files
+
+
+@pytest.mark.parametrize('runner', [
+    _run_tasks_sequential,
+    partial(_run_tasks_parallel, max_parallel_tasks=1),
+])
+def test_runner_uses_priority(monkeypatch, runner, example_tasks):
+    """Check that the runner tries to respect task priority."""
+    order = []
+
+    def _run(self, input_files):
+        print(f'running task {self.name} with priority {self.priority}')
+        order.append(self.priority)
+        return [f'{self.name}_test.nc']
+
+    monkeypatch.setattr(BaseTask, '_run', _run)
+    monkeypatch.setattr(esmvalcore._task, 'Pool', ThreadPool)
+
+    runner(example_tasks)
+    print(order)
+    assert len(order) == 12
+    assert order == sorted(order)

environment.yml
pip install -e '.[develop]'
parse_log_pytest
environment.yml
pytest pytest-cov pytest-xdist pytest-mock pytest-asyncio
apt-get update apt-get install -y gcc
3.9
pytest --no-header -rA --tb=line --color=no -p no:cacheprovider -W ignore::DeprecationWarning
alabaster==0.7.16
antlr4-python3-runtime @ file:///home/conda/feedstock_root/build_artifacts/antlr-python-runtime-meta_1662478324044/work
astroid==3.3.9
attrs==25.3.0
babel==2.17.0
build==1.2.2.post1
Cartopy @ file:///home/conda/feedstock_root/build_artifacts/cartopy_1726175364746/work
certifi @ file:///home/conda/feedstock_root/build_artifacts/certifi_1739515848642/work/certifi
cf-units @ file:///home/conda/feedstock_root/build_artifacts/cf-units_1725441254906/work
cftime @ file:///home/conda/feedstock_root/build_artifacts/cftime_1725400455427/work
charset-normalizer==3.4.1
click @ file:///home/conda/feedstock_root/build_artifacts/click_1734858813237/work
click-plugins==1.1.1
cligj==0.7.2
cloudpickle @ file:///home/conda/feedstock_root/build_artifacts/cloudpickle_1736947526808/work
colorama==0.4.6
contourpy @ file:///home/conda/feedstock_root/build_artifacts/contourpy_1727293517607/work
coverage==7.8.0
cycler @ file:///home/conda/feedstock_root/build_artifacts/cycler_1733332471406/work
Cython @ file:///home/conda/feedstock_root/build_artifacts/cython_1739227939853/work
dask @ file:///home/conda/feedstock_root/build_artifacts/dask-core_1722976580461/work
dill==0.3.9
docutils==0.21.2
dodgy==0.2.1
easytest==0.1.5
esmpy @ file:///home/conda/feedstock_root/build_artifacts/esmpy_1743174093731/work/src/addon/esmpy
-e git+https://github.com/ESMValGroup/ESMValCore.git@d917aa9e14fdc6be3870949038bab78a16880522#egg=ESMValCore
exceptiongroup==1.2.2
execnet==2.1.1
fiona==1.10.1
flake8==7.2.0
flake8-polyfill==1.0.2
fonttools @ file:///home/conda/feedstock_root/build_artifacts/fonttools_1738940303262/work
fsspec @ file:///home/conda/feedstock_root/build_artifacts/fsspec_1743361113926/work
gitdb==4.0.12
GitPython==3.1.44
