Here is a recap of how I made it work for my project. In my case, the need to build binaries for Linux came up while working on my project edit-text, a collaborative test editor for the web written in Rust. I spent a long time rereading the same compiler logs before it actually dawned on me—I was compiling on my web server and not my laptop. If you have a githook that takes new source code pushed via git and loads it into a Docker container, deploying via git just sends up your source directory and points at a rustc compiler.
On each new deploy, your server has to rebuild from your Dockerfile from scratch, and unless you configure it to support caching this throws away the benefit of quickly iterating on your code. The approach I have the most experience with is to take the compilation environment and just run it locally on my machine.
With Docker, we have easy way to run Linux environments even on Mac and to pin it to the same development environment I have on my server. Since Docker on my machine will be running Linux in a hypervisor, local performance should beat what I can do on my server even with the overhead of not being the host OS. Did you know Rust has a first-party story for cross-compiling for Linux using Docker? I developed this set of command line arguments to get cross-compilation with caching working:.
The binaries this produced, amazingly, worked when I copied them to and ran them on my Linux server. Compiling locally was marginally faster. But there were drawbacks to this approach for cross-compilation:. There are a actually handful of components you need to make cross-compiling work:.
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Passing --target when running cargo build run changes the assembly your CPU outputs and bundled in object files supported by that OS. But we have to install the new toolchain adding that capability to Cargo. This is done with the command rustup target add. This installs the new compilation target based on its target triplet , which means:. So why choose musl?
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This might even mean we can skip steps 2 and 3 above. Finally, we need a program that links our compiled objects together. At this point we need to tell Rust about the linker. The official way to do this is to add a new file named. So when my code started throwing linking errors, I just ran the following in my shell:.
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Shared libraries are ones your program links to these at runtime once the program starts , rather than literally embedding them in their binary at compile time static libraries. The latter is helpful when we want to get into a function whose source code is unavailable. In such cases, Force Step Into jumps right to disassembly:. Apart from the debugger itself, we can switch the renderers it will use when showing Rust types in the Variables pane:.
These formatters build tree views for strings, structs, enums, and vectors, making it easier for you to look inside child elements. In fact, when earlier we started a debug session from the gutter menu, CLion created a temporary Cargo Command configuration, which we can see greyed out in the switcher:. Temporary configurations are fully functional, but you can only have a limited number of them at a time. So if you debug many targets and tests using gutter menus, only the last few corresponding configurations will be available.
You can always use Save… to make them permanent though.
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Use the following pattern for the Command field: [run] or [test] [build options] [--] [program arguments]. Notice the -- prefix followed by an extra space. It separates the input arguments from the build options that will be passed to Cargo. When we debug this configuration, the plugin will start by calling cargo build [build options] and then it will launch the binary under the debugger with [program arguments].
Now we can save this configuration. Because of this, Evaluate Expression currently works only in simple cases like arithmetic and logic operations with possible access to structure elements and pointers. The same limitations apply to the expressions you can set for conditional breakpoints. If we pick a pointer in the Variables pane and call Show in Memory View from the context menu, we will get into the raw memory of the running process.
This action opens a window with a byte memory region starting from the chosen address. While we are stepping through the code, the Memory View highlights the changes happening in the current range:. Another tiny but handy feature is the Hex View. It calculates hexadecimal values for integer variables and shows them alongside the original formatting or instead of it.
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The Hex View is under development at the moment. If you want to turn it on, follow these instructions from the web help.
One more feature that can help us debug is a configuration setting called Backtrace. Here is an example of how it looks when Backtrace is set to Full:. If you have any questions, feel free to ask them here in the comments or ping the IntelliJ Rust team in gitter. The following commands will install everything for you, entirely from the cli, so you can run them over ssh if need be.
Run the following command in a directory where you keep your projects. The cargo command will create a new directory called hello-rouille and populates it with the files you'll use to create your app. Edit the Cargo.
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You are going to add the following line in the [dependencies] section:. Run the following commands to run the web app, which will serve the web app on port , then verify that your app is being served by sending a request to the web app from another terminal. You will need Passenger installed, for instructions on how to install Passenger click here. Regardless of how your app accepts port arguments, the startup string must be able to convert from a cli argument to what works for your app.
In our example we converted the port argument to an envvar to show how one may need to change how the port is passed to your app.