spark/dev/README.md

C++ Intellisense for Spark on Windows (VS Code)

Steps

1. Install the C++ extension
2. Install the CMake extension
3. Copy c_cpp_properties.json from this folder to $workspaceFolder/.vscode/
4. In the VS Code Command Palette, run CMake: Select Configure Preset, then select 'spark' from the dropdown

Notes

• Intellisense won't work for generated files/types until you build libspark

C++ Intellisense for Sparkd on Linux (VS Code)

1. Install the CMake extension
2. Install the Clangd extension
3. (Optional) Install the C++ extension (needed for debugging, but intellisense should work without it).
4. If the C++ extension is installed, disable its intellisense in your workspace settings (Clangd intellisense is better)

   "C_Cpp.intelliSenseEngine": "disabled"
   

5. In the VS Code Command Palette, run CMake: Select Configure Preset, then select the preset you wish to build from the dropdown
   • The Clang presets may work best with the Clangd extension
   • Intellisense won't work for generated files/types until you build libspark

Build Spark on Windows

Dependencies

• CMake (version >= 3.23)
• Python (version >= 3.9)
• Visual Studio (2022)
• Dotnet (sdk version >= 7.0.0)

References

• CMakePresets
• Visual Studio 17 2022 (CMake generator)
• Python Virtual Environment

Notes

• Run commands from the repo root dir unless otherwise noted

1. Set up the Python virtual environment
   

   # Create the virtual environment
   python3 -m venv .venv
   
   # Activate the virtual environment
   .venv\bin\activate.bat
   
   # Update pip
   python -m pip install --upgrade pip
   
   # Install packages
   pip install -r requirements.txt
   

2. Build
   • Run commands in python virtual environment

   # Configure
   cmake --preset spark
   
   # Build Debug
   cmake --build --preset spark-debug
   dotnet build spark_client.sln --configuration Debug
   
   # Build Release
   cmake --build --preset spark-release
   dotnet build spark_client.sln --configuration Release
   

Build Sparkd on Linux

Dependencies

• CMake (version >= 3.23)
• Ninja Build
• Python (version >= 3.9)

References

• CMakePresets
• Ninja (CMake generator)
• Python Virtual Environment
• Devcontainer

Prerequisites

• Open repository in a VS Code Devcontainer, or create your own docker container in which to build

Notes

• Run commands from the repo root dir unless otherwise noted
  

1. Set up the Python virtual environment

   # Create the virtual environment
   python3 -m venv .venv
   
   # Activate the virtual environment
   . .venv/bin/activate
   
   # Update pip
   python -m pip install --upgrade pip
   
   # Install packages
   pip install -r requirements.txt
   

2. Build
   • Run commands in python virtual environment

   # Configure clang debug
   cmake --preset sparkd-clang-debug
   
   # Build clang debug
   cmake --build --preset spark-clang-debug
   
   # Configure gcc release
   cmake --build --preset sparkd-gcc-release
   
   # Build gcc release
   cmake --build --preset sparkd-gcc-release
   

Build Spark Api Server on Windows

Dependencies

• CMake (version >= 3.23)
• Python (version >= 3.9)
• Visual Studio (version)
• Dotnet (sdk version >= 7.0.0)

References

• CMakePresets
• Visual Studio 17 2022 (CMake generator)
• Python Virtual Environment

Notes

• Run commands from the repo root dir unless otherwise noted

1. Set up the Python Virtual Environment

   # Create the virtual environment
   python3 -m venv .venv
   
   # Activate the virtual environment
   .venv\bin\activate.bat
   
   # Update pip
   python -m pip install --upgrade pip
   
   # Install packages
   pip install -r requirements.txt
   

2. Build
   • Run in python virtual environment

   # Configure
   cmake --preset spark-api-server-windows
   
   # Build debug
   cmake --build --preset spark-api-server-windows-debug
   dotnet build Spark.Api.Server.sln --configuration Debug
   
   # Build release
   cmake --build --preset spark-api-server-windows-release
   dotnet build Spark.Api.Server.sln --configuration Release
   

Build Spark Api Server on Linux

Dependencies

• CMake (version >= 3.23)
• Ninja Build
• Python (version >= 3.9)
• Dotnet (sdk version >= 7.0.0)

References

• CMakePresets
• Ninja Multi-Config (CMake generator)
• Python Virtual Environment

Prerequisites

• Open repository in a VS Code Devcontainer, or create your own docker container in which to build

Notes

• Run commands from the repo root dir unless otherwise noted

1. Set up the Python Virtual Environment

   # Create the virtual environment
   python3 -m venv .venv
   
   # Activate the virtual environment
   . .venv/bin/activate
   
   # Update pip
   python -m pip install --upgrade pip
   
   # Install packages
   pip install -r requirements.txt
   

2. Build
   • Run in python virtual environment

   # Configure
   cmake --preset spark-api-server-linux
   
   # Build debug
   cmake --build --preset spark-api-server-linux-debug
   dotnet build Spark.Api.Server.sln --configuration Debug
   
   # Build release
   cmake --build --preset spark-api-server-linux-release
   dotnet build Spark.Api.Server.sln --configuration Release