idna==3.10
imagesize==1.4.1
importlib_metadata @ file:///home/conda/feedstock_root/build_artifacts/importlib-metadata_1737420181517/work
importlib_resources @ file:///home/conda/feedstock_root/build_artifacts/importlib_resources_1736252299705/work
iniconfig==2.1.0
isodate==0.6.1
isort==6.0.1
Jinja2 @ file:///home/conda/feedstock_root/build_artifacts/jinja2_1741263328855/work
kiwisolver @ file:///home/conda/feedstock_root/build_artifacts/kiwisolver_1725459266648/work
llvmlite==0.43.0
locket @ file:///home/conda/feedstock_root/build_artifacts/locket_1650660393415/work
lxml==5.3.1
MarkupSafe @ file:///home/conda/feedstock_root/build_artifacts/markupsafe_1733219680183/work
matplotlib==3.9.4
mccabe==0.7.0
mock==5.2.0
munkres==1.1.4
nc-time-axis==1.4.1
netCDF4 @ file:///home/conda/feedstock_root/build_artifacts/netcdf4_1733253338730/work
networkx==3.2.1
nose==1.3.7
numba==0.60.0
numpy @ file:///home/conda/feedstock_root/build_artifacts/numpy_1732314280888/work/dist/numpy-2.0.2-cp39-cp39-linux_x86_64.whl#sha256=62d98eb3da9f13e6b227c430d01026b7427f341b3fdcb838430f2a9e520417b1
packaging @ file:///home/conda/feedstock_root/build_artifacts/packaging_1733203243479/work
partd @ file:///home/conda/feedstock_root/build_artifacts/partd_1715026491486/work
pathspec==0.12.1
pep8-naming==0.10.0
pillow @ file:///home/conda/feedstock_root/build_artifacts/pillow_1735929703139/work
platformdirs==4.3.7
pluggy==1.5.0
prospector==1.16.1
prov==2.0.1
psutil==7.0.0
pycodestyle==2.13.0
pydocstyle==6.3.0
pydot==3.0.4
pyflakes==3.3.1
Pygments==2.19.1
pylint==3.3.6
pylint-celery==0.3
pylint-django==2.6.1
pylint-plugin-utils==0.8.2
pyparsing @ file:///home/conda/feedstock_root/build_artifacts/pyparsing_1743089729650/work
pyproj @ file:///home/conda/feedstock_root/build_artifacts/pyproj_1726679693937/work
pyproject_hooks==1.2.0
pyroma==4.2
pyshp @ file:///home/conda/feedstock_root/build_artifacts/pyshp_1733821528126/work
pytest==8.3.5
pytest-asyncio==0.26.0
pytest-cov==6.0.0
pytest-env==1.1.5
pytest-flake8==1.3.0
pytest-html==4.1.1
pytest-metadata==3.1.1
pytest-mock==3.14.0
pytest-xdist==3.6.1
python-dateutil @ file:///home/conda/feedstock_root/build_artifacts/python-dateutil_1733215673016/work
pytz==2025.2
PyYAML @ file:///home/conda/feedstock_root/build_artifacts/pyyaml_1737454647378/work
rdflib==6.3.2
requests==2.32.3
requirements-detector==1.3.2
scipy @ file:///home/conda/feedstock_root/build_artifacts/scipy-split_1716470218293/work/dist/scipy-1.13.1-cp39-cp39-linux_x86_64.whl#sha256=e6696cb8683d94467891b7648e068a3970f6bc0a1b3c1aa7f9bc89458eafd2f0
scitools-iris @ file:///home/conda/feedstock_root/build_artifacts/iris_1709571258262/work
semver==3.0.4
setoptconf-tmp==0.3.1
