366 lines
18 KiB
Markdown
366 lines
18 KiB
Markdown
# Guide to rust-analyzer
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## About the guide
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This guide describes the current start of the rust-analyzer as of 2019-01-20
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(commit hash guide-2019-01). Its purpose is to
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document various problems and architectural solutions related to the problem of
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building IDE-first compiler.
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## The big picture
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On the highest possible level, rust analyzer is a stateful component. Client may
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apply changes to the analyzer (new contents of `foo.rs` file is "fn main() {}")
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and it may ask semantic questions about the current state (what is the
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definition of the identifier with offset 92 in file `bar.rs`?). Two important
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properties hold:
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* Analyzer does not do any IO. It starts in an empty state and all input data is
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provided via `apply_change` API.
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* Only queries about the current state are supported. One can, of course,
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simulate undo and redo by keeping log of changes and inverse-changes.
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## IDE API
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To see this big picture, let's take a look at the [`AnalysisHost`] and
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[`Analysis`] pair of types. `AnalysisHost` has three methods:
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* `default` for creating an empty analysis
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* `apply_change(&mut self)` to make changes (this is how you get from an empty
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state to something interesting)
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* `analysis(&self)` to get an instance of `Analysis`
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`Analysis` has a ton of methods for IDEs, like `goto_definition`, or
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`completions`. Both inputs and outputs of `Analysis`' methods are formulated in
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terms of files and offsets, and **not** in terms of Rust concepts like structs,
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traits, etc. The "typed" API with Rust specific types is slightly lower in the
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stack, we'll talk about it later.
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[`AnalysisHost`]: https://github.com/rust-analyzer/rust-analyzer/blob/guide-2019-01/crates/ra_ide_api/src/lib.rs#L265-L284
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[`Analysis`]: https://github.com/rust-analyzer/rust-analyzer/blob/guide-2019-01/crates/ra_ide_api/src/lib.rs#L291-L478
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The reason for `Analysis` and `AnalysisHost` separation is that we want apply
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changes "uniquely", but we might want to fork an `Analysis` and send it to
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another thread for background processing. That is, there is only a single
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`AnalysisHost`, but there may be several (equivalent) `Analysis`.
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Note that all of the `Analysis` API return `Cancelable<T>`. This is required to
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be responsive in IDE setting. Sometimes a long-running query is being computed
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and the user types something in the editor and asks for completion. In this
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case, we cancel the long-running computation (so it returns `Err(Canceled)`),
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apply the change and execute request for completion. We never use stale data to
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answer requests. Under the cover, `AnalysisHost` "remembers" all outstanding
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`Analysis` instances. `AnalysisHost::apply_change` method cancels all
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`Analysis`es, blocks until of them are `Dropped` and then applies change
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in-place. This is the familiar to rustaceans read-write lock interior
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mutability.
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Next, lets talk about what are inputs to the Analysis, precisely.
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## Inputs
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Rust Analyzer never does any IO itself, all inputs get passed explicitly via
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`AnalysisHost::apply_change` method, which accepts a single argument:
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`AnalysisChange`. [`AnalysisChange`] is a builder for a single change
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"transaction", so it suffices to study its methods to understand all of the
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input data.
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[`AnalysisChange`]: https://github.com/rust-analyzer/rust-analyzer/blob/guide-2019-01/crates/ra_ide_api/src/lib.rs#L119-L167
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The `(add|change|remove)_file` methods control the set of the input files, where
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each file has an integer id (`FileId`, picked by the client), text (`String`)
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and a filesystem path. Paths are tricky, they'll be explained in source roots
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section, together with `add_root` method. `add_library` method allows to add a
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group of files which are assumed to rarely change. It's mostly an optimization
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and does not change fundamental picture.
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`set_crate_graph` method allows to control how the input files are partitioned
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into compilation unites -- crates. It also controls (in theory, not implemented
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yet) `cfg` flags. `CrateGraph` is a directed acyclic graph of crates. Each crate
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has a root `FileId`, a set of active `cfg` flags and a set of dependencies. Each
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dependency is a pair of a crate and a name. It is possible to have two crates
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with the same root `FileId` but different `cfg`-flags/dependencies. This model
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is lower than Cargo's model of packages: each Cargo package consists of several
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targets, each of which is a separate crate (or several crates, if you try
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different feature combinations).
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Procedural macros should become inputs as well, but currently they are not
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supported. Procedural macro will be a black box `Box<dyn Fn(TokenStream) -> TokenStream>`
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function, and will be inserted into the crate graph just like dependencies.
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Soon we'll talk how we build an LSP server on top of `Analysis`, but first,
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let's deal with that paths issue.
