Some hacks for fast develop
launch.json
{
"name": "Python: Current File",
"type": "python",
"request": "launch",
"program": "${file}",
"console": "integratedTerminal",
},
{
"name": "Python C++ Debugger",
"type": "pythoncpp",
"request": "launch",
"pythonLaunchName": "Python: Current File",
"cppAttachName": "(gdb) Attach",
// "preLaunchTask": "debug build cpp files"
},
{
"name": "(gdb) Attach",
"type": "cppdbg",
"request": "attach",
"program": "PATH TO PYTHON",
"processId": "",
"MIMode": "gdb",
"setupCommands": [
{
"description": "Enable pretty-printing for gdb",
"text": "-enable-pretty-printing",
"ignoreFailures": true
}
]
// "postDebugTask": "Enable ptrace_scope",
// "preLaunchTask": "Disable ptrace_scope",
},
echo 0 | sudo tee /proc/sys/kernel/yama/ptrace_scopeчтобы не было постояного запроса прав суперюзера- не забыть компилировать файл в режиме Debug
pip install virtualenv && virtualenv venv --python=python3.8
- тут пока не будет подробной инструкции, но важно не забывать добавлять в
bashrc code ~/.bashrc
export MYPYTHONPATH="" # вставить python
export LD_LIBRARY_PATH=/usr/local/cuda-11.8/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
export PATH=/usr/local/cuda-11.8/bin${PATH:+:${PATH}}
CUDNN_PATH=${MYPYTHONPATH}/python3.8/site-packages/nvidia/cudnn
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$CONDA_PREFIX/lib/:$CUDNN_PATH/lib- в основном решает проблемы связанные с bashrc
- не забыть добавить в .inputrc возможность ctrl+backspace
echo -e \"\\C-H\":\"\\C-W\" > ~/.inputrc
cat input.json | jq -c > output.json
pre-commit run --all-files