GRASS-Wiki - User contributions [en]

GRASS Community Meeting San Michele 2026

2026-04-24T07:57:13Z

Sbl: /* Participation */

[[File:Sanmichele.png|frameless|center|1000px|San Michele all'Adige]]

{{toc|right}}

The ''GRASS Community Meeting'' for contributors and developers will be happening from '''July 11 - 19, 2026''' in [https://www.openstreetmap.org/relation/46990#map=12/46.1349/11.1947 San Michele all'Adige, Trentino, Italy].

== Sponsors ==

Sponsors make the event possible. Learn more about [https://grass.osgeo.org/contribute/sponsoring/ Sponsoring].

* [https://www.osgeo.org/ OSGeo]: 2500 USD (see [https://wiki.osgeo.org/w/index.php?title=GRASS_Community_Meeting_2026:_Budget budget]]).

[[File:Osgeo logo.png|none|left|alt=Light and dark green logo of OSGeo saying Your Open Source Compass|Open Source Geospatial Foundation]]

== Purpose ==
The ''GRASS Community Meeting'' is a great occasion for folks to support the development by actively contributing to the project in different ways. These include source code updates, documentation (manuals, wiki, tutorials), translations, website improvements or likewise. The community meeting is also a get-together where supporters, contributors, power users and developers make decisions and tackle larger problems related to the project, discuss and collaboratively resolve bugs, plan the direction for the project and work on new features. We welcome people committed to improving the GRASS project and the interfaces to QGIS, GDAL, PostGIS, R, OGC Services and others.

The focus is on GRASS maintenance, and interaction with other projects. Many maintenance tasks, infrastructure changes, and planning of large changes especially benefits from maintainers being in one place and time zone. While the specific topics highly depend on the participants, we will prioritize topics which require highly synchronous collaboration, such as the CMake build system transition and API transitions. The [https://grass.osgeo.org/news/2025_05_27_grass_dev_summit_report/ 2025 event report] gives an overview of what was achieved last year.

We do require participants to work on GRASS or connections to other projects. However, we leave them the freedom to work on what they think is the best contribution to the project given their skills and time available.

== Agenda ==

Agenda is forthcoming.

=== Saturday, July 11 ===

Day of arrival. Contact organizers if you are interested in individualized program or helping with organization.

=== Sunday, July 12 ===
=== Monday, July 13 ===
=== Tuesday, July 14 ===
=== Wednesday, July 15 ===
=== Thursday, July 16 ===
=== Friday, July 17 ===
=== Saturday, July 18 ===
=== Sunday, July 19 ===

Day of departure.

== Participation ==

Please add your name here:

{|class="wikitable sortable" border="2" cellspacing="0" cellpadding="4" rules="all" style="margin:1em 1em 1em 0; border:solid 1px #AAAAAA; border-collapse:collapse; background-color:#edf9c7; font-size:95%; empty-cells:show;"
!width=50px|'''Number'''
!width=130px|'''Participant '''
!width=100px|'''Country'''
!width=100px|'''Arrival'''
!width=100px|'''Departure'''
!'''Topics'''
!'''Notes'''
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|1
| [[User:Lucadelu|Luca Delucchi]]
| Italy
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|2
| [[User:wenzeslaus|Vaclav Petras]]
| United States
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|3
| [[User:Annakrat|Anna Petrasova]]
| United States
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|4
| [[User:Neteler|Markus Neteler]]
| Germany
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|5
| [[User:Sbl|Stefan Blumentrath]]
| Norway
| 11.07. (presumably)
| 18.07. (presumably)
| Handling Copernicus data with GRASS / actinia
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|6
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== Venue ==
The meeting will be hosted at [https://fmach.it/ Fondazione Edmund Mach] (FEM) in San Michele all'Adige, Trentino, Italy — about 15 km north of Trento. FEM is a research and education center with on-site facilities that allow participants to work, sleep, and eat in the same location.

[https://maps.app.goo.gl/5YEuEts6qXvky7HD9 Map]

=== Getting there ===

San Michele all'Adige is reachable by train on the Trento–Bolzano line (San Michele all'Adige–Mezzocorona station), with frequent connections from Trento (~15 minutes) and Verona (~1 hour). The nearest airports are Verona (VRN), Venice Marco Polo (VCE) and Treviso (TSF), Milan Bergamo (BGY), Malpensa (MXP), and Linate (LIN), Bologna (BLQ), and Innsbruck (INN) in Austria. Trento is also the host city of FOSS4G Italy 2026 (July 9–11), making it convenient to combine both events.

