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Issue #604/#644 move ProcessBasedJobCreator example to more extensive…
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soxofaan committed Oct 16, 2024
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102 changes: 102 additions & 0 deletions docs/cookbook/job_manager.rst
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Expand Up @@ -2,6 +2,9 @@
Multi Backend Job Manager
====================================

API
===

.. warning::
This is a new experimental API, subject to change.

Expand All @@ -15,6 +18,105 @@ Multi Backend Job Manager

.. autoclass:: openeo.extra.job_management.ParquetJobDatabase


.. autoclass:: openeo.extra.job_management.ProcessBasedJobCreator
:members:
:special-members: __call__


.. _job-management-with-process-based-job-creator:

Job creation based on parameterized processes
===============================================

The openEO API supports parameterized processes out of the box,
which allows to work with flexible, reusable openEO building blocks
in the form of :ref:`user-defined processes <user-defined-processes>`
or `remote openEO process definitions <https://github.com/Open-EO/openeo-api/tree/draft/extensions/remote-process-definition>`_.
This can also be leveraged for job creation in the context of the
:py:class:`~openeo.extra.job_management.MultiBackendJobManager`:
define a "template" job as a parameterized process
and let the job manager fill in the parameters
from a given data frame.

The :py:class:`~openeo.extra.job_management.ProcessBasedJobCreator` helper class
allows to do exactly that.
Given a reference to a parameterized process,
such as a user-defined process or remote process definition,
it can be used directly as ``start_job`` callable to
:py:meth:`~openeo.extra.job_management.MultiBackendJobManager.run_jobs`
which will fill in the process parameters from the dataframe.

Basic :py:class:`~openeo.extra.job_management.ProcessBasedJobCreator` example
-----------------------------------------------------------------------------

Basic usage example with a remote process definition:

.. code-block:: python
:linenos:
:caption: Basic :py:class:`~openeo.extra.job_management.ProcessBasedJobCreator` example snippet
:emphasize-lines: 10-15, 28
from openeo.extra.job_management import (
MultiBackendJobManager,
create_job_db,
ProcessBasedJobCreator,
)
# Job creator, based on a parameterized openEO process
# (specified by the remote process definition at given URL)
# which has parameters "start_date" and "bands" for example.
job_starter = ProcessBasedJobCreator(
namespace="https://example.com/my_process.json",
parameter_defaults={
"bands": ["B02", "B03"],
},
)
# Initialize job database from a dataframe,
# with desired parameter values to fill in.
df = pd.DataFrame({
"start_date": ["2021-01-01", "2021-02-01", "2021-03-01"],
})
job_db = create_job_db("jobs.csv").initialize_from_df(df)
# Create and run job manager,
# which will start a job for each of the `start_date` values in the dataframe
# and use the default band list ["B02", "B03"] for the "bands" parameter.
job_manager = MultiBackendJobManager(...)
job_manager.run_jobs(job_db=job_db, start_job=job_starter)
In this example, a :py:class:`ProcessBasedJobCreator` is instantiated
based on a remote process definition,
which has parameters ``start_date`` and ``bands``.
When passed to :py:meth:`~openeo.extra.job_management.MultiBackendJobManager.run_jobs`,
a job for each row in the dataframe will be created,
with parameter values based on matching columns in the dataframe:

- the ``start_date`` parameter will be filled in
with the values from the "start_date" column of the dataframe,
- the ``bands`` parameter has no corresponding column in the dataframe,
and will get its value from the default specified in the ``parameter_defaults`` argument.


:py:class:`~openeo.extra.job_management.ProcessBasedJobCreator` with geometry handling
---------------------------------------------------------------------------------------------

Apart from the intuitive name-based parameter-column linking,
:py:class:`~openeo.extra.job_management.ProcessBasedJobCreator`
also automatically links:

- a process parameters that accepts inline GeoJSON geometries/features
(which practically means it has a schema like ``{"type": "object", "subtype": "geojson"}``,
as produced by :py:meth:`Parameter.geojson <openeo.api.process.Parameter.geojson>`).
- with the geometry column in a `GeoPandas <https://geopandas.org/>`_ dataframe.

even if the name of the parameter does not exactly match
the name of the GeoPandas geometry column (``geometry`` by default).
This automatic liking is only done if there is only one
GeoJSON parameter and one geometry column in the dataframe.


.. admonition:: to do

Add example with geometry handling.
15 changes: 14 additions & 1 deletion docs/rst-cheatsheet.rst
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Expand Up @@ -50,6 +50,15 @@ More explicit code block with language hint (and no need for double colon)
>>> 3 + 5
8
Code block with additional features (line numbers, caption, highlighted lines,
for more see https://www.sphinx-doc.org/en/master/usage/restructuredtext/directives.html#directive-code-block)

.. code-block:: python
:linenos:
:caption: how to say hello
:emphasize-lines: 1
print("hello world")
References:
Expand All @@ -60,4 +69,8 @@ References:

- refer to the reference with::

:ref:`target`
:ref:`target` or :ref:`custom text <target>`

- inline URL references::

`Python <https://www.python.org/>`_
53 changes: 13 additions & 40 deletions openeo/extra/job_management.py
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Expand Up @@ -948,47 +948,13 @@ class ProcessBasedJobCreator:
for each row of the dataframe managed by the :py:class:`MultiBackendJobManager`
by filling in the process parameters with corresponding row values.
Usage example with a remote process definition:
.. seealso::
See :ref:`job-management-with-process-based-job-creator`
for more information and examples.
.. code-block:: python
from openeo.extra.job_management import (
MultiBackendJobManager,
create_job_db,
ProcessBasedJobCreator,
)
# Job creator, based on a parameterized openEO process
# (specified by the remote process definition at given URL)
# which has, say, parameters "start_date" and "bands" for example.
job_starter = ProcessBasedJobCreator(
namespace="https://example.com/my_process.json",
parameter_defaults={
# Default value for the "bands" parameter
# (to be used when not available in the dataframe)
"bands": ["B02", "B03"],
},
)
# Initialize job database from a dataframe,
# with desired parameter values to fill in.
df = pd.DataFrame({
"start_date": ["2021-01-01", "2021-02-01", "2021-03-01"],
...
})
job_db = create_job_db("jobs.csv").initialize_from_df(df)
# Create and run job manager
job_manager = MultiBackendJobManager(...)
job_manager.run_jobs(job_db=job_db, start_job=job_starter)
The factory will take care of filling in the process parameters
based on matching column names in the dataframe from the job database
(like "start_date" in the example above).
This intuitive name-based matching should cover most use cases,
but for some more advanced use cases, there are additional options
to provide overrides and fallbacks:
Process parameters are linked to dataframe columns by name.
While this intuitive name-based matching should cover most use cases,
there are additional options for overrides or fallbacks:
- When provided, ``parameter_column_map`` will be consulted
for resolving a process parameter name (key in the dictionary)
Expand All @@ -1010,6 +976,7 @@ class ProcessBasedJobCreator:
- Finally if no (default) value can be determined and the parameter
is not flagged as optional, an error will be raised.
:param process_id: (optional) openEO process identifier.
Can be omitted when working with a remote process definition
that is fully defined with a URL in the ``namespace`` parameter.
Expand All @@ -1024,6 +991,12 @@ class ProcessBasedJobCreator:
to dataframe column names as value.
.. versionadded:: 0.33.0
.. warning::
This is an experimental API subject to change,
and we greatly welcome
`feedback and suggestions for improvement <https://github.com/Open-EO/openeo-python-client/issues>`_.
"""
def __init__(
self,
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