Compute the callgraph of a crate.
The output of cargo-callgraph
is currently target/doc/dependencies.dot
(it’s
hardcoded).
Assuming you are on linux, you can use dot -Txlib target/doc/dependencies.dot
to generate an image from the graphviz text file. dot
is part of graphviz.
You should be able to install it using your package manager (apt, pacman, brew,
…).
You can also use dot -Tpng target/doc/dependencies.dot > some_file.png
or dot -Tpng:cairo target/doc/dependencies.dot > some_file.svg
if you prefer. Note
that dot -Tsvg
has a bug the miscompute the size of the fonts, so you need to
use -Tsvg:cairo
instead. You can the use image viewer like eog
or even
firefox
ot open the svg file.
The -Txlib
backend of graphviz, while very convenient on Linux (you don’t need
to have a intermediate png file) doesn’t work on mac. In that case you must use
the -Tpng
option instead. On linux you can open a png file with
xdg-open my-graph.png
and on mac you can do the same with open my-graph.png
.
Instead of using dot
, you can also use fdp
(it's provided alongside dot
).
Functions will be more spread on the screen.
cargo run -- test/test1/src/main.rs && dot target/doc/dependencies.dot -Txlib
On mac, use instead
cargo run -- test/test1/src/main.rs && dot target/doc/dependencies.dot -Tpng > graph.png && open graph.png
First you need to build (either in debug or release mode cargo-callgraph
.
cargo build
Then you can move in the test repository and generate the callgraph. To do so
you need to adjust RUSTDOC
to point to the binary you just compiled.
cd test/test1
env RUSTDOC=../../target/debug/cargo-callgraph cargo doc && dot target/doc/dependencies.dot -Txlib
on mac, use instead
cd test/test1
env RUSTDOC=../../target/debug/cargo-callgraph cargo doc && dot target/doc/dependencies.dot -Tpng > graph.png && open graph.png
Currently, I highly advice against testing cargo-callgraph
on any crate that
has more than 500 SLOC since the output will be very hard to visualize, and
dot
is extremely slow with bigger graph.
Like for the test project, you will first need to compile the current crate with
cargo build
. Then you will need to use the same nighly version that this crate
use to generate the callgraph. Fortunately, it’s easy to know which version
works, since it’s in the rust-toolchain
file (it’s the channel
in followed
by your target triple).
[toolchain]
channel = "nightly-2020-12-10"
components = ["rustc-dev", "llvm-tools-preview"]
cd /your/other/crate
RUSTDOC=/path/to/cargo-callgraph/target/debug/cargo-callgraph cargo doc && dot -Txlib target/dot/dependencies.dot
env RUSTDOC=/Users/robinm/perso/cargo-callgraph/target/debug/cargo-callgraph cargo doc && dot /Users/robinm/perso/cargo-callgraph/target/dot/dependencies.dot -Tpng > x.png && open x.png
I recommend using the --no-deps
option, in order to limit a bit the size of
the output. dot
(or fdp
for that matter) is very slow with huge graphs.
Since this is a fork of rustc, this project is distributed using the same licenses.
Rust is primarily distributed under the terms of both the MIT license and the Apache License (Version 2.0), with portions covered by various BSD-like licenses.
See LICENSE-APACHE, LICENSE-MIT, and COPYRIGHT for details.
When I started working on this project I had a 3 week break between two jobs, and I used my free time to work on a static analyser that would display information about the callgraph of a Rust project. In a perfect world I would love to have a tool that can give a bird-eye view of your source code. This would be especially useful when you start working on a huge codebase and you want to understand both the general architecture or specific details that interact with various part of the codebase. This project was my attempt to create such tool. It was unfortunately a much bigger task that what I expected, and I never took the time to finish it.
My idea was to compute (statically) the call graph of the whole project, then display that callgraph. I chose to analyse Rust code, because it’s grammar make it much more friendly for writing tools than C++ (two language that I’m very familiar with and that I use regularly). To extract the information from the source-code, I forked the Rust compiler, and to display the result, my tool was generating a .dot file that can be converted to a png or svg using the command dot (from the graphviz project).
Extracting the call-graph is very easy, as long as you don’t have function
pointers (both raw pointers or any kind of v-table, like when using &dyn Trait
), but as soon as you have those it become much more involved
because they add indirections. When I started to work on my project, I thought
that the hard part was going to correctly extract the information I need, and
it’s where I spend the most time. I choose to fork the Rust compiler as a
baseline, re-using most of the infrastructure used by rustdoc. I think I should
have based my work on rust-analyser instead, because maintaining a fork of
rustc is complicated since a lot of internal data structures changes quite
often. In retrospective, I think that rust-analyser would have been a base
easier to maintain than rustc. Because of this my project works only with some
random nightly version of rustc from 2021 but fortunately I pinned it, so
I can still compile it!
The second part of that project was to display the call graph. At first I thought that generating a simple dot file (and using graphviz as I said earlier to generate the svg/png) was enough. My goal was to have a proof of concept, not a production-grade tool at the first try! I was wrong of thinking that graphviz would be enough! The amount of information I was generating in that text file was so huge that it took forever to generate the images even for very small (500 LoC) project being analyzed. I also realized that adding interactivity would have been a huge plus. For example dynamically showing/hiding some part of the call graph. Unfortunately I ran out of time when I realized that. I gave myself 3 weeks to have a proof of concept, but I was far from it. After that I had a new job, so much less time and motivation. It’s the main reason why I never finished it.
To sum-up it was a very interesting project. I learned a lot, both how a compiler was working, how the rustc project was organized (the people I interacted with were very lovely), and how about leading a project in general. Most of what I’ve done was extremely exploratory, and I can feel it in the quality of the code I wrote. You can still find most of what I’ve done in this file.