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## Source roots (aka filesystems are horrible)
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This is a non-essential section, feel free to skip.
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The previous section said that the file system path is an attribute of a file,
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but this is not a whole truth. Making it an absolute `PathBuf` will be bad for
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several reasons. First, file-systems are full of (platform-dependent) edge cases:
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* it's hard (requires a syscall) to decide if two paths are equivalent
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* some file-systems are case-sensitive
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* paths are not necessary UTF-8
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* symlinks can form cycles
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Second, this might hurt reproducibility and hermeticity of builds. In theory,
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moving a project from `/foo/bar/my-project` to `/spam/eggs/my-project` should
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not change a bit in the output. However, if absolute path is a part of the
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input, it is at least in theory observable, and *could* affect the output.
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Yet another problem is that we really-really want to avoid doing IO, but with
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Rust the set of "input" files is not necessary known up-front. In theory, you
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can have `#[path="/dev/random"] mod foo;`.
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To solve (or explicitly refuse to solve) these problems rust analyzer uses the
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concept of source root. Roughly speaking, source roots is a contents of a
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directory on a file systems, like `/home/matklad/projects/rustraytracer/**.rs`.
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More precisely, all files (`FileId`s) are partitioned into disjoint
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`SourceRoot`s. Each file has a relative utf-8 path within the `SourceRoot`.
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`SourceRoot` has an identity (integer id). Crucially, the root path of the
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source root itself is unknown to the analyzer: client is supposed to maintain a
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mapping between SourceRoot ids (which are assigned by the client) and actual
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`PathBuf`s. `SourceRoot`s give a sane tree model of the file system to the
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analyzer.
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Note that `mod`, `#[path]` and `include!()` can only reference files from the
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same source root. It is of course is possible to explicitly add extra files to
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the source root, even `/dev/random`.
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## Language Server Protocol
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Now let's see how `Analysis` API is exposed via JSON RPC based LSP protocol. The
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hard part here is managing changes (which can come either from the file system
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or from the editor) and concurrency (we want to spawn background jobs for things
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like syntax highlighting). We use the event loop pattern to manage the zoo, and
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the loop is the [`main_loop_inner`] function. The [`main_loop`] does a one-time
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initialization and tearing down of the resources.
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[`main_loop`]: https://github.com/rust-analyzer/rust-analyzer/blob/guide-2019-01/crates/ra_lsp_server/src/main_loop.rs#L51-L110
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[`main_loop_inner`]: https://github.com/rust-analyzer/rust-analyzer/blob/guide-2019-01/crates/ra_lsp_server/src/main_loop.rs#L156-L258
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Let's walk through a typical analyzer session!
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First, we need to figure out what to analyze. To do this, we run `cargo
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metadata` to learn about Cargo packages for current workspace and dependencies,
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and we run `rustc --print sysroot` and scan sysroot to learn about crates like
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`std`. Currently we load this configuration once at the start of the server, but
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it should be possible to dynamically reconfigure it later without restart.
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[main_loop.rs#L62-L70](https://github.com/rust-analyzer/rust-analyzer/blob/guide-2019-01/crates/ra_lsp_server/src/main_loop.rs#L62-L70)
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The [`ProjectModel`] we get after this step is very Cargo and sysroot specific,
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it needs to be lowered to get the input in the form of `AnalysisChange`. This
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happens in [`ServerWorldState::new`] method. Specifically
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* Create a `SourceRoot` for each Cargo package and sysroot.
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* Schedule a file system scan of the roots.
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* Create an analyzer's `Crate` for each Cargo **target** and sysroot crate.
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* Setup dependencies between the crates.
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[`ProjectModel`]: https://github.com/rust-analyzer/rust-analyzer/blob/guide-2019-01/crates/ra_lsp_server/src/project_model.rs#L16-L20
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[`ServerWorldState::new`]: https://github.com/rust-analyzer/rust-analyzer/blob/guide-2019-01/crates/ra_lsp_server/src/server_world.rs#L38-L160
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The results of the scan (which may take a while) will be processed in the body
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of the main loop, just like any other change. Here's where we handle
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* [File system changes](https://github.com/rust-analyzer/rust-analyzer/blob/guide-2019-01/crates/ra_lsp_server/src/main_loop.rs#L194)
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* [Changes from the editor](https://github.com/rust-analyzer/rust-analyzer/blob/guide-2019-01/crates/ra_lsp_server/src/main_loop.rs#L377)
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After a single loop's turn, we group them into one `AnalysisChange` and
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[apply] it. This always happens on the main thread and blocks the loop.
