Rizin
unix-like reverse engineering framework and cli tools
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title: Using Parsers
All of Tree-sitter's parsing functionality is exposed through C APIs. Applications written in higher-level languages can use Tree-sitter via binding libraries like node-tree-sitter or the tree-sitter rust crate, which have their own documentation.
This document will describe the general concepts of how to use Tree-sitter, which should be relevant regardless of what language you're using. It also goes into some C-specific details that are useful if you're using the C API directly or are building a new binding to a different language.
All of the API functions shown here are declared and documented in the tree_sitter/api.h
header file. You may also want to browse the online Rust API docs, which correspond to the C APIs closely.
To build the library on a POSIX system, just run make
in the Tree-sitter directory. This will create a static library called libtree-sitter.a
as well as dynamic libraries.
Alternatively, you can incorporate the library in a larger project's build system by adding one source file to the build. This source file needs two directories to be in the include path when compiled:
source file:
tree-sitter/lib/src/lib.c
include directories:
tree-sitter/lib/src
tree-sitter/lib/include
There are four main types of objects involved when using Tree-sitter: languages, parsers, syntax trees, and syntax nodes. In C, these are called TSLanguage
, TSParser
, TSTree
, and TSNode
.
TSLanguage
is an opaque object that defines how to parse a particular programming language. The code for each TSLanguage
is generated by Tree-sitter. Many languages are already available in separate git repositories within the the Tree-sitter GitHub organization. See the next page for how to create new languages.TSParser
is a stateful object that can be assigned a TSLanguage
and used to produce a TSTree
based on some source code.TSTree
represents the syntax tree of an entire source code file. It contains TSNode
instances that indicate the structure of the source code. It can also be edited and used to produce a new TSTree
in the event that the source code changes.TSNode
represents a single node in the syntax tree. It tracks its start and end positions in the source code, as well as its relation to other nodes like its parent, siblings and children.Here's an example of a simple C program that uses the Tree-sitter JSON parser.
This program uses the Tree-sitter C API, which is declared in the header file tree-sitter/api.h
, so we need to add the tree-sitter/lib/include
directory to the include path. We also need to link libtree-sitter.a
into the binary. We compile the source code of the JSON language directly into the binary as well.
In the example above, we parsed source code stored in a simple string using the ts_parser_parse_string
function:
You may want to parse source code that's stored in a custom data structure, like a piece table or a rope. In this case, you can use the more general ts_parser_parse
function:
The TSInput
structure lets you to provide your own function for reading a chunk of text at a given byte offset and row/column position. The function can return text encoded in either UTF8 or UTF16. This interface allows you to efficiently parse text that is stored in your own data structure.
Tree-sitter provides a DOM-style interface for inspecting syntax trees. A syntax node's type is a string that indicates which grammar rule the node represents.
Syntax nodes store their position in the source code both in terms of raw bytes and row/column coordinates:
Every tree has a root node:
Once you have a node, you can access the node's children:
You can also access its siblings and parent:
These methods may all return a null node to indicate, for example, that a node does not have a next sibling. You can check if a node is null:
Tree-sitter produces concrete syntax trees - trees that contain nodes for every individual token in the source code, including things like commas and parentheses. This is important for use-cases that deal with individual tokens, like syntax highlighting. But some types of code analysis are easier to perform using an abstract syntax tree - a tree in which the less important details have been removed. Tree-sitter's trees support these use cases by making a distinction between named and anonymous nodes.
Consider a grammar rule like this:
A syntax node representing an if_statement
in this language would have 5 children: the condition expression, the body statement, as well as the if
, (
, and )
tokens. The expression and the statement would be marked as named nodes, because they have been given explicit names in the grammar. But the if
, (
, and )
nodes would not be named nodes, because they are represented in the grammar as simple strings.
You can check whether any given node is named:
When traversing the tree, you can also choose to skip over anonymous nodes by using the _named_
variants of all of the methods described above:
If you use this group of methods, the syntax tree functions much like an abstract syntax tree.
To make syntax nodes easier to analyze, many grammars assign unique field names to particular child nodes. The next page explains how to do this on your own grammars. If a syntax node has fields, you can access its children using their field name:
Fields also have numeric ids that you can use, if you want to avoid repeated string comparisons. You can convert between strings and ids using the TSLanguage
:
The field ids can be used in place of the name:
In applications like text editors, you often need to re-parse a file after its source code has changed. Tree-sitter is designed to support this use case efficiently. There are two steps required. First, you must edit the syntax tree, which adjusts the ranges of its nodes so that they stay in sync with the code.
Then, you can call ts_parser_parse
again, passing in the old tree. This will create a new tree that internally shares structure with the old tree.