shapely @ file:///home/conda/feedstock_root/build_artifacts/shapely_1741166945909/work
six @ file:///home/conda/feedstock_root/build_artifacts/six_1733380938961/work
smmap==5.0.2
snowballstemmer==2.2.0
Sphinx==7.4.7
sphinx-rtd-theme==3.0.2
sphinxcontrib-applehelp==2.0.0
sphinxcontrib-devhelp==2.0.0
sphinxcontrib-htmlhelp==2.1.0
sphinxcontrib-jquery==4.1
sphinxcontrib-jsmath==1.0.1
sphinxcontrib-qthelp==2.0.0
sphinxcontrib-serializinghtml==2.0.0
stratify @ file:///home/conda/feedstock_root/build_artifacts/python-stratify_1725548815810/work
toml==0.10.2
tomli==2.2.1
tomlkit==0.13.2
toolz @ file:///home/conda/feedstock_root/build_artifacts/toolz_1733736030883/work
trove-classifiers==2025.3.19.19
typing_extensions==4.13.0
unicodedata2 @ file:///home/conda/feedstock_root/build_artifacts/unicodedata2_1736692503055/work
urllib3==2.3.0
vmprof==0.4.18.1
xxhash @ file:///home/conda/feedstock_root/build_artifacts/python-xxhash_1740594800419/work
yamale==6.0.0
yamllint==1.37.0
yapf==0.43.0
zipp @ file:///home/conda/feedstock_root/build_artifacts/zipp_1732827521216/work

name: ESMValCore
channels:
  - https://repo.anaconda.com/pkgs/main
  - https://repo.anaconda.com/pkgs/r
  - conda-forge
dependencies:
  - _libgcc_mutex=0.1=conda_forge
  - _openmp_mutex=4.5=2_gnu
  - adwaita-icon-theme=48.0=unix_0
  - antlr-python-runtime=4.11.1=pyhd8ed1ab_0
  - at-spi2-atk=2.38.0=h0630a04_3
  - at-spi2-core=2.40.3=h0630a04_0
  - atk-1.0=2.38.0=h04ea711_2
  - attr=2.5.1=h166bdaf_1
  - binutils_impl_linux-64=2.43=h4bf12b8_4
  - binutils_linux-64=2.43=h4852527_4
  - blosc=1.21.6=he440d0b_1
  - brotli=1.1.0=hb9d3cd8_2
  - brotli-bin=1.1.0=hb9d3cd8_2
  - bzip2=1.0.8=h4bc722e_7
  - c-ares=1.34.4=hb9d3cd8_0
  - ca-certificates=2025.1.31=hbcca054_0
  - cairo=1.18.4=h3394656_0
  - cartopy=0.23.0=py39h3b40f6f_2
  - certifi=2025.1.31=pyhd8ed1ab_0
  - cf-units=3.2.0=py39hf3d9206_6
  - cftime=1.6.4=py39hf3d9206_1
  - click=8.1.8=pyh707e725_0
  - cloudpickle=3.1.1=pyhd8ed1ab_0
  - contourpy=1.3.0=py39h74842e3_2
  - cycler=0.12.1=pyhd8ed1ab_1
  - cython=3.0.12=py39hbce0bbb_0
  - dask-core=2024.8.0=pyhd8ed1ab_0
  - dbus=1.13.6=h5008d03_3
  - epoxy=1.5.10=h166bdaf_1
  - esmf=8.8.0=mpi_mpich_h7cf99a1_100
  - esmpy=8.8.0=pyhecae5ae_1
  - expat=2.6.4=h5888daf_0
  - font-ttf-dejavu-sans-mono=2.37=hab24e00_0
  - font-ttf-inconsolata=3.000=h77eed37_0
  - font-ttf-source-code-pro=2.038=h77eed37_0
  - font-ttf-ubuntu=0.83=h77eed37_3
  - fontconfig=2.15.0=h7e30c49_1
  - fonts-conda-ecosystem=1=0
  - fonts-conda-forge=1=0
  - fonttools=4.56.0=py39h9399b63_0
  - freetype=2.13.3=h48d6fc4_0
  - fribidi=1.0.10=h36c2ea0_0
  - fsspec=2025.3.1=pyhd8ed1ab_0
  - gcc_impl_linux-64=14.2.0=hdb7739f_2
  - gcc_linux-64=14.2.0=h5910c8f_8
