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Dev container tutorial
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lukstep
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README.md
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README.md
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# Raspberry Pi Pico Docker SDK
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Lightweight Raspberry Pi Pico C++ SDK container.
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A lightweight SDK environment for Raspberry Pi Pico in a Docker container.
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## Pull container from Docker Hub and run
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## Pulling the Image from Docker Hub and Running
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The latest image is available on [Docker Hub](https://hub.docker.com/repository/docker/lukstep/raspberry-pi-pico-sdk/general)
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and can be used to run a container.
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The following commands show how to run the container using the Docker Hub image:
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The latest version of the image is stored on [Docker Hub](https://hub.docker.com/repository/docker/lukstep/raspberry-pi-pico-sdk/general)
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and can be used for container runs.
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Commands below show how to run a container, using an image from Docker Hub
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```
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docker run -d -it --name pico-sdk --mount type=bind,source=${PWD},target=/home/dev lukstep/raspberry-pi-pico-sdk:latest
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docker exec -it pico-sdk /bin/sh
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```
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The directory from which the `docker run` command was called will be mounted to /home/dev in the container.
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So after attaching to the SDK container you can build your project following the steps:
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The directory from which the `docker run` command was executed will be mounted in the container at `/home/dev`.
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After attaching to the SDK container, you can build your project by executing the following steps:
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```
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cd /home/dev
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mkdir build
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cd build
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cmake .. && make -j4
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```
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## Build image and run container:
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## Building the Image and Running the Container
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To build your own SDK image, You need to clone this repository and run the following commands:
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To build your own SDK image, clone this repository and run the following commands:
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```
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cd raspberry-pi-pico-docker-sdk
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docker build . --tag pico-sdk
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docker run -d -it --name pico-sdk --mount type=bind,source=${PWD},target=/home/dev pico-sdk
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docker exec -it pico-sdk /bin/sh
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```
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## Visual Studio Code as Rassberry Pi PICO projects IDE
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## Visual Studio Code as IDE for Raspberry Pi Pico Projects
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You can use the SDK container with Visual Studio Code as Raspberry Pi Pico projects IDE.
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You can use the SDK container with Visual Studio Code to create an IDE for Raspberry Pi Pico projects.
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There are two solutions prepared: a new one using the Visual Studio Dev Containers extension and an old one with manual configuration.
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### Attaching VSCode to SDK Docker container
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### [Visual Studio Code Dev Container](https://code.visualstudio.com/docs/devcontainers/containers)
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Follow the instruction below to set up VSCode:
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#### Prerequisites
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1. Install [Visual Studio Code](https://code.visualstudio.com) and next [Remote Development](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.vscode-remote-extensionpack) extensions.
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To use the dev container, you need to have VSCode, Docker, and the VSCode extensions installed.
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Follow [this](https://code.visualstudio.com/docs/devcontainers/tutorial#_prerequisites) guide for setup.
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#### Using the Dev Container for Pico IDE
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2. Open the terminal and go to the projects you want to open in VSCode.
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- Clone [pico-dev-container](https://github.com/lukstep/pico-dev-container/tree/main) repository.
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- Open `pico-dev-container` folder in Visual Studio Code.
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- In VSCode, click the button in the bottom left corner of VSCode and select: Reopen in Container...
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- Build the project.
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- Enjoy coding you Pico project with Intellisense.
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3. Pull SDK image from Docker HUB and run SDK container via the following command. The container must be running while you attach to it via VSCode.
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```
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docker run -d -it --name pico-sdk --mount type=bind,source=${PWD},target=/home/dev lukstep/raspberry-pi-pico-sdk:latest
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docker exec -it pico-sdk /bin/sh
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```
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4. When the container is launched, go to VSCode, click the green button in the lower left corner of VSCode and select options: Attach to Running Container...
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5. Select the SDK container.
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6. Then a new VSCode window will open. At the bottom window, you can see that it is attached to the SDK container.
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7. Now, there is needed to open project files. Your project is mounted to `/home/dev` in the container. Go to EXPLORE tab in VSCode and click Open Folder. In opened window write `/home/dev` and click the OK button.
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8. Now You can explore, develop and build your Raspberry Pi Pico project via Visual Studio Code!
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### Pico SDK aware Intellisense
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For an IntelliSense that will be aware of Raspberry Pi Pico SDK dependencies, we will use [Clangd](https://clangd.llvm.org). Clangd is a C/C++ language server provided by the LLVM project. To Setup Clang as Intellisense engine follow instruction below:
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1. To begin with, you need to install the server itself (Clangd is not installed by default in the SDK container image), to do this in the terminal call the command:
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```
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apk add clang-extra-tools
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```
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2. Next is needed to install the Visual Studio Code [Clangd extension](https://marketplace.visualstudio.com/items?itemName=llvm-vs-code-extensions.vscode-clangd).
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1. To set-up The Clangd extension, in the project root directory, create folder .vcode with file settings.json. To settings.json past configuration from the snippet below:
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```json
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{
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"C_Cpp.intelliSenseEngine": "Disabled",
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"clangd.path": "/usr/bin/clangd",
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"clangd.checkUpdates": false,
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"clangd.restartAfterCrash": true,
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"clangd.detectExtensionConflicts": true,
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"clangd.arguments": ["-log=verbose",
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"-pretty",
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"--background-index",
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"--query-driver=/usr/bin/arm-none-eabi-gcc",
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"--compile-commands-dir=/home/dev/build"]
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}
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```
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4. For clangd to work, it needs a `compile_commands.json` file. This file contains the compilation and dependency information of each file in the project. To create it you need to add to the CMake command, `-DCMAKE_EXPORT_COMPILE_COMMANDS=1`. So You need to build your project with the command:
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```
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mkdir build
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cd build
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cmake -DCMAKE_EXPORT_COMPILE_COMMANDS=1 ..
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make
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```
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5. Now IntelliSense should work!. Now you should see a prompt when you start typing. If you hover your cursor over a function from the SDK you should see its documentation, You can go to the function definition by pressing F12.
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### Manual configuration of VSCode as Pico IDE (old)
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Refer [here](docs/vscode_manual_setup.md) for step-by-step instruction
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