When you edit a syntax tree, the positions of its nodes will change. If you have stored any TSNode
instances outside of the TSTree
, you must update their positions separately, using the same TSInput
value, in order to update their cached positions.
This ts_node_edit
function is only needed in the case where you have retrieved TSNode
instances before editing the tree, and then after editing the tree, you want to continue to use those specific node instances. Often, you'll just want to re-fetch nodes from the edited tree, in which case ts_node_edit
is not needed.
Sometimes, different parts of a file may be written in different languages. For example, templating languages like EJS and ERB allow you to generate HTML by writing a mixture of HTML and another language like JavaScript or Ruby.
Tree-sitter handles these types of documents by allowing you to create a syntax tree based on the text in certain ranges of a file.
For example, consider this ERB document:
Conceptually, it can be represented by three syntax trees with overlapping ranges: an ERB syntax tree, a Ruby syntax tree, and an HTML syntax tree. You could generate these syntax trees with the following code:
This API allows for great flexibility in how languages can be composed. Tree-sitter is not responsible for mediating the interactions between languages. Instead, you are free to do that using arbitrary application-specific logic.
Tree-sitter supports multi-threaded use cases by making syntax trees very cheap to copy.
Internally, copying a syntax tree just entails incrementing an atomic reference count. Conceptually, it provides you a new tree which you can freely query, edit, reparse, or delete on a new thread while continuing to use the original tree on a different thread. Note that individual TSTree
instances are not thread safe; you must copy a tree if you want to use it on multiple threads simultaneously.
You can access every node in a syntax tree using the TSNode
APIs described above, but if you need to access a large number of nodes, the fastest way to do so is with a tree cursor. A cursor is a stateful object that allows you to walk a syntax tree with maximum efficiency.
You can initialize a cursor from any node:
You can move the cursor around the tree:
These methods return true
if the cursor successfully moved and false
if there was no node to move to.
You can always retrieve the cursor's current node, as well as the field name that is associated with the current node.
Many code analysis tasks involve searching for patterns in syntax trees. Tree-sitter provides a small declarative language for expressing these patterns and searching for matches. The language is similar to the format of Tree-sitter's unit test system.
A query consists of one or more patterns, where each pattern is an S-expression that matches a certain set of nodes in a syntax tree. The expression to match a given node consists of a pair of parentheses containing two things: the node's type, and optionally, a series of other S-expressions that match the node's children. For example, this pattern would match any binary_expression
node whose children are both number_literal
nodes:
Children can also be omitted. For example, this would match any binary_expression
where at least one of child is a string_literal
node:
In general, it's a good idea to make patterns more specific by specifying field names associated with child nodes. You do this by prefixing a child pattern with a field name followed by a colon. For example, this pattern would match an assignment_expression
node where the left
child is a member_expression
whose object
is a call_expression
.
You can also constrain a pattern so that it only matches nodes that lack a certain field. To do this, add a field name prefixed by a !
within the parent pattern. For example, this pattern would match a class declaration with no type parameters:
The parenthesized syntax for writing nodes only applies to named nodes. To match specific anonymous nodes, you write their name between double quotes. For example, this pattern would match any binary_expression
where the operator is !=
and the right side is null
:
When matching patterns, you may want to process specific nodes within the pattern. Captures allow you to associate names with specific nodes in a pattern, so that you can later refer to those nodes by those names. Capture names are written after the nodes that they refer to, and start with an @
character.
For example, this pattern would match any assignment of a function
to an identifier
, and it would associate the name the-function-name
with the identifier:
And this pattern would match all method definitions, associating the name the-method-name
with the method name, the-class-name
with the containing class name:
You can match a repeating sequence of sibling nodes using the postfix +
and *
repetition operators, which work analogously to the +
and *
operators in regular expressions. The +
operator matches one or more repetitions of a pattern, and the *
operator matches zero or more.
For example, this pattern would match a sequence of one or more comments:
This pattern would match a class declaration, capturing all of the decorators if any were present:
You can also mark a node as optional using the ?
operator. For example, this pattern would match all function calls, capturing a string argument if one was present:
You can also use parentheses for grouping a sequence of sibling nodes. For example, this pattern would match a comment followed by a function declaration:
Any of the quantification operators mentioned above (+
, *
, and ?
) can also be applied to groups. For example, this pattern would match a comma-separated series of numbers:
An alternation is written as a pair of square brackets ([]
) containing a list of alternative patterns. This is similar to character classes from regular expressions ([abc]
matches either a, b, or c).
For example, this pattern would match a call to either a variable or an object property. In the case of a variable, capture it as @function
, and in the case of a property, capture it as @method
:
This pattern would match a set of possible keyword tokens, capturing them as @keyword
:
A wildcard node is represented with an underscore (_
), it matches any node. This is similar to .
in regular expressions. There are two types, (_)
will match any named node, and _
will match any named or anonymous node.
