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https://github.com/andreinechaev/nvcc4jupyter.git
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Create devcontainer for quick dev setups
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FROM ubuntu
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ARG VENV_PATH=/opt/dev-venv
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ENV VENV_ACTIVATE=${VENV_PATH}/bin/activate
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RUN apt update
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RUN apt install -y python3.10-venv nvidia-cuda-toolkit gcc vim git
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# the mkdir command bypasses a profiler error, which allows us to run it with
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# host code only to at least check that the profiler parameters are correctly
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# provided; without this line, some tests will fail
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RUN mkdir -p /usr/lib/x86_64-linux-gnu/nsight-compute/sections
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# we create the virtualenv here so that the devcontainer.json setting
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# python.defaultInterpreterPath can be used to find it; if we do it in the
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# post_create.sh script, the virtualenv will not be loaded and features like
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# pylance, black, isort, etc. will not work
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RUN python3.10 -m venv ${VENV_PATH}
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RUN echo "source ${VENV_ACTIVATE}" >> ~/.bashrc
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{
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"name": "Python Environment",
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"build": {
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"dockerfile": "Dockerfile",
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"context": ".."
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},
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"postCreateCommand": "bash .devcontainer/post_create.sh",
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"customizations": {
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"vscode": {
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"extensions": [
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"editorconfig.editorconfig",
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"ms-azuretools.vscode-docker",
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"ms-python.python",
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"ms-python.vscode-pylance",
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"ms-python.pylint",
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"ms-python.isort",
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"ms-python.flake8",
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"ms-python.black-formatter",
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"ryanluker.vscode-coverage-gutters"
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],
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"settings": {
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"python.defaultInterpreterPath": "/opt/dev-venv/bin/python"
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}
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}
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}
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}
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#!/bin/bash
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# install developer dependencies
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pip install .[dev]
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# make sure the developer uses pre-commit hooks
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pre-commit install
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