#0 building with "desktop-linux" instance using docker driver

#1 [internal] load build definition from Dockerfile
#1 transferring dockerfile: 252B 0.0s done
#1 DONE 0.1s

#2 [internal] load metadata for docker.io/library/python:3.12-slim@sha256:05cda9777409a9c3ffddd94a4c476b79f0769a0b4857f0c7ed9226b6800b0d6f
#2 DONE 0.1s

#3 [internal] load .dockerignore
#3 transferring context: 2B done
#3 DONE 0.0s

#4 [1/4] FROM docker.io/library/python:3.12-slim@sha256:05cda9777409a9c3ffddd94a4c476b79f0769a0b4857f0c7ed9226b6800b0d6f
#4 resolve docker.io/library/python:3.12-slim@sha256:05cda9777409a9c3ffddd94a4c476b79f0769a0b4857f0c7ed9226b6800b0d6f 0.0s done
#4 CACHED

#5 [internal] load build context
#5 transferring context: 115B done
#5 DONE 0.0s

#6 [2/4] COPY env/requirements.txt /tmp/requirements.txt
#6 DONE 0.0s

#7 [3/4] RUN pip install --no-cache-dir -r /tmp/requirements.txt
#7 3.009 Collecting numpy==2.1.3 (from -r /tmp/requirements.txt (line 1))
#7 3.364   Downloading numpy-2.1.3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.metadata (63 kB)
#7 3.648 Collecting pandas==2.2.3 (from -r /tmp/requirements.txt (line 2))
#7 3.681   Downloading pandas-2.2.3-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.whl.metadata (89 kB)
#7 3.960 Collecting scipy==1.14.1 (from -r /tmp/requirements.txt (line 3))
#7 4.291   Downloading scipy-1.14.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.metadata (113 kB)
#7 4.370 Collecting python-dateutil>=2.8.2 (from pandas==2.2.3->-r /tmp/requirements.txt (line 2))
#7 4.403   Downloading python_dateutil-2.9.0.post0-py2.py3-none-any.whl.metadata (8.4 kB)
#7 4.458 Collecting pytz>=2020.1 (from pandas==2.2.3->-r /tmp/requirements.txt (line 2))
#7 4.474   Downloading pytz-2026.5-py2.py3-none-any.whl.metadata (22 kB)
#7 4.538 Collecting tzdata>=2022.7 (from pandas==2.2.3->-r /tmp/requirements.txt (line 2))
#7 4.587   Downloading tzdata-2026.5-py2.py3-none-any.whl.metadata (1.4 kB)
#7 4.679 Collecting six>=1.5 (from python-dateutil>=2.8.2->pandas==2.2.3->-r /tmp/requirements.txt (line 2))
#7 4.730   Downloading six-1.17.0-py2.py3-none-any.whl.metadata (1.7 kB)
#7 4.760 Downloading numpy-2.1.3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (13.6 MB)
#7 5.301    ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 13.6/13.6 MB 25.8 MB/s eta 0:00:00
#7 5.321 Downloading pandas-2.2.3-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.whl (15.2 MB)
#7 5.763    ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 15.2/15.2 MB 34.2 MB/s eta 0:00:00
#7 5.778 Downloading scipy-1.14.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (35.3 MB)
#7 6.967    ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 35.3/35.3 MB 30.1 MB/s eta 0:00:00
#7 6.986 Downloading python_dateutil-2.9.0.post0-py2.py3-none-any.whl (229 kB)
#7 7.021 Downloading pytz-2026.5-py2.py3-none-any.whl (506 kB)
#7 7.053 Downloading tzdata-2026.5-py2.py3-none-any.whl (347 kB)
#7 7.086 Downloading six-1.17.0-py2.py3-none-any.whl (11 kB)
#7 7.193 Installing collected packages: pytz, tzdata, six, numpy, scipy, python-dateutil, pandas
#7 15.92 Successfully installed numpy-2.1.3 pandas-2.2.3 python-dateutil-2.9.0.post0 pytz-2026.5 scipy-1.14.1 six-1.17.0 tzdata-2026.5
#7 15.92 WARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager, possibly rendering your system unusable. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv. Use the --root-user-action option if you know what you are doing and want to suppress this warning.
#7 16.05 
#7 16.05 [notice] A new release of pip is available: 25.0.1 -> 26.2.1
#7 16.05 [notice] To update, run: pip install --upgrade pip
#7 DONE 16.6s

#8 [4/4] WORKDIR /study
#8 DONE 0.1s

#9 exporting to image
#9 exporting layers
#9 exporting layers 5.7s done
#9 exporting manifest sha256:7d57de3c01f7a3430e483124e8cf0919d505f1447da728ee18335f24eca7123b done
#9 exporting config sha256:1ab4c0efe12e45559249597170cdc9cd0c085201e5ada53fd9560ddbd211d20a done
#9 exporting attestation manifest sha256:27850e6e3e8bc7bb63c898900ee3028ca737e1a09f88c3bd8b8b380c04bbcd14 done
#9 exporting manifest list sha256:df9dc959e8418bd5ab5bb11d5d164368c32ef998adaa0a59c5f001d64dafe2db done
#9 naming to docker.io/library/sj-harness:288d29345765524c done
#9 unpacking to docker.io/library/sj-harness:288d29345765524c
#9 unpacking to docker.io/library/sj-harness:288d29345765524c 6.1s done
#9 DONE 11.9s