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[apply]: https://github.com/rust-analyzer/rust-analyzer/blob/guide-2019-01/crates/ra_lsp_server/src/server_world.rs#L216
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To handle requests, like ["goto definition"], we create an instance of the
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`Analysis` and [`schedule`] the task (which consumes `Analysis`) onto
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threadpool. [The task] calls the corresponding `Analysis` method, while
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massaging the types into the LSP representation. Keep in mind that if we are
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executing "goto definition" on the threadpool and a new change comes in, the
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task will be canceled as soon as the main loop calls `apply_change` on the
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`AnalysisHost`.
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["goto definition"]: https://github.com/rust-analyzer/rust-analyzer/blob/guide-2019-01/crates/ra_lsp_server/src/server_world.rs#L216
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[`schedule`]: https://github.com/rust-analyzer/rust-analyzer/blob/guide-2019-01/crates/ra_lsp_server/src/main_loop.rs#L426-L455
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[The task]: https://github.com/rust-analyzer/rust-analyzer/blob/guide-2019-01/crates/ra_lsp_server/src/main_loop/handlers.rs#L205-L223
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This concludes the overview of the analyzer's programing *interface*. Next, lets
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dig into the implementation!
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## Salsa
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The most straightforward way to implement "apply change, get analysis, repeat"
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API would be to maintain the input state and to compute all possible analysis
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information from scratch after every change. This works, but scales poorly with
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the size of the project. To make this fast, we need to take advantage of the
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fact that most of the changes are small, and that analysis results are unlikely
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to change significantly between invocations.
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To do this we use [salsa]: a framework for incremental on-demand computation.
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You can skip the rest of the section if you are familiar with rustc red-green
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algorithm.
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[salsa]: https://github.com/salsa-rs/salsa
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It's better to refer to salsa's docs to learn about it. Here's a small excerpt:
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The key idea of salsa is that you define your program as a set of queries. Every
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query is used like function K -> V that maps from some key of type K to a value
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of type V. Queries come in two basic varieties:
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* **Inputs**: the base inputs to your system. You can change these whenever you
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like.
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* **Functions**: pure functions (no side effects) that transform your inputs
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into other values. The results of queries is memoized to avoid recomputing
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them a lot. When you make changes to the inputs, we'll figure out (fairly
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intelligently) when we can re-use these memoized values and when we have to
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recompute them.
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For further discussion, its important to understand one bit of "fairly
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intelligently". Suppose we have to functions, `f1` and `f2`, and one input, `i`.
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We call `f1(X)` which in turn calls `f2(Y)` which inspects `i(Z)`. `i(Z)`
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returns some value `V1`, `f2` uses that and returns `R1`, `f1` uses that and
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returns `O`. Now, let's change `i` at `Z` to `V2` from `V1` and try to compute
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`f1(X)` again. Because `f1(X)` (transitively) depends on `i(Z)`, we can't just
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reuse its value as is. However, if `f2(Y)` is *still* equal to `R1` (despite the
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`i`'s change), we, in fact, *can* reuse `O` as result of `f1(X)`. And that's how
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salsa works: it recomputes results in *reverse* order, starting from inputs and
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progressing towards outputs, stopping as soon as it sees an intermediate value
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that hasn't changed.
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## Salsa Input Queries
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All analyzer information is stored in a salsa database. `Analysis` and
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`AnalysisHost` types are newtype wrappers for [`RootDatabase`] -- a salsa
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database.
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[`RootDatabase`]: https://github.com/rust-analyzer/rust-analyzer/blob/guide-2019-01/crates/ra_ide_api/src/db.rs#L88-L134
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Salsa input queries are defined in [`FilesDatabase`] (which is a part of
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`RootDatabase`). They closely mirror the familiar `AnalysisChange` structure:
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indeed, what `apply_change` does is it sets the values of input queries.
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[`FilesDatabase`]: https://github.com/rust-analyzer/rust-analyzer/blob/guide-2019-01/crates/ra_db/src/input.rs#L150-L174
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## From text to semantic model
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The bulk of the rust-analyzer is transforming input text into semantic model of
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Rust code: a web of entities like modules, structs, functions and traits.
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An important fact to realize is that (unlike most other languages like C# or
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Java) there isn't a one-to-one mapping between source code and semantic model. A
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single function definition in the source code might result in several semantic
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functions: for example, the same source file might be included as a module into
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several crate, or a single "crate" might be present in the compilation DAG
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several times, with different sets of `cfg`s enabled.