  - gdk-pixbuf=2.42.12=hb9ae30d_0
  - geos=3.13.1=h97f6797_0
  - glib-tools=2.84.0=h4833e2c_0
  - graphite2=1.3.13=h59595ed_1003
  - graphviz=12.2.1=h5ae0cbf_1
  - gtk3=3.24.43=h0c6a113_5
  - gts=0.7.6=h977cf35_4
  - harfbuzz=11.0.0=h76408a6_0
  - hdf4=4.2.15=h2a13503_7
  - hdf5=1.14.3=mpi_mpich_h7f58efa_9
  - hicolor-icon-theme=0.17=ha770c72_2
  - icu=75.1=he02047a_0
  - importlib-metadata=8.6.1=pyha770c72_0
  - importlib-resources=6.5.2=pyhd8ed1ab_0
  - importlib_metadata=8.6.1=hd8ed1ab_0
  - importlib_resources=6.5.2=pyhd8ed1ab_0
  - iris=3.8.1=pyha770c72_0
  - jinja2=3.1.6=pyhd8ed1ab_0
  - kernel-headers_linux-64=3.10.0=he073ed8_18
  - keyutils=1.6.1=h166bdaf_0
  - kiwisolver=1.4.7=py39h74842e3_0
  - krb5=1.21.3=h659f571_0
  - lcms2=2.17=h717163a_0
  - ld_impl_linux-64=2.43=h712a8e2_4
  - lerc=4.0.0=h27087fc_0
  - libaec=1.1.3=h59595ed_0
  - libblas=3.9.0=31_h59b9bed_openblas
  - libbrotlicommon=1.1.0=hb9d3cd8_2
  - libbrotlidec=1.1.0=hb9d3cd8_2
  - libbrotlienc=1.1.0=hb9d3cd8_2
  - libcap=2.75=h39aace5_0
  - libcblas=3.9.0=31_he106b2a_openblas
  - libcups=2.3.3=h4637d8d_4
  - libcurl=8.12.1=h332b0f4_0
  - libdeflate=1.23=h4ddbbb0_0
  - libedit=3.1.20250104=pl5321h7949ede_0
  - libev=4.33=hd590300_2
  - libexpat=2.6.4=h5888daf_0
  - libfabric=2.1.0=ha770c72_0
  - libfabric1=2.1.0=h14e6f36_0
  - libffi=3.4.6=h2dba641_0
  - libgcc=14.2.0=h767d61c_2
  - libgcc-devel_linux-64=14.2.0=h9c4974d_102
  - libgcc-ng=14.2.0=h69a702a_2
  - libgcrypt-lib=1.11.0=hb9d3cd8_2
  - libgd=2.3.3=h6f5c62b_11
  - libgfortran=14.2.0=h69a702a_2
  - libgfortran-ng=14.2.0=h69a702a_2
  - libgfortran5=14.2.0=hf1ad2bd_2
  - libglib=2.84.0=h2ff4ddf_0
  - libgomp=14.2.0=h767d61c_2
  - libgpg-error=1.51=hbd13f7d_1
  - libhwloc=2.11.2=default_h0d58e46_1001
  - libiconv=1.18=h4ce23a2_1
  - libjpeg-turbo=3.0.0=hd590300_1
  - liblapack=3.9.0=31_h7ac8fdf_openblas
  - liblzma=5.6.4=hb9d3cd8_0
  - libnetcdf=4.9.2=mpi_mpich_h761946e_14
  - libnghttp2=1.64.0=h161d5f1_0
  - libnl=3.11.0=hb9d3cd8_0
  - libnsl=2.0.1=hd590300_0
  - libopenblas=0.3.29=pthreads_h94d23a6_0
  - libpnetcdf=1.13.0=mpi_mpich_hdce4f7b_101
  - libpng=1.6.47=h943b412_0
  - librsvg=2.58.4=he92a37e_3
  - libsanitizer=14.2.0=hed042b8_2
  - libsqlite=3.49.1=hee588c1_2
  - libssh2=1.11.1=hf672d98_0
  - libstdcxx=14.2.0=h8f9b012_2
  - libstdcxx-ng=14.2.0=h4852527_2
  - libsystemd0=257.4=h4e0b6ca_1
  - libtiff=4.7.0=hd9ff511_3
  - libudev1=257.4=hbe16f8c_1
  - libudunits2=2.2.28=h40f5838_3
  - libunwind=1.7.2=he02047a_0
  - libuuid=2.38.1=h0b41bf4_0
  - libwebp-base=1.5.0=h851e524_0
  - libxcb=1.17.0=h8a09558_0
  - libxcrypt=4.4.36=hd590300_1
  - libxkbcommon=1.8.1=hc4a0caf_0
  - libxml2=2.13.7=h8d12d68_0
  - libzip=1.11.2=h6991a6a_0