== Accommodation and Costs ==

''Participation is free of charge''. However, participants should plan for the following costs:

* Travel
* Lodging

Participants can stay on-site at the FEM convitto (dormitory), keeping the community together for the full duration of the meeting:

* €35 per person per night
* Double and triple rooms (triples include a small kitchen)
* A mandatory on-site supervisor is required at €200 per night (flat fee, shared across the group)
* Family members are welcome to stay in the dormitory as well
* [https://cif.fmach.it/content/download/2701/78358/file/brochure_convitto.pdf Brochure]

For anyone preferring alternative lodging, hotels and B&Bs are available in San Michele and nearby Trento.

Lunches on weekdays can be taken at the FEM canteen (mensa), located on the same campus. Details and pricing are being finalized.

== Individual Preparation ==

* Bring your own computer
* Bring {{wikipedia|AC power plugs and sockets|power adapter}} if needed (Italy: 230V, 50Hz, {{wikipedia|Europlug|Type C}}, {{wikipedia|Schuko|Type F}}, and {{wikipedia|AC power plugs and sockets: L|Type L}} sockets are common)
* Install git and the compiler tools, and come with a working GRASS development environment if possible. See [https://github.com/OSGeo/grass/blob/main/CONTRIBUTING.md here] for details.

== FAQ ==

* ''How was it last time?''
** Splendid! See [[GRASS Developer Summit Raleigh 2025]]!
* ''Is the GRASS Community Meeting for developers only?''
** No, the meeting is open to all users, supporters, contributors, power users and developers ''who want to make a meaningful contribution to the project''.
* ''Where can I get help and more information about the community meeting?''
** Contact local organizer [[User:Lucadelu|Luca Delucchi]] (<tt><lucadeluge at gmail com></tt>) or [[User:wenzeslaus|Vaclav Petras]] (<tt><wenzeslaus at gmail com></tt>) for budget questions.

[[Category: Workshops]]
[[Category: Code Sprint]]
[[Category: 2026]]

User:Sbl

2026-04-24T07:54:39Z

Sbl: Created page with "'''OSGeo Wiki''' https://wiki.osgeo.org/wiki/Stefan_Blumentrath '''GitHub''' https://github.com/ninsbl"

'''OSGeo Wiki'''
https://wiki.osgeo.org/wiki/Stefan_Blumentrath
'''GitHub'''
https://github.com/ninsbl

GRASS GSoC Ideas 2026

2026-02-05T09:05:30Z

Sbl: /* Ideas */

== About ==
Important: While we are still an OSGeo project, we changed our fiscal sponsor to [https://numfocus.org/ NumFOCUS].

''As a result, GRASS participates in GSoC under the [https://numfocus.org/ NumFOCUS] umbrella organization.''

Read more about our governance [https://grass.osgeo.org/about/governance/ on GRASS website].

* [https://numfocus.org/programs/google-summer-code The NumFOCUS GSoC main page]
* [https://github.com/numfocus/gsoc/blob/master/CONTRIBUTING-contributors.md NumFOCUS guidelines for contributors].
* [https://summerofcode.withgoogle.com/ Official GSoC page at Google]

== AI Tool Usage Policy ==
We acknowledge that applicants may use AI tools (like ChatGPT, Copilot, etc.) to assist with proposal writing and coding. However:

* Your proposal should reflect your own understanding and voice. AI-generated "slop" (overly generic or regurgitated content) is easy to spot and will hurt your application.
* We evaluate applications primarily on GitHub contributions and communication with the GRASS community, not just proposal polish.
* Show us you understand the project through high-quality pull requests on GitHub.
* Disclose AI usage: If you use AI tools in your proposal or code contributions, please disclose the extent to which you used them (e.g., for brainstorming, proofreading, code suggestions, etc.).

== Ideas ==
If you are a student you can suggest a new idea or pick up an existing one. In any case write about it to [https://discourse.osgeo.org/c/grass/developer/61 OSGeo Discourse forum for GRASS developers], [https://github.com/OSGeo/grass/discussions GitHub Discussions], or [https://gitter.im/grassgis/community Gitter].

