Switch to uv for Docker pip compile and install

.github/workflows/dea-intertidal-image.yml

@@ -85,9 +85,9 @@ jobs:
           wget --no-verbose https://www.dropbox.com/s/uemd8ib2vfw5nad/tide_models.zip?dl=1 -O tide_models.zip
           unzip -q tide_models.zip
 
-          # Run integration tests using Docker, setting up datacube access, AWS configuration and
-          # adding volumes that provide access to tide model data and allow us to export artifacts
-          # from the run
+          # Run integration tests using Docker. The command sets up datacube access, AWS configuration,
+          # and adds volumes to allow access to model outputs outside the container (used to commit outputs
+          # using git). It also provides access to tide model data for the tests.
           docker run \
             --net=host \
             --env DATACUBE_DB_URL \
@@ -96,18 +96,12 @@ jobs:
             --env AWS_ACCESS_KEY_ID \
             --env AWS_SECRET_ACCESS_KEY \
             --env AWS_SESSION_TOKEN \
-            --volume ${GITHUB_WORKSPACE}:/code \
+            --volume ${GITHUB_WORKSPACE}:/app \
             --volume ${GITHUB_WORKSPACE}/tide_models:/var/share/tide_models \
-            --volume ${GITHUB_WORKSPACE}/artifacts:/mnt/artifacts \
             dea_intertidal pytest -v --cov=intertidal --cov-report=xml tests
 
-          # Copy out validation outputs produced by the integration tests and place them
-          # in correct output locations so they can be committed back into the repository
-          cp ./artifacts/validation.jpg ./tests/validation.jpg
-          cp ./artifacts/validation.csv ./tests/validation.csv
-          cp ./artifacts/README.md ./tests/README.md
-
       # Commit validation results produced by integration tests back into repo
+      # (relies on having previously added a volume to access outputs outside of the container)
       - name: Commit validation results into repository
         uses: stefanzweifel/git-auto-commit-action@v4
         if: github.event_name == 'pull_request'
@@ -116,7 +110,7 @@ jobs:
           commit_message: Automatically update integration test validation results
           file_pattern: 'tests/validation.jpg tests/validation.csv tests/README.md'
 
-      # Post validation tesults as comment on PR
+      # Post validation tesults as a comment on the pull request
       - name: Post validation results as comment
         uses: mshick/add-pr-comment@v2
         if: github.event_name == 'pull_request'

Dockerfile

@@ -12,38 +12,28 @@ ENV DEBIAN_FRONTEND=noninteractive \
 RUN apt-get update && \
     apt-get install -y \
       build-essential \
-      fish \
       git \
-      vim \
-      htop \
-      wget \
-      unzip \
       python3-pip \
       libpq-dev \
     && apt-get autoclean && \
     apt-get autoremove && \
     rm -rf /var/lib/{apt,dpkg,cache,log}
 
-# Install pip-tools
-RUN pip install pip-tools
+# Set up working directory
+WORKDIR /app
 
-# Pip installation
-RUN mkdir -p /conf
-# COPY requirements.in /conf/
-# RUN pip-compile --extra-index-url=https://packages.dea.ga.gov.au/ --output-file=/conf/requirements.txt /conf/requirements.in
-COPY requirements.txt /conf/
-RUN pip install -r /conf/requirements.txt \
-    && pip install --no-cache-dir awscli==1.33.37
+# Copy requirements file first
+COPY requirements.in /app/requirements.in
 
-# Copy source code and install it
-RUN mkdir -p /code
-WORKDIR /code
-ADD . /code
+# Install uv and requirements
+RUN pip install uv && \
+    uv pip compile /app/requirements.in -o /app/requirements.txt && \
+    uv pip install -r /app/requirements.txt --system
 
-RUN echo "Installing dea-intertidal through the Dockerfile."
-RUN pip install --extra-index-url="https://packages.dea.ga.gov.au" .
+# Now copy the rest of the files
+COPY . /app
 
-RUN pip freeze && pip check
-
-# Make sure it's working
-RUN dea-intertidal --help
+# Install DEA Intertidal and verify installation
+RUN uv pip install . --system && \
+    uv pip check && \
+    dea-intertidal --help

requirements.in

@@ -1,7 +1,7 @@
---extra-index-url=https://packages.dea.ga.gov.au/
 aiohttp
 botocore
 click==8.1.7
+dask==2024.3.1
 datacube[s3,performance]==1.8.19
 dea-tools==0.3.4
 eodatasets3==0.30.6

tests/README.md

@@ -10,10 +10,10 @@ Integration tests
 
 This directory contains tests that are run to verify that DEA Intertidal code runs correctly. The ``test_intertidal.py`` file runs a small-scale full workflow analysis over an intertidal flat in the Gulf of Carpentaria using the DEA Intertidal [Command Line Interface (CLI) tools](../notebooks/Intertidal_CLI.ipynb), and compares these results against a LiDAR validation DEM to produce some simple accuracy metrics.
 
-The latest integration test completed at **2024-10-03 15:33**. Compared to the previous run, it had an:
-- RMSE accuracy of **0.15 m ( :heavy_minus_sign: no change)**
-- MAE accuracy of **0.12 m ( :heavy_minus_sign: no change)**
-- Bias of **0.12 m ( :heavy_minus_sign: no change)**
+The latest integration test completed at **2025-02-14 11:12**. Compared to the previous run, it had an:
+- RMSE accuracy of **0.14 m ( :heavy_check_mark: improved by 0.001)**
+- MAE accuracy of **0.12 m ( :heavy_check_mark: improved by 0.002)**
+- Bias of **0.12 m ( :heavy_check_mark: improved by 0.002)**
 - Pearson correlation of **0.975 ( :heavy_minus_sign: no change)**
 
 

tests/test_intertidal.py

@@ -65,9 +65,9 @@ def test_dem_accuracy(
     val_path="tests/data/lidar_10m_tests.tif",
     mod_path="data/processed/ga_s2ls_intertidal_cyear_3/0-0-1/tes/ting/2021--P1Y/ga_s2ls_intertidal_cyear_3_testing_2021--P1Y_final_elevation.tif",
     input_csv="tests/validation.csv",
-    output_csv="artifacts/validation.csv",
-    output_plot="artifacts/validation.jpg",
-    output_md="artifacts/README.md",
+    output_csv="tests/validation.csv",
+    output_plot="tests/validation.jpg",
+    output_md="tests/README.md",
 ):
     """
     Compares elevation outputs of the previous CLI step against
@@ -195,7 +195,7 @@ def test_dem_accuracy(
     ax2.set_ylabel("Metres (m)")
     ax2.set_xlabel(None)
 
-    # Write into mounted artifacts directory
+    # Write output CSV
     accuracy_df.to_csv(output_csv)
     plt.savefig(output_plot, dpi=100, bbox_inches="tight")
 

tests/validation.csv

@@ -68,3 +68,4 @@ time,Correlation,RMSE,MAE,R-squared,Bias,Regression slope
 2024-09-24 00:07:47.380872+00:00,0.975,0.146,0.125,0.95,0.119,1.112
 2024-09-24 05:42:35.688710+00:00,0.975,0.146,0.125,0.95,0.119,1.112
 2024-10-03 05:33:20.186227+00:00,0.975,0.146,0.125,0.95,0.119,1.112
+2025-02-14 00:12:00.333318+00:00,0.975,0.145,0.123,0.95,0.117,1.118