  - libzlib=1.3.1=hb9d3cd8_2
  - locket=1.0.0=pyhd8ed1ab_0
  - lz4-c=1.10.0=h5888daf_1
  - markupsafe=3.0.2=py39h9399b63_1
  - matplotlib-base=3.9.4=py39h16632d1_0
  - mpi=1.0.1=mpich
  - mpich=4.3.0=h1a8bee6_100
  - munkres=1.1.4=pyh9f0ad1d_0
  - ncurses=6.5=h2d0b736_3
  - netcdf-fortran=4.6.1=mpi_mpich_h2e543cf_8
  - netcdf4=1.7.2=nompi_py39h9d02bfe_101
  - numpy=2.0.2=py39h9cb892a_1
  - openjpeg=2.5.3=h5fbd93e_0
  - openssl=3.4.1=h7b32b05_0
  - packaging=24.2=pyhd8ed1ab_2
  - pango=1.56.3=h9ac818e_1
  - parallelio=2.6.3=mpi_mpich_h43d51f9_100
  - partd=1.4.2=pyhd8ed1ab_0
  - pcre2=10.44=hba22ea6_2
  - pillow=11.1.0=py39h15c0740_0
  - pip=25.0.1=pyh8b19718_0
  - pixman=0.44.2=h29eaf8c_0
  - proj=9.5.1=h0054346_0
  - pthread-stubs=0.4=hb9d3cd8_1002
  - pyparsing=3.2.3=pyhd8ed1ab_1
  - pyproj=3.6.1=py39h306d449_10
  - pyshp=2.3.1=pyhd8ed1ab_1
  - python=3.9.21=h9c0c6dc_1_cpython
  - python-dateutil=2.9.0.post0=pyhff2d567_1
  - python-stratify=0.3.0=py39hf3d9206_3
  - python-xxhash=3.5.0=py39h8cd3c5a_2
  - python_abi=3.9=5_cp39
  - pyyaml=6.0.2=py39h9399b63_2
  - qhull=2020.2=h434a139_5
  - rdma-core=56.0=h5888daf_0
  - readline=8.2=h8c095d6_2
  - scipy=1.13.1=py39haf93ffa_0
  - setuptools=75.8.2=pyhff2d567_0
  - shapely=2.0.7=py39h322cc2b_1
  - six=1.17.0=pyhd8ed1ab_0
  - snappy=1.2.1=h8bd8927_1
  - sqlite=3.49.1=h9eae976_2
  - sysroot_linux-64=2.17=h0157908_18
  - tk=8.6.13=noxft_h4845f30_101
  - toolz=1.0.0=pyhd8ed1ab_1
  - tzdata=2025b=h78e105d_0
  - ucx=1.18.0=hfd9a62f_2
  - udunits2=2.2.28=h40f5838_3
  - unicodedata2=16.0.0=py39h8cd3c5a_0
  - wayland=1.23.1=h3e06ad9_0
  - wheel=0.45.1=pyhd8ed1ab_1
  - xkeyboard-config=2.43=hb9d3cd8_0
  - xorg-libice=1.1.2=hb9d3cd8_0
  - xorg-libsm=1.2.6=he73a12e_0
  - xorg-libx11=1.8.12=h4f16b4b_0
  - xorg-libxau=1.0.12=hb9d3cd8_0
  - xorg-libxcomposite=0.4.6=hb9d3cd8_2
  - xorg-libxcursor=1.2.3=hb9d3cd8_0
  - xorg-libxdamage=1.1.6=hb9d3cd8_0
  - xorg-libxdmcp=1.1.5=hb9d3cd8_0
  - xorg-libxext=1.3.6=hb9d3cd8_0
  - xorg-libxfixes=6.0.1=hb9d3cd8_0
  - xorg-libxi=1.8.2=hb9d3cd8_0
  - xorg-libxinerama=1.1.5=h5888daf_1
  - xorg-libxrandr=1.5.4=hb9d3cd8_0
  - xorg-libxrender=0.9.12=hb9d3cd8_0
  - xorg-libxtst=1.2.5=hb9d3cd8_3
  - xxhash=0.8.3=hb9d3cd8_0
  - yaml=0.2.5=h7f98852_2
  - zipp=3.21.0=pyhd8ed1ab_1
  - zlib=1.3.1=hb9d3cd8_2
  - zstd=1.5.7=hb8e6e7a_2
  - pip:
      - alabaster==0.7.16
      - astroid==3.3.9
      - attrs==25.3.0
      - babel==2.17.0
      - build==1.2.2.post1
      - charset-normalizer==3.4.1
      - click-plugins==1.1.1
      - cligj==0.7.2
      - colorama==0.4.6
      - coverage==7.8.0
      - dill==0.3.9
      - docutils==0.21.2
      - dodgy==0.2.1
      - easytest==0.1.5