You are invited as well to have a close look at ideas from previous years ([https://trac.osgeo.org/grass/wiki/GSoC/2014 2014], [https://trac.osgeo.org/grass/wiki/GSoC/2015 2015], [https://trac.osgeo.org/grass/wiki/GSoC/2016 2016],
[https://trac.osgeo.org/grass/wiki/GSoC/2017 2017],
[https://trac.osgeo.org/grass/wiki/GSoC/2018 2018],
[https://trac.osgeo.org/grass/wiki/GSoC/2019 2019],
[https://trac.osgeo.org/grass/wiki/GSoC/2020 2020],
[https://trac.osgeo.org/grass/wiki/GSoC/2021 2021],
[https://trac.osgeo.org/grass/wiki/GSoC/2022 2022],
[https://trac.osgeo.org/grass/wiki/GSoC/2023 2023])
which have not yet been implemented.
You can also look at accepted GRASS GSoC [https://trac.osgeo.org/grass/wiki/GSoC projects from previous years] for an idea of scope.''

=== Parallelization of existing tools ===

There are several tools that would benefit from parallelization with OpenMP, e.g. r.texture, r.fill.stats, r/v.surf.idw, r.viewshed, v.to.rast, r.grow.distance, v.surf.bspline, r.proj, ...
For overview of current state, see [[Raster_Parallelization_with_OpenMP]].

* Requirements: familiarity with C, OpenMP
* Mentor: Huidae Cho
* Co-mentor: Vaclav Petras, Anna Petrasova
* Project length: Large (350 hours)
* Rating: difficult
* Expected Outcomes: parallelized 2-5 tools, depending on complexity
* Test of skills (one or more):
** Address https://github.com/OSGeo/grass/issues/5776 (carefully read the existing conversation in the issue and linked PR)
** Pick a tool and develop prototype implementation of the parallelization.

=== Improve GRASS user experience in Jupyter Notebook ===
[[File:Jupyter_interactive_viewshed.png|500px|thumb|right|InteractiveMap in grass.jupyter library]]
Python package [https://grass.osgeo.org/grass-stable/manuals/libpython/grass.jupyter.html grass.jupyter] was developed during [https://trac.osgeo.org/grass/wiki/GSoC/2021/JupyterAndGRASS GSoC 2021] to simplify running GRASS from Jupyter Notebooks and displaying data. This project could focus on adding features such as better symbology handling and adding legend to InteractiveMap and better integration with matplotlib.

* Requirements: Python
* Mentor: Anna Petrasova
* Co-mentor: Vaclav Petras, Helena Mitasova, Corey White
* Project length: Large (350 hours)
* Rating: easy to medium
* Expected Outcomes: improved user experience when using GRASS through notebooks
* Test of skills: write a test for [https://github.com/OSGeo/grass/tree/main/python/grass/jupyter grass.jupyter library] using python unittest or pytest, more info [https://grass.osgeo.org/grass-devel/manuals/libpython/gunittest_testing.html here] or rewrite some of the functions in grass.jupyter library using the new [https://grass.osgeo.org/grass-devel/manuals/python_intro.html#running-tools Tools API].

=== Add JSON output to different tools ===
There are several tools in GRASS that would benefit from a JSON-formatted output.
Besides adding the JSON output, the work would also include adding tests and basic documentation.
* Requirements: C, Python
* Mentor: Vaclav Petras
* Co-mentor: Anna Petrasova, Corey White
* Project length: Large (350 hours)
* Rating: easy to medium
* Expected Outcomes: 10-20 tools (depending on project length and complexity of the tool) tools with well tested JSON output
* Test of skills (pick one or more):
** https://github.com/OSGeo/grass/issues/6968
** https://github.com/OSGeo/grass/issues/6969
** https://github.com/OSGeo/grass/issues/6970

=== Support writing tests with pytest ===

* The current testing framework, ''[https://grass.osgeo.org/grass-stable/manuals/libpython/gunittest.html grass.gunittest]'', was written before migration to Git/GitHub and when long free runs in 3rd party services were unthinkable. Additionally, some no longer relevant goals were prioritized, such as independence on the current code, detailed custom HTML reports, success tracking over time, and high specialization towards GRASS-specifics.
* ''grass.gunittest'' is based on Python ''unittest'' package and many projects since then migrated to //pytest//, e.g., GDAL and Numpy. While ''unittest'' is inspired by Java's JUnit, ''pytest'' is designed to support writing small, readable tests, and uses plain `assert` statements instead of many different assert methods.
* Using ''pytest'' should lead to tests which feel more like Python scripts and to minimum of testing-specific code.
* An example issue of ''grass.gunittest'' is that it doesn't work well with tests of the main GRASS executable (prominence of `grass ... --exec` is yet another new thing which changed since ''grass.gunittest'' was designed).
* Two main things needed:
** Create general comparison functions from the ''grass.gunittest'' assert methods so that they can be used with pytest.
** Current grass.script.setup.init function and grass.script.core.create_location function don't work well in the context of a pytest test function. More
* Additional things needed:
** Fixture for pytest to set up and tear down a GRASS session in a temporary mapset.