For example, this pattern would match any node inside a call:
The anchor operator, .
, is used to constrain the ways in which child patterns are matched. It has different behaviors depending on where it's placed inside a query.
When .
is placed before the first child within a parent pattern, the child will only match when it is the first named node in the parent. For example, the below pattern matches a given array
node at most once, assigning the @the-element
capture to the first identifier
node in the parent array
:
Without this anchor, the pattern would match once for every identifier in the array, with @the-element
bound to each matched identifier.
Similarly, an anchor placed after a pattern's last child will cause that child pattern to only match nodes that are the last named child of their parent. The below pattern matches only nodes that are the last named child within a block
.
Finally, an anchor between two child patterns will cause the patterns to only match nodes that are immediate siblings. The pattern below, given a long dotted name like a.b.c.d
, will only match pairs of consecutive identifiers: a, b
, b, c
, and c, d
.
Without the anchor, non-consecutive pairs like a, c
and b, d
would also be matched.
The restrictions placed on a pattern by an anchor operator ignore anonymous nodes.
You can also specify arbitrary metadata and conditions associated with a pattern by adding predicate S-expressions anywhere within your pattern. Predicate S-expressions start with a predicate name beginning with a #
character. After that, they can contain an arbitrary number of @
-prefixed capture names or strings.
For example, this pattern would match identifier whose names is written in SCREAMING_SNAKE_CASE
:
And this pattern would match key-value pairs where the value
is an identifier with the same name as the key:
Note - Predicates are not handled directly by the Tree-sitter C library. They are just exposed in a structured form so that higher-level code can perform the filtering. However, higher-level bindings to Tree-sitter like the Rust crate or the WebAssembly binding implement a few common predicates like #eq?
and #match?
.
Create a query by specifying a string containing one or more patterns:
If there is an error in the query, then the error_offset
argument will be set to the byte offset of the error, and the error_type
argument will be set to a value that indicates the type of error:
The TSQuery
value is immutable and can be safely shared between threads. To execute the query, create a TSQueryCursor
, which carries the state needed for processing the queries. The query cursor should not be shared between threads, but can be reused for many query executions.
You can then execute the query on a given syntax node:
You can then iterate over the matches:
This function will return false
when there are no more matches. Otherwise, it will populate the match
with data about which pattern matched and which nodes were captured.
In languages with static typing, it can be helpful for syntax trees to provide specific type information about individual syntax nodes. Tree-sitter makes this information available via a generated file called node-types.json
. This node types file provides structured data about every possible syntax node in a grammar.
You can use this data to generate type declarations in statically-typed programming languages. For example, GitHub's Semantic uses these node types files to generate Haskell data types for every possible syntax node, which allows for code analysis algorithms to be structurally verified by the Haskell type system.
The node types file contains an array of objects, each of which describes a particular type of syntax node using the following entries:
Every object in this array has these two entries:
"type"
- A string that indicates which grammar rule the node represents. This corresponds to the ts_node_type
function described above."named"
- A boolean that indicates whether this kind of node corresponds to a rule name in the grammar or just a string literal. See above for more info.Examples:
Together, these two fields constitute a unique identifier for a node type; no two top-level objects in the node-types.json
should have the same values for both "type"
and "named"
.
Many syntax nodes can have children. The node type object describes the possible children that a node can have using the following entries:
"fields"
- An object that describes the possible fields that the node can have. The keys of this object are field names, and the values are child type objects, described below."children"
- Another child type object that describes all of the node's possible named children without fields.A child type object describes a set of child nodes using the following entries:
"required"
- A boolean indicating whether there is always at least one node in this set."multiple"
- A boolean indicating whether there can be multiple nodes in this set."types"
- An array of objects that represent the possible types of nodes in this set. Each object has two keys: "type"
and "named"
, whose meanings are described above.Example with fields:
Example with children:
In Tree-sitter grammars, there are usually certain rules that represent abstract categories of syntax nodes (e.g. "expression", "type", "declaration"). In the grammar.js
file, these are often written as hidden rules whose definition is a simple choice
where each member is just a single symbol.
Normally, hidden rules are not mentioned in the node types file, since they don't appear in the syntax tree. But if you add a hidden rule to the grammar's supertypes
list, then it will show up in the node types file, with the following special entry:
"subtypes"
- An array of objects that specify the types of nodes that this 'supertype' node can wrap.Example:
Supertype nodes will also appear elsewhere in the node types file, as children of other node types, in a way that corresponds with how the supertype rule was used in the grammar. This can make the node types much shorter and easier to read, because a single supertype will take the place of multiple subtypes.
Example: