#0 building with "desktop-linux" instance using docker driver #1 [internal] load build definition from Dockerfile #1 transferring dockerfile: 239B done #1 DONE 0.0s #2 [internal] load metadata for public.ecr.aws/docker/library/python:3.12-slim #2 DONE 1.8s #3 [internal] load .dockerignore #3 transferring context: 2B done #3 DONE 0.0s #4 [internal] load build context #4 transferring context: 179B done #4 DONE 0.0s #5 [1/3] FROM public.ecr.aws/docker/library/python:3.12-slim@sha256:05cda9777409a9c3ffddd94a4c476b79f0769a0b4857f0c7ed9226b6800b0d6f #5 resolve public.ecr.aws/docker/library/python:3.12-slim@sha256:05cda9777409a9c3ffddd94a4c476b79f0769a0b4857f0c7ed9226b6800b0d6f 0.0s done #5 CACHED #6 [2/3] COPY env/ /opt/sj-env/ #6 DONE 0.0s #7 [3/3] RUN pip install --no-cache-dir --root-user-action=ignore -r /opt/sj-env/requirements.txt #7 0.915 Collecting numpy==2.2.6 (from -r /opt/sj-env/requirements.txt (line 1)) #7 1.025 Downloading numpy-2.2.6-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.metadata (63 kB) #7 1.128 Collecting scipy==1.15.3 (from -r /opt/sj-env/requirements.txt (line 2)) #7 1.146 Downloading scipy-1.15.3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.metadata (61 kB) #7 1.212 Collecting pandas==2.2.3 (from -r /opt/sj-env/requirements.txt (line 3)) #7 1.228 Downloading pandas-2.2.3-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.whl.metadata (89 kB) #7 1.498 Collecting nibabel==5.3.2 (from -r /opt/sj-env/requirements.txt (line 4)) #7 1.516 Downloading nibabel-5.3.2-py3-none-any.whl.metadata (9.1 kB) #7 1.568 Collecting statsmodels==0.14.4 (from -r /opt/sj-env/requirements.txt (line 5)) #7 1.790 Downloading statsmodels-0.14.4-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.metadata (9.2 kB) #7 1.825 Collecting patsy==1.0.1 (from -r /opt/sj-env/requirements.txt (line 6)) #7 1.845 Downloading patsy-1.0.1-py2.py3-none-any.whl.metadata (3.3 kB) #7 1.873 Collecting packaging==25.0 (from -r /opt/sj-env/requirements.txt (line 7)) #7 1.890 Downloading packaging-25.0-py3-none-any.whl.metadata (3.3 kB) #7 1.922 Collecting python-dateutil>=2.8.2 (from pandas==2.2.3->-r /opt/sj-env/requirements.txt (line 3)) #7 2.025 Downloading python_dateutil-2.9.0.post0-py2.py3-none-any.whl.metadata (8.4 kB) #7 2.083 Collecting pytz>=2020.1 (from pandas==2.2.3->-r /opt/sj-env/requirements.txt (line 3)) #7 2.107 Downloading pytz-2026.5-py2.py3-none-any.whl.metadata (22 kB) #7 2.130 Collecting tzdata>=2022.7 (from pandas==2.2.3->-r /opt/sj-env/requirements.txt (line 3)) #7 2.144 Downloading tzdata-2026.5-py2.py3-none-any.whl.metadata (1.4 kB) #7 2.175 Collecting typing-extensions>=4.6 (from nibabel==5.3.2->-r /opt/sj-env/requirements.txt (line 4)) #7 2.189 Downloading typing_extensions-4.16.0-py3-none-any.whl.metadata (3.3 kB) #7 2.226 Collecting six>=1.5 (from python-dateutil>=2.8.2->pandas==2.2.3->-r /opt/sj-env/requirements.txt (line 3)) #7 2.241 Downloading six-1.17.0-py2.py3-none-any.whl.metadata (1.7 kB) #7 2.259 Downloading numpy-2.2.6-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (14.0 MB) #7 2.940 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 14.0/14.0 MB 20.9 MB/s eta 0:00:00 #7 2.956 Downloading scipy-1.15.3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (35.2 MB) #7 4.469 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 35.2/35.2 MB 25.1 MB/s eta 0:00:00 #7 4.485 Downloading pandas-2.2.3-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.whl (15.2 MB) #7 5.392 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 15.2/15.2 MB 16.8 MB/s eta 0:00:00 #7 5.408 Downloading nibabel-5.3.2-py3-none-any.whl (3.3 MB) #7 5.528 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 3.3/3.3 MB 29.2 MB/s eta 0:00:00 #7 5.784 Downloading statsmodels-0.14.4-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (10.3 MB) #7 8.088 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 10.3/10.3 MB 4.5 MB/s eta 0:00:00 #7 8.123 Downloading patsy-1.0.1-py2.py3-none-any.whl (232 kB) #7 8.138 Downloading packaging-25.0-py3-none-any.whl (66 kB) #7 8.160 Downloading python_dateutil-2.9.0.post0-py2.py3-none-any.whl (229 kB) #7 8.174 Downloading pytz-2026.5-py2.py3-none-any.whl (506 kB) #7 8.209 Downloading typing_extensions-4.16.0-py3-none-any.whl (45 kB) #7 8.313 Downloading tzdata-2026.5-py2.py3-none-any.whl (347 kB) #7 8.343 Downloading six-1.17.0-py2.py3-none-any.whl (11 kB) #7 8.470 Installing collected packages: pytz, tzdata, typing-extensions, six, packaging, numpy, scipy, python-dateutil, patsy, nibabel, pandas, statsmodels #7 15.62 Successfully installed nibabel-5.3.2 numpy-2.2.6 packaging-25.0 pandas-2.2.3 patsy-1.0.1 python-dateutil-2.9.0.post0 pytz-2026.5 scipy-1.15.3 six-1.17.0 statsmodels-0.14.4 typing-extensions-4.16.0 tzdata-2026.5 #7 DONE 16.0s #8 exporting to image #8 exporting layers #8 exporting layers 6.1s done #8 exporting manifest sha256:a37f24a570854c5cda5f35696681c7439d77775d84495ddaa007b9b9931d272f done #8 exporting config sha256:031db225f11f3a8c4daf3c0dc39227205d8233c2eaf6abfed502668a6db0842d done #8 exporting attestation manifest sha256:55a2a206e976d368a3fcaa3f52ccd402cb6e0285832f367f7504f515f3cd57fd done #8 exporting manifest list sha256:fd4df93cc6f7dfd986e9d220ec552a2bd33852b45a657789d1dd085b2d7e399b done #8 naming to docker.io/library/sj-harness:2e8340d37b707f5f done #8 unpacking to docker.io/library/sj-harness:2e8340d37b707f5f #8 unpacking to docker.io/library/sj-harness:2e8340d37b707f5f 1.6s done #8 DONE 7.8s