Dockerfile

FROM python:3.11-slim

ENV DEBIAN_FRONTEND=noninteractive
ENV TZ=Etc/UTC
ENV PYTHONUNBUFFERED=1
ENV PYTHONDONTWRITEBYTECODE=1

# System dependencies for C++ extension compilation
RUN apt-get update && apt-get install -y \
    git \
    patch \
    build-essential \
    g++ \
    cmake \
    libgomp1 \
    ninja-build \
    && rm -rf /var/lib/apt/lists/*

RUN pip install --upgrade pip

WORKDIR /testbed

# Full clone of the `bench` branch — every dataset base_commit lives on
# this branch, and a full (non-treeless, non-shallow) clone guarantees
# their trees are all locally available. A treeless or shallow clone
# would force git to lazy-fetch on the harness's per-task
# `git reset --hard <base_commit>`, and that fetch is flaky enough in
# CI sandboxes to silently leave the working tree on the wrong commit.
RUN git clone --branch bench https://github.com/bobbyyyan/scorch.git .

# Pre-create venv with CPU-only PyTorch so setup.sh's `pip install -r
# requirements.txt` (unpinned `torch`) sees the requirement as already
# satisfied. The default Linux torch wheel pulls in ~3.8GiB of CUDA libs
# (nvidia/, triton/, libtorch_cuda.so) that the 2-CPU Daytona sandboxes
# never use — the CPU wheel skips all of that.
RUN python3 -m venv venv && \
    venv/bin/pip install --no-cache-dir --upgrade pip && \
    venv/bin/pip install --no-cache-dir --index-url https://download.pytorch.org/whl/cpu torch

# Run setup.sh to install remaining requirements and build the C++
# extension; then drop the pip cache (~2.7GiB, only needed during install).
RUN bash setup.sh && \
    rm -rf /root/.cache

# Activate venv for subsequent commands
ENV PATH="/testbed/venv/bin:$PATH"
ENV VIRTUAL_ENV="/testbed/venv"

COPY run_tests.sh /testbed/run_tests.sh
RUN chmod +x /testbed/run_tests.sh

CMD ["/testbed/run_tests.sh"]