Canopy data pull moved to the tree-canopy repo

README.md

@@ -127,7 +127,7 @@ Settings are read one name at a time: first from the environment, then from the
 
 - `GITHUB_REPORTS_TOKEN` for `--upload` (GitHub token with write access to the reports repo)
 - `GITHUB_REPORTS_REPO` (default `modelearth/reports`) and `GITHUB_REPORTS_SITE` (default `https://model.earth/reports/`), to push somewhere else, for example your own fork while testing
-- `DATACOMMONS_API_KEY` for parameter files that use `dcid` and for `process/canopy/canopy-process.py` (request one at [apikeys.datacommons.org](https://apikeys.datacommons.org/))
+- `DATACOMMONS_API_KEY` for parameter files that use `dcid`, and for the canopy data pull in [tree-canopy](https://github.com/ModelEarth/tree-canopy/blob/main/pipeline/canopy-process.py) (request one at [apikeys.datacommons.org](https://apikeys.datacommons.org/))
 - `ENABLE_GPU=true` to use cuML models when RAPIDS is installed (falls back to scikit-learn otherwise)
 
 When a key is missing, the CLI and the Flask `/run` endpoint explain where to get it.

projects.md

@@ -14,7 +14,7 @@ Write Loren when you've submitted a pull request to show your name.
 4. DONE: Send report files from the local python run to GitHub (`api/run_models.py --upload`, `push_report`; the Run Models page pushes with a browser-saved token). Set `GITHUB_REPORTS_REPO` to push to your own fork of [reports](https://github.com/ModelEarth/reports) when testing. - Vivek
 5. PARTIALLY DONE: Add output files to the "[report](https://github.com/ModelEarth/reports/)" folder and add smart formatting in the index.html and javascript report display. We send its content to GitHub as a final step in run_models.py.
 6. DONE: Run the Forest Canopy and all-years parameter files through `api/run_models.py` unchanged: join column aliases (`id`, `join.key`, `targets.column`), 5-digit FIPS matching, index-column drop, readable NAICS names in feature importance. - Vivek
-7. IN PROGRESS: Automated pull of recent forest canopy data from Google Data Commons (`process/canopy/canopy-process.py`), replacing the manually added target file and the missing timeseries file in [tree-canopy](https://github.com/ModelEarth/tree-canopy). Needs a `DATACOMMONS_API_KEY`. - Vivek
+7. IN PROGRESS: Automated pull of recent forest canopy data from Google Data Commons, now in the tree-canopy repo as [pipeline/canopy-process.py](https://github.com/ModelEarth/tree-canopy/blob/main/pipeline/canopy-process.py) ([tree-canopy PR #1](https://github.com/ModelEarth/tree-canopy/pull/1)). Writes the timeseries and target CSVs the Forest Canopy parameters use. Needs a `DATACOMMONS_API_KEY`. - Vivek
 8. TO DO: Decide what the `timeseries` section of a parameters file should drive (extra features per year, a trend target, or a chart in the report). `run_models.py` currently reports whether the file is reachable and does nothing else with it.
 9. TO DO: Pull 2-column targets (location id, Target) for UN topics directly from Google Data Commons using `dcid` values in parameters.yaml; `parameters-gdc.yaml` and `parameters_un_gcd.yaml` are the starting points. - Vivek (Nov 5)
 10. TO DO: More parameters files that join features and targets on county Fips, including the [all-years](https://github.com/ModelEarth/community-timelines/tree/main/training/all-years) features for states beyond Minnesota (one wide row per county, `Emp-<naics>-<year>` columns).