      - exceptiongroup==1.2.2
      - execnet==2.1.1
      - fiona==1.10.1
      - flake8==7.2.0
      - flake8-polyfill==1.0.2
      - gitdb==4.0.12
      - gitpython==3.1.44
      - idna==3.10
      - imagesize==1.4.1
      - iniconfig==2.1.0
      - isodate==0.6.1
      - isort==6.0.1
      - llvmlite==0.43.0
      - lxml==5.3.1
      - mccabe==0.7.0
      - mock==5.2.0
      - nc-time-axis==1.4.1
      - networkx==3.2.1
      - nose==1.3.7
      - numba==0.60.0
      - pathspec==0.12.1
      - pep8-naming==0.10.0
      - platformdirs==4.3.7
      - pluggy==1.5.0
      - prospector==1.16.1
      - prov==2.0.1
      - psutil==7.0.0
      - pycodestyle==2.13.0
      - pydocstyle==6.3.0
      - pydot==3.0.4
      - pyflakes==3.3.1
      - pygments==2.19.1
      - pylint==3.3.6
      - pylint-celery==0.3
      - pylint-django==2.6.1
      - pylint-plugin-utils==0.8.2
      - pyproject-hooks==1.2.0
      - pyroma==4.2
      - pytest==8.3.5
      - pytest-asyncio==0.26.0
      - pytest-cov==6.0.0
      - pytest-env==1.1.5
      - pytest-flake8==1.3.0
      - pytest-html==4.1.1
      - pytest-metadata==3.1.1
      - pytest-mock==3.14.0
      - pytest-xdist==3.6.1
      - pytz==2025.2
      - rdflib==6.3.2
      - requests==2.32.3
      - requirements-detector==1.3.2
      - semver==3.0.4
      - setoptconf-tmp==0.3.1
      - smmap==5.0.2
      - snowballstemmer==2.2.0
      - sphinx==7.4.7
      - sphinx-rtd-theme==3.0.2
      - sphinxcontrib-applehelp==2.0.0
      - sphinxcontrib-devhelp==2.0.0
      - sphinxcontrib-htmlhelp==2.1.0
      - sphinxcontrib-jquery==4.1
      - sphinxcontrib-jsmath==1.0.1
      - sphinxcontrib-qthelp==2.0.0
      - sphinxcontrib-serializinghtml==2.0.0
      - toml==0.10.2
      - tomli==2.2.1
      - tomlkit==0.13.2
      - trove-classifiers==2025.3.19.19
      - typing-extensions==4.13.0
      - urllib3==2.3.0
      - vmprof==0.4.18.1
      - yamale==6.0.0
      - yamllint==1.37.0
      - yapf==0.43.0
prefix: /opt/conda/envs/ESMValCore

tests/integration/test_task.py::test_run_tasks[2] tests/integration/test_task.py::test_run_tasks[3] tests/integration/test_task.py::test_run_tasks[4] tests/integration/test_task.py::test_run_tasks[16] tests/integration/test_task.py::test_run_tasks[None] tests/integration/test_task.py::test_runner_uses_priority[_run_tasks_sequential] tests/integration/test_task.py::test_runner_uses_priority[runner1]
tests/integration/test_task.py::flake-8::FLAKE8 tests/integration/test_task.py::test_run_tasks[1]
esmvalcore/preprocessor/__init__.py esmvalcore/_recipe.py esmvalcore/_task.py doc/esmvalcore/recipe.rst
esmvalcore/preprocessor/__init__.py esmvalcore/_recipe.py esmvalcore/_task.py doc/esmvalcore/recipe.rst