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The semantic interface is declared in [`code_model_api`] module. Each entity is
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identified by integer id and has a bunch of methods which take a salsa database
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as an argument and returns other entities (which are ids). Internally, this
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methods invoke various queries on the database to build the model on demand.
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Here's [the list of queries].
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[`code_model_api`]: https://github.com/rust-analyzer/rust-analyzer/blob/guide-2019-01/crates/ra_hir/src/code_model_api.rs
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[the list of queries]: https://github.com/rust-analyzer/rust-analyzer/blob/7e84440e25e19529e4ff8a66e521d1b06349c6ec/crates/ra_hir/src/db.rs#L20-L106
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The first step of building the model is parsing the source code.
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## Syntax trees
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An important property of the Rust language is that each file can be parsed in
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isolation. Unlike, say, `C++`, an `include` can't change the meaning of the
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syntax. For this reason, Rust analyzer can build a syntax tree for each "source
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file", which could then be reused by several semantic models if this file
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happens to be a part of several crates.
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Rust analyzer uses a similar representation of syntax trees to that of `Roslyn`
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and Swift's new [libsyntax]. Swift's docs give an excellent overview of the
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approach, so I skip this part here and instead outline the main characteristics
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of the syntax trees:
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* Syntax trees are fully lossless. Converting **any** text to a syntax tree and
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back is a total identity function. All whitespace and comments are explicitly
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represented in the tree.
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* Syntax nodes have generic `(next|previous)_sibling`, `parent`,
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`(first|last)_child` functions. You can get from any one node to any other
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node in the file using only these functions.
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* Syntax nodes know their range (start offset and length) in the file.
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* Syntax nodes share the ownership of their syntax tree: if you keep a reference
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to a single function, the whole enclosing file is alive.
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* Syntax trees are immutable and the cost of replacing the subtree is
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proportional to the depth of the subtree. Read Swift's docs to learn how
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immutable + parent pointers + cheap modification is possible.
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* Syntax trees are build on best-effort basis. All accessor methods return
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`Option`s. The tree for `fn foo` will contain a function declaration with
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`None` for parameter list and body.
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* Syntax trees do not know the file they are build from, they only know about
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the text.
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The implementation is based on the generic [rowan] crate on top of which a
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[rust-specific] AST is generated.
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[libsyntax]: https://github.com/apple/swift/tree/5e2c815edfd758f9b1309ce07bfc01c4bc20ec23/lib/Syntax
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[rowan]: https://github.com/rust-analyzer/rowan/tree/100a36dc820eb393b74abe0d20ddf99077b61f88
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[rust-specific]: https://github.com/rust-analyzer/rust-analyzer/blob/guide-2019-01/crates/ra_syntax/src/ast/generated.rs
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The next step in constructing the semantic model is ...
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## Building a Module Tree
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The algorithm for building a tree of modules is to start with a crate root
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(remember, each `Crate` from a `CrateGraph` has a `FileId`), collect all mod
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declarations and recursively process child modules. This is handled by the
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[`module_tree_query`], with a two slight variations.
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[`module_tree_query`]: https://github.com/rust-analyzer/rust-analyzer/blob/guide-2019-01/crates/ra_hir/src/module_tree.rs#L116-L123
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First, rust analyzer builds a module tree for all crates in a source root
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simultaneously. The main reason for this is historical (`module_tree` predates
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`CrateGraph`), but this approach also allows to account for files which are not
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part of any crate. That is, if you create a file but do not include it as a
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submodule anywhere, you still get semantic completion, and you get a warning
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about free-floating module (the actual warning is not implemented yet).
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The second difference is that `module_tree_query` does not *directly* depend on
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the "parse" query (which is confusingly called `source_file`). Why would calling
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the parse directly be bad? Suppose the user changes the file slightly, by adding
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an insignificant whitespace. Adding whitespace changes the parse tree (because
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it includes whitespace), and that means recomputing the whole module tree.
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We deal with this problem by introducing an intermediate [`submodules_query`].
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This query processes the syntax tree an extract a set of declared submodule
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names. Now, changing the whitespace results in `submodules_query` being
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re-executed for a *single* module, but because the result of this query stays
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the same, we don't have to re-execute [`module_tree_query`]. In fact, we only
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need to re-execute it when we add/remove new files or when we change mod
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declarations.
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[`submodules_query`]: https://github.com/rust-analyzer/rust-analyzer/blob/guide-2019-01/crates/ra_hir/src/module_tree.rs#L41)
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We store the resulting modules in a `Vec`-based indexed arena. The indices in
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the arena becomes module identifiers.
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## Location Interner pattern
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## Macros and recursive locations
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## Name resolution
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## Source Map pattern
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## Tying it all together: completion
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