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# Doing a local shallow clone - keeps the container secure
# and much slimmer than using COPY directly or making a
# remote clone
ARG BASE_CONTAINER="numpy/numpy-dev:latest"
FROM gitpod/workspace-base:latest as clone
COPY --chown=gitpod . /tmp/numpy_repo
# the clone should be deep enough for versioneer to work
RUN git clone --shallow-since=2021-05-22 file:////tmp/numpy_repo /tmp/numpy
# -----------------------------------------------------------------------------
# Using the numpy-dev Docker image as a base
# This way, we ensure we have all the needed compilers and dependencies
# while reducing the build time
FROM ${BASE_CONTAINER} as build
# -----------------------------------------------------------------------------
USER root
# -----------------------------------------------------------------------------
# ---- ENV variables ----
# ---- Directories needed ----
ENV WORKSPACE=/workspace/numpy/ \
CONDA_ENV=numpy-dev
# Allows this Dockerfile to activate conda environments
SHELL ["/bin/bash", "--login", "-o", "pipefail", "-c"]
# Copy over the shallow clone
COPY --from=clone --chown=gitpod /tmp/numpy ${WORKSPACE}
# Everything happens in the /workspace/numpy directory
WORKDIR ${WORKSPACE}
# Build numpy to populate the cache used by ccache
RUN git config --global --add safe.directory /workspace/numpy
RUN git submodule update --init --depth=1 -- numpy/core/src/umath/svml
RUN conda activate ${CONDA_ENV} && \
python setup.py build_ext --inplace && \
ccache -s
# Gitpod will load the repository into /workspace/numpy. We remove the
# directory from the image to prevent conflicts
RUN rm -rf ${WORKSPACE}
# -----------------------------------------------------------------------------
# Always return to non privileged user
USER gitpod
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