* Requirements: Python
* Project length: Large (350 hours)
* Mentor: Vaclav Petras
* Co-mentor: Stefan Blumentrath
* Proposed by: Vaclav Petras
* Rating: easy to medium
* Expected Outcomes: Convenient way of writing tests with pytest
* Test of skills: Fix failing tests and/or write new tests (more is better). Alternatively, addressing a smaller problem in the testing framework is a good task, too.

=== Fix known code defects ===

* Fix code defects (security or code quality) such as those reported by Coverity Scan.
* Mentors: Vaclav Petras
* Co-mentors: ?
* Proposed by: Vaclav Petras
* Project length: Large (350 hours)
* Rating: medium
* Requirements:
** Language: C
** Proposal: Define milestones which will be used during the evaluation.
* Expected outcomes:
** Reduction of issues by 70-100%.
** New tests for changed code if missing.
* Test and training tasks (complete more than one): Fix cppcheck issue.

=== Subcommand CLI for GRASS ===

* Make running of GRASS tools in command line as easy as possible.
** `grass run r.slope.aspect elevation=elevation.tiff slope=slope.tiff aspect=aspect.tiff`
* Project length: Large (350 hours)
* Rating: medium
* Requirements:
** Language: Python
** Proposal: Student needs to show sufficient understanding of data and project handling in GRASS. Furthermore, the proposal needs to present, at least, concrete formulation of ideas, identification of missing and existing parts, and new subcommands.
* Mentors: Vaclav Petras
* Co-mentors: Stefan Blumentrath, Corey White
* Proposed by: Vaclav Petras
* Expected outcomes:
** A subcommand which runs a GRASS tool on GeoTiff and GeoPackage in one step.
** A complete parity with the existing CLI.
** An underlying Python API which will be used to implement the CLI.
* Test and training tasks (complete one or more): Add a subcommand, sub-subcommand, or an option to the experimental interface (with tests).
** Add `--region` to set a temporary computational region for the execution, e.g. `--region="raster=raster_name"`.
** Add `--import-raster=some/file.tiff` which imports (r.import) a raster file (same for vector and similarly for export).
** Add `--link-raster=some/file.tiff` which links (r.external) a raster file (same for vector and similarly for r.external.out).

Current state:

# Reveals the existing subcommands
PYTHONPATH=$(grass --config python-path) python -m grass.app --help
# Allows running subset of commands
grass run --help


=== GUI: Add space-time datasets support in Data Catalog ===
[[File:GUI_data_tab.png|400px|thumb|right|Data catalog]]
Currently GRASS Data Catalog shows only raster and vector maps. The goal of this project is to add support for space-time datasets. It is mainly space-time raster datasets. In the next phase of the project support for other types of space-time datasets (vector and 3D raster) could be added. Besides displaying space-time datasets in the layer tree, it is also about adding the equivalent functionality currently available for raster and vector layers from the context menu.

* Requirements: familiar with Python
* Project length: Large (350 hours)
* Mentor: Martin Landa
* Co-mentor: Anna Petrasova
* Proposed by: Martin Landa
* Rating: medium
* Expected Outcomes: 175 hours basic support for space-time raster datasets; 350 extended support also for other space-time datasets types (vector, 3D raster)
* Test of skills:
** suggest/implement solution for completing https://github.com/OSGeo/grass/issues/2599

=== Searchable metadata in Space Time Datasets ===
The temporal framework in GRASS was initially developed almost 15 years ago. Spatio-temporal data has become more widely available since then and new standards emerged like e.g. ''[https://docs.ogc.org/cs/25-004/25-004.html STAC]'' with ''[https://github.com/stac-extensions/stac-extensions.github.io extensions]'', or the ''[https://cfconventions.org/ CF-conventions]''. The aim of this project is to extend the metadata model in the temporal framework to improve discoverability of map datasets registered in TGIS and to allow users to embed extended metadata with the registered maps in a Space Time Dataset in a searchable way. Ideally, the new model is able to account for the standards mentioned above.

See also: https://github.com/OSGeo/grass/issues/1938

* Requirements: Python, SQL, JSON
* Project length: Large (350 hours)
* Mentor: Stefan Blumentrath
* Co-mentor: ???
* Proposed by: Stefan Blumentrath
* Rating: medium
* Expected Outcomes:
** an updated TGIS database model (version 4) that:
*** is oriented on relevant metadata standards (STAC, CF-Convention, ...)
*** allows to use metadata in temporal_where to select relevant elements of Space time datasets
** updated tool to create space time datasets (t.create) in the TGIS database with extended metadata
** updated tool to register map datasets (t.register) in the TGIS database with extended metadata
** Conversion tool for database Upgrades (v3 to v4)
** a new tool to update / modify metadata in the TGIS database
** Storage of timeseries metadata for both C-based and temporal Tools

* Test of skills (e.g.):
** address one or more sub-tasks from https://github.com/OSGeo/grass/issues/3427 (add append-mode to selected new tool(s))
** suggest/implement solution for https://github.com/OSGeo/grass/issues/3394 (more complex task)
** suggest/implement solution for https://github.com/OSGeo/grass/issues/7041

=== Add {your research idea} to GRASS ===

* In general, you can propose any topic, but you can specifically propose integrating your research or research idea into GRASS.
* Requirements:
** Language:
*** Depends on the project, often Python, sometimes C.
*** Adding your latest ecological analysis
** Proposal:
*** Discuss relevance to GRASS.
*** Describe technical steps needed for integration.
*** Describe whether it is an addition of a tool (module) or a change in one of the libraries. If it is a tool, specify if it should be included in the core grass repository or in grass-addons repository and why.
*** Specify what research was done and what needs to be accomplished in order to have usable product at the end of summer.
*** Specify who will provide the research expertise.
* Project length: Large (350 hours)
* Rating: from low to hard
* Mentors:
** GRASS project will provide technical mentors, but it is up to the applicant to ensure the research part is mentored well. An exception may be granted to applicants which can demonstrate that the research is finished or that they have enough expertise themselves.
** Possible technical mentors: Vaclav Petras, Anna Petrasova
** Research mentors: Bring in an expert from your field, e.g., your academic advisor or project principal investigator (if needed).
* Proposed by: Vaclav Petras
* Expected outcome: Working feature which is integrated and merged at the end of the project.
* Test and training tasks:
** Create a test in Python for an existing tool in the grass-addons repository or in the core grass repository.

=== Title of idea ===

Description here

* Requirements:
* Project length: (175 or 350 hours)
* Mentor:
* Proposed by:
* Rating:
* Expected Outcomes:
* Test of skills:
* Other:

== Tips for students ==
* Follow official [https://github.com/numfocus/gsoc/blob/master/CONTRIBUTING-contributors.md NumFOCUS guidelines].
* Include "GRASS" in the title of our idea to easily distinguish ideas and projects inside NumFOCUS.
* If you have your own ideas we encourage you to propose them. Explain them on the [https://discourse.osgeo.org/c/grass/developer/61 on our Discourse].
* Follow some good practices in your ideas and proposals:
** Stress why the project would be useful.
** Show that you know how you will proceed. That is, make sure that you can demonstrate that the proposal is feasible in the given time frame.
** Be specific in the implementation (or at least as specific as you can).
** Explain what the final product will look like and how it will work. You can add drawings or mock-ups.
** Explain how the idea relates to existing GRASS functions, features, and needs.
** Do not include steps such as "install GRASS", "compile GRASS libraries (on my machine)", "read about the API". You should do this before applying to GSoC.
* Compile GRASS from source and prepare environment for development:
** Read [https://github.com/OSGeo/grass/blob/main/CONTRIBUTING.md CONTRIBUTING file].
* Prove your worth by being active on the [https://discourse.osgeo.org/c/grass/developer/61 GRASS Discourse] or other channels ([https://github.com/OSGeo/grass/discussions GitHub Discussions], fix some [https://github.com/OSGeo/grass/issues bugs], and/or implement some (smaller) features, or write some (simpler) GRASS module, and post it to mailing list. There's no better way to demonstrate your willingness and abilities. Do this before start you apply to GSoC.
* Also note that fixing existing bugs and/or implementing enhancements will be a part of student evaluation.

{{GSoC}}