Drop datashader from packaging and install docs
Nobody has claimed this yet.
Assessment
- Difficulty
- 2/5
- Estimated time
- 1-3 hours
- Newbie friendliness
- 45/100
- Issue type
- Refactor
- Clarity
- Clearly specified
- Activity status
- Quiet
- Tech stack
- matplotlib, python
- Domain
- build-system, documentation
Research direction
Wait until the listed source, benchmark, notebook, and example issues are complete, then inspect the examples extra in setup.cfg and the dependency table in docs/source/getting_started/installation.rst. Remove the remaining datashader entries, ensure the stated plotting dependency is covered, and verify a clean examples install, the xrspatial import, and the specified grep command.
Written by the indexing model from the issue text.
Description
Reason or Problem
datashader is currently listed under the examples extra in setup.cfg. Once the source code, user-guide notebooks, and example notebooks no longer import it, the dependency declaration should go away so a fresh pip install xarray-spatial[examples] no longer pulls datashader.
This is the closing step of the wider effort to remove datashader as a dependency. xarray-spatial's own rasterize() (xrspatial/rasterize.py, available as arr.xrs.rasterize(...)) covers the vector-rasterization use cases, and matplotlib covers the visualization use cases.
Proposal
- Remove the
datashader >= 0.15.0line fromsetup.cfg(theexamplesextra). - Make sure
matplotlib(and any colormap source the notebooks now rely on) is present in the appropriate extra. - Remove the
datashaderrow fromdocs/source/getting_started/installation.rst.
Done when
- A clean environment installs xarray-spatial without datashader, and
python -c "import xrspatial"succeeds. grep -rn datashader xrspatial/ setup.cfg docs/source/getting_started/returns nothing.
The only datashader references left in the repo after this are the comparison benchmark and the historical-credit prose, both kept on purpose.
Blocked by
This must land last, after every issue below, otherwise [examples] users lose datashader while the notebooks still import it.
Source and benchmark:
- #3451 Remove canvas_like and datashader references from source code
- #3452 Guard the datashader import in the rasterizer benchmark
User-guide notebooks:
- #3453 surface
- #3454 proximity
- #3455 focal
- #3456 zonal
- #3457 classification
- #3458 multispectral
- #3459 fire
- #3460 pathfinding
Example notebooks and script:
- #3461 Pathfinding_Austin_Road_Network
- #3462 pharmacy-deserts
- #3463 classification-methods
- #3464 animated_hillshade.py
- Dominant language
- Python
- Stars
- 972
- Forks
- 92
- Avg merge
- 2d 12h
- Merged PRs (30d)
- 7
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
More from xarray-contrib/xarray-spatial
-
Difficulty 1/5 Under an hour Newbie friendliness 68/100
xarray-contrib/xarray-spatial#3726 ·
-
api area:surface bug severity:medium sweep-api-consistency
Difficulty 2/5 1-3 hours Newbie friendliness 82/100
xarray-contrib/xarray-spatial#3712 ·
-
Difficulty 1/5 Under an hour Newbie friendliness 88/100
xarray-contrib/xarray-spatial#3710 ·
-
bug
Difficulty 1/5 1-3 hours Newbie friendliness 88/100
xarray-contrib/xarray-spatial#3707 ·
-
area:surface documentation user-guide-example
Difficulty 2/5 1-3 hours Newbie friendliness 72/100
xarray-contrib/xarray-spatial#3464 ·
All issues in xarray-contrib/xarray-spatial
Similar issues
-
area/auth bug comp/agent P3 platform/discord type/security
Difficulty 2/5 1-3 hours Newbie friendliness 88/100
NousResearch/hermes-agent#117848 ·
-
Difficulty 2/5 1-3 hours Newbie friendliness 74/100
bancolombia/sentinel#23 ·
-
test md OpenCI
Difficulty 2/5 1-3 hours Newbie friendliness 74/100
-
integration:quickjs org:external priority:backlog topic:code-interpreter topic:middleware type:feature
Difficulty 2/5 1-3 hours Newbie friendliness 74/100
langchain-ai/deepagents#6450 ·
-
bug client
Difficulty 2/5 1-3 hours Newbie